Analysis of Increased EGFR and IGF-1R Signaling and Its Correlation with Socio-Epidemiological Features and Biological Profile in Breast Cancer Patients: A Study in Northern Brazil - Silva Rocha F (Dove Medical Press, 2021)
Francianne Silva Rocha,1,* Jersey Heitor da Silva Maués,2,3,* Cynthia Mara Brito Lins Pereira,4 Caroline Aquino Moreira-Nunes,5 Rommel Mário Rodriguez Burbano2,3 1Mastology Department, Ophir Loyola Hospital, Belém, PA, Brazil; 2Laboratory of Molecular Biology, Ophir Loyola Hospital, Belém, PA, Brazil; 3Laboratory of Human Cytogenetics, Institute of Biological Sciences, Federal University of Pará, Belém, PA, Brazil; 4Oncology Research Center, Hospital Universitário João De Barros Barreto, Belém, PA, Brazil; 5Laboratory of Pharmacogenetics, Drug Research and Development Center (NPDM), Federal University of Ceará, Fortaleza, CE, Brazil*These authors contributed equally to this workCorrespondence: Caroline Aquino Moreira-NunesLaboratory of Pharmacogenetics, Drug Research and Development Center (NPDM), Federal University of Ceará, Coronel Nunes De Melo St, n 1000, Rodolfo Teófilo, CEP: 60416-000, Fortaleza, CE, BrazilTel +55 85333668033Email carolfam@gmail.comIntroduction: Breast cancer (BC) is the second most frequent cancer worldwide. It is known that a subset of BC has amplification, and overexpression of the epidermal growth factor receptor (EGFR) and high expression of the insulin-like growth factor receptor-1 (IGF-1R) are correlated with a favorable prognosis. This study aimed to evaluate the prognostic and predictive values of the EGFR and IGF-1R in tumor samples from patients with BC and their correlation with socio-epidemiological features.Patients and Methods: We analyzed socio-epidemiological, clinical–pathological data and tumor tissues from 124 patients with BC undergoing treatment, to assess levels of EGFR and IGF-1R mRNA and protein. The predictive performance included the calculation of area-under-the-curve (AUC) to discriminate groups of patients with high and low mRNA expression associated with survival analysis within each molecular group of BC.Results: We found a significant expression increase (p < 0.001) in EGFR associated with body mass index, angiolymphatic invasion, compromised lymph nodes and follow-up in 58.1% of the triple-negative and HER overexpression tumors. The increase in IGF-IR was significant (p < 0.001) in 41.9% of luminal tumors A and B. ROC analysis showed that EGFR had a higher predictive performance (AUC = 0.891) than IGF-1R (AUC = 0.60). The Kaplan–Meier analysis indicated that only the high expression of EGFR was associated with a decreased probability of survival for patients, what did not happen with IGF-1R.Conclusion: Our results suggest that EGFR and IGF-1R expression patterns associated with the clinical characteristics of patients and biological profile influenced the evolution of BC.Keywords: breast cancer, hormonal receptors, EGFR, IGF-IR, predictive performance