» Articles » PMID: 33126898

Development of Prognosis Model for Colon Cancer Based on Autophagy-related Genes

Overview
Publisher Biomed Central
Date 2020 Oct 31
PMID 33126898
Citations 12
Authors
Affiliations
Soon will be listed here.
Abstract

Background: Autophagy 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.

Methods: Expression 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.

Results: Twenty 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.

Conclusion: The 8 ARGs can be used to predict the prognosis of patients and provide information for their individualized treatment.

Citing Articles

Circadian rhythm genes contribute to the prognosis prediction and potential therapeutic target in gastric cancer.

Zhang C, Yin W, Yuan L, Xiao L, Yu J, Xiao W Sci Rep. 2024; 14(1):25426.

PMID: 39455662 PMC: 11511820. DOI: 10.1038/s41598-024-76565-w.


Four centrosome-related genes to predict the prognosis and drug sensitivity of patients with colon cancer.

Wang H, Diao Y, Tan P, Liang H World J Gastrointest Oncol. 2024; 16(5):1908-1924.

PMID: 38764831 PMC: 11099447. DOI: 10.4251/wjgo.v16.i5.1908.


Expression and Clinical Significance of IRE1-XBP1s, p62, and Caspase-3 in Colorectal Cancer Patients.

Zarafshani M, Mahmoodzadeh H, Soleimani V, Moosavi M, Rahmati M Iran J Med Sci. 2024; 49(1):10-21.

PMID: 38322164 PMC: 10839142. DOI: 10.30476/IJMS.2023.96922.2856.


Identification of Hypoxia-Associated Signature in Colon Cancer to Assess Tumor Immune Microenvironment and Predict Prognosis Based on 14 Hypoxia-Associated Genes.

Chen P, Li Z, Liang Y, Wei M, Jiang H, Chen S Int J Gen Med. 2023; 16:2503-2518.

PMID: 37346810 PMC: 10281280. DOI: 10.2147/IJGM.S407005.


Autophagy and the Insulin-like Growth Factor (IGF) System in Colonic Cells: Implications for Colorectal Neoplasia.

Kasprzak A Int J Mol Sci. 2023; 24(4).

PMID: 36835075 PMC: 9959216. DOI: 10.3390/ijms24043665.


References
1.
Tian X, Sun D, Zhao S, Xiong H, Fang J . Screening of potential diagnostic markers and therapeutic targets against colorectal cancer. Onco Targets Ther. 2015; 8:1691-9. PMC: 4501159. DOI: 10.2147/OTT.S81621. View

2.
Gil J, Ramsey D, Pawlowski P, Szmida E, Leszczynski P, Bebenek M . The Influence of Tumor Microenvironment on ATG4D Gene Expression in Colorectal Cancer Patients. Med Oncol. 2018; 35(12):159. PMC: 6208841. DOI: 10.1007/s12032-018-1220-6. View

3.
Schroll M, Liu X, Herzog S, Skube S, Hummon A . Nutrient restriction of glucose or serum results in similar proteomic expression changes in 3D colon cancer cell cultures. Nutr Res. 2016; 36(10):1068-1080. PMC: 5119765. DOI: 10.1016/j.nutres.2016.08.002. View

4.
Kamburov A, Lawrence M, Polak P, Leshchiner I, Lage K, Golub T . Comprehensive assessment of cancer missense mutation clustering in protein structures. Proc Natl Acad Sci U S A. 2015; 112(40):E5486-95. PMC: 4603469. DOI: 10.1073/pnas.1516373112. View

5.
Goruppi S, Procopio M, Jo S, Clocchiatti A, Neel V, Dotto G . The ULK3 Kinase Is Critical for Convergent Control of Cancer-Associated Fibroblast Activation by CSL and GLI. Cell Rep. 2017; 20(10):2468-2479. PMC: 5616185. DOI: 10.1016/j.celrep.2017.08.048. View