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Updated: Jan 8, 2026
Using Human Differentially Expressed Gene Lists to Perform Downstream Pathway Enrichment Analysis and Target Prioritization
Published on: October 3, 2025
A systems biology approach to unveil shared therapeutic targets and pathological pathways across major human cancers
Aftab Alam1, Mohd Faizan Siddiqui2, Rifat Hamoudi3,4,5
1Department of Medical Microbiology and Immunology, College of Medicine and Health Sciences, United Arab Emirates University, Al Ain, United Arab Emirates.
Abstract:
Cancer remains a major cause of global mortality. Despite their distinct clinical and molecular characteristics, different cancer types often share fundamental molecular mechanisms that remain underexplored. In this study, we systematically profiled transcriptomic data from four highly prevalent cancers, including breast, lung, colorectal, and prostate, to uncover shared molecular signatures with diagnostic and prognostic value. Using The Cancer Genome Atlas (TCGA) datasets and a rigorous integrative workflow, we combined differential expression analysis, Elastic Net-based feature selection, and weighted gene co-expression network analysis (WGCNA) to identify 179 cross-cancer signature genes linked to clinical traits. Protein-protein interaction (PPI) analysis and Markov Cluster Algorithm (MCL) clustering further refined these into 26 robust hub genes with strong diagnostic potential. Survival analyses demonstrated that these hub genes possess strong prognostic potential, while pan-cancer assessment revealed consistent dysregulation across more than 20 cancer types. Several hub genes also displayed context-dependent immunomodulatory roles within the tumor microenvironment. Notably, 16 hub genes showed strong associations with metastatic disease: some were consistently downregulated, suggesting tumor-suppressive functions, whereas others were upregulated in a cancer-specific manner, reflecting context-dependent oncogenic roles. We constructed a hub gene-based signature and demonstrated its potential as a prognostic marker in these four cancers types. This comprehensive analysis offers valuable insights into shared oncogenic mechanisms, contributing to improved diagnosis, prognosis, and targeted therapies across multiple cancer types.
Insights
Researchers identified 26 key genes shared across multiple cancer types, offering new diagnostic and prognostic markers. These cross-cancer genes reveal common molecular mechanisms, aiding in developing targeted therapies for breast, lung, colorectal, and prostate cancers.
Area of Science:
- Genomics
- Molecular Biology
- Cancer Research
Background:
- Cancer exhibits diverse clinical and molecular features, yet fundamental shared mechanisms are underexplored.
- Identifying common molecular pathways across different cancer types is crucial for advancing diagnosis and treatment.
Purpose of the Study:
- To uncover shared molecular signatures with diagnostic and prognostic value across four prevalent cancer types (breast, lung, colorectal, prostate).
- To identify robust gene signatures that reflect common oncogenic mechanisms and clinical traits.
Main Methods:
- Systematic transcriptomic profiling of The Cancer Genome Atlas (TCGA) datasets.
- Integrative analysis including differential expression, Elastic Net, Weighted Gene Co-expression Network Analysis (WGCNA), Protein-Protein Interaction (PPI), and Markov Cluster Algorithm (MCL) clustering.
- Pan-cancer assessment and survival analyses to evaluate diagnostic and prognostic potential.
Main Results:
- Identified 179 cross-cancer signature genes, refined to 26 robust hub genes with significant diagnostic potential.
- Demonstrated strong prognostic value of these hub genes through survival analyses.
- Observed consistent dysregulation of hub genes across over 20 cancer types, with context-dependent immunomodulatory roles.
- Highlighted 16 hub genes associated with metastasis, exhibiting both tumor-suppressive and oncogenic functions.
- Developed a hub gene-based signature with potential as a prognostic marker.
Conclusions:
- Shared molecular mechanisms exist across diverse cancer types, offering opportunities for pan-cancer therapeutic strategies.
- The identified hub genes serve as valuable diagnostic and prognostic biomarkers.
- This study provides insights into common oncogenic pathways, supporting the development of targeted therapies and improved cancer management.
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