期刊
FRONTIERS IN ONCOLOGY
卷 11, 期 -, 页码 -出版社
FRONTIERS MEDIA SA
DOI: 10.3389/fonc.2021.595099
关键词
ARGs; prognostic indicator; CRC; nomogram; risk model
类别
资金
- Science and Technology Planning Project of Guangdong Province, China [2017A030223006, 2016A020215128]
- Science and Technology Planning Project of Guangzhou, China [201704020077]
- Second Batch of Scientific Research Projects of Dengfeng Plan [DFJH201913]
- Research Fund of CSCO-Roche Oncology [Y-2019Roche-190]
- Research Fund of CSCO-Hansoh Oncology [Y-HS2019/2-050]
- Research Fund of Guangdong General Hospital [y012015338]
- Yuexiu Science and Information Center of Guangzhou Scientific Foundation [2012-GX-046]
This study investigates the prognostic value of autophagy-related genes in colorectal cancer, identifying key prognostic genes and constructing a predictive model. The results suggest that these genes can serve as independent prognostic indicators with potential clinical applications.
Autophagy plays a complex role in tumors, sometimes promoting cancer cell survival and sometimes inducing apoptosis, and its role in the colorectal tumor microenvironment is controversial. The purpose of this study was to investigate the prognostic value of autophagy-related genes (ARGs) in colorectal cancer. We identified 37 differentially expressed autophagy-related genes by collecting TCGA colorectal tumor transcriptome data. A single-factor COX regression equation was used to identify 11 key prognostic genes, and a prognostic risk prediction model was constructed based on multifactor COX analysis. We classified patients into high and low risk groups according to prognostic risk parameters (p <0.001) and determined the prognostic value they possessed by survival analysis and the receiver operating characteristic (ROC) curve in the training and test sets of internal tests. In a multifactorial independent prognostic analysis, this risk value could be used as an independent prognostic indicator (HR=1.167, 95% CI=1.078-1.264, P<0.001) and was a robust predictor without any staging interference. To make it more applicable to clinical procedures, we constructed nomogram based on risk parameters and parameters of key clinical characteristics. The area under ROC curve for 3-year and 5-year survival rates were 0.735 and 0.718, respectively. These will better enable us to monitor patient prognosis, thus improve patient outcomes.
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