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

Although CDKN2A is the most frequent high-risk melanoma susceptibility gene, the underlying genetic factors for most melanoma-prone families remain unknown. Using whole exome sequencing, we identified a rare variant that arose as a founder mutation in the telomere shelterin POT1 gene (g.7:124493086 C>T, Ser270Asn) in five unrelated melanoma-prone families from Romagna, Italy. Carriers of this variant had increased telomere length and elevated fragile telomeres suggesting that this variant perturbs telomere maintenance. Two additional rare POT1 variants were identified in all cases sequenced in two other Italian families, yielding a frequency of POT1 variants comparable to that of CDKN2A mutations in this population. These variants were not found in public databases or in 2,038 genotyped Italian controls. We also identified two rare recurrent POT1 variants in American and French familial melanoma cases. Our findings suggest that POT1 is a major susceptibility gene for familial melanoma in several populations.

We investigated whether the gut microbiota differed in 48 postmenopausal breast cancer case patients, pretreatment, vs 48 control patients. Microbiota profiles in fecal DNA were determined by Illumina sequencing and taxonomy of 16S rRNA genes. Estrogens were quantified in urine. Case-control comparisons employed linear and unconditional logistic regression of microbiota α-diversity (PD_whole tree) and UniFrac analysis of β-diversity, with two-sided statistical tests. Total estrogens correlated with α-diversity in control patients (Spearman Rho = 0.37, P = .009) but not case patients (Spearman Rho = 0.04, P = .77). Compared with control patients, case patients had statistically significantly altered microbiota composition (β-diversity, P = .006) and lower α-diversity (P = .004). Adjusted for estrogens and other covariates, odds ratio of cancer was 0.50 (95% confidence interval = 0.30 to 0.85) per α-diversity tertile. Differences in specific taxa were not statistically significant when adjusted for multiple comparisons. This pilot study shows that postmenopausal women with breast cancer have altered composition and estrogen-independent low diversity of their gut microbiota. Whether these affect breast cancer risk and prognosis is unknown.

Accumulating evidence indicates that the gut microbiota affects colorectal cancer development, but previous studies have varied in population, technical methods, and associations with cancer. Understanding these variations is needed for comparisons and for potential pooling across studies. Therefore, we performed whole-genome shotgun sequencing on fecal samples from 52 pre-treatment colorectal cancer cases and 52 matched controls from Washington, DC. We compared findings from a previously published 16S rRNA study to the metagenomics-derived taxonomy within the same population. In addition, metagenome-predicted genes, modules, and pathways in the Washington, DC cases and controls were compared to cases and controls recruited in France whose specimens were processed using the same platform. Associations between the presence of fecal Fusobacteria, Fusobacterium, and Porphyromonas with colorectal cancer detected by 16S rRNA were reproduced by metagenomics, whereas higher relative abundance of Clostridia in cancer cases based on 16S rRNA was merely borderline based on metagenomics. This demonstrated that within the same sample set, most, but not all taxonomic associations were seen with both methods. Considering significant cancer associations with the relative abundance of genes, modules, and pathways in a recently published French metagenomics dataset, statistically significant associations in the Washington, DC population were detected for four out of 10 genes, three out of nine modules, and seven out of 17 pathways. In total, colorectal cancer status in the Washington, DC study was associated with 39% of the metagenome-predicted genes, modules, and pathways identified in the French study. More within and between population comparisons are needed to identify sources of variation and disease associations that can be reproduced despite these variations. Future studies should have larger sample sizes or pool data across studies to have sufficient power to detect associations that are reproducible and significant after correction for multiple testing.

Lung cancer is the leading cause of cancer-related death, with non-small cell lung cancer (NSCLC) being the predominant form of the disease. Most lung cancer is caused by the accumulation of genomic alterations due to tobacco exposure. To uncover its mutational landscape, we performed whole-exome sequencing in 31 NSCLCs and their matched normal tissue samples. We identified both common and unique mutation spectra and pathway activation in lung adenocarcinomas and squamous cell carcinomas, two major histologies in NSCLC. In addition to identifying previously known lung cancer genes (TP53, KRAS, EGFR, CDKN2A and RB1), the analysis revealed many genes not previously implicated in this malignancy. Notably, a novel gene CSMD3 was identified as the second most frequently mutated gene (next to TP53) in lung cancer. We further demonstrated that loss of CSMD3 results in increased proliferation of airway epithelial cells. The study provides unprecedented insights into mutational processes, cellular pathways and gene networks associated with lung cancer. Of potential immediate clinical relevance, several highly mutated genes identified in our study are promising druggable targets in cancer therapy including ALK, CTNNA3, DCC, MLL3, PCDHIIX, PIK3C2B, PIK3CG and ROCK2.

