Identification of epistatic interactions through genome-wide association studies in sporadic medullary and juvenile papillary thyroid carcinomas
Tóm tắt
The molecular mechanisms leading to sporadic medullary thyroid carcinoma (sMTC) and juvenile papillary thyroid carcinoma (PTC), two rare tumours of the thyroid gland, remain poorly understood. Genetic studies on thyroid carcinomas have been conducted, although just a few loci have been systematically associated. Given the difficulties to obtain single-loci associations, this work expands its scope to the study of epistatic interactions that could help to understand the genetic architecture of complex diseases and explain new heritable components of genetic risk. We carried out the first screening for epistasis by Multifactor-Dimensionality Reduction (MDR) in genome-wide association study (GWAS) on sMTC and juvenile PTC, to identify the potential simultaneous involvement of pairs of variants in the disease. We have identified two significant epistatic gene interactions in sMTC (CHFR-AC016582.2 and C8orf37-RNU1-55P) and three in juvenile PTC (RP11-648k4.2-DIO1, RP11-648k4.2-DMGDH and RP11-648k4.2-LOXL1). Interestingly, each interacting gene pair included a non-coding RNA, providing thus support to the relevance that these elements are increasingly gaining to explain carcinoma development and progression. Overall, this study contributes to the understanding of the genetic basis of thyroid carcinoma susceptibility in two different case scenarios such as sMTC and juvenile PTC.
Tài liệu tham khảo
Figge JJ. Epidemiology of thyroid cancer. In: Wartofsky LVND, editor. Thyroid Cancer: A Comprehensive Guide to Clinical Management. Totowa: Human Press; 1999.
Randolph GW, Maniar D. Medullary carcinoma of the thyroid. Cancer Control. 2000;7(3):253–61.
Moline J EC: Multiple Endocrine Neoplasia Type 2. In: SourceGeneReviews® [Internet]. Edited by Pagon RA AM, Ardinger HH, Wallace SE, Amemiya A, Bean LJH, Bird TD, Dolan CR, Fong CT, Smith RJH, Stephens K, editors. Seattle: University of Washington, Seattle; 2005.
Eng C, Clayton D, Schuffenecker I, Lenoir G, Cote G, Gagel RF, et al. The relationship between specific RET proto-oncogene mutations and disease phenotype in multiple endocrine neoplasia type 2. International RET mutation consortium analysis. Jama. 1996;276(19):1575–9.
Fernandez RM, Pecina A, Antinolo G, Navarro E, Borrego S. Analysis of RET polymorphisms and haplotypes in the context of sporadic medullary thyroid carcinoma. Thyroid. 2006;16(4):411–7.
Landa I, Robledo M. Association studies in thyroid cancer susceptibility: are we on the right track? J Mol Endocrinol. 2011;47(1):R43–58.
Ruiz-Llorente S, Montero-Conde C, Milne RL, Moya CM, Cebrian A, Leton R, et al. Association study of 69 genes in the ret pathway identifies low-penetrance loci in sporadic medullary thyroid carcinoma. Cancer Res. 2007;67(19):9561–7.
Kondo T, Ezzat S, Asa SL. Pathogenetic mechanisms in thyroid follicular-cell neoplasia. Nat Rev Cancer. 2006;6(4):292–306.
Dottorini ME, Vignati A, Mazzucchelli L, Lomuscio G, Colombo L. Differentiated thyroid carcinoma in children and adolescents: a 37-year experience in 85 patients. J Nucl Med. 1997;38(5):669–75.
Sassolas G, Hafdi-Nejjari Z, Ferraro A, Decaussin-Petrucci M, Rousset B, Borson-Chazot F, et al. Oncogenic alterations in papillary thyroid cancers of young patients. Thyroid. 2012;22(1):17–26.
Hod N, Hagag P, Baumer M, Sandbank J, Horne T. Differentiated thyroid carcinoma in children and young adults: evaluation of response to treatment. Clin Nucl Med. 2005;30(6):387–90.
