Machine learning algorithm integrates bulk and single-cell transcriptome sequencing to reveal immune-related personalized therapy prediction features for pancreatic cancer

Longjun Zang; Baoming Zhang; Yanling Zhou; Fusheng Zhang; Xiaodong Tian; Zhongming Tian; Dongjie Chen; Qingwang Miao

doi:doi:10.18632/aging.205293

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Research Paper Volume 15, Issue 23 pp 14109—14140

Machine learning algorithm integrates bulk and single-cell transcriptome sequencing to reveal immune-related personalized therapy prediction features for pancreatic cancer

Figure 5. Prediction of chemotherapy and immunotherapy. (A, B) The relationship between the IRS score and the infiltration of immune cells. (C) Estimated IC50 of common chemical compounds between IRS_high and _low groups. (D) IPS scores between IRS_high and _low groups. (E, F) The correlation between IRS score and TME/TMB score. (G) Contingency table between immunotherapy responses (anti-PD-1 and anti-CTLA-4) and IRS groups based on SubMap analysis.