Skip to main content

Advertisement

Log in

Tumor immune microenvironment components and the other markers can predict the efficacy of neoadjuvant chemotherapy for breast cancer

  • REVIEW ARTICLE
  • Published:
Clinical and Translational Oncology Aims and scope Submit manuscript

Abstract

Breast cancer is an epithelial malignant tumor that occurs in the terminal ducts of the breast. Neoadjuvant chemotherapy (NACT) is an important part of breast cancer treatment. Its purpose is to use systemic treatment for some locally advanced breast cancer patients, to decrease the tumor size and clinical stage so that non-operable breast cancer patients can have a chance to access surgical treatment, or patients who are not suitable for breast-conserving surgery can get the opportunity of breast-conserving. However, some patients who do not respond to NACT will lead deterioration in their condition. Therefore, prediction of NACT efficacy in breast cancer is vital for precision therapy. The tumor microenvironment (TME) has a crucial role in the carcinogenesis and therapeutic response of breast cancer. In this review, we summarized the immune cells, immune checkpoints, and other biomarkers in the TME that can evaluate the efficacy of NACT in treating breast cancer. We believe that the detection and evaluation of the TME components in breast cancer are helpful to predict the efficacy of NACT, and the prediction methods are in the prospect. In addition, we also summarized other predictive factors of NACT, such as imaging examination, biochemical markers, and multigene/multiprotein profiling.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2

Similar content being viewed by others

Data availability

Not applicable.

References

  1. Rabbani A, Finn RM, Ausió J. The anthracycline antibiotics: antitumor drugs that alter chromatin structure. BioEssays. 2005;27(1):50–6. https://doi.org/10.1002/bies.20160.

    Article  CAS  PubMed  Google Scholar 

  2. Hung JH, Chen CY, Omar HA, Huang KY, Tsao CC, Chiu CC, et al. Reactive oxygen species mediate Terbufos-induced apoptosis in mouse testicular cell lines via the modulation of cell cycle and pro-apoptotic proteins. Environ Toxicol. 2016;31(12):1888–98. https://doi.org/10.1002/tox.22190.

    Article  CAS  PubMed  Google Scholar 

  3. Mackey JR, Martin M, Pienkowski T, Rolski J, Guastalla JP, Sami A, et al. Adjuvant docetaxel, doxorubicin, and cyclophosphamide in node-positive breast cancer: 10-year follow-up of the phase 3 randomised BCIRG 001 trial. Lancet Oncol. 2013;14(1):72–80. https://doi.org/10.1016/s1470-2045(12)70525-9.

    Article  CAS  PubMed  Google Scholar 

  4. Loibl S, Untch M, Burchardi N, Huober J, Sinn BV, Blohmer JU, et al. A randomised phase II study investigating durvalumab in addition to an anthracycline taxane-based neoadjuvant therapy in early triple-negative breast cancer: clinical results and biomarker analysis of GeparNuevo study. Ann Oncol. 2019;30(8):1279–88. https://doi.org/10.1093/annonc/mdz158.

    Article  CAS  PubMed  Google Scholar 

  5. Members of Breast Cancer Expert Panel on C. [Expert panel consensus on pathological diagnosis of breast cancer with neoadjuvant therapy, the 2020 version]. Zhonghua Bing Li Xue Za Zhi. 2020;49(4):296–304. https://doi.org/10.3760/cma.j.cn112151-20200102-00007.

  6. Choi J, Gyamfi J, Jang H, Koo JS. The role of tumor-associated macrophage in breast cancer biology. Histol Histopathol. 2018;33(2):133–45. https://doi.org/10.14670/hh-11-916.

