Development and validation of metabolism-related gene signature in prognostic prediction of gastric cancer

Computational and Structural Biotechnology Journal
Tianqi LuoYingbo Chen

Abstract

Gastric cancer is one of the most common malignant tumours in the world. As one of the crucial hallmarks of cancer reprogramming of metabolism and the relevant researches have a promising application in the diagnosis treatment and prognostic prediction of malignant tumours. This study aims to identify a group of metabolism-related genes to construct a prediction model for the prognosis of gastric cancer. A large cohort of gastric cancer cases (1121 cases) from public database was included in our analysis and classified patients into training and testing cohorts at a ratio of 7: 3. After identifying a list of metabolism-related genes having prognostic value, we constructed a risk score based on metabolism-related genes using LASSO-COX method. According to the risk score, patients were divided into high- and low-risk groups. Our results revealed that high-risk patients had a significantly worse prognosis than low-risk patients in both the training (high-risk vs low-risk patients; five years overall survival: 37.2% vs 72.2%; p < 0.001) and testing cohorts (high-risk vs low-risk patients; five years overall survival: 42.9% vs 62.9%; p < 0.001). This observation was validated in the external validation cohort (high-risk vs. low-risk...Continue Reading

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Citations

Jan 30, 2021·Computational and Structural Biotechnology Journal·Abhijit DasguptaRajat K De

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Datasets Mentioned

BETA
GSE13861

Software Mentioned

R
survival ROC
glmnet
survminer
sva
GSEA
LASSO
Metascape

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