PubMed · 10477377
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A Lansiaux, D Fabbro, T Meyer, F Hamy, C Bailly. [PKC 412].. https://pubmed.ncbi.nlm.nih.gov/10477377/
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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.
Malignant melanoma displays strong resistance against various antineoplastic drugs. The mechanisms conferring this intrinsic resistance are unclear. To better understand the molecular events associated with drug resistance in melanoma, a panel of human melanoma cell variants exhibiting low and high levels of resistance to 4 commonly used drugs in melanoma treatment, i.e., vindesine, etoposide, fotemustine and cisplatin, was characterized by differential display reverse transcription-polymerase chain reaction (DDRT-PCR). Of 269 mRNA fragments found to be altered in expression level by DDRT-PCR, a total of 11 cDNA clones was characterized after confirmation of a differential expression pattern by Northern blot analyses. These clones include 3 genes (DSM-1, DSM-3 and DSM-5) of known function, 4 previously sequenced genes (DSM-2, DSM-4, DSM-6 and DSM-7) of uncharacterized function and 4 novel genes (DSM-8-DSM-11) without match in GenBank. All of these genes exhibited altered mRNA expression in high level etoposide-resistant cells, whereby 7 genes (DSM-1-DSM-6 and DSM-8) were found to be decreased in the transcription rate in these etoposide-resistant cells. The mRNA synthesis of the remaining genes (DSM-7 and DSM-9-DSM11) was enhanced in high level etoposide-resistant melanoma cells. The expression of 5 (DSM-5 and DSM-7-DSM-10) of the cloned cDNA encoding mRNAs was modulated in various independently established drug-resistant melanoma cells, indicating to be associated with drug resistance. Further characterization of these genes may yield inside into the biology and development of drug resistance in malignant melanoma.
Ceramide (Cer) accumulating during the execution phase of apoptosis is generated from plasma membrane sphingomyelin (SM), which gains access to a sphingomyelinase due to phospholipid scrambling (Tepper, A. D., Ruurs, P., Wiedmer, T., Sims, P., Borst, J., and van Blitterswijk, W. J. (2000) J. Cell. Biol. 150, 155-164). To evaluate the functional significance of this Cer pool, we aimed to convert it to glucosylceramide (GlcCer), by constitutive overexpression of glucosylceramide synthase (GCS). Jurkat cells, retrovirally transduced with GCS cDNA, showed a 10-12-fold increase in GCS activity in vitro and a 7-fold elevated basal GlcCer level in vivo. However, Cer accumulating during apoptosis induced by ligation of the death receptor CD95, treatment with the anti-cancer drug etoposide, or exposure to gamma-radiation was not glycosylated by GCS. Likewise, Cer liberated at the plasma membrane by bacterial SMase was not converted by the enzyme. Thus, GCS, located at the Golgi, is topologically segregated from Cer produced in the plasma membrane. In contrast, de novo synthesized Cer as well as an exogenously supplied cell-permeable Cer analog were efficiently glycosylated, apparently due to different Cer topology and distinct physicochemical behavior of the synthetic Cer species, respectively. Exogenous cell-permeable Cer species, despite their conversion by GCS, effectively induced apoptosis. We also observed that GCS activity is down-regulated in cells undergoing apoptosis. In conclusion, GCS can convert de novo synthesized Cer but not SM-derived Cer, and, therefore, the ability of GCS overexpression to protect cells from possible detrimental effects of Cer accumulation is limited.