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Analysis of RPL37A, MTSS1, and HTRA1 expression as potential markers for pathologic complete response and survival

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Abstract

Background

Non-metastatic locally advanced breast carcinoma (LABC) treatment involves neoadjuvant chemotherapy (NCT). We evaluated the association of clinical–pathological data and immunoexpression of hormone receptors, HER2 and Ki67, and new biomarkers, RPL37A, MTSS1 and HTRA1, with pathological complete response (PCR) or tumour resistance (stable disease or disease progression), disease-free survival (DFS) and cancer-specific survival (CSS).

Methods

This is a retrospective study of 333 patients with LABC who underwent NCT. Expression of MTSS1, RPL37A and HTRA1/PRSS11 was evaluated by immunohistochemistry in TMA slides. Cutoff values were established for low and high tumour expression. ROC plotter evaluated response to NCT. Chi-square test for factors related to PCR, and Kaplan–Meier test and Cox model for factors related to DFS and CSS were prformed.

Results

The mean follow-up was 70.0 months and PCR rate was 15.6%. At 120 months, DFS rate was 32.5% and CSS rate was 67.1%. In multivariate analysis, there was an association between: (1) necrosis presence, intense inflammatory infiltrate, ER absence, HER2 molecular subtype and high RPL3A expression with increased odds of PCR; (2) lymph node involvement (LNI), high Ki67, low RPL37A and high HTRA1 expression with increased risk for NCT non-response; (3) LNI, high proliferation, necrosis absence, low RPL37A and high HTRA1 expression with increased recurrence risk; (4) advanced LNI, ER negative tumours, high HTRA1, low RPL37A expression and desmoplasia presence with higher risk of cancer death.

Conclusion

RPL37A is a potential biomarker for response to NCT and for prognosis. Additional studies evaluating HTRA1 and MTSS1 prognostic value are needed.

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References

  1. International Agency for Research on Cancer - World Health Organization. Cancer Today. Data visualization tools for exploring the global cancer burden in 2018. https://gco.iarc.fr/today/home. Accessed 15 august 2020

  2. Vieira RAC, Biller G, Uemura G, Ruiz CA, Curado MP. Breast cancer screening in developing countries. Clinics. 2017;72:244.

    Article  Google Scholar 

  3. Mauri D, Pavlidis N, Ioannidis JP. Neoadjuvant versus adjuvant systemic treatment in breast cancer: a meta-analysis. J Natl Cancer Inst. 2005;97:188–94.

    Article  Google Scholar 

  4. Gralow JR, Burstein HJ, Wood W, Hortobagyi GN, Gianni L, von Minckwitz G, et al. Preoperative therapy in invasive breast cancer: pathologic assessment and systemic therapy issues in operable disease. J Clin Oncol. 2008;26:814–9.

    Article  Google Scholar 

  5. Kaufmann M, von Minckwitz G, Mamounas EP, Cameron D, Carey LA, Cristofanilli M, et al. Recommendations from an international consensus conference on the current status and future of neoadjuvant systemic therapy in primary breast cancer. Ann Surg Oncol. 2012;19:1508–16.

    Article  Google Scholar 

  6. Kong X, Moran MS, Zhang N, Haffty B, Yang Q. Meta-analysis confirms achieving pathological complete response after neoadjuvant chemotherapy predicts favourable prognosis for breast cancer patients. Eur J Cancer. 2011;47:2084–90.

    Article  Google Scholar 

  7. Folgueira MA, Snitcovsky IM, Del Valle PR, Katayama ML, Brentani MM, Vieira RA. Transcriptional profile and response to neoadjuvant chemotherapy in breast cancer. Rev Assoc Med Bras. 2011;57:347–52.

    Article  Google Scholar 

  8. Folgueira MA, Carraro DM, Brentani H, Patrao DF, Barbosa EM, Netto MM, et al. Gene expression profile associated with response to doxorubicin-based therapy in breast cancer. Clin Cancer Res. 2005;11:7434–43.

    Article  CAS  Google Scholar 

  9. Chang JC, Wooten EC, Tsimelzon A, Hilsenbeck SG, Gutierrez MC, Elledge R, et al. Gene expression profiling for the prediction of therapeutic response to docetaxel in patients with breast cancer. Lancet. 2003;362:362–9.

