Varaico: Literature-Extracted Genetic Variants

Gene:TP53
Variant:p.I50N
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TP53

NM_000546.6:p.I50N

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

TP53 variant clusters stratify phenotypic diversity in germline carriers and reveal an osteosarcoma-prone subgroup.

Fischer NW et al.

Nature Communications, 2025

41022739 (PubMed )
Supplement: 41467_2025_63528_MOESM7_ESM.xlsx › Sheet1

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

Source, co-occurrence, and prognostic value of PTEN mutations or loss in colorectal cancer.

Serebriiskii IG et al.

Npj Genomic Medicine, 2023

38001126 (PubMed )
Supplement: 41525_2023_384_MOESM1_ESM.xlsx › Table_S8

Clinical significance of genetic profiling based on different anatomic sites in patients with mucosal melanoma who received or did not receive immune checkpoint inhibitors.

Wang HY et al.

Cancer Cell International, 2023

37649078 (PubMed )
Supplement: 12935_2023_3032_MOESM2_ESM.pdf

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

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

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

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

Structural analyses of DNA recognition by the AML1/Runx-1 Runt domain and its allosteric control by CBFbeta.

Tahirov TH et al.

Cell, 2001

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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."