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Cross-cancer transcriptomic integration identifies a core immune-signaling network in hormone-driven malignancies
Prasanna Kumar Selvam1, Supraja Mohan1, Karthick Vasudevan1
1Manipal Academy of Higher Education (MAHE), Manipal, India; Institute of Bioinformatics, International Technology Park, Bangalore, India.
None:
Hormone-dependent malignancies, including breast, ovarian, thyroid, and prostate cancers, are driven by dysregulated endocrine signaling but exhibit marked heterogeneity in molecular architecture and therapeutic response. Whether these cancers share conserved transcriptional programs that transcend tissue-of-origin remains incompletely understood. In this study, we applied a systematic, direction-aware transcriptomic framework to identify shared gene expression signatures across hormone-driven malignancies using RNA-sequencing data with matched non-malignant controls. Differential expression analysis was performed independently for each cancer type using DESeq2, identifying 15,648 significant differentially expressed genes (DEGs). Integration of DEGs across cancers using a presence-direction matrix revealed limited universal overlap, with only one gene shared across all four cancers. Leave-one-out sensitivity analysis demonstrated that prostate cancer exhibited reduced transcriptional concordance relative to other malignancies. Exclusion of prostate cancer resulted in the highest overlap and direction-consistent dysregulation, identifying 10,948 shared DEGs across breast, ovarian, and thyroid cancers, including 1043 genes with consistent regulatory direction. Restriction to genes common to all three retained cancers defined a core pan-hormone transcriptional signature comprising 270 genes. These genes were prioritized using a composite statistical score integrating mean absolute log2 fold change and Fisher-combined adjusted p-values across cancers. Functional enrichment analysis of the top 100 ranked genes using g:Profiler revealed significant enrichment of immune-related biological processes, cytokine signaling, membrane-associated signal transduction, and protein-protein interaction functions. Collectively, this study identifies a conserved immune-signaling-centric transcriptional program shared across breast, ovarian, and thyroid cancers.
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