Immune-Omics Networks of CD27, PD1, and PDL1 in Non-Small Cell Lung Cancer

Simple Summary There are currently no effective biomarkers to select chemotherapy, immunotherapy, and radiotherapy for treating lung cancer patients. This study identified genetic networks containing major immune-checkpoint inhibitors CD27, PD1, and PDL1, and their associated prognostic genes and proliferation genes in lung cancer tumors. A 5-gene prognostic model was developed and validated in extensive cohorts to select patients at a high risk for developing metastasis. CRISPR-Cas9 and RNA interference screening data were used in the selection of proliferation genes. These genes were associated with chemoresponse and radiotherapy response in lung cancer cell lines and patient tumors. This immune-omics network led to the discovery of repositioning drugs for improving lung cancer treatment. To date, there are no prognostic/predictive biomarkers to select chemotherapy, immunotherapy, and radiotherapy in individual non-small cell lung cancer (NSCLC) patients. Major immune-checkpoint inhibitors (ICIs) have more DNA copy number variations (CNV) than mutations in The Cancer Genome Atlas (TCGA) NSCLC tumors. Nevertheless, CNV-mediated dysregulated gene expression in NSCLC is not well understood. Integrated CNV and transcriptional profiles in NSCLC tumors (n = 371) were analyzed using Boolean implication networks for the identification of a multi-omics CD27, PD1, and PDL1 network, containing novel prognostic genes and proliferation genes. A 5-gene (EIF2AK3, F2RL3, FOSL1, SLC25A26, and SPP1) prognostic model was developed and validated for patient stratification (p < 0.02, Kaplan-Meier analyses) in NSCLC tumors (n = 1163). A total of 13 genes (COPA, CSE1L, EIF2B3, LSM3, MCM5, PMPCB, POLR1B, POLR2F, PSMC3, PSMD11, RPL32, RPS18, and SNRPE) had a significant impact on proliferation in 100% of the NSCLC cell lines in both CRISPR-Cas9 (n = 78) and RNA interference (RNAi) assays (n = 92). Multiple identified genes were associated with chemoresponse and radiotherapy response in NSCLC cell lines (n = 117) and patient tumors (n = 966). Repurposing drugs were discovered based on this immune-omics network to improve NSCLC treatment.