An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

Driver Fusions and Their Implications in the Development and Treatment of Human Cancers.

Gene fusions represent an important class of somatic alterations in cancer. We systematically investigated fusions in 9,624 tumors across 33 cancer types using multiple fusion calling tools. We identified a total of 25,664 fusions, with a 63% validation rate. Integration of gene expression, copy number, and fusion annotation data revealed that fusions involving oncogenes tend to exhibit increased expression, whereas fusions involving tumor suppressors have the opposite effect. For fusions involving kinases, we found 1,275 with an intact kinase domain, the proportion of which varied significantly across cancer types. Our study suggests that fusions drive the development of 16.5% of cancer cases and function as the sole driver in more than 1% of them. Finally, we identified druggable fusions involving genes such as TMPRSS2, RET, FGFR3, ALK, and ESR1 in 6.0% of cases, and we predicted immunogenic peptides, suggesting that fusions may provide leads for targeted drug and immune therapy

Impact of clinical phenotypes on management and outcomes in European atrial fibrillation patients: a report from the ESC-EHRA EURObservational Research Programme in AF (EORP-AF) General Long-Term Registry

Background: Epidemiological studies in atrial fibrillation (AF) illustrate that clinical complexity increase the risk of major adverse outcomes. We aimed to describe European AF patients\u2019 clinical phenotypes and analyse the differential clinical course. Methods: We performed a hierarchical cluster analysis based on Ward\u2019s Method and Squared Euclidean Distance using 22 clinical binary variables, identifying the optimal number of clusters. We investigated differences in clinical management, use of healthcare resources and outcomes in a cohort of European AF patients from a Europe-wide observational registry. Results: A total of 9363 were available for this analysis. We identified three clusters: Cluster 1 (n = 3634; 38.8%) characterized by older patients and prevalent non-cardiac comorbidities; Cluster 2 (n = 2774; 29.6%) characterized by younger patients with low prevalence of comorbidities; Cluster 3 (n = 2955;31.6%) characterized by patients\u2019 prevalent cardiovascular risk factors/comorbidities. Over a mean follow-up of 22.5 months, Cluster 3 had the highest rate of cardiovascular events, all-cause death, and the composite outcome (combining the previous two) compared to Cluster 1 and Cluster 2 (all P <.001). An adjusted Cox regression showed that compared to Cluster 2, Cluster 3 (hazard ratio (HR) 2.87, 95% confidence interval (CI) 2.27\u20133.62; HR 3.42, 95%CI 2.72\u20134.31; HR 2.79, 95%CI 2.32\u20133.35), and Cluster 1 (HR 1.88, 95%CI 1.48\u20132.38; HR 2.50, 95%CI 1.98\u20133.15; HR 2.09, 95%CI 1.74\u20132.51) reported a higher risk for the three outcomes respectively. Conclusions: In European AF patients, three main clusters were identified, differentiated by differential presence of comorbidities. Both non-cardiac and cardiac comorbidities clusters were found to be associated with an increased risk of major adverse outcomes

Systematics of the Neotropical Genus Leptodactylus Fitzinger, 1826 (Anura: Leptodactylidae): Phylogeny, the Relevance of Non-molecular Evidence, and Species Accounts

