Associated Papers
Integrative Computational Analysis of TP53 Exon 5-6 Mutations in Oral Cavity, Prostate, and Breast Cancers in a Senegalese Population.
Mbaye M et al.
Genes, 2026
TP53 mutation heterogeneity reveals distinct prognoses in mantle cell lymphoma.
Liu S et al.
Annals of Hematology, 2026
41559357 (PubMed )
Supplement: 277_2026_6771_MOESM2_ESM.xlsx › TableS3
Neoantigenic properties of TP53 variants influence cancer risk in individuals with Li-Fraumeni syndrome.
Montellier E et al.
Ebiomedicine, 2026
41370968 (PubMed )
Supplement: mmc2.xlsx › Table_S1
Mapping cryptic phosphorylation sites in the human proteome.
Gasparotto D et al.
The Embo Journal, 2025
41044218 (PubMed )
Supplement: 44318_2025_567_MOESM5_ESM.xlsx › Table
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
41126324 (PubMed )
Supplement: 13073_2025_1536_MOESM2_ESM.xlsx › Table_S2
Deep CRISPR mutagenesis characterizes the functional diversity of TP53 mutations.
Funk JS et al.
Nature Genetics, 2025
39774325 (PubMed )
Supplement: 41588_2024_2039_MOESM5_ESM.xlsx › SuppFig6
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
39634561 (PubMed )
Supplement: mmc2.xlsx › TableS1
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
39085601 (PubMed )
Supplement: 439_2024_2691_MOESM2_ESM.xlsx › TP53
Mutations in the TP53, VEGFA, and CTH Genes as Key Molecular Markers for the Diagnosis of Glioblastoma.
Khalil SS et al.
Cureus, 2024
Different impacts of TP53 mutations on cell cycle-related gene expression among cancer types.
Sasaki K et al.
Scientific Reports, 2023
36964217 (PubMed )
Supplement: 41598_2023_32092_MOESM1_ESM.xlsx › Suppl._table_S1
TP53_PROF: a machine learning model to predict impact of missense mutations in TP53.
Ben-Cohen G et al.
Briefings in Bioinformatics, 2022
Analysis of single-nucleotide polymorphisms in genes associated with triple-negative breast cancer.
G V et al.
Frontiers in Genetics, 2022
36561320 (PubMed )
Supplement: Table2.xlsx › TP53
Comprehensive Identification of Deleterious TP53 Missense VUS Variants Based on Their Impact on TP53 Structural Stability.
Tam B et al.
International Journal of Molecular Sciences, 2021
34768775 (PubMed )
Supplement: ijms-22-11345-s001.zip › Supplementary_table › Supplementary_table_1.xlsx › Sheet1
Pathogenic genetic variants from highly connected cancer susceptibility genes confer the loss of structural stability.
Reza MN et al.
Scientific Reports, 2021
34584144 (PubMed )
Supplement: 41598_2021_98547_MOESM1_ESM.zip › Supplementary_files-5-8-21 › Supplementary_file_3.xlsx › Sheet1
Identification and functional characterization of new missense SNPs in the coding region of the TP53 gene.
Doffe F et al.
Cell Death and Differentiation, 2021
33257846 (PubMed )
Supplement: 41418_2020_672_MOESM3_ESM.xlsx › Table_S2c
From uncertainty to pathogenicity: clinical and functional interrogation of a rare TP53 in-frame deletion.
Quinn EA et al.
Cold Spring Harbor Molecular Case Studies, 2019
30886117 (PubMed )
Supplement: supp_mcs.a003921_Supplemental_Table_1a.xlsx › S_Table1a._TP53_in_ClinVar
Variable population prevalence estimates of germline TP53 variants: A gnomAD-based analysis.
de Andrade KC et al.
Human Mutation, 2019
30352134 (PubMed )
Supplement: supplement_1.xlsx › Supplementary_Table_1
Copy number signatures and mutational processes in ovarian carcinoma.
Macintyre G et al.
Nature Genetics, 2018
30104763 (PubMed )
Supplement: NIHMS78219-supplement-3.xlsx › mutated_cases
Distribution bias analysis of germline and somatic single-nucleotide variations that impact protein functional site and neighboring amino acids.
Pan Y et al.
Scientific Reports, 2017
TP53 mutations in human cancer: database reassessment and prospects for the next decade.
Leroy B et al.
Human Mutation, 2014
24665023 (PubMed )
Supplement: supplement_1.pdf
Potentially functional SNPs (pfSNPs) as novel genomic predictors of 5-FU response in metastatic colorectal cancer patients.
Wang J et al.
Plos One, 2014
25372392 (PubMed )
Supplement: pone.0111694.s006.pdf
A genetic progression model of Braf(V600E)-induced intestinal tumorigenesis reveals targets for therapeutic intervention.
Rad R et al.
Cancer Cell, 2013
Predicting the functional impact of protein mutations: application to cancer genomics.
Reva B et al.
Nucleic Acids Research, 2011
21727090 (PubMed )
Supplement: supp_gkr407_Supplement2_Table_SM1_COSMIC_mutations.xls › Sheet1
Proteasomal degradation of p53 by human papillomavirus E6 oncoprotein relies on the structural integrity of p53 core domain.
Bernard X et al.
Plos One, 2011
Genome-wide analysis to predict protein sequence variations that change phosphorylation sites or their corresponding kinases.
Ryu GM et al.
Nucleic Acids Research, 2009
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