December 2, 2025Scientific ReportsOpen Access

Transfer learning with multiomics integration and deep neural networks reveals drug resistance mechanisms in cancer

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Transfer learning predicts drug response in cancer, suggesting pathways for resistance to paclitaxel and gemcitabine.

Drug response predictions achieved strong performance based on area under the precision-recall curve analysis.
Pathway enrichment highlighted FYN-mediated focal adhesion as critical in paclitaxel resistance.
Analysis involved deep neural networks and transfer learning on the GDSC and TCGA datasets.
Findings underscore the role of somatic mutations and copy number aberrations in drug resistance mechanisms.

Alpsoy et al. (2025) studied this question.

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