A novel spatial framework to validate arsenic exposure gene expression profiling in bladder cancer using multiplex FISH and AI-powered digital pathology.

ABSTRACT: Bladder cancer exhibits marked spatial heterogeneity in gene expression and immune infiltration. In this exploratory pilot study, we integrate multiplex fluorescence in situ hybridization (mFISH) with AI-assisted digital pathology to characterize the spatial distribution of a previously validated three-gene arsenic-responsive risk model (NKIRAS2, AKTIP, HLA-DQA1). Initially identified in arsenic-exposed individuals and associated with bladder cancer risk, this gene panel achieved 94% training and 75% validation AUC in prior genomic models (PMC8760535). We analyzed five bladder tumor specimens using whole-slide mFISH imaging and HoverNet-based nuclear segmentation to quantify gene expression at single-cell resolution. Spatial profiling revealed elevated expression scores in tumor-adjacent r

SUBMITTER: Singhal S 

PROVIDER: S-EPMC12575843 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature