ArticleFrontiers in genetics2021
Bioinformatics-Based Identification of Tumor Microenvironment-Related Prognostic Genes in Pancreatic Cancer.
Article in Frontiers in genetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 8 citations in OpenAlex.
- Article
- Tumor microenvironment: barrier or opportunity towards effective cancer therapy.Journal of biomedical science · 2022Review
- Multi-omics landscape and clinical significance of aComputational and structural biotechnology journal · 2022Article
- Identification of Prognostic Biomarkers of Glioblastoma Based on Multidatabase Integration and Its Correlation with Immune-Infiltration Cells.Journal of oncology · 2022Article
- Mitophagy-Related Gene Signature for Prediction Prognosis, Immune Scenery, Mutation, and Chemotherapy Response in Pancreatic Cancer.Frontiers in cell and developmental biology · 2021Article
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Authors and funding
8 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveGrowing evidence has highlighted that the immune and stromal cells that infiltrate in pancreatic cancer microenvironment significantly influence tumor progression. However, reliable microenvironment-related prognostic gene signatures are yet to be established. The present study aimed to elucidate tumor microenvironment-related prognostic genes in pancreatic cancer.
methodsWe applied the ESTIMATE algorithm to categorize patients with pancreatic cancer from TCGA dataset into high and low immune/stromal score groups and determined their differentially expressed genes. Then, univariate and LASSO Cox regression was performed to identify overall survival-related differentially expressed genes (DEGs). And multivariate Cox regression analysis was used to screen independent prognostic genes and construct a risk score model. Finally, the performance of the risk score model was evaluated by Kaplan-Meier curve, time-dependent receiver operating characteristic and Harrell's concordance index.
resultsThe overall survival analysis demonstrated that high immune/stromal score groups were closely associated with poor prognosis. The multivariate Cox regression analysis indicated that the signatures of four genes, including TRPC7, CXCL10, CUX2, and COL2A1, were independent prognostic factors. Subsequently, the risk prediction model constructed by those genes was superior to AJCC staging as evaluated by time-dependent receiver operating characteristic and Harrell's concordance index, and both KRAS and TP53 mutations were closely associated with high risk scores. In addition, CXCL10 was predominantly expressed by tumor associated macrophages and its receptor CXCR3 was highly expressed in T cells at the single-cell level.
conclusionsThis study comprehensively investigated the tumor microenvironment and verified immune/stromal-related biomarkers for pancreatic cancer.
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