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  • Published: 16 February 2024

PLK4 as a potential target to enhance radiosensitivity in triple-negative breast cancer

  • Sierra Pellizzari 1   na1 ,
  • Vasudeva Bhat 1 , 2   na1 ,
  • Harjot Athwal 1 ,
  • David W. Cescon 3 , 4 ,
  • Alison L. Allan 1 , 2 , 5 &
  • Armen Parsyan 1 , 2 , 5 , 6  

Radiation Oncology volume  19 , Article number:  24 ( 2024 ) Cite this article

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Radioresistance is one of the barriers to developing more effective therapies against the most aggressive, triple-negative, breast cancer (TNBC) subtype. In our previous studies, we showed that inhibition of Polo-like Kinase 4 (PLK4) by a novel drug, CFI-400945 significantly enhances the anticancer effects of radiotherapy (RT) compared to single treatment alone. Here we further investigate the role of PLK4 in enhancing radiation effects in TNBC and explore mechanisms of PLK4 inhibition and radiation combinatorial antiproliferative effects. To assess cellular proliferation in response to treatments, we used colony formation assays in TNBC cell lines and patient-derived organoids (PDOs). Downregulation of PLK4 expression was achieved using siRNA silencing in TNBC cell lines. Immunofluorescence against centrin was used to assess the alteration of centriole amplification in response to treatments. We observed that inhibition of PLK4 by CFI-400945 or Centrinone B or its downregulation by siRNA, when combined with RT, resulted in a significant increase in antiproliferative effect in TNBC cells lines and PDOs compared to untreated or single-treated cells. Anticancer synergy was observed using a response matrix in PDOs treated with CFI-400945 and RT. We show that the overamplification of centrioles might be involved in the combined antiproliferative action of RT and PLK4 inhibition. Our data suggest that PLK4 is a promising target for enhancing the anticancer effects of RT in TNBC that, at least in part, is modulated by the overamplification of centrioles. These results support further mechanistic and translational studies of anti-PLK4 agents and RT as an anticancer combination treatment strategy.

Introduction

Effective treatment strategies for triple-negative breast cancer (TNBC) are needed, given poor oncological outcomes in this aggressive disease subtype. To improve patient outcomes in TNBC, new therapeutics and multimodality treatments are being investigated. Polo-like Kinase 4 (PLK4), a regulator of centriole duplication [ 1 , 2 ], was found to be a promising target for drug development in breast cancer [ 3 ]. Several PLK4 inhibitors were developed, including an orally available drug, CFI-400945 [ 3 ] and a highly specific Centrinone B [ 4 ]. CFI-400945 was well-tolerated in a Phase I clinical trial [ 5 ] and has entered Phase II studies in metastatic breast cancer (NCT03624543). Inhibition of PLK4 dysregulates centriole duplication and induces genomic instability and aneuploidy in cancer cells, causing antiproliferative effects and cell death [ 1 , 3 , 6 ]. Genomic instability is also a sequela of effects of radiotherapy (RT), a commonly used modality for breast cancer treatment [ 6 , 7 ]. Ionizing radiation is also known to induce centriole-related aberrations and centrosome overduplication [ 8 , 9 ]. Thus, the combination of PLK4 inhibition with RT might synergize in dysregulation of centrioles leading to, compared to single-agent treatment, further genomic instability of cancer cells and enhanced antiproliferative effects. In our previous studies, we showed that CFI-400945 and RT indeed can act synergistically in vitro and in vivo to decrease TNBC proliferation [ 6 ]. Here, we further investigate if previously observed [ 6 ] anticancer synergy of CFI-400945 with RT are specific to PLK4 inhibition since this drug is known for its off-target effects (e.g. inhibition of Aurora Kinase B) [ 3 ]. We also investigate various approaches to PLK4 inhibition in various cell models and explore the mechanisms of synergistic antiproliferative effects of CFI-400945 in combination with RT in TNBC. Our data suggest that the combination effect of CFI-400945 with RT in TNBC is driven by inhibition of PLK4, which, together with RT leads to the further overamplification of centrioles compared to single agent treatments. This centriole dysregulation likely leads to further exacerbation of genomic instability and genotoxic stress, which in turn reflects in the observed synergistic effects of combination treatment. Our results support further mechanistic and translational studies of anti-PLK4 agents and RT as a novel multimodality combination treatment strategy in TNBC and potentially other cancers.

Materials and methods

Colony and organoid forming assays.

Human triple negative breast cancer cell lines, MDA-MB-468 (ExPASy Cellosaurus Research Resource
Identifier (RRID): CVCL_0419), MDA-MB-231 (RRID: CVCL_0062) and SUM159 (RRID: CVCL_5423), were used. MDA-MB-468 and MDA-MB-231 cell lines were obtained from Dr. Ann Chambers (London Regional Cancer Program; London, ON). SUM159 cell line was obtained from Asterand Inc. (Detroit, MI, USA). All the cell lines were authenticated via third party testing (IDEXX BioAnalytic, Columbia MO, USA) using short tandem repeat (STR) profiling (using 9 markers) in August 2021. All experiments were performed using mycoplasma-free cell lines. The BPDXO58 and PDO66 organoid lines were provided by the Princess Margaret Cancer Centre Living Biobank (Toronto, ON). Colony and organoid formation assays (CFA) were performed as previously described [ 10 , 11 ]. Radiation experiments were performed using a Cobalt-60 unit (London Regional Cancer Program, ON) 16–20 h after seeding, media was then replaced and supplemented with the drug (CFI-400945, SelleckChem, PA; Centrinone B, Tocris Bioscience, Bristol, UK) or vehicle control at various concentrations. In pre-treatment combination studies, cells were treated first with RT or the drug 16–20 h after plating, then 4 days later were treated with the drug or RT, respectively. For assessing combination effects in colony formation assays, we used the drug concentration and RT doses closer to IC50/ID50, specific to each cell line. This selection was based on the envisioned translational and biological relevance of these treatments, since IC50/ID50 would represent more clinically relevant concentrations/doses.

siRNA knockdown studies

Cells were transfected with either scrambled control or PLK4- targeting siRNA (GAAGAUAGCAAUUAUGUGU) (Dharmacon, CO) using Lipofectamine RNAiMAX transfection reagent following the manufacturer’s protocol (Invitrogen, MA) and replated in CFA format 16 h after transfection. In parallel, a subset of transfected cells was assessed for PLK4 knockdown 48 h after transfection using RT-qPCR after RNA isolation using the TRIzol reagent (Invitrogen). Total RNA (1 µg) was reverse transcribed using the Superscript IV VILO master mix (Invitrogen). PLK4 knockdown was quantified using PLK4 and GAPDH-specific primers (Supp. Table 1 ) Brilliant III SYBR green qPCR master mix (Agilent Technologies, Inc, CA) on the QuantStudio 3 Real-Time PCR System (Applied Biosystems, MA). The cycle threshold (Ct) values of PLK4 were normalized to GAPDH internal control to calculate ΔC t values. The difference in PLK4 expression between scrambled control and PLK4 knockdown samples were determined by calculating fold change with the 2 − ΔΔC t method as previously described [ 12 ].

Statistical analysis

All experiments were performed a minimum of three times, unless specified otherwise. Synergy was calculated using Bliss score using SynergyFinder software [ 13 ]. Statistical analysis was performed using GraphPad Prism Software V9.0.1 (Dotmatics, CA). Half-maximal inhibitory concentration (IC50, for drugs) and half-maximal inhibitory dose (ID50, for RT) were calculated using dose response curves and a nonlinear regression model (Supp. Figure  1 ). Statistical analysis of the data from CFA and immunohistochemistry experiments comparing control, single agent and combination treatment effects was performed using Two-Way ANOVA. Statistical significance was defined as p  ≤ 0.05.

figure 1

Anticancer effects of CFI-400945 and RT in TNBC cell lines and patient-derived organoids. Combination of CFI-400945 and RT demonstrates significant augmentation of anticancer effect by decreasing colony formation in (A) MDA-MB-468, (B) SUM159 and (C) MDA-MB-231 cells compared to control (*), RT (α) or CFI-400945 (β) only ( p  ≤ 0.05), upon simultaneous or sequential combination treatments. The combination effect was observed and was not significantly altered by the pre-treatment of cells with CFI-400945 or RT compared to simultaneous treatment. Synergy of the CFI-400945 and RT combination treatment was observed in (D) BPDXO58 and (E) PDO66 at various concentrations of the drug and RT doses using organoid formation assays. Bright-field microscopy images (4× magnification) were taken 14 days following treatment. The number of organoids were counted by 2 independent observers in at least 3 random fields per each well. The counts were normalized to respective controls in each group. Average number of organoids was normalized to that of control (no-RT, no-drug). Bliss synergy scores were calculated with SynergyFinder and are displayed in the heatmap, where intensity of red indicates higher degree of synergy. RT– Radiotherapy, SF– Surviving Fraction. Scale bar = 500 μm

CFI-400945 and RT demonstrate combinatorial anticancer effect

In MDA-MB-468, (Fig.  1 A) simultaneous combination treatment resulted in a 91.0 ± 5.6% decrease in colony formation compared to control ( p ≤0.05), which translates to an 8.3- and 5.5-fold decrease in colony formation compared to RT or CFI-400945 only treatments respectively. Similar combinatorial effects were observed in other studied cell lines (Fig.  1 B &C ). We evaluated the sequential scheduling of the RT and drug treatments and observed that different sequencing resulted in similar combinatorial effects and did not significantly alter the efficacy of the combination compared to simultaneous administration (Fig.  1 A and B). Hence, subsequent experiments were carried out using simultaneous RT and drug administration protocol. In patient-derived models, BPDXO58 (Fig.  1 D) and PDO66 (Fig.  1 E), we also observed synergy between CFI-400945 and RT at various dose combinations (Bliss synergy scores of 17.88 (BPDXO58) and 11.93 (PDO66)). In BPDXO58, 5 nM of CFI-400945 and 2.5 Gy of RT resulted in a 12.7-fold decrease in organoid formation compared to control treatment, while single agent CFI-400945 and RT at these doses resulted in only a 1.1-fold and 1.2-fold decrease, respectively (Fig.  1 D). Similar trends were observed in PDO66 (Fig.  1 E).

Alternative targeting of PLK4 exhibits combination effects with RT

We used PLK4 knockdown with siRNA to investigate if the observed combination effect of CFI-400945 and RT is mediated by PLK4 inhibition and if downregulation of PLK4 expression leads to similar combination effects with RT. In MDA-MB-468, MDA-MB-231 and SUM159 cells, siRNA targeting of PLK4 resulted in up to 75% reduction of its mRNA and 50–75% average reduction in protein levels (Supp Fig.  2 A-C). In MDA-MB-468, combination treatment with RT and PLK4 knockdown resulted in reduction of colony formation by 73.5 ± 7.0% compared to control ( p ≤0.05) (Fig.  2 A). Similarly, compared to control, PLK4 silencing together with RT treatment significantly ( p  < 0.05) reduced colony formation by 90.9±6.0% and 69.4±2.6% in MDA-MB-231 and SUM159 cells respectively (Fig.  2 B-C).

figure 2

Loss of function or inhibition of PLK4 enhances RT induced anticancer effects. Combination of the PLK4 knockdown and RT demonstrates increased anticancer effects, compared to single-agent treatments in (A) MDA-MB-468, (B) MDA-MB-231 and (C) SUM159 cells transfected with either scrambled control (scr) or PLK4-targeting siRNA (si PLK4 ) and treated with RT ( p  ≤ 0.05 compared to control (*), RT (α) or siPLK4 (β) only). Combination treatment of (D) MDA-MB-468, (E) MDA-MB-231 and (F) SUM159 cells with RT and PLK4 inhibitor Centrinone B results in decreased colony formation compared to control (*), RT (α) or Centrinone B (β) only ( n  = 3, p  ≤ 0.05). CB– Centrinone B, RT– Radiotherapy, SF– Surviving Fraction

Next, we investigated the role of PLK4 inhibition in enhancing RT’s antiproliferative effects by another, highly potent PLK4-specific inhibitor, Centrinone B [ 4 ]. In MDA-MB-468 cells, the combination of Centrinone B and RT resulted in a 56.6 ± 10.1% decrease in colony formation, whereas 15.2 ± 3.5% and 35.9 ± 1.9% decreases were observed for Centrinone B or RT alone, respectively ( p ≤0.05) (Fig.  2 D). Similar effects were observed in other cell lines, where, compared to control, Centrinone B and RT combination treatment significantly ( p  < 0.05) reduced colony formation by 94.2±1.2% in MDA-MB-231 and 69.3±5.8% in SUM159 cells (Fig.  2 E & F ).

Centriole overduplication may contribute to the combination anticancer effects of CFI-400945 and RT

Inhibition of PLK4 by CFI-400945 is known to induce centriole duplication at lower concentrations [ 3 ]. Using immunocytochemistry for Centrin, a centriole-associated protein, Mason et al. observed increased numbers of centrioles at spindle poles in MDA-MB-468 cells treated with CFI-400945 [ 3 ]. Using a similar experimental approach, we assessed that combination treatment resulted in further overamplification of centrioles (≥3) at spindle poles compared to control in TNBC cell lines (Fig.  3 A). In MDA-MB-468 cells, combination treatment resulted in 37.7 ± 4.9% increase in the proportion of cells with centriole overamplification compared to control ( p ≤0.05) (Fig.  3 B). Similar effects were observed in other cell lines (Fig.  3 C and D ).

figure 3

PLK4 inhibition enhances anticancer effects of RT via overamplification of centrioles. (A) Representative images depicting nuclear staining by DAPI (blue) and centriole staining by Centrin (green) in MDA-MB-468 cells. Immunocytochemistry for Centrin in (B) MDA-MB-468 ( n  = 4), (C) MDA-MB-231 ( n  = 3), and (D) SUM159 ( n  = 3) cells indicated a significant increase in centriole amplification in combination treatment compared to control (*), RT (α) or CFI-400945 (β) only ( p  ≤ 0.05)

Multimodality combination strategies with chemotherapeutics might improve RT response while providing systemic control in treatment-resistant TNBC [ 14 , 15 ]. Genomic instability is known to increase cancer cell radiosensitivity [ 16 ]. Exploring this vulnerability through combinations of RT and systemic agents is a promising strategy. PLK4 inhibition is an emerging new strategy for cancer, including breast cancer, and has been extensively studied [ 17 , 18 ]. Various PLK4 inhibitors have been described, such as YLT11 [ 19 ] and Centrinone B [ 20 ]. However, CFI-400945 is the compound that has been the most extensively studied and has entered clinical trials (NCT03624543) in patients with breast cancer [ 5 ]. Mason et al. (2014) [ 3 ] characterized CFI-400945, investigating it as a single agent, and provided the foundational concepts regarding this compound. Given its promise as a novel anti-breast cancer agent and orally available drug, our group investigated if the combination of this compound with RT would enhance anticancer effects through further exacerbation of genomic instability [ 6 ]. In that study, the first to our knowledge to examine the combination of PLK4 inhibitors with RT, the synergistic effect of CFI-400945 and RT was shown. However, limited models were initially used to test the efficacy of this combination. Moreover, due to potential off-target effects of CFI-400945, it remained to be confirmed that the combination effect was indeed acting directly through PLK4 inhibition. The mechanistic effects of the combination treatment remained unclear. The latter has important translational implications in terms of studying other PLK4 inhibitors with RT to enhance anticancer effects. The aforementioned issues have been addressed in the current study.

Our previous [ 6 ] and current data provide strong support that CFI-400945 combined with RT works synergistically to deliver substantially greater anticancer effects than single agent treatments. Synergistic benefits of this combination were confirmed in translationally-relevant PDO models, suggesting that it might be effective in tackling cancer heterogeneity and treatment resistance. In the current manuscript, we provide new information regarding the combination of PLK4 inhibition together with RT.

First, we investigated various sequencing schedules of CFI-400945 with RT and their antiproliferative effects. We did not observe substantial differences in combinatorial effects under various treatment sequencing schedules, likely due to the short periods of culture under various treatment conditions in vitro.

Secondly, we, for the first time, show that specific PLK4 inhibition, at least in part, is responsible for enhanced anticancer effects previously observed upon combination treatment with CFI-400945 and RT. Since CFI-400945 is known to exhibit off-target effects at higher concentrations [ 4 ], we explored if PLK4 inhibition is in fact responsible for the antiproliferative synergistic effects with RT using a highly specific PLK4 inhibitor and RNA interference approaches. Reduction of PLK4 expression by siRNA or its inhibition with a highly-selective Centrinone B [ 4 ] also enhanced anticancer effects when combined with RT. Although combinatorial effects observed with CFI-400945 were overall stronger compared to siRNA silencing or Centrinone B treatment it is difficult to draw direct comparisons due to experimental differences, such as transient action of siRNA and drug concentrations. Overall, our data suggests that PLK4 is a promising target for enhancing RT effects in TNBC. These findings have important implications for translational research since other PLK4 inhibition strategies are being developed and might soon enter clinical trials [ 21 ]. Thus, the knowledge that the PLK4-specific inhibition is a promising strategy for enhancing effects of RT can be further utilized to investigate and develop multimodality treatment approaches in breast and potentially other cancers.

Next, we explored mechanistic aspects of the anticancer effects of PLK4 inhibition with RT. It is worth noting, that while PLK4 is known to play an essential role in centriole and centrosome control, the detailed mechanisms of its action are largely unknown. PLK4 has a known role in cell cycle control by regulating the process of centriole duplication [ 22 ]. Hence, inhibition of PLK4 can cause centrosome-related errors, such as centrosome amplification which leads to improper mitotic progression, genomic instability and subsequent cancer cell death [ 3 ]. While centriole overduplication is a purported mechanism of the anti-cancer effect of CFI-400945 as a single agent [ 3 ], other mechanisms might also be at play during its monotherapy or combination treatment. RT has been shown to induce centrosome amplification in cancer cells via centriole splitting or overamplification [ 23 , 24 , 25 ]. However, RT is also known to utilize a multitude of other mechanisms through which it asserts its anticancer effects [ 15 ]. Taken together, we aimed to investigate if the combination effect of CFI-400945 inhibition with RT works through centriole overduplication. We, for the first time, show that the combination effect of the drug and RT is, at least in part, promoted by centriole overduplication. The latter is indicative of genomic instability and mitotic catastrophe, which may lead to cancer cell death [ 24 , 25 , 26 , 27 ].

Our data suggest a model whereby the combined action of PLK4 inhibition and RT leads to increased overamplification of centrioles, which in turn increases genomic instability, compromises the ability of cancer cells to cope with genotoxic stress and results in enhanced anticancer effects. Additional studies might further shed light on the mechanism of action of PLK4 inhibition and RT, serve to identify novel targets for radiosensitization and facilitate translation of this approach to a clinical setting to improve outcomes in patients with TNBC.

Overall, our study shows that PLK4 inhibition together with RT, compared to single agent treatments, further enhances anticancer effects in TNBC. This novel multimodality approach can be potentially utilized in downstaging the primary and axillary lymph node tumors in the neoadjuvant setting, commonly used in TNBC, to improve operability or to convert inoperable tumors to operable ones. This approach might also be proven useful in the metastatic setting (e.g. skin, liver, bones) where radiotherapy effects on the metastatic deposit can be further enhanced by concurrent administration of CFI-400945. Similarly, the combination can be explored in the postoperative, or adjuvant setting to potentially decrease the incidence of locoregional recurrence. The fact that CFI-400945 is orally available makes it an attractive candidate for the multimodal treatment with RT in these settings. Notably, and pending results of Phase II (NCT03624543) trials for CFI-400945 as a single agent, its administration with RT might provide benefits of not only improved loco-regional disease control but also systemic disease control. Due to adverse effects, such as neutropenia, observed upon CFI-400945 treatment in Phase I trials [ 5 ], lower doses of the drug could be explored in clinical studies together with RT. Potential benefits of these various management approaches can be further explored in clinical trials with RT and CFI-400945 or other novel PLK4 inhibitors in TNBC. Moreover, our previous [ 6 ] and current findings support the rationale for translational and clinical studies of this combination in other breast cancer subtypes and other cancer types.

Data availability

Supporting data can be found in the supplementary section of the manuscript.

Abbreviations

  • Triple-negative breast cancer

Polo-like kinase 4

  • Radiotherapy

Patient-derived organoids

Colony and organoid formation assay

Cycle threshold

Half-maximal inhibitory concentration

Half-maximal inhibitory dose

Standard deviation

Yamamoto S, Kitagawa D. Self-organization of Plk4 regulates symmetry breaking in centriole duplication. Nat Commun. 2019;10(1):1810.

Article   PubMed   PubMed Central   ADS   Google Scholar  

Bettencourt-Dias M, Glover DM. Centrosome biogenesis and function: centrosomics brings new understanding. Nat Rev Mol Cell Biol. 2007;8(6):451–63.

Article   CAS   PubMed   Google Scholar  

Mason JM, Lin DC, Wei X, Che Y, Yao Y, Kiarash R, et al. Functional characterization of CFI-400945, a Polo-like kinase 4 inhibitor, as a potential anticancer agent. Cancer Cell. 2014;26(2):163–76.

Suri A, Bailey AW, Tavares MT, Gunosewoyo H, Dyer CP, Grupenmacher AT et al. Evaluation of protein kinase inhibitors with PLK4 cross-over potential in a pre-clinical model of Cancer. Int J Mol Sci. 2019;20(9).

Veitch ZW, Cescon DW, Denny T, Yonemoto LM, Fletcher G, Brokx R, et al. Safety and tolerability of CFI-400945, a first-in-class, selective PLK4 inhibitor in advanced solid tumours: a phase 1 dose-escalation trial. Br J Cancer. 2019;121(4):318–24.

Article   CAS   PubMed   PubMed Central   Google Scholar  

Parsyan A, Cruickshank J, Hodgson K, Wakeham D, Pellizzari S, Bhat V, et al. Anticancer effects of radiation therapy combined with Polo-Like kinase 4 (PLK4) inhibitor CFI-400945 in triple negative breast cancer. Breast. 2021;58:6–9.

Article   PubMed   PubMed Central   Google Scholar  

Huang RX, Zhou PK. DNA damage response signaling pathways and targets for radiotherapy sensitization in cancer. Signal Transduct Target Ther. 2020;5(1):60.

Sato N, Mizumoto K, Nakamura M, Tanaka M. Radiation-induced centrosome overduplication and multiple mitotic spindles in human tumor cells. Exp Cell Res. 2000;255(2):321–6.

Douthwright S, Sluder G. Link between DNA damage and centriole disengagement/reduplication in untransformed human cells. J Cell Physiol. 2014;229(10):1427–36.

Brix N, Samaga D, Belka C, Zitzelsberger H, Lauber K. Analysis of clonogenic growth in vitro. Nat Protoc. 2021;16(11):4963–91.

Franken NA, Rodermond HM, Stap J, Haveman J, van Bree C. Clonogenic assay of cells in vitro. Nat Protoc. 2006;1(5):2315–9.

Livak KJ, Schmittgen TD. Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) method. Methods. 2001;25(4):402–8.

Ianevski A, Giri AK, Aittokallio T. SynergyFinder 2.0: visual analytics of multi-drug combination synergies. Nucleic Acids Res. 2020;48(W1):W488–W93.

Zhou ZR, Wang XY, Yu XL, Mei X, Chen XX, Hu QC, et al. Building radiation-resistant model in triple-negative breast cancer to screen radioresistance-related molecular markers. Ann Transl Med. 2020;8(4):108.

Bhat V, Pellizzari S, Allan AL, Wong E, Lock M, Brackstone M, et al. Radiotherapy and radiosensitization in breast cancer: molecular targets and clinical applications. Crit Rev Oncol Hematol. 2022;169:103566.

Article   PubMed   Google Scholar  

Bakhoum SF, Kabeche L, Wood MD, Laucius CD, Qu D, Laughney AM, et al. Numerical chromosomal instability mediates susceptibility to radiation treatment. Nat Commun. 2015;6:5990.

Article   CAS   PubMed   ADS   Google Scholar  

Zhang X, Wei C, Liang H, Han L. Polo-Like kinase 4’s critical role in Cancer Development and Strategies for Plk4-Targeted therapy. Front Oncol. 2021;11:587554.

Garvey DR, Chhabra G, Ndiaye MA, Ahmad N. Role of Polo-Like kinase 4 (PLK4) in epithelial cancers and recent progress in its small molecule targeting for Cancer Management. Mol Cancer Ther. 2021;20(4):632–40.

Lei Q, Xiong L, Xia Y, Feng Z, Gao T, Wei W, et al. YLT-11, a novel PLK4 inhibitor, inhibits human breast cancer growth via inducing maladjusted centriole duplication and mitotic defect. Cell Death Dis. 2018;9(11):1066.

Wong YL, Anzola JV, Davis RL, Yoon M, Motamedi A, Kroll A, et al. Cell biology. Reversible centriole depletion with an inhibitor of Polo-like kinase 4. Science. 2015;348(6239):1155–60.

Article   CAS   PubMed   PubMed Central   ADS   Google Scholar  

Repare Therapeutics Unveils Two Programs Expected to Enter Clinical Trials in 2024.: RP-1664, an oral PLK4 inhibitor, and RP-3467, an Oral Polθ Inhibitor 2023 [.

Moyer TC, Holland AJ. PLK4 promotes centriole duplication by phosphorylating STIL to link the procentriole cartwheel to the microtubule wall. Elife. 2019;8.

Fujimoto M, Bo T, Yamamoto K, Yasui H, Yamamori T, Inanami O. Radiation-induced abnormal centrosome amplification and mitotic catastrophe in human cervical tumor HeLa cells and murine mammary tumor EMT6 cells. J Clin Biochem Nutr. 2020;67(3):240–7.

Dodson H, Wheatley SP, Morrison CG. Involvement of centrosome amplification in radiation-induced mitotic catastrophe. Cell Cycle. 2007;6(3):364–70.

Denu RA, Shabbir M, Nihal M, Singh CK, Longley BJ, Burkard ME, et al. Centriole Overduplication is the predominant mechanism leading to centrosome amplification in Melanoma. Mol Cancer Res. 2018;16(3):517–27.

Maxwell CA, Fleisch MC, Costes SV, Erickson AC, Boissière A, Gupta R, et al. Targeted and nontargeted effects of ionizing radiation that impact genomic instability. Cancer Res. 2008;68(20):8304–11.

Cosenza MR, Cazzola A, Rossberg A, Schieber NL, Konotop G, Bausch E, et al. Asymmetric centriole numbers at spindle poles cause chromosome missegregation in Cancer. Cell Rep. 2017;20(8):1906–20.

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Acknowledgements

We would like to thank Jennifer Cruickshank (University of Toronto and the Princess Margaret Cancer Centre) for their input on the manuscript, as well as assistance and knowledge pertaining to the culture of PDO models.

A.P. lab research is supported by the Cancer Research Society (CRS) and Canadian Institutes of Health Research (CIHR)/Institute of Cancer Research (ICR), Operating Grants 2022 Competition, Targeted Funding Opportunity; Young Investigator Startup Grant, Department of Surgery, Western University and the London Regional Cancer Program Catalyst Grant for Translational Cancer Research, Western University (London, ON). A. P. is supported by the Clinician Scientist Award, Department of Surgery, Western University, and the Academic Medical Organization of Southwestern Ontario (AMOSO) Opportunities Fund (London, ON). A.L.A. breast cancer research is supported by the Canadian Institutes of Health Research and a London Regional Cancer Program Catalyst Grant. A.L.A., V.B., S.P. and H.A. are supported by the Breast Cancer Society of Canada. V.B is supported by a Western Postdoctoral Fellowship (Western University). S. P. was supported by Ontario Graduate Scholarship (OGS).

Author information

Sierra Pellizzari and Vasudeva Bhat contributed equally.

Authors and Affiliations

Department of Anatomy and Cell Biology, Western University, N6A 3K7, London, ON, Canada

Sierra Pellizzari, Vasudeva Bhat, Harjot Athwal, Alison L. Allan & Armen Parsyan

London Regional Cancer Program, London Health Sciences Centre and London Health Sciences, Centre Research Inc, N6A 5W9, London, ON, Canada

Vasudeva Bhat, Alison L. Allan & Armen Parsyan

Princess Margaret Cancer Centre, University Health Network, University of Toronto, M5G 2M9, Toronto, ON, Canada

David W. Cescon

Department of Medical Oncology and Hematology, University of Toronto, M5G 2C1, Toronto, ON, Canada

Department of Oncology, Western University, N6A 3K7, London, ON, Canada

Alison L. Allan & Armen Parsyan

Department of Surgery, St Joseph’s Health Care and London Health Sciences Centre, Western University, N6A 4V2, London, ON, Canada

Armen Parsyan

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Contributions

S.P., V.B. and H.A. conducted experiments, analyzed and interpreted the data. S.P., V.B. and H.A were involved in original draft preparation. A.L.A., D.W.C., A.P. were involved in reviewing and editing of the manuscript. A.P. was involved in study conceptualization, supervision and funding acquisition. All authors have read and agreed to the published version of the manuscript.

Corresponding author

Correspondence to Armen Parsyan .

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Ethics approval.

The study was conducted in accordance with the Declaration of Helsinki and approved by the Institutional Review Board (or Ethics Committee) of Western University (protocol codes 118685 (30/Mar/2021); 118019 (25/Jan/2021)).

Conflict of interest

D.W.C. reports advisory services to AstraZeneca, Exact Sciences, Eisai, Gilead, GlaxoSmithKline, Inivata, Merck, Novartis, Pfizer, and Roche; reports research funding (to institution) from AstraZeneca, Gilead, GlaxoSmithKline, Inivata, Merck, Pfizer, and Roche; is a member of a trial steering committee for AstraZeneca, Merck, and GlaxoSmithKline; and D.W.C. holds a patent (US62/675,228) for methods of treating cancers characterized by a high expression level of spindle and kinetochore associated complex subunit 3 ( SKA3 ) gene.

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Electronic supplementary material

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case study on triple negative breast cancer

13014_2024_2410_MOESM1_ESM.jpeg

Supplementary Material 1. Supplementary Fig.1. Dose response curves of single agent treatments in TNBC cell lines Colony formation assays were performed in TNBC cell lines by treating with a range of doses of (A) RT, (B) CFI-400945 or (C) Centrinone B to identify ID50 (RT) or IC50 (drug) values using non-linear regression analysis. The number of colonies counted was normalized to untreated control. SF– Surviving Fraction

case study on triple negative breast cancer

13014_2024_2410_MOESM2_ESM.jpeg

Supplementary Material 2. Supplementary Fig.2. PLK4 knockdown efficiency in TNBC cells MDA-MB-468 (A and B) , MDA-MB-231 (C and D) and SUM159 (E and F) cells were depleted of PLK4 using siRNA, and the knockdown efficiency was determined by RT-qPCR and Western blot analysis. Reduction of the PLK4 expression by the siRNA silencing was confirmed by RT-qPCR (A, C and E) and immunoblotting (B, D and F) . The cycle threshold (Ct) values of PLK4 were normalized to actin internal control (Suppl. Table 1). For immunoblotting, PLK4 band intensity was normalized to the band intensity of actin to calculate normalized band intensity. scr– Scramble control siRNA

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Pellizzari, S., Bhat, V., Athwal, H. et al. PLK4 as a potential target to enhance radiosensitivity in triple-negative breast cancer. Radiat Oncol 19 , 24 (2024). https://doi.org/10.1186/s13014-024-02410-z

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  • Breast Cancer
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  • Combination therapy

Radiation Oncology

ISSN: 1748-717X

case study on triple negative breast cancer

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  • Published: 14 February 2024

Icariin exerts anti-tumor activity by inducing autophagy via AMPK/mTOR/ULK1 pathway in triple-negative breast cancer

  • Mei Zhao 1   na1 ,
  • Panling Xu 1 , 2   na1 ,
  • Wenjing Shi 1 ,
  • Juan Wang 1 ,
  • Ting Wang 1 , 2 &
  • Ping Li 1 , 2 , 3  

Cancer Cell International volume  24 , Article number:  74 ( 2024 ) Cite this article

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Breast cancer is the most prevalent female tumor, of which triple-negative breast cancer (TNBC) accounts for about 15%. Characterized by its aggressive nature and limited treatment options, TNBC currently stands as a significant clinical challenge. This study aimed to investigate the effects of icariin (ICA) on TNBC and explore the underlying molecular mechanism.

Cell viability was assessed using CCK-8 assay, whereas the impact of ICA on cell proliferation was determined using colony formation assay and detection of proliferating cell nuclear antigen protein. Wound healing and transwell assays were used to evaluate the effects of ICA on cell migration and invasion, respectively. Flow cytometry was used to analyze cell cycle distribution and apoptosis. Transmission electron microscopy and monodansylcaverine staining were performed to detect the induction of autophagy, whereas molecular docking was conducted to predict the potential targets associated with autophagy. The in vivo anti-tumor effects of ICA were evaluated using a TNBC 4T1 xenograft mouse model. Protein expression levels were examined using immunoblotting and immunohistochemistry.

In vitro, ICA effectively suppressed the viability, proliferation, migration, and invasion of TNBC cells and induced G0/G1 phase cell cycle arrest, apoptosis, and autophagy in TNBC cells by regulating the adenosine monophosphate-activated protein kinase (AMPK)/mammalian target of rapamycin (mTOR)/Unc-51-like kinase 1 (ULK1) signaling pathway. The knockdown of AMPK and inhibition of autophagy with 3-methyladenine reversed the effects of ICA, highlighting the importance of AMPK and autophagy in the anti-cancer mechanism of ICA. In vivo, ICA significantly inhibited TNBC growth, promoted autophagy, and regulated AMPK/mTOR/ULK1 pathway.

Conclusions

Our findings demonstrated that ICA exerts anti-cancer effects against TNBC and the associated molecular mechanisms. This study will help to facilitate further preclinical and clinical investigations for the treatment of TNBC.

Breast cancer (BC) is associated with the highest incidence of malignancy in females, with up to 2.3 million new cases reported in 2020 [ 1 ]. Triple-negative breast cancer (TNBC), which accounts for approximately 15% of all BC cases, is characterized by the absence of estrogen receptors, progesterone receptors, and human epidermal growth factor receptor 2 expression. Tumors of this subtype are highly heterogeneous and aggressive, often associated with early recurrence, and preferentially occur in young females, especially those of Asian and African descent [ 2 , 3 , 4 ]. The unique biological characteristics of TNBC hinder its treatment. Although chemotherapy remains the primary treatment for TNBC, significant side effects and drug resistance limit its efficacy [ 5 ]. Therefore, alternative treatment for TNBC remains warranted.

Autophagy is a cellular process that maintains cellular homeostasis by recycling damaged organelles and misfolded proteins [ 6 , 7 ]. In cancer, autophagy exhibits complex and contextually relevant functions associated with tumor suppression, promotion, or therapy resistance. In early clinical trials, potent autophagy inducers, such as tamoxifen and everolimus, as well as autophagy inhibitors, such as chloroquine, approved by the U.S. Food and Drug Administration, have been used in combination with chemotherapy or radiation to increase tumor cell death or restore chemotherapy sensitivity [ 8 , 9 ]. Several recent studies have linked autophagy to TNBC, making it a potential target for TNBC therapy.

Some Chinese herbal medicines and their extracts have been found to have the potential to regulate autophagic pathways and, therefore, have anti-cancer treatment potential. For example, artemisinin induces autophagy in cancer cells, inducing cell death [ 10 ]. Icariin (ICA) is a flavonoid extracted from Epimedium with potent anti-proliferative effects against hepatocellular carcinoma, pancreatic cancer, and BC [ 11 , 12 , 13 , 14 ]. However, the molecular mechanism underlying the effects of ICA on autophagy-mediated anti-TNBC activity remains unclear.

Therefore, this study investigates the anti-cancer effects of ICA on TNBC and its underlying mechanisms. We found that ICA inhibited cell viability, proliferation, and invasion, blocked the cell cycle, and inhibited autophagy and apoptosis in TNBC cells. Furthermore, ICA promoted cellular autophagy by activating the adenosine monophosphate-activated protein kinase (AMPK)/mammalian target of rapamycin (mTOR)/Unc-51-like kinase 1 (ULK1) signaling pathway. Our findings suggest ICA as a natural product acting on autophagy with anti-tumor activity against TNBC.

Cells and reagents

Human TNBC cell lines MDA-MB-468 (468) and MDA-MB-231 (231), and mouse TNBC cell lines 4T1 were purchased from the National Collection of Authenticated Cell Cultures (Shanghai, China) and identified using short tandem repeat sequence analysis. Cells were cultured in DMEM medium (BI, USA) containing 10% fetal bovine serum (BI, USA) and 1% penicillin–streptomycin solution (100 × , Beyotime, China) in a humid incubator with 5% CO 2 at 37 °C. ICA (purity > 98%, as measured using high-performance liquid chromatography) was purchased from Shanghai Yuanye Bio-Technology Co., Ltd. (China). ICA was dissolved in 100 mM of 100% dimethyl sulfoxide (DMSO) and stored at − 20 °C. The medium used contained no more than 0.1% DMSO. Metformin (MET) and 3-Methyladenine (3-MA) were purchased from MedChemExpress (USA) and configured with phosphate buffer saline (PBS) when used.

