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Development and validation of a metabolic gene signature for predicting overall survival in patients with colon cancer

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Abstract

The reprogramming of cellular metabolism is a hallmark of tumorigenesis. However, the prognostic value of metabolism-related genes in colon cancer remains unclear. This study aimed to identify a metabolic gene signature to categorize colon cancer patients into high- and low-risk groups and predict prognosis. Samples from the Gene Expression Omnibus database were used as the training cohort, while samples from The Cancer Genome Atlas database were used as the validation cohort. A metabolic gene signature was established to investigate a robust risk stratification for colon cancer. Subsequently, a prognostic nomogram was established combining the metabolism-related risk score and clinicopathological characteristics of patients. A total of 351 differentially expressed metabolism-related genes were identified in colon cancer. After univariate analysis and least absolute shrinkage and selection operator-penalized regression analysis, an eight-gene metabolic signature (MTR, NANS, HADH, IMPA2, AGPAT1, GGT5, CYP2J2, and ASL) was identified to classify patients into high- and low-risk groups. High-risk patients had significantly shorter overall survival than low-risk patients in both the training and validation cohorts. A high-risk score was positively correlated with proximal colon cancer (P = 0.012), BRAF mutation (P = 0.049), and advanced stage (P = 0.027). We established a prognostic nomogram based on metabolism-related gene risk score and clinicopathologic factors. The areas under the curve and calibration curves indicated that the established nomogram showed a good accuracy of prediction. We have established a novel metabolic gene signature that could predict overall survival in colon cancer patients and serve as a biomarker for colon cancer.

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Availability of data and material

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

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Author notes

  1. Jun Ren and Juan Feng contributed equally to this work.

Authors and Affiliations

  1. Department of Gastrointestinal Surgery II, Renmin Hospital of Wuhan University, No. 238, Jiefang Road, Wuhan, 430060, Hubei, China

    Jun Ren, Wei Song, Chuntao Wang, Yuhang Ge & Tao Fu

  2. Department of Breast Surgery, Renmin Hospital of Wuhan University, Wuhan, 430060, Hubei, China

    Juan Feng

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  1. Jun Ren
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Contributions

JR and JF designed the experiment. JR, JF, WS, and CTW undertook the data acquisition. JR, JF, WS, and YHG were involved in the interpretation of data. JR and JF analyzed and visualized the data. All authors drafted and revised the manuscript. The final manuscript was read and approved by all authors.

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Correspondence to Tao Fu.

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Ren, J., Feng, J., Song, W. et al. Development and validation of a metabolic gene signature for predicting overall survival in patients with colon cancer. Clin Exp Med 20, 535–544 (2020). https://doi.org/10.1007/s10238-020-00652-1

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  • DOI: https://doi.org/10.1007/s10238-020-00652-1

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