Cancer Essential Genes Stratified Lung Adenocarcinoma Patients with Distinct Survival Outcomes and Identified a Subgroup from the Terminal Respiratory Unit Type with Different Proliferative Signatures in Multiple Cohorts

SIMPLE SUMMARY: Several genes are essential for tumor growth and predict poor prognoses of patients, however, most of their roles in lung adenocarcinoma (LUAD) are unclear. In addition, a good classification strategy for cancer patients would be a useful tool for future personalized medicine. In LUAD, the existing subtype classification, including the terminal respiratory unit (TRU), proximal-inflammatory (PI), and proximal-proliferative (PP) subtypes, is mainly based on genes with variant expression levels across patients without considering the oncogenetic roles of those genes. Thus, the LUAD essential genes were identified and used to stratify patients into distinct survival outcomes, TP53 mutation statuses, E2F target activities, and tumor mutation burdens. Moreover, TRU-type patients could be further divided into clinically and molecularly different subgroups based on our classifier. Integration of existing subtypes with our classification strategy provides a more comprehensive understanding of the heterogeneity of LUAD, and can guide us to identifying potential targets for future personalized medicine. ABSTRACT: Background: Heterogeneous features of lung adenocarcinoma (LUAD) are used to stratify patients into terminal respiratory unit (TRU), proximal-proliferative (PP), and proximal-inflammatory (PI) subtypes. A more-accurate subtype classification would be helpful for future personalized medicine. However, these stratifications are based on genes with variant expression levels without considering their tumor-promoting roles. We attempted to identify cancer essential genes for LUAD stratification and their clinical and biological differences. Methods: Essential genes in LUAD were identified using genome-scale CRIPSR screening of RNA sequencing data from Project Achilles and The Cancer Genome Atlas (TCGA). Patients were stratified using consensus clustering. Survival outcomes, genomic alterations, signaling activities, and immune profiles within clusters were investigated using other independent cohorts. Findings: Thirty-six genes were identified as essential to LUAD, and there were used for stratification. Essential gene-classified clusters exhibited distinct survival rates and proliferation signatures across six cohorts. The cluster with the worst prognosis exhibited TP53 mutations, high E2F target activities, and high tumor mutation burdens, and harbored tumors vulnerable to topoisomerase I and poly(ADP ribose) polymerase inhibitors. TRU-type patients could be divided into clinically and molecularly different subgroups based on these essential genes. Conclusions: Our study showed that essential genes to LUAD not only defined patients with different survival rates, but also refined preexisting subtypes.