BackgroundLung adenocarcinoma (LUAD) is the most common histologic subtype of lung cancer and has a high risk of distant metastasis at every disease stage. We aimed to characterize the genomic landscape of LUAD and identify mutation signatures associated with tumor progression.Methods and FindingsWe performed an integrative genomic analysis, incorporating whole exome sequencing (WES), determination of DNA copy number and DNA methylation, and transcriptome sequencing for 101 LUAD samples from the Environment And Genetics in Lung cancer Etiology (EAGLE) study. We detected driver genes by testing whether the nonsynonymous mutation rate was significantly higher than the background mutation rate and replicated our findings in public datasets with 724 samples. We performed subclonality analysis for mutations based on mutant allele data and copy number alteration data. We also tested the association between mutation signatures and clinical outcomes, including distant metastasis, survival, and tumor grade. We identified and replicated two novel candidate driver genes, POU class 4 homeobox 2 (POU4F2) (mutated in 9 [8.9%] samples) and ZKSCAN1 (mutated in 6 [5.9%] samples), and characterized their major deleterious mutations. ZKSCAN1 was part of a mutually exclusive gene set that included the RTK/RAS/RAF pathway genes BRAF, EGFR, KRAS, MET, and NF1, indicating an important driver role for this gene. Moreover, we observed strong associations between methylation in specific genomic regions and somatic mutation patterns. In the tumor evolution analysis, four driver genes had a significantly lower fraction of subclonal mutations (FSM), including TP53 (p = 0.007), KEAP1 (p = 0.012), STK11 (p = 0.0076), and EGFR (p = 0.0078), suggesting a tumor initiation role for these genes. Subclonal mutations were significantly enriched in APOBEC-related signatures (p < 2.5×10−50). The total number of somatic mutations (p = 0.0039) and the fraction of transitions (p = 5.5×10−4) were associated with increased risk of distant metastasis. Our study’s limitations include a small number of LUAD patients for subgroup analyses and a single-sample design for investigation of subclonality.ConclusionsThese data provide a genomic characterization of LUAD pathogenesis and progression. The distinct clonal and subclonal mutation signatures suggest possible diverse carcinogenesis pathways for endogenous and exogenous exposures, and may serve as a foundation for more effective treatments for this lethal disease. LUAD’s high heterogeneity emphasizes the need to further study this tumor type and to associate genomic findings with clinical outcomes.

About 30% stage I non-small cell lung cancer (NSCLC) patients undergoing resection will recur. Robust prognostic markers are required to better manage therapy options. MicroRNAs (miRNAs) are a class of small non-coding RNAs of 19-25 nt and play important roles in gene regulation in human cancers. The purpose of this study is to identify miRNA expression profiles that would better predict prognosis of stage I NSCLC. MiRNAs extracted from 527 stage I NSCLC patients were profiled on the human miRNA expression profiling v2 panel (Illumina). The expression profiles were analyzed for their association with cancer subtypes, lung cancer brain metastasis and recurrence/relapse free survival (RFS). MiRNA expression patterns between lung adenocarcinoma and squamous cell carcinoma differed significantly with 171 miRNAs, including Let-7 family members and miR-205. Ten miRNAs associated with brain metastasis were identified including miR-145*, which inhibit cell invasion and metastasis. Two miRNA signatures that are highly predictive of RFS were identified. The first contained 34 miRNAs derived from 357 stage I NSCLC patients independent of cancer subtype, whereas the second containing 27 miRNAs was adenocarcinoma specific. Both signatures were validated using formalin-fixed paraffin embedded and/or fresh frozen tissues in independent data set with 170 stage I patients. Our findings have important prognostic or therapeutic implications for the management of stage I lung cancer patients. The identified miRNAs hold great potential as targets for histology-specific treatment or prevention and treatment of recurrent disease.

BackgroundAlteration of the gut microbial population (dysbiosis) may increase the risk for allergies and other conditions. This study sought to clarify the relationship of dysbiosis with allergies in adults.MethodsPublicly available American Gut Project questionnaire and fecal 16S rRNA sequence data were analyzed. Fecal microbiota richness (number of observed species) and composition (UniFrac) were used to compare adults with versus without allergy to foods (peanuts, tree nuts, shellfish, other) and non-foods (drug, bee sting, dander, asthma, seasonal, eczema). Logistic and Poisson regression models adjusted for potential confounders. Odds ratios and 95% confidence intervals (CI) were calculated for lowest vs highest richness tertile. Taxonomy associations considered 122 non-redundant taxa (of 2379 total taxa) with ≥ 0.1% mean abundance.ResultsSelf-reported allergy prevalence among the 1879 participants (mean age, 45.5 years; 46.9% male) was 81.5%, ranging from 2.5% for peanuts to 40.5% for seasonal. Fecal microbiota richness was markedly lower with total allergies (P = 10− 9) and five particular allergies (P ≤ 10− 4). Richness odds ratios were 1.7 (CI 1.3–2.2) with seasonal, 1.8 (CI 1.3–2.5) with drug, and 7.8 (CI 2.3–26.5) with peanut allergy. These allergic participants also had markedly altered microbial community composition (unweighted UniFrac, P = 10− 4 to 10− 7). Total food and non-food allergies were significantly associated with 7 and 9 altered taxa, respectively. The dysbiosis was most marked with nut and seasonal allergies, driven by higher Bacteroidales and reduced Clostridiales taxa.InterpretationAmerican adults with allergies, especially to nuts and seasonal pollen, have low diversity, reduced Clostridiales, and increased Bacteroidales in their gut microbiota. This dysbiosis might be targeted to improve treatment or prevention of allergy.