PubMed · 15338757
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Armando Santoro, Luca Castagna, Massimo Magagnoli. 2003. Lymphomas.. https://pubmed.ncbi.nlm.nih.gov/15338757/
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Drug response differs substantially in cancer patients due to inter- and intra-tumor heterogeneity. Particularly, transcriptome context, especially tumor microenvironment, has been shown playing a significant role in shaping the actual treatment outcome. In this study, we develop a deep variational autoencoder (VAE) model to compress thousands of genes into latent vectors in a low-dimensional space. We then demonstrate that these encoded vectors could accurately impute drug response, outperform standard signature-gene based approaches, and appropriately control the overfitting problem. We apply rigorous quality assessment and validation, including assessing the impact of cell line lineage, cross-validation, cross-panel evaluation, and application in independent clinical data sets, to warrant the accuracy of the imputed drug response in both cell lines and cancer samples. Specifically, the expression-regulated component (EReX) of the observed drug response achieves high correlation across panels. Using the well-trained models, we impute drug response of The Cancer Genome Atlas data and investigate the features and signatures associated with the imputed drug response, including cell line origins, somatic mutations and tumor mutation burdens, tumor microenvironment, and confounding factors. In summary, our deep learning method and the results are useful for the study of signatures and markers of drug response.
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BACKGROUND: The platelet-derived growth factor receptor (PDFG-r), a tyrosine kinase, is expressed in 88% of primary prostate cancer and in 80% of the metastases. The tyrosine kinase inhibitor imatinib blocks the PDGF signaling pathway by inhibiting PDGF-r autophosphorylation. We examined the cytotoxic effects of imatinib in combination with other anticancer agents in the human prostate cancer cell lines LNCaP, PC-3, and DU 145. METHODS: The cells were exposed to imatinib and to the other drugs simultaneously for 5 days. Cell growth inhibition was determined by XTT assay. The cytotoxic effects in combinations were evaluated at the inhibitory concentration of 50% level by the isobologram. RESULTS: Imatinib produced additive effects with estramustine phosphate (EMP) and 4-hydroperoxy-cyclophosphamide in all three cell lines. In combination with etoposide imatinib produced additive effects in two of three cell lines. Imatinib with docetaxel produced antagonistic effects in PC-3 and additive to antagonistic effects in LNCaP and DU 145 cells. CONCLUSIONS: The simultaneous exposure of imatinib and EMP would be effective against hormone sensitive and hormone insensitive cell lines and this combination should be evaluated in clinical trials. In contrast, the simultaneous exposure of imatinib and docetaxel would have little therapeutic efficacy. Although there are gaps between in vitro studies and clinical trials, the present findings provide useful information for the establishment of clinical protocols involving imatinib in hormone-refractory prostate cancer.