Leveraging auxiliary data from arbitrary distributions to boost GWAS discovery with Flexible cFDR

Genome-wide association studies (GWAS) have identified thousands of genetic variants that are associated with complex traits. However, a stringent significance threshold is required to identify robust genetic associations. Leveraging relevant auxiliary covariates has the potential to boost statistical power to exceed the significance threshold. Particularly, abundant pleiotropy and the non-random distribution of SNPs across various functional categories suggests that leveraging GWAS test statistics from related traits and/or functional genomic data may boost GWAS discovery. While type 1 error rate control has become standard in GWAS, control of the false discovery rate can be a more powerful approach. The conditional false discovery rate (cFDR) extends the standard FDR framework by conditioning on auxiliary data to call significant associations, but current implementations are restricted to auxiliary data satisfying specific parametric distributions, typically GWAS p-values for related traits. We relax these distributional assumptions, enabling an extension of the cFDR framework that supports auxiliary covariates from arbitrary continuous distributions (“Flexible cFDR”). Our method can be applied iteratively, thereby supporting multi-dimensional covariate data. Through simulations we show that Flexible cFDR increases sensitivity whilst controlling FDR after one or several iterations. We further demonstrate its practical potential through application to an asthma GWAS, leveraging various functional genomic data to find additional genetic associations for asthma, which we validate in the larger, independent, UK Biobank data resource.     

Toward the precision breast cancer survival prediction utilizing combined whole genome-wide expression and somatic mutation analysis

Background

Breast cancer is the most common type of invasive cancer in woman. It accounts for approximately 18% of all cancer deaths worldwide. It is well known that somatic mutation plays an essential role in cancer development. Hence, we propose that a prognostic prediction model that integrates somatic mutations with gene expression can improve survival prediction for cancer patients and also be able to reveal the genetic mutations associated with survival.

Method

Differential expression analysis was used to identify breast cancer related genes. Genetic algorithm (GA) and univariate Cox regression analysis were applied to filter out survival related genes. DAVID was used for enrichment analysis on somatic mutated gene set. The performance of survival predictors were assessed by Cox regression model and concordance index(C-index).

Results

We investigated the genome-wide gene expression profile and somatic mutations of 1091 breast invasive carcinoma cases from The Cancer Genome Atlas (TCGA). We identified 118 genes with high hazard ratios as breast cancer survival risk gene candidates (log rank p?<? 0.0001 and c-index?=?0.636). Multiple breast cancer survival related genes were found in this gene set, including FOXR2, FOXD1, MTNR1B and SDC1. Further genetic algorithm (GA) revealed an optimal gene set consisted of 88 genes with higher c-index (log rank p?<? 0.0001 and c-index?=?0.656). We validated this gene set on an independent breast cancer data set and achieved a similar performance (log rank p?<? 0.0001 and c-index?=?0.614). Moreover, we revealed 25 functional annotations, 15 gene ontology terms and 14 pathways that were significantly enriched in the genes that showed distinct mutation patterns in the different survival risk groups. These functional gene sets were used as new features for the survival prediction model. In particular, our results suggested that the Fanconi anemia pathway had an important role in breast cancer prognosis.

Conclusions

Our study indicated that the expression levels of the gene signatures remain the effective indicators for breast cancer survival prediction. Combining the gene expression information with other types of features derived from somatic mutations can further improve the performance of survival prediction. The pathways that were associated with survival risk suggested by our study can be further investigated for improving cancer patient survival.

