PubMed · 9395755
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C N Williams. 1997. Interferon therapy.. https://pubmed.ncbi.nlm.nih.gov/9395755/
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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.
The ability of lonidamine (LND), an energolytic derivative of indazole-carboxylic acid, to modulate the cytotoxicity of Taxol (TX) was investigated in the A2780 human ovarian cancer cell line. Different cytotoxicity results were obtained as a function of treatment schedule. Specifically, TX followed by LND produced synergistic effects. Conversely, antagonistic effects were recorded when drugs were given simultaneously or according to the opposite sequence. TX induced an oligonucleosomal DNA fragmentation typical of the apoptotic process. The extent and the kinetics of DNA cleavage in samples treated with the taxane alone were similar to those of samples treated with the TX-LND sequence. Activation of Yama protease and degradation of poly (ADP-ribose) polymerase were not observed after individual or combined treatment. LND did not appreciably modify the effect exerted by TX on proteins involved in cell cycle progression (i.e., inhibition of p34cdc2 expression) and apoptosis (i.e., upregulation of wt p53 and transactivation of p21waf1), and only caused a slight induction of the Bax protein. LND alone did not affect tubulin polymerization in A2780 cells and, when administered after a 24 hr TX exposure, did not appreciably alter the extent of tubulin polymerization induced by the taxane. Although additional studies are needed to define the molecular basis of the TX-LND interaction, our results suggest that LND can positively modulate the antitumor activity of TX in ovarian cancer cells and indicate that the energolytic is potentially useful in combination therapy including the taxane in ovarian cancer patients.
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