Skip to main content

Advertisement

SpringerLink
Log in

Predictive significance of HIF-1α, Snail, and PD-L1 expression in breast cancer

  • Research
  • Published:
Clinical and Experimental Medicine Aims and scope Submit manuscript

Abstract

Currently, the prediction of breast cancer (BC) effectiveness to drug treatment is based on determining the expression level of steroid hormone receptors and human epidermal growth factor receptor type 2 (HER2). However, significant differences in individual response to drug treatment require the search for new predictive markers. Here, by comprehensively examining HIF-1α, Snail, and PD-L1 expression in BC tumor tissue, we demonstrate that high levels of these markers correlate with unfavorable factors of BC prognosis: the presence of regional and distant metastases and lymphovascular and perineural invasion. Analyzing the predictive significance of markers, we show that the most significant predictors of chemoresistant HER2-negative BC are a high PD-L1 level and a low Snail level, while in HER2-positive BC, only a high PD-L1 level is an independent predictor of chemoresistant BC. Our results suggest that using immune checkpoint inhibitors in these groups of patients may improve drug therapy effectiveness.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

Data availability

The datasets generated and analyzed during the current study are available from the corresponding author on reasonable request.

References

  1. WHO. Breast cancer. https://www.who.int/news-room/fact-sheets/detail/breast-cancer

  2. 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 

  3. Tarighati E, Keivan H, Mahani H. A review of prognostic and predictive biomarkers in breast cancer. Clin Exp Med. 2022. https://doi.org/10.1007/s10238-021-00781-1.

    Article  PubMed  Google Scholar 

  4. Nie C, Lv H, Bie L, Hou H, Chen X. Hypoxia-inducible factor 1-alpha expression correlates with response to neoadjuvant chemotherapy in women with breast cancer. Medicine (Baltimore). 2018;97(51):e13551. https://doi.org/10.1097/MD.0000000000013551.

    Article  CAS  PubMed  Google Scholar 

  5. Cai F, Xiao H, Sun Y, Wang D, Tang J. Expression of snail and E-cadherin in drug-resistant MCF-7/ADM breast cancer cell strains. J Coll Physicians Surg Pak. 2019;29(3):240–4. https://doi.org/10.29271/jcpsp.2019.03.240.

    Article  PubMed  Google Scholar 

  6. Zhang J, Zhang S, Gao S, Ma Y, Tan X, Kang Y, Ren W. HIF-1α, TWIST-1 and ITGB-1, associated with tumor stiffness, as novel predictive markers for the pathological response to neoadjuvant chemotherapy in breast cancer. Cancer Manag Res. 2020;12:2209–22. https://doi.org/10.2147/CMAR.S246349.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Jing X, Yang F, Shao C, Wei K, Xie M, Shen H, Shu Y. Role of hypoxia in cancer therapy by regulating the tumor microenvironment. Mol Cancer. 2019;18(1):157. https://doi.org/10.1186/s12943-019-1089-9.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Messeha SS, Zarmouh NO, Soliman KFA. Polyphenols modulating effects of PD-L1/PD-1 checkpoint and EMT-mediated PD-L1 overexpression in breast cancer. Nutrients. 2021;13(5):1718. https://doi.org/10.3390/nu13051718.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Jiang Y, Zhan H. Communication between EMT and PD-L1 signaling: new insights into tumor immune evasion. Cancer Lett. 2020;468:72–81. https://doi.org/10.1016/j.canlet.2019.10.013.

    Article  CAS  PubMed  Google Scholar 

  10. Sahoo S, Nayak SP, Hari K, Purkait P, Mandal S, Kishore A, et al. Immunosuppressive traits of the hybrid epithelial/mesenchymal phenotype. Front Immunol. 2021;12:797261. https://doi.org/10.3389/fimmu.2021.797261.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. 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 

  12. Brierley J, Gospodarowicz M. K. (Mary K.), Wittekind, Ch. (Christian) (2017). TNM classification of malignant tumors (8th edition) Oxford, UK ; Hoboken, NJ : Wiley, 2017. ISBN 9781119263548 (Adobe PDF)

  13. Ogston KN, Miller ID, Payne S, Hutcheon AW, Sarkar TK, Smith I, et al. A new histological grading system to assess response of breast cancers to primary chemotherapy: prognostic significance and survival. Breast. 2003;12(5):320–7. https://doi.org/10.1016/s0960-9776(03)00106-1.