     

CCGD-ESCC: A Comprehensive Database for Genetic Variants Associated with Esophageal Squamous Cell Carcinoma in Chinese Population

Esophageal squamous-cell carcinoma (ESCC) is one of the most lethal malignancies in the world and occurs at particularly higher frequency in China. While several genome-wide association studies (GWAS) of germline variants and whole-genome or whole-exome sequencing studies of somatic mutations in ESCC have been published, there is no comprehensive database publically available for this cancer. Here, we developed the Chinese Cancer Genomic Database-Esophageal Squamous Cell Carcinoma (CCGD-ESCC) database, which contains the associations of 69,593 single nucleotide polymorphisms (SNPs) with ESCC risk in 2022 cases and 2039 controls, survival time of 1006 ESCC patients (survival GWAS) and gene expression (expression quantitative trait loci, eQTL) in 94 ESCC patients. Moreover, this database also provides the associations between 8833 somatic mutations and survival time in 675 ESCC patients. Our user-friendly database is a resource useful for biologists and oncologists not only in identifying the associations of genetic variants or somatic mutations with the development and progression of ESCC but also in studying the underlying mechanisms for tumorigenesis of the cancer. CCGD-ESCC is freely accessible at http://db.cbi.pku.edu.cn/ccgd/ESCCdb.     

Macrophage expression of tartrate-resistant acid phosphatase as a prognostic indicator in colon cancer

Recent research has indicated that separate populations of macrophages are associated with differing outcomes in cancer survival. In our study, we examine macrophage expression of tartrate-resistant acid phosphatase (TRAP) and its effect on survival in colon cancer. Immunohistochemical analysis on colorectal adenocarcinomas confirmed macrophage expression of TRAP. Co-localization of TRAP with CD68, a pan-macrophage marker, revealed that TRAP is present in some but not all sub-populations of macrophages. Further co-localization of TRAP with CD163, an M2 marker, revealed that TRAP is expressed by both M2 and non-M2 macrophages. TRAP expression was then measured using the AQUA method of quantitative immunofluorescence in a tissue microarray consisting of 233 colorectal cancer patients seen at Yale-New Haven Hospital. Survival analysis revealed that patients with high TRAP expression have a 22 % increase in 5-year survival (uncorrected log-rank p = 0.025) and a 47 % risk reduction in disease-specific death (p = 0.02). This finding was validated in a second cohort of older cases consisting of 505 colorectal cancer patients. Patients with high TRAP expression in the validation set had a 19 % increase in 5-year survival (log-rank p = 0.0041) and a 52 % risk reduction in death (p = 0.0019). These results provide evidence that macrophage expression of TRAP is associated with improved outcome and implicates TRAP as a potential biomarker in colon cancer.     

ERBB4 Promoter Polymorphism Is Associated with Poor Distant Disease-Free Survival in High-Risk Early Breast Cancer

A number of genetic variants have been linked to increased risk of breast cancer. Little is, however, known about the prognostic significance of hereditary factors. Here, we investigated the frequency and prognostic significance of two ERBB4 promoter region variants, −782G>T (rs62626348) and −815A>T (rs62626347), in a cohort of 1010 breast cancer patients. The frequency of nine previously described somatic ERBB4 kinase domain mutations was also analyzed. Clinical material used in the study consisted of samples from the phase III, adjuvant, FinHer breast cancer trial involving 1010 women. Tumor DNA samples were genotyped for ERBB4 variants and somatic mutations using matrix-assisted laser desorption ionization/time of flight mass spectrometry. Paraffin-embedded tumor sections from all patients were immunohistochemically stained for ErbB4 expression. Association of ERBB4 genotype to distant disease-free survival (DDFS) was assessed using Kaplan-Meier and Cox regression analyses. Genotyping was successful for 91–93% of the 1010 samples. Frequencies observed for the ERBB4 variants were 2.5% and 1.3% for −782G>T and −815A>T, respectively. Variant −815A>T was significantly associated with poor survival (HR  = 2.86 [95% CI 1.15–6.67], P = 0.017). In contrast, variant −782G>T was associated with well-differentiated cancer (P = 0.019). Two (0.2%) ERBB4 kinase domain mutations were found, both of which have previously been shown to be functional and promote cancer cell growth in vitro. These data present the germ-line ERBB4 variant −815A>T as a novel prognostic marker in high-risk early breast cancer and indicate the presence of rare but potentially oncogenic somatic ERBB4 mutations in breast cancer.     

