Development of prognosis model for colon cancer based on autophagy-related genes

World Journal of Surgical Oncology

Yuanmin Xu¹  Xu Wang¹  Bo Chen¹  Ting Li¹  Wenqi Yang¹ 

[1] Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, 230032, Hefei, Anhui, China;

关键词: Autophagy-related genes;    Prognosis model;    Colon cancer;    TCGA;   

DOI  :  10.1186/s12957-020-02061-w

来源: Springer

【 摘 要 】

BackgroundAutophagy is an orderly catabolic process for degrading and removing unnecessary or dysfunctional cellular components such as proteins and organelles. Although autophagy is known to play an important role in various types of cancer, the effects of autophagy-related genes (ARGs) on colon cancer have not been well studied.MethodsExpression profiles from ARGs in 457 colon cancer patients were retrieved from the TCGA database (https://portal.gdc.cancer.gov). Differentially expressed ARGs and ARGs related to overall patient survival were identified. Cox proportional-hazard models were used to investigate the association between ARG expression profiles and patient prognosis.ResultsTwenty ARGs were significantly associated with the overall survival of colon cancer patients. Five of these ARGs had a mutation rate ≥ 3%. Patients were divided into high-risk and low-risk groups based on Cox regression analysis of 8 ARGs. Low-risk patients had a significantly longer survival time than high-risk patients (p < 0.001). Univariate and multivariate Cox regression analysis showed that the resulting risk score, which was associated with infiltration depth and metastasis, could be an independent predictor of patient survival. A nomogram was established to predict 1-, 3-, and 5-year survival of colon cancer patients based on 5 independent prognosis factors, including the risk score. The prognostic nomogram with online webserver was more effective and convenient to provide information for researchers and clinicians.ConclusionThe 8 ARGs can be used to predict the prognosis of patients and provide information for their individualized treatment.

【 授权许可】

CC BY