    Article  CAS  Google Scholar 

  10. Bonnefoi H, Underhill C, Iggo R, Cameron D. Predictive signatures for chemotherapy sensitivity in breast cancer: are they ready for use in the clinic? Eur J Cancer. 2009;45:1733–43.

    Article  CAS  Google Scholar 

  11. Barros Filho MK, Katayama MLH, Brentani H, Abreu APS, Barbosa EM, Oliveira CT, Brentani MM, Folgueira MAAK. Gene trio signatures as molecular markers to predict response to doxorubicin cyclophosphamide neoadjuvant chemotherapy in breast cancer patients. Braz J Med Biol Res. 2010;43:1225–311.

    Article  CAS  Google Scholar 

  12. Zumbrunn J, Trueb B. Primary structure of a putative serine protease specific for IGF-binding proteins. FEBS Lett. 1996;398:187–92.

    Article  CAS  Google Scholar 

  13. Altobelli E, Marzioni D, Lattanzi A, Angeletti PM. Htr A1: Its future potential as a novel biomarker for cancer. Oncol Rep. 2015;34:555–66.

    Article  CAS  Google Scholar 

  14. Lehner A, Magdolen V, Schuster T, Kotzsch M, Kiechle M, Meindl A, et al. Downregulation of serine protease HTRA1 is associated with poor survival in breast cancer. PLoS ONE. 2013;8:e60359.

    Article  CAS  Google Scholar 

  15. Xie F, Ye L, Ta M, Zhang L, Jiang WG. MTSS1: a multifunctional protein and its role in cancer invasion and metastasis. Front Biosci (Schol Ed). 2011;3:621–31.

    Article  Google Scholar 

  16. Zhong J, Shaik S, Wan L, Tron AE, Wang Z, Sun L, et al. SCF beta-TRCP targets MTSS1 for ubiquitination-mediated destruction to regulate cancer cell proliferation and migration. Oncotarget. 2013;4:2339–533.

    Article  Google Scholar 

  17. Parr C, Jiang WG. Metastasis suppressor 1 (MTSS1) demonstrates prognostic value and anti-metastatic properties in breast cancer. Eur J Cancer. 2009;45:1673–83.

    Article  CAS  Google Scholar 

  18. Fowler CB, Man YG, Zhang S, O'Leary TJ, Mason JT, Cunningham RE. Tissue microarrays: construction and uses. Methods Mol Biol. 2011;724:23–35.

    Article  CAS  Google Scholar 

  19. Barros Filho MC, Katayama ML, Brentani H, Abreu AP, Barbosa EM, Oliveira CT, et al. Gene trio signatures as molecular markers to predict response to doxorubicin cyclophosphamide neoadjuvant chemotherapy in breast cancer patients. Braz J Med Biol Res. 2010;43:1225–311.

    Article  CAS  Google Scholar 

  20. Therasse P, Arbuck SG, Eisenhauer EA, Wanders J, Kaplan RS, Rubinstein L, et al. New guidelines to evaluate the response to treatment in solid tumors. European organization for research and treatment of cancer, National Cancer Institute of the United States, National Cancer Institute of Canada. J Natl Cancer Inst. 2000;92:205–16.

    Article  CAS  Google Scholar 

  21. Carey LA, Perou CM, Livasy CA, Dressler LG, Cowan D, Conway K, et al. Race, breast cancer subtypes, and survival in the Carolina Breast Cancer Study. JAMA. 2006;295:2492–502.

    Article  CAS  Google Scholar 

  22. Cheang MC, Chia SK, Voduc D, Gao D, Leung S, Snider J, et al. Ki67 index, HER2 status, and prognosis of patients with luminal B breast cancer. J Natl Cancer Inst. 2009;101:736–50.

    Article  CAS  Google Scholar 

  23. Fekete JT, Gyorffy B. ROCplot.org: Validating predictive biomarkers of chemotherapy/hormonal therapy/anti-HER2 therapy using transcriptomic data of 3,104 breast cancer patients. Int J Cancer. 2019;145:3140.

    Article  CAS  Google Scholar 

  24. Resende U, Cabello C, Oliveira Botelho Ramalho S, Zeferino LC. Predictors of pathological complete response in women with clinical complete response to neoadjuvant chemotherapy in breast carcinoma. Oncology. 2018;95:229–38.