A Pathway-Centric Survey of Somatic Mutations in Chinese Patients with Colorectal Carcinomas

Previous genetic studies on colorectal carcinomas (CRC) have identified multiple somatic mutations in four candidate pathways (TGF-β, Wnt, P53 and RTK-RAS pathways) on populations of European ancestry. However, it is under-studied whether other populations harbor different sets of hot-spot somatic mutations in these pathways and other oncogenes. In this study, to evaluate the mutational spectrum of novel somatic mutations, we assessed 41 pairs of tumor-stroma tissues from Chinese patients with CRC, including 29 colon carcinomas and 12 rectal carcinomas. We designed Illumina Custom Amplicon panel to target 43 genes, including genes in the four candidate pathways, as well as several known oncogenes for other cancers. Candidate mutations were validated by Sanger sequencing, and we further used SIFT and PolyPhen-2 to assess potentially functional mutations. We discovered 3 new somatic mutations in gene APC, TCF7L2, and PIK3CA that had never been reported in the COSMIC or NCI-60 databases. Additionally, we confirmed 6 known somatic mutations in gene SMAD4, APC, FBXW7, BRAF and PTEN in Chinese CRC patients. While most were previously reported in CRC, one mutation in PTEN was reported only in malignant endometrium cancer. Our study confirmed the existence of known somatic mutations in the four candidate pathways for CRC in Chinese patients. We also discovered a number of novel somatic mutations in these pathways, which may have implications for the pathogenesis of CRC.     

Integrative Analysis of Somatic Mutations Altering MicroRNA Targeting in Cancer Genomes

Determining the functional impact of somatic mutations is crucial to understanding tumorigenesis and metastasis. Recent sequences of several cancers have provided comprehensive lists of somatic mutations across entire genomes, enabling investigation of the functional impact of somatic mutations in non-coding regions. Here, we study somatic mutations in 3′UTRs of genes that have been identified in four cancers and computationally predict how they may alter miRNA targeting, potentially resulting in dysregulation of the expression of the genes harboring these mutations. We find that somatic mutations create or disrupt putative miRNA target sites in the 3′UTRs of many genes, including several genes, such as MITF, EPHA3, TAL1, SCG3, and GSDMA, which have been previously associated with cancer. We also integrate the somatic mutations with germline mutations and results of association studies. Specifically, we identify putative miRNA target sites in the 3′UTRs of BMPR1B, KLK3, and SPRY4 that are disrupted by both somatic and germline mutations and, also, are in linkage disequilibrium blocks with high scoring markers from cancer association studies. The somatic mutation in BMPR1B is located in a target site of miR-125b; germline mutations in this target site have previously been both shown to disrupt regulation of BMPR1B by miR-125b and linked with cancer.     

A Robust GWSS Method to Simultaneously Detect Rare and Common Variants for Complex Disease

The rapid advances in sequencing technologies and the resulting next-generation sequencing data provide the opportunity to detect disease-associated variants with a better solution, in particular for low-frequency variants. Although both common and rare variants might exert their independent effects on the risk for the trait of interest, previous methods to detect the association effects rarely consider them simultaneously. We proposed a class of test statistics, the generalized weighted-sum statistic (GWSS), to detect disease associations in the presence of common and rare variants with a case-control study design. Information of rare variants was aggregated using a weighted sum method, while signal directions and strength of the variants were considered at the same time. Permutations were performed to obtain the empirical p-values of the test statistics. Our simulation showed that, compared to the existing methods, the GWSS method had better performance in most of the scenarios. The GWSS (in particular VDWSS-t) method is particularly robust for opposite association directions, association strength, and varying distributions of minor-allele frequencies. It is therefore promising for detecting disease-associated loci. For empirical data application, we also applied our GWSS method to the Genetic Analysis Workshop 17 data, and the results were consistent with the simulation, suggesting good performance of our method. As re-sequencing studies become more popular to identify putative disease loci, we recommend the use of this newly developed GWSS to detect associations with both common and rare variants.     