Cell viability assay

Suspensions of 468, 231, and 4T1 cells were seeded in 96-well plates at a concentration of 1 × 10 4 cells/well and incubated for 24 h. After adherence, cells were treated with different concentrations of ICA (0, 12.5, 25, 50, 75, and 100 µmol/L) and incubated at 37 °C for 24, 48, or 72 h. Cell viability was measured using an enhanced Cell Counting Kit-8 (CCK-8) (Beyotime, China). Cells were stored in a solution containing CCK-8 DMEM (10 μL CCK-8 at 100 μL DMEM) for 2 h at 37 °C. Absorbance at 450 nm was measured using a microplate reader (Biotek Synergy H1, USA).

Colony formation assay

The 468 and 4T1 cells were inoculated in 6-well plates (400–600 cells/well) for 48 h and then treated with different concentrations of ICA for 24 h. Following a 10-day incubation, colonies containing > 50 cells were fixed with 4% paraformaldehyde for 15 min, stained with 0.5% crystal violet for 20 min, imaged, and counted using ImageJ software (Germany). The experiment was repeated three times.

Wound healing assay

Cells were inoculated into 6-well plates and scratched with the tip of a 1-mL pipette when the cells reached approximately 90% confluence. Cells were treated with different concentrations of ICA and cultured for 48 h. After scratching at 0, 24, and 48 h, cells were imaged using a microscope (Olympus, Japan). Wound closure was measured using ImageJ software.

Transwell invasion assay

To assess the effect of ICA on cell invasion, cell culture chambers (Corning, NY, USA) were placed in a 24-well plate to separate the upper and lower chambers. Then, 1 × 10 5 DMEM cell suspensions pretreated with different concentrations of ICA for 24 h were seeded into the upper chamber pre-coated with Matrigel, and a medium containing 10% FBS was placed in the lower chamber. Incubation at 37 °C for 24 h, non-invasive cells were wiped off the filter's upper surface using a cotton swab. On the bottom surface, invasive cells were fixed with 4% paraformaldehyde and stained with 0.1% crystal violet. Finally, the cells were imaged and counted under a microscope (Olympus, Japan).

Cell cycle assay

Cell cycle analysis was performed using a Cell Cycle and Apoptosis Analysis Kit (Beyotime, China). Cells were collected following treatment with ICA and fixed in 70% ethanol at 4 °C for 24 h. A propidium iodide staining solution was applied to the cell samples, and they were incubated in the dark for 30 min at 37 °C. Flow cytometry (Beckman, USA) was used to detect the cell cycle, and Modfit software (version 5.0, USA) was used to analyze it.

Cell apoptosis assay

The Annexin V-FITC Apoptosis Detection Kit (Beyotime, China) was used to detect cell apoptosis. Cells were stained with Annexin V-FITC/PI and analyzed using flow cytometry after being treated with ICA, ICA ± 3-MA, or ICA ± MET. Apoptotic cells were considered to be Annexin V + /PI + .

Autophagy staining assay

An Autophagy Staining Assay Kit with monodansylcaverine (MDC) (Beyotime, China) was used to detect autophagy. Cells treated with different concentrations were incubated with MDC staining solution at 37 °C in the dark for 30 min. The green fluorescence observed using a fluorescence microscope (Olympus, Japan) indicated an autophagosome.

Western blot analysis

Cells were treated with ICA for 24 h and then were lysed with RIPA lysis buffer containing phosphatase inhibitor and phenylmethylsulfonyl fluoride, and protein samples were separated using 12.5%, 10%, or 6% SDS-PAGE gels and transferred to PVDF membranes. Tumor tissues from mice were immersed in RIPA buffer, ground using a tissue homogenizer (JINGXIN CO.,LTD, China), and centrifuged to obtain the supernatant, which was referred to as tissue protein samples. After blocking with QuickBlock ™ Blocking Buffer (Beyotime, China) for 20 min at room temperature, the membrane was incubated overnight with the primary antibody (1:1000) at 4 °C and incubated at room temperature for 1 h with the second antibody (HRP-labeled Goat Anti-Rabbit IgG(H + L), 1:5000). The target blots were then obtained using a highly sensitive enhanced chemiluminescence reagent (Beyotime, China) on the machine (Bio-Rad, USA). Antibodies against β-actin (AF5003), LC3B (AL221), AMPK alpha 1 (AF1627), and phospho-AMPK alpha 1 (Ser496) (AF2677) were purchased from Beyotime Company (China); phospho-ULK1 (Ser757) [Ser758] (AF4387), mTOR (AF6308), and phospho-mTOR (Ser2481) (AF3309) were purchased from Affinity company (China); proliferating cell nuclear antigen (PCNA; 13110) was purchased from Cell Signaling Technology (USA); BECN1 (T55092F), P62 (T55546F), and ULK1 (T5692F) were gifted by Abmart company (China); and the second antibody HRP-labeled Goat Anti-Rabbit IgG(H + L) (A0208) was purchased from Beyotime Company (China).

Molecular docking

The structures of AMPK (PDB ID:4CFH), mTOR (PDB ID:3JBZ), and ULK1 (PDB ID:4WNO) were obtained from the PDB database ( https://www.pdbus.org/ ). PyMol 2.5.0a0 software (Schrödinger, USA) was used to remove water molecules and irrelevant ligands from the target protein structures using AMPK, mTOR, and ULK1 proteins as receptors. The ICA structure was obtained from PubChem ( https://pubchem.ncbi.nlm.nih.gov ). The receptors were docked to the ligand ICA following hydrogenation, and atomic charges were added using AutoDock Tools-1.5.7 software (Scripps Research, USA). Molecular docking was carried out using AutoDock AutoDock4.2.6 software (Scripps Research, USA). PyMOL 2.5.0a0 was used to observe the binding of ICA to AMPK, mTOR, and ULK1.

Knockdown of AMPK

The small interfering RNA of AMPK (si-AMPK) and negative control (si-NC) were designed and synthesized by GenePharma Co., Ltd (China). Approximately 1 × 10 5 cells were seeded per well in a 6-well plate and cultured until reaching 50–60% confluence. Transfection was performed using Lipo8000 ™ Transfection Reagent (Beyotime, China) along with si-AMPK or si-NC (100 pmol/well). After 12 h, the medium was replaced, and cells were further cultured for an additional 36 h. Then, the cells underwent intervention with ICA (25 µM) for 24 h.

In vivo tumor xenograft models

Five-week-old female BALB/c mice were purchased from Huachuang Sino Medicine Technology Co. Ltd. (SCXK2020-0009). All animal procedures were performed in accordance with the China Animal Welfare Guidelines and approved by the Animal Ethics Committee of Anhui Medical University (LLSC20160112). After 1 week of adaptation, 5 × 10 6 4T1 cells were subcutaneously injected into the right lower back of each mouse. The mice were randomly divided into three groups (control, 20, and 40 mg/kg) (n = 6) when the tumor volume reached approximately 100 mm 3 (after approximately 1 week). Then, the daily injections of ICA were given intraperitoneally to mice in different groups. The tumor size and body weight of each mouse were measured every 3 days. The tumor volume was determined using digital Vernier calipers according to the formula: V (mm 3 ) = 1/2 × length × width 2 . After 15 days, the mice were anesthetized and sacrificed, and tumor tissues were collected, measured, and imaged. Tumor tissues and main organs were fixed in 4% paraformaldehyde for subsequent experiments.

Hematoxylin and eosin (H&E) staining and immunohistochemistry (IHC)

After fixation for at least 24 h, the tissues were dehydrated with ethanol solution and xylene, embedded in paraffin, and cut into 5-µm sections. Sections were rehydrated with ethanol and stained with hematoxylin (Sigma, USA) and eosin (Sigma, USA). Other sections were dewaxed and rehydrated, and antigens were extracted with 0.01 M sodium citrate buffer (pH 6.0). The sections were sequentially incubated with 3% hydrogen peroxide, 0.1% Triton X-100, and 3% BSA and treated with primary antibodies against Ki67, LC3B, or P62 for 2 h at 37 °C, followed by secondary antibodies. Finally, the sections were treated with 3,3ʹ-diaminobenzidine tetrahydrochloride and hematoxylin, dehydrated, dried, and then observed under a microscope.

Statistical analysis

The results are presented as mean ± standard deviation (SD) from at least three independent experiments. One-way analysis of variance (ANOVA) (Dunnett’s post-hoc test) and Student's t- test were used for data analysis. P < 0.05 were considered statistically significant, recorded as *P < 0.05, **P < 0.01, and ***P < 0.001.

ICA effectively inhibited viability and proliferation of TNBC cells in vitro

The chemical structure of ICA is shown in Fig.  1 A. To evaluate the inhibitory effect of ICA on TNBC cells viability, TNBC cell lines 468, 4T1, and 231 were treated with different concentrations of ICA (0, 6.25, 12.5, 25, 50, and 100 µM) for 24, 48, and 72 h. As shown in Fig.  1 B–D, ICA significantly reduced the viability of all cells, with 468 (half maximal inhibitory concentration of 27.71, 20.93, and 12.85 µM for 24, 48, and 72 h, respectively) and 4T1 (37.70, 19.74, and 12.45 µM) cells being more sensitive than 231 (47.93, 28.79, and 14.84 µM). The 468 and 4T1 represent human and murine TNBC cell lines, respectively, selected for subsequent studies. The anti-proliferative activity of ICA was verified by colony formation assays and western blot analyses. The results showed that, compared to the control group (0 µM), treatment with ICA led to a significant reduction in colony size and number (Fig.  1 E, F), as well as a significantly decreased expression of the PCNA protein (Fig.  1 G, H).

figure 1

ICA inhibited the growth and proliferation of TNBC cells in vitro. A The chemical structure of ICA. B – D Cell viability analysis using CCK-8 assays of MDA-MB-468, 4T1, and MDA-MB-231 cells following treatment with different concentrations (0, 6.25, 12.5, 25, 50, and 100 µM) of ICA for 24, 48, or 72 h. E , F Colony formation analysis of 468 and 4T1 cells following treatment with different concentrations (0, 12.5, and 25 µM) of ICA. G , H The protein expression of PCNA was detected using western blotting with β-actin as an internal control. Bars represent the means ± SD of at least three independent experiments; *P < 0.05, **P < 0.01, and ***P < 0.001 compared with the control group (0 µM). ICA icariin, TNBC triple-negative breast cancer, CCK-8 Cell Counting Kit-8, PCNA proliferating cell nuclear antigen

ICA inhibited the migration and invasion of TNBC cells in vitro

Wound-healing assays were used to evaluate ICA's effect on TNBC cell migration. The results showed that the migration of both 468 (Fig.  2 A, B) and 4T1 (Fig.  2 C, D) cells was significantly inhibited compared with the control group at 24 and 48 h following ICA treatment. Additionally, based on transwell invasion assay results, ICA had a significant anti-invasive effect on both 468 and 4T1 cells in a concentration-dependent manner compared with the control group (Fig.  2 D, E).

figure 2

ICA suppressed migration and invasion in TNBC cells. A – D After treatment with different concentrations (0, 12.5, and 25 µM) of ICA, wound healing of MDA-MB-468 and 4T1 cells was measured. B , D Analysis of the results of wound healing experiments on MDA-MB-468 and 4T1 cells. E , F After treatment with different concentrations of ICA, transwell invasion for MDA-MB-468 and 4T1 cells was measured. Bars represent the means ± SD of at least three independent experiments; *P < 0.05, **P < 0.01, and ***P < 0.001 compared with the control group (0 µM). ICA icariin, TNBC triple-negative breast cancer

ICA induced cell cycle arrest, apoptosis, and autophagy

As shown in Fig.  3 A, B, flow cytometry analysis suggested that the percentage of S-phase cells decreased, while that of G0/G1-phase cells increased following treatment with ICA for 24 h. These results indicated that ICA effectively induced cell cycle arrest in the G0/G1 phase. Additionally, flow cytometric analyses revealed that ICA treatment of TNBC cells for 24 h significantly induced apoptosis in a concentration-dependent manner. To further explore the anti-TNBC activity of ICA, we investigated its effect on autophagy. Transmission electron microscopy (TEM) revealed the presence of autophagic vacuoles and autolysosomes in 468 and 4T1 cells after exposure to ICA for 24 h (red arrows indicating autophagosomes, and black arrows indicating autolysosomes, as shown in Fig.  3 E). Additionally, MDC can specifically label autophagosomes through ion trapping and bind to membrane lipids; therefore, it is also often used to detect autophagy [ 15 ]. As shown in Fig.  3 F, the green fluorescent dots represent the autophagosome cells produced following ICA treatment; the mean fluorescence intensity of autophagosomes was significantly increased compared with that in the control group (0 µM) (Fig.  3 G). Certainly, there are three key genes associated with autophagy. LC3B-II indicates autophagic vesicles, BECN1 (Beclin1) coordinates autophagy proteins to autophagic vesicles, and P62 (SQSTM1) degrades within autophagic lysosomes after increased autophagic flux [ 16 ]. In 468 and 4T1 cells, ICA treatment resulted in the dose-dependent conversion of LC3B-I to LC3B-II and increased BECN1 expression, whereas P62 protein levels were significantly reduced (Fig.  3 H, I).

figure 3

ICA induced cell cycle arrest, apoptosis, and autophagy in TNBC cells. A , B MDA-MB-468 and 4T1 cells were treated with different concentrations of ICA (0, 12.5, and 25 µM). The cell cycle distribution was analyzed using flow cytometry. C , D MDA-MB-468 and 4T1 cells were treated with ICA (0, 12.5, and 25 µM) followed by Annexin V/PI double staining and analyzed using flow cytometry. E MDA-MB-468 and 4T1 cells were treated with ICA (25 µM) and detected by TEM. The red arrows represent autophagosomes, and the black arrows denote autolysosomes. F , G MDA-MB-468 and 4T1 cells treated with different concentrations of ICA (0, 12.5, and 25 µM) were stained with MDC and imaged using a microscope (20 ×). The green circles represent autophagosomes. H , I The protein expression of P62, BECN1, and LC3B was determined using western blotting with β-actin as an internal control. Bars represent the means ± SD of at least three independent experiments; *P < 0.05, **P < 0.01, and ***P < 0.001 compared with the control group (0 µM). ICA icariin, TNBC triple-negative breast cancer, TEM transmission electron microscope, P62 SQSTM1, BECN1 Beclin1, LC3B MAP1LC3B

ICA promoted autophagy by regulating AMPK/mTOR/ULK1 signaling pathway in TNBC cells

ULK1 is closely associated with the formation of autophagic vesicles regulated by upstream signaling pathways such as AMPK and mTOR [ 17 ]. Therefore, to further validate the role of ICA in the AMPK/mTOR/ULK1 pathway, molecular docking was used to determine whether ICA could act on the three target proteins. Figure  4 A–C shows the docking diagrams of ICA with AMPK, mTOR, and ULK1, respectively, with orange representing ICA, purple representing the residues that link the protein to ICA, and yellow representing the hydrogen bonds connecting ICA to the proteins. In Fig.  4 D–G, the phosphorylation levels of AMPK and ULK1 increased with escalating doses of ICA treatment, whereas the phosphorylation level of mTOR decreased with increasing doses. These results suggest that ICA could activate the AMPK/mTOR/ULK1 signaling pathway in TNBC cells.

figure 4

ICA regulated the AMPK/mTOR/ULK1 signaling pathway. A – C Mode of ICA binding with AMPK, mTOR, and ULK1. The chemical structure in orange indicates ICA, and the purple structure indicates the binding site of ICA, AMPK, mTOR, and ULK1. D , E The effect of ICA on the expression of AMPK, ULK1, and mTOR and their phosphorylation in MDA-MB-468 cells; F , G in 4T1 cells. Bars represent the means ± SD of at least three independent experiments; ns, not significant; *P < 0.05, **P < 0.01, and ***P < 0.001 compared with the control group (0 µM). ICA icariin, AMPK adenosine 5ʹ-monophosphate (AMP)-activated protein kinase, mTOR mammalian target of rapamycin, ULK1 Unc-51-like kinase 1

To further explore the role of AMPK in ICA-induced autophagy and apoptosis, we utilized flow cytometry and western blotting analyses. We compared the therapeutic effects of ICA and MET, a known AMPK and autophagy inducer [ 18 , 19 ] on TNBC cells. The results indicated that ICA’s impact on AMPK, P62 protein expression, and LC3B-II/LC3B-I ratio (Fig.  5 A, B), as well as its modulation of cell apoptosis (Fig.  5 C, D), is similar to MET. The combined use of both drugs further enhanced autophagy and apoptosis. Upon siRNA-mediated knockdown of AMPK, ICA treatment in MDA-MB-468 and 4T1 cells resulted in a decrease in the LC3-II/I ratio, an increase in P62 expression, and corresponding changes in mTOR, ULK1, and their phosphorylated proteins (Fig.  5 E, F). Additionally, apoptotic cell death significantly decreased (Fig.  5 G, H). These data indicated that the AMPK/mTOR/ULK1 pathway plays a crucial regulatory role in ICA-induced autophagy and apoptosis.

figure 5

ICA regulated autophagy and apoptosis by acting on AMPK. A , B Western blotting showing the expression of AMPK, P62, and LC3B proteins in MDA-MB-468 and 4T1 after ICA with or without MET (5 mM) exposure, with β-actin as an internal control. C , D MDA-MB-468 and 4T1 cells were treated with ICA (25 µM) with or without MET (5 mM). Apoptosis was analyzed using flow cytometry. E , F The protein expression levels of P62, LC3B, as well as AMPK, mTOR, ULK1, and their phosphorylated proteins were detected using western blotting analyses after knocking down AMPK in TNBC cells. G , H The apoptosis was analyzed by flow cytometry after knocking down AMPK in TNBC cells. Bars represent the means ± SD of at least three independent experiments; ns, not significant; *P < 0.05, **P < 0.01, and ***P < 0.001. ICA icariin, TNBC triple-negative breast cancer, MET metformin, P62 SQSTM1, BECN1 Beclin1, LC3B MAP1LC3B, AMPK adenosine 5ʹ-monophosphate (AMP)-activated protein kinase, mTOR mammalian target of rapamycin, ULK1 Unc-51-like kinase 1

Autophagy inhibitor 3-MA reversed the effect of ICA

To further investigate the effect of ICA on autophagy in TNBC cells, the autophagy inhibitor, 3-MA, was used in combination with ICA. The addition of 3-MA reduced the proportion of apoptotic TNBC cells (Fig.  6 A, B) and reversed the ICA-induced changes in BECN1, LC3B-II/LC3B-I, and p62 protein levels (Fig.  6 C, D). These results suggest that ICA exerts its anti-tumor effects by inducing autophagy.

figure 6

On TNBC cells, 3-MA reversed the effects of ICA. A , B MDA-MB-468 and 4T1 cells were treated with ICA (25 µM) with or without 3-MA (5 mM). Apoptosis was analyzed using flow cytometry. C , D Western blotting showing the expression of P62, BECN1, and LC3B proteins in MDA-MB-468 and 4T1 after ICA with or without 3-MA exposure, with β-actin as an internal control. Bars represent the means ± SD of at least three independent experiments; *P < 0.05, **P < 0.01, and ***P < 0.001 compared with the control group (0 µM). TNBC triple-negative breast cancer, 3-MA 3-methyladenine, ICA icariin, P62 SQSTM1, BECN1 Beclin1, LC3B MAP1LC3B

