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Additional file 1: Appendix 1.0. Study design and subjects. Appendix 2.0. Assessment of risk factors. Appendix 3.0. Definition of GC cases. Table S1. Results of univariate Cox regression analysis in the CKB cohort. Table S2. Results of multivariate Cox regression model and corresponding risk points in sensitivity analysis 1: excluding weak variables in the simplified model. Table S3. Results of multivariate Cox regression model and corresponding risk points in sensitivity analysis 2: integrating lifestyle factors as an index. Table S4. Results of multivariate Cox regression model and corresponding risk points in sensitivity analysis 3: excluding participants who had GC diagnosis within the first year after recruitment. Table S5. Results of multivariate Cox regression model and corresponding risk points in sensitivity analysis 4: excluding participants who had cancer at baseline. Table S6. Results and corresponding risk points in sensitivity analysis 5: competing risk model by considering death as a competing event. Table S7. Risk categories by deciles of the GCRS in the CKB cohort. Table S8. Internal validation of the GCRS in different regions of CKB. Table S9. Harrell’s C-index of the GCRS from ten-fold cross validation in the CKB cohort. Table S10. Risk categories of the GCRS in the Changzhou cohort. Table S11. Risk categories and associated 3-year, 5-year, and 10-year risk of incident GC derived from CKB. Table S12. Risk categories of different gastric lesions in the Yangzhou screening program. Table S13. Performance of the GCRS across different predicted risk cutoffs in the Yangzhou screening program. Table S14. Risk categories of different gastric lesions in the Yangzhou screening program in sensitivity analysis 1: excluding weak variables in the simplified model. Table S15. Risk categories of different gastric lesions in the Yangzhou screening program in sensitivity analysis 2: integrating lifestyle factors as an index. Table S16. Risk categories of different gastric lesions in the Yangzhou screening program in sensitivity analysis 3: excluding participants who had GC diagnosis within the first year after recruitment. Table S17. Risk categories of different gastric lesions in the Yangzhou screening program in sensitivity analysis 4: excluding participants who had cancer at baseline. Table S18. Risk categories of different gastric lesions in the Yangzhou screening program in sensitivity analysis 5: competing risk model. Table S19. The GCRS and corresponding 3-year, 5-year, and 10-year risk of incident GC derived from the CKB cohort. Fig. S1. Study design and eligible participants’ selection procedures in three studies. Fig. S2. The relationship of the GCRS with incident GC risk in the CKB cohort. Fig. S3. The relationship of the GCRS with incident GC risk in the Changzhou cohort. Fig. S4. Calibration and discrimination of the GCRS in sensitivity analysis 1: excluding weak variables in the simplified model. Fig. S5. Calibration and discrimination of the GCRS in sensitivity analysis 2: integrating lifestyle factors as an index. Fig. S6. Calibration and discrimination of the GCRS in sensitivity analysis 3: excluding participants who had GC diagnosis within the first year after recruitment. Fig. S7. Calibration and discrimination of the GCRS in sensitivity analysis 4: excluding participants who had cancer at baseline. Fig. S8. Calibration and discrimination of the GCRS in sensitivity analysis 5: competing risk model.

Ovarian cancer survival varies considerably among patients, to which germline variation may also contribute in addition to mutational signatures. To identify genetic markers modulating ovarian cancer outcome, we performed a genome-wide association study in 2130 Chinese ovarian cancer patients and found a hitherto unrecognized locus at 3p26.1 to be associated with the overall survival (Pcombined = 8.90 × 10−10). Subsequent statistical fine-mapping, functional annotation, and eQTL mapping prioritized a likely casual SNP rs9311399 in the non-coding regulatory region. Mechanistically, rs9311399 altered its enhancer activity through an allele-specific transcription factor binding and a long-range interaction with the promoter of a lncRNA BHLHE40-AS1. Deletion of the rs9311399-associated enhancer resulted in expression changes in several oncogenic signaling pathway genes and a decrease in tumor growth. Thus, we have identified a novel genetic locus that is associated with ovarian cancer survival possibly through a long-range gene regulation of oncogenic pathways.

