Identification and functional characterization of new missense SNPs in the coding region of the TP53 gene
Jazyk angličtina Země Velká Británie, Anglie Médium print-electronic
Typ dokumentu časopisecké články, práce podpořená grantem
Grantová podpora
-
Radiumhemmets Forskningsfonder (Cancer Research Foundations of Radiumhemmet)
Radiumhemmets Forskningsfonder (Cancer Research Foundations of Radiumhemmet)
PubMed
33257846
PubMed Central
PMC8166836
DOI
10.1038/s41418-020-00672-0
PII: 10.1038/s41418-020-00672-0
Knihovny.cz E-zdroje
- MeSH
- geny p53 genetika MeSH
- jednonukleotidový polymorfismus genetika MeSH
- lidé MeSH
- missense mutace genetika MeSH
- nádorový supresorový protein p53 genetika MeSH
- nádory genetika MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- Názvy látek
- nádorový supresorový protein p53 MeSH
Infrequent and rare genetic variants in the human population vastly outnumber common ones. Although they may contribute significantly to the genetic basis of a disease, these seldom-encountered variants may also be miss-identified as pathogenic if no correct references are available. Somatic and germline TP53 variants are associated with multiple neoplastic diseases, and thus have come to serve as a paradigm for genetic analyses in this setting. We searched 14 independent, globally distributed datasets and recovered TP53 SNPs from 202,767 cancer-free individuals. In our analyses, 19 new missense TP53 SNPs, including five novel variants specific to the Asian population, were recurrently identified in multiple datasets. Using a combination of in silico, functional, structural, and genetic approaches, we showed that none of these variants displayed loss of function compared to the normal TP53 gene. In addition, classification using ACMG criteria suggested that they are all benign. Considered together, our data reveal that the TP53 coding region shows far more polymorphism than previously thought and present high ethnic diversity. They furthermore underline the importance of correctly assessing novel variants in all variant-calling pipelines associated with genetic diagnoses for cancer.
Central European Institute of Technology Masaryk University Brno Czech Republic
Department of Immunology Genetics and Pathology Uppsala University Uppsala Sweden
Department of Life Science Sorbonne Université Paris France
Department of Oncology Pathology Bioclinicum Karolinska Institutet Stockholm Sweden
Department of Women's and Children's Health Karolinska University Hospital Stockholm Sweden
Faculty of Science Department of Experimental Biology Masaryk University Brno Czech Republic
Metabolomics and Cell Biology Platforms Institut Gustave Roussy Villejuif France
Pôle de Biologie Hôpital Européen Georges Pompidou AP HP Paris France
Zobrazit více v PubMed
Ballinger ML, Best A, Mai PL, Khincha PP, Loud JT, Peters JA, et al. Baseline surveillance in Li-Fraumeni syndrome using whole-body magnetic resonance imaging: a meta-analysis. JAMA Oncol. 2017;3:1634–9. PubMed PMC
Malcikova J, Tausch E, Rossi D, Sutton LA, Soussi T, Zenz T, et al. ERIC recommendations for TP53 mutation analysis in chronic lymphocytic leukemia-update on methodological approaches and results interpretation. Leukemia. 2018;32:1070–80. PubMed PMC
