Varaico: Literature-Extracted Genetic Variants

Gene:TP53
Variant:p.V122M
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TP53

NM_000546.6:p.V122M

Associated Papers

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

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

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

Using multiplexed functional data to reduce variant classification inequities in underrepresented populations.

Dawood M et al.

Genome Medicine, 2024

39627863 (PubMed )
Supplement: 13073_2024_1392_MOESM1_ESM.xlsx › Table_S18

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

TP53 germline pathogenic variants in modern humans were likely originated during recent human history.

Kou SH et al.

Nar Cancer, 2023

37304756 (PubMed )
Supplement: zcad025_supplemental_files.zip › Supplementary_Table_2.xlsx › BVs

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

Integration of deep learning with Ramachandran plot molecular dynamics simulation for genetic variant classification.

Tam B et al.

Iscience, 2023

36879825 (PubMed )
Supplement: mmc2.xlsx › TP53

vaRHC: an R package for semi-automation of variant classification in hereditary cancer genes according to ACMG/AMP and gene-specific ClinGen guidelines.

Munté E et al.

Bioinformatics (oxford, England), 2023

36916756 (PubMed )
Supplement: btad128_supplementary_data.zip › btad128_Supplementary_Data › Supplementary_tables10022023.xlsx › ST12-TP53

Evaluation of AlphaFold structure-based protein stability prediction on missense variations in cancer.

Keskin Karakoyun H et al.

Frontiers in Genetics, 2023

36896237 (PubMed )
Supplement: Table1.xlsx › clinvar_breastcancer_allvariant

Association of Inherited Mutations in DNA Repair Genes with Localized Prostate Cancer.

Lee DJ et al.

European Urology, 2022

34711450 (PubMed )
Supplement: NIHMS1772233-supplement-Supplementary_Tables.xlsx › TableS4

TP53_PROF: a machine learning model to predict impact of missense mutations in TP53.

Ben-Cohen G et al.

Briefings in Bioinformatics, 2022

35043155 (PubMed )
Supplement: supplementary_table_s1_bbab524.xlsx › S1B._Negative_Set

Mouse model and human patient data reveal critical roles for Pten and p53 in suppressing POLE mutant tumor development.

Park VS et al.

Nar Cancer, 2022

35252866 (PubMed )
Supplement: zcac004_supplemental_file.xlsx › Supp_Table_4

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 of relevant genetic alterations in cancer using topological data analysis.

Rabadán R et al.

Nature Communications, 2020

32732999 (PubMed )
Supplement: 41467_2020_17659_MOESM3_ESM.xls › TableS1

Aberrant expression and mutation-inducing activity of AID in human lung cancer.

Shinmura K et al.

Annals of Surgical Oncology, 2011

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Regarding the variants extracted from papers and shown text snippets from research papers, the following holds: "Some rights reserved. This work permits non-commercial use, distribution and reproduction in any medium, provided the original author and source are credited."