    Article  CAS  Google Scholar 

  25. Yang D, Chen MB, Wang LQ, Yang L, Liu CY, Lu PH. Bcl-2 expression predicts sensitivity to chemotherapy in breast cancer: a systematic review and meta-analysis. J Exp Clin Cancer Res. 2013;32:105.

    Article  CAS  Google Scholar 

  26. Kim KI, Lee KH, Kim TR, Chun YS, Lee TH, Park HK. Ki-67 as a predictor of response to neoadjuvant chemotherapy in breast cancer patients. J Breast Cancer. 2014;17:40–6.

    Article  Google Scholar 

  27. Chen MB, Zhu YQ, Xu JY, Wang LQ, Liu CY, Ji ZY, et al. Value of TP53 status for predicting response to neoadjuvant chemotherapy in breast cancer: a meta-analysis. PLoS ONE. 2012;7:e39655.

    Article  CAS  Google Scholar 

  28. Colleoni M, Viale G, Goldhirsch A. Lessons on responsiveness to adjuvant systemic therapies learned from the neoadjuvant setting. Breast. 2009;18(Suppl 3):S137–S140140.

    Article  Google Scholar 

  29. Masuda H, Baggerly KA, Wang Y, Zhang Y, Gonzalez-Angulo AM, Meric-Bernstam F, et al. Differential response to neoadjuvant chemotherapy among 7 triple-negative breast cancer molecular subtypes. Clin Cancer Res. 2013;19:5533–40.

    Article  CAS  Google Scholar 

  30. Spring LM, Fell G, Arfe A, Sharma C, Greenup R, Reynolds KL, et al. Pathologic complete response after neoadjuvant chemotherapy and impact on breast cancer recurrence and survival: a comprehensive meta-analysis. Clin Cancer Res. 2020;26:2838–48.

    Article  Google Scholar 

  31. Bhargava R, Beriwal S, Dabbs DJ, Ozbek U, Soran A, Johnson RR, et al. Immunohistochemical surrogate markers of breast cancer molecular classes predicts response to neoadjuvant chemotherapy: a single institutional experience with 359 cases. Cancer. 2010;116:1431–9.

    Article  CAS  Google Scholar 

  32. Xie F, Ye L, Chen J, Wu N, Zhang Z, Yang Y, et al. The impact of metastasis suppressor-1, MTSS1, on oesophageal squamous cell carcinoma and its clinical significance. J Transl Med. 2011;9:95.

    Article  Google Scholar 

  33. Wang D, Xu MR, Wang T, Li T, Zhu J. MTSS1 overexpression correlates with poor prognosis in colorectal cancer. J Gastrointest Surg. 2011;15:1205–12.

    Article  Google Scholar 

  34. Filipits M, Rudas M, Jakesz R, Dubsky P, Fitzal F, Singer CF, et al. A new molecular predictor of distant recurrence in ER-positive, HER2-negative breast cancer adds independent information to conventional clinical risk factors. Clin Cancer Res. 2011;17:6012–20.

    Article  CAS  Google Scholar 

  35. Sobral RA, Honda ST, Katayama ML, Brentani H, Brentani MM, Patrao DF, et al. Tumor slices as a model to evaluate doxorubicin in vitro treatment and expression of trios of genes PRSS11, MTSS1, CLPTM1 and PRSS11, MTSS1, SMYD2 in canine mammary gland cancer. Acta Vet Scand. 2008;50:27.

    Article  Google Scholar 

  36. Wang D, Feng J, Xu B. A meta-analysis of platinum-based neoadjuvant chemotherapy versus standard neoadjuvant chemotherapy for triple-negative breast cancer. Future Oncol. 2019;15:2779.

    Article  CAS  Google Scholar 

  37. Gianni L, Pienkowski T, Im YH, Roman L, Tseng LM, Liu MC, et al. Efficacy and safety of neoadjuvant pertuzumab and trastuzumab in women with locally advanced, inflammatory, or early HER2-positive breast cancer (neosphere): a randomised multicentre, open-label, phase 2 trial. Lancet Oncol. 2012;13:25–322.

