Additional file 1 of Mutations of PI3K-AKT-mTOR pathway as predictors for immune cell infiltration and immunotherapy efficacy in dMMR/MSI-H gastric adenocarcinoma
Creators: name: Wang, Zhenghang
name: Wang, Xinyu
name: Xu, Yu
name: Li, Jian
name: Zhang, Xiaotian
name: Peng, Zhi
name: Hu, Yajie
name: Zhao, Xinya
name: Dong, Kun
name: Zhang, Bei
name: Gao, Chan
name: Zhao, Xiaochen
name: Chen, Hui
name: Cai, Jinping
name: Bai, Yuezong
name: Sun, Yu
name: Shen, Lin
Publisher: name: figshare
Year: 2022
Subjects: subject: Genetics
subject: FOS: Biological sciences
subject: Molecular Biology
subject: Pharmacology
subject: Immunology
subject: FOS: Clinical medicine
subject: Biological Sciences not elsewhere classified
subject: Cancer
subject: Infectious Diseases
subject: FOS: Health sciences
subject: Plant Biology
subject: Virology

description: Additional file 1. Fig. S1. Work flow and patient selection. Fig. S2. Association between the results of IHC, PCR, and NGS testing for identifying dMMR/MSI-H gastric adenocarcinoma. Fig. S3. Mutations of PI3K-AKT-mTOR pathway of the concordant MSI-H cases in the surgery cohort. Fig. S4. Representative images of hematoxylin-eosin and PD-L1 staining of MSI-H STAD samples in the 3DMed cohort. Fig. S5. GSEA of gene signatures related to immune activation, interleukin pathways, and NOTCH signaling in comparisons between samples with or without mutation in PI3K-AKT-mTOR pathway. Fig. S6. ROC curves illustrating the association of response rate with TMB and PD-L1 CPS. Fig. S7. Predictive effect of PTEN mutation and NMP in PTENWT dMMR/MSI-H gastric adenocarcinomas. Fig. S8. Association between mutations in PI3K-AKT-mTOR pathway and concentration of peripheral blood immune cells in patients with dMMR/MSI-H G/GEJ adenocarcinoma in the ICI treatment cohort. Fig. S9. Prognostic effect of the genetic aberration in PI3K-AKT-mTOR pathway in the TCGA cohort. Table S1. List of the genes in the 3DMed 733-gene panel. Table S2. Members of the analyzed signaling pathways in the surgery cohort. Table S3. Antibodies used in flow cytometry. Table S4. List of gene signatures in GSEA. Table S5. Clinicopathological and genomic characteristics in the surgery cohort. Table S6. Association between the results of IHC, PCR, and NGS testing for identifying dMMR/MSI-H gastric adenocarcinoma. Table S7. Genomic characteristics of the discordant samples. Table S8. Clinicopathological characteristics of concordant dMMR/MSI-H samples according to the evaluation of immune infiltration in the surgery cohort. Table S9. Clinicopathological characteristics of dMMR/MSI-H samples with evaluation of immune infiltration according to the history of neoadjuvant chemotherapy in the surgery cohort. Table S10. Sensitivity analysis of the correlation between mutations in PI3K-AKT-mTOR pathway and immune cell infiltration. Table S11. Detailed information of the MSI-H gastric adenocarcinoma samples evaluated by both 381-gene panel and PD-L1 kit retrieved from the 3DMed database. Table S12. Clinicopathological characteristics of MSI-H STAD according to the genetic aberration in PI3K-AKT-mTOR pathway in the TCGA cohort. Table S13. The mutations of the members in the PI3K-AKT-mTOR pathway and mutation sites in the five MSI-H GAC cell lines. Table S14. The IC50 values of every cell line for the PI3K-AKT-mTOR inhibitors, the inhibitors targeting VEGFR or EGFR, and chemotherapeutic drugs. Table S15. Baseline characteristics of the patients with dMMR/MSI-H G/GEJ adenocarcinoma in the ICI treatment cohort. Table S16. Univariable and multivariable analysis of PFS and OS in the ICI treatment cohort.