Article

GenoGlyph: Pan-cancer genomic mutation inference and risk stratification from diagnostic histopathology slides

2026-07-09

Abstract excerpt

<title>Abstract</title> <p> Genomic alterations drive therapeutic decisions in solid tumors, yet next-generation sequencing remains inaccessible in a substantial fraction of clinical settings worldwide. We present GenoGlyph, an interpretable deep learning framework designed to decode the grammar of histopathology for pan-cancer genomic mutational inference and clinical risk stratification. Across 6,391 whole-sli...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 01b1d917-f75a-5fa8-8feb-429ba4a0cc43
DOI: 10.21203/rs.3.rs-10158096/v1

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

GenoGlyph: Pan-cancer genomic mutation inference and risk stratification from diagnostic histopathology slidesDOI 10.21203/rs.3.rs-10158096/v1Read

Pan-cancer image-based detection of clinically actionable genetic alterations.Semantic proximity Read

Integrated histopathologic modeling of detailed tumor subtypes and actionable biomarkersSemantic proximity Read

A multimodal foundation model linking histopathology and DNA methylationSemantic proximity Read

Predicting Mutational Status of Driver and Suppressor Genes Directly from Histopathology With Deep Learning: A Systematic Study Across 23 Solid Tumor TypesSemantic proximity Read

Towards real-world molecular pathology diagnosis of cancer with cross-modal AISemantic proximity Read

A systematic analysis of deep learning in genomics and histopathology for precision oncology.Semantic proximity Read

Pan-cancer computational histopathology reveals mutations, tumor composition and prognosis.Semantic proximity Read

Predicting tumour mutational burden from histopathological images using multiscale deep learningSemantic proximity Read

Machine learning enabled prediction of digital biomarkers from whole slide histopathology imagesSemantic proximity Read

Weakly supervised annotation-free cancer detection and prediction of genotype in routine histopathology.Semantic proximity Read

Rapid Screening Using Pathomorphologic Interpretation to Detect BRAFV600E Mutation and Microsatellite Instability in Colorectal Cancer.Semantic proximity Read

Phenotypic inference from sparse tumor genomes informs an explainable deep-learning model for cancer prognosisSemantic proximity Read