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
The theory of massively repeated evolution and full identifications of cancer-driving nucleotides (CDNs).
Zhang L et al.
Elife, 2024
39688960 (PubMed )
Supplement: elife-99340-supp1.xlsx › CDN.Missense.gnomad
Genomic characterization of AML with aberrations of chromosome 7: a multinational cohort of 519 patients.
Halik A et al.
Journal of Hematology & Oncology, 2024
39160538 (PubMed )
Supplement: 13045_2024_1590_MOESM1_ESM.xlsx › Suppl._Dataset_4_TS_SNV
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
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
Lenalidomide promotes the development of TP53-mutated therapy-related myeloid neoplasms.
Sperling AS et al.
Blood, 2022
35512188 (PubMed )
Supplement: BLOOD_BLD-2021-014956-mmc1.pdf
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
Modeling (not so) rare developmental disorders associated with mutations in the protein-tyrosine phosphatase SHP2.
Solman M et al.
Frontiers in Cell and Developmental Biology, 2022
Highly multiplexed quantifications of 299 somatic mutations in colorectal cancer patients by automated MALDI-TOF mass spectrometry.
Xu C et al.
Bmc Medical Genomics, 2020
33008377 (PubMed )
Supplement: 12920_2020_804_MOESM1_ESM.xls › SuppTable1
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
Germline pathogenic variants of 11 breast cancer genes in 7,051 Japanese patients and 11,241 controls.
Momozawa Y et al.
Nature Communications, 2018
30287823 (PubMed )
Supplement: 41467_2018_6581_MOESM5_ESM.xlsx › SD2
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
Pan-urologic cancer genomic subtypes that transcend tissue of origin.
Chen F et al.
Nature Communications, 2017
28775315 (PubMed )
Supplement: 41467_2017_289_MOESM7_ESM.xlsx › mutation_data
Mutational landscape reflects the biological continuum of plasma cell dyscrasias.
Rossi A et al.
Blood Cancer Journal, 2017
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