Machine learning developed an intratumor heterogeneity signature for predicting prognosis and immunotherapy benefits in cholangiocarcinoma

Commentary: Machine learning developed an intratumor heterogeneity signature for predicting prognosis and immunotherapy benefits in cholangiocarcinoma

“…The lower the IRS score, the lower the tumor immune dysfunction and rejection score, the lower the tumor microsatellite instability score, the lower the immune escape score, the lower the MATH score, and the higher the mutation burden score in patients with cholangiocarcinoma. This is consistent with previous findings [ [8] , [9] , [10] ] reported in related studies. Single-cell sequencing and in vitro cell assays were used to validate the large database cholangiocarcinoma prognostic model.…”

“…I was very interested to read the paper by Chen et al [ 8 ] on the successful construction of a prognostic model predicting the effect of immunotherapy for cholangiocarcinoma by applying machine learning algorithms and further revealing the intra-tumor heterogeneity of cholangiocarcinoma. In this study, the authors used a variety of statistical methods for integrated machine learning to construct a prognostic model of ITH-related features (IRS) for cholangiocarcinoma.…”

“…The results of this study [ 8 ] found that the AUC of the 2-year, 3-year, and 4-year ROC curves in the TCGA cohort were 0.955, 0.950, and 1.000, respectively. The lower the IRS score, the lower the tumor immune dysfunction and rejection score, the lower the tumor microsatellite instability score, the lower the immune escape score, the lower the MATH score, and the higher the mutation burden score in patients with cholangiocarcinoma.…”

“…Chen et al [ 8 ] cleverly applied machine learning to predict prognosis and immunotherapy outcomes in cholangiocarcinoma, successfully exploiting intratumoral heterogeneity. Its advantage is that, through comprehensive and in-depth data learning, it improves the interpretation accuracy of individual patient differences and lays the foundation for individualized treatment.…”