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February 25, 2026Briefings in Bioinformatics1 citationsOpen Access

Revealing shared molecular markers and mechanisms in colorectal cancer and COVID-19 through bioinformatics and machine learning

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HWHairui WangHYHaodong YaoWNWenchao Niu

Key Points

  • The aim is to identify overlapping molecular mechanisms in colorectal cancer and COVID-19, focusing on immune regulation.
  • Integrated bulk transcriptomics with single-cell data for analysis.
  • Applied differential expression and weighted gene co-expression networks.
  • Utilized machine learning for feature selection to identify shared hub genes.
  • Constructed a transcription factor–microRNA–target network using modified algorithms.
  • Identified a core molecular signature of 31 shared hub genes.
  • Found significant downregulation of four key genes associated with reduced CD8+ T cell infiltration.
  • Revealed that p53 was upregulated while miR-3619-5p was downregulated, indicating immune dysfunction.
  • E-4031 emerged as a potential therapeutic agent targeting the identified core genes.

Abstract

Abstract Colorectal cancer (CRC) and Coronavirus Disease 2019 (COVID-19) are distinct diseases that may share overlapping molecular mechanisms, particularly in immune dysregulation. However, the specific regulatory pathways driving this shared pathophysiology have remained elusive, as prior studies have been limited by single-level data. To dissect this common pathobiology, we implemented a synergistic computational framework, integrating bulk transcriptomics with single-cell data. Through a multi-tiered analysis pipeline employing differential expression, weighted gene co-expression networks, and machine learning–based feature selection, we pinpointed a core molecular signature of 31 shared hub genes. Among these, four core candidates—GPR15, PTGDR2, FCER1A, and MAL—were significantly downregulated, a finding robustly associated with impaired CD8+ T cell infiltration. Delving deeper into the regulatory architecture using a modified weighted out-degree centrality algorithm, we constructed an integrated transcription factor–microRNA–target network. Network analysis revealed upregulation of p53 and downregulation of miR-3619-5p as possible drivers of immune dysfunction. Finally, E-4031 was identified through molecular simulation as a potential therapeutic agent targeting all four core genes. These findings uncover a shared regulatory axis involving immune suppression and transcriptional disruption, and provide promising diagnostic and therapeutic targets for CRC and COVID-19.

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Cite This Study

Wang et al. (2026) studied this question.

synapsesocial.com/papers/699e90eff5123be5ed04e346https://doi.org/10.1093/bib/bbag065
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