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Exome-wide analyses identify low-frequency variant in CYP26B1 and additional coding variants associated with esophageal squamous cell carcinoma

Abstract

Genome-wide association studies have identified common variants associated with risk of esophageal squamous cell carcinoma (ESCC). However, these common variants cannot explain all heritability of ESCC. Here we report an exome-wide interrogation of 3,714 individuals with ESCC and 3,880 controls for low-frequency susceptibility loci, with two independent replication samples comprising 7,002 cases and 8,757 controls. We found six new susceptibility loci in CCHCR1, TCN2, TNXB, LTA, CYP26B1 and FASN (P = 7.77 × 10−24 to P = 1.49 × 10−11), and three low-frequency variants had relatively high effect size (odds ratio > 1.5). Individuals with the rs138478634-GA genotype had significantly lower levels of serum all-trans retinoic acid, an anticancer nutrient, than those with the rs138478634-GG genotype (P = 0.0004), most likely due to an enhanced capacity of variant CYP26B1 to catabolize this agent. These findings emphasize the important role of rare coding variants in the development of ESCC.

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Fig. 1: Manhattan plot for associations between genetic variants and ESCC risk.
Fig. 2: Significant gene–lifestyle interaction for the CYP26B1 rs138478634 variant.
Fig. 3: CYP26B1 rs138478634 variant influences ESCC risk by altering the catabolic activity of the enzyme.

References

  1. Chen, W. et al. Cancer statistics in China, 2015. CA Cancer J. Clin. 66, 115–132 (2016).

    Article  PubMed  Google Scholar 

  2. Torre, L. A. et al. Global cancer statistics, 2012. CA Cancer J. Clin. 65, 87–108 (2015).

    Article  PubMed  Google Scholar 

  3. Abnet, C. C. et al. A shared susceptibility locus in PLCE1 at 10q23 for gastric adenocarcinoma and esophageal squamous cell carcinoma. Nat. Genet. 42, 764–767 (2010).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  4. Wang, L. D. et al. Genome-wide association study of esophageal squamous cell carcinoma in Chinese subjects identifies susceptibility loci at PLCE1 and C20orf54. Nat. Genet. 42, 759–763 (2010).

    CAS  Article  PubMed  Google Scholar 

  5. Wu, C. et al. Genome-wide association study identifies three new susceptibility loci for esophageal squamous-cell carcinoma in Chinese populations. Nat. Genet. 43, 679–684 (2011).

    CAS  Article  PubMed  Google Scholar 

  6. Wu, C. et al. Genome-wide association analyses of esophageal squamous cell carcinoma in Chinese identify multiple susceptibility loci and gene-environment interactions. Nat. Genet. 44, 1090–1097 (2012).

    CAS  Article  PubMed  Google Scholar 

  7. Wu, C. et al. Joint analysis of three genome-wide association studies of esophageal squamous cell carcinoma in Chinese populations. Nat. Genet. 46, 1001–1006 (2014).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  8. Chang, J. et al. Risk prediction of esophageal squamous-cell carcinoma with common genetic variants and lifestyle factors in Chinese population. Carcinogenesis 34, 1782–1786 (2013).

    CAS  Article  PubMed  Google Scholar 

  9. Huyghe, J. R. et al. Exome array analysis identifies new loci and low-frequency variants influencing insulin processing and secretion. Nat. Genet. 45, 197–201 (2013).

    CAS  Article  PubMed  Google Scholar 

  10. Wessel, J. et al. Low-frequency and rare exome chip variants associate with fasting glucose and type 2 diabetes susceptibility. Nat. Commun. 6, 5897 (2015).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  11. Jin, G. et al. Low-frequency coding variants at 6p21.33 and 20q11.21 are associated with lung cancer risk in Chinese populations. Am. J. Hum. Genet. 96, 832–840 (2015).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  12. Rhee, E. P. et al. An exome array study of the plasma metabolome. Nat. Commun. 7, 12360 (2016).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  13. Zhou, F. et al. Deep sequencing of the MHC region in the Chinese population contributes to studies of complex disease. Nat. Genet. 48, 740–746 (2016).

    CAS  Article  PubMed  Google Scholar 

  14. Altucci, L. & Gronemeyer, H. The promise of retinoids to fight against cancer. Nat. Rev. Cancer 1, 181–193 (2001).

    CAS  Article  PubMed  Google Scholar 

  15. Lu, T. Y. et al. Inhibition effects of all trans-retinoic acid on the growth and angiogenesis of esophageal squamous cell carcinoma in nude mice. Chin. Med. J. (Engl.) 124, 2708–2714 (2011).