ICA inhibited tumor growth and promoted autophagy in vivo

To determine the antitumor effects of ICA in vivo, 4T1 tumor-bearing mice were treated with 20 or 40 mg/kg ICA. Figure  7 A–C shows that ICA treatment significantly inhibited the growth and weight of 4T1 tumors in a dose-dependent manner compared with the control group. The mice’s body weight did not change significantly during treatment compared with the control group (Fig.  7 D). H&E staining showed that the tumors in the ICA-treated group showed loosening of the tumor cell layer and coagulation or fragmentation of the nucleus, whereas no significant necrosis was observed in the liver, kidney, or spleen tissues (Fig.  7 E). ICA showed no significant side effects and did not cause major organ damage during treatment. The immunohistochemical analyses of the tumors revealed that ICA inhibited nuclear Ki-67-positive cell proliferation, enhanced LC3B expression, and reduced the expression of P62, thereby promoting autophagy and inhibiting proliferation (Fig.  7 F, G). The western blotting results of tumor tissue proteins suggested that ICA also increased the phosphorylation of AMPK and ULK1 while reducing the expression of phosphorylated mTOR protein in vivo.

figure 7

ICA inhibited tumor growth and promoted autophagy in vivo. A Image of 4T1 tumors from different groups. B Average tumor weight of each group. Bars represent the means ± SD of six mice. C The growth of 4T1 xenograft tumors during treatment with control (vehicle), ICA (20 mg/kg), and ICA (40 mg/kg). Bars represent the means ± SD of six mice. D Changes in body weight of mice in different groups during treatment. Bars represent the means ± SD of six mice. E H&E staining of tumor, liver, kidney, and spleen tissues in each group. F , G Ki-67, P62 and LC3B immunohistochemical results of tumors from each group. Bars represent the means ± SD of three independent experiments. H , I The protein expression of p-mTOR, mTOR, p-ULK1, ULK1, p-AMPK, and AMPK in xenograft tumor. Bars represent the means ± SD of three mice tumor samples. *P < 0.05, **P < 0.01, and ***P < 0.001 compared with the control group (0 µM). ICA icariin, TNBC triple-negative breast cancer, H&E hematoxylin and eosin

ICA is the main active ingredient of the traditional Chinese medicine Epimedium, which has several therapeutic properties, such as anti-rheumatic [ 20 ]. ICA has been shown to have anti-tumor activities in vitro and in vivo. Our results showed that ICA exhibits anti-TNBC properties both in vivo and in vitro. We also found that the anti-cancer effect of ICA was associated with the promotion of autophagy, possibly via ICA activation of the AMPK/mTOR/ULK1 pathway. Our study revealed a novel mechanism of ICA in TNBC associated with tumor autophagy, suggesting ICA is a promising treatment strategy against TNBC.

ICA inhibited the viability and proliferation of MDA-MB-468 and 4T1 cells in a concentration- and time-dependent manner and induced apoptosis. Moreover, the results of the mouse xenograft model experiments showed that ICA significantly inhibited tumor growth while reducing the proliferation index and promoting autophagy. Further studies on the mechanism of ICA killing of TNBC cells revealed that autophagic vesicle production was increased in ICA-treated TNBC cells. Additionally, with higher ICA doses, the LC3-BII/LC3B-I ratio increased (an indicator of autophagic flux), BECN1 expression increased (a marker of autophagosome formation), and p62 expression decreased (an indicator of autophagic degradation) [ 21 ]. Autophagy has emerged as a potential target for cancer therapy [ 22 , 23 ]. Several small molecules target autophagy and may, therefore, be used for TNBC treatment. For example, SLLN-15 (an oral selenopurine molecule), LYN-1604 (a ULK1 agonist), and flubendazole exert anti-tumor effects by inducing autophagy [ 24 , 25 , 26 ].

Autophagy and apoptosis, two programmed cell death pathways, have been focal points in cancer research. These two metabolic pathways play crucial roles in maintaining cellular and organismal homeostasis [ 27 ]. Ideally, autophagy and apoptosis contribute to tumor suppression, as autophagy aids in eliminating cancer cells, whereas apoptosis prevents their survival [ 28 , 29 ]. However, as cancer progresses, autophagy exhibits a dual role due to its crosstalk with the regulatory mechanisms of apoptosis. For one thing, autophagy itself serves as a form of cell death known as autophagic cell death. Specific inhibition of autophagy by suppressing, depleting, or deleting various crucial autophagy-related genes and/or proteins could prevent cell death, which proves that the ultimate cell death process is caused by autophagy rather than apoptosis [ 30 , 31 ]. For another, the induction of autophagy promotes the activation of apoptosis. Autophagic proteins play an additional role in the transduction of pro-apoptotic signals, finally leading to cell death by inducing apoptosis [ 32 , 33 ]. Additionally, there is another situation where autophagy inhibits apoptosis. This is generally achieved by clearing damaged mitochondria, increasing the threshold for apoptosis induction, and selectively reducing the abundance of pro-apoptotic proteins in the cytoplasm [ 32 , 34 ]. In simple terms, autophagy is a metabolic pathway in most eukaryotic cells that promotes both cancer cell survival (protective autophagy) and death (cytotoxic/non-protective autophagy) in different types and stages of cancer [ 35 ]. Therefore, whether autophagy is beneficial or inhibitory to therapeutic outcomes is context-dependent. To further investigate the impact of ICA on autophagy and apoptosis, we conducted experiments using the autophagosome formation inhibitor 3-MA. The results showed treatment with 3-MA inhibited the effect of ICA, suggesting that autophagy regulates TNBC cell apoptosis.

An increasing body of evidence suggests a paradoxical role of autophagy in response to anticancer treatments, much like its capacity to either trigger cell death or enhance cell survival. One perspective is that autophagy is activated as a protective mechanism, mediating the acquisition of acquired resistance in certain cancer cells during chemotherapy. Another perspective is that autophagy may also function as an executioner, with anticancer treatment enhancing autophagic cell death [ 36 ]. In some preclinical models, autophagy inhibition synergistically enhances cytotoxicity with several anticancer drugs. For instance, the combination of chloroquine with 5-fluorouracil increases its anti-colorectal cancer effect, and co-administration with topotecan enhances its anti-lung cancer effect [ 37 , 38 ]. In contrast, some studies have found that inducing autophagic cell death is an alternative method to kill tumor cells without developing resistance to anticancer drugs. The synergistic promotion of autophagy is observed when autophagy inducers are combined with cytotoxic drugs. For example, the combination of cannabinoids (autophagy inducers) and temozolomide (TMZ) strongly activates autophagy-mediated cancer cell death, resulting in a potent antitumor effect against both TMZ-sensitive and TMZ-resistant tumors [ 39 ]. Therefore, the role of autophagy in cancer treatment is not straightforward; it may vary depending on cell types, stress signals, and other circumstances. Areas that need to be further addressed through experiments include elucidating the impact of the tumor microenvironment on autophagic function and determining the role of autophagy in regulating treatment sensitivity.

The AMPK/mTOR/ULK1 signaling pathway plays an important role in regulating autophagy. In this study, we used molecular docking technology to predict whether ICA could act on these three targets. Western blotting results suggested that ICA treatment increased the phosphorylation of AMPK and ULK1 in TNBC cells and decreased the phosphorylation of mTOR. Subsequently, we utilized si-RNA to knock down AMPK in cells, reversing ICA’s effects on cell autophagy and apoptosis. As a key regulator of energy metabolism, cell growth, and autophagy, AMPK can be activated in various ways, including reactive oxygen species (ROS) [ 40 , 41 ]. A previous study showed that ICA increases ROS production and activates mitochondrial apoptosis pathways [ 14 ]. mTOR, which regulates cell growth and metabolism, negatively regulates autophagy activation [ 42 ]. ULK1, a serine/threonine kinase, induces autophagosome formation [ 43 ]. In this canonical pathway, AMPK directly phosphorylates and activates ULK1; mTOR is a key regulator of autophagy as it inhibits ULK1 activation [ 44 ]. The results of the molecular docking experiments showed that ICA can act on various targets, and ULK1 can be activated both directly by phosphorylated AMPK and indirectly by mTOR inactivation, thereby affecting autophagy (Fig.  8 ). Understanding the interplay between ICA, the AMPK/mTOR/ULK1 signaling pathway, and autophagy can provide insights into the mechanisms underlying the therapeutic effects of ICA in TNBC. Targeting this pathway and modulating autophagy may provide new opportunities for the development of combination therapies to improve the outcomes of patients with TNBC.

figure 8

Schematic illustration of the ICA effects on TNBC. ICA icariin, TNBC triple-negative breast cancer

This study has some limitations. Firstly, the study did not investigate the pharmacokinetics and pharmacodynamics of ICA, and therefore, its safety and efficacy as a potential therapeutic agent remain to be investigated. Secondly, the influence of ICA on the sensitivity of TNBC to chemotherapy drugs has not been investigated and is currently under investigation for further refinement. Lastly, meticulously planned randomized controlled trials have the potential to yield crucial clinical insights and establish a more robust theoretical framework for the clinical implementation of ICA in TNBC management. Consequently, additional research endeavors are necessary to delve deeper into the role of ICA in TNBC treatment and unravel its underlying mechanism.

Our study demonstrated the potent anti-TNBC efficacy of ICA both in vivo and in vitro and revealed the molecular mechanism by which ICA induces autophagy to inhibit TNBC progression by activating the AMPK/mTOR/ULK1 signaling pathway. These findings suggest the potential of ICA as a therapeutic agent for the treatment of TNBC. Further studies are warranted to verify our findings, identify molecular targets, and overcome the limitations of experimental models. This study provides novel insights into the mechanism of action of ICA and will help to facilitate future research and development of TNBC-targeted therapies.

Availability of data and materials

Data will be made available on request.

Abbreviations

Breast cancer

Triple-negative breast cancer

Food and Drug Administration

Triple-negative breast cancers

Hematoxylin and eosin

Immunohistochemistry

Diaminobenzidine tetrahydrochloride

Standard deviation

Adenosine monophosphate-activated protein kinase

Unc-51-like kinase 1

Mammalian target of rapamycin

Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 Countries. CA Cancer J Clin. 2021;71:209–49.

Article   PubMed   Google Scholar  

Zagami P, Carey LA. Triple negative breast cancer: pitfalls and progress. Npj Breast Cancer. 2022;8:1–10.

Article   Google Scholar  

Yin L, Duan J-J, Bian X-W, Yu S. Triple-negative breast cancer molecular subtyping and treatment progress. Breast Cancer Res. 2020;22:61.

Article   PubMed   PubMed Central   Google Scholar  

Won K-A, Spruck C. Triple-negative breast cancer therapy: current and future perspectives (Review). Int J Oncol. 2020;57:1245–61.

Article   CAS   PubMed   PubMed Central   Google Scholar  

Bai X, Ni J, Beretov J, Graham P, Li Y. Triple-negative breast cancer therapeutic resistance: Where is the Achilles’ heel? Cancer Lett. 2021;497:100–11.

Article   CAS   PubMed   Google Scholar  

Glick D, Barth S, Macleod KF. Autophagy: cellular and molecular mechanisms. J Pathol. 2010;221:3–12.

Li W, He P, Huang Y, Li Y-F, Lu J, Li M, et al. Selective autophagy of intracellular organelles: recent research advances. Theranostics. 2021;11:222–56.

Morgan MJ, Gamez G, Menke C, Hernandez A, Thorburn J, Gidan F, et al. Regulation of autophagy and chloroquine sensitivity by oncogenic RAS in vitro is context-dependent. Autophagy. 2014;10:1814–26.

Vakifahmetoglu-Norberg H, Xia H, Yuan J. Pharmacologic agents targeting autophagy. J Clin Invest. 2015;125:5–13.

Chen G-Q, Benthani FA, Wu J, Liang D, Bian Z-X, Jiang X. Artemisinin compounds sensitize cancer cells to ferroptosis by regulating iron homeostasis. Cell Death Differ. 2020;27:242–54.

Liu Y, Yang H, Xiong J, Zhao J, Guo M, Chen J, et al. Icariin as an emerging candidate drug for anticancer treatment: Current status and perspective. Biomed Pharmacother Biomed Pharmacother. 2023;157:113991.

Li S, Dong P, Wang J, Zhang J, Gu J, Wu X, et al. Icariin, a natural flavonol glycoside, induces apoptosis in human hepatoma SMMC-7721 cells via a ROS/JNK-dependent mitochondrial pathway. Cancer Lett. 2010;298:222–30.

Zheng X, Li D, Li J, Wang B, Zhang L, Yuan X, et al. Optimization of the process for purifying icariin from Herba Epimedii by macroporous resin and the regulatory role of icariin in the tumor immune microenvironment. Biomed Pharmacother Biomed Pharmacother. 2019;118:109275.

Song L, Chen X, Mi L, Liu C, Zhu S, Yang T, et al. Icariin-induced inhibition of SIRT6/NF-κB triggers redox mediated apoptosis and enhances anti-tumor immunity in triple-negative breast cancer. Cancer Sci. 2020;111:4242–56.

Biederbick A, Kern HF, Elsässer HP. Monodansylcadaverine (MDC) is a specific in vivo marker for autophagic vacuoles. Eur J Cell Biol. 1995;66:3–14.

CAS   PubMed   Google Scholar  

Sharif T, Martell E, Dai C, Ghassemi-Rad MS, Hanes MR, Murphy PJ, et al. HDAC6 differentially regulates autophagy in stem-like versus differentiated cancer cells. Autophagy. 2019;15:686–706.

Kim J, Kundu M, Viollet B, Guan K-L. AMPK and mTOR regulate autophagy through direct phosphorylation of Ulk1. Nat Cell Biol. 2011;13:132–41.

Foretz M, Guigas B, Bertrand L, Pollak M, Viollet B. Metformin: from mechanisms of action to therapies. Cell Metab. 2014;20:953–66.

Chen C, Wang H, Geng X, Zhang D, Zhu Z, Zhang G, et al. Metformin exerts anti-AR-negative prostate cancer activity via AMPK/autophagy signaling pathway. Cancer Cell Int. 2021;21:404.

Tan H-L, Chan K-G, Pusparajah P, Saokaew S, Duangjai A, Lee L-H, et al. Anti-cancer properties of the naturally occurring aphrodisiacs: icariin and its derivatives. Front Pharmacol. 2016. https://doi.org/10.3389/fphar.2016.00191 .

Klionsky DJ, Abdel-Aziz AK, Abdelfatah S, Abdellatif M, Abdoli A, Abel S, et al. Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)1. Autophagy. 2021;17:1–382.

Abd El-Aziz YS, Gillson J, Jansson PJ, Sahni S. Autophagy: a promising target for triple negative breast cancers. Pharmacol Res. 2022;175:106006.

Levy JMM, Towers CG, Thorburn A. Targeting autophagy in cancer. Nat Rev Cancer. 2017;17:528–42.

Chang C-H, Bijian K, Wernic D, Su J, da Silva SD, Yu H, et al. A novel orally available seleno-purine molecule suppresses triple-negative breast cancer cell proliferation and progression to metastasis by inducing cytostatic autophagy. Autophagy. 2019;15:1376–90.

Ouyang L, Zhang L, Fu L, Liu B. A small-molecule activator induces ULK1-modulating autophagy-associated cell death in triple negative breast cancer. Autophagy. 2017;13:777–8.

Zhen Y, Zhao R, Wang M, Jiang X, Gao F, Fu L, et al. Flubendazole elicits anti-cancer effects via targeting EVA1A-modulated autophagy and apoptosis in Triple-negative Breast Cancer. Theranostics. 2020;10:8080–97.

Das S, Shukla N, Singh SS, Kushwaha S, Shrivastava R. Mechanism of interaction between autophagy and apoptosis in cancer. Apoptosis. 2021;26:512–33.

Yun CW, Lee SH. The roles of autophagy in cancer. Int J Mol Sci. 2018;19:3466.

Carneiro BA, El-Deiry WS. Targeting apoptosis in cancer therapy. Nat Rev Clin Oncol. 2020;17:395–417.

Shen H-M, Codogno P. Autophagic cell death: loch Ness monster or endangered species? Autophagy. 2011;7:457–65.

Kroemer G, Levine B. Autophagic cell death: the story of a misnomer. Nat Rev Mol Cell Biol. 2008;9:1004–10.

Mariño G, Niso-Santano M, Baehrecke EH, Kroemer G. Self-consumption: the interplay of autophagy and apoptosis. Nat Rev Mol Cell Biol. 2014;15:81–94.

Liu G, Pei F, Yang F, Li L, Amin AD, Liu S, et al. Role of autophagy and apoptosis in non-small-cell lung cancer. Int J Mol Sci. 2017;18:367.

Bonora M, Giorgi C, Pinton P. Molecular mechanisms and consequences of mitochondrial permeability transition. Nat Rev Mol Cell Biol. 2022;23:266–85.

Russo M, Russo GL. Autophagy inducers in cancer. Biochem Pharmacol. 2018;153:51–61.

Sui X, Chen R, Wang Z, Huang Z, Kong N, Zhang M, et al. Autophagy and chemotherapy resistance: a promising therapeutic target for cancer treatment. Cell Death Dis. 2013;4:e838.

Wang Y, Peng R-Q, Li D-D, Ding Y, Wu X-Q, Zeng Y-X, et al. Chloroquine enhances the cytotoxicity of topotecan by inhibiting autophagy in lung cancer cells. Chin J Cancer. 2011;30:690–700.

Sasaki K, Tsuno NH, Sunami E, Tsurita G, Kawai K, Okaji Y, et al. Chloroquine potentiates the anti-cancer effect of 5-fluorouracil on colon cancer cells. BMC Cancer. 2010;10:370.

Torres S, Lorente M, Rodríguez-Fornés F, Hernández-Tiedra S, Salazar M, García-Taboada E, et al. A combined preclinical therapy of cannabinoids and temozolomide against glioma. Mol Cancer Ther. 2011;10:90–103.

Herzig S, Shaw RJ. AMPK: guardian of metabolism and mitochondrial homeostasis. Nat Rev Mol Cell Biol. 2018;19:121–35.

Duan P, Hu C, Quan C, Yu T, Zhou W, Yuan M, et al. 4-Nonylphenol induces apoptosis, autophagy and necrosis in Sertoli cells: Involvement of ROS-mediated AMPK/AKT-mTOR and JNK pathways. Toxicology. 2016;341–343:28–40.

Kim J, Guan K-L. mTOR as a central hub of nutrient signalling and cell growth. Nat Cell Biol. 2019;21:63–71.

