Germline Sequencing Identifies Rare Variants in Finnish Subjects with Familial Germ Cell Tumors

References

• Olson TA, Murray MJ, Rodriguez-galindo C, et al. Pediatric and adolescent extracranial germ cell tumors: the road to collaboration. J Clin Oncol. 2015;33(27):3018–3028. doi:10.1200/JCO.2014.60.5337
   PubMed Web of Science ®Google Scholar
• Pierce JL, Frazier AL, Amatruda JF. Pediatric germ cell tumors: a developmental perspective. Adv Urol. 2018;2018. doi:10.1155/2018/9059382.
   Web of Science ®Google Scholar
• Variants in BAK1, SPRY4, and GAB2 are associated with pediatric germ cell tumors: a report from the Children’s Oncology GroupHHS Public Access: Genes Chromosome Cancer. 2018;56(7):612–625. doi:10.1002/gcc.22457.Variants
   Google Scholar
• Acharya S, Dewees T, Shinohara ET, Perkins SM. Long-term outcomes and late effects for childhood and young adulthood intracranial germinomas. Neuro-Oncology. 2015;17(5):741–746. doi:10.1093/neuonc/nou311
   Web of Science ®Google Scholar
• Ferlin A, Pengo M, Pizzol D, Carraro U, Frigo AC, Foresta C. Variants in KITLG predispose to testicular germ cell cancer independently from spermatogenic function. Endocr Relat Cancer. 2012;101–108. doi:10.1530/ERC-11-0340
   Web of Science ®Google Scholar
• Olie RA, Looijenga LHJ, Boerrigter L, Top B, Rodenhuis S, Langeveld A. N- and KRAS mutations in primary testicular germ cell tumors: incidence and possible biological implications. Genes Chromosomes Cancer. 1995;116:110–116.
   Web of Science ®Google Scholar
• Mostert M, Rosenberg C, Stoop H, Schuyer M, Timmer A. Comparative genomic and in situ hybridization of germ cell tumors of the infantile testis. Lab Invest. 2000;80(7):1055–1064.
   Web of Science ®Google Scholar
• Rijlaarsdam MA, Tax DMJ, Gillis AJM, Dorssers LCJ. Genome wide DNA methylation profiles provide clues to the origin and pathogenesis of germ cell tumors. PLoS One. 2015;1–34. doi:10.1371/journal.pone.0122146
   Web of Science ®Google Scholar
• Chheda H, Palta P, Pirinen M, et al. Whole-genome view of the consequences of a population bottleneck using 2926 genome sequences from Finland and United Kingdom. Nat Publ Gr. 2017;25(4):477–484. doi:10.1038/ejhg.2016.205
   Web of Science ®Google Scholar
• Li H, Durbin R. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics. 2009;25(14):1754–1760. doi:10.1093/bioinformatics/btp324
   PubMed Web of Science ®Google Scholar
• Auwera GA, Carneiro MO, Hartl C, et al. From FastQ data to high‐confidence variant calls: the genome analysis toolkit best practices pipeline. Curr Protoc Bioinformatics. 2013;43(1). doi:10.1002/0471250953.bi1110s43
   Google Scholar
• DePristo MA, Banks E, Poplin R, et al. A framework for variation discovery and genotyping using next-generation DNA sequencing data. Nat Genet. 2011;43(5):491–498. doi:10.1038/ng.806
   PubMed Web of Science ®Google Scholar
• McKenna A, Hanna M, Banks E, et al. The genome analysis toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res. 2010;20(9):1297–1303. doi:10.1101/gr.107524.110
   PubMed Web of Science ®Google Scholar
• Karczewski KJ, Francioli LC, Tiao G, et al. Variation across 141,456 human exomes and genomes reveals the spectrum of loss-of- function intolerance across human protein-coding genes. BioRxiv. 2019:531210.
   Google Scholar
• Sim N-L, Kumar P, Hu J, Henikoff S, Schneider G, Ng PC. SIFT web server: predicting effects of amino acid substitutions on proteins. Nucleic Acids Res. 2012;40(W1):W452–W457. doi:10.1093/nar/gks539
   PubMed Web of Science ®Google Scholar
• Adzhubei IA, Schmidt S, Peshkin L, et al. A method and server for predicting damaging missense mutations. Nat Methods. 2010;7(4):248–249. doi:10.1038/nmeth0410-248
   PubMed Web of Science ®Google Scholar
• Schwarz JM, Cooper DN, Schuelke M, Seelow D. MutationTaster2: mutation prediction for the deep-sequencing age. Nat Methods. 2014;11(4):361–362. doi:10.1038/nmeth.2890
   PubMed Web of Science ®Google Scholar
• Reva B, Antipin Y, Sander C. Predicting the functional impact of protein mutations: application to cancer genomics. Nucleic Acids Res. 2011;39(17):e118. doi:10.1093/nar/gkr407
   PubMed Web of Science ®Google Scholar
• Rogers MF, Shihab HA, Mort M, Cooper DN, Gaunt TR, Campbell C. FATHMM-XF: accurate prediction of pathogenic point mutations via extended features. Hancock J, ed. Bioinformatics. 2018;34(3):511–513. doi:10.1093/bioinformatics/btx536
   PubMed Web of Science ®Google Scholar
• Page A, Navarro M. Context-dependent role of IKK β in cancer. Genes. 2017;8(12):376. doi:10.3390/genes8120376
   Web of Science ®Google Scholar
• Hacioglu BM, Kodaz H, Erdogan B, Cinkaya A, Tastekin E. K-RAS and N-RAS mutations in testicular germ cell tumors. Bosn J Basic Med Sci. 2017;17:159–163.
