DataSheet_1_Predictive and Prognostic Value of Selected MicroRNAs in Luminal Breast Cancer.docx (756.77 kB)

DataSheet_1_Predictive and Prognostic Value of Selected MicroRNAs in Luminal Breast Cancer.docx

Download (756.77 kB)
posted on 11.09.2019, 12:50 by Maria Amorim, João Lobo, Mário Fontes-Sousa, Helena Estevão-Pereira, Sofia Salta, Paula Lopes, Nuno Coimbra, Luís Antunes, Susana Palma de Sousa, Rui Henrique, Carmen Jerónimo

Breast cancer (BrC) is the most frequent malignancy and the leading cause of cancer death among women worldwide. Approximately 70% of BrC are classified as luminal-like subtype, expressing the estrogen receptor. One of the most common and effective adjuvant therapies for this BrC subtype is endocrine therapy. However, its effectiveness is limited, with relapse occurring in up to 40% of patients. Because microRNAs have been associated with several mechanisms underlying endocrine resistance and sensitivity, they may serve as predictive and/or prognostic biomarkers in this setting. Hence, the main goal of this study was to investigate whether miRNAs deregulated in endocrine-resistant BrC may be clinically relevant as prognostic and predictive biomarkers in patients treated with adjuvant endocrine therapy. A global expression assay allowed for the identification of microRNAs differentially expressed between luminal BrC patients with or without recurrence after endocrine adjuvant therapy. Then, six microRNAs were chosen for validation using quantitative reverse transcription polymerase chain reaction in a larger set of tissue samples. Thus, miR-30c-5p, miR-30b-5p, miR-182-5p, and miR-200b-3p were found to be independent predictors of clinical benefit from endocrine therapy. Moreover, miR-182-5p and miR-200b-3p displayed independent prognostic value for disease recurrence in luminal BrC patients after endocrine therapy. Our results indicate that selected miRNAs’ panels may constitute clinically useful ancillary tools for management of luminal BrC patients. Nevertheless, additional validation, ideally in a multicentric setting, is required to confirm our findings.