Rare Variant Association Testing by Adaptive Combination of P-values

With the development of next-generation sequencing technology, there is a great demand for powerful statistical methods to detect rare variants (minor allele frequencies (MAFs)<1%) associated with diseases. Testing for each variant site individually is known to be underpowered, and therefore many methods have been proposed to test for the association of a group of variants with phenotypes, by pooling signals of the variants in a chromosomal region. However, this pooling strategy inevitably leads to the inclusion of a large proportion of neutral variants, which may compromise the power of association tests. To address this issue, we extend the -MidP method (Cheung et al., 2012, Genet Epidemiol 36: 675–685) and propose an approach (named ‘adaptive combination of P-values for rare variant association testing’, abbreviated as ‘ADA’) that adaptively combines per-site P-values with the weights based on MAFs. Before combining P-values, we first imposed a truncation threshold upon the per-site P-values, to guard against the noise caused by the inclusion of neutral variants. This ADA method is shown to outperform popular burden tests and non-burden tests under many scenarios. ADA is recommended for next-generation sequencing data analysis where many neutral variants may be included in a functional region.     

Polygenic in vivo validation of cancer mutations using transposons

The in vivo validation of cancer mutations and genes identified in cancer genomics is resource-intensive because of the low throughput of animal experiments. We describe a mouse model that allows multiple cancer mutations to be validated in each animal line. Animal lines are generated with multiple candidate cancer mutations using transposons. The candidate cancer genes are tagged and randomly expressed in somatic cells, allowing easy identification of the cancer genes involved in the generated tumours. This system presents a useful, generalised and efficient means for animal validation of cancer genes.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-014-0455-6) contains supplementary material, which is available to authorized users.     

Large-scale evaluation of candidate genes identifies associations between VEGF polymorphisms and bladder cancer risk

Common genetic variation could alter the risk for developing bladder cancer. We conducted a large-scale evaluation of single nucleotide polymorphisms (SNPs) in candidate genes for cancer to identify common variants that influence bladder cancer risk. An Illumina GoldenGate assay was used to genotype 1,433 SNPs within or near 386 genes in 1,086 cases and 1,033 controls in Spain. The most significant finding was in the 5′ UTR of VEGF (rs25648, p for likelihood ratio test, 2 degrees of freedom = 1 × 10⁻⁵). To further investigate the region, we analyzed 29 additional SNPs in VEGF, selected to saturate the promoter and 5′ UTR and to tag common genetic variation in this gene. Three additional SNPs in the promoter region (rs833052, rs1109324, and rs1547651) were associated with increased risk for bladder cancer: odds ratio (95% confidence interval): 2.52 (1.06–5.97), 2.74 (1.26–5.98), and 3.02 (1.36–6.63), respectively; and a polymorphism in intron 2 (rs3024994) was associated with reduced risk: 0.65 (0.46–0.91). Two of the promoter SNPs and the intron 2 SNP showed linkage disequilibrium with rs25648. Haplotype analyses revealed three blocks of linkage disequilibrium with significant associations for two blocks including the promoter and 5′ UTR (global p = 0.02 and 0.009, respectively). These findings are biologically plausible since VEGF is critical in angiogenesis, which is important for tumor growth, its elevated expression in bladder tumors correlates with tumor progression, and specific 5′ UTR haplotypes have been shown to influence promoter activity. Associations between bladder cancer risk and other genes in this report were not robust based on false discovery rate calculations. In conclusion, this large-scale evaluation of candidate cancer genes has identified common genetic variants in the regulatory regions of VEGF that could be associated with bladder cancer risk.     