    CAS  Google Scholar 

  16. Alizadeh, F. et al. Retinoids and their biological effects against cancer. Int. Immunopharmacol. 18, 43–49 (2014).

    CAS  Article  PubMed  Google Scholar 

  17. Chen, M. C., Hsu, S. L., Lin, H. & Yang, T. Y. Retinoic acid and cancer treatment. Biomedicine (Taipei) 4, 22 (2014).

    Article  Google Scholar 

  18. Kim, H. et al. The retinoic acid synthesis gene ALDH1a2 is a candidate tumor suppressor in prostate cancer. Cancer Res. 65, 8118–8124 (2005).

    CAS  Article  PubMed  Google Scholar 

  19. Hou, J. et al. Hepatic RIG-I predicts survival and interferon-α therapeutic response in hepatocellular carcinoma. Cancer Cell 25, 49–63 (2014).

    CAS  Article  PubMed  Google Scholar 

  20. Zhang, N. N. et al. RIG-I plays a critical role in negatively regulating granulocytic proliferation. Proc. Natl. Acad. Sci. USA 105, 10553–10558 (2008).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  21. Jiang, L. J. et al. RA-inducible gene-I induction augments STAT1 activation to inhibit leukemia cell proliferation. Proc. Natl. Acad. Sci. USA 108, 1897–1902 (2011).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  22. Bhattacharya, N. et al. Normalizing microbiota-induced retinoic acid deficiency stimulates protective CD8+ T cell-mediated immunity in colorectal cancer. Immunity 45, 641–655 (2016).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  23. Goralczyk, R. Beta-carotene and lung cancer in smokers: review of hypotheses and status of research. Nutr. Cancer 61, 767–774 (2009).

    CAS  Article  PubMed  Google Scholar 

  24. Li, T., Molteni, A., Latkovich, P., Castellani, W. & Baybutt, R. C. Vitamin A depletion induced by cigarette smoke is associated with the development of emphysema in rats. J. Nutr. 133, 2629–2634 (2003).

    CAS  Article  PubMed  Google Scholar 

  25. Xue, Y., Harris, E., Wang, W. & Baybutt, R. C. Vitamin A depletion induced by cigarette smoke is associated with an increase in lung cancer-related markers in rats. J. Biomed. Sci. 22, 84 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  26. Clugston, R. D. & Blaner, W. S. The adverse effects of alcohol on vitamin A metabolism. Nutrients 4, 356–371 (2012).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  27. Menendez, J. A. & Lupu, R. Fatty acid synthase and the lipogenic phenotype in cancer pathogenesis. Nat. Rev. Cancer 7, 763–777 (2007).

    CAS  Article  PubMed  Google Scholar 

  28. Kuhajda, F. P. Fatty-acid synthase and human cancer: new perspectives on its role in tumor biology. Nutrition 16, 202–208 (2000).

    CAS  Article  PubMed  Google Scholar 

  29. Kuhajda, F. P. Fatty acid synthase and cancer: new application of an old pathway. Cancer Res. 66, 5977–5980 (2006).

    CAS  Article  PubMed  Google Scholar 

  30. Nguyen, P. L. et al. Fatty acid synthase polymorphisms, tumor expression, body mass index, prostate cancer risk, and survival. J. Clin. Oncol. 28, 3958–3964 (2010).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  31. Eggert, S. L. et al. Genome-wide linkage and association analyses implicate FASN in predisposition to Uterine Leiomyomata. Am. J. Hum. Genet. 91, 621–628 (2012).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  32. Campa, D. et al. Genetic variation in genes of the fatty acid synthesis pathway and breast cancer risk. Breast Cancer Res. Treat. 118, 565–574 (2009).

    CAS  Article  PubMed  Google Scholar 

  33. Wuerges, J. et al. Structural basis for mammalian vitamin B12 transport by transcobalamin. Proc. Natl. Acad. Sci. USA 103, 4386–4391 (2006).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  34. Tajuddin, S. M. et al. Genetic and non-genetic predictors of LINE-1 methylation in leukocyte DNA. Environ. Health Perspect. 121, 650–656 (2013).

    PubMed  PubMed Central  Google Scholar 

  35. Hazra, A. et al. Twenty-four non-synonymous polymorphisms in the one-carbon metabolic pathway and risk of colorectal adenoma in the Nurses’ Health Study. Carcinogenesis 28, 1510–1519 (2007).