Zhang L, Ouyang L, Guo Y, Zhang J, Liu B. UNC-51-like Kinase 1: from an autophagic initiator to multifunctional drug target. J Med Chem. 2018;61:6491–500.

Pyo KE, Kim CR, Lee M, Kim J-S, Kim KI, Baek SH. ULK1 O-GlcNAcylation is crucial for activating VPS34 via ATG14L during autophagy initiation. Cell Rep. 2018;25:2878-2890.e4.

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Mei Zhao and Panling Xu have contributed equally to this work.

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Department of Chinese Integrative Medicine Oncology, The First Affiliated Hospital of Anhui Medical University, 120 Wanshui Road, Hefei, 230032, Anhui, People’s Republic of China

Mei Zhao, Panling Xu, Wenjing Shi, Juan Wang, Ting Wang & Ping Li

Department of Integrated Traditional Chinese and Western Medicine, Anhui Medical University, Hefei, China

Panling Xu, Ting Wang & Ping Li

Graduate School of Anhui University of Traditional Chinese Medicine, Hefei, China

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ZM, XP and LP: conceptualization, methodology; SW and WJ: validation, data curation; ZM and XP: writing-original draft preparation; ZM, XP and WT: visualization, investigation; WT and LP: supervision, project administration; ZM, XP and LP: writing- reviewing and editing.

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Zhao, M., Xu, P., Shi, W. et al. Icariin exerts anti-tumor activity by inducing autophagy via AMPK/mTOR/ULK1 pathway in triple-negative breast cancer. Cancer Cell Int 24 , 74 (2024). https://doi.org/10.1186/s12935-024-03266-9

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DOI : https://doi.org/10.1186/s12935-024-03266-9

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case study on triple negative breast cancer

Clinical Trials

Triple-negative breast cancer.

Displaying 35 studies

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This randomized phase II trial studies how well carboplatin and paclitaxel with or without atezolizumab before surgery works in treating patients with newly diagnosed, stage II-III triple negative breast cancer. Monoclonal antibodies, such as atezolizumab, may block tumor growth in different ways by targeting certain cells. Drugs used in chemotherapy, such as carboplatin and paclitaxel, work in different ways to stop the growth of tumor cells, either by killing the cells, by stopping them from dividing, or by stopping them from spreading. Giving carboplatin and paclitaxel with or without atezolizumab before surgery may make the tumor smaller and reduce the ...

The purpose of this trilal is to study a combination of neoadjuvant radiotherapy (RT), immunotherapy (pembrolizumab) and chemotherapy for lymph node-positive, triple negative (TN) or hormone receptor positive/HER2-negative breast cancer.

The purpose of this study is to determine whether treatment with alpelisib in combination with nab-paclitaxel is safe and effective in subjects with advanced triple negative breast cancer (aTNBC) who carry either a PIK3CA mutation (Study Part A) or have PTEN loss without PIK3CA mutation (Study Parts B1 and B2)

The purpose of this trial is to determine how well estradiol works in treating patients with estrogen receptor beta (ER beta) positive, triple negative breast cancer that has spread to nearby tissue or lymph nodes (locally advanced) or other places in the body (metastatic). Hormone receptors like ER beta allow the body to respond appropriately to hormones. Triple negative means that the breast cancer does not express other hormone receptors called ER alpha, progesterone, and HER2. In some people with triple negative breast cancer, ER beta is overexpressed. Tumor cells that overexpress ER beta grow slower in the laboratory and ...

This randomized phase II trial studies how well cisplatin works with or without veliparib in treating patients with triple-negative breast cancer and/or BRCA mutation-associated breast cancer that has come back or has or has not spread to the brain. Drugs used in chemotherapy, such as cisplatin, work in different ways to stop the growth of tumor cells, either by killing the cells, by stopping them from dividing, or by stopping them from spreading. Veliparib may stop the growth of tumor cells by blocking some of the enzymes needed for cell growth. It is not yet known if cisplatin is more ...

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The primary purpose of the Safety-Run-in Cohort 1 of this study is to evaluate the safety, tolerability, and recommended Phase 2 dose of magrolimab in combination with nab-paclitaxel or paclitaxel. In Phase 2 Cohort 1, the study will compare the efficacy of magrolimab in combination with nab-paclitaxel or paclitaxel versus nab-paclitaxel or paclitaxel alone as determined by progression-free survival (PFS) by investigator assessment

The primary purpose of the Safety-Run-in Cohort 2 of this study is to evaluate the safety, tolerability, and recommended Phase 2 dose of magrolimab in combination with sacituzumab govitecan. In Cohort 2 (Safety Run-in Cohort 2 and Phase 2 Cohort 2) the study will evaluate the efficacy of magrolimab in combination ...

This research study is studying Ruxolitinib as possible treatment for Inflammatory Breast Cancer (IBC). The Following drugs will be use in combination with Ruxolinitinib. - Paclitaxel (also called Taxol) - Doxorubicin also called Adriamycin - Cyclophosphamide, also called Cytoxan

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This is an international, multi-center, open-label, randomized, Phase III study in patients with metastatic TNBC refractory or relapsing after at least 2 prior chemotherapies (including a taxane) for their metastatic disease. Patients meeting eligibility will be randomized 1:1 to receive either sacituzumab govitecan or treatment of physician choice (TPC), which needs to be selected prior to randomization from one of the 4 allowed regimens. Randomization will be stratified by number of prior chemotherapies for advanced disease (2-3 vs > 3) and geographical location (North America vs Europe). Patients will be treated until progression, unacceptable toxicity, study withdrawal, or death, whichever ...

Objective: To determine the Overall Response Rate (ORR) to Imprime PGG + pembrolizumab in subjects with advanced melanoma or metastatic TNBC

Safety: To characterize the safety of Imprime PGG + pembrolizumab given in combination

Hypothesis: Restore (for melanoma) or enhance (for TNBC) sensitivity to checkpoint inhibitors (CPI) by appropriate and effective stimulation of the subject's innate and adaptive immune systems in those subjects who have failed 1st line therapy

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To evaluate the safety and tolerability of AMG 650 in adult participants and to determine the maximum tolerated dose (MTD) and/or recommended phase 2 dose (RP2D).

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A Phase 1a/1b Open-Label Study to Evaluate the Safety, Tolerability, Pharmacokinetics, and Pharmacodynamics of PY314 as a Single Agent and In Combination with Pembrolizumab in Subjects with Advanced Solid Tumors

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The purpose of this trial is to evaluate the safety of GEN1046 in patients with malignant solid tumors.

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Investigators profile three treatment response trajectories to close in on triple-negative breast cancer

C edars-Sinai Cancer investigators have analyzed the cells within triple-negative breast cancer tumors before and after radiation therapy with immunotherapy, identifying three patient groups with different responses to the treatment. Their study, published in Cancer Cell , found that for some patients with this difficult-to-treat cancer, radiation therapy plus immunotherapy could yield the best tumor-fighting immune response prior to surgery.

"Our most important finding was identifying these three different patient groups," said Simon Knott, Ph.D., co-director of the Applied Genomics Shared Resource at Cedars-Sinai Cancer and senior author of the study.

One group, Knott said, didn't respond at all to therapy, one responded well to immunotherapy, and one responded only to immunotherapy plus radiation therapy. "This could help us employ our most aggressive treatment options only when needed most," Knott said.

Triple-negative breast cancer is so called because its cells test negative for receptors to the hormones estrogen and progesterone and for a protein called HER2. These tumors, which account for 10%-15% of breast cancers, grow and spread faster than other types and, in general, have fewer treatment options.

Patients with triple-negative breast cancer generally receive treatment to shrink their tumors before having surgery. Immunotherapy, which uses a person's own immune system to fight cancer, is part of that pre-surgical treatment.

"Triple-negative breast cancer is the only type of breast cancer we treat with immunotherapy," said Stephen Shiao, MD, Ph.D., co-director of the Cancer Therapeutics Program at Cedars-Sinai Cancer and first author of the study. "Unfortunately, only 20% to 30% of patients respond to immunotherapy on its own. Combining it with chemotherapy boosts response to 60% but exposes patients to significant toxicity."

To determine whether a combination of radiation therapy and immunotherapy would improve patient response, investigators launched a clinical trial. During the trial, they examined tumors from 34 triple-negative breast cancer patients.

Patients underwent biopsies before treatment, after one course of immunotherapy, and after a second course of immunotherapy plus radiation therapy. Investigators then analyzed the biopsied tissues.

They used single-cell genetic profiling to identify the cancer cells and different types of immune cells making up each tumor. They also looked at proteins expressed by cells, mapping their positions and permitting a better understanding of how the different cells interact.

The analysis yielded profiles for three types of responders, Knott said.

"We saw that tumors of patients who didn't respond at all to pre-surgical therapy had no immune cells in them, and tumors of patients who responded right away to immunotherapy were packed with certain types of immune cells," Knott said. "That wasn't surprising. But we found another group of patients with tumors that looked quite similar to the tumors of non-responders and didn't respond to the initial round of immunotherapy.

"However, they did respond after the combination of immunotherapy and radiotherapy. After the combination therapy, immune cells invaded the tumors, and the tumors shrank."

Dan Theodorescu, MD, Ph.D., director of Cedars-Sinai Cancer and the PHASE ONE Distinguished Chair, said that the study's findings suggest radiotherapy may positively impact immune response in these tumors.

"This study will guide investigators toward the next generation of clinical trials," Theodorescu said. "The investigators also describe a new framework for mapping the distribution of immune cells within tumors, and that could help us identify new precision medicine approaches for patients with breast and other cancers."

Investigators' next task is to find practical ways to identify these responder groups in a clinical setting via blood samples or other means to better tailor treatments. They will also explore the possibility of combining radiotherapy with other types of immunotherapy prior to surgery as a way to improve patient response for high-risk patients, Shiao said.

More information: Theodorescu et al, Single-cell and spatial profiling identify three response trajectories to pembrolizumab and radiation therapy in triple negative breast cancer, Cancer Cell (2024). DOI: 10.1016/j.ccell.2023.12.012 . www.cell.com/cancer-cell/fullt … 1535-6108(23)00440-3

Provided by Cedars-Sinai Medical Center

Credit: Unsplash/CC0 Public Domain

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  • Int J Surg Case Rep

A case report of locally advanced triple negative breast cancer showing pathological complete response to weekly paclitaxel with bevacizumab treatment following disease progression during anthracycline-based neoadjuvant chemotherapy

Hideo shigematsu.

a Department of Breast Surgery, National Hospital Organization Kure Medical Center and Chugoku Cancer Center, Kure-City, Hiroshima, Japan

Shinji Ozaki

Daisuke yasui, taizo hirata.

b Department of Medical Oncology, National Hospital Organization Kure Medical Center and Chugoku Cancer Center, Kure-City, Hiroshima, Japan

  • • There is no standard therapy for locally advanced TNBC showing disease progression during NAC.
  • • We presented a case of locally advanced TNBC showing pCR to weekly paclitaxel with bevacizumab treatment showing PD during standard NAC.
  • • This report suggests the potential of bevacizumab in response-guided sequential therapy and this finding should be confirmed in clinical trial.

Introduction

Neoadjuvant chemotherapy (NAC) is the standard of care for locally advanced triple negative breast cancer, however, approximately 5% of cases show disease progression during NAC. Although downstaging is essential to create an opportunity for curative surgery and to improve the local control outcome in such a case, no additional line of chemotherapy has been established.

Case presentation

A 60-year-old woman was referred to our hospital for an axillary mass presenting three weeks ago and was diagnosed as having right locally advanced (T2N2M0, stage IIIA) triple negative breast cancer. After two courses of epirubicine and cyclophosphamide as NAC, disease progression was recognized and curative resection was considered impossible due to enlarged axillary lymph nodes showing invasion to surrounding tissue. As second-line chemotherapy, weekly paclitaxel with bevacizumab treatment was initiated and significant shrinkage was immediately obtained. A clinically complete response was diagnosed after four courses of weekly paclitaxel with bevacizumab and she underwent a right breast mastectomy with axillary lymph node dissection without major complications. Histopathological examination of surgical specimens showed no residual invasive or noninvasive disease and she was diagnosed as having a pathological complete response.

Conclusions

Although the addition of bevacizumab to standard adjuvant chemotherapy is not recommended in unselected triple negative breast cancer, the potent effect on tumor shrinkage should be considered in the treatment of locally advanced triple negative breast cancer showing disease progression during standard NAC.

1. Introduction

Neoadjuvant chemotherapy (NAC) has become the standard-of-care for non-metastatic breast cancer with results from randomized trials showing equivalent long-term survival for NAC compared with survival for adjuvant chemotherapy [1] . Anthracycline- and taxane-based chemotherapy are recommended as standard NAC [2] , [3] , [4] among patients with triple-negative breast cancer (TNBC), however, approximately 5% of the cases show disease progression during NAC [5] , [6] , [7] . If patients have inoperable disease, next-line chemotherapy is considered to create the opportunity for curative surgery and local control. The selection of an additional chemotherapy regimen is done at the discretion of physicians because there are no clinical trials that have evaluated the efficacy and safety of treatments in patients who showed disease progression during NAC.

In this case report, we describe a case of locally advanced triple negative breast cancer showing a pathological complete response to weekly paclitaxel with bevacizumab treatment following disease progression during anthracycline-based neoadjuvant chemotherapy. This case report has been reported in line with the SCARE criteria [8] .

2. Case presentation

A 60-year-old post-menopausal woman presented at a local clinic with a right axillary mass that had appeared three weeks previous. Right breast cancer with axillary lymph node metastases was suspected and she was referred to our hospital. Physical examination showed a right breast mass at the C area and fixed and enlarged axillary lymph nodes. In her past history, she underwent total gastrectomy and received adjuvant doxifluridine therapy for gastric cancer 15 years ago with no sign of recurrence. She had no family history of breast or ovarian cancer. An abdominal scar for a gastrectomy and emaciation (BMI = 17.6) was recognized. Laboratory results showed a normal range for the tumor markers. Mammography showed focal asymmetric density with clustered pleomorphic calcification, indicating BI-RAD category 4. Ultrasonography confirmed an irregular mass in the right breast and ipsilateral multiple axillary lymph nodes that were enlarged and fixed to one another. Magnetic resonance imaging (MRI) also showed a right breast mass of 3 cm diameter, and multiple enlarged and fixed axillary lymph nodes. Positron emission tomography computed tomography (PET-CT) showed a right breast mass with SUVmax 19.73 and multiple axillary lymph node swelling with a SUVmax range from 4.74 to 25.2 ( Fig. 1 ). No definitive finding of distant metastases was recognized with these modalities. Histopathological examination of core needle biopsy (CNB) of the right breast tumor showed invasive ductal carcinoma. Immunohistochemical examination and fluorescence in situ hybridization of the tumor cells showed negative results for estrogen receptor, progesterone receptor and HER2, indicating that her breast tumor was a triple negative breast cancer (TNBC) subtype. The nuclear grade 3 was recognized and the Ki67 index was 53.39%. With these findings, she was diagnosed as having right locally advanced triple negative breast cancer.

Fig. 1

Magnetic resonance imaging showed right breast mass with 3 cm diameter in the upper outer portion of right breast and, multiple enlarged and fixed axillary lymph nodes with edematous change of surrounding soft tissue (A, B). Positron emission tomography computed tomography (PET-CT) showed right breast mass with SUVmax 19.73 and multiple axillary lymph node swelling with SUVmax range from 4.74 to 25.2 (C, D).

Because curative surgery is thought to be difficult due to the matted and fixed axillary metastases, NAC was initiated to reduce the tumor burden and to allow for complete resection and local control. Tri-weekly epirubicine 90 mg/m 2 and cyclophosphamide 600 mg/m 2 were initiated. After two courses of chemotherapy, she complained about enlargement of a right breast mass. CT showed progressive disease of a right breast tumor and axillary lymph nodes (25% increment in the sum of breast tumor and axillary lymph node) and her disease was diagnosed as remaining inoperable. Considering the high response rate and the low frequency of disease progression, the addition of bevacizumab or carboplatin to a taxane-based neoadjuvant chemotherapy regimen was suggested. Because increments of hematologic and gastrointestinal toxicities associated with the addition of carboplatin were considered crucial for her condition after total gastrectomy, weekly paclitaxel 90 mg/m 2 with biweekly bevacizumab 10 mg/kg was selected. After initiation of weekly paclitaxel with bevacizumab, there was significant shrinkage of the breast tumor and axillary lymph nodes. Bevacizumab was discontinued at the 4th cycle to reduce the risk of operative complications. After completion of 4 cycles of a weekly paclitaxel with bevacizumab regimen, clinical complete response (cCR) was recognized by CT and MRI findings ( Fig. 2 ). No serious or unknown adverse event occurred during NAC. The weekly paclitaxel with bevacizumab was well tolerated and no dose-reduction or delayed administration was required. She underwent right breast mastectomy and axillary lymph node dissection (level I and level II) as a standard procedure by a doctor in charge. Intraoperative findings showed a remarkable scar in the axillar and no mass was found in breast or axilla. There were no major complications, including bleeding, thrombosis or delay of wound healing, and she left the hospital eight days after the operation. Histopathological examination of surgical specimens showed pathological complete response (pCR) with no residual disease in the breast and dissected axillary nodes ( Fig. 3 ). The patient was satisfied with the tumor shrinkage and complete resection of the disease without any significant complications. Postoperative radiation therapy to her chest wall and regional lymph node was performed as adjuvant therapy, and she was ambulatory followed without any recurrence at a 6-month follow-up.

Fig. 2

Computed tomography before NAC (A, B), after 2 cycles of EC (C, D), and after 4 cycles of weekly paclitaxel with bevacizumab (E, F). After 2 cycles of EC, progressive disease was recognized with 25% increment in the sum of breast tumor and axillary lymph node. Clinical complete response was recognized after completion of 4 cycles of weekly paclitaxel with bevacizumab (E, F). Last computed tomography was performed without contrast media because of patient allergic reaction.

Fig. 3

Histological findings of the right breast (A) and axillary lymph nodes (B) (H&E stain X20). There was scarring with invasion of lymphocytes, histiocyte and multinucleated giant cell. No residual breast cancer cells were recognized showing a pathological complete response (Grade 3).

3. Discussion

Because TNBC have a higher risk of relapse compared with other subtypes and are not sensitive to endocrine or HER2-targeting therapy, adjuvant chemotherapy is recommended for most patients with TNBC. For patients with TNBC, NAC is a reasonable alternative to adjuvant chemotherapy and significantly more patients with TNBC were treated with NAC compared with a luminal type [9] . NAC is administered not only to downstage the tumor for less extensive surgery or for improved cosmetic outcome, but also to permit an early evaluation of chemotherapy, which can facilitate response-guided adjuvant treatment. A recently published phase III trial showed that adjuvant capecitabine therapy improved long-term prognosis among HER2-negative breast cancer patients who had residual invasive disease after standard anthracycline and/or taxane-based NAC [10] ; the rate of disease-free survival was 69.8% in the capecitabine group as compared with 56.1% in the control group, and the overall survival rate was 78.8% versus 70.3% among patients with triple negative disease. With these findings, more patients with TNBC are expected to receive NAC.