Common Genetic Variants in Wnt Signaling Pathway Genes as Potential Prognostic Biomarkers for Colorectal Cancer

Compelling evidence has implicated the Wnt signaling pathway in the pathogenesis of colorectal cancer. We assessed the use of tag single nucleotide polymorphisms (tSNPs) in adenomatous polyposis coli (APC)/β-catenin (CTNNB1) genes to predict outcomes in patients with colorectal cancer. We selected and genotyped 10 tSNP to predict common variants across entire APC and CTNNB1 genes in 282 colorectal cancer patients. The associations of these tSNPs with distant metastasis-free survival and overall survival were evaluated by Kaplan-Meier analysis, Cox regression model, and survival tree analysis. The 5-year overall survival rate was 68.3%. Survival tree analysis identified a higher-order genetic interaction profile consisting of the APC rs565453, CTNNB1 2293303, and APC rs1816769 that was significantly associated with overall survival. The 5-year survival overall rates were 89.2%, 66.1%, and 58.8% for the low-, medium-, and high-risk genetic profiles, respectively (log-rank P = 0.001). After adjusting for possible confounders, including age, gender, carcinoembryonic antigen levels, tumor differentiation, stage, lymphovascular invasion, perineural invasion, and lymph node involvement, the genetic interaction profile remained significant. None of the studied SNPs were individually associated with distant metastasis-free survival and overall survival. Our results suggest that the genetic interaction profile among Wnt pathway SNPs might potentially increase the prognostic value in outcome prediction for colorectal cancer.     

A method to reduce ancestry related germline false positives in tumor only somatic variant calling

Background

Significant clinical and research applications are driving large scale adoption of individualized tumor sequencing in cancer in order to identify tumors-specific mutations. When a matched germline sample is available, somatic mutations may be identified using comparative callers. However, matched germline samples are frequently not available such as with archival tissues, which makes it difficult to distinguish somatic from germline variants. While population databases may be used to filter out known germline variants, recent studies have shown private germline variants result in an inflated false positive rate in unmatched tumor samples, and the number germline false positives in an individual may be related to ancestry.

Methods

First, we examined the relationship between the germline false positives and ancestry. Then we developed and implemented a tumor only caller (LumosVar) that leverages differences in allelic frequency between somatic and germline variants in impure tumors. We used simulated data to systematically examine how copy number alterations, tumor purity, and sequencing depth should affect the sensitivity of our caller. Finally, we evaluated the caller on real data.

Results

We find the germline false-positive rate is significantly higher for individuals of non-European Ancestry largely due to the limited diversity in public polymorphism databases and due to population-specific characteristics such as admixture or recent expansions. Our Bayesian tumor only caller (LumosVar) is able to greatly reduce false positives from private germline variants, and our sensitivity is similar to predictions based on simulated data.

Conclusions

Taken together, our results suggest that studies of individuals of non-European ancestry would most benefit from our approach. However, high sensitivity requires sufficiently impure tumors and adequate sequencing depth. Even in impure tumors, there are copy number alterations that result in germline and somatic variants having similar allele frequencies, limiting the sensitivity of the approach. We believe our approach could greatly improve the analysis of archival samples in a research setting where the normal is not available.

     

Integrated RNA and DNA sequencing improves mutation detection in low purity tumors

Identifying somatic mutations is critical for cancer genome characterization and for prioritizing patient treatment. DNA whole exome sequencing (DNA-WES) is currently the most popular technology; however, this yields low sensitivity in low purity tumors. RNA sequencing (RNA-seq) covers the expressed exome with depth proportional to expression. We hypothesized that integrating DNA-WES and RNA-seq would enable superior mutation detection versus DNA-WES alone. We developed a first-of-its-kind method, called UNCeqR, that detects somatic mutations by integrating patient-matched RNA-seq and DNA-WES. In simulation, the integrated DNA and RNA model outperformed the DNA-WES only model. Validation by patient-matched whole genome sequencing demonstrated superior performance of the integrated model over DNA-WES only models, including a published method and published mutation profiles. Genome-wide mutational analysis of breast and lung cancer cohorts (n = 871) revealed remarkable tumor genomics properties. Low purity tumors experienced the largest gains in mutation detection by integrating RNA-seq and DNA-WES. RNA provided greater mutation signal than DNA in expressed mutations. Compared to earlier studies on this cohort, UNCeqR increased mutation rates of driver and therapeutically targeted genes (e.g. PIK3CA, ERBB2 and FGFR2). In summary, integrating RNA-seq with DNA-WES increases mutation detection performance, especially for low purity tumors.     

Clinical Significance in Oral Cavity Squamous Cell Carcinoma of Pathogenic Somatic Mitochondrial Mutations

Somatic mutations affecting the mitochondrial DNA (mtDNA) have been frequently observed in human cancers and proposed as important oncological biomarkers. However, the clinical significance of mtDNA mutations in cancer remains unclear. This study was therefore performed to explore the possible clinical use in assessing oral squamous cell carcinoma (OSCC) of pathogenic mtDNA mutations. The entire mitochondrial genome of 300 OSCC with their matched control DNAs was screened by direct sequencing and criteria were set to define a pathogenic somatic mutation. The patients'' TP53 R72P genotypes were determined by polymerase chain reaction-restriction fragment length polymorphism. The relationships between pathogenic somatic mutations, clinicopathogical features, TP53 R72P genotype and clinical prognosis were analyzed. Overall, 645 somatic mtDNA mutations were identified and 91 of these mutations were defined as pathogenic. About one quarter (74/300) of the OSCC tumor samples contained pathogenic mutations. Individuals with the TP53 R allele had a higher frequency of pathogenic somatic mutation than those with the PP genotype. Kaplan-Meier analysis indicated that TP53 R allele patients with pathogenic somatic mutations demonstrated a significant association with a poorer disease-free survival than other individuals (HR = 1.71; 95% CI, 1.15–2.57; p = 0.009) and this phenomenon still existed after adjusting for mtDNA haplogroup, tumor stage with treatment regimens, differentiation and age at diagnosis (HR = 1.59; 95% CI, 1.06–2.40; p = 0.03). Subgroup analyses showed that this phenomenon was limited to patients who received adjuvant radiotherapy/chemo-radiotherapy after surgery. The results strongly indicated that pathogenic mtDNA mutations are a potential prognostic marker for OSCCs. Furthermore, functional mitochondria may play an active role in cancer development and the patient''s response to radiotherapy/chemo-radiotherapy.     

Digging for gold nuggets: uncovering novel candidate genes for variation in gastrointestinal nematode burden in a wild bird species

The extent to which genotypic variation at a priori identified candidate genes can explain variation in complex phenotypes is a major debate in evolutionary biology. Whereas some high‐profile genes such as the MHC or MC1R clearly do account for variation in ecologically relevant characters, many complex phenotypes such as response to parasite infection may well be underpinned by a large number of genes, each of small and effectively undetectable effect. Here, we characterize a suite of novel candidate genes for variation in gastrointestinal nematode (Trichostrongylus tenuis) burden among red grouse (Lagopus lagopus scotica) individuals across a network of moors in north‐east Scotland. We test for associations between parasite load and genotypic variation in twelve genes previously identified to be differentially expressed in experimentally infected red grouse or genetically differentiated among red grouse populations with overall different parasite loads. These genes are associated with a broad physiological response including immune system processes. Based on individual‐level generalized linear models, genotypic variants in nine genes were significantly associated with parasite load, with effect sizes accounting for differences of 514–666 worms per bird. All but one of these variants were synonymous or untranslated, suggesting that these may be linked to protein‐coding variants or affect regulatory processes. In contrast, population‐level analyses revealed few and inconsistent associations with parasite load, and little evidence of signatures of natural selection. We discuss the broader significance of these contrasting results in the context of the utility of population genomics and landscape genomics approaches in detecting adaptive genomic signatures.     

