02331nas a2200265   4500008004100000022001400041245012500055210006900180260000800249300001400257490000700271520136700278653004601645653001201691653003401703653003001737653005201767653002101819100001901840700001801859700001801877700001901895700002101914856013001935       2020                        eng d  a1747-027700aPrediction of survival rate and effect of drugs on cancer patients with somatic mutations of genes: an AI-based approach0 aPrediction of survival rate and effect of drugs on cancer patien  cSEP  a1005-10190 v963 a<p>The causal role of somatic mutation and its interrelationship with gene expression profile during tumor development has already been observed, which plays a major role to decide the cancer grades and overall survival. Accurate and robust prediction of tumor grades and patients' overall survival are important for prognosis, risk factors identification and betterment of the treatment strategy, especially for highly lethal tumors, like gliomas. Here, with the help of more accurate and widely used machine learning-based approaches, we propose an integrative computational pipeline that incorporates somatic mutations and gene expression profile for survival and grade prediction of glioma patients and simultaneously relates it to the drugs to be administered. This study gives us a clear understanding that the same drug is not effective for the treatment of same grade of cancer if the gene mutations are different. The alteration in a specific gene plays a very important role in tumor progression and should also be considered for the selection of appropriate drugs. This proposed framework includes all the necessary factors required for enhancement of therapeutic designs and could be useful for clinicians in determining an accurate and personalized treatment strategy for individual patients suffering from different life threatening diseases.</p>
10agene expression and copy number variation10agliomas10agrade and survival prediction10amachine learning strategy10asignificant gene prediction and effect of drugs10asomatic mutation1 aSaurabh, Rochi1 aNandi, Sutanu1 aSinha, Noopur1 aShukla, Mudita1 aSarkar, Ram, Rup  uhttps://library.ncl.res.in/content/prediction-survival-rate-and-effect-drugs-cancer-patients-somatic-mutations-genes-ai-based