Genomic signatures for paclitaxel and gemcitabine resistance in breast cancer derived by machine learning

Increasingly, the effectiveness of adjuvant chemotherapy agents for breast cancer has been related to changes in the genomic profile of tumors. We investigated correspondence between growth inhibitory concentrations of paclitaxel and gemcitabine (GI50) and gene copy number, mutation, and expression first in breast cancer cell lines and then in patients. Genes encoding direct targets of these drugs, metabolizing enzymes, transporters, and those previously associated with chemoresistance to paclitaxel (n=31 genes) or gemcitabine (n=18) were analyzed.
Source: Molecular Oncology - Category: Cancer & Oncology Authors: Source Type: research