    Article  CAS  PubMed  Google Scholar 

  7. Li JJ, Tsang JY, Tse GM. Tumor microenvironment in breast cancer-updates on therapeutic implications and pathologic assessment. Cancers (Basel). 2021. https://doi.org/10.3390/cancers13164233.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Urueña C, Lasso P, Bernal-Estevez D, Rubio D, Salazar AJ, Olaya M, et al. The breast cancer immune microenvironment is modified by neoadjuvant chemotherapy. Sci Rep. 2022;12(1):7981. https://doi.org/10.1038/s41598-022-12108-5.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Wargo JA, Reuben A, Cooper ZA, Oh KS, Sullivan RJ. Immune effects of chemotherapy, radiation, and targeted therapy and opportunities for combination with immunotherapy. Semin Oncol. 2015;42(4):601–16. https://doi.org/10.1053/j.seminoncol.2015.05.007.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Tan W, Yang M, Yang H, Zhou F, Shen W. Predicting the response to neoadjuvant therapy for early-stage breast cancer: tumor-, blood-, and imaging-related biomarkers. Cancer Manag Res. 2018;10:4333–47. https://doi.org/10.2147/cmar.S174435.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Mao Y, Qu Q, Zhang Y, Liu J, Chen X, Shen K. The value of tumor infiltrating lymphocytes (TILs) for predicting response to neoadjuvant chemotherapy in breast cancer: a systematic review and meta-analysis. PLoS ONE. 2014;9(12): e115103. https://doi.org/10.1371/journal.pone.0115103.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Kaewkangsadan V, Verma C, Eremin JM, Cowley G, Ilyas M, Eremin O. Crucial contributions by T lymphocytes (effector, regulatory, and checkpoint inhibitor) and cytokines (TH1, TH2, and TH17) to a pathological complete response induced by neoadjuvant chemotherapy in women with breast cancer. J Immunol Res. 2016;2016:4757405. https://doi.org/10.1155/2016/4757405.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Wang Y, Dong T, Xuan Q, Zhao H, Qin L, Zhang Q. Lymphocyte-activation gene-3 expression and prognostic value in neoadjuvant-treated triple-negative breast cancer. J Breast Cancer. 2018;21(2):124–33. https://doi.org/10.4048/jbc.2018.21.2.124.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Rao N, Qiu J, Wu J, Zeng H, Su F, Qiu K, et al. Significance of tumor-infiltrating lymphocytes and the expression of topoisomerase iiα in the prediction of the clinical outcome of patients with triple-negative breast cancer after taxane-anthracycline-based neoadjuvant chemotherapy. Chemotherapy. 2017;62(4):246–55. https://doi.org/10.1159/000470900.

    Article  CAS  PubMed  Google Scholar 

  15. Osuna-Gómez R, Arqueros C, Galano C, Mulet M, Zamora C, Barnadas A, et al. Effector mechanisms of CD8+ HLA-DR+ T cells in breast cancer patients who respond to neoadjuvant chemotherapy. Cancers (Basel). 2021. https://doi.org/10.3390/cancers13246167.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Muraro E, Comaro E, Talamini R, Turchet E, Miolo G, Scalone S, et al. Improved natural killer cell activity and retained anti-tumor CD8(+) T cell responses contribute to the induction of a pathological complete response in HER2-positive breast cancer patients undergoing neoadjuvant chemotherapy. J Transl Med. 2015;13:204. https://doi.org/10.1186/s12967-015-0567-0.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Asano Y, Kashiwagi S, Goto W, Kurata K, Noda S, Takashima T, et al. Tumour-infiltrating CD8 to FOXP3 lymphocyte ratio in predicting treatment responses to neoadjuvant chemotherapy of aggressive breast cancer. Br J Surg. 2016;103(7):845–54. https://doi.org/10.1002/bjs.10127.

    Article  CAS  PubMed  Google Scholar 

  18. Zhou J, Tang Z, Gao S, Li C, Feng Y, Zhou X. Tumor-associated macrophages: recent insights and therapies. Front Oncol. 2020;10:188. https://doi.org/10.3389/fonc.2020.00188.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Ji F, Yuan JM, Gao HF, Xu AQ, Yang Z, Yang CQ, et al. Tumor microenvironment characterization in breast cancer identifies prognostic and neoadjuvant chemotherapy relevant signatures. Front Mol Biosci. 2021;8:759495. https://doi.org/10.3389/fmolb.2021.759495.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Waks AG, Stover DG, Guerriero JL, Dillon D, Barry WT, Gjini E, et al. The immune microenvironment in hormone receptor-positive breast cancer before and after preoperative chemotherapy. Clin Cancer Res. 2019;25(15):4644–55. https://doi.org/10.1158/1078-0432.Ccr-19-0173.

    Article  CAS  PubMed  Google Scholar 

  21. Blenman KRM, Marczyk M, Karn T, Qing T, Li X, Gunasekharan V, et al. Predictive markers of response to neoadjuvant durvalumab with nab-paclitaxel and dose-dense doxorubicin/cyclophosphamide in basal-like triple-negative breast cancer. Clin Cancer Res. 2022;28(12):2587–97. https://doi.org/10.1158/1078-0432.Ccr-21-3215.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Lee HJ, Lee JJ, Song IH, Park IA, Kang J, Yu JH, et al. Prognostic and predictive value of NanoString-based immune-related gene signatures in a neoadjuvant setting of triple-negative breast cancer: relationship to tumor-infiltrating lymphocytes. Breast Cancer Res Treat. 2015;151(3):619–27. https://doi.org/10.1007/s10549-015-3438-8.

    Article  CAS  PubMed  Google Scholar 

  23. Sakaguchi A, Horimoto Y, Onagi H, Ikarashi D, Nakayama T, Nakatsura T, et al. Plasma cell infiltration and treatment effect in breast cancer patients treated with neoadjuvant chemotherapy. Breast Cancer Res. 2021;23(1):99. https://doi.org/10.1186/s13058-021-01477-w.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Kim R, Kawai A, Wakisaka M, Funaoka Y, Yasuda N, Hidaka M, et al. A potential role for peripheral natural killer cell activity induced by preoperative chemotherapy in breast cancer patients. Cancer Immunol Immunother. 2019;68(4):577–85. https://doi.org/10.1007/s00262-019-02305-z.

