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Article

Causal Prediction of TP53 Variant Pathogenicity Using a Perturbation-Informed Protein Language Model.

Advanced science (Weinheim, Baden-Wurttemberg, Germany) - 1 Jun 2026

Chen Huiying, Zhao Yang, Hu Boqiang, Wang Wuke, Song Minfang, Zhao Annabeth Xinyu, Li Xiangyang, Wang Gefei, Wang Yanfen, Zheng Weiyan, Zhang Xinpeng, Lin Xia, Yin Yanbin, Huang Xingxu, Zheng Jinfang, Liang Tingbo

Abstract excerpt

Accurate prediction of variant functional impact is crucial for understanding human diseases, particularly for cancer-related genes such as TP53. Advances in high-throughput mutational assays have enhanced variant effect prediction (VEP), but missense classification remains challenging due to the limitations of broad, non-gene-specific models. Here we present CaVepP53, a TP53-specific predictor fine-tuned on...

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Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

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Identifiers

PMID: 41955512
DOI: 10.1002/advs.202516332
PMCID: PMC13285122

Genes

TP53
ATM
BAP1
BRCA1
RAD51C
VHL

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026.

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