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ABSTRACT: Background
Molecular mechanism of lung squamous cell carcinoma (LUSC) remains poorly understood, hampering effective targeted therapies or precision diagnosis about LUSC. We devised an integrative framework to investigate on the molecular patterns of LUSC by systematically mining the genomic, transcriptional and clinical information.Methods
We utilized the genomics and transcriptomics data for the LUSC cohorts in The Cancer Genome Atlas.. Both kinds of omics data for 33 types of cancers were downloaded from The NCI's Genomic Data Commons (GDC) (https://gdc.cancer.gov/about-data/publications/pancanatlas). The genomics data were processed in mutation annotation format (maf), and the transcriptomics data were determined by RNA-seq method. Mutation significance was estimated by MutSigCV. Prognosis analysis was based on the cox proportional hazards regression (Coxph) model.Results
Significant somatic mutated genes (SMGs) like NFE2L2, RASA1 and COL11A1 and their potential down-stream pathways were recognized. Furthermore, two LUSC-specific and prognosis-meaningful subtypes were identified. Interestingly, the good prognosis subtype was enriched with mutations in CUL3/KEAP1/NRF2 pathway and with markedly suppressed expressions of multiple down-stream pathways like epithelial mesenchymal transition. The subtypes were verified by the other two cohorts. Additionally, primarily regulated down-stream elements of different SMGs were also estimated. NFE2L2, KEAP1 and RASA1 mutations showed remarkable effects on the subtype-determinant gene expressions, especially for the inflammatory relevant genes.Conclusions
This study supplies valuable references on potential down-stream processes of SMGs and an alternative way to classify LUSC.
SUBMITTER: Liu Z
PROVIDER: S-EPMC7240936 | biostudies-literature |
REPOSITORIES: biostudies-literature