   Web of Science ®Google Scholar
• Bedi U, Scheel AH, Hennion M, Begus-Nahrmann Y, Rüschoff J, Johnsen SA. SUPT6H controls estrogen receptor activity and cellular differentiation by multiple epigenomic mechanisms. Oncogene. 2015;34(4):465–473. doi:10.1038/onc.2013.558
   PubMed Web of Science ®Google Scholar
• Hirabayashi K, Yasuda M, Kajiwara H, et al. Alterations in mucin expression in ovarian mucinous tumors: immunohistochemical analysis of MUC2, MUC5AC, MUC6, and CD10 expression. Acta Histochem Cytochem. 2008;41(2):15–21. doi:10.1267/ahc.08008
   Web of Science ®Google Scholar
• Kaikkonen E, Rantapero T, Zhang Q, et al. ANO7 is associated with aggressive prostate cancer. Int J Cancer. 2018;143(10):2479–2487. doi:10.1002/ijc.31746
   Web of Science ®Google Scholar
• Backen AC, Cole CL, Lau SC, et al. Heparan sulphate synthetic and editing enzymes in ovarian cancer. Br J Cancer. 2007;96(10):1544–1548. doi:10.1038/sj.bjc.6603747
   PubMed Web of Science ®Google Scholar
• Joshi HP, Subramanian IV, Schnettler EK, et al. Dynamin 2 along with microRNA-199a reciprocally regulate hypoxia-inducible factors and ovarian cancer metastasis. Proc Natl Acad Sci U S A. 2014;111(14):5331–5336. doi:10.1073/pnas.1317242111
   PubMed Web of Science ®Google Scholar
• Dummler, Bettina et al. “Pak protein kinases and their role in cancer.” Cancer metastasis reviews. 2009;28(1-2):51–63. doi:10.1007/s10555-008-9168-1
   Google Scholar
• Phan NN, Wang C-Y, Chen C-F, Sun Z, Lai M-D, Lin Y-C. Voltage-gated calcium channels: novel targets for cancer therapy. Oncol Lett. 2017;14(2):2059–2074. doi:10.3892/ol.2017.6457
   PubMed Web of Science ®Google Scholar
• Hashimoto M, Ichihara M, Watanabe T, et al. Expression of CD109 in human cancer. Oncogene. 2004:3716–3720. doi:10.1038/sj.onc.1207418.
   Web of Science ®Google Scholar
• Qi R, Dong F, Liu Q, Murakumo Y, Liu J. CD109 and squamous cell carcinoma. J Transl Med. 2018;1–8. doi:10.1186/s12967-018-1461-3
   Web of Science ®Google Scholar
• Kitajima S, Thummalapalli R, Barbie DA. Seminars in cell & developmental biology inflammation as a driver and vulnerability of KRAS mediated oncogenesis. Semin Cell Dev Biol. 2016;58:127–135. doi:10.1016/j.semcdb.2016.06.009
   Web of Science ®Google Scholar
• Edson MA, Nagaraja AK, Matzuk MM. The mammalian ovary from genesis to revelation. Endocr Rev. 2009;30:624–712. doi:10.1210/er.2009-0012
   PubMed Web of Science ®Google Scholar
• Talukder AH, Meng Q, Kumar R. CRIPak, a novel endogenous Pak1 inhibitor. Oncogene. 2006;1311–1319. doi:10.1038/sj.onc.1209172
   Web of Science ®Google Scholar
• Schraml P, Schwerdtfeger G, Burkhalter F, et al. Combined array comparative genomic hybridization and tissue microarray analysis suggest PAK1 at 11q13. 5-q14 as a critical oncogene target in ovarian carcinoma. Ame J Pathol. 2003;163(3):985–992.
   PubMed Web of Science ®Google Scholar
• Ong CC, Jubb AM, Haverty PM, et al. apoptosis of tumor cells. Proc Natl Acad Sci. 2011;1(18):2–7. doi:10.1073/pnas.1103350108
   Web of Science ®Google Scholar