Potential biomarkers as a predictive factor of response to primary chemotherapy in breast cancer patients

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.

Validation of the online PREDICT tool in a cohort of early breast cancer in Brazil

PREDICT is a tool designed to estimate the benefits of adjuvant therapy and the overall survival of women with early breast cancer. The model uses clinical, histological, and immunohistochemical variables. This study aimed to evaluate the model's performance in a Brazilian population. We assessed the discrimination and calibration of the PREDICT model to estimate overall survival (OS) in five and ten years of follow-up in a cohort of 873 women with early breast cancer diagnosed from January 2001 to December 2016. A total of 743 patients had estrogen receptor (ER)-positive and 130 had ER-negative tumors. The area under the receiver operating characteristic (ROC) curve (AUC) for discrimination was 0.72 (95%CI: 0.66-0.78) at five years and 0.67 (95%CI: 0.61-0.72) at ten years for women with ER-positive tumors. The AUC was 0.72 (95%CI: 0.62-0.81) at five years and 0.67 (95%CI: 0.54-0.77) at ten years for women with ER-negative tumors. The predicted survival in ER-positive tumors was 91.0% (95%CI: 90.2-91.6%) at five years and 79.3% (95%CI: 77.7-81.0%) at ten years, and the observed survival 90.7% (95%CI: 88.6-92.9%) and 77.2% (95%CI: 73.4-81.4%), respectively. The predicted survival in ER-negative tumors was 84.5% (95%CI: 82.5-86.6%) at five years and 75.0% (95%CI: 71.6-78.5%) at ten years, and the observed survival 76.3% (95%CI: 69.1-84.3%) and 67.9% (95%CI: 58.6-78.6%), respectively. In conclusion, PREDICT was accurate to estimate OS in women with ER-positive tumors and overestimated the OS in women with ER-negative tumors.