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Article

[Driver gene mutations predicted by pathology-foundation-model and their clinical associations in clear cell renal cell carcinoma].

Zhonghua bing li xue za zhi = Chinese journal of pathology - 8 May 2026

Tan S Y, Zhang Y Y, Chen W, Li J N, Wei Y R, Wang M, Fan L N, Wang Z

Abstract excerpt

Objective: To evaluate the performance of a deep learning framework based on the PathOrchestra pathology foundation model for predicting key driver gene mutations (VHL, PBRM1, BAP1, and SETD2) in clear cell renal cell carcinoma (ccRCC), and to analyze the associations of these mutations with clinicopathological characteristics and prognosis using whole-exome sequencing data. Methods: Whole-slide images and...

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Share to Carcinoma, Renal Cell
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Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

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Source

Identifiers

PMID: 42103618
DOI: 10.3760/cma.j.cn112151-20251111-00742

Genes

BAP1
PBRM1
SETD2
VHL

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 8 Sept 2026.

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