Döhner H, Estey E, Grimwade D, Amadori S, Appelbaum FR, Büchner T, et al. Diagnosis and management of AML in adults: 2017 ELN recommendations from an international expert panel. Blood. 2017;129:424–47. PubMed PMC
Karki R, Pandya D, Elston RC, Ferlini C. Defining “mutation” and “polymorphism” in the era of personal genomics. BMC Med Genom. 2015;8:37. PubMed PMC
Musumeci L, Arthur JW, Cheung FS, Hoque A, Lippman S, Reichardt JK. Single nucleotide differences (SNDs) in the dbSNP database may lead to errors in genotyping and haplotyping studies. Hum Mutat. 2010;31:67–73. PubMed PMC
Arthur JW, Cheung FS, Reichardt JK. Single nucleotide differences (SNDs) continue to contaminate the dbSNP database with consequences for human genomics and health. Hum Mutat. 2015;36:196–9. PubMed
Lek M, Karczewski KJ, Minikel EV, Samocha KE, Banks E, Fennell T, et al. Analysis of protein-coding genetic variation in 60,706 humans. Nature. 2016;536:285–91. PubMed PMC
Beckman G, Birgander R, Sjalander A, Saha N, Holmberg PA, Kivela A, et al. Is p53 polymorphism maintained by natural selection? Hum Hered. 1994;44:266–70. PubMed
Jennis M, Kung CP, Basu S, Budina-Kolomets A, Leu JI, Khaku S, et al. An African-specific polymorphism in the TP53 gene impairs p53 tumor suppressor function in a mouse model. Genes Dev. 2016;30:918–30. PubMed PMC
Felley-Bosco E, Weston A, Cawley HM, Bennett WP, Harris CC. Functional studies of a germ-line polymorphism at codon 47 within the p53 gene. Am J Hum Genet. 1993;53:752–9. PubMed PMC
Edlund K, Larsson O, Ameur A, Bunikis I, Gyllensten U, Leroy B, et al. Data-driven unbiased curation of the TP53 tumor suppressor gene mutation database and validation by ultradeep sequencing of human tumors. Proc Natl Acad Sci USA. 2012;109:9551–6. PubMed PMC
Liu X, Wu C, Li C, Boerwinkle E. dbNSFP v3.0: a one-stop database of functional predictions and annotations for human nonsynonymous and splice-site SNVs. Hum Mutat. 2016;37:235–41. PubMed PMC
Peng G, Bojadzieva J, Ballinger ML, Li J, Blackford AL, Mai PL, et al. Estimating TP53 mutation carrier probability in families with Li-Fraumeni syndrome using LFSPRO. Cancer Epidemiol Biomark Prev. 2017;26:837–44. PubMed PMC
Gonzalez KD, Noltner KA, Buzin CH, Gu D, Wen-Fong CY, Nguyen VQ, et al. Beyond Li Fraumeni syndrome: clinical characteristics of families with p53 germline mutations. J Clin Oncol. 2009;27:1250–6. PubMed
Soussi T, Leroy B, Devir M, Rosenberg S. High prevalence of cancer-associated TP53 variants in the gnomAD database: a word of caution concerning the use of variant filtering. Hum Mutat. 2019;40:516–24. PubMed
Kato S, Han SY, Liu W, Otsuka K, Shibata H, Kanamaru R, et al. Understanding the function-structure and function-mutation relationships of p53 tumor suppressor protein by high-resolution missense mutation analysis. Proc Natl Acad Sci U S A. 2003;100:8424–9. PubMed PMC
Kotler E, Shani O, Goldfeld G, Lotan-Pompan M, Tarcic O, Gershoni A, et al. A systematic p53 mutation library links differential functional impact to cancer mutation pattern and evolutionary conservation. Mol Cell. 2018;71:178–90.e8. PubMed
Giacomelli AO, Yang X, Lintner RE, McFarland JM, Duby M, Kim J, et al. Mutational processes shape the landscape of TP53 mutations in human cancer. Nat Genet. 2018;50:1381–7. PubMed PMC
Ishioka C, Frebourg T, Yan YX, Vidal M, Friend SH, Schmidt S, et al. Screening patients for heterozygous p53 mutations using a functional assay in yeast. Nat Genet. 1993;5:124–9. PubMed
