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
Understanding the IDH1 missense SNPs on expression of genes involved in Glioblastoma multiforme.
Kakde GS et al.
Computational Biology and Chemistry, 2025
Detection of clinically relevant variants in the TP53 gene below 10% allelic frequency: A multicenter study by ERIC, the European Research Initiative on CLL.
Pavlova S et al.
Hemasphere, 2025
39840379 (PubMed )
Supplement: HEM3-9-e70065-s001.xlsx › Table_S5
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
Baseline Mutations and ctDNA Dynamics as Prognostic and Predictive Factors in ER-Positive/HER2-Negative Metastatic Breast Cancer Patients.
Pascual J et al.
Clinical Cancer Research : an Official Journal of the American Association for Cancer Research, 2023
37490393 (PubMed )
Supplement: ccr-23-0956_supplementary_table_s2_suppts2.xlsx › PEARL_baseline_mutations
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
Molecular Divergence upon EGFR-TKI Resistance Could Be Dependent on the Exon Location of the Original EGFR-Sensitizing Mutation.
Serna-Blasco R et al.
Cancers, 2022
36139605 (PubMed )
Supplement: cancers-14-04446-s001.zip › Supplemental_data_S4.xlsx › variants_datasheet
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
Immune pathways and TP53 missense mutations are associated with longer survival in canine osteosarcoma.
Das S et al.
Communications Biology, 2021
34635775 (PubMed )
Supplement: 42003_2021_2683_MOESM4_ESM.xlsx › S_Data_3
Modeling plasticity and dysplasia of pancreatic ductal organoids derived from human pluripotent stem cells.
Breunig M et al.
Cell Stem Cell, 2021
Identification of relevant genetic alterations in cancer using topological data analysis.
Rabadán R et al.
Nature Communications, 2020
32732999 (PubMed )
Supplement: 41467_2020_17659_MOESM3_ESM.xls › TableS1
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
Germ-line and somatic EPHA2 coding variants in lens aging and cataract.
Bennett TM et al.
Plos One, 2017
29267365 (PubMed )
Supplement: pone.0189881.s008.xlsx › S8a._Cat__1__all
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
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