Varaico: Literature-Extracted Genetic Variants

Gene:TP53
Variant:p.W23C
Back to variants list

TP53

NM_000546.6:p.W23C

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

Comparison of TP53 mutations in myelodysplasia and acute leukemia suggests divergent roles in initiation and progression.

Jambhekar A et al.

Blood Neoplasia, 2024

40453522 (PubMed )
Supplement: BNEO_NEO-2023-000115-mmc1.xlsx › AML

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

RB1 aberrations predict outcomes of immune checkpoint inhibitor combination therapy in NSCLC.

Wang Q et al.

Frontiers in Oncology, 2023

37441425 (PubMed )
Supplement: Table_3.xlsx › mutations

Landscape of somatic alterations in large-scale solid tumors from an Asian population.

Wu L et al.

Nature Communications, 2022

35871175 (PubMed )
Supplement: 41467_2022_31780_MOESM6_ESM.xlsx › Supplementary_Data_4

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

Sequence-structure functional implications and molecular simulation of high deleterious nonsynonymous substitutions in IDH1 revealed the mechanism of drug resistance in glioma.

Suleman M et al.

Frontiers in Pharmacology, 2022

Comprehensive Study of Germline Mutations and Double-Hit Events in Esophageal Squamous Cell Cancer.

Zeng B et al.

Frontiers in Oncology, 2021

33889545 (PubMed )
Supplement: Table_6.xlsx › Sheet1

Mutational processes shape the landscape of TP53 mutations in human cancer.

Giacomelli AO et al.

Nature Genetics, 2018

30224644 (PubMed )
Supplement: NIHMS1501645-supplement-4.xlsx › Giacomelli_et_al_New_Supplement

Structure-Based Analysis Reveals Cancer Missense Mutations Target Protein Interaction Interfaces.

Engin HB et al.

Plos One, 2016

27043210 (PubMed )
Supplement: pone.0152929.s003.xlsx › mut_effects_per_ppi
Select a paper to view details
UCSC Genome Browser·Imprint·Privacy·Terms·Feedback·Email Updates·

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."