METHODS: We conducted a meta-analysis of four NPC GWAS among Chinese individuals (2,152 cases; 3,740 controls). Forty-three noteworthy findings outside the MHC region were identified and targeted for replication in a pooled analysis of four independent case-control studies across three regions in Asia (4,716 cases; 5,379 controls). A meta-analysis that combined results from the initial GWA and replication studies was performed.
RESULTS: In the combined meta-analysis, rs31489, located within the CLPTM1L/TERT region on chromosome 5p15.33, was strongly associated with NPC (OR = 0.81; P value 6.3 × 10(-13)). Our results also provide support for associations reported from published NPC GWAS-rs6774494 (P = 1.5 × 10(-12); located in the MECOM gene region), rs9510787 (P = 5.0 × 10(-10); located in the TNFRSF19 gene region), and rs1412829/rs4977756/rs1063192 (P = 2.8 × 10(-8), P = 7.0 × 10(-7), and P = 8.4 × 10(-7), respectively; located in the CDKN2A/B gene region).
CONCLUSIONS: We have identified a novel association between genetic variation in the CLPTM1L/TERT region and NPC. Supporting our finding, rs31489 and other SNPs in this region have been reported to be associated with multiple cancer sites, candidate-based studies have reported associations between polymorphisms in this region and NPC, the TERT gene has been shown to be important for telomere maintenance and has been reported to be overexpressed in NPC, and an EBV protein expressed in NPC (LMP1) has been reported to modulate TERT expression/telomerase activity.
IMPACT: Our finding suggests that factors involved in telomere length maintenance are involved in NPC pathogenesis.
METHODS: A discovery cohort of Malaysian Chinese descent (NPC patients, n = 140; Healthy controls, n = 256) were genotyped using Illumina® HumanOmniExpress BeadChip. PennCNV and cnvPartition calling algorithms were applied for CNV calling. Taqman CNV assays and digital PCR were used to validate CNV calls and replicate candidate copy number variant region (CNVR) associations in a follow-up Malaysian Chinese (NPC cases, n = 465; and Healthy controls, n = 677) and Malay cohort (NPC cases, n = 114; Healthy controls, n = 124).
RESULTS: Six putative CNVRs overlapping GRM5, MICA/HCP5/HCG26, LILRB3/LILRA6, DPY19L2, RNase3/RNase2 and GOLPH3 genes were jointly identified by PennCNV and cnvPartition. CNVs overlapping GRM5 and MICA/HCP5/HCG26 were subjected to further validation by Taqman CNV assays and digital PCR. Combined analysis in Malaysian Chinese cohort revealed a strong association at CNVR on chromosome 11q14.3 (Pcombined = 1.54x10-5; odds ratio (OR) = 7.27; 95% CI = 2.96-17.88) overlapping GRM5 and a suggestive association at CNVR on chromosome 6p21.3 (Pcombined = 1.29x10-3; OR = 4.21; 95% CI = 1.75-10.11) overlapping MICA/HCP5/HCG26 genes.
CONCLUSION: Our results demonstrated the association of CNVs towards NPC susceptibility, implicating a possible role of CNVs in NPC development.
METHODS: To discover novel pancreatic cancer risk loci and possible causal genes, we performed a pancreatic cancer transcriptome-wide association study in Europeans using three approaches: FUSION, MetaXcan, and Summary-MulTiXcan. We integrated genome-wide association studies summary statistics from 9040 pancreatic cancer cases and 12 496 controls, with gene expression prediction models built using transcriptome data from histologically normal pancreatic tissue samples (NCI Laboratory of Translational Genomics [n = 95] and Genotype-Tissue Expression v7 [n = 174] datasets) and data from 48 different tissues (Genotype-Tissue Expression v7, n = 74-421 samples).