    Article  CAS  PubMed  Google Scholar 

  25. Kaewkangsadan V, Verma C, Eremin JM, Cowley G, Ilyas M, Satthaporn S, et al. The differential contribution of the innate immune system to a good pathological response in the breast and axillary lymph nodes induced by neoadjuvant chemotherapy in women with large and locally advanced breast cancers. J Immunol Res. 2017;2017:1049023. https://doi.org/10.1155/2017/1049023.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Santisteban M, Solans BP, Hato L, Urrizola A, Mejías LD, Salgado E, et al. Final results regarding the addition of dendritic cell vaccines to neoadjuvant chemotherapy in early HER2-negative breast cancer patients: clinical and translational analysis. Ther Adv Med Oncol. 2021;13:17588359211064652. https://doi.org/10.1177/17588359211064653.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Verma C, Eremin JM, Robins A, Bennett AJ, Cowley GP, El-Sheemy MA, et al. Abnormal T regulatory cells (Tregs: FOXP3+, CTLA-4+), myeloid-derived suppressor cells (MDSCs: monocytic, granulocytic) and polarised T helper cell profiles (Th1, Th2, Th17) in women with large and locally advanced breast cancers undergoing neoadjuvant chemotherapy (NAC) and surgery: failure of abolition of abnormal treg profile with treatment and correlation of treg levels with pathological response to NAC. J Transl Med. 2013;11:16. https://doi.org/10.1186/1479-5876-11-16.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Yao L, Jia G, Lu L, Ma W. Breast cancer patients: who would benefit from neoadjuvant chemotherapies? Curr Oncol. 2022;29(7):4902–13. https://doi.org/10.3390/curroncol29070389.

    Article  PubMed  PubMed Central  Google Scholar 

  29. Litviakov N, Tsyganov M, Larionova I, Ibragimova M, Deryusheva I, Kazantseva P, et al. Expression of M2 macrophage markers YKL-39 and CCL18 in breast cancer is associated with the effect of neoadjuvant chemotherapy. Cancer Chemother Pharmacol. 2018;82(1):99–109. https://doi.org/10.1007/s00280-018-3594-8.

    Article  CAS  PubMed  Google Scholar 

  30. Kzhyshkowska J, Larionova I, Liu T. YKL-39 as a potential new target for anti-angiogenic therapy in cancer. front Immunol. 2019;10:2930. https://doi.org/10.3389/fimmu.2019.02930.

    Article  CAS  PubMed  Google Scholar 

  31. Li F, Zhao Y, Wei L, Li S, Liu J. Tumor-infiltrating Treg, MDSC, and IDO expression associated with outcomes of neoadjuvant chemotherapy of breast cancer. Cancer Biol Ther. 2018;19(8):695–705. https://doi.org/10.1080/15384047.2018.1450116.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Montero AJ, Diaz-Montero CM, Deutsch YE, Hurley J, Koniaris LG, Rumboldt T, et al. Phase 2 study of neoadjuvant treatment with NOV-002 in combination with doxorubicin and cyclophosphamide followed by docetaxel in patients with HER-2 negative clinical stage II-IIIc breast cancer. Breast Cancer Res Treat. 2012;132(1):215–23. https://doi.org/10.1007/s10549-011-1889-0.

    Article  CAS  PubMed  Google Scholar 

  33. Ferrari P, Scatena C, Ghilli M, Bargagna I, Lorenzini G, Nicolini A. Molecular mechanisms, biomarkers and emerging therapies for chemotherapy resistant TNBC. Int J Mol Sci. 2022. https://doi.org/10.3390/ijms23031665.

    Article  PubMed  PubMed Central  Google Scholar 

  34. Leng X, Huang G, Zhang L, Ding J, Ma F. Changes in tumor stem cell markers and epithelial-mesenchymal transition markers in nonluminal breast cancer after neoadjuvant chemotherapy and their correlation with contrast-enhanced ultrasound. Biomed Res Int. 2020;2020:3869538. https://doi.org/10.1155/2020/3869538.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Li X, Warren S, Pelekanou V, Wali V, Cesano A, Liu M, et al. Immune profiling of pre- and post-treatment breast cancer tissues from the SWOG S0800 neoadjuvant trial. J Immunother Cancer. 2019;7(1):88. https://doi.org/10.1186/s40425-019-0563-7.

    Article  PubMed  PubMed Central  Google Scholar 

  36. Eiro N, Gonzalez LO, Fraile M, Cid S, Schneider J, Vizoso FJ. Breast cancer tumor stroma: cellular components, phenotypic heterogeneity, intercellular communication, prognostic implications and therapeutic opportunities. Cancers (Basel). 2019. https://doi.org/10.3390/cancers11050664.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Kotiyal S, Bhattacharya S. Epithelial mesenchymal transition and vascular mimicry in breast cancer stem cells. Crit Rev Eukaryot Gene Expr. 2015;25(3):269–80. https://doi.org/10.1615/critreveukaryotgeneexpr.2015014042.

