Familial colorectal cancer: search for novel predisposition genes
Jazyk angličtina Země Velká Británie, Anglie Médium electronic
Typ dokumentu časopisecké články
PubMed
41469725
PubMed Central
PMC12849417
DOI
10.1186/s40246-025-00901-y
PII: 10.1186/s40246-025-00901-y
Knihovny.cz E-zdroje
- Klíčová slova
- Colorectal cancer, Familial cancer, Genetic predisposition, Multiple primaries,
- MeSH
- dospělí MeSH
- genetická predispozice k nemoci * MeSH
- kolorektální nádory * genetika patologie MeSH
- lidé středního věku MeSH
- lidé MeSH
- mapy interakcí proteinů genetika MeSH
- rodokmen MeSH
- sekvenování exomu MeSH
- senioři MeSH
- signální transdukce genetika MeSH
- zárodečné mutace MeSH
- Check Tag
- dospělí MeSH
- lidé středního věku MeSH
- lidé MeSH
- mužské pohlaví MeSH
- senioři MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
BACKGROUND: Family history of colorectal cancer (CRC) and multiple primary CRCs in a single person may indicate inherited CRC predisposition. METHODS: In the present study, we performed whole exome/genome sequencing on germline DNA from at least two CRC cases in 19 families and from family members with a double primary CRC from seven additional families. We used a set of in silico predictions in combination with a STRING protein-protein interaction and pathway analysis to identify the most likely variants predisposing to CRC. RESULTS: We identified Cell cycle/DNA repair and TGFβ signaling/Focal adhesion/Extracellular matrix organization pathways as highly significant protein-protein interaction networks. Variants in the APCDD1, CYBA, PTK7 and SRC genes were identified in more than one family, and they were shown to dysregulate basic cellular functions, potentially leading to cancer development. Most variants were private to a family, and each family had more than one candidate variant, suggesting a synergistic or polygenic mode of inheritance. This hypothesis, as well as validation of the identified variants and pathways and their functional consequences, need confirmation by other family-based studies. CONCLUSIONS: Different types of family-based analyses together with in silico predictions are helpful to identify candidate genes and pathways for CRC predisposition.
Chair of Drug and Cosmetics Biotechnology Warsaw University of Technology Warsaw Poland
Division of Cancer Epidemiology German Cancer Research Center Heidelberg Germany
Division of Immune Regulation in Cancer German Cancer Research Center Heidelberg Germany
Zobrazit více v PubMed
Hemminki K, Sundquist K, Sundquist J, Forsti A, Hemminki A, Li X. Familial risks and proportions describing population landscape of familial cancer. Cancers (Basel). 2021. 10.3390/cancers13174385. PubMed DOI PMC
Hemminki K, Li X, Dong C. Second primary cancers after sporadic and familial colorectal cancer. Cancer Epidemiol Biomarkers Prev. 2001;10(7):793–8. PubMed
Valle L, de Voer RM, Goldberg Y, Sjursen W, Forsti A, Ruiz-Ponte C, et al. Update on genetic predisposition to colorectal cancer and polyposis. Mol Aspects Med. 2019;69:10–26. PubMed DOI
Palles C, Cazier JB, Howarth KM, Domingo E, Jones AM, Broderick P, et al. Germline mutations affecting the proofreading domains of POLE and POLD1 predispose to colorectal adenomas and carcinomas. Nat Genet. 2013;45(2):136–44. PubMed DOI PMC
Weren RD, Ligtenberg MJ, Kets CM, de Voer RM, Verwiel ET, Spruijt L, et al. A germline homozygous mutation in the base-excision repair gene NTHL1 causes adenomatous polyposis and colorectal cancer. Nat Genet. 2015;47(6):668–71. PubMed DOI
Adam R, Spier I, Zhao B, Kloth M, Marquez J, Hinrichsen I, et al. Exome sequencing identifies biallelic PubMed DOI PMC
Jaeger E, Leedham S, Lewis A, Segditsas S, Becker M, Cuadrado PR, et al. Hereditary mixed polyposis syndrome is caused by a 40-kb upstream duplication that leads to increased and ectopic expression of the BMP antagonist GREM1. Nat Genet. 2012;44(6):699–703. PubMed DOI PMC
Gala MK, Mizukami Y, Le LP, Moriichi K, Austin T, Yamamoto M, et al. Germline mutations in oncogene-induced senescence pathways are associated with multiple sessile serrated adenomas. Gastroenterology. 2014;146(2):520–9. PubMed DOI PMC
