Ontology highlight
ABSTRACT:
Patients and methods: Series of quiescent UC-related transcriptome data obtained from the Gene Expression Omnibus (GEO) data set were divided into a training set and a validation set. Gene Set Variation Analysis (GSVA), Gene Set Enrichment Analysis (GSEA), and \Weighted Correlation Network Analysis (WGCNA) combined with protein-protein interaction (PPI) analysis were used to identify the pathways and gene signatures related to tumorigenesis among quiescent UC patients. A generalized linear model (GLM) of Poisson regression based on the training set was applied to estimate the diagnostic power of the gene signature in our validation set.
Results: The tumor necrosis factor (TNF) signaling via NF-?B pathway was significantly augmented with the highest normalized enrichment score (NES). The genes in the brown module from WGCNA have shown a significant correlation with CAC (Pearson coefficient = 0.83, p = 6e-06). A subset of NF-?B related genes (FOS, CCL4, CXCL1, MYC, CEBPB, ATF3, and JUNB) were identified with a relatively higher expression level in CAC samples. The diagnostic value of this 7-gene biomarker was estimated by the receiver operating characteristic (ROC) curve with an area under the ROC curve (AUC) at 0.82 (p<0.0001, 95% CI: 0.7098-0.9400) in the validation cohort.
Conclusion: In summary, the increased expression of this seven-NF-?B-related gene signature may act as a powerful index for tumorigenesis prediction among patients with UC in remission.
SUBMITTER: Ge CY
PROVIDER: S-EPMC7719442 | biostudies-literature | 2020
REPOSITORIES: biostudies-literature
Pharmacogenomics and personalized medicine 20201202
<h4>Purpose</h4>Ulcerative colitis (UC) patients have an increased risk of colorectal cancer (CRC), and compared with sporadic CRC, ulcerative colitis-associated colorectal cancer (CAC) is more aggressive with a worse prognosis. This study aimed to identify a gene signature to predict the risk of CAC for patients with UC in remission.<h4>Patients and methods</h4>Series of quiescent UC-related transcriptome data obtained from the Gene Expression Omnibus (GEO) data set were divided into a training ...[more]