FACING THE ENEMY: MIRNAS 19B-3P AND 146A-5P AS POTENTIAL BIOMARKERS OF DOXORUBICIN RESISTANCE IN TRIPLE NEGATIVE BREAST CANCER

MORO J; DUCA RB; GRAÑA K; DE LUCA P; DE SIERVI A

MAR DEL PLATA

Congreso; 67 Reunión Anual SAIC; 2022

Breast Cancer (BCa) is the most prevalent global malignancy and one of the leading causes of cancer deaths. Despite the novel therapies, resistance to chemotherapeutic drugs is a major challenge for effective therapy. Doxorubicin is a drug that is vastly used for BCa treatment which makes it an interesting target for the study of drug resistance. MiRNAs are short non-coding RNAs that act as post-transcriptional regulators of gene expression. Our aim was to identify a panel of miRNAs as possible biomarkers for doxorubicin resistance in triple negative breast cancer (TNBC) cells. Initially, we determined the IC50 to doxorubicin from several human and murine TNBC cell lines using MTS assays. Afterward, the expression levels of a panel of miRNAs were measured by RT-qPCR. This panel was selected based on previous results from our lab and bibliography. We have selected the most sensitive cell line, 4T1 (IC50= 0.33+ 0.08) to generate a doxorubicin-resistant variant cell line (4T1DR) by chronic exposition to sublethal increasing doses of doxorubicin for 8 months. We found that 4T1DR showed 4 times higher IC50 compared to control cells (4T1DR, IC50= 1.37 + 0.11). We have determined miRNAs expression of these cells (4T1DR and 4T1 control) by RT-qPCR. We have found significantly up-regulation of miR-19b-3p and miR-146a-5p expression levels in 4T1DR in comparison to 4T1 control cells. These miRNAs are implicated in several KEGG pathways related to cancer and drug resistance such as p53 signaling, cell cycle, and apoptosis. In addition, miR-146a-5p is upregulated in BCa tissue compared to normal adjacent tissue in one cohort of 16 paired samples (GSE97811). We have found miR-19b-3p expression levels increase in the plasma of BCa patients compared to healthy donors (GSE 73002, N=1280 per group). The results obtained so far are a promising landscape for finding an effective way to predict the failure of chemotherapy and eventually, inhibit drug resistance.