    CAS  Article  PubMed  Google Scholar 

  36. Hazra, A. et al. Germline polymorphisms in the one-carbon metabolism pathway and DNA methylation in colorectal cancer. Cancer Causes Control 21, 331–345 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  37. Martinelli, M. et al. A candidate gene study of one-carbon metabolism pathway genes and colorectal cancer risk. Br. J. Nutr. 109, 984–989 (2013).

    CAS  Article  PubMed  Google Scholar 

  38. Tse, K. P. et al. Genome-wide association study reveals multiple nasopharyngeal carcinoma-associated loci within the HLA region at chromosome 6p21.3. Am. J. Hum. Genet. 85, 194–203 (2009).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  39. Shiraishi, K. et al. A genome-wide association study identifies two new susceptibility loci for lung adenocarcinoma in the Japanese population. Nat. Genet. 44, 900–903 (2012).

    CAS  Article  PubMed  Google Scholar 

  40. Savage, S. A. et al. Genome-wide association study identifies two susceptibility loci for osteosarcoma. Nat. Genet. 45, 799–803 (2013).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  41. Chen, D. et al. Genome-wide association study of susceptibility loci for cervical cancer. J. Natl. Cancer Inst. 105, 624–633 (2013).

    CAS  Article  PubMed  Google Scholar 

  42. Asumalahti, K. et al. Coding haplotype analysis supports HCR as the putative susceptibility gene for psoriasis at the MHC PSORS1 locus. Hum. Mol. Genet. 11, 589–597 (2002).

    CAS  Article  PubMed  Google Scholar 

  43. Orozco, G. et al. Common genetic variants associated with disease from genome-wide association studies are mutually exclusive in prostate cancer and rheumatoid arthritis. BJU Int. 111, 1148–1155 (2013).

    CAS  Article  PubMed  Google Scholar 

  44. Kote-Jarai, Z. et al. Seven prostate cancer susceptibility loci identified by a multi-stage genome-wide association study. Nat. Genet. 43, 785–791 (2011).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  45. Mao, J. R. et al. Tenascin-X deficiency mimics Ehlers-Danlos syndrome in mice through alteration of collagen deposition. Nat. Genet. 30, 421–425 (2002).

    CAS  Article  PubMed  Google Scholar 

  46. Ikuta, T., Ariga, H. & Matsumoto, K. Extracellular matrix tenascin-X in combination with vascular endothelial growth factor B enhances endothelial cell proliferation. Genes Cells 5, 913–927 (2000).

    CAS  Article  PubMed  Google Scholar 

  47. Minamitani, T., Ariga, H. & Matsumoto, K. Adhesive defect in extracellular matrix tenascin-X-null fibroblasts: a possible mechanism of tumor invasion. Biol. Pharm. Bull. 25, 1472–1475 (2002).

    CAS  Article  PubMed  Google Scholar 

  48. Aggarwal, B. B. Signalling pathways of the TNF superfamily: a double-edged sword. Nat. Rev. Immunol. 3, 745–756 (2003).

    CAS  Article  PubMed  Google Scholar 

  49. Niwa, Y. et al. Lymphotoxin-alpha polymorphism and the risk of cervical cancer in Japanese subjects. Cancer Lett. 218, 63–68 (2005).

    CAS  Article  PubMed  Google Scholar 

  50. Wang, S. S. et al. Common gene variants in the tumor necrosis factor (TNF) and TNF receptor superfamilies and NF-kB transcription factors and non-Hodgkin lymphoma risk. PLoS One 4, e5360 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  51. Aissani, B. et al. The major histocompatibility complex conserved extended haplotype 8.1 in AIDS-related non-Hodgkin lymphoma. J. Acquir. Immune Defic. Syndr. 52, 170–179 (2009).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  52. Skibola, C. F. et al. Tumor necrosis factor (TNF) and lymphotoxin-alpha (LTA) polymorphisms and risk of non-Hodgkin lymphoma in the InterLymph Consortium. Am. J. Epidemiol. 171, 267–276 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  53. Lu, R. et al. A functional polymorphism of lymphotoxin-alpha (LTA) gene rs909253 is associated with gastric cancer risk in an Asian population. Cancer. Epidemiol. 36, e380–e386 (2012).

    CAS  Google Scholar 

  54. Zhang, Y. et al. Tumor necrosis factor-α induced protein 8 polymorphism and risk of non-Hodgkin’s lymphoma in a Chinese population: a case-control study. PLoS One 7, e37846 (2012).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  55. Zhou, P. et al. The lymphotoxin-α 252A>G polymorphism and breast cancer: a meta-analysis. Asian Pac. J. Cancer Prev. 13, 1949–1952 (2012).

