首页|First Affiliated Hospital of Hunan Normal University Reports Findings in Cholang iocarcinoma (Machine learning developed an intratumor heterogeneity signature fo r predicting prognosis and immunotherapy benefits in cholangiocarcinoma)
First Affiliated Hospital of Hunan Normal University Reports Findings in Cholang iocarcinoma (Machine learning developed an intratumor heterogeneity signature fo r predicting prognosis and immunotherapy benefits in cholangiocarcinoma)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Oncology - Cholangioca rcinoma is the subject of a report. According to news reporting out of Hunan, Pe ople's Republic of China, by NewsRx editors, research stated, "Cholangiocarcinom a is a kind of epithelial cell malignancy with high mortality. Intratumor hetero geneity (ITH) is involved in tumor progression, aggressiveness, treatment resist ance, and disease recurrence." Our news journalists obtained a quote from the research from the First Affiliate d Hospital of Hunan Normal University, "Integrative machine learning procedure i ncluding 10 methods (random survival forest, elastic network, Lasso, Ridge, step wise Cox, CoxBoost, partial least squares regression for Cox, supervised princip al components, generalized boosted regression modeling, and survival support vec tor machine) was performed to construct an ITH-related signature (IRS) for chola ngiocarcinoma. Single cell analysis was performed to clarify the communication b etween immune cell subtypes. Cellular experiment was used to verify the biologic al function of hub gene. The optimal prognostic IRS developed by Lasso method se rved as an independent risk factor and had a stable and powerful performance in predicting the overall survival rate in cholangiocarcinoma, with the AUC of 2-, 3-, and 4-year ROC curve being 0.955, 0.950 and 1.000 in TCGA cohort. low IRS sc ore indicated with a lower tumor immune dysfunction and exclusion score, lower t umor microsatellite instability, lower immune escape score, lower MATH score, an d higher mutation burden score in cholangiocarcinoma. Single cell analysis revea led a strong communication between fibroblasts, microphage and epithelial cells by specific ligand-receptor pairs, including COL4A1-(ITGAV+ITGB8) and COL1A2-(IT GAV+ITGB8). Down-regulation of BET1L inhibited the proliferation, migration and invasion as well as promoted apoptosis of cholangiocarcinoma cell. Integrative m achine learning analysis was performed to construct a novel IRS in cholangiocarc inoma."
HunanPeople's Republic of ChinaAsiaCancerCholangiocarcinomaCyborgsDrugs and TherapiesEmerging TechnologiesGeneticsHealth and MedicineImmunotherapyMachine LearningOncologyRisk and Prevention
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