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
Comprehensive classification of TP53 somatic missense variants based on their impact on p53 structural stability.
Tam B et al.
Briefings in Bioinformatics, 2024
39140857 (PubMed )
Supplement: table_s1_bbae400.xlsx › Sheet1
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
Whole-genome analysis identifies novel drivers and high-risk double-hit events in relapsed/refractory myeloma.
Ansari-Pour N et al.
Blood, 2023
36223594 (PubMed )
Supplement: BLOOD_BLD-2022-017010-mmc2.xlsx › Supplementary_Table_S2
Integrated Whole-Exome and Transcriptome Sequencing Indicated Dysregulation of Cholesterol Metabolism in Eyelid Sebaceous Gland Carcinoma.
Wang Y et al.
Translational Vision Science & Technology, 2023
36735267 (PubMed )
Supplement: tvst-12-2-4_s001.xls › S3-SNVs
Mutations found in cell-free DNAs of patients with malignant lymphoma at remission can derive from clonal hematopoiesis.
Suehara Y et al.
Cancer Science, 2019
Finding driver mutations in cancer: Elucidating the role of background mutational processes.
Brown AL et al.
Plos Computational Biology, 2019
31034466 (PubMed )
Supplement: pcbi.1006981.s010.xlsx › final_benchmark
Binding of Amphipathic Cell Penetrating Peptide p28 to Wild Type and Mutated p53 as studied by Raman, Atomic Force and Surface Plasmon Resonance spectroscopies.
Signorelli S et al.
Biochimica Et Biophysica Acta. General Subjects, 2017
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