    Article  PubMed  Google Scholar 

  56. Sainz, J. et al. Effect of type 2 diabetes predisposing genetic variants on colorectal cancer risk. J. Clin. Endocrinol. Metab. 97, E845–E851 (2012).

    CAS  Article  PubMed  Google Scholar 

  57. Huang, Y. et al. Four genetic polymorphisms of lymphotoxin-alpha gene and cancer risk: a systematic review and meta-analysis. PLoS One 8, e82519 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  58. Goldstein, J. I. et al. zCall: a rare variant caller for array-based genotyping: genetics and population analysis. Bioinformatics 28, 2543–2545 (2012).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  59. Price, A. L. et al. Principal components analysis corrects for stratification in genome-wide association studies. Nat. Genet. 38, 904–909 (2006).

    CAS  Article  PubMed  Google Scholar 

  60. Lou, J. et al. A functional polymorphism located at transcription factor binding sites, rs6695837 near LAMC1 gene, confers risk of colorectal cancer in Chinese populations. Carcinogenesis 38, 177–183 (2017).

    PubMed  Google Scholar 

  61. Li, J. et al. A low-frequency variant in SMAD7 modulates TGF-β signaling and confers risk for colorectal cancer in Chinese population. Mol. Carcinog. 56, 1798–1807 (2017).

    CAS  Article  PubMed  Google Scholar 

  62. Li, Y., Willer, C. J., Ding, J., Scheet, P. & Abecasis, G. R. MaCH: using sequence and genotype data to estimate haplotypes and unobserved genotypes. Genet. Epidemiol. 34, 816–834 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  63. Jia, X. et al. Imputing amino acid polymorphisms in human leukocyte antigens. PLoS One 8, e64683 (2013).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  64. Pruim, R. J. et al. LocusZoom: regional visualization of genome-wide association scan results. Bioinformatics 26, 2336–2337 (2010).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  65. Kane, M. A., Folias, A. E., Wang, C. & Napoli, J. L. Quantitative profiling of endogenous retinoic acid in vivo and in vitro by tandem mass spectrometry. Anal. Chem. 80, 1702–1708 (2008).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  66. Chen, W. et al. Genome-wide association analyses provide genetic and biochemical insights into natural variation in rice metabolism. Nat. Genet. 46, 714–721 (2014).

    CAS  Article  PubMed  Google Scholar 

  67. Kane, M. A., Chen, N., Sparks, S. & Napoli, J. L. Quantification of endogenous retinoic acid in limited biological samples by LC/MS/MS. Biochem. J. 388, 363–369 (2005).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

This work was supported by the National Key Research and Development Plan Program (2016YFC1302702 to X.M., 2016YFC1302701 to C.W. and 2016YFC1302703 to R.Z.); the National Program for Support of Top-notch Young Professionals, National Natural Science Foundation of China (81171878, 81222038 to X.M.); the Fok Ying Tung Foundation for Young Teachers in the Higher Education Institutions of China (131038 to X.M.); and the Program for HUST Academic Frontier Youth Team (to X.M.).

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X.M. and C.W. were the overall principal investigators of this study, who conceived the study and obtained financial support, were responsible for study design and oversaw the entire study, and synthesized the paper. J.C. performed statistical analyses, interpreted the results and drafted the initial manuscript. J.C., R.Z., J.T., J. Li, K.Z., J.K., J. Lou, W.C., B.Z., N.S., Y. Zhang, Y.G., Y.Y., Y. Zhu, D.Z. and X.P. performed laboratory analyses. Z.Z. and X.Z. were responsible for patient recruitment and sample preparation from Hebei province. K.H., T.W. and D.L. reviewed the manuscript. All authors have approved the final report for publication.

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Correspondence to Chen Wu or Xiaoping Miao.

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Supplementary Figure 1

Summary of the study design and work flow

Supplementary Figure 2 Plots for genetic matching of three principal components derived from the PCA of 3,714 cases with ESCC and 3,880 controls, and 206 HapMap individuals without relationships

(a) PC1 versus PC2 for 3,714 cases, 3,880 controls and 206 HapMap individuals, including 57 YRIs, 60 CEUs, 44 JPTs, and 45 CHBs. (b) PC1 versus PC2 for 3,714 ESCC cases and 3,880 controls. (c) PC1 versus PC3 for 3,714 ESCC cases and 3,880 controls. (d) PC2 versus PC3 for 3,714 ESCC cases and 3,880 controls. The case-control matching suggested minimal evidence of population stratification.