    Article  PubMed  Google Scholar 

  38. Reddy SM, Reuben A, Barua S, Jiang H, Zhang S, Wang L, et al. Poor response to neoadjuvant chemotherapy correlates with mast cell infiltration in inflammatory breast cancer. Cancer Immunol Res. 2019;7(6):1025–35. https://doi.org/10.1158/2326-6066.Cir-18-0619.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Zhou Y, Tian Q, Gao H, Zhu L, Yang J, Zhang J, et al. Correlation between immune-related genes and tumor-infiltrating immune cells with the efficacy of neoadjuvant chemotherapy for breast cancer. Front Genet. 2022;13:905617. https://doi.org/10.3389/fgene.2022.905617.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Cho HH, Park M, Park H, Ko ES, Hwang NY, Im YH, et al. The tumor-fat interface volume of breast cancer on pretreatment MRI is associated with a pathologic response to neoadjuvant chemotherapy. Biology (Basel). 2020. https://doi.org/10.3390/biology9110391.

    Article  PubMed  PubMed Central  Google Scholar 

  41. Oshi M, Tokumaru Y, Angarita FA, Lee L, Yan L, Matsuyama R, et al. Adipogenesis in triple-negative breast cancer is associated with unfavorable tumor immune microenvironment and with worse survival. Sci Rep. 2021;11(1):12541. https://doi.org/10.1038/s41598-021-91897-7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Maguire OA, Ackerman SE, Szwed SK, Maganti AV, Marchildon F, Huang X, et al. Creatine-mediated crosstalk between adipocytes and cancer cells regulates obesity-driven breast cancer. Cell Metab. 2021;33(3):499-512.e6. https://doi.org/10.1016/j.cmet.2021.01.018.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Lu Y, Wang P, Lan N, Kong F, Abdumijit A, Tu S, et al. Metabolic syndrome predicts response to neoadjuvant chemotherapy in breast cancer. Front Oncol. 2022;12:899335. https://doi.org/10.3389/fonc.2022.899335.

    Article  PubMed  PubMed Central  Google Scholar 

  44. Xu Y, Zhang Z, Zhang L, Zhang C. Novel module and hub genes of distinctive breast cancer associated fibroblasts identified by weighted gene co-expression network analysis. Breast Cancer. 2020;27(5):1017–28. https://doi.org/10.1007/s12282-020-01101-3.

    Article  PubMed  Google Scholar 

  45. Yu S, Lu Y, Su A, Chen J, Li J, Zhou B, et al. A CD10-OGP membrane peptolytic signaling axis in fibroblasts regulates lipid metabolism of cancer stem cells via SCD1. Adv Sci (Weinh). 2021;8(19): e2101848. https://doi.org/10.1002/advs.202101848.

    Article  CAS  PubMed  Google Scholar 

  46. Katayama MLH, Vieira R, Andrade VP, Roela RA, Lima L, Kerr LM, et al. Stromal cell signature associated with response to neoadjuvant chemotherapy in locally advanced breast cancer. Cells. 2019. https://doi.org/10.3390/cells8121566.

    Article  PubMed  PubMed Central  Google Scholar 

  47. Gampenrieder SP, Westphal T, Greil R. Antiangiogenic therapy in breast cancer. Memo. 2017;10(4):194–201. https://doi.org/10.1007/s12254-017-0362-0.

    Article  PubMed  PubMed Central  Google Scholar 

  48. Kim R, Kawai A, Wakisaka M, Sawada S, Shimoyama M, Yasuda N, et al. Immune correlates of the differing pathological and therapeutic effects of neoadjuvant chemotherapy in breast cancer. Eur J Surg Oncol. 2020;46(1):77–84. https://doi.org/10.1016/j.ejso.2019.09.146.

    Article  PubMed  Google Scholar 

  49. Wang RX, Chen S, Huang L, Zhou Y, Shao ZM. Monitoring serum VEGF in neoadjuvant chemotherapy for patients with triple-negative breast cancer: a new strategy for early prediction of treatment response and patient survival. Oncologist. 2019;24(6):753–61. https://doi.org/10.1634/theoncologist.2017-0602.

    Article  CAS  PubMed  Google Scholar 

  50. Alhesa A, Awad H, Bloukh S, Al-Balas M, El-Sadoni M, Qattan D, et al. PD-L1 expression in breast invasive ductal carcinoma with incomplete pathological response to neoadjuvant chemotherapy. Int J Immunopathol Pharmacol. 2022;36:3946320221078433. https://doi.org/10.1177/03946320221078433.

