Abstract
BackgroundGastric cancer is a fatal gastrointestinal cancer with high morbidity and poor prognosis. The dismal 5-year survival rate warrants reliable biomarkers to assess and improve the prognosis of gastric cancer. Distinguishing driver mutations that are required for the cancer phenotype from passenger mutations poses a formidable challenge for cancer genomics.MethodsWe integrated the multi-omics data of 293 primary gastric cancer patients from The Cancer Genome Atlas (TCGA) to identify key driver genes by establishing a prognostic model of the patients. Analyzing both copy number alteration and somatic mutation data helped us to comprehensively reveal molecular markers of genomic variation. Integrating the transcription level of genes provided a unique perspective for us to discover dysregulated factors in transcriptional regulation.ResultsWe comprehensively identified 31 molecular markers of genomic variation. For instance, the copy number alteration of WASHC5 (also known as KIAA0196) frequently occurred in gastric cancer patients, which cannot be discovered using traditional methods based on significant mutations. Furthermore, we revealed that several dysregulation factors played a hub regulatory role in the process of biological metabolism based on dysregulation networks. Cancer hallmark and functional enrichment analysis showed that these key driver (KD) genes played a vital role in regulating programmed cell death. The drug response patterns and transcriptional signatures of KD genes reflected their clinical application value.ConclusionsThese findings indicated that KD genes could serve as novel prognostic biomarkers for further research on the pathogenesis of gastric cancers. Our study elucidated a multidimensional and comprehensive genomic landscape and highlighted the molecular complexity of GC.
Highlights
Gastric cancer is a fatal gastrointestinal cancer with high morbidity and poor prognosis
We revealed the biological functions of key driver (KD) genes, such as programmed cell death, and the clinical characteristics, including the drug response patterns and the prognostic efficacy of expression signatures in Gastric cancer (GC) patients
Driver mutations of cancer confer tumour cell growth advantages during carcinogenesis and disease progression, distinguishing driver mutations from passenger mutations poses a formidable challenge for cancer genomics [7, 15]
Summary
Gastric cancer is a fatal gastrointestinal cancer with high morbidity and poor prognosis. The dismal 5year survival rate warrants reliable biomarkers to assess and improve the prognosis of gastric cancer. Distinguishing driver mutations that are required for the cancer phenotype from passenger mutations poses a formidable challenge for cancer genomics. The metastasis and recurrence of GC gradually develop due to tumour evolution, resulting in a poor prognosis, with a dismal 5-year survival rate of only approximately 29.3% [3, 4]. Many bioinformatics tools dedicated to driver genes identification have been developed [13, 14], the number and specificity of cancer-driver genes remain a matter of debate, distinguishing driver genes from passenger genes poses a formidable challenge for cancer genomics [15]
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