PubMed · 14207316
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E BOYLAND, R NERY. 1964-09-26. DIHYDROXYUREA.. https://doi.org/10.1038/2031379a0
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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.
Although the physiological actions of many herbs are gradually being elucidated at the molecular level, it remains unclear how individual components of herbs contribute to their biological activities. In the present study, the antiproliferative activity of Coptidis rhizoma, a medicinal herb, and the major component berberine was investigated in 8 human pancreatic cancer cell lines. Gene expression patterns associated with sensitivities to each agent were analyzed with oligonucleotide arrays that comprised approximately 11,000 genes. We used a tetrazolium dye (MTT) assay to determine ID(50) values after the 8 cell lines were exposed to the 2 agents for 72 hr. The ID(50) value for berberine was correlated positively with that for C. rhizoma (r=0.725, p=0.0401). C. rhizoma killed tumor cells more effectively than purified berberine when normalized to the level of berberine present in the herb. From the oligonucleotide array data, we selected 20 and 13 genes with strong correlations (r(2)>0.81) to ID(50) values for berberine and C. rhizoma, respectively. Among these 33 genes, the levels of expression of 12 were correlated with the ID(50) values of both agents, suggesting that these genes are associated with tumor-killing activity of berberine in C. rhizoma. Expression of the remaining 21 genes was correlated with the ID(50) value of either purified berberine or C. rhizoma. Thus, we identified common and distinct genes responsible for anti-proliferative activities of purified berberine and C. rhizoma. This strategy may improve our understanding of the actions of herbs with antitumor activities.
Polyamines are essential for the growth and function of normal cells. They interact with various macromolecules, both electrostatically and covalently and, as a consequence, have a variety of cellular effects. The complexity of polyamine metabolism and the multitude of compensatory mechanisms that are invoked to maintain polyamine homoeostasis argue that these amines are critical to cell survival. The regulation of polyamine content within cells occurs at several levels, including transcription and translation. In addition, novel features such as the +1 frameshift required for antizyme production and the rapid turnover of several of the enzymes involved in the pathway make the regulation of polyamine metabolism a fascinating subject. The link between polyamine content and human disease is unequivocal, and significant success has been obtained in the treatment of a number of parasitic infections. Targeting the polyamine pathway as a means of treating cancer has met with limited success, although the development of drugs such as DFMO (alpha-difluoromethylornithine), a rationally designed anticancer agent, has revolutionized our understanding of polyamine function in cell growth and provided 'proof of concept' that influencing polyamine metabolism and content within tumour cells will prevent tumour growth. The more recent development of the polyamine analogues has been pivotal in advancing our understanding of the necessity to deplete all three polyamines to induce apoptosis in tumour cells. The current thinking is that the polyamine inhibitors/analogues may also be useful agents in the chemoprevention of cancer and, in this area, we may yet see a revival of DFMO. The future will be in adopting a functional genomics approach to identifying polyamine-regulated genes linked to either carcinogenesis or apoptosis.