    Article  CAS  PubMed  Google Scholar 

  51. Sarradin V, Lusque A, Filleron T, Dalenc F, Franchet C. Immune microenvironment changes induced by neoadjuvant chemotherapy in triple-negative breast cancers: the MIMOSA-1 study. Breast Cancer Res. 2021;23(1):61. https://doi.org/10.1186/s13058-021-01437-4.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Dieci MV, Tsvetkova V, Griguolo G, Miglietta F, Tasca G, Giorgi CA, et al. Integration of tumour infiltrating lymphocytes, programmed cell-death ligand-1, CD8 and FOXP3 in prognostic models for triple-negative breast cancer: Analysis of 244 stage I-III patients treated with standard therapy. Eur J Cancer. 2020;136:7–15. https://doi.org/10.1016/j.ejca.2020.05.014.

    Article  CAS  PubMed  Google Scholar 

  53. Hoffmann LG, Sarian LO, Vassallo J, de Paiva Silva GR, Ramalho SOB, Ferracini AC, et al. Evaluation of PD-L1 and tumor infiltrating lymphocytes in paired pretreatment biopsies and post neoadjuvant chemotherapy surgical specimens of breast carcinoma. Sci Rep. 2021;11(1):22478. https://doi.org/10.1038/s41598-021-00944-w.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Oner G, Önder S, Karatay H, Ak N, Tükenmez M, Müslümanoğlu M, et al. Clinical impact of PD-L1 expression in triple-negative breast cancer patients with residual tumor burden after neoadjuvant chemotherapy. World J Surg Oncol. 2021;19(1):264. https://doi.org/10.1186/s12957-021-02361-9.

    Article  PubMed  PubMed Central  Google Scholar 

  55. Tarantino P, Gandini S, Trapani D, Criscitiello C, Curigliano G. Immunotherapy addition to neoadjuvant chemotherapy for early triple negative breast cancer: A systematic review and meta-analysis of randomized clinical trials. Crit Rev Oncol Hematol. 2021;159:103223. https://doi.org/10.1016/j.critrevonc.2021.103223.

    Article  PubMed  Google Scholar 

  56. Xin Y, Shen G, Zheng Y, Guan Y, Huo X, Li J, et al. Immune checkpoint inhibitors plus neoadjuvant chemotherapy in early triple-negative breast cancer: a systematic review and meta-analysis. BMC Cancer. 2021;21(1):1261. https://doi.org/10.1186/s12885-021-08997-w.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Li Y, Cui X, Yang YJ, Chen QQ, Zhong L, Zhang T, et al. Serum sPD-1 and sPD-L1 as biomarkers for evaluating the efficacy of neoadjuvant chemotherapy in triple-negative breast cancer patients. Clin Breast Cancer. 2019;19(5):326-32.e1. https://doi.org/10.1016/j.clbc.2019.03.008.

    Article  CAS  PubMed  Google Scholar 

  58. Zhu Y, Zhu X, Tang C, Guan X, Zhang W. Progress and challenges of immunotherapy in triple-negative breast cancer. Biochim Biophys Acta Rev Cancer. 2021;1876(2):188593. https://doi.org/10.1016/j.bbcan.2021.188593.

    Article  CAS  PubMed  Google Scholar 

  59. Solomon BL, Garrido-Laguna I. TIGIT: a novel immunotherapy target moving from bench to bedside. Cancer Immunol Immunother. 2018;67(11):1659–67. https://doi.org/10.1007/s00262-018-2246-5.

    Article  CAS  PubMed  Google Scholar 

  60. Abbasov A, Aktas Cetin E, Cabioglu N, Mollavelioglu B, Onder S, Emiroglu S, et al. Differential expression of novel immune checkpoint receptors on tumor infiltrating lymphocytes in patients with locally advanced breast cancer after neoadjuvant chemotherapy. Neoplasma. 2021;68(5):1079–90. https://doi.org/10.4149/neo_2021_210127N141.

    Article  PubMed  Google Scholar 

  61. Cabioglu N, Onder S, Oner G, Karatay H, Tukenmez M, Muslumanoglu M, et al. TIM3 expression on TILs is associated with poor response to neoadjuvant chemotherapy in patients with locally advanced triple-negative breast cancer. BMC Cancer. 2021;21(1):357. https://doi.org/10.1186/s12885-021-08054-6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Li F, Wei L, Li S, Liu J. Indoleamine-2,3-dioxygenase and Interleukin-6 associated with tumor response to neoadjuvant chemotherapy in breast cancer. Oncotarget. 2017;8(64):107844–58. https://doi.org/10.18632/oncotarget.22253.

    Article  PubMed  PubMed Central  Google Scholar 

  63. Zhao Y, Wei L, Liu J, Li F. Chemoresistance was correlated with elevated expression and activity of indoleamine 2,3-dioxygenase in breast cancer. Cancer Chemother Pharmacol. 2020;85(1):77–93. https://doi.org/10.1007/s00280-019-04009-8.