No association between genetic variants in angiogenesis and inflammation pathway genes and breast cancer survival among Chinese women

Background: Angiogenesis and inflammation are implicated in breast cancer prognosis; however, the role of individual germline variation in related genes is unknown. Methods: A two-stage candidate pathway association study was conducted among 6983 Chinese women. Stage 1 included 2884 women followed for a median of 5.7 years; Stage 2 included 4099 women followed for a median of 4.0 years. Cox proportional hazards regression was used to estimate the effects of genetic variants on disease-free survival (DFS) and overall survival (OS). Results: Stage 1 included genotyping of 506 variants in 22 genes; analysis was conducted for 370 common variants. Nominally significant associations with DFS and/or OS were found for 20 loci in ten genes in Stage 1; variants in 19 loci were successfully genotyped and evaluated in Stage 2. In analyses of both study stages combined, nominally significant associations were found for nine variants in seven genes; none of these associations surpassed a significance threshold level corrected for the total number of variants evaluated in this study. Conclusions: No association with survival was found for 370 common variants in 22 angiogenesis and inflammation pathway genes among Chinese women with breast cancer. Impact: Our data do not support a large role for common genetic variation in 22 genes in breast cancer prognosis; research on angiogenesis and inflammation genes should focus on common variation in other genes, rare host variants, or tumor alterations.     

Genomic profile analysis of diffuse-type gastric cancers

Background

Stomach cancer is the third deadliest among all cancers worldwide. Although incidence of the intestinal-type gastric cancer has decreased, the incidence of diffuse-type is still increasing and its progression is notoriously aggressive. There is insufficient information on genome variations of diffuse-type gastric cancer because its cells are usually mixed with normal cells, and this low cellularity has made it difficult to analyze the genome.

Results

We analyze whole genomes and corresponding exomes of diffuse-type gastric cancer, using matched tumor and normal samples from 14 diffuse-type and five intestinal-type gastric cancer patients. Somatic variations found in the diffuse-type gastric cancer are compared to those of the intestinal-type and to previously reported variants. We determine the average exonic somatic mutation rate of the two types. We find associated candidate driver genes, and identify seven novel somatic mutations in CDH1, which is a well-known gastric cancer-associated gene. Three-dimensional structure analysis of the mutated E-cadherin protein suggests that these new somatic mutations could cause significant functional perturbations of critical calcium-binding sites in the EC1-2 junction. Chromosomal instability analysis shows that the MDM2 gene is amplified. After thorough structural analysis, a novel fusion gene TSC2-RNF216 is identified, which may simultaneously disrupt tumor-suppressive pathways and activate tumorigenesis.

Conclusions

We report the genomic profile of diffuse-type gastric cancers including new somatic variations, a novel fusion gene, and amplification and deletion of certain chromosomal regions that contain oncogenes and tumor suppressors.     

Chromothripsis is a common mechanism driving genomic rearrangements in primary and metastatic colorectal cancer

Background

Structural rearrangements form a major class of somatic variation in cancer genomes. Local chromosome shattering, termed chromothripsis, is a mechanism proposed to be the cause of clustered chromosomal rearrangements and was recently described to occur in a small percentage of tumors. The significance of these clusters for tumor development or metastatic spread is largely unclear.

Results

We used genome-wide long mate-pair sequencing and SNP array profiling to reveal that chromothripsis is a widespread phenomenon in primary colorectal cancer and metastases. We find large and small chromothripsis events in nearly every colorectal tumor sample and show that several breakpoints of chromothripsis clusters and isolated rearrangements affect cancer genes, including NOTCH2, EXO1 and MLL3. We complemented the structural variation studies by sequencing the coding regions of a cancer exome in all colorectal tumor samples and found somatic mutations in 24 genes, including APC, KRAS, SMAD4 and PIK3CA. A pairwise comparison of somatic variations in primary and metastatic samples indicated that many chromothripsis clusters, isolated rearrangements and point mutations are exclusively present in either the primary tumor or the metastasis and may affect cancer genes in a lesion-specific manner.

Conclusions

We conclude that chromothripsis is a prevalent mechanism driving structural rearrangements in colorectal cancer and show that a complex interplay between point mutations, simple copy number changes and chromothripsis events drive colorectal tumor development and metastasis.