Associated Papers
TP53 mutation heterogeneity reveals distinct prognoses in mantle cell lymphoma.
Liu S et al.
Annals of Hematology, 2026
Neoantigenic properties of TP53 variants influence cancer risk in individuals with Li-Fraumeni syndrome.
Montellier E et al.
Ebiomedicine, 2026
A quantitative, Bayesian-informed approach to gene-specific variant classification: Updated Expert Panel recommendations improve classification of TP53 germline variants for Li-Fraumeni syndrome.
Fortuno C et al.
Genome Medicine, 2025
TP53 variant clusters stratify phenotypic diversity in germline carriers and reveal an osteosarcoma-prone subgroup.
Fischer NW et al.
Nature Communications, 2025
Deep CRISPR mutagenesis characterizes the functional diversity of TP53 mutations.
Funk JS et al.
Nature Genetics, 2025
Clustering of TP53 variants into functional classes correlates with cancer risk and identifies different phenotypes of Li-Fraumeni syndrome.
Montellier E et al.
Iscience, 2024
Scalable approaches for generating, validating and incorporating data from high-throughput functional assays to improve clinical variant classification.
Padigepati SR et al.
Human Genetics, 2024
Comprehensive classification of TP53 somatic missense variants based on their impact on p53 structural stability.
Tam B et al.
Briefings in Bioinformatics, 2024
Different impacts of TP53 mutations on cell cycle-related gene expression among cancer types.
Sasaki K et al.
Scientific Reports, 2023
Repurposing antiparasitic antimonials to noncovalently rescue temperature-sensitive p53 mutations.
Tang Y et al.
Cell Reports, 2022
Analysis and Interpretation of the Impact of Missense Variants in Cancer.
Petrosino M et al.
International Journal of Molecular Sciences, 2021
Comprehensive Study of Germline Mutations and Double-Hit Events in Esophageal Squamous Cell Cancer.
Zeng B et al.
Frontiers in Oncology, 2021
Phase and context shape the function of composite oncogenic mutations.
Gorelick AN et al.
Nature, 2020
Finding driver mutations in cancer: Elucidating the role of background mutational processes.
Brown AL et al.
Plos Computational Biology, 2019
INDELseek: detection of complex insertions and deletions from next-generation sequencing data.
Au CH et al.
Bmc Genomics, 2017
Human apurinic/apyrimidinic endonuclease 1.
Li M et al.
Antioxidants & Redox Signaling, 2014
mCSM: predicting the effects of mutations in proteins using graph-based signatures.
Pires DE et al.
Bioinformatics (oxford, England), 2014
Assessment of computational methods for predicting the effects of missense mutations in human cancers.
Gnad F et al.
Bmc Genomics, 2013
Functional characterization of a promoter polymorphism in APE1/Ref-1 that contributes to reduced lung cancer susceptibility.
Lu J et al.
Faseb Journal : Official Publication of the Federation of American Societies for Experimental Biology, 2009
Polymorphisms of DNA repair genes and risk of non-small cell lung cancer.
Zienolddiny S et al.
Carcinogenesis, 2006
Semirational design of active tumor suppressor p53 DNA binding domain with enhanced stability.
Nikolova PV et al.
Proceedings of the National Academy of Sciences of the United States of America, 1998
Molecular and structural characterization of disease-associated APE1 polymorphisms.
Whitaker AM et al.
Dna Repair, 0