    Article  CAS  PubMed  Google Scholar 

  64. Asano Y, Kashiwagi S, Takada K, Ishihara S, Goto W, Morisaki T, et al. Clinical significance of expression of immunoadjuvant molecules (LAG-3, TIM-3, OX-40) in neoadjuvant chemotherapy for breast cancer. Anticancer Res. 2022;42(1):125–36. https://doi.org/10.21873/anticanres.15466.

    Article  CAS  PubMed  Google Scholar 

  65. Cerbelli B, Scagnoli S, Mezi S, De Luca A, Pisegna S, Amabile MI, et al. Tissue immune profile: a tool to predict response to neoadjuvant therapy in triple negative breast cancer. Cancers (Basel). 2020. https://doi.org/10.3390/cancers12092648.

    Article  PubMed  PubMed Central  Google Scholar 

  66. Lusho S, Durando X, Mouret-Reynier MA, Kossai M, Lacrampe N, Molnar I, et al. Platelet-to-lymphocyte ratio is associated with favorable response to neoadjuvant chemotherapy in triple negative breast cancer: a study on 120 patients. Front Oncol. 2021;11:678315. https://doi.org/10.3389/fonc.2021.678315.

    Article  PubMed  PubMed Central  Google Scholar 

  67. Şahin AB, Cubukcu E, Ocak B, Deligonul A, Oyucu Orhan S, Tolunay S, et al. Low pan-immune-inflammation-value predicts better chemotherapy response and survival in breast cancer patients treated with neoadjuvant chemotherapy. Sci Rep. 2021;11(1):14662. https://doi.org/10.1038/s41598-021-94184-7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Graziano V, Grassadonia A, Iezzi L, Vici P, Pizzuti L, Barba M, et al. Combination of peripheral neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio is predictive of pathological complete response after neoadjuvant chemotherapy in breast cancer patients. Breast. 2019;44:33–8. https://doi.org/10.1016/j.breast.2018.12.014.

    Article  PubMed  Google Scholar 

  69. Wang J, Wang X, Chen R, Liang M, Li M, Ma G, et al. Circulating tumor cells may serve as a supplement to RECIST in neoadjuvant chemotherapy of patients with locally advanced breast cancer. Int J Clin Oncol. 2022;27(5):889–98. https://doi.org/10.1007/s10147-022-02125-9.

    Article  CAS  PubMed  Google Scholar 

  70. Cai G, Guan Z, Jin Y, Su Z, Chen X, Liu Q, et al. Circulating T-cell repertoires correlate with the tumor response in patients with breast cancer receiving neoadjuvant chemotherapy. JCO Precis Oncol. 2022;6: e2100120. https://doi.org/10.1200/po.21.00120.

    Article  PubMed  PubMed Central  Google Scholar 

  71. Wei B, Shan Y, Du Z, Yin C, Zhang Q, Lin H, et al. Identifying circulating tumor DNA mutations associated with neoadjuvant chemotherapy efficacy in local advanced breast cancer. Appl Biochem Biotechnol. 2022. https://doi.org/10.1007/s12010-022-03946-0.

    Article  PubMed  Google Scholar 

  72. Duffy MJ, Harbeck N, Nap M, Molina R, Nicolini A, Senkus E, et al. Clinical use of biomarkers in breast cancer: Updated guidelines from the European Group on Tumor Markers (EGTM). Eur J Cancer. 2017;75:284–98. https://doi.org/10.1016/j.ejca.2017.01.017.

    Article  CAS  PubMed  Google Scholar 

  73. Li F, Ma L, Geng C, Liu C, Deng H, Yue M, et al. Analysis of the relevance between molecular subtypes and efficacy of neoadjuvant chemotherapy in breast cancer as well as its prognostic factors. Pathol Res Pract. 2018;214(8):1166–72. https://doi.org/10.1016/j.prp.2018.06.010.

    Article  CAS  PubMed  Google Scholar 

  74. von Minckwitz G, Sinn HP, Raab G, Loibl S, Blohmer JU, Eidtmann H, et al. Clinical response after two cycles compared to HER2, Ki-67, p53, and bcl-2 in independently predicting a pathological complete response after preoperative chemotherapy in patients with operable carcinoma of the breast. Breast Cancer Res. 2008;10(2):R30. https://doi.org/10.1186/bcr1989.

    Article  CAS  Google Scholar 

  75. Rossi L, Verrico M, Tomao S, Ricci F, Fontana A, Spinelli GP, et al. Expression of ER, PgR, HER-2, and Ki-67 in core biopsies and in definitive histological specimens in patients with locally advanced breast cancer treated with neoadjuvant chemotherapy. Cancer Chemother Pharmacol. 2020;85(1):105–11. https://doi.org/10.1007/s00280-019-03981-5.

    Article  CAS  PubMed  Google Scholar 

  76. La Forgia D, Vestito A, Lasciarrea M, Comes MC, Diotaiuti S, Giotta F, et al. Response predictivity to neoadjuvant therapies in breast cancer: a qualitative analysis of background parenchymal enhancement in DCE-MRI. J Pers Med. 2021. https://doi.org/10.3390/jpm11040256.