    Article  PubMed  Google Scholar 

  14. Yang X, Rao J, Yang W, Shui R. Evaluation of the predictive and prognostic values of stromal tumor-infiltrating lymphocytes in HER2-positive breast cancers treated with neoadjuvant chemotherapy. Target Oncol. 2018;13(6):757–67. https://doi.org/10.1007/s11523-018-0602-1.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Wang L, Luo R, Lu Q, Jiang K, Hong R, Lee K, et al. Miller-payne grading and 70-gene signature are associated with prognosis of hormone receptor-positive, human epidermal growth factor receptor 2-negative early-stage breast cancer after neoadjuvant chemotherapy. Front Oncol. 2021;11:735670. https://doi.org/10.3389/fonc.2021.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Chang HY, Tseng YK, Chen YC, Shu CW, Lin MI, Liou HH, et al. High snail expression predicts a poor prognosis in breast invasive ductal carcinoma patients with HER2/EGFR-positive subtypes. Surg Oncol. 2018;27(2):314–20. https://doi.org/10.1016/j.suronc.2018.05.002.

    Article  PubMed  Google Scholar 

  17. Luo M, Clouthier SG, Deol Y, Liu S, Nagrath S, Azizi E, Wicha MS. Breast cancer stem cells: current advances and clinical implications. Methods Mol Biol. 2015;1293:1–49. https://doi.org/10.1007/978-1-4939-2519-3_1.

    Article  PubMed  Google Scholar 

  18. Zhang C, Samanta D, Lu H, Bullen JW, Zhang H, Chen I, et al. Hypoxia induces the breast cancer stem cell phenotype by HIF-dependent and ALKBH5-mediated m6A-demethylation of NANOG mRNA. Proc Natl Acad Sci USA. 2016;113(14):E2047–56. https://doi.org/10.1073/pnas.1602883113.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Mansour FA, Al-Mazrou A, Al-Mohanna F, Al-Alwan M, Ghebeh H. PD-L1 is overexpressed on breast cancer stem cells through notch3/mTOR axis. Oncoimmunology. 2020;9(1):1729299. https://doi.org/10.1080/2162402X.2020.1729299.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Gooding AJ, Schiemann WP. Epithelial-mesenchymal transition programs and cancer stem cell phenotypes: mediators of breast cancer therapy resistance. Mol Cancer Res. 2020;18(9):1257–70. https://doi.org/10.1158/1541-7786.MCR-20-0067.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Chen J, Liu S, Su Y, Zhang X. ALDH1+ stem cells demonstrate more stem cell-like characteristics than CD44+/CD24-/low stem cells in different molecular subtypes of breast cancer. Transl Cancer Res. 2020;9(3):1652–9. https://doi.org/10.21037/tcr.2020.01.53.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Li D, Li L, Yang W, Chen L, Chen X, Wang Q, Hao B, Jin W, Cao Y. Prognostic values of SNAI family members in breast cancer patients. Ann Transl Med. 2020;8(15):922. https://doi.org/10.21037/atm-20-681.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Khadri FZ, Issac MSM, Gaboury LA. Impact of epithelial-mesenchymal transition on the immune landscape in breast cancer. Cancers (Basel). 2021;13(20):5099. https://doi.org/10.3390/cancers13205099.

    Article  CAS  PubMed  Google Scholar 

  24. Saitoh M. Involvement of partial EMT in cancer progression. J Biochem. 2018;164(4):257–64. https://doi.org/10.1093/jb/mvy047.

    Article  CAS  PubMed  Google Scholar 

  25. Fabisiewicz A, Szostakowska-Rodzos M, Zaczek AJ, Grzybowska EA. Circulating tumor cells in early and advanced breast cancer; biology and prognostic value. Int J Mol Sci. 2020;21(5):1671. https://doi.org/10.3390/ijms21051671.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Kurozumi S, Inoue K, Matsumoto H, Fujii T, Horiguchi J, Oyama T, et al. Clinicopathological values of PD-L1 expression in HER2-positive breast cancer. Sci Rep. 2019;9(1):16662. https://doi.org/10.1038/s41598-019-52944-6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Catacchio I, Silvestris N, Scarpi E, Schirosi L, Scattone A, Mangia A. Intratumoral, rather than stromal, CD8+ T cells could be a potential negative prognostic marker in invasive breast cancer patients. Transl Oncol. 2019;12(3):585–95. https://doi.org/10.1016/j.tranon.2018.12.005.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Evangelou Z, Papoudou-Bai A, Karpathiou G, Kourea H, Kamina S, Goussia A, et al. PD-L1 expression and tumor-infiltrating lymphocytes in breast cancer: clinicopathological analysis in women younger than 40 years old. In Vivo. 2020;34(2):639–47. https://doi.org/10.21873/invivo.11818.