Grochova D, Vankova J, Damborsky J, Ravcukova B, Smarda J, Vojtesek B, et al. Analysis of transactivation capability and conformation of p53 temperature-dependent mutants and their reactivation by amifostine in yeast. Oncogene. 2008;27:1243–52. PubMed
Lee CW, Martinez-Yamout MA, Dyson HJ, Wright PE. Structure of the p53 transactivation domain in complex with the nuclear receptor coactivator binding domain of CREB binding protein. Biochemistry. 2010;49:9964–71. PubMed PMC
Joerger AC, Fersht AR. Structural biology of the tumor suppressor p53. Annu Rev Biochem. 2008;77:557–82. PubMed
Dahabreh IJ, Schmid CH, Lau J, Varvarigou V, Murray S, Trikalinos TA. Genotype misclassification in genetic association studies of the rs1042522 TP53 (Arg72Pro) polymorphism: a systematic review of studies of breast, lung, colorectal, ovarian, and endometrial cancer. Am J Epidemiol. 2013;177:1317–25. PubMed PMC
Joerger AC, Ang HC, Fersht AR. Structural basis for understanding oncogenic p53 mutations and designing rescue drugs. Proc Natl Acad Sci U S A. 2006;103:15056–61. PubMed PMC
Kitayner M, Rozenberg H, Rohs R, Suad O, Rabinovich D, Honig B, et al. Diversity in DNA recognition by p53 revealed by crystal structures with Hoogsteen base pairs. Nat Struct Mol Biol. 2010;17:423–9. PubMed PMC
Schmidt M, Bachhuber A, Victor A, Steiner E, Mahlke M, Lehr HA, et al. p53 expression and resistance against paclitaxel in patients with metastatic breast cancer. J Cancer Res Clin Oncol. 2003;129:295–302. PubMed
Natan E, Baloglu C, Pagel K, Freund SM, Morgner N, Robinson CV, et al. Interaction of the p53 DNA-binding domain with Its N-terminal extension modulates the stability of the p53 tetramer. J Mol Biol. 2011;409:358–68. PubMed PMC
Kitayner M, Rozenberg H, Kessler N, Rabinovich D, Shaulov L, Haran TE, et al. Structural basis of DNA recognition by p53 tetramers. Mol Cell. 2006;22:741–53. PubMed
Joerger AC, Fersht AR. The p53 pathway: origins, inactivation in cancer, and emerging therapeutic approaches. Annu Rev Biochem. 2016;85:375–404. PubMed
Ou YH, Chung PH, Sun TP, Shieh SY. p53 C-terminal phosphorylation by CHK1 and CHK2 participates in the regulation of DNA-damage-induced C-terminal acetylation. Mol Biol Cell. 2005;16:1684–95. PubMed PMC
Richards S, Aziz N, Bale S, Bick D, Das S, Gastier-Foster J, et al. Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genet Med. 2015;17:405–24. PubMed PMC
de Andrade KC, Frone MN, Wegman-Ostrosky T, Khincha PP, Kim J, Amadou A, et al. Response to: concern regarding classification of germlineTP53 variants as likely pathogenic. Hum Mutat. 2019;40:832–3. PubMed
Evans DG, Turnbull C, Woodward ER. Concern regarding classification of germline TP53 variants as likely pathogenic. Hum Mutat. 2019;40:828–31. PubMed
Keinan A, Clark AG. Recent explosive human population growth has resulted in an excess of rare genetic variants. Science. 2012;336:740–3. PubMed PMC
Coventry A, Bull-Otterson LM, Liu X, Clark AG, Maxwell TJ, Crosby J, et al. Deep resequencing reveals excess rare recent variants consistent with explosive population growth. Nat Commun. 2010;1:131. PubMed PMC
Gröbner SN, Worst BC, Weischenfeldt J, Buchhalter I, Kleinheinz K, Rudneva VA, et al. The landscape of genomic alterations across childhood cancers. Nature. 2018;555:321–7. PubMed
