RESUMO
In this study, we identified miRNAs and their potential mRNA targets that are intricately linked to primary chemotherapy response in patients with invasive ductal carcinomas. A cohort of individuals diagnosed with advanced invasive breast ductal carcinoma who underwent primary chemotherapy served as the cornerstone of our study. We conducted a comparative analysis of microRNA expression among patients who either responded or did not respond to primary systemic therapy. To analyze the correlation between the expression of the whole transcriptome and the 24 differentially expressed (DE) miRNAs, we harnessed the extensive repository of The Cancer Genome Atlas (TCGA) database. We mapped molecular mechanisms associated with these miRNAs and their targets from TCGA breast carcinomas. The resultant expression profile of the 24 DE miRNAs emerged as a potent and promising predictive model, offering insights into the intricate dynamics of chemotherapy responsiveness of advanced breast tumors. The discriminative analysis based on the principal component analysis identified the most representative miRNAs across breast cancer samples (miR-210, miR-197, miR-328, miR-519a, and miR-628). Moreover, the consensus clustering generated four possible clusters of TCGA patients. Further studies should be conducted to advance these findings.
Assuntos
Biomarcadores Tumorais , Neoplasias da Mama , Carcinoma Ductal de Mama , MicroRNAs , Humanos , Neoplasias da Mama/tratamento farmacológico , Neoplasias da Mama/genética , Feminino , MicroRNAs/análise , Biomarcadores Tumorais/análise , Carcinoma Ductal de Mama/tratamento farmacológico , Carcinoma Ductal de Mama/genética , Carcinoma Ductal de Mama/patologia , Pessoa de Meia-Idade , Perfilação da Expressão Gênica , Regulação Neoplásica da Expressão Gênica , Adulto , Idoso , TranscriptomaRESUMO
In this study, we identified miRNAs and their potential mRNA targets that are intricately linked to primary chemotherapy response in patients with invasive ductal carcinomas. A cohort of individuals diagnosed with advanced invasive breast ductal carcinoma who underwent primary chemotherapy served as the cornerstone of our study. We conducted a comparative analysis of microRNA expression among patients who either responded or did not respond to primary systemic therapy. To analyze the correlation between the expression of the whole transcriptome and the 24 differentially expressed (DE) miRNAs, we harnessed the extensive repository of The Cancer Genome Atlas (TCGA) database. We mapped molecular mechanisms associated with these miRNAs and their targets from TCGA breast carcinomas. The resultant expression profile of the 24 DE miRNAs emerged as a potent and promising predictive model, offering insights into the intricate dynamics of chemotherapy responsiveness of advanced breast tumors. The discriminative analysis based on the principal component analysis identified the most representative miRNAs across breast cancer samples (miR-210, miR-197, miR-328, miR-519a, and miR-628). Moreover, the consensus clustering generated four possible clusters of TCGA patients. Further studies should be conducted to advance these findings.