    Article  PubMed  PubMed Central  Google Scholar 

  77. Liu J, Sun D, Chen L, Fang Z, Song W, Guo D, et al. Radiomics analysis of dynamic contrast-enhanced magnetic resonance imaging for the prediction of sentinel lymph node metastasis in breast cancer. Front Oncol. 2019;9:980. https://doi.org/10.3389/fonc.2019.00980.

    Article  PubMed  PubMed Central  Google Scholar 

  78. Harada TL, Uematsu T, Nakashima K, Kawabata T, Nishimura S, Takahashi K, et al. Evaluation of breast edema findings at T2-weighted breast MRI is useful for diagnosing occult inflammatory breast cancer and can predict prognosis after neoadjuvant chemotherapy. Radiology. 2021;299(1):53–62. https://doi.org/10.1148/radiol.2021202604.

    Article  PubMed  Google Scholar 

  79. Skarping I, Förnvik D, Heide-Jørgensen U, Sartor H, Hall P, Zackrisson S, et al. Mammographic density as an image-based biomarker of therapy response in neoadjuvant-treated breast cancer patients. Cancer Causes Control. 2021;32(3):251–60. https://doi.org/10.1007/s10552-020-01379-w.

    Article  PubMed  Google Scholar 

  80. Sudhir R, Koppula VC, Rao TS, Sannapareddy K, Rajappa SJ, Murthy SS. Accuracy of digital mammography, ultrasound and MRI in predicting the pathological complete response and residual tumor size of breast cancer after completion of neoadjuvant chemotherapy. Indian J Cancer. 2021. https://doi.org/10.4103/ijc.IJC_795_19.

    Article  Google Scholar 

  81. Palshof FK, Lanng C, Kroman N, Benian C, Vejborg I, Bak A, et al. Prediction of pathologic complete response in breast cancer patients comparing magnetic resonance imaging with ultrasound in neoadjuvant setting. Ann Surg Oncol. 2021;28(12):7421–9. https://doi.org/10.1245/s10434-021-10117-8.

    Article  PubMed  Google Scholar 

  82. Nakai K, Mitomi H, Alkam Y, Arakawa A, Yao T, Tokuda E, et al. Predictive value of MGMT, hMLH1, hMSH2 and BRCA1 protein expression for pathological complete response to neoadjuvant chemotherapy in basal-like breast cancer patients. Cancer Chemother Pharmacol. 2012;69(4):923–30. https://doi.org/10.1007/s00280-011-1777-7.

    Article  CAS  PubMed  Google Scholar 

  83. Raychaudhuri M, Bronger H, Buchner T, Kiechle M, Weichert W, Avril S. MicroRNAs miR-7 and miR-340 predict response to neoadjuvant chemotherapy in breast cancer. Breast Cancer Res Treat. 2017;162(3):511–21. https://doi.org/10.1007/s10549-017-4132-9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  84. Pease AM, Riba LA, Gruner RA, Tung NM, James TA. Oncotype DX(®) recurrence score as a predictor of response to neoadjuvant chemotherapy. Ann Surg Oncol. 2019;26(2):366–71. https://doi.org/10.1245/s10434-018-07107-8.

    Article  PubMed  Google Scholar 

  85. Soliman H, Wagner S, Flake DD 2nd, Robson M, Schwartzberg L, Sharma P, et al. Evaluation of the 12-gene molecular score and the 21-gene recurrence score as predictors of response to neo-adjuvant chemotherapy in estrogen receptor-positive, HER2-negative breast cancer. Ann Surg Oncol. 2020;27(3):765–71. https://doi.org/10.1245/s10434-019-08039-7.

    Article  PubMed  PubMed Central  Google Scholar 

  86. Cheng Y, Lin L, Li X, Lu A, Hou C, Wu Q, et al. ADAM10 is involved in the oncogenic process and chemo-resistance of triple-negative breast cancer via regulating Notch1 signaling pathway, CD44 and PrPc. Cancer Cell Int. 2021;21(1):32. https://doi.org/10.1186/s12935-020-01727-5.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  87. Liu J, Wang S, Wang C, Kong X, Sun P. Prognostic value of using glucosylceramide synthase and cytochrome P450 family 1 subfamily A1 expression levels for patients with triple-negative breast cancer following neoadjuvant chemotherapy. Exp Ther Med. 2021;21(3):247. https://doi.org/10.3892/etm.2021.9678.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  88. Li J, Zhang S, Ye C, Liu Q, Cheng Y, Ye J, et al. Androgen receptor: a new marker to predict pathological complete response in HER2-positive breast cancer patients treated with trastuzumab plus pertuzumab neoadjuvant therapy. J Pers Med. 2022. https://doi.org/10.3390/jpm12020261.

