Development and Validation of a Prognostic Classifier Based on Lipid Metabolism–Related Genes in Gastric Cancer
Background: Dysregulation of lipid metabolism plays important roles in the tumorigenesis and progression of gastric cancer (GC). The present study aimed to establish a prognostic model based on the lipid metabolism–related genes in GC patients. Materials and Methods: Two GC datasets from the Gene Ex...
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Published in | Frontiers in molecular biosciences Vol. 8; p. 691143 |
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Main Authors | , , , , , , , |
Format | Journal Article |
Language | English |
Published |
Frontiers Media S.A
30.06.2021
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Subjects | |
Online Access | Get full text |
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Summary: | Background:
Dysregulation of lipid metabolism plays important roles in the tumorigenesis and progression of gastric cancer (GC). The present study aimed to establish a prognostic model based on the lipid metabolism–related genes in GC patients.
Materials and Methods:
Two GC datasets from the Gene Expression Atlas, GSE62254 (
n
= 300) and GSE26942 (
n
= 217), were used as training and validation cohorts to establish a risk predictive scoring model. The efficacy of this model was assessed by ROC analysis. The association of the risk predictive scores with patient characteristics and immune cell subtypes was evaluated. A nomogram was constructed based on the risk predictive score model and other prognostic factors.
Results:
A risk predictive score model was established based on the expression of 19 lipid metabolism–related genes (LPL, IPMK, PLCB3, CDIPT, PIK3CA, DPM2, PIGZ, GPD2, GPX3, LTC4S, CYP1A2, GALC, SGMS1, SMPD2, SMPD3, FUT6, ST3GAL1, B4GALNT1, and ACADS). The time-dependent ROC analysis revealed that the risk predictive score model was stable and robust. Patients with high risk scores had significantly unfavorable overall survival compared with those with low risk scores in both the training and validation cohorts. A higher risk score was associated with more aggressive features, including a higher tumor grade, a more advanced TNM stage, and diffuse type of Lauren classification of GC. Moreover, distinct immune cell subtypes and signaling pathways were found between the high–risk and low–risk score groups. A nomogram containing patients’ age, tumor stage, adjuvant chemotherapy, and the risk predictive score could accurately predict the survival probability of patients at 1, 3, and 5 years.
Conclusion
: A novel 19-gene risk predictive score model was developed based on the lipid metabolism–related genes, which could be a potential prognostic indicator and therapeutic target of GC. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 These authors have contributed equally to this work Mingyue Li, University of Pennsylvania, United States Edited by: Zhe-Sheng Chen, St. John’s University, United States Reviewed by: Yingyan Yu, Shanghai Jiao Tong University, China Lei Shi, Georgia State University, United States This article was submitted to Molecular Diagnostics and Therapeutics, a section of the journal Frontiers in Molecular Biosciences |
ISSN: | 2296-889X 2296-889X |
DOI: | 10.3389/fmolb.2021.691143 |