Cancer medicine · 2026
Linking Targeted Pancreatic Cancer Genes With Metabolic Disorders: A Cross-Species Translational Pathway.
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Nath Dipanwita, Ditchfield Caitlin, Price Joshua, Sivakumar Shivan, Jones Simon W, Acharjee Animesh
Аннотация
INTRODUCTION: Pancreatic ductal adenocarcinoma (PDAC) remains one of the most lethal malignancies because of its typically late diagnosis and limited treatment options, with surgical resection being the primary intervention. Emerging studies have consistently reported associations between PDAC and metabolic dysfunctions, including obesity, chronic inflammation, and diabetes. In this study, we investigated the molecular interplay between PDAC-associated genes and metabolic disorder pathways.
METHODS: We analysed publicly available bulk RNA-Seq datasets from human and murine adipose tissues, complemented by single-cell RNA-Seq data from advanced-stage PDAC. A set of key genes, ITGAM, PECAM1, CCL5, STAT1, STAT2, and CD44, was examined for expression patterns across datasets. Unsupervised clustering techniques were applied to single-cell data to identify transcriptionally distinct populations. Functional analyses were conducted using KEGG pathway enrichment and STRING-based protein-protein interaction networks. To experimentally validate transcriptomic findings, we performed ΔCT-based quantitative PCR (qPCR) on human adipose tissue samples.
RESULTS: Gene expression analyses revealed significantly high expression of PDAC-associated markers in both obese human and mouse models. Specific single-cell clusters demonstrated transcriptional profiles linked to metabolic dysregulation in PDAC. Enrichment and network analyses implicated diabetic complication pathways and inflammatory signalling cascades. Experimental validation confirmed that genes such as ITGAM, CCL5, CXCL10, STAT1, and STAT2 were significantly upregulated in obese individuals compared to lean controls, underscoring a potential immunometabolic axis in PDAC pathophysiology.
CONCLUSION: Our findings highlight a strong association between the upregulation of PDAC recurrence genes and the activation of metabolic pathways linked to obesity, diabetes, and inflammation. The consistent expression patterns across species suggest potential for developing targeted therapies to inhibit these metabolic pathways post-pancreatic cancer resection, potentially reducing fatality.
METHODS: We analysed publicly available bulk RNA-Seq datasets from human and murine adipose tissues, complemented by single-cell RNA-Seq data from advanced-stage PDAC. A set of key genes, ITGAM, PECAM1, CCL5, STAT1, STAT2, and CD44, was examined for expression patterns across datasets. Unsupervised clustering techniques were applied to single-cell data to identify transcriptionally distinct populations. Functional analyses were conducted using KEGG pathway enrichment and STRING-based protein-protein interaction networks. To experimentally validate transcriptomic findings, we performed ΔCT-based quantitative PCR (qPCR) on human adipose tissue samples.
RESULTS: Gene expression analyses revealed significantly high expression of PDAC-associated markers in both obese human and mouse models. Specific single-cell clusters demonstrated transcriptional profiles linked to metabolic dysregulation in PDAC. Enrichment and network analyses implicated diabetic complication pathways and inflammatory signalling cascades. Experimental validation confirmed that genes such as ITGAM, CCL5, CXCL10, STAT1, and STAT2 were significantly upregulated in obese individuals compared to lean controls, underscoring a potential immunometabolic axis in PDAC pathophysiology.
CONCLUSION: Our findings highlight a strong association between the upregulation of PDAC recurrence genes and the activation of metabolic pathways linked to obesity, diabetes, and inflammation. The consistent expression patterns across species suggest potential for developing targeted therapies to inhibit these metabolic pathways post-pancreatic cancer resection, potentially reducing fatality.