    Article  PubMed  PubMed Central  Google Scholar 

  89. Vishnukumar S, Umamaheswaran G, Anichavezhi D, Indumathy S, Adithan C, Srinivasan K, et al. P-glycoprotein expression as a predictor of response to neoadjuvant chemotherapy in breast cancer. Indian J Cancer. 2013;50(3):195–9. https://doi.org/10.4103/0019-509x.118726.

    Article  CAS  PubMed  Google Scholar 

  90. Liu S, Wang H, Li J, Zhang J, Wu J, Li Y, et al. FZR1 as a novel biomarker for breast cancer neoadjuvant chemotherapy prediction. Cell Death Dis. 2020;11(9):804. https://doi.org/10.1038/s41419-020-03004-9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  91. Tanino H, Kosaka Y, Nishimiya H, Tanaka Y, Minatani N, Kikuchi M, et al. BRCAness and prognosis in triple-negative breast cancer patients treated with neoadjuvant chemotherapy. PLoS ONE. 2016;11(12): e0165721. https://doi.org/10.1371/journal.pone.0165721.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  92. Würfel FM, Wirtz RM, Winterhalter C, Taffurelli M, Santini D, Mandrioli A, et al. HLA-J, a non-pseudogene as a new prognostic marker for therapy response and survival in breast cancer. Geburtshilfe Frauenheilkd. 2020;80(11):1123–33. https://doi.org/10.1055/a-1128-6664.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  93. Ritter A, Hirschfeld M, Berner K, Rücker G, Jäger M, Weiss D, et al. Circulating non-coding RNA-biomarker potential in neoadjuvant chemotherapy of triple negative breast cancer? Int J Oncol. 2020;56(1):47–68. https://doi.org/10.3892/ijo.2019.4920.

    Article  CAS  PubMed  Google Scholar 

  94. Zheng A, Zhang L, Song X, Jin F. Clinical significance of SPRY4-IT1 in efficacy and survival prediction in breast cancer patients undergoing neoadjuvant chemotherapy. Histol Histopathol. 2020;35(4):361–70. https://doi.org/10.14670/hh-18-175.

    Article  CAS  PubMed  Google Scholar 

  95. Casey MC, Sweeney KJ, Brown JA, Kerin MJ. Exploring circulating micro-RNA in the neoadjuvant treatment of breast cancer. Int J Cancer. 2016;139(1):12–22. https://doi.org/10.1002/ijc.29985.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  96. Gu X, Xue JQ, Han SJ, Qian SY, Zhang WH. Circulating microRNA-451 as a predictor of resistance to neoadjuvant chemotherapy in breast cancer. Cancer Biomark. 2016;16(3):395–403. https://doi.org/10.3233/cbm-160578.

    Article  CAS  PubMed  Google Scholar 

  97. Liu B, Su F, Chen M, Li Y, Qi X, Xiao J, et al. Serum miR-21 and miR-125b as markers predicting neoadjuvant chemotherapy response and prognosis in stage II/III breast cancer. Hum Pathol. 2017;64:44–52. https://doi.org/10.1016/j.humpath.2017.03.016.

    Article  CAS  PubMed  Google Scholar 

  98. Liu B, Su F, Li Y, Qi X, Liu X, Liang W, et al. Changes of serum miR34a expression during neoadjuvant chemotherapy predict the treatment response and prognosis in stage II/III breast cancer. Biomed Pharmacother. 2017;88:911–7. https://doi.org/10.1016/j.biopha.2017.01.133.

    Article  CAS  PubMed  Google Scholar 

  99. Wang L, Wang B, Wen H, Mao J, Ren Y, Yang H. Exosomes: a rising star in breast cancer (Review). Oncol Rep. 2020;44(2):407–23. https://doi.org/10.3892/or.2020.7638.

    Article  CAS  PubMed  Google Scholar 

  100. Sueta A, Fujiki Y, Goto-Yamaguchi L, Tomiguchi M, Yamamoto-Ibusuki M, Iwase H, et al. Exosomal miRNA profiles of triple-negative breast cancer in neoadjuvant treatment. Oncol Lett. 2021;22(6):819. https://doi.org/10.3892/ol.2021.13080.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Funding

This work was supported by grants from the National Undergraduate Innovation Project of China (No. 202210486098).

Author information

Authors and Affiliations

Authors

Contributions

Conceptualization: W.Z., K.X., H.C.; writing—original: draft W.Z., K.X.; writing—review and editing: L.W., H.C; supervision: H.C. All authors have read and agreed to the published version of the manuscript.

Corresponding author

Correspondence to Honglei Chen.

Ethics declarations

Conflict of interest

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

Ethical approval (Research involving human participants and/or animals)

Not applicable.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhang, W., Xu, K., Li, Z. et al. Tumor immune microenvironment components and the other markers can predict the efficacy of neoadjuvant chemotherapy for breast cancer. Clin Transl Oncol 25, 1579–1593 (2023). https://doi.org/10.1007/s12094-023-03075-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12094-023-03075-y

Keywords

Navigation