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 8. Identification of potential agents for high IRS score PCs. (A) Data availability of drug sensitive data in CTRP and PRISM datasets. (B) Validation of the predicted drug sensitive data based on literature. (C) Potential agents for high IRS patients were identified from CTRP and PRISM datasets. (D) The CMap score of four candidate compounds. (E) The IRS score between Capan-2 and Panc 08.13 cell lines. (F) The AUC value of four candidate compounds in Capan-2 and Panc 08.13 cell lines.