Although a large proportion of TNBC shows a response to NAC, more than 5% of cases show progressive disease during standard NAC [5] , [7] . Because the residual tumor burden after NAC is associated with disease recurrence [11] , tumor shrinkage is crucial not only for cosmetic outcome and local control, but also to improve long-term survival in such cases. Although no clinical trials have evaluated the efficacy and safety of an additional-line of chemotherapy in patients who showed disease progression during NAC, it is reasonable to select regimens that show a substantial antitumor effect with a high response rate and low frequency of progressive disease. In patients with TNBC, the addition of bevacizumab or carboplatin to anthracycline- and taxane-based chemotherapy can be the most potent regimen in regards to achieving tumor shrinkage [5] , [12] , [13] , [14] . Large randomized clinical trials have demonstrated a significantly higher response rate and pCR rates with the addition of bevacizumab or carboplatin to anthracycline- and taxane-based neoadjuvant NAC. In CALGB 40603, adding either agent significantly increased the rate of the pCR in breast; and 60% of the carboplatin group achieved pCR breast compared with 46% in the control group, and 59% of the bevacizumab group compared with 48% in the control group. In addition, 6 of 108 patients who started standard NAC stopped treatment for progressive disease, and only 1 of 113 patients assigned to the bevacizumab group showed disease progression during NAC [5] . Although the addition of these agents to NAC is not recommended in general due to a lack of long-term survival benefit and an increased rate of adverse events, the potent effect on tumor shrinkage should be considered in selected situations where disease progression is recognized during standard NAC.

In this case report, we administered weekly paclitaxel with bevacizumab to the patient. The weekly paclitaxel with biweekly bevacizumab was well tolerated and no dose reduction or delay of schedule was recognized despite of the patient’s status of emaciation after total gastrectomy. After initiation of weekly paclitaxel with bevacizumab, immediate tumor shrinkage and relief of tenderness of her breast was obtained, and cCR was achieved after 4 cycle treatment. She underwent a standard mastectomy and axillary lymph node dissection with no major surgical and post-operative complications and pCR was recognized at both breast and lymph nodes. She was satisfied with the course of treatment and was ambulatory without any complications.

Of course, the significant effect of weekly paclitaxel with bevacizumab in this case could be by chance, however, the response-guided sequential addition of bevacizumab has shown advantages in clinical trial. In an AVATAXHER trial, patients with HER2-positive breast cancer that did not show a metabolic response after two cycles of neoadjuvant docetaxel and trastuzumab treatment were randomly assigned to receive four cycles of docetaxel and trastuzumab plus bevacizumab or continued on docetaxel plus trastuzumab alone [15] . Patients assigned to the addition of bevacizumab showed a significantly higher pCR rate compared with those assigned to continue the same regimen; pCR was noted at a rate of 43.8% in the bevacizumab group and 24.0% in the control group. This finding of response-guided sequential therapy suggests the potential of bevacizumab in the treatment of breast cancer, and this hypothesis should be confirmed in further clinical trials targeting patients with TNBC showing disease progression during standard NAC.

4. Conclusion

In this case report, the incorporation of bevacizumab showed significant tumor shrinkage of TNBC showing disease progression during standard NAC, and facilitated complete resection with less extensive surgery. Although the addition of bevacizumab to standard NAC is not recommended in the treatment of breast cancer, this case report showed the potential of bevacizumab in response-guided sequential therapy of TNBC. The incorporation of bevacizumab to chemotherapy should be evaluated in further clinical trials targeting patients with TNBC showing disease progression during standard NAC.

Conflicts of interest

The authors declare that they have no competing interests.

This study did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Ethical approval

This case report was approved by the Kure Medical Center review board (28–79).

Written informed consent was obtained from the patient for publication of this case report and accompanying images.

Authors’ contribution

HS designed the study, conducted the investigation, and wrote the manuscript. SO performed the surgery and supervised the study. DY supervised the study. TH administered the neoadjuvant chemotherapy and supervised the work. All of the authors contributed to the final version of the manuscript. All authors read and approved the final manuscript.

Hideo Shigematsu,

Department of Breast Surgery, National Hospital Organization Kure Medical Center and Chugoku Cancer Center, Kure-City, Hiroshima, Japan.

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  • Published: 20 February 2024

Neutrophil extracellular trap-associated risk index for predicting outcomes and response to Wnt signaling inhibitors in triple-negative breast cancer

  • Zhidong Huang 1 , 2 , 3   na1 ,
  • Jinhui Wang 1 , 2 , 3   na1 ,
  • Bo Sun 1 , 2 , 3   na1 ,
  • Mengyang Qi 1 , 2 , 3 ,
  • Shuang Gao 1 , 2 , 3 &
  • Hong Liu 1 , 2 , 3  

Scientific Reports volume  14 , Article number:  4232 ( 2024 ) Cite this article

Metrics details

  • Cancer therapy
  • Computational biology and bioinformatics
  • Tumour biomarkers

Triple-negative breast cancer (TNBC) is a type of breast cancer with poor prognosis, which is prone to distant metastasis and therapy resistance. The presence of neutrophil extracellular traps (NETs) contributes to the progression of breast cancer and is an efficient predictor of TNBC. We obtained the bulk and single-cell RNA sequencing data from public databases. Firstly, we identified five NET-related genes and constructed NET-related subgroups. Then, we constructed a risk index with three pivotal genes based on the differentially expressed genes between subgroups. Patients in the high-risk group had worse prognosis, clinicopathological features, and therapy response than low-risk group. Functional enrichment analysis revealed that the low-risk group was enriched in Wnt signaling pathway, and surprisingly, the drug sensitivity prediction showed that Wnt signaling pathway inhibitors had higher drug sensitivity in the low-risk group. Finally, verification experiments in vitro based on MDA-MB-231 and BT-549 cells showed that tumor cells with low-risk scores had less migration, invasion, and proliferative abilities and high drug sensitivity to Wnt signaling pathway inhibitors. In this study, multi-omics analysis revealed that genes associated with NETs may influence the occurrence, progression, and treatment of TNBC. Moreover, the bioinformatics analysis and cell experiments demonstrated that the risk index could predict the population of TNBC likely to benefit from treatment with Wnt signaling pathway inhibitors.

Introduction

Female breast cancer (BC) accounted for 24.2% of all incident cancer cases (2.1 million), based on the global cancer statistics from 2020 1 . Triple-negative breast cancer (TNBC), which is negative for the expression of estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2, accounts for about 15–20% of all breast cancers 2 . Compared with Luminal and human epidermal growth factor receptor 2 enriched subtypes, TNBC is subject to poor prognosis, lack of therapeutic targets, high rate of recurrence and metastasis, and chemotherapy resistance 3 . With progress in high-throughput sequencing, single-cell sequencing, spatial transcriptome sequencing, and computational biology technology, several novel potential biomarkers at the genetic and epigenetic levels have been discovered from tissues or peripheral blood samples 4 , 5 , 6 , providing a basis for new approaches for the diagnosis and treatment of BC.

As the most abundant type of granulocytes or leukocytes, neutrophils are indispensable effector cells in the process of innate immunity, and their effects are primarily exerted through phagocytosis, granulation, and release of neutrophil extracellular traps (NETs) 7 . Neutrophils can support tumor proliferation and metastasis by adjusting the death and migration of tumor cells, immunoreaction, and angiogenesis through NETosis, that is, the NET formation process of neutrophils 8 . Active neutrophils release proteins and DNA–histone complexes that make up NETs 9 . Furthermore, NETs promote tumor progression and metastasis. For example, two types of NET-related proteases, neutrophil elastase and matrix metalloproteinase 9 can cleave laminin, an integrin α3β1 activation epitope. This leads to FAK/ERK/MLCK/YAP signaling in tumor cells, reactivating dormant cancer cells 10 . Yang et al. found that the transmembrane protein CCDC25 of BC cells recognizes DNA from extracellular NET components to activate the ILK–β-parvin pathway to improve the motor capacity of cancer cells 11 . Patients with BC and colon cancer who develop liver metastases have high levels of NET-related DNA, which acts as a chemotactic factor to promote the liver metastasis of BC. In the early stages of BC, serum NETs are crucial for predicting liver metastases.

Tumor in an individual develops and progresses through a series of steps, ranging from tumorigenesis, metastasis, and treatment resistance. Average gene mutation frequency and gene expression is reflected by bulk RNA sequencing, which assists in better understanding of the molecular characteristics of each step of tumorigenesis by identifying sensitive biomarkers, mutations, and gene expression profiles 5 , 12 , 13 . Compared with bulk RNA sequencing, single-cell sequencing is considerably better for probing cellular and microenvironment heterogeneity at single-cell resolution. Thus, integrating clinicopathological information with single-cell sequencing data can provide more accurate biomarkers for the early diagnosis and cure of patients and explore treatment-related types or states of cancer cells) 14 , 15 , 16 .

Purpose and significance of the present research was to explore the features and clinical worth of NET-related genes using bioinformatics analyses and in vitro cell line experiments and provide new diagnostic markers and cure strategies, as well as predicting their survival chances. To achieve this, multi-omics data (e.g., interactome, transcriptome, proteome, and genome) were combined, and the molecular characteristics and prognostic role of NET-related genes were analyzed using bulk RNA-seq and single-cell sequencing data. Additionally, a new NET-related subtype of TNBC and a risk index linked to NETs were identified for predicting prognosis and informing TNBC treatment.

Landscape of copy number variation and gene mutation in NET-related genes

The gain of copy number was greater than the loss of copy number in most NET-related genes. ACTG1, FCGR2B, KCNN3, MNDA, NLRP3, S100A12, S100A8, and S100A9 were more likely to show copy number gain than other genes, whereas AZU1, MFN2, LCP1, PADI4, ELANE, and PRTN3 were more likely to show copy number loss (Fig. S1 ). With respect to the mutation status of the NET-related genes, up to 38.81% of the samples with TNBC had NET-related gene mutations. PIK3CA had the highest gene mutation frequency of 11%. The remaining 135 genes, with a mutation rate of < 4%, were relatively conserved (Fig.  1 A).

figure 1

( A ) Waterfall diagram showing the frequency and type of mutations in the NET-related genes using the R package “maftools”. ( B ) Differential expression analysis of NET-related genes in TNBC and non-TNBC tissues using Wilcoxon rank-sum tests. ( C ) Prognostic network diagram showing the co-expression relationships and the prognosis using univariate Cox regression of differentially expressed NET-related genes. ( D ) Venn diagram showing the genes in common between univariate Cox analysis and Kaplan–Meier (K–M) analysis. ( E ) Heatmap depicts consensus clustering solution (k = 2) for NET-related genes using the consensus clustering algorithm. ( F ) Principal component analysis (PCA) was performed based on the gene matrices of NET-related subtype. ( G ) K–M survival analysis comparing clusters A and B. ( H ) Volcano map shows NET-DEGs between cluster B and A.

Establishment of NET-related subtypes

A total of 27 NET-related genes were aberrantly expressed in TNBC samples based on the TCGA-TNBC cohort (Fig.  1 B), which were incorporated into subsequent analyses of prognostic value. In the K–M survival analysis conducted on the TCGA-TNBC cohort, 18 NET-related genes demonstrated relevance to overall survival (OS) (Fig. S2 ). In the univariate Cox regression analysis, CLEC4E, CLEC7A, and CCL4 expressions were favorable factors (HR < 1), whereas positive CTSG and MAPK3 expressions were risk factors for poor prognosis (HR > 1) (Fig.  1 C). The results of the K–M survival analysis and univariate Cox regression analysis were intersected to identify five prognostically related genes (Fig.  1 D). Based on the five prognostic genes, TNBC patients' segmentation was based on the analysis of unsupervised consensus clustering, dividing into A and B subtypes (Fig.  1 E).

Functional enrichment and immune microenvironment analysis revealed the characteristics of NET-related subtypes

The PCA showed that the samples with TNBC are easy to tell apart based on the new NET-related subtype, which verified the effect of NET-related subtypes (Fig.  1 F). K–M survival curves for clusters A and B showed that cluster A was associated with better OS (Fig.  1 G). In addition, the functional enrichment analysis using GSVA indicated that immune-relevant pathways (e.g., Cytokine–cytokine receptor interactions signaling pathway, Antigen processing and presentation signaling pathway, Primary immunodeficiency, Nature killer cell-mediated cytotoxicity, T cell receptor signaling pathway, B cell receptor signaling pathway, etc.) and tumor-related pathways, such as JAK/STAT signaling pathway concentrated in cluster A (Fig. S3A ). As shown in Fig. S3B , the infiltration degree of immune cell in TNBC was obviously different between A and B subtype, except for CD56 dim natural killer cells, eosinophils, mast cells, monocyte, and plasmacytoid dendritic cell. In general, the A subtype has higher infiltration degree.

Comparing gene expression between clusters A and B, 430 DEGs were identified (Fig.  1 H). Functional enrichment analyses indicated that these genes were remarkably enriched in GO terms including leukocyte-mediated immunity, positive regulation of cell activation, external side of plasma membrane, and antigen-binding. The KEGG analysis showed that NET-DEGs were significantly enriched in immune-associated pathways (cytokine–cytokine receptor interaction, cell-adhesion molecules, chemokine signaling, Th17 cell differentiation, etc.) (Fig. S3C ).

Landscape of hub DEGs between two subtypes in single-cell expression profile

Based on the PPI network and the degree of expression of each protein, 15 top hub DEGs were identified (Fig.  2 A). Based on the scRNA-seq dataset GSE161529, 35,585 cells from four primary TNBC samples were obtained for subsequent analysis. After applying the dimension reduction method of PCA, 13 clusters were obtained. Seventeen cell subsets were obtained and visualized using tSNE analysis (Fig.  2 B). Figure  2 C shows the distribution of the 15 hub DEGs in single cells. Intercellular communication analysis to predict gene interactions between different cell types (Fig.  2 D) showed that fibroblasts had the highest number of communications with other cell types in TNBC tissues. Figure  2 E shows the communication strength among all cell types in TNBC tissues. Epithelial cells showed stronger communication with fibroblasts, monocytes, T cells, and B cells. The hub DEGs were involved in cell–cell communication between monocytes and fibroblasts, between monocytes and tissue stem cells, and among monocytes in the GALECTIN signaling pathway which was related to tumor immune evasion (Fig.  2 F).

figure 2

Identification and of hub NET-DEGs and the analysis of scRNA-seq data (GSE161529) ( A ) The co-expression network based on the top 15 hub NET-DEGs using the STRING online database. ( B ) tSNE plot of the unsupervised cluster analysis labeled by cell types. ( C ) The expression of hub NET-DEGs in single-cell level. ( D ) The number of cell–cell interactions between different cells in TNBC. ( E ) The cell–cell interaction strength between different cells in TNBC. ( F ) Calectin signaling pathway network in cell–cell communications.

Construction and validation of the risk index

A total of 62 prognostic NET-DEGs were screened via univariate Cox regression analysis (Table S3 ). After using TCGA-TNBC as the training cohort and GEO-TNBC as the testing cohort, we established a risk index of three genes through LASSO regression analysis (Fig.  3 A). As shown in the Sankey plot, the number of death events in the high-risk group was higher than that in the low-risk group (Fig.  3 B). The risk score plot, showing the relevance between the risk score and outcomes. The number of death events increased with the risk score. The heat map shows the differences in the expression of risk index-related genes between the distinct risk groups. The over-expressed gene in the high-risk group was REEP6, whereas those in low-risk group were GBP1P1, and MOXD1 (Fig. S4A,B ). The time-dependent analysis of ROC and K–M survival curves suggested that the risk index had a high predictive accuracy. Consistency in results was observed across both the training and testing cohorts (Fig.  3 C,D).

figure 3

Construction of risk index and nomogram. ( A ) Partial likelihood deviance for least absolute shrinkage and selection operator (LASSO) coefficient profiles. ( B ) Sankey diagram showing the process for building the risk index and there was a statistically significant difference in death events between various risk group. ( C ) and ( D ) The time-dependent analysis of ROC and K–M survival curves were used to assess predictive accuracy of risk index and compare the difference of survival outcome between various risk group in the training cohort (TCGA-TNBC cohort) and testing cohort (GEO-TNBC cohort). ( E ) A nomogram constructed on the basis of age, T stage, N stage, M stage, and risk score generated using the R package “rms.” ( F ) The time-dependent analysis of ROC was used to assess the time-dependent accuracy of the nomogram.

To better combine the risk index with clinical application we developed a nomogram based on the patient’s age, risk score, T stage, N stage, and M stage which was used to more intuitively predict the OS probability at 1, 3, and 5 years (Fig.  3 E). The time-dependent accuracy of the nomogram was assessed by ROC curves (Fig.  3 F).

Clinicopathological, immune and gene mutational features of different risk groups

Apart from examining the overall survival of patients, previous studies have reported an association between NETs and the recurrence and metastasis of tumors. The K–M survival analysis revealed that higher-risk patients in the TCGA-TNBC cohort exhibited a shorter Disease-Free Interval (DFI) (Fig. S5A ). Additionally, utilizing the GSE58812 dataset, we also observed that patients in the high-risk group had a shorter Metastasis-Free Survival (MFS) (Fig. S5B ), which indicated that high-risk patients experience more recurrence and metastasis compared to the low-risk group.

Moreover, we analyzed the differences in clinicopathological characteristics and therapy responses of patients in various risk groups. In TNBC patients treated with radiotherapy, patients in the low-risk group had better therapeutic reaction (Figs. 4 A, S5C ). For chemotherapy drugs, the IC50 values of commonly used chemotherapy drugs (Cisplatin, Gemcitabine, Olaparib, Talazoparib and Vincristine) in breast cancer patients within the high-risk group were higher than those in the low-risk group (Fig. S5D ). Nevertheless, patients in the high-risk group tended to show higher pathological staging, poorer survival status, more positive lymph nodes, and higher pathological N stage (Fig.  4 B).

figure 4

( A ) The efficacy of radiotherapy was different in various risk groups. ( B ) The clinicopathological information and outcomes of two risk groups was compared. ( C ) The degree of immune cell infiltration of various risk groups was analyzed and compared. ( D ) “ESTIMATE” algorithm was applied to estimate the tumor stromal, immune, and estimate score of patients in disparate risk groups. ( E ) The comparison of two risk groups of TMB using Wilcoxon rank-sum tests. ( F ) Waterfall graph showing the top 20 genes in mutation frequency in disparate risk groups using the R package “maftools”.