Schonfeld SJ, Lee C, Berrington de Gonzalez A. Medical exposure to radiation and thyroid cancer. Clin Oncol (R Coll Radiol). 2011;23(4):244–50.
Fridman MV, Savva NN, Krasko OV, Zborovskaya AA, Mankovskaya SV, Schmid KW, et al. Clinical and pathologic features of ‘sporadic’ papillary thyroid carcinoma registered in 2005-2008 years in children and adolescents of Belarus. Thyroid. 2012;22(10):1016-24.
Manolio TA, Collins FS. The HapMap and genome-wide association studies in diagnosis and therapy. Annu Rev Med. 2009;60:443–56.
Hindorff LA, Sethupathy P, Junkins HA, Ramos EM, Mehta JP, Collins FS, et al. Potential etiologic and functional implications of genome-wide association loci for human diseases and traits. Proc Natl Acad Sci U S A. 2009;106(23):9362–7.
Mackay TF, Moore JH. Why epistasis is important for tackling complex human disease genetics. Genome Med. 2014;6(6):42.
Musani SK, Shriner D, Liu N, Feng R, Coffey CS, Yi N, et al. Detection of gene x gene interactions in genome-wide association studies of human population data. Hum Hered. 2007;63(2):67–84.
Ritchie MD, Hahn LW, Roodi N, Bailey LR, Dupont WD, Parl FF, et al. Multifactor-dimensionality reduction reveals high-order interactions among estrogen-metabolism genes in sporadic breast cancer. Am J Hum Genet. 2001;69(1):138–47.
Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MA, Bender D, et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet. 2007;81(3):559–75.
Price AL, Patterson NJ, Plenge RM, Weinblatt ME, Shadick NA, Reich D. Principal components analysis corrects for stratification in genome-wide association studies. Nat Genet. 2006;38(8):904–9.
Clarke GM, Anderson CA, Pettersson FH, Cardon LR, Morris AP, Zondervan KT. Basic statistical analysis in genetic case–control studies. Nat Protoc. 2011;6(2):121–33.
Benjamini Y, Drai D, Elmer G, Kafkafi N, Golani I. Controlling the false discovery rate in behavior genetics research. Behav Brain Res. 2001;125(1-2):279–84.
de Bakker PI, Yelensky R, Pe’er I, Gabriel SB, Daly MJ, Altshuler D. Efficiency and power in genetic association studies. Nat Genet. 2005;37(11):1217–23.
González CYB M, F Salavert, R, Sánchez, J, Dopazo, Medina I. Multicore and Cloud-Based Solutions for Genomic Variant Analysis. In: Euro-Par 2012: Parallel Processing Workshops Lecture Notes in Computer Science vol. 7640; Springer, Berlin 2013: 273–284.
da Huang W, Sherman BT, Lempicki RA. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc. 2009;4(1):44–57.
Bulusu KC, Tym JE, Coker EA, Schierz AC, Al-Lazikani B. canSAR: updated cancer research and drug discovery knowledgebase. Nucleic Acids Res. 2014;42(Database issue):D1040–1047.
Forbes SA, Bindal N, Bamford S, Cole C, Kok CY, Beare D, et al. COSMIC: mining complete cancer genomes in the Catalogue of Somatic Mutations in Cancer. Nucleic Acids Res. 2011;39(Database issue):D945–950.
Stelzer G, Dalah I, Stein TI, Satanower Y, Rosen N, Nativ N, et al. In-silico human genomics with GeneCards. Hum Genomics. 2011;5(6):709–17.
Warde-Farley D, Donaldson SL, Comes O, Zuberi K, Badrawi R, Chao P, et al. The GeneMANIA prediction server: biological network integration for gene prioritization and predicting gene function. Nucleic Acids Res. 2010;38(Web Server issue):W214–220.
Uhlen M, Fagerberg L, Hallstrom BM, Lindskog C, Oksvold P, Mardinoglu A, et al. Proteomics. Tissue-based map of the human proteome. Science. 2015;347(6220):1260419.
