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Background: Epigenetic regulatory genes (epiRG) are pivotal in the epigenetic regulation of the human genome, primarily through DNA and histone modifications. These genes are frequently mutated in human cancers, particularly bladder cancer (BC). However, the functional impact of epiRG mutations on patient outcomes remains poorly understood.
Methods: In this study, we developed gene signatures for the most frequent genomic aberrations of epiRG using The Cancer Genome Atlas Bladder Carcinoma (TCGA-BLCA) dataset and validated these signatures with independent tumor expression profiles for prognostic relevance. Furthermore, we evaluated the role of these signature scores in the immune system within the tumor microenvironment (TME). Finally, we assessed the correlation between epiRG and global DNA methylation.
Results: Our results indicated that the inferred aberration-specific signature scores were more predictive of patient stratification than the genomic aberrations. Notably, certain signature scores were significantly associated with patient progression, whereas others correlated with the tumor immune microenvironment via interactions with the immune system. Patients with mutations had high signature scores in CREBBP-mut and EP300-mut, which revealed poor overall survival. Conversely, KDM6A-mut signatures showed an opposite trend, with low scores linking to favorable prognosis through enhanced immune activity. Also, other epiRG signature scores were strongly correlated with the immune system in TME and successfully predicted patients who responded to immunotherapy. Global methylation analysis revealed that high signature scores of KDM6A-mut are associated with hypomethylation.
Conclusions: These findings collectively establish epiRG signature scores as powerful biomarkers that integrate genomic, epigenetic, and immune microenvironment features for improved prognostic prediction in bladder cancer. This integrative approach not only advances our understanding of epigenetic mechanisms in BC but also offers potential for developing innovative prognostic tools and therapeutic strategies tailored to personalized medicine.
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http://dx.doi.org/10.1002/cam4.71057 | DOI Listing |
Int J Biol Macromol
September 2025
Department of Computational Biology, Indraprastha Institute of Information Technology Delhi (IIIT-Delhi), Okhla Phase III, New Delhi, 110020, India; Infosys Centre for Artificial Intelligence, Indraprastha Institute of Information Technology Delhi (IIIT-Delhi), Okhla Phase III, New Delhi, 110020, In
Understanding the structural and functional diversity of toxin proteins is critical for elucidating macromolecular behavior, mechanistic variability, and structure-driven bioactivity. Traditional approaches have primarily focused on binary toxicity prediction, offering limited resolution into distinct modes of action of toxins. Here, we present MultiTox, an ensemble stacking framework for the classification of toxin proteins based on their molecular mode of action: neurotoxins, cytotoxins, hemotoxins, and enterotoxins.
View Article and Find Full Text PDFComput Biol Chem
September 2025
Department of Bioengineering and Biotechnology, Birla Institute of Technology, Mesra, Ranchi, India. Electronic address:
Women are susceptible to hormonal imbalances and endocrine-related disorders such as Polycystic Ovary Syndrome (PCOS), Ovarian Cancer (OC), and Major Depressive Disorder (MDD). This study aims to identify gene-level interconnections among these conditions using omics-based bioinformatic approaches. Publicly available GEO datasets, viz.
View Article and Find Full Text PDFJ Clin Invest
September 2025
The University of Texas at Austin, Austin, United States of America.
Background: Following SARS-CoV-2 infection, ~10-35% of COVID-19 patients experience long COVID (LC), in which debilitating symptoms persist for at least three months. Elucidating biologic underpinnings of LC could identify therapeutic opportunities.
Methods: We utilized machine learning methods on biologic analytes provided over 12-months after hospital discharge from >500 COVID-19 patients in the IMPACC cohort to identify a multi-omics "recovery factor", trained on patient-reported physical function survey scores.
Cancer Biol Med
September 2025
State Key Laboratory of Holistic Integrative Management of Gastrointestinal Cancers, Peking University Cancer Hospital & Institute, Beijing 100142, China.
Objective: The key molecular events signifying the -induced gastric carcinogenesis process are largely unknown.
Methods: Bulk tissue-proteomics profiling were leveraged across multi-stage gastric lesions from Linqu ( = 166) and Beijing sets ( = 99) and single-cell transcriptomic profiling ( = 18) to decipher key molecular signatures of -related gastric lesion progression and gastric cancer (GC) development. The association of key proteins association with gastric lesion progression and GC development were prospectively studied building on follow-up of the Linqu set and UK Biobank ( = 48,529).
Eur Heart J
September 2025
Institute of Pharmacology and Toxicology, University Medical Centre Göttingen, Robert-Koch-Straße 40, 37075 Göttingen, Germany.
Background And Aims: Atrial fibrillation (AF) is a prevalent complication after cardiac surgery, worsening patient outcomes. Considering the established role of Ca2+-handling abnormalities in AF pathogenesis, this study aimed to evaluate if integrating cytosolic Ca2+-handling measurements with clinical risk factors enhances the risk prediction of post-operative AF.
Methods: Clinical data from 558 patients undergoing cardiac surgery without pre-existing AF from two centres were analysed.