    Article  CAS  Google Scholar 

  38. Wuerstlein R, Harbeck N. Neoadjuvant therapy for HER2-positive breast cancer. Rev Recent Clin Trials. 2017;12:81–92.

    Article  CAS  Google Scholar 

  39. Penault-Llorca F, Abrial C, Raoelfils I, Cayre A, Mouret-Reynier MA, Leheurteur M, et al. Comparison of the prognostic significance of Chevallier and Sataloff's pathologic classifications after neoadjuvant chemotherapy of operable breast cancer. Hum Pathol. 2008;39:1221–8.

    Article  Google Scholar 

  40. Pinder SE, Brown JP, Gillett C, Purdie CA, Speirs V, Thompson AM, et al. The manufacture and assessment of tissue microarrays: suggestions and criteria for analysis, with breast cancer as an example J. Clin Pathol. 2013;66:169–77.

    Article  CAS  Google Scholar 

  41. Hayes DF, Ethier S, Lippman ME. New guidelines for reporting of tumor marker studies in breast cancer research and treatment: REMARK. Breast Cancer Res Treat. 2006;100:237–8.

    Article  Google Scholar 

Download references

Funding

This study was funded by FAPESP (2012/19642-0). MAAKF received a research productivity grant from CNPq, agência do Ministério da Ciência, Tecnologia, Inovações e Comunicações (MCTIC).

Author information

Authors and Affiliations

  1. Programa de Pós-Graduação em Oncologia, Hospital de Câncer de Barretos, Rua Antenor Duarte Villela, 1331, Bairro Dr Paulo Prata, Barretos, São Paulo, 14.784-400, Brasil

    Guilherme Freire Angotti Carrara, Adriane Feijo Evangelista, Cristovam Scapulatempo-Neto & René Aloisio da Costa Vieira

  2. Centro de Pesquisa Molecular em Oncologia, Hospital de Câncer de Barretos, Barretos, Brasil

    Adriane Feijo Evangelista

  3. Departamento de Patologia, Hospital de Câncer de Barretos, Barretos, Brasil

    Cristovam Scapulatempo-Neto, Lucas Faria Abrahão-Machado, Mariana Andozia Morini & Ligia Maria Kerr

  4. Programa de Pós-Graduação em Oncologia, Departamento de Radiologia e Oncologia, Faculdade de Medicina, FMUSP Universidade de São Paulo, FMUSP, São Paulo, Brasil

    Maria Aparecida Azevedo Koike Folgueira

  5. Programa de Pós-Graduação em Ginecologia, Obstetricia e Mastologia, Faculdade de Medicina de Botucatu/UNESP, Botucatu, São Paulo, Brasil

    René Aloisio da Costa Vieira

Authors
  1. Guilherme Freire Angotti Carrara
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  2. Adriane Feijo Evangelista
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  3. Cristovam Scapulatempo-Neto
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  4. Lucas Faria Abrahão-Machado
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  5. Mariana Andozia Morini
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  6. Ligia Maria Kerr
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  7. Maria Aparecida Azevedo Koike Folgueira
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  8. René Aloisio da Costa Vieira
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Corresponding author

Correspondence to René Aloisio da Costa Vieira.

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Conflict of interest

The author Vieira RAC received research grants from FAPESP, but he declares no conflict of interest. Folgueira MAAK received grants from CNPQ, but she declares no conflict of interest. All the other authors (Carrara GFA; Evangelista AF; Scapulatempo-Neto C; Abrahão-Machado LF; Morini MA and Kerr LM) declare no conflict of interest.

Ethical approval

The Barretos Cancer Hospital Ethics Committee approved this study (number 135/2008 from 21/02/2008 and addendum 19/03/2012). All procedures performed were in accordance with the ethical standards of the institutional and national research committee (Barretos Cancer Hospital Ethics Committee). They were performed in accordance with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.

Informed consent

As it was a retrospective study, informed consent was considered not necessary from the local ethics committee. There are global statistics, and the confidentiality of the patients was preserved.

Remark

REMARK recommendations were followed [41].

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Carrara, G.F.A., Evangelista, A.F., Scapulatempo-Neto, C. et al. Analysis of RPL37A, MTSS1, and HTRA1 expression as potential markers for pathologic complete response and survival. Breast Cancer 28, 307–320 (2021). https://doi.org/10.1007/s12282-020-01159-z

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