Associated Papers
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
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
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
Clinicopathological and molecular characteristics of patients with hypermutant lung cancer: A retrospective cohort study.
Zhang H et al.
Oncology Letters, 2021
33692861 (PubMed )
Supplement: Supplementary_Data.pdf
Tissue-specific microRNA expression alters cancer susceptibility conferred by a TP53 noncoding variant.
Deng Q et al.
Nature Communications, 2019
31699989 (PubMed )
Supplement: 41467_2019_13002_MOESM1_ESM.pdf
Validation and utilisation of high-coverage next-generation sequencing to deliver the pharmacological audit trail.
Ong M et al.
British Journal of Cancer, 2014
Dissection of the sequence-specific DNA binding and exonuclease activities reveals a superactive yet apoptotically impaired mutant p53 protein.
Ahn J et al.
Cell Cycle (georgetown, Tex.), 2009
Functional protein microarrays for parallel characterisation of p53 mutants.
Boutell JM et al.
Proteomics, 2004
Analysis of the DNA-binding activity of p53 mutants using functional protein microarrays and its relationship to transcriptional activation.
Malcikova J et al.
Biological Chemistry, 0
Higher TP53 somatic mutation prevalence from liquid biopsy analysis in ever smoker non-small-cell lung cancer patients.
Erdem HB et al.
Mutation Research, 0
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