Barrett T, Wilhite SE, Ledoux P, Evangelista C, Kim IF, Tomashevsky M, et al. NCBI GEO: archive for functional genomics data sets--update. Nucleic Acids Res. 2013;41(Database issue):D991–995.
Gaudet P, Michel PA, Zahn-Zabal M, Cusin I, Duek PD, Evalet O, et al. The neXtProt knowledgebase on human proteins: current status. Nucleic Acids Res. 2015;43(Database issue):D764–770.
Xie C, Yuan J, Li H, Li M, Zhao G, Bu D, et al. NONCODEv4: exploring the world of long non-coding RNA genes. Nucleic Acids Res. 2014;42(Database issue):D98–103.
Bleda M, Tarraga J, de Maria A, Salavert F, Garcia-Alonso L, Celma M, et al. CellBase, a comprehensive collection of RESTful web services for retrieving relevant biological information from heterogeneous sources. Nucleic Acids Res. 2012;40(Web Server issue):W609–614.
Derks S, Cleven AH, Melotte V, Smits KM, Brandes JC, Azad N, van Criekinge W, de Bruine AP, Herman JG, van Engeland M: Emerging evidence for CHFR as a cancer biomarker: from tumor biology to precision medicine. Cancer Metastasis Rev 2013.
Holley CL, Topkara VK. An introduction to small non-coding RNAs: miRNA and snoRNA. Cardiovasc Drugs Ther. 2011;25(2):151–9.
Frasca F, Rustighi A, Malaguarnera R, Altamura S, Vigneri P, Del Sal G, et al. HMGA1 inhibits the function of p53 family members in thyroid cancer cells. Cancer Res. 2006;66(6):2980–9.
Zou M, Baitei EY, Alzahrani AS, Al-Mohanna F, Farid NR, Meyer B, et al. Oncogenic activation of MAP kinase by BRAF pseudogene in thyroid tumors. Neoplasia. 2009;11(1):57–65.
Alonso R, Salavert F, Garcia-Garcia F, Carbonell-Caballero J, Bleda M, Garcia-Alonso L, et al. Babelomics 5.0: functional interpretation for new generations of genomic data. Nucleic Acids Res. 2015;43(W1):W117–121.
Arnaldi LA, Borra RC, Maciel RM, Cerutti JM. Gene expression profiles reveal that DCN, DIO1, and DIO2 are underexpressed in benign and malignant thyroid tumors. Thyroid. 2005;15(3):210–21.
Binzak BA, Wevers RA, Moolenaar SH, Lee YM, Hwu WL, Poggi-Bach J, et al. Cloning of dimethylglycine dehydrogenase and a new human inborn error of metabolism, dimethylglycine dehydrogenase deficiency. Am J Hum Genet. 2001;68(4):839–47.
Bell A, Bell D, Weber RS, El-Naggar AK. CpG island methylation profiling in human salivary gland adenoid cystic carcinoma. Cancer. 2011;117(13):2898–909.
He H, Li W, Liyanarachchi S, Jendrzejewski J, Srinivas M, Davuluri RV, et al. Genetic predisposition to papillary thyroid carcinoma: involvement of FOXE1, TSHR and a novel lincRNA gene, PTCSC2. J Clin Endocrinol Metab. 2014;100(1):E164–72. doi:10.1210/jc.2014-2147.
Wang Y, Guo Q, Zhao Y, Chen J, Wang S, Hu J, et al. BRAF-activated long non-coding RNA contributes to cell proliferation and activates autophagy in papillary thyroid carcinoma. Oncol Lett. 2014;8(5):1947–52.
Fernandez RM, Bleda M, Luzon-Toro B, Garcia-Alonso L, Arnold S, Sribudiani Y, et al. Pathways systematically associated to Hirschsprung’s disease. Orphanet J Rare Dis. 2013;8(1):187.