Lingyan Xiao,Yongbiao Huang,Wan Qin,Chaofan Liu,Hong Qiu,Bo Liu,Xianglin Yuan. A metabolism-associated gene signature with prognostic value in colorectal cancer. Oncol Transl Med, 2022, 8: 43-54. |
A metabolism-associated gene signature with prognostic value in colorectal cancer |
Received:September 19, 2021 Revised:March 07, 2022 |
View Full Text View/Add Comment Download reader |
KeyWord:colorectal cancer (CRC); prognostic; metabolism; RNA-seq; The Cancer Genome Atlas (TCGA) |
Author Name | Affiliation | E-mail | Lingyan Xiao | Department of Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology | 15580329472@163.com | Yongbiao Huang | Department of Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology | | Wan Qin | Department of Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology | | Chaofan Liu | Department of Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology | | Hong Qiu | Department of Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology | | Bo Liu | Department of Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology | boliu888@hotmail.com | Xianglin Yuan | Department of Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology | |
|
Hits: 3207 |
Download times: 3241 |
Abstract: |
Objective In this study, our goal was to explore the role of metabolism-associated genes in colorectal
cancer (CRC) and construct a prognostic model for patients with CRC.
Methods Differential expression analysis was conducted using RNA-sequencing data from The Cancer
Genome Atlas (TCGA) dataset. Enrichment analyses were performed to determine the function of
dysregulated metabolism-associated genes. The protein-protein interaction (PPI) network, Kaplan-Meier
curves, and stepwise Cox regression analyses identified key metabolism-associated genes. A prognostic
model was constructed using LASSO Cox regression analysis and visualized as a nomogram. Survival
analyses were conducted in the TCGA and Expression Omnibus (GEO) cohorts to demonstrate the
predictive ability of the model.
Results A total of 332 differentially expressed metabolism-associated genes in CRC were screened
from the TCGA cohort. Differentially expressed metabolism-associated genes mainly participate in
the metabolism of nucleoside phosphate, ribose phosphate, lipids, and fatty acids. A PPI network was
constructed out of 328 key genes. A prognostic model was established based on five prognostic genes
(ALAD, CHDH, ISYNA1, NAT1, and P4HA1) and was demonstrated to predict survival in the TCGA and
GEO cohorts accurately.
Conclusion The metabolism-associated prognostic model can predict the survival of patients with
CRC. Our work supplements previous work focusing on determining prognostic factors of CRC and lays a
foundation for further mechanistic exploration. |
Close |
|
|
|