RESULTS: We identified 25 genes whose genetically predicted expression was statistically significantly associated with pancreatic cancer risk (false discovery rate < .05), including 14 candidate genes at 11 novel loci (1p36.12: CELA3B; 9q31.1: SMC2, SMC2-AS1; 10q23.31: RP11-80H5.9; 12q13.13: SMUG1; 14q32.33: BTBD6; 15q23: HEXA; 15q26.1: RCCD1; 17q12: PNMT, CDK12, PGAP3; 17q22: SUPT4H1; 18q11.22: RP11-888D10.3; and 19p13.11: PGPEP1) and 11 at six known risk loci (5p15.33: TERT, CLPTM1L, ZDHHC11B; 7p14.1: INHBA; 9q34.2: ABO; 13q12.2: PDX1; 13q22.1: KLF5; and 16q23.1: WDR59, CFDP1, BCAR1, TMEM170A). The association for 12 of these genes (CELA3B, SMC2, and PNMT at novel risk loci and TERT, CLPTM1L, INHBA, ABO, PDX1, KLF5, WDR59, CFDP1, and BCAR1 at known loci) remained statistically significant after Bonferroni correction.
CONCLUSIONS: By integrating gene expression and genotype data, we identified novel pancreatic cancer risk loci and candidate functional genes that warrant further investigation.
FINDINGS: We present a draft genome assembly that includes 200 Gb of Illumina reads, 4 Gb of Moleculo synthetic long reads, and 108 Gb of Chicago libraries, with a final size matching the estimated genome size of 2.7 Gb, and a scaffold N50 of 4.8 Mb. We also present an alternative assembly including 27 Gb raw reads generated using the Pacific Biosciences platform. In addition, we sequenced the proteome of the same individual and RNA from 3 different tissue types from 3 other species of squid (Onychoteuthis banksii, Dosidicus gigas, and Sthenoteuthis oualaniensis) to assist genome annotation. We annotated 33,406 protein-coding genes supported by evidence, and the genome completeness estimated by BUSCO reached 92%. Repetitive regions cover 49.17% of the genome.
CONCLUSIONS: This annotated draft genome of A. dux provides a critical resource to investigate the unique traits of this species, including its gigantism and key adaptations to deep-sea environments.
OBJECTIVE: To test if SNPs associated with other traits may also affect the risk of aggressive prostate cancer.
DESIGN, SETTING, AND PARTICIPANTS: SNPs implicated in any phenotype other than prostate cancer (p≤10(-7)) were identified through the catalog of published GWAS and tested in 2891 aggressive prostate cancer cases and 4592 controls from the Breast and Prostate Cancer Cohort Consortium (BPC3). The 40 most significant SNPs were followed up in 4872 aggressive prostate cancer cases and 24,534 controls from the Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome (PRACTICAL) consortium.
OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Odds ratios (ORs) and 95% confidence intervals (CIs) for aggressive prostate cancer were estimated.
RESULTS AND LIMITATIONS: A total of 4666 SNPs were evaluated by the BPC3. Two signals were seen in regions already reported for prostate cancer risk. rs7014346 at 8q24.21 was marginally associated with aggressive prostate cancer in the BPC3 trial (p=1.6×10(-6)), whereas after meta-analysis by PRACTICAL the summary OR was 1.21 (95% CI 1.16-1.27; p=3.22×10(-18)). rs9900242 at 17q24.3 was also marginally associated with aggressive disease in the meta-analysis (OR 0.90, 95% CI 0.86-0.94; p=2.5×10(-6)). Neither of these SNPs remained statistically significant when conditioning on correlated known prostate cancer SNPs. The meta-analysis by BPC3 and PRACTICAL identified a third promising signal, marked by rs16844874 at 2q34, independent of known prostate cancer loci (OR 1.12, 95% CI 1.06-1.19; p=4.67×10(-5)); it has been shown that SNPs correlated with this signal affect glycine concentrations. The main limitation is the heterogeneity in the definition of aggressive prostate cancer between BPC3 and PRACTICAL.
CONCLUSIONS: We did not identify new SNPs for aggressive prostate cancer. However, rs16844874 may provide preliminary genetic evidence on the role of the glycine pathway in prostate cancer etiology.
PATIENT SUMMARY: We evaluated whether genetic variants associated with several traits are linked to the risk of aggressive prostate cancer. No new such variants were identified.