Clostridioides difficile is best known for causing antibiotic-related diarrhea, but a new review from China suggests it may also promote gastrointestinal cancers, especially colorectal cancer (CRC). The authors summarize clinical data, epidemiology, and tumor models showing how recurrent infection, toxins, inflammation, metabolism, and biofilms could reshape the colonic microenvironment. They argue chronic C. difficile infection as a potential driver of colorectal tumorigenesis and a promising biomarker, offering new insights for effective CRC prevention and therapy.

A team led by Prof. Fei Ling from South China University of Technology developed PRTS (Pathology-driven Reconstruction of Transcriptomic States), a deep learning framework that predicts single-cell-resolution spatial transcriptomics directly from H&E-stained histology images.

Researchers at the University of Navarra in Spain, have developed RNACOREX, a new open-source software tool that reveals hidden genetic regulatory networks involved in cancer and helps predict patient survival. Tested across 13 different tumor types using data from The Cancer Genome Atlas (TCGA), RNACOREX identifies key interactions between microRNAs and messenger RNAs—molecular relationships that are often missed by conventional analyses.

Unlike many artificial intelligence models that function as “black boxes,” RNACOREX produces interpretable molecular maps that show how genes interact within tumors. These networks can stratify patients according to survival probability with accuracy comparable to advanced AI approaches, while clearly explaining the biological mechanisms behind the predictions.

Published in PLOS Computational Biology, the study demonstrates how RNACOREX can uncover shared molecular patterns across cancers, highlight individual molecules of biomedical interest, and generate new hypotheses about tumor progression. Freely available via GitHub and PyPI, the tool is designed to be accessible for research laboratories worldwide and represents a step forward in explainable AI for precision oncology.