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

G Mantini ¹, A Agostini ^2,3, M Tufo ²

⁰Bioinformatics Research Core Facility, Gemelli Science and Technology Park (GSTeP), Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy. giulia.mantini@policlinicogemelli.it.

Scientific Reports +

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December 31, 2024

View abstract on PubMed

Summary

This study used Weighted Gene Co-expression Network Analysis (WGCNA) to identify genes linked to pancreatic cancer stroma and patient survival. Researchers found specific gene signatures associated with stromal content and patient prognosis, offering potential new biomarkers.

Area Of Science

Oncology
Bioinformatics
Genomics

Background

The tumor stroma significantly influences pancreatic cancer progression and aggressiveness.
Weighted Gene Co-expression Network Analysis (WGCNA) has been used for pancreatic cancer research but not to specifically isolate stroma-associated genes and survival outcomes from bulk RNA data.

Purpose Of The Study

To apply WGCNA to pancreatic ductal adenocarcinoma (PDAC) bulk RNA data to identify genes associated with stromal content and patient survival.
To discover novel stromal-specific gene signatures and prognostic markers in PDAC.

Main Methods

Utilized WGCNA on gene expression profiles and clinical data from 140 PDAC patients (TCGA cohort).
Identified gene modules associated with clinical traits, focusing on a module linked to stromal content.
Performed survival analysis (log-rank test, Cox regression) on identified genes.
Validated stromal specificity of a key gene (HPGDS) using Human Protein Atlas (TMA cohort).
Employed Gene Set Enrichment Analysis (GSEA) to assess enrichment of stromal signatures.

Main Results

Four gene modules were found to correlate with PDAC patient clinical traits.
A module of 2459 genes was significantly associated with stromal sample content.
HPGDS and ITGA9-AS1 were identified as indicators of favorable prognosis.
KCMF1 and YARS1 were associated with poorer prognostic outcomes.
HPGDS demonstrated stromal specificity.
The identified stromal module was enriched for known stromal signatures (Moffitt, Puleo).

Conclusions

WGCNA successfully uncovered a stromal-specific gene signature in pancreatic ductal adenocarcinoma.
HPGDS, ITGA9-AS1, KCMF1, and YARS1 represent potential prognostic biomarkers for PDAC.
These findings highlight the importance of the tumor microenvironment in PDAC and offer new avenues for therapeutic strategies.

Keywords:

Biomarkers PDAC Stroma Survival WGCNA

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