PubMed · 13856963
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CHEMOTHERAPY.. https://pubmed.ncbi.nlm.nih.gov/13856963/
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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.
We have previously identified tumor susceptibility gene101 (TSG101), overexpressed in vincristine-resistant human gastric adenocarcinoma cell line SGC7901/VCR using a modified subtractive hybridization method and Western blot. In the present study, we constructed two siRNA eukaryotic expression vectors of TSG101 and transfected them into SGC7901/VCR cells to examine whether the down-regulation of TSG101 increased cell sensitivity towards chemotherapeutic drugs. After transfection, the expression of TSG101 was dramatically decreased in TSG101 siRNA transfectants compared with that in parental cells and empty vector control cells. The down-regulation of TSG101 could significantly enhance the sensitivity of SGC7901/VCR cells to vincristine and adriamycin. The capacity of cells to efflux adriamycin markedly decreased in TSG101 siRNA transfectants. These observations suggested that the siRNA constructs of TSG101 we made could effectively down-regulate the expression of TSG101 and reverse the resistant phenotype of gastric cancer cells. The preliminary study suggested that TSG101 might play an important role in multidrug resistance of gastric carcinoma.
Histone deacetylases (HDAC) are ubiquitously distributed through chromatin. Nevertheless HDAC inhibitors (HDACi), such as SAHA, selectively alter the transcription of as few as 2-5% of expressed genes in various transformed cells. p21(WAF1) is one of the most commonly induced genes in cells cultured with SAHA. Understanding the mechanism of the selective effects of the HDACi is a challenging problem. Gui et al. have identified effects of SAHA on p21(WAF1) promotor associated proteins that explain, at least in part, the selective effects of HDAC in altering gene expression.