Leroy B, Ballinger ML, Baran-Marszak F, Bond GL, Braithwaite A, Concin N, et al. Recommended guidelines for validation, quality control, and reporting of TP53 variants in clinical practice. Cancer Res. 2017;77:1250–60. PubMed PMC
Koch L. Exploring human genomic diversity with gnomAD. Nat Rev Genet. 2020;21:448. PubMed
Woods NT, Baskin R, Golubeva V, Jhuraney A, De-Gregoriis G, Vaclova T, et al. Functional assays provide a robust tool for the clinical annotation of genetic variants of uncertain significance. NPJ Genom Med. 2016;1:16001. PubMed PMC
Flanagan SE, Patch AM, Ellard S. Using SIFT and PolyPhen to predict loss-of-function and gain-of-function mutations. Genet Test Mol Biomark. 2010;14:533–7. PubMed
Fortuno C, James PA, Young EL, Feng B, Olivier M, Pesaran T, et al. Improved, ACMG-compliant, in silico prediction of pathogenicity for missense substitutions encoded by TP53 variants. Hum Mutat. 2018;39:1061–9. PubMed PMC
Donehower LA, Soussi T, Korkut A, Liu Y, Schultz A, Cardenas M, et al. Integrated analysis of TP53 gene and pathway alterations in The Cancer Genome Atlas. Cell Rep. 2019;28:1370–84.e5. PubMed PMC
Carbonnier V, Leroy B, Rosenberg S, Soussi T. Comprehensive assessment of TP53 loss of function using multiple combinatorial mutagenesis libraries. Sci Rep. 2020; in press. PubMed PMC
de Andrade KC, Mirabello L, Stewart DR, Karlins E, Koster R, Wang M, et al. Higher-than-expected population prevalence of potentially pathogenic germline TP53 variants in individuals unselected for cancer history. Hum Mutat. 2017;38:1723–30. PubMed PMC
de Andrade KC, Frone MN, Wegman-Ostrosky T, Khincha PP, Kim J, Amadou A, et al. Variable population prevalence estimates of germline TP53 variants: a gnomAD-based analysis. Hum Mutat. 2019;40:97–105. PubMed PMC
Fortuno C, Cipponi A, Ballinger ML, Tavtigian SV, Olivier M, Ruparel V, et al. A quantitative model to predict pathogenicity of missense variants in the TP53 gene. Hum Mutat. 2019;40:788–800. PubMed
Oren M, Rotter V. Mutant p53 gain-of-function in cancer. Cold Spring Harb Perspect Biol. 2010;2:a001107. PubMed PMC
Soussi T, Wiman KG. TP53: an oncogene in disguise. Cell Death Differ. 2015;22:1239–49. PubMed PMC
Kastenhuber ER, Lowe SW. Putting p53 in Context. Cell. 2017;170:1062–78. PubMed PMC
Riley T, Sontag E, Chen P, Levine A. Transcriptional control of human p53-regulated genes. Nat Rev Mol Cell Biol. 2008;9:402–12. PubMed
Inga A, Storici F, Darden TA, Resnick MA. Differential transactivation by the p53 transcription factor is highly dependent on p53 level and promoter target sequence. Mol Cell Biol. 2002;22:8612–25. PubMed PMC
Campomenosi P, Monti P, Aprile A, Abbondandolo A, Frebourg T, Gold B, et al. p53 mutants can often transactivate promoters containing a p21 but not Bax or PIG3 responsive elements. Oncogene. 2001;20:3573–9. PubMed
Engeland K. Cell cycle arrest through indirect transcriptional repression by p53: I have a DREAM. Cell Death Differ. 2018;25:114–32. PubMed PMC
Fischer M, Grossmann P, Padi M, DeCaprio JA. Integration of TP53, DREAM, MMB-FOXM1 and RB-E2F target gene analyses identifies cell cycle gene regulatory networks. Nucleic Acids Res. 2016;44:6070–86. PubMed PMC
Sirugo G, Williams SM, Tishkoff SA. The missing diversity in human genetic studies. Cell. 2019;177:26–31. PubMed PMC
