The pan-cancer analysis of whole genomes The expansion of whole-genome sequencing studies from individual ICGC and TCGA working groups presented the opportunity to undertake a meta-analysis of genomic features across tumour types. To achieve this, the PCAWG Consortium was established. A Technical Working Group implemented the informatics analyses by aggregating the raw sequencing data from different working groups that studied individual tumour types, aligning the sequences to the human genome and delivering a set of high-quality somatic mutation calls for downstream analysis (Extended Data Fig. 1). Given the recent meta-analysis

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A sample size with sufficient statistical power is critical to the success of genetic association studies to detect causal genes of human complex diseases. Genome-wide association studies require much larger sample sizes to achieve an adequate statistical power. We estimated the statistical power with increasing numbers of markers analyzed and compared the sample sizes that were required in case-control studies and case-parent studies. We computed the effective sample size and statistical power using Genetic Power Calculator. An analysis using a larger number of markers requires a larger sample size. Testing a single-nucleotide polymorphism (SNP) marker requires 248 cases, while testing 500,000 SNPs and 1 million markers requires 1,206 cases and 1,255 cases, respectively, under the assumption of an odds ratio of 2, 5% disease prevalence, 5% minor allele frequency, complete linkage disequilibrium (LD), 1:1 case/control ratio, and a 5% error rate in an allelic test. Under a dominant model, a smaller sample size is required to achieve 80% power than other genetic models. We found that a much lower sample size was required with a strong effect size, common SNP, and increased LD. In addition, studying a common disease in a case-control study of a 1:4 case-control ratio is one way to achieve higher statistical power. We also found that case-parent studies require more samples than case-control studies. Although we have not covered all plausible cases in study design, the estimates of sample size and statistical power computed under various assumptions in this study may be useful to determine the sample size in designing a population-based genetic association study.

OBJECTIVE:Evaluations of screening or diagnostic tests sometimes incorporate measures of overall accuracy , diagnostic accuracy , or test efficiency . These terms refer to a single summary measurement calculated from 2 × × × × 2 contingency tables that is the overall probability that a patient will be correctly classified by a screening or diagnostic test. We assessed the value of overall accuracy in studies of test validity, a topic that has not received adequate emphasis in the clinical literature. DESIGN:Guided by previous reports, we summarize the issues concerning the use of overall accuracy. To document its use in contemporary studies, a search was performed for test evaluation studies published in the clinical literature from 2000 to 2002 in which overall accuracy derived from a 2 × × × × 2 contingency table was reported. MEASUREMENTS AND MAIN RESULTS:Overall accuracy is the weighted average of a test's sensitivity and specificity, where sensitivity is weighted by prevalence and specificity is weighted by the complement of prevalence. Overall accuracy becomes particularly problematic as a measure of validity as 1) the difference between sensitivity and specificity increases and/or 2) the prevalence deviates away from 50%. Both situations lead to an increasing deviation between overall accuracy and either sensitivity or specificity. A summary of results from published studies ( N = = = = 25) illustrated that the prevalencedependent nature of overall accuracy has potentially negative consequences that can lead to a distorted impression of the validity of a screening or diagnostic test. CONCLUSIONS:Despite the intuitive appeal of overall accuracy as a single measure of test validity, its dependence on prevalence renders it inferior to the careful and balanced consideration of sensitivity and specificity.

Adiponectin is associated with obesity and insulin resistance. To date, there has been no genome-wide association study (GWAS) of adiponectin levels in Asians. Here we present a GWAS of a cohort of Korean volunteers. A total of 4,001 subjects were genotyped by using a genome-wide marker panel in a two-stage design (979 subjects initially and 3,022 in a second stage). Another 2,304 subjects were used for follow-up replication studies with selected markers. In the discovery phase, the top SNP associated with mean log adiponectin was rs3865188 in CDH13 on chromosome 16 (p = 1.69 × 10(-15) in the initial sample, p = 6.58 × 10(-39) in the second genome-wide sample, and p = 2.12 × 10(-32) in the replication sample). The meta-analysis p value for rs3865188 in all 6,305 individuals was 2.82 × 10(-83). The association of rs3865188 with high-molecular-weight adiponectin (p = 7.36 × 10(-58)) was even stronger in the third sample. A reporter assay that evaluated the effects of a CDH13 promoter SNP in complete linkage disequilibrium with rs3865188 revealed that the major allele increased expression 2.2-fold. This study clearly shows that genetic variants in CDH13 influence adiponectin levels in Korean adults.

Purpose:The interferon regulatory factor 6 (IRF6), the gene that causes van der Woude syndrome has been shown to be associated with nonsyndromic cleft lip with or without palate in several populations. This study aimed to confirm the contribution of IRF6 to cleft lip with or without palate risk in additional Asian populations. Methods: A set of 13 single nucleotide polymorphisms was tested for association with cleft lip with or without palate in 77European American, 146 Taiwanese, 34 Singaporean, and 40 Korean case-parent trios using both the transmission disequilibrium test and conditional logistic regression models. Results: Evidence of linkage and association was observed among all four populations; and two specific haplotypes [GC composed of rs2235373-rs2235371 (p.V274I) and AAG of rs599021-rs2235373-rs595918] showed the most significant over-and undertransmission among Taiwanese cases (P ϭ 9 ϫ 10 Ϫ6 and P ϭ 5 ϫ 10 Ϫ6 , respectively). The AGC/CGC diplotype composed of rs599021-rs2235373-rs2013162 showed almost a 7-fold increase in risk among the Taiwanese sample (P Ͻ

Cancers require telomere maintenance mechanisms for unlimited replicative potential. They achieve this through TERT activation or alternative telomere lengthening associated with ATRX or DAXX loss. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, we dissect whole-genome sequencing data of over 2500 matched tumor-control samples from 36 different tumor types aggregated within the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium to characterize the genomic footprints of these mechanisms. While the telomere content of tumors with ATRX or DAXX mutations (ATRX/DAXX trunc) is increased, tumors with TERT modifications show a moderate decrease of telomere content. One quarter of all tumor samples contain somatic integrations of telomeric sequences into non-telomeric DNA. This fraction is increased to 80% prevalence in ATRX/DAXX trunc tumors, which carry an aberrant telomere variant repeat (TVR) distribution as another genomic marker. The latter feature includes enrichment or depletion of the previously undescribed singleton TVRs TTCGGG and TTTGGG, respectively. Our systematic analysis provides new insight into the recurrent genomic alterations associated with telomere maintenance mechanisms in cancer.

Many primary tumours have low levels of molecular oxygen (hypoxia), and hypoxic tumours respond poorly to therapy. Pan-cancer molecular hallmarks of tumour hypoxia remain poorly understood, with limited comprehension of its associations with specific mutational processes, non-coding driver genes and evolutionary features. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2658 cancers across 38 tumour types, we quantify hypoxia in 1188 tumours spanning 27 cancer types. Elevated hypoxia associates with increased mutational load across cancer types, irrespective of underlying mutational class. The proportion of mutations attributed to several mutational signatures of unknown aetiology directly associates with the level of hypoxia, suggesting underlying mutational processes for these signatures. At the gene level, driver mutations in TP53, MYC and PTEN are enriched in hypoxic tumours, and mutations in PTEN interact with hypoxia to direct tumour evolutionary trajectories. Overall, hypoxia plays a critical role in shaping the genomic and evolutionary landscapes of cancer.