Dataset Information

Quantifying the Genetic Correlation between Multiple Cancer Types.

ABSTRACT: Background: Many cancers share specific genetic risk factors, including both rare high-penetrance mutations and common SNPs identified through genome-wide association studies (GWAS). However, little is known about the overall shared heritability across cancers. Quantifying the extent to which two distinct cancers share genetic origin will give insights to shared biological mechanisms underlying cancer and inform design for future genetic association studies.Methods: In this study, we estimated the pair-wise genetic correlation between six cancer types (breast, colorectal, lung, ovarian, pancreatic, and prostate) using cancer-specific GWAS summary statistics data based on 66,958 case and 70,665 control subjects of European ancestry. We also estimated genetic correlations between cancers and 14 noncancer diseases and traits.Results: After adjusting for 15 pair-wise genetic correlation tests between cancers, we found significant (P < 0.003) genetic correlations between pancreatic and colorectal cancer (rg = 0.55, P = 0.003), lung and colorectal cancer (rg = 0.31, P = 0.001). We also found suggestive genetic correlations between lung and breast cancer (rg = 0.27, P = 0.009), and colorectal and breast cancer (rg = 0.22, P = 0.01). In contrast, we found no evidence that prostate cancer shared an appreciable proportion of heritability with other cancers. After adjusting for 84 tests studying genetic correlations between cancer types and other traits (Bonferroni-corrected P value: 0.0006), only the genetic correlation between lung cancer and smoking remained significant (rg = 0.41, P = 1.03 × 10-6). We also observed nominally significant genetic correlations between body mass index and all cancers except ovarian cancer.Conclusions: Our results highlight novel genetic correlations and lend support to previous observational studies that have observed links between cancers and risk factors.Impact: This study demonstrates modest genetic correlations between cancers; in particular, breast, colorectal, and lung cancer share some degree of genetic basis. Cancer Epidemiol Biomarkers Prev; 26(9); 1427-35. ©2017 AACR.

SUBMITTER: Lindstrom S

PROVIDER: S-EPMC5582139 | biostudies-literature | 2017 Sep

REPOSITORIES: biostudies-literature

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Quantifying the Genetic Correlation between Multiple Cancer Types.

Lindström Sara S Finucane Hilary H Bulik-Sullivan Brendan B Schumacher Fredrick R FR Amos Christopher I CI Hung Rayjean J RJ Rand Kristin K Gruber Stephen B SB Conti David D Permuth Jennifer B JB Lin Hui-Yi HY Goode Ellen L EL Sellers Thomas A TA Amundadottir Laufey T LT Stolzenberg-Solomon Rachael R Klein Alison A Petersen Gloria G Risch Harvey H Wolpin Brian B Hsu Li L Huyghe Jeroen R JR Chang-Claude Jenny J Chan Andrew A Berndt Sonja S Eeles Rosalind R Easton Douglas D Haiman Christopher A CA Hunter David J DJ Neale Benjamin B Price Alkes L AL Kraft Peter P

Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology 20170621 9

<b>Background:</b> Many cancers share specific genetic risk factors, including both rare high-penetrance mutations and common SNPs identified through genome-wide association studies (GWAS). However, little is known about the overall shared heritability across cancers. Quantifying the extent to which two distinct cancers share genetic origin will give insights to shared biological mechanisms underlying cancer and inform design for future genetic association studies.<b>Methods:</b> In this study, ...[more]

PMID: 28637796

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Project description:To investigate the association between the susceptibility to cervical cancer and the single nucleotide polymorphisms of 5 tumor necrosis factor-? promoter genes (rs361525, rs1800629, rs1800750, rs1799964, and rs673) in Chinese women. A total of 946 peripheral blood samples were collected from women of Han Ethnicity in Shandong province. Of them, 452 were diagnosed with cervical squamous cell carcinomas. The study also included a control group of 494 healthy women. The targeted single nucleotide polymorphisms were analyzed by TaqMan probe method. (1) The rate of high-risk subtype human papillomavirus infection in exfoliated cervical epithelial cells was significantly higher in patients with cervical cancer than the control group (91.4% vs 10.3%, P < .01). The rate of human papillomavirus infection was lower in patients with carcinoma in situ than those with invasive carcinoma (77.9% vs 95.4%, P < .01). (2) There was a significant difference for rs361525 genotype (CC/CT/TT) between the control, carcinoma in situ, and invasive carcinoma groups ( P < .001). Both rs1800629 and rs1799964 genotypes (both GG/GA/AA) were also different between these groups ( P < .001 and P < .001). (3) The allele frequencies of rs361525, rs1800629, and rs1799964 were significantly correlated with the diagnosis of cervical cancer. The frequency of T allele in rs361525 was significantly higher for cervical cancer group (10.8%) than control group (3.8%; odds ratio = 3.04, 95% confidence interval = 1.76-5.25, P < .01). The frequency of A allele in rs1800629 was significantly higher for cervical cancer (29.9%) than control group (14.2%; odds ratio = 2.58, 95% confidence interval = 1.87-3.56, P < .01). The frequency of A allele in rs1799964 was also higher for cervical cancer group (38.3%) than control group (16.4%; odds ratio = 1.43, 95% confidence interval = 1.07-1.91, P < .05). The rs361525, rs1800629, and rs17999645 were significantly correlated with the diagnosis of cervical cancer.

Dataset Information

Quantifying the Genetic Correlation between Multiple Cancer Types.

Publications

Quantifying the Genetic Correlation between Multiple Cancer Types.

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