Supplementary Figure 3 Quantile-quantile plot and genomic inflation factor lambda for associations with ESCC risk

The results were based on 3,714 ESCC cases and 3,880 controls in the discovery stage of this study. The red circles represent the distribution of P values for the association in the discovery stage. The observed versus expected χ2 test statistics shows no evidence for inflation of χ2 tests (inflation factor λ = 1.032).

Supplementary Figure 4 Regional plots of association results and recombination rates within the four significant susceptibility loci

(a-f) rs130079 (a), rs117353193 (b), rs204900 (c), rs1041981 (d), rs138478634 (e) and rs17848945 (f). The association results were based on imputation results of 3,714 ESCC cases and 3,880 controls in the discovery stage of this study. P values are two sided and were calculated by an additive model in logistic regression analysis adjusted for sex, age, smoking status, drinking status and the first three principle components. For each plot, the −log10P values (y-axis) of the SNPs are presentedaccording to their chromosomal positions (x-axis). The genetic recombination rates (cM/Mb) estimated using the 1000 Genomes June2014 ASN samples are shown with ablue line; we annotated the genes within the region of interest, and these genes are shown as arrows. The LD r2 values were calculated using pairwise linkage disequilibrium analyses. The top genotyped SNP is labeled by rs ID, and the r2 values of the rest of the SNPs with the top genotyped SNP are indicated by different colors.

Supplementary Figure 5 Linkage disequilibrium plot of rs117353193

(a) Regional plot of LD r2 and recombination rates in a 1-Mb region centered by rs117353193. The LD r2 was calculated based on the 1000 Genomes phase 3 ASN population. (b) The LD block plot of variants with LD r2 > 0.1 for rs117353193. The LD r2 was calculated using pairwise linkage disequilibrium analyses in PLINK based on 504 individuals from the 1000 Genomes phase 3 ASN population.

Supplementary Figure 6 Linkage disequilibrium plot of rs17848945

(a) Regional plot of LD r2 and recombination rates in a 1-Mb region centered by rs17848945. The LD r2 was calculated based on the 1000 Genomes phase 3 ASN population. (b) The LD block plot of variants with LD r2 > 0.1 for rs17848945. The LD r2 was calculated using pairwise linkage disequilibrium analyses in PLINK based on 504 individuals from the 1000 Genomes phase 3 ASN population.

Supplementary Figure 7 Linkage disequilibrium plot of rs138478634

(a) Regional plot of LD r2 and recombination rates in a 1-Mb region centered by rs138478634. The LD r2 was calculated based on the 1000 Genomes phase 3 ASN population. (b) The LD block plot of variants with LD r2 > 0.1 for rs138478634. The LD r2 was calculated using pairwise linkage disequilibrium analyses in PLINK based on 504 individuals from the 1000 Genomes phase 3 ASN population.

Supplementary Figure 8 Stratification analysis of the association between risk of ESCC and the six identified SNPs

(a-f) rs130079 (a), rs117353193 (b), rs204900 (c), rs1041981 (d), rs138478634 (e) and rs17848945 (f). Each box and horizontal line represent the OR point estimate and 95% CI derived from the additive model. The analyses were based on 10,716 ESCC cases and 12,637 controls in this study. The area of each box is proportional to the statistical weight of the study. The heterogeneity P values are shown in the right side of the plots.

Supplementary Figure 9 Histogram distribution of minor allele frequencies of variants interrogated in this study in controls

The y-axis shows number of variants. The x-axis shows range of minor allele frequencies.

Supplementary Figure 10 Result of the test of transfection efficiency

(a-f) Relative expression levels of CYP26B1 are shown as determined by western blot (a-d) or qRT–PCR (e,f). The western blot experiment was repeated independently three times with similar results. KYSE30 and KYSE150 cells were transfected with CYP26B1[G], CYP26B1[A] and control vector (a,c,e) or targeting siRNAs and siControl (b,d,f). (a,b) Cropped western blot are shown. (c,d) Full scans of western blots are shown. (e,f) Results present means ± s.e.m. from three independent experiments and each had three replications. P values were compared with control by two-sided unpaired Student’s t-test.

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Chang, J., Zhong, R., Tian, J. et al. Exome-wide analyses identify low-frequency variant in CYP26B1 and additional coding variants associated with esophageal squamous cell carcinoma. Nat Genet 50, 338–343 (2018). https://doi.org/10.1038/s41588-018-0045-8

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