Osteosarcoma, a malignant primary bone tumor most commonly diagnosed in children and adolescents, has a poorly understood genetic etiology. Genome-wide association studies (GWAS) and candidate-gene analyses have identified putative risk variants in subjects of European ancestry. However, despite higher incidence among African-American and Hispanic children, little is known regarding common heritable variation that contributes to osteosarcoma incidence and clinical presentation across racial/ethnic groups. In a multi-ethnic sample of non-Hispanic white, Hispanic, African-American and Asian/Pacific Islander children (537 cases, 2165 controls), we performed association analyses assessing previously-reported loci for osteosarcoma risk and metastasis, including meta-analysis across racial/ethnic groups. We also assessed a previously described association between genetic predisposition to longer leukocyte telomere length (LTL) and osteosarcoma risk in this independent multi-ethnic dataset. In our sample, we were unable to replicate previously-reported loci for osteosarcoma risk or metastasis detected in GWAS of European-ancestry individuals in either ethnicity-stratified analyses or meta-analysis across ethnic groups. Our analyses did confirm that genetic predisposition to longer LTL is a risk factor for osteosarcoma (ORmeta: 1.22; 95% CI: 1.09-1.36; P = 3.8 × 10-4), and the strongest effect was seen in Hispanic subjects (OR: 1.32; 95% CI: 1.12-1.54, P = 6.2 × 10-4). Our findings shed light on the replicability of osteosarcoma risk loci across ethnicities and motivate further characterization of these genetic factors in diverse clinical cohorts.

OBJECTIVE: Genome-wide association studies (GWASs) for epithelial ovarian cancer (EOC) have focused largely on populations of European ancestry. We aimed to identify common germline variants associated with EOC risk in Asian women. METHODS: Genotyping was performed as part of the OncoArray project. Samples with >60% Asian ancestry were included in the analysis. Genotyping was performed on 533,631 SNPs in 3238 Asian subjects diagnosed with invasive or borderline EOC and 4083 unaffected controls. After imputation, genotypes were available for 11,595,112 SNPs to identify associations. RESULTS: At chromosome 6p25.2, SNP rs7748275 was associated with risk of serous EOC (odds ratio [OR] = 1.34, P = 8.7 × 10-9) and high-grade serous EOC (HGSOC) (OR = 1.34, P = 4.3 × 10-9). SNP rs6902488 at 6p25.2 (r2 = 0.97 with rs7748275) lies in an active enhancer and is predicted to impact binding of STAT3, P300 and ELF1. We identified additional risk loci with low Bayesian false discovery probability (BFDP) scores, indicating they are likely to be true risk associations (BFDP

BackgroundAlthough increased height has been associated with osteosarcoma risk in previous epidemiologic studies, to the authors' knowledge the relative contribution of stature during different developmental timepoints remains unclear. Furthermore, the question of how genetic determinants of height impact osteosarcoma etiology remains unexplored. Genetic variants associated with stature in previous genome-wide association studies may be biomarkers of osteosarcoma risk.MethodsThe authors tested the associations between osteosarcoma risk and polygenic scores for adult height (416 variants), childhood height (6 variants), and birth length (5 variants) in 864 osteosarcoma cases and 1879 controls of European ancestry.ResultsEach standard deviation increase in the polygenic score for adult height, corresponding to a 1.7-cm increase in stature, was found to be associated with a 1.10-fold increase in the risk of osteosarcoma (95% confidence interval [95% CI], 1.01-1.19; P =.027). Each standard deviation increase in the polygenic score for childhood height, corresponding to a 0.5-cm increase in stature, was associated with a 1.10-fold increase in the risk of osteosarcoma (95% CI, 1.01-1.20; P =.023). The polygenic score for birth length was not found to be associated with osteosarcoma risk (P =.11). When adult and childhood height scores were modeled together, they were found to be independently associated with osteosarcoma risk (P =.037 and P = .043, respectively). An expression quantitative trait locus for cartilage intermediate layer protein 2 (CILP2), rs8103992, was significantly associated with osteosarcoma risk after adjustment for multiple comparisons (odds ratio, 1.35; 95% CI, 1.16-1.56 [P = 7.93×10-5 and Padjusted =.034]).ConclusionsA genetic propensity for taller adult and childhood height attainments contributed independently to osteosarcoma risk in the current study data. These results suggest that the biological pathways affecting normal bone growth may be involved in osteosarcoma etiology.

Circulating Epstein-Barr virus DNA is a predictor of disease recurrence in patients with nasopharyngeal carcinoma. Circulating human papillomavirus (HPV) DNA has been detected in the sera of some patients with HPV-positive squamous cell carcinoma of the oropharynx (OPC). The goal of the current study was to determine whether pretreatment serum HPV DNA is a useful biomarker for disease recurrence in patients with HPV-positive OPC.The study included patients with newly diagnosed, previously untreated OPC. Tumor HPV status was determined by polymerase chain reaction; serum HPV DNA was detected using real-time polymerase chain reaction. Differences in clinical characteristics between patients who were positive and negative for pretreatment serum HPV DNA were described using standard descriptive statistical methods. Kaplan-Meier curves were generated and log-rank tests were used to detect statistically significant differences in progression-free survival (PFS).A total of 262 patients were included. Patients with high N category and those with TNM stage IV disease were found to have higher rates of detectable pretreatment serum HPV DNA. Patients with HPV-positive tumors had better PFS than patients with HPV-negative tumors. Among patients with HPV-positive tumors, those who were negative for pretreatment serum HPV DNA had better PFS than those who were positive for pretreatment serum HPV DNA, but this result was not statistically significant.Pretreatment serum HPV DNA was associated with higher N category and overall disease stage. However, pretreatment serum HPV DNA does not appear to have clinical usefulness as a marker for disease recurrence among patients with OPC.

