Paclitaxel, the most commonly used form of
chemotherapy, is utilized in curative protocols in different types of
cancer. The response to treatment differs among patients. Biological interpretation of a mechanism to explain this personalized response is still unavailable. Since
paclitaxel is known to target BCL2 and TUBB1, we used pan-
cancer genomic data from hundreds of patients to show that a single-
nucleotide variant in the BCL2 sequence can predict a patient's response to
paclitaxel. Here, we show a connection between this BCL2 genomic variant, its transcript structure, and
protein abundance. We demonstrate these findings in silico, in vitro, in
formalin-fixed
paraffin-embedded (FFPE) tissue, and in patient lymphocytes. We show that
tumors with the specific variant are more resistant to
paclitaxel. We also show that
tumor and normal cells with the variant express higher levels of BCL2
protein, a phenomenon that we validated in an independent cohort of patients. Our results indicate BCL2 sequence variations as determinants of
chemotherapy resistance. The knowledge of individual BCL2 genomic sequences prior to the choice of
chemotherapy may improve patient survival. The current work also demonstrates the benefit of community-wide, integrative omics data sources combined with in-lab experimentation and validation sets.