    Article  PubMed  PubMed Central  Google Scholar 

  29. Hong M, Kim JW, Kim MK, Chung BW, Ahn SK. Programmed cell death-ligand 1 expression in stromal immune cells is a marker of breast cancer outcome. J Cancer. 2020;11(24):7246–52. https://doi.org/10.7150/jca.50441.

    Article  PubMed  PubMed Central  Google Scholar 

  30. Cirqueira MB, Mendonça CR, Noll M, Soares LR, dePaulaCarneiroCysneiros MA, Paulinelli RR, et al. Prognostic role of PD-L1 expression in invasive breast cancer a systematic review and meta-analysis. Cancers (Basel). 2021;13(23):6090. https://doi.org/10.3390/cancers13236090.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Du Q, Che J, Jiang X, Li L, Luo X, Li Q. PD-L1 acts as a promising immune marker to predict the response to neoadjuvant chemotherapy in breast cancer patients. Clin Breast Cancer. 2020;20(1):e99–111. https://doi.org/10.1016/j.clbc.2019.06.014.

    Article  CAS  PubMed  Google Scholar 

  32. Stovgaard ES, Dyhl-Polk A, Roslind A, Balslev E, Nielsen D. PD-L1 expression in breast cancer: expression in subtypes and prognostic significance: a systematic review. Breast Cancer Res Treat. 2019;174(3):571–84. https://doi.org/10.1007/s10549-019-05130-1.

    Article  CAS  PubMed  Google Scholar 

  33. Almozyan S, Colak D, Mansour F, Alaiya A, Al-Harazi O, Qattan A, et al. PD-L1 promotes OCT4 and Nanog expression in breast cancer stem cells by sustaining PI3K/AKT pathway activation. Int J Cancer. 2017;141(7):1402–12. https://doi.org/10.1002/ijc.30834.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Zhang X, Wang D, Liu Z, Wang Z, Li Q, Xu H, et al. The diagnostic accuracy of magnetic resonance imaging in predicting pathologic complete response after neoadjuvant chemotherapy in patients with different molecular subtypes of breast cancer. Quant Imag Med Surg. 2020;10(1):197–210. https://doi.org/10.21037/qims.2019.11.16.

    Article  Google Scholar 

  35. von Waldenfels G, Loibl S, Furlanetto J, Machleidt A, Lederer B, Denkert C, et al. Outcome after neoadjuvant chemotherapy in elderly breast cancer patients—a pooled analysis of individual patient data from eight prospectively randomized controlled trials. Oncotarget. 2018;9(20):15168–79. https://doi.org/10.18632/oncotarget.24586.

    Article  Google Scholar 

  36. von Minckwitz G, Darb-Esfahani S, Loibl S, Huober J, Tesch H, Solbach C, et al. Responsiveness of adjacent ductal carcinoma in situ and changes in HER2 status after neoadjuvant chemotherapy/trastuzumab treatment in early breast cancer–results from the GeparQuattro study (GBG 40). Breast Cancer Res Treat. 2012;132(3):863–70. https://doi.org/10.1007/s10549-011-1621-0.

    Article  CAS  Google Scholar 

  37. Pu S, Wang K, Liu Y, Liao X, Chen H, He J, Zhang J. Nomogram-derived prediction of pathologic complete response (pCR) in breast cancer patients treated with neoadjuvant chemotherapy (NCT). BMC Cancer. 2020;20(1):1120. https://doi.org/10.1186/s12885-020-07621-7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Zhang J, Xiao L, Pu S, Liu Y, He J, Wang K. Can we reliably identify the pathological outcomes of neoadjuvant chemotherapy in patients with breast cancer? Development and validation of a logistic regression nomogram based on preoperative factors. Ann Surg Oncol. 2021;28(5):2632–45. https://doi.org/10.1245/s10434-020-09214-x.