We report a genome-wide association study for melanoma that was conducted by the GenoMEL Consortium. Our discovery phase included 2,981 individuals with melanoma and 1,982 study-specific control individuals of European ancestry, as well as an additional 6,426 control subjects from French or British populations, all of whom were genotyped for 317,000 or 610,000 single-nucleotide polymorphisms (SNPs). Our analysis replicated previously known melanoma susceptibility loci. Seven new regions with at least one SNP with P < 10−5 and further local imputed or genotyped support were selected for replication using two other genome-wide studies (from Australia and Texas, USA). Additional replication came from case-control series from the UK and The Netherlands. Variants at three of the seven loci replicated at P < 10−3: an SNP in ATM (rs1801516, overall P = 3.4 × 10−9), an SNP in MX2 (rs45430, P = 2.9 × 10−9) and an SNP adjacent to CASP8 (rs13016963, P = 8.6 × 10−10). A fourth locus near CCND1 remains of potential interest, showing suggestive but inconclusive evidence of replication (rs1485993, overall P = 4.6 × 10−7 under a fixed-effects model and P = 1.2 × 10−3 under a random-effects model). These newly associated variants showed no association with nevus or pigmentation phenotypes in a large British case-control series.

We report a genome-wide association study for melanoma that was conducted by the GenoMEL Consortium. Our discovery phase included 2,981 individuals with melanoma and 1,982 study-specific control individuals of European ancestry, as well as an additional 6,426 control subjects from French or British populations, all of whom were genotyped for 317,000 or 610,000 single-nucleotide polymorphisms (SNPs). Our analysis replicated previously known melanoma susceptibility loci. Seven new regions with at least one SNP with P < 10−5 and further local imputed or genotyped support were selected for replication using two other genome-wide studies (from Australia and Texas, USA). Additional replication came from case-control series from the UK and The Netherlands. Variants at three of the seven loci replicated at P < 10−3: an SNP in ATM (rs1801516, overall P = 3.4 × 10−9), an SNP in MX2 (rs45430, P = 2.9 × 10−9) and an SNP adjacent to CASP8 (rs13016963, P = 8.6 × 10−10). A fourth locus near CCND1 remains of potential interest, showing suggestive but inconclusive evidence of replication (rs1485993, overall P = 4.6 × 10−7 under a fixed-effects model and P = 1.2 × 10−3 under a random-effects model). These newly associated variants showed no association with nevus or pigmentation phenotypes in a large British case-control series.

Author(s): Jung, Su Yon; Mancuso, Nicholas; Papp, Jeanette; Sobel, Eric; Zhang, Zuo-Feng | Abstract: PurposeThe role of insulin resistance (IR) in developing postmenopausal breast cancer has not been thoroughly resolved and may be confounded by lifestyle factors such as obesity. We examined whether genetically determined IR is causally associated with breast cancer risk.MethodsWe conducted Mendelian randomization (MR) analyses using individual-level data from our previous meta-analysis of a genome-wide association study (GWAS) (n = 11,109 non-Hispanic white postmenopausal women). Four single-nucleotide polymorphisms were associated with fasting glucose (FG), 2 with fasting insulin (FI), and 6 with homeostatic model assessment-IR (HOMA-IR) but were not associated with obesity. We used this GWAS to employ hazard ratios (HRs) for breast cancer risk by adjusting for potential confounding factors.ResultsNo direct association was observed between comprising 12 IR genetic instruments and breast cancer risk (HR = 0.93, 95% CI: 0.76-1.14). In phenotype-specific analysis, genetically elevated FG was associated with reduced risk for breast cancer (main contributor of this MR-effect estimate: G6PC2 rs13431652; HR = 0.59, 95% CI: 0.35-0.99). Genetically driven FI and HOMA-IR were not significantly associated. Stratification analyses by body mass index, exercise, and dietary fat intake with combined phenotypes showed that genetically elevated IR was associated with greater breast cancer risk in overall obesity and inactive subgroups (single contributor: MTRR/LOC729506 rs13188458; HR = 2.21, 95% CI: 1.03-4.75).ConclusionsWe found complex evidence for causal association between IR and risk of breast cancer, which may support the potential value of intervention trials to lower IR and reduce breast cancer risk.