Epidemiological characterization of hormonal receptor profiles and associated histopathological characteristics in Rwandan women with breast cancer: a retrospective study

Abstract

Background Breast cancer is the most common cancer in women worldwide and the second leading cause of cancer mortality in Rwanda. The knowledge of hormonal receptors and Human Epidermal growth factor Receptor -2 (Her-2/Neu) profile remains crucial in the management of breast cancer, even in this –omics era. However, Immunohistochemistry staining and practice remains scarce in many hospital settings, especially in LMICS including Rwanda. This study aimed at determining the distribution of breast cancer molecular subtypes, and associated clinical outcome in Rwandan women. Methodology This study combined method consisting of an initial hospital-based epidemiological retrospective design to document the epidemiological data for breast cancer patients in Rwanda from January 2014 to June 2021. Records of patients with confirmed breast cancer were documented from 4 cancer centers of excellence in Rwanda. Results A high number of participants expressed estrogen receptor positive (55.6%) and HER2 was the lowest expressed receptor (33.1%). The triple negative breast cancer (TNBC) was more prevalent (37%), followed by luminal A (26%), HER2-enriched (24%) and luminal B (13%). These subtypes were found significantly different with regards to menopausal status, histological grades and hormonal therapy (p<0.0001). Conclusion This study revealed that patients who got treatment, especially hormonal therapy have much more chances of living than those who haven’t gone under treatment. Moreover, aggressive histological type and grade were also overexpressed. These suggest the introduction of other targeted therapies, and inclusion of ‘omic’ technologies necessary to individual characteristics of molecular landscape to manage breast cancer patients, especially TNBC patients. Future research on genetic characterization using genomic sequencing will shed light on the associated variant genes for breast cancer personalized medicine.