    Article  PubMed  Google Scholar 

  39. Xu W, Chen X, Deng F, Zhang J, Zhang W, Tang J. Predictors of neoadjuvant chemotherapy response in breast cancer: a review. Onco Targets Ther. 2020;13:5887–99. https://doi.org/10.2147/OTT.S253056.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Li C, Ma RZ, Han GY, Guo YH, Zhang YN, Zhang YT, et al. A potential predictive biomarker for miller/payne grading: PD-L1 expression before neoadjuvant chemotherapy in breast cancer. Oncol Res Treat. 2020;43(11):573–83. https://doi.org/10.1159/000508139.

    Article  CAS  PubMed  Google Scholar 

  41. 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 

  42. Asano Y, Kashiwagi S, Goto W, Takada K, Takahashi K, Morisaki T, et al. Prediction of treatment responses to neoadjuvant chemotherapy in triple-negative breast cancer by analysis of immune checkpoint protein expression. J Transl Med. 2018;16(1):87. https://doi.org/10.1186/s12967-018-1458-y.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Frank GA, Kuznetsova OA, Zavalishina LE, Andreeva YY, Olyushina EM, Vinogradov IY, et al. PD-L1-status raka molochnoĭ zhelezy [PD-L1 status in breast cancer]. Arkh Patol. 2019;81(2):3–9. Russian. https://doi.org/10.17116/patol2019810213.

  44. Gao L, Guo Q, Li X, Yang X, Ni H, Wang T, et al. MiR-873/PD-L1 axis regulates the stemness of breast cancer cells. EBioMedicine. 2019;41:395–407. https://doi.org/10.1016/j.ebiom.2019.02.034.

    Article  PubMed  PubMed Central  Google Scholar 

  45. Nanda R, Liu MC, Yau C, Shatsky R, Pusztai L, Wallace A, et al. Effect of pembrolizumab plus neoadjuvant chemotherapy on pathologic complete response in women with early-stage breast cancer: an analysis of the ongoing phase 2 adaptively randomized I-SPY2 trial. JAMA Oncol. 2020;6(5):676–84. https://doi.org/10.1001/jamaoncol.2019.6650.

    Article  PubMed  Google Scholar 

  46. Marinelli D, Mazzotta M, Pizzuti L, Krasniqi E, Gamucci T, Natoli C, et al. Neoadjuvant immune-checkpoint blockade in triple-negative breast cancer: current evidence and literature-based meta-analysis of randomized trials. Cancers (Basel). 2020;12(9):2497. https://doi.org/10.3390/cancers12092497.

    Article  CAS  PubMed  Google Scholar 

Download references

Funding

The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.

Author information

Author notes

  1. Evgenia Zubareva, Marina Senchukova and Tatyana Karmakova have contributed equally to this work.

Authors and Affiliations

  1. Mammological Center, Orenburg Regional Clinical Oncology Center, Orenburg, Orenburg Region, Russian Federation, 460021

    Evgenia Zubareva

  2. Department of Oncology, Orenburg State Medical University, Orenburg, Orenburg Region, Russian Federation, 460000

    Marina Senchukova

  3. Department of Predicting the Effectiveness of Conservative Therapy, P.A. Herzen Moscow Oncology Research Institute, Branch of the National Medical Research Radiological Center of the Ministry of Health of Russian Federation, Moscow, Moscow Region, Russian Federation, 125284

    Tatyana Karmakova

Authors
  1. Evgenia Zubareva
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Marina Senchukova
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Tatyana Karmakova
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Marina Senchukova.

Ethics declarations

Competing interests

The authors declare no competing interests.

Ethics approval

The study was performed in accordance with the Helsinki Declaration and internationally recognized guidelines. The protocol was approved by the Institutional Review Board of the Orenburg State Medical University (Protocol No. 234 of September 23, 2019).

Additional information

Publisher's Note

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

Supplementary Information

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

Zubareva, E., Senchukova, M. & Karmakova, T. Predictive significance of HIF-1α, Snail, and PD-L1 expression in breast cancer. Clin Exp Med 23, 2369–2383 (2023). https://doi.org/10.1007/s10238-023-01026-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10238-023-01026-z

Keywords

Search

Navigation