Yamada H, Shinmura K, Okudela K, Goto M, Suzuki M, Kuriki K, et al. Identification and characterization of a novel germ line p53 mutation in familial gastric cancer in the Japanese population. Carcinogenesis. 2007;28:2013–8. PubMed
Murphy ME, Liu S, Yao S, Huo D, Liu Q, Dolfi SC, et al. A functionally significant SNP in TP53 and breast cancer risk in African-American women. NPJ Breast Cancer. 2017;3:5. PubMed PMC
Wildeman M, van Ophuizen E, den Dunnen JT, Taschner PE. Improving sequence variant descriptions in mutation databases and literature using the Mutalyzer sequence variation nomenclature checker. Hum Mutat. 2008;29:6–13. PubMed
den Dunnen JT, Dalgleish R, Maglott DR, Hart RK, Greenblatt MS, McGowan-Jordan J, et al. HGVS recommendations for the description of sequence variants: 2016 update. Hum Mutat. 2016;37:564–9. PubMed
Network CGAR. Weinstein JN, Collisson EA, Mills GB, Shaw KR, Ozenberger BA, et al. The Cancer Genome Atlas Pan-Cancer analysis project. Nat Genet. 2013;45:1113–20. PubMed PMC
Hudson TJ, Anderson W, Artez A, Barker AD, Bell C, Bernabe RR, et al. International network of cancer genome projects. Nature. 2010;464:993–8. PubMed PMC
Zehir A, Benayed R, Shah RH, Syed A, Middha S, Kim HR, et al. Mutational landscape of metastatic cancer revealed from prospective clinical sequencing of 10,000 patients. Nat Med. 2017;23:703–13. PubMed PMC
Soussi T, Kato S, Levy PP, Ishioka C. Reassessment of the TP53 mutation database in human disease by data mining with a library of TP53 missense mutations. Hum Mutat. 2005;25:6–17. PubMed
Holmila R, Fouquet C, Cadranel J, Zalcman G, Soussi T. Splice mutations in the p53 gene: case report and review of the literature. Hum Mutat. 2003;21:101–2. PubMed
Supek F, Miñana B, Valcárcel J, Gabaldón T, Lehner B. Synonymous mutations frequently act as driver mutations in human cancers. Cell. 2014;156:1324–35. PubMed
Ribeiro RC, Sandrini F, Figueiredo B, Zambetti GP, Michalkiewicz E, Lafferty AR, et al. An inherited p53 mutation that contributes in a tissue-specific manner to pediatric adrenal cortical carcinoma. Proc Natl Acad Sci U S A. 2001;98:9330–5. PubMed PMC
Bienert S, Waterhouse A, de Beer TA, Tauriello G, Studer G, Bordoli L, et al. The SWISS-MODEL Repository-new features and functionality. Nucleic Acids Res. 2017;45:D313–19. PubMed PMC
Pucci F, Bourgeas R, Rooman M. Predicting protein thermal stability changes upon point mutations using statistical potentials: introducing HoTMuSiC. Sci Rep. 2016;6:23257. PubMed PMC
Ioannidis NM, Rothstein JH, Pejaver V, Middha S, McDonnell SK, Baheti S, et al. REVEL: an ensemble method for predicting the pathogenicity of rare missense variants. Am J Hum Genet. 2016;99:877–85. PubMed PMC
Niroula A, Urolagin S, Vihinen M. PON-P2: prediction method for fast and reliable identification of harmful variants. PLoS ONE. 2015;10:e0117380. PubMed PMC
Pejaver V, Urresti J, Lugo-Martinez J, Pagel KA, Lin GN, Nam H, et al. MutPred2: inferring the molecular and phenotypic impact of amino acid variants. bioRxiv. 10.1101/134981. PubMed PMC
Li B, Krishnan VG, Mort ME, Xin F, Kamati KK, Cooper DN, et al. Automated inference of molecular mechanisms of disease from amino acid substitutions. Bioinformatics. 2009;25:2744–50. PubMed PMC
Gray VE, Hause RJ, Luebeck J, Shendure J, Fowler DM. Quantitative missense variant effect prediction using large-scale mutagenesis data. Cell Syst. 2018;6:116–24.e3. PubMed PMC