Considering that TNBC is the most immunogenic type of BC, we analyzed the role of risk scores in the tumor microenvironment. According to the CIBERSORT algorithm, we calculated the percentage abundance of 22 types of immune cells per sample to assess the relevance between the degrees of infiltration of immune cells in tumors and risk index. The results of the bar plots showed that the low-risk group had higher levels of CD4 + T cells, M1 macrophages, and mast cells, which have a tumor-suppressive effect, while the high-risk group had higher levels of M2 macrophages, which promote tumor growth (Fig.  4 C). Furthermore, correlation between tumor microenvironment and risk scores of the various risk groups differed in the immune and estimate scores (Fig.  4 D).

With respect to the correlation between the risk index and TMB, the TMB of the low-risk group was higher than high-risk group (Fig.  4 E). Our findings are consistent with previous literature reporting that the higher TMB, the better OS and therapy response in TNBC. Meanwhile, TP53, PIK3CA and TTN were the top 3 frequently mutated gene in both high- and low-risk groups, and PIK3CA and TTN were more likely to be altered in the high-risk group than in low-risk group (Fig.  4 F).

Low-risk group exhibited increased drug sensitivity to Wnt signaling pathway inhibitors

TNBC often has a poor prognosis because of the lack of corresponding therapeutic targets, which encouraged us to explore potential drug targets. We carried out the KEGG functional enrichment analysis. The results indicated that the high-risk group enriched in cardiac muscle contraction, drug metabolism by cytochrome p450, metabolism of xenobiotics by cytochrome p450, steroid hormone biosynthesis, and tyrosine metabolism. Also, the low-risk group was related to allograft rejection, autoimmune thyroid disease, JAK-STAT signaling pathway, Type I diabetes mellitus, and Wnt signaling pathway (Fig.  5 A). It was worth noting that TNBC patients with lower risk score showed apparently higher drug sensitivity to three Wnt signaling pathway inhibitors (Wnt-C59, IWP-2, and XVA-939) (Fig.  5 B). Apparently, the finding provided clues for the significance of the risk index in TNBC patients.

figure 5

( A ) The KEGG enrichment analysis was used to explore the potential biological functions of various groups. ( B ) Prediction and comparison of drug sensitivity to Wnt signaling pathway in various risk groups.

TNBC cell lines with low-risk score had low malignancy and high sensitivity to Wnt signaling pathways inhibitors

To further validate our findings, we performed in vitro cell experiments. By the application of the CCLE database, risk scores were calculated for various TNBC cell lines. Figure  6 A shows that MDA-MB-231 was the cell line with the highest risk score, while BT-549 had the lowest risk score. To validate previous studies, we performed migration, invasion, wound healing, and colony formation assays. We found that MDA-MB-231 had higher invasion, migration, and proliferation activities than BT-549 (Fig.  6 B–D), consistent with the conclusion of our previous study. In addition, to verify the results of drug sensitivity prediction, we selected the Wnt signaling pathway inhibitor XVA939 with the most significant difference of IC50 between high and low risk for drug sensitivity testing. Dose‐response growth curve of XVA-939 showed that BT-549 had a higher sensitivity to XVA-939 than MDA-MB-231(Fig.  6 E). The above results suggest that risk index may provide prognosis prediction and personalized treatment guidance for patients with TNBC.

figure 6

( A ) Risk score for each TNBC cell lines calculated from the CCLE database. ( B – C ) The wound healing, migration, and invasion assays was performed to compare the invasion and migration ability between MDA-MB-231 and BT-549. ( D ) Colony formation assay was carried out to explore the cell proliferation ability of MDA-MB-231 and BT-549. ( E ) Cytotoxicity assay to compare the drug sensitivity of MDA-MB-231 and BT-549 to different concentrations of XVA-939.

TNBC is an aggressive subtype with significant heterogeneity and frequently develops resistance to treatment 17 . As per the current clinical guidelines, surgical resection, chemotherapy, and radiotherapy are the mainstay curative treatment options for TNBC patients 18 , 19 . Therefore, patients with TNBC generally have a poor prognosis, and there is an urgent need to explore the pathogenesis of TNBC further to improve clinical diagnosis and treatment. However, there are a few reports about the characteristics and the impact of NETs on patient survival in TNBC. The current study explored the characteristic of NET-related genes on the basis of bulk RNA-seq and scRNA-seq data, and established NET-related subtypes and a risk index that can be applied to clinical practice as a tool for prognosis and radiotherapy response prediction of TNBC patients. Further, it may improve the prognosis in TNBC patients by screening those who may benefit from treatment of Wnt signaling pathway inhibitors.

NETs are important components of the antimicrobial arms of neutrophils. Given the correct stimulus, neutrophils can extrude their nuclear DNA and reticular projects into the extracellular environment. Electron microscopy has shown that these reticuloDNA projections can be modified by a number of granular proteins, including NE, MPO, calguard, cathepsin G, proteinase 3, matrix metalloproteinase 9, and bactericidal/permeability-increasing protein 20 , 21 . During cancer growth, metastasis, and thrombosis, the excessive production of NETs and/or inadequate clearance may represent critical events. Therefore, therapeutic strategies that decrease abnormal NET production or facilitate NET degradation have potential clinical applications 22 . Several drugs can target NETs, and many are in development 23 , 24 , 25 . However, the formation and function of NETs in cancer tissue are yet to be fully elucidated. The characteristics of NET-related genes in tumor tissues need to be further analyzed to develop additional treatment modalities for TNBC.

NETs play an indispensable role in tumorigenesis and drug resistance. In pancreatic ductal carcinoma, interleukin (IL)-17 is highly expressed, and its recruitment of neutrophils triggers NETs to promote tumor multidrug resistance 26 . In high-grade gliomas, NETs induced by tumor-infiltrating neutrophils have also been shown to serve as oncogenic markers. In glioblastoma, NETs stimulate the NF-κB signaling pathway, thereby accelerating the secretion of IL-8 and further recruiting neutrophils. Tumor-infiltrating neutrophils mediate the formation of NETs through the PI3K/AKT/ROS axis, and through positive feedback, excessive NETs, in turn, promote the proliferation, migration, and invasion of cancer cells 27 . Our study showed that NET-related genes have genetic mutations and CNVs and were abnormally expressed in TNBC, indicating that NETs also play an important role in the normal mammary epithelial cell to proliferate abnormally and become cancerous. Besides, a novel NET-related subtype was identified with the help of TNBC-specific NET-related genes. The prognosis, functional enrichment analysis, and degree of tumor immune cell infiltration differed according in the two NET-related subtypes. Cluster A, associated with a better prognosis, was active in immune-related pathways and had a higher degree of immune cell infiltration. A previous report showed that a high extent of tumor cell infiltration is related to the positive response to adjuvant and neoadjuvant therapy in TNBC 28 . In other words, NET-related subtypes significantly distinguished TNBC patients with different survival outcomes, treatment responses, and immune microenvironment.

To further explore the value of NETs in the prognosis prediction and treatment of TNBC patients, the current study identified NET-DEGs between A and B subtype as potential biomarkers and constructed a risk index. The functional enrichment analyses (the GO and KEGG enrichment) showed that these potential biomarkers were relevant to immune-associated functions and signaling pathways, indicating that NETs play a key role in immunity, consistent with the results of the above studies. The communication between tumor cells and tumor microenvironment affects cellular biological processes through unequivocal signaling molecules, including ligands, receptors, metabolites, ions, and structural or secreted proteins. Inferring cell–cell interactions by integrating scRNA-seq data and gene expression with ligand-receptor information provides a new method to identify the underlying mechanisms of tumor progression 29 , 30 , 31 . The current study predicted the intercellular communication of hub DEGs identified through PPI network analysis based on scRNA data set and found that hub DEGs were mostly expressed in TNBC epithelial cells, T cells, and monocyte and PTPRC primarily played a vital role in TNBC via the GALECTIN signaling network, which was involved in the process of tumor immune evasion 32 . This finding provides a novel basis for further research on TNBC tumorigenesis.

Based on these potential biomarkers, a risk index and nomogram were established. In this study, the risk index exhibited reliable and sensitive performance in predicting the effectiveness of radiotherapy and chemotherapy in TNBC patients. These findings suggest a certain correlation between NETs and the effectiveness of chemo- and radiotherapy. Furthermore, previous studies have found that NETs could induce distant metastasis or recurrence of tumors by awakening dormant tumor cells and damaging endothelial cells to promote tumor cell infiltration 33 , 34 . In our research, survival analysis based on disease-free interval (DFI) showed a poorer prognosis for patients in the high-risk group compared to the low-risk group. This suggested that patients in the high-risk group are more susceptible to distant tumor metastasis or recurrence events.

To verify the results of our analysis, we further conducted out in vitro cell experiments. First, we calculated the risk score of 7 TNBC cell lines through the CCLE database, and MDA-MB-231 and BT549 with the highest and lowest risk scores were used in migration, invasion, wound healing, and colony formation assays. The experimental results showed that the MDA-MB-231 had higher level of malignancy, which was consistent with the results of bioinformatics analyses. A significant difference was found between high- and low-risk groups in their immune microenvironment and signature of the genome. In tumor immune infiltration analysis, we could find that immune cells (CD4 + T cell and M1 macrophage) with higher levels of infiltration in the low-risk group which play a role in consistent tumor growth in the tumor microenvironment 35 , 36 . TMB, which is consistent with PD-L1 expression, is a powerful prognostic biomarker for immune checkpoint blockade selection in different cancers 37 . BC with high TMB is more likely to benefit from PD-1 inhibitors 38 . In the present study, the low-risk group with better outcomes and therapy responses had more samples with gene mutations and higher TMB than the high-risk group, consistent with a previous study 39 .

Compared with other BC molecular subtypes, the treatment options for TNBC are few 40 , so it is particularly important to find new therapeutic drug targets for TNBC patients. According to the functional enrichment analysis of the high- and low-risk group, we found that TNBC patients in the low-risk group were significantly enriched in the Wnt and JAK/STAT signaling pathway. Surprisingly, patients in the low-risk group were more sensitive to treatment by Wnt signaling pathway inhibitors. Furthermore, the dose‐response growth curve of CCK-8 assay also validates the result that the cell viability of BT-549 with lower risk scores than those of MDA-MB-231 showed a significant decrease after adding XVA-939.

Despite the advantages of the current study, there are some limitations. First, the clinical application value of risk index was only validated in vitro; however, in vivo experiments must be carried out. Moreover, according to the above analyses, our conclusions provided a novel perspective for exploring the relationship between NET and TNBC, which should be proved by further experiments.

Conclusions

NET plays a prominent role in TNBC. NET-related subtype based on NET-related genes clearly distinguishes patients with different characteristics. The risk index based on the NET-related potential biomarkers could provide a tool for predicting long-term prognosis and therapy responses in patients with TNBC; and, even more, identify potential beneficiaries of Wnt signaling pathway inhibitors. Furthermore, in vitro cell experiments also confirmed our findings.

Materials and methods

Data acquisition and processing.

The baseline data of BC patients participating in the study has been listed in Table S1 . The copy number, somatic mutation, bulk RNA sequencing (RNA-seq) data, and clinicopathological information of BC were gained from The Cancer Genome Atlas (TCGA) database ( https://www.cancer.gov/ccg/research/genome-sequencing/tcga ). The TCGA RNA-seq data were transformed into TPM format and designated as the TCGA-TNBC cohort for subsequent analysis. The microarray data of TNBC downloaded from Gene expression Omnibus ( https://www.ncbi.nlm.nih.gov/geo/index.cgi ) were GSE58812 and GSE135565. The microarray data were normalized using the "normalizeBetweenArrays" function in the R software. GSE58812 and GSE135565 were combined to form the GEO-TNBC cohort, and the “sva” R package 41 exclusively addressed batch effects in these two GEO datasets. Moreover, in the process of constructing risk index, the data from TCGA-TNBC cohort were used for training cohort, meanwhile, the data from GEO-TNBC were utilized for testing cohort. Single-cell RNA-seq (scRNA-seq) data were downloaded from GSE161529 for the analysis of hub genes. A total of 136 neutrophil-related gene sets and NETosis-related gene sets, as the NET-related gene set, were obtained from previous study 42 , 43 , 44 , 45 (Table S2 ).

Somatic mutation and copy number variations (CNV) analysis

Waterfall plots, using the R package “maftools” 46 were constructed to characterize the NET-related genes and tumor mutational burden (TMB). A comparison between diverse groups was carried out using the R package "ggpubr,"( https://cran.r-project.org/web/packages/ggpubr/index.html ) and the correlation between risk index and TMB was visualized using boxplots and correlation plots. Besides, the frequency of CNV in NET-related genes was analyzed on the basis of the copy number data.

Screening of TNBC-specific NET-related genes

The identification of TNBC-specific NET-related genes was based on differential expression and survival analysis, including univariate Cox regression and Kaplan–Meier (K–M) analyses. The R package "limma" 47 was used to identify differentially expressed genes (DEGs) between TNBC and non-TNBC subtypes. The R packages “survival” ( https://cran.r-project.org/web/packages/survival/index.html ) was applied to survival analyses based on the above genes and K–M survival curves for significant DEGs (i.e., those with p-values < 0.05) were plotted. The optimal threshold for defining high and low expression of genes in the K–M analysis was determined using the "survminer" R package ( https://CRAN.R-project.org/package=survminer ) with the goal of including as many valuable NET-related genes as possible for subsequent analysis. R packages “ggplot2” ( https://ggplot2.tidyverse.org ) and “VennDiagram” ( https://CRAN.R-project.org/package=VennDiagram ) were used for plotting Venn diagrams. The prognostic and differential NET-related genes were obtained for subsequent analyses.

Development of NET-related subtypes

R package “ConsensuClusterPlus” 48 with parameters: reps = 50, pItem = 0.8, pFeature = 1, clusterAlg = “km,” distance = “euclidean,” and seed = 123,456 was used to separate patients into various subtypes in the integrated cohort. The “prcomp” function in the R software, and the R package “ggplot2” was used to simplify high-dimensional data for better visualization and analysis.

Functional enrichment analysis

We carried out GSVA enrichment analysis visualized as a heat map constructed in the R package “GSVA” 49 . The subgroups identified by the R package "limma" were considered significant (adjusted p-value < 0.05). An analysis of GO functional enrichment and GO classification annotation of DEGs was performed using Gene Ontology (GO). The GO database ( https://www.geneontology.org/ ) was used to determine the biological functions of the enriched GO terms. R package “clusterProfiler” 50 was applied for the Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathways and the GSEA enrichment analyses.

Tumor immune cell infiltration: differential analyses

Scores from the single-sample gene set enrichment analysis were calculated using the “gsva” function in the R package “GSVA.” CIBERSORT algorithm 51 was devoted to estimate the degree of immune infiltration in each sample. Correlation analysis between the risk signature and immune cell infiltration was performed using the R function “vioplot” ( https://github.com/TomKellyGenetics/vioplot ).

Identification of hub NET-related DEGs

The Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) online database ( https://string-db.org/ ) was used to construct an interaction network between proteins, and the Cytoscape (version 3.8.1) software 52 was used to visualize and analyze this result. Protein–protein interaction (PPI) networks were presented as figures, with nodes illustrating proteins and edges depicting associated interactions. The CytoHubba plugin 53 in Cytoscape was used to identify core genes.

Single-cell RNA sequencing data analysis

The R package “Seurat” ( https://cran.r-project.org/web/packages/Seurat/index.html ) was implemented to analyze scRNA-seq data. A Seurat object was created for the combined samples using the CreateSeuratObject function with parameters: min.cells = 3, min.features = 50. The percentage of mitochondrial reads was determined with PercentageFeatureSet function with pattern = “ˆmt-” parameter. Cells were filtered by nFeature (percent-mt (< 5) and & nFeature_RNA (> 50). Single-cell counts data were log-transformed using the NormalizeData function, with a scale_factor of 10,000. The first 20 principal components were clustered, and clusters with a resolution of 1 were identified. The t-stochastic neighboring embedding method (tSNE) was utilized to achieve the purpose of dimensionality reduction with the help of Seurat. The Seurat function “FindMarkers” and the Wilcox test were used to analyze the differential gene expression between clusters. According to DEGs between the clusters, cell types were confirmed. The Seurat toolkit “VlnPlot,” “DoHeatmap,” and “FeaturePlot” functions were used to generate violin, heat, and individual tSNE plots, respectively, for the given gene. After input of quality-controlled and normalized expression matrix, inference and analysis of cell–cell communication was performed using the R package “CellChat” 30 .

The risk index, which could predict the outcome and cure responds of patients, was identified using machine learning algorithms (the adaptive least absolute shrinkage and selection operator (LASSO) based on the NET-related DEG (NET-DEG) expression matrix of TCGA-TNBC data (training cohort). The risk score for each patient was calculated using the following formula:

The grouping of patients based on the median of the risk score (high- and low-risk groups). Parameters were tuned using the training cohort, and the validation cohort utilized the training cohort threshold to classify into high and low-risk groups. Between group differences in OS, gene expression, and outcomes were analyzed using K–M survival analysis, heat maps, and scatter plots, respectively. Time-dependent receiver operating characteristic (ROC) curves were used to estimate the predictive efficacy of the risk index and nomogram and drawn using the calculation procedure. Nomograms of the multivariable models were generated using the R package “rms” ( https://CRAN.R-project.org/package=rms ).

Drug sensitivity analysis

Based on the Genomics of Drug Sensitivity in Cancer v2 (GDSC2) database ( https://www.cancerrxgene.org/ ), we evaluated the half-maximal inhibitory concentration (IC50) of various drugs in the different risk score patients, by using the “oncopredict” algorithm 54 .

TNBC cell lines and culture

MDA-MB-231 and BT-549 cells, were purchased from Procell (Wuhan, China). MDA-MB-231 was cultured in DMEM high glucose medium (Gibco, USA) supplemented with 10% fetal bovine serum (FBS) (Gibco), and 1% penicillin and streptomycin (P/S) at 37 °C in a moist incubator under 5% CO 2 . BT-549 was cultured in RPMI-1640 medium (Gibco) supplemented with 0.023 U/ml insulin, 10% FBS, and 1% P/S in a moist incubator at 37 °C under 5% CO 2 .

Migration, invasion, and wound healing assay

Migration and invasion assays were performed in 24-well transwell chambers. TNBC cells were seeded into the upper chamber (8 mm pore size) with medium (DMEM high glucose or RPMI-1640), and the bottom chamber was filled with DMEM high glucose or RPMI-1640 containing 20% FBS. After 72 h, the cells on the lower surface of the filter were fixed and imaged, and five different fields of view was quantified using Image J software to get an average sum of cells. For the wound healing assay, cells were seeded into six-well plates at 5 × 10 5 cells/well. Cell monolayer was scratched using a 200-μl pipette tip and washed with phosphate buffer solution to remove cell debris. Then the cells were cultured in serum-free DMEM high glucose or RPMI-1640 medium and each wound was imaged at 0 h, 24 h and 48 h, respectively after injury.