Chubb D, Broderick P, Frampton M, Kinnersley B, Sherborne A, Penegar S, et al. Genetic diagnosis of high-penetrance susceptibility for colorectal cancer (CRC) is achievable for a high proportion of familial CRC by exome sequencing. J Clin Oncol. 2015;33(5):426–32. PubMed DOI
Miao B, Skopelitou D, Srivastava A, Giangiobbe S, Dymerska D, Paramasivam N, et al. Whole-exome sequencing identifies a novel germline variant in PTK7 gene in familial colorectal cancer. Int J Mol Sci. 2022. 10.3390/ijms23031295. PubMed DOI PMC
Skopelitou D, Miao B, Srivastava A, Kumar A, Kuswick M, Dymerska D, et al. Whole exome sequencing identifies APCDD1 and HDAC5 genes as potentially cancer predisposing in familial colorectal cancer. Int J Mol Sci. 2021;22(4):1837. PubMed DOI PMC
Skopelitou D, Miao B, Srivastava A, Kumar A, Kuswik M, Dymerska D, et al. A novel low-risk germline variant in the SH2 domain of the SRC gene affects multiple pathways in familial colorectal cancer. J Pers Med. 2021;11(4):262. PubMed DOI PMC
Skopelitou D, Srivastava A, Miao B, Kumar A, Dymerska D, Paramasivam N, et al. Whole exome sequencing identifies novel germline variants of SLC15A4 gene as potentially cancer predisposing in familial colorectal cancer. Mol Genet Genomics. 2022;297(4):965–79. PubMed DOI PMC
Zhu L, Miao B, Dymerska D, Kuswik M, Bueno-Martinez E, Sanoguera-Miralles L, et al. Germline variants of CYBA and TRPM4 predispose to familial colorectal cancer. Cancers (Basel). 2022. 10.3390/cancers14030670. PubMed DOI PMC
Forsti A, Ambrozkiewicz F, Marciniak M, Lubinski J, Hemminki K. Search for germline gene variants in colorectal cancer families presenting with multiple primary colorectal cancers. Int J Cancer. 2025;156(7):1393–403. PubMed DOI PMC
Kumar A, Bandapalli OR, Paramasivam N, Giangiobbe S, Diquigiovanni C, Bonora E, et al. Familial cancer variant prioritization pipeline version 2 (FCVPPv2) applied to a papillary thyroid cancer family. Sci Rep. 2018;8(1):11635. PubMed DOI PMC
Szklarczyk D, Gable AL, Lyon D, Junge A, Wyder S, Huerta-Cepas J, et al. STRING v11: protein-protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets. Nucleic Acids Res. 2019;47(D1):D607–13. PubMed DOI PMC
McLaren W, Gil L, Hunt SE, Riat HS, Ritchie GR, Thormann A, et al. The Ensembl variant effect predictor. Genome Biol. 2016;17(1):122. PubMed DOI PMC
Rentzsch P, Schubach M, Shendure J, Kircher M. CADD-splice-improving genome-wide variant effect prediction using deep learning-derived splice scores. Genome Med. 2021;13(1):31. PubMed DOI PMC
Kumar P, Henikoff S, Ng PC. Predicting the effects of coding non-synonymous variants on protein function using the SIFT algorithm. Nat Protoc. 2009;4(7):1073–81. PubMed DOI
Adzhubei I, Jordan DM, Sunyaev SR. Predicting functional effect of human missense mutations using PolyPhen-2. Curr Protoc Hum Genet. 2013;76:7–20. PubMed PMC
Chun S, Fay JC. Identification of deleterious mutations within three human genomes. Genome Res. 2009;19(9):1553–61. PubMed DOI PMC
Schwarz JM, Rodelsperger C, Schuelke M, Seelow D. Mutationtaster evaluates disease-causing potential of sequence alterations. Nat Methods. 2010;7(8):575–6. PubMed DOI
Reva B, Antipin Y, Sander C. Predicting the functional impact of protein mutations: application to cancer genomics. Nucleic Acids Res. 2011;39(17):e118. PubMed DOI PMC
Shihab HA, Gough J, Cooper DN, Stenson PD, Barker GL, Edwards KJ, et al. Predicting the functional, molecular, and phenotypic consequences of amino acid substitutions using hidden Markov models. Hum Mutat. 2013;34(1):57–65. PubMed DOI 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(3):235–41. PubMed DOI PMC
Choi Y, Sims GE, Murphy S, Miller JR, Chan AP. Predicting the functional effect of amino acid substitutions and indels. PLoS ONE. 2012;7(10):e46688. PubMed DOI PMC
Cheng J, Novati G, Pan J, Bycroft C, Žemgulytė A, Applebaum T, et al. Accurate proteome-wide missense variant effect prediction with AlphaMissense. Science. 2023;381(6664):eadg7492. PubMed DOI
