Weighted gene co-expression network analysis reveals key stromal prognostic markers in pancreatic cancer

In recent years, it has been shown that stroma compartment can favor tumor proliferation and aggressiveness. Although extensive research with network analyses such as Weighted Gene Co-expression Network Analysis (WGCNA) has been conducted on pancreatic cancer and its stromal components, WGCNA has not previously been applied to isolate and identify genes associated with the abundance of stroma and survival outcome from bulk RNA data. We investigated the gene expression profile and clinical information of 140 pancreatic ductal adenocarcinoma patients from TCGA. Network analysis was performed using WGCNA and four modules were found to be associated to patients' clinical traits. Specifically, one module of 2459 genes, was associated to stromal sample content. Subsequently, those genes were further analyzed for survival association through log-rank test and Cox regression. HPGDS and ITGA9-AS1 emerged as significant indicators of favorable prognosis while KCMF1 and YARS1 were implicated in poorer prognostic outcomes. Importantly, HPGDS was found to be stromal-specific in the TMA cohort of Human Protein Atlas. Single sample GSEA showed that the stromal module is enriched for stromal signature of Moffitt and Puleo. These findings suggest that we uncovered a stromal specific signature through WGCNA and found putative prognostic markers.

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Publication Details

Journal
Scientific Reports
Published
2024-12-30
DOI
https://doi.org/10.1038/s41598-024-82563-9
Citations
3
Primary Topic
Pancreatic and Hepatic Oncology Research
Type
article
Field-Weighted Citation Impact
0.85

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Weighted gene co-expression network analysis reveals key stromal prognostic markers in pancreatic cancer

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3 citations
Scientific Reports
Pancreatic and Hepatic Oncology Research
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article

Weighted gene co-expression network analysis reveals key stromal prognostic markers in pancreatic cancer

Giovanna Mantini, Carmine Carbone, Simonetta Rossi, Luciano Giacò, Giovanni Scambia, Lisa Salvatore, G. Tortora, Antonio De Agostini, M. Tufo, Michele Kulesko
article en
3 citations

Abstract

In recent years, it has been shown that stroma compartment can favor tumor proliferation and aggressiveness. Although extensive research with network analyses such as Weighted Gene Co-expression Network Analysis (WGCNA) has been conducted on pancreatic cancer and its stromal components, WGCNA has not previously been applied to isolate and identify genes associated with the abundance of stroma and survival outcome from bulk RNA data. We investigated the gene expression profile and clinical information of 140 pancreatic ductal adenocarcinoma patients from TCGA. Network analysis was performed using WGCNA and four modules were found to be associated to patients' clinical traits. Specifically, one module of 2459 genes, was associated to stromal sample content. Subsequently, those genes were further analyzed for survival association through log-rank test and Cox regression. HPGDS and ITGA9-AS1 emerged as significant indicators of favorable prognosis while KCMF1 and YARS1 were implicated in poorer prognostic outcomes. Importantly, HPGDS was found to be stromal-specific in the TMA cohort of Human Protein Atlas. Single sample GSEA showed that the stromal module is enriched for stromal signature of Moffitt and Puleo. These findings suggest that we uncovered a stromal specific signature through WGCNA and found putative prognostic markers.

Scientific ReportsVol. 14(1)
Università Cattolica del Sacro Cuore (IT), Agostino Gemelli University Polyclinic (IT)
Ministero della Salute
Good health and well-being
Openalex Percentile: Top 21%
Pancreatic and Hepatic Oncology Research
0.85
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