Colony formation assay

Cells were planted and cultured in six-well plates at 1000cells/well, three replicate wells per experiment. After two weeks, the colonies were washed, fixed, stained, and recorded. The results were analyzed using Image J and Prism software.

Cytotoxicity of Wnt signaling pathways inhibitor XVA-939

The number of cells was determined using the cell counting kit-8 (CCK-8, Solarbio, China) assay. MDA-MB-231 and BT-549 cells were resuspended in serum-free DMEM and RPMI-1640, respectively. The cell suspension (100 µL) was added to each well of the 96-well plate at a density of 8 × 10 3 cells/well followed by 24-h incubation at 5% CO 2 and 37 °C. 100 µL of the medium supplemented with 0, 0.01, 0.1, 0.5, 1, 2, 5, 10, and 20 µM of XVA-939 (Solarbio, China), respectively was added to each well and incubated for 24-h at 5% CO 2 and 37 °C. Solution was removed from each well after incubation and the colorimetric solution (10 µL/well) was added into each well. After 2-h incubation, absorbance at 450 nm was evaluated.

Statistical analysis

The differences between the two subtypes or the risk groups were evaluated using Wilcoxon rank-sum tests. The Kruskal–Wallis test and one-way analysis of variance were carried out to assess the differences among three or more groups. OS was compared among groups using log-rank test. Hazard ratios (HRs) were calculated, and independent risk factors were identified using univariate and multivariate Cox regression. All statistical analyses were conducted using R version 4.2.2. at a significance of p < 0.05.

Data availability

The datasets analyzed during the current study are available in the GEO ( https://www.ncbi.nlm.nih.gov/geo/ ) and TCGA ( https://portal.gdc.cancer.gov ) repository, including GSE58812, GSE135565, GSE161529, and TCGA-TNBC.

Sung, H. et al. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J. Clin. 71 , 209–249. https://doi.org/10.3322/caac.21660 (2021).

Article   PubMed   Google Scholar  

Bai, X., Ni, J., Beretov, J., Graham, P. & Li, Y. Triple-negative breast cancer therapeutic resistance: Where is the Achilles’ heel?. Cancer Lett. 497 , 100–111. https://doi.org/10.1016/j.canlet.2020.10.016 (2021).

Article   CAS   PubMed   Google Scholar  

Singh, D. D. & Yadav, D. K. TNBC: Potential targeting of multiple receptors for a therapeutic breakthrough, nanomedicine, and immunotherapy. Biomedicines https://doi.org/10.3390/biomedicines9080876 (2021).

Article   PubMed   PubMed Central   Google Scholar  

Nicolini, A., Ferrari, P. & Duffy, M. J. Prognostic and predictive biomarkers in breast cancer: Past, present and future. Semin. Cancer Biol. 52 , 56–73. https://doi.org/10.1016/j.semcancer.2017.08.010 (2018).

Ma, J. et al. m5C-Atlas: A comprehensive database for decoding and annotating the 5-methylcytosine (m5C) epitranscriptome. Nucleic Acids Res. 50 , D196-d203. https://doi.org/10.1093/nar/gkab1075 (2022).

Huang, D. et al. Geographic encoding of transcripts enabled high-accuracy and isoform-aware deep learning of RNA methylation. Nucleic Acids Res. 50 , 10290–10310. https://doi.org/10.1093/nar/gkac830 (2022).

Article   CAS   PubMed   PubMed Central   Google Scholar  

Papayannopoulos, V. Neutrophil extracellular traps in immunity and disease. Nat. Rev. Immunol. 18 , 134–147. https://doi.org/10.1038/nri.2017.105 (2018).

Xiao, Y. et al. Cathepsin C promotes breast cancer lung metastasis by modulating neutrophil infiltration and neutrophil extracellular trap formation. Cancer Cell 39 , 423-437.e427. https://doi.org/10.1016/j.ccell.2020.12.012 (2021).

Masucci, M. T., Minopoli, M., Del Vecchio, S. & Carriero, M. V. The emerging role of neutrophil extracellular traps (NETs) in tumor progression and metastasis. Front. Immunol. 11 , 1749. https://doi.org/10.3389/fimmu.2020.01749 (2020).

Albrengues, J. et al. Neutrophil extracellular traps produced during inflammation awaken dormant cancer cells in mice. Science https://doi.org/10.1126/science.aao4227 (2018).

Yang, L. et al. DNA of neutrophil extracellular traps promotes cancer metastasis via CCDC25. Nature 583 , 133–138. https://doi.org/10.1038/s41586-020-2394-6 (2020).

Article   ADS   CAS   PubMed   Google Scholar  

Song, B. et al. m6A-TSHub: Unveiling the Context-specific m(6)A Methylation and m6A-affecting Mutations in 23 Human Tissues. Genomics Proteomics Bioinform. https://doi.org/10.1016/j.gpb.2022.09.001 (2022).

Article   Google Scholar  

Zhang, Y. et al. DirectRMDB: A database of post-transcriptional RNA modifications unveiled from direct RNA sequencing technology. Nucleic Acids Res. 51 , D106-d116. https://doi.org/10.1093/nar/gkac1061 (2023).

Zhang, Q. & Gu, M. L. Single-cell sequencing and its application in breast cancer. Yi Chuan 42 , 250–268. https://doi.org/10.16288/j.yczz.19-268 (2020).

Chung, W. et al. Single-cell RNA-seq enables comprehensive tumour and immune cell profiling in primary breast cancer. Nat. Commun. 8 , 15081. https://doi.org/10.1038/ncomms15081 (2017).

Article   ADS   CAS   PubMed   PubMed Central   Google Scholar  

Hwang, B., Lee, J. H. & Bang, D. Single-cell RNA sequencing technologies and bioinformatics pipelines. Exp. Mol. Med. 50 , 1–14. https://doi.org/10.1038/s12276-018-0071-8 (2018).

So, J. Y., Ohm, J., Lipkowitz, S. & Yang, L. Triple negative breast cancer (TNBC): Non-genetic tumor heterogeneity and immune microenvironment: Emerging treatment options. Pharmacol. Ther. 237 , 108253. https://doi.org/10.1016/j.pharmthera.2022.108253 (2022).

Gradishar, W. J. et al. NCCN Guidelines® Insights: Breast Cancer, Version 4.2023. J. Natl. Compr. Cancer Netw. 21 , 594–608. https://doi.org/10.6004/jnccn.2023.0031 (2023).

de Jong, V. M. T. et al. Prognostic value of stromal tumor-infiltrating lymphocytes in young, node-negative, triple-negative breast cancer patients who did not receive (neo)adjuvant systemic therapy. J. Clin. Oncol. 40 , 2361–2374. https://doi.org/10.1200/jco.21.01536 (2022).

Mantovani, A., Cassatella, M. A., Costantini, C. & Jaillon, S. Neutrophils in the activation and regulation of innate and adaptive immunity. Nat. Rev. Immunol. 11 , 519–531. https://doi.org/10.1038/nri3024 (2011).

Kolaczkowska, E. & Kubes, P. Neutrophil recruitment and function in health and inflammation. Nat. Rev. Immunol. 13 , 159–175. https://doi.org/10.1038/nri3399 (2013).

Cristinziano, L. et al. Neutrophil extracellular traps in cancer. Semin. Cancer Biol. 79 , 91–104. https://doi.org/10.1016/j.semcancer.2021.07.011 (2022).

Volkov, D. V., Tetz, G. V., Rubtsov, Y. P., Stepanov, A. V. & Gabibov, A. G. Neutrophil extracellular traps (NETs): Opportunities for targeted therapy. Acta Naturae 13 , 15–23. https://doi.org/10.32607/actanaturae.11503 (2021).

Chen, Y. et al. The role of neutrophil extracellular traps in cancer progression, metastasis and therapy. Exp. Hematol. Oncol. 11 , 99. https://doi.org/10.1186/s40164-022-00345-3 (2022).

Shahzad, M. H. et al. Neutrophil extracellular traps in cancer therapy resistance. Cancers https://doi.org/10.3390/cancers14051359 (2022).

Zhang, Y. et al. Interleukin-17-induced neutrophil extracellular traps mediate resistance to checkpoint blockade in pancreatic cancer. J. Exp. Med. https://doi.org/10.1084/jem.20190354 (2020).

Zha, C. et al. Neutrophil extracellular traps mediate the crosstalk between glioma progression and the tumor microenvironment via the HMGB1/RAGE/IL-8 axis. Cancer Biol. Med. 17 , 154–168 (2020).

Dieci, M. V., Miglietta, F. & Guarneri, V. Immune infiltrates in breast cancer: Recent updates and clinical implications. Cells https://doi.org/10.3390/cells10020223 (2021).

Shao, X., Lu, X., Liao, J., Chen, H. & Fan, X. New avenues for systematically inferring cell–cell communication: Through single-cell transcriptomics data. Protein Cell 11 , 866–880. https://doi.org/10.1007/s13238-020-00727-5 (2020).

Jin, S. et al. Inference and analysis of cell–cell communication using Cell Chat. Nat. Commun. 12 , 1088. https://doi.org/10.1038/s41467-021-21246-9 (2021).

Liu, Z., Sun, D. & Wang, C. Evaluation of cell–cell interaction methods by integrating single-cell RNA sequencing data with spatial information. Genome Biol. 23 , 218. https://doi.org/10.1186/s13059-022-02783-y (2022).

Rabinovich, G. A. & Conejo-García, J. R. Shaping the immune landscape in cancer by galectin-driven regulatory pathways. J. Mol. Biol. 428 , 3266–3281. https://doi.org/10.1016/j.jmb.2016.03.021 (2016).

Sosa, M. S., Bragado, P. & Aguirre-Ghiso, J. A. Mechanisms of disseminated cancer cell dormancy: An awakening field. Nat. Rev. Cancer 14 , 611–622. https://doi.org/10.1038/nrc3793 (2014).

Snoderly, H. T., Boone, B. A. & Bennewitz, M. F. Neutrophil extracellular traps in breast cancer and beyond: Current perspectives on NET stimuli, thrombosis and metastasis, and clinical utility for diagnosis and treatment. Breast Cancer Res. 21 , 145. https://doi.org/10.1186/s13058-019-1237-6 (2019).

Miggelbrink, A. M. et al. CD4 T-cell exhaustion: Does it exist and what are its roles in cancer?. Clin. Cancer Res. 27 , 5742–5752. https://doi.org/10.1158/1078-0432.Ccr-21-0206 (2021).

Xia, Y. et al. Engineering macrophages for cancer immunotherapy and drug delivery. Adv. Mater. 32 , e2002054. https://doi.org/10.1002/adma.202002054 (2020).

Chan, T. A. et al. Development of tumor mutation burden as an immunotherapy biomarker: Utility for the oncology clinic. Ann. Oncol. 30 , 44–56. https://doi.org/10.1093/annonc/mdy495 (2019).

Barroso-Sousa, R. et al. Prevalence and mutational determinants of high tumor mutation burden in breast cancer. Ann. Oncol. 31 , 387–394. https://doi.org/10.1016/j.annonc.2019.11.010 (2020).

Gao, C. et al. Tumor mutation burden and immune invasion characteristics in triple negative breast cancer: Genome high-throughput data analysis. Front. Immunol. 12 , 650491. https://doi.org/10.3389/fimmu.2021.650491 (2021).

Yin, L., Duan, J. J., Bian, X. W. & Yu, S. C. Triple-negative breast cancer molecular subtyping and treatment progress. Breast Cancer Res. 22 , 61. https://doi.org/10.1186/s13058-020-01296-5 (2020).

Leek, J. T., Johnson, W. E., Parker, H. S., Jaffe, A. E. & Storey, J. D. The sva package for removing batch effects and other unwanted variation in high-throughput experiments. Bioinformatics 28 , 882–883. https://doi.org/10.1093/bioinformatics/bts034 (2012).

Wu, J. et al. Identification of renal ischemia reperfusion injury subtypes and predictive strategies for delayed graft function and graft survival based on neutrophil extracellular trap-related genes. Front. Immunol. 13 , 1047367. https://doi.org/10.3389/fimmu.2022.1047367 (2022).

Xin, H. et al. Noninvasive evaluation of neutrophil extracellular traps signature predicts clinical outcomes and immunotherapy response in hepatocellular carcinoma. Front. Immunol. 14 , 1134521. https://doi.org/10.3389/fimmu.2023.1134521 (2023).

Li, M. et al. Neutrophil extracellular traps-related signature predicts the prognosis and immune infiltration in gastric cancer. Front. Med. 10 , 1174764. https://doi.org/10.3389/fmed.2023.1174764 (2023).

Feng, C. et al. A neutrophil extracellular traps-related classification predicts prognosis and response to immunotherapy in colon cancer. Sci. Rep. 13 , 19297. https://doi.org/10.1038/s41598-023-45558-6 (2023).

Mayakonda, A., Lin, D. C., Assenov, Y., Plass, C. & Koeffler, H. P. Maftools: Efficient and comprehensive analysis of somatic variants in cancer. Genome Res. 28 , 1747–1756. https://doi.org/10.1101/gr.239244.118 (2018).

Ritchie, M. E. et al. limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res. 43 , e47. https://doi.org/10.1093/nar/gkv007 (2015).

Wilkerson, M. D. & Hayes, D. N. ConsensusClusterPlus: A class discovery tool with confidence assessments and item tracking. Bioinformatics 26 , 1572–1573. https://doi.org/10.1093/bioinformatics/btq170 (2010).

Hänzelmann, S., Castelo, R. & Guinney, J. GSVA: Gene set variation analysis for microarray and RNA-seq data. BMC Bioinform. 14 , 7. https://doi.org/10.1186/1471-2105-14-7 (2013).

Wu, T. et al. clusterProfiler 4.0: A universal enrichment tool for interpreting omics data. Innovation 2 , 100141. https://doi.org/10.1016/j.xinn.2021.100141 (2021).

Chen, B., Khodadoust, M. S., Liu, C. L., Newman, A. M. & Alizadeh, A. A. Profiling tumor infiltrating immune cells with CIBERSORT. Methods Mol. Biol. 1711 , 243–259. https://doi.org/10.1007/978-1-4939-7493-1_12 (2018).

Shannon, P. et al. Cytoscape: A software environment for integrated models of biomolecular interaction networks. Genome Res. 13 , 2498–2504. https://doi.org/10.1101/gr.1239303 (2003).

Chin, C. H. et al. cytoHubba: Identifying hub objects and sub-networks from complex interactome. BMC Syst. Biol. 8 (Suppl 4), S11. https://doi.org/10.1186/1752-0509-8-s4-s11 (2014).

Maeser, D., Gruener, R. F. & Huang, R. S. oncoPredict: An R package for predicting in vivo or cancer patient drug response and biomarkers from cell line screening data. Brief Bioinform. https://doi.org/10.1093/bib/bbab260 (2021).

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These authors contributed equally: Zhidong Huang, Jinhui Wang and Bo Sun.

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The Second Surgical Department of Breast Cancer, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Tianjin, China

Zhidong Huang, Jinhui Wang, Bo Sun, Mengyang Qi, Shuang Gao & Hong Liu

Tianjin’s Clinical Research Center for Cancer, Tianjin, China

Key Laboratory of Breast Cancer Prevention and Therapy, Tianjin Medical University, Ministry of Education, Tianjin, China

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HL designed and supervised the study. ZH, JW, and BS analyzed the data and wrote the original draft. MQ and SG edited the draft. All authors contributed to the article and approved the submitted version.

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Huang, Z., Wang, J., Sun, B. et al. Neutrophil extracellular trap-associated risk index for predicting outcomes and response to Wnt signaling inhibitors in triple-negative breast cancer. Sci Rep 14 , 4232 (2024). https://doi.org/10.1038/s41598-024-54888-y

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case study on triple negative breast cancer

Real-World Data from a Refractory Triple-Negative Breast Cancer Cohort Selected Using a Clinical Data Warehouse Approach

Affiliations.

  • 1 Division of Hematology-Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Korea.
  • 2 Center for Research Resource Standardization, Research Institution for Future Medicine, Samsung Medical Center, Seoul 06351, Korea.
  • 3 Samsung Advanced Institute for Health Sciences & Technology (SAIHST), Sungkyunkwan University, Seoul 06351, Korea.
  • 4 Division of Breast Surgery, Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Korea.
  • 5 Departments of Radiation Oncology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Korea.
  • 6 Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University, Suwon 16419, Korea.
  • PMID: 34830990
  • PMCID: PMC8616548
  • DOI: 10.3390/cancers13225835

Purpose: Triple-negative breast cancer (TNBC) is well known for its aggressive course and poor prognosis. In this study, we sought to investigate clinical, demographic, and pathologic characteristics and treatment outcomes of patients with refractory, metastatic TNBC selected by a clinical data warehouse (CDW) approach.

Patients and methods: Data were extracted from the real-time breast cancer registry integrated into the Data Analytics and Research Window for Integrated Knowledge C (DARWIN-C), the CDW of Samsung Medical Center. Between January 1997 and December 2019, a TNBC cohort was searched for in the breast cancer registry, which includes records from more than 40,000 patients. Among them, cases of pathologically confirmed metastatic TNBC (mTNBC) were selected as the cohort group ( n = 451). The extracted data from the registry via the CDW platform included clinical, pathological, laboratory, and chemotherapy information. Refractory TNBC was defined as confirmed distant metastasis within one year after adjuvant treatment.

Results: This study comprised a total of 451 patients with mTNBC, including 69 patients with de novo mTNBC, 131 patients in the nonrefractory TNBC group with confirmed stage IV disease after one year of adjuvant treatment, and 251 patients with refractory mTNBC, whose disease recurred as stage IV within one year after completing adjuvant treatment. The refractory mTNBC cohort was composed of patients with disease that recurred at stage IV after surgery (refractory mTNBC after surgery) ( n = 207) and patients in whom metastasis was confirmed during neoadjuvant chemotherapy (unresectable TNBC due to progression during neoadjuvant chemotherapy) ( n = 44). Patients in the refractory mTNBC group were younger than those in the nonrefractory group (median age 46 vs. 51 years; p < 0.001). Considering the pathological findings, the refractory group had a greater proportion of cases with Ki-67 ≥ 3+ than did the nonrefractory group (71% vs. 47%; p = 0.004). During a median 8.4 years of follow-up, the overall survival was 24.8 months in the nonrefractory mTNBC group and 14.3 months in the refractory mTNBC group ( p < 0.001), and the median progression-free survival periods were 6.2 months and 4.2 months, respectively ( p < 0.001). The median disease-free survival period was 30.1 months in the nonrefractory mTNBC group and only 7.6 months in the refractory mTNBC group. Factors related to metastatic sites affecting overall survival were liver metastasis at diagnosis ( p < 0.001) and leptomeningeal involvement ( p = 0.001).

Conclusions: We revealed that patients with refractory mTNBC had a much poorer prognosis among all mTNBC cases and described the characteristics of this patient group.

Keywords: CDW; metastatic breast cancer; triple-negative breast cancer.

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