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(4):877–85. PubMed DOI PMC
Cooper GM, Stone EA, Asimenos G, Green ED, Batzoglou S, Sidow A. Distribution and intensity of constraint in mammalian genomic sequence. Genome Res. 2005;15(7):901–13. PubMed DOI PMC
Siepel A, Bejerano G, Pedersen JS, Hinrichs AS, Hou M, Rosenbloom K, et al. Evolutionarily conserved elements in vertebrate, insect, worm, and yeast genomes. Genome Res. 2005;15(8):1034–50. PubMed DOI PMC
Pollard KS, Hubisz MJ, Rosenbloom KR, Siepel A. Detection of nonneutral substitution rates on mammalian phylogenies. Genome Res. 2010;20(1):110–21. PubMed DOI PMC
Karczewski KJ, Francioli LC, Tiao G, Cummings BB, Alfoldi J, Wang Q, et al. The mutational constraint spectrum quantified from variation in 141,456 humans. Nature. 2020;581(7809):434–43. PubMed DOI PMC
Pejaver V, Urresti J, Lugo-Martinez J, Pagel KA, Lin GN, Nam HJ, et al. Inferring the molecular and phenotypic impact of amino acid variants with MutPred2. Nat Commun. 2020;11(1):5918. PubMed DOI PMC
Jaganathan K, KyriazopoulouPanagiotopoulou S, McRae JF, Darbandi SF, Knowles D, Li YI, et al. Predicting splicing from primary sequence with deep learning. Cell. 2019;176(3):535-48.e24. PubMed DOI
Cheng J, Nguyen TYD, Cygan KJ, Çelik MH, Fairbrother WG, Avsec Ž, et al. MMSplice: modular modeling improves the predictions of genetic variant effects on splicing. Genome Biol. 2019;20(1):48. PubMed DOI PMC
Brohee S, van Helden J. Evaluation of clustering algorithms for protein-protein interaction networks. BMC Bioinform. 2006;7:488. PubMed DOI PMC
Valle L, Vilar E, Tavtigian SV, Stoffel EM. Genetic predisposition to colorectal cancer: syndromes, genes, classification of genetic variants and implications for precision medicine. J Pathol. 2019;247(5):574–88. PubMed DOI PMC
Kumar A, Paramasivam N, Bandapalli OR, Schlesner M, Chen T, Sijmons R, et al. A rare large duplication of MLH1 identified in Lynch syndrome. Hered Cancer Clin Pract. 2021;19(1):10. PubMed DOI PMC
Helgadottir HT, Thutkawkorapin J, Rohlin A, Nordling M, Lagerstedt-Robinson K, Lindblom A. Identification of known and novel familial cancer genes in Swedish colorectal cancer families. Int J Cancer. 2021;149(3):627–34. PubMed DOI
Tanskanen T, Gylfe AE, Katainen R, Taipale M, Renkonen-Sinisalo L, Järvinen H, et al. Systematic search for rare variants in Finnish early-onset colorectal cancer patients. Cancer Genet. 2015;208(1–2):35–40. PubMed DOI
Diaz-Gay M, Franch-Exposito S, Arnau-Collell C, Park S, Supek F, Munoz J, et al. Integrated analysis of germline and tumor DNA identifies new candidate genes involved in familial colorectal cancer. Cancers (Basel). 2019. 10.3390/cancers11030362. PubMed DOI PMC
Arora S, Yan H, Cho I, Fan HY, Luo B, Gai X, et al. Genetic variants that predispose to DNA double-strand breaks in lymphocytes from a subset of patients with familial colorectal carcinomas. Gastroenterology. 2015;149(7):1872-83.e9. PubMed DOI PMC
Esteban-Jurado C, Franch-Expósito S, Muñoz J, Ocaña T, Carballal S, López-Cerón M, et al. The Fanconi anemia DNA damage repair pathway in the spotlight for germline predisposition to colorectal cancer. Eur J Hum Genet. 2016;24(10):1501–5. PubMed DOI PMC
Smith CG, Naven M, Harris R, Colley J, West H, Li N, et al. Exome resequencing identifies potential tumor-suppressor genes that predispose to colorectal cancer. Hum Mutat. 2013;34(7):1026–34. PubMed DOI
Singh AK, Talseth-Palmer B, Xavier A, Scott RJ, Drabløs F, Sjursen W. Detection of germline variants with pathogenic potential in 48 patients with familial colorectal cancer by using whole exome sequencing. BMC Med Genomics. 2023;16(1):126. PubMed DOI PMC
Cornish AJ, Gruber AJ, Kinnersley B, Chubb D, Frangou A, Caravagna G, et al. The genomic landscape of 2,023 colorectal cancers. Nature. 2024;633(8028):127–36. PubMed DOI PMC
Ahmed SBM, Prigent SA. Insights into the Shc family of adaptor proteins. J Mol Signal. 2017;12:2. PubMed DOI PMC
Popova NV, Jücker M. The functional role of extracellular matrix proteins in cancer. Cancers (Basel). 2022. 10.3390/cancers14010238. PubMed DOI PMC