A phylogeny of the species-rich clade of the Neotropical frog genus Leptodactylus sensu stricto is presented on the basis of a total evidence analysis of molecular (mitochondrial and nuclear markers) and non-molecular (adult and larval morphological and behavioral characters) sampled from > 80% of the 75 currently recognized species. Our results support the monophyly of Leptodactylus sensu stricto, with Hydrolaetare placed as its sister group. The reciprocal monophyly of Hydrolaetare and Leptodactylus sensu stricto does not require that we consider Hydrolaetare as either a subgenus or synonym of Leptodactylus sensu lato. We recognize Leptodactylus sensu stricto, Hydrolaetare, Adenomera, and Lithodytes as valid monophyletic genera. Our results generally support the traditionally recognized Leptodactylus species groups, with exceptions involving only a few species that are easily accommodated without proposing new groups or significantly altering contents. The four groups form a pectinate tree, with the Leptodactylus fuscus group diverging first, followed by the L. pentadactylus group, which is sister to the L. latrans and L. melanonotus groups. To evaluate the impact of non-molecular evidence on our results, we compared our total evidence results with results obtained from analyses using only molecular data. Although non-molecular evidence comprised only 3.5% of the total evidence matrix, it had a strong impact on our total evidence results. Only one species group was monophyletic in the molecular-only analysis, and support differed in 86% of the 54 Leptodactylus clades that are shared by the results of the two analyses. Even though no non-molecular evidence was included for Hydrolaetare, exclusion of that data partition resulted in that genus being nested within Leptodactylus, demonstrating that the inclusion of a small amount of non-molecular evidence for a subset of species can alter not only the placement of those species, but also species that were not scored for those data. The evolution of several natural history and reproductive traits is considered in the light of our phylogenic framework. Invasion of rocky outcrops, larval oophagy, and use of underground reproductive chambers are restricted to species of the Leptodactylus fuscus and L. pentadactylus groups. In contrast, larval schooling, larval attendance, and more complex parental care are restricted to the L. latrans and L. melanonotus groups. Construction of foam nests is plesiomorphic in Leptodactylus but their placement varies extensively (e.g., underground chambers, surface of waterbodies, natural or excavated basins). Information on species synonymy, etymology, adult and larval morphology, advertisement call, and geographic distribution is summarized in species accounts for the 30 species of the Leptodactylus fuscus group, 17 species of the L. pentadactylus group, eight species of the L. latrans group, and 17 species of the L. melanonotus group, as well as the three species that are currently unassigned to any species group.Se presenta una filogenia del género Leptodactylus, un ciado neotropical rico en especies, basada en análises combinados de datos moleculares (marcadores nuclear y mitocondriales) y no moleculares (caracteres de la morfología de adultos y larvas así como de comportamiento) se muestrearon > 80% de las 75 especies reconocidas. Los resultados apoyan la monofília de Leptodactylus sensu stricto, con Hydrolaetare como su grupo hermano. La monofília recíproca de Hydrolaetare y Leptodactylus no requiere considerar a Hydrolaetare como un subgénero o sinónimo de Leptodactylus sensu lato. Se reconocen Leptodactylus sensu stricto, Hydrolaetare, Adenomera y Lithodytes como géneros monofiléticos válidos. Los resultados en general resuelven los grupos tradicionalmente reconocidos de Leptodactylus, con excepciones de algunas especies que son reasignadas sin la necesidad de proponer nuevos grupos o alterar significativamente el contenido de los grupos tradicionales. Los cuatro grupos de especies forman una topología pectinada donde el grupo de L. fuscus tiene una posición basal, seguido por el grupo de L. pentadactylus que es el grupo hermano al clado formado por los grupo de L. latrans y L. melanonotus. Se estimó el impacto de los datos no moleculares en los resultados, comparándose los resultados de evidencia total con los de los análises de datos moleculares solamente. Los datos no moleculares representan un 3.5% de la matriz de evidencia total, pero estos datos tuvieron un impacto significativo en los resultados del análisis de evidencia total. En el análisis estrictamente molecular solamente un grupo de especies resultó monofilético, y el apoyo difirió en 86% de los 54 ciados de Leptodactylus compartidos entre los dos análises. A pesar que datos no moleculares no fueron incluidos para Hydrolaetare, la exclusión de evidencia no molecular resultó en el género estar dentro de Leptodactylus, demostrando que la inclusión de evidencia no molecular pequeña para un subgrupo de especies altera no solamente la posición topológica de esas especies, sino tambien de las especies para las cuales dichos datos no fueron codificados. La evolución de patrones de historia natural y reprodución se evalúan en el contexto filogenético. La invasión de afloramientos rocosos y la construción de cámaras de reprodución subterraneas está limitada a los grupos de Leptodactylus fuscus y L. pentadactylus, mientras que la oofagia larval está restringida al grupo de L. pentadactylus. Por otro lado, los cárdumenes larvales, la proteción del cárdumen, y otros comportamientos parentales complejos carecterizan al clado formado por los grupos de especies de L. latrans y L. melanonotus. Los resúmenes de especies incluyen información de sinonimias, etimología, morfología de adultos y larvas, cantos, y distribución geográfica para las 30 especies del grupo de Leptodactylus fuscus, 17 especies del grupo L. pentadactylus, ocho especies del grupo de L. latrans, 17 especies del grupo de L. melanonotus, así como para las tres especies que actualmente no se encuentran asociadas a ninguno de los grupos de especies.Taran Grant was supported by Conselho Nacional de Desenvolvimento Científico e Tecnológico Proc. 307001/2011-3 and Fundação de Amparo à Pesquisa do Estado de São Paulo Proc. 2012/10000-5

The Cancer Genome Atlas Comprehensive Molecular Characterization of Renal Cell Carcinoma

Renal cell carcinoma(RCC) is not a single disease, but several histologically defined cancers with different genetic drivers, clinical courses, and therapeutic responses. The current study evaluated 843 RCC from the three major histologic subtypes, including 488 clear cell RCC, 274 papillary RCC, and 81 chromophobe RCC. Comprehensive genomic and phenotypic analysis of the RCC subtypes reveals distinctive features of each subtype that provide the foundation for the development of subtype-specific therapeutic and management strategies for patients affected with these cancers. Somatic alteration of BAP1, PBRM1, and PTEN and altered metabolic pathways correlated with subtype-specific decreased survival, while CDKN2A alteration, increased DNA hypermethylation, and increases in the immune-related Th2 gene expression signature correlated with decreased survival within all major histologic subtypes. CIMP-RCC demonstrated an increased immune signature, and a uniform and distinct metabolic expression pattern identified a subset of metabolically divergent (MD) ChRCC that associated with extremely poor survival

Somatic Mutational Landscape of Splicing Factor Genes and Their Functional Consequences across 33 Cancer Types

Hotspot mutations in splicing factor genes have been recently reported at high frequency in hematological malignancies, suggesting the importance of RNA splicing in cancer. We analyzed whole-exome sequencing data across 33 tumor types in The Cancer Genome Atlas (TCGA), and we identified 119 splicing factor genes with significant non-silent mutation patterns, including mutation over-representation, recurrent loss of function (tumor suppressor-like), or hotspot mutation profile (oncogene-like). Furthermore, RNA sequencing analysis revealed altered splicing events associated with selected splicing factor mutations. In addition, we were able to identify common gene pathway profiles associated with the presence of these mutations. Our analysis suggests that somatic alteration of genes involved in the RNA-splicing process is common in cancer and may represent an underappreciated hallmark of tumorigenesis

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although the MYC oncogene has been implicated in cancer, a systematic assessment of alterations of MYC, related transcription factors, and co-regulatory proteins, forming the proximal MYC network (PMN), across human cancers is lacking. Using computational approaches, we define genomic and proteomic features associated with MYC and the PMN across the 33 cancers of The Cancer Genome Atlas. Pan-cancer, 28% of all samples had at least one of the MYC paralogs amplified. In contrast, the MYC antagonists MGA and MNT were the most frequently mutated or deleted members, proposing a role as tumor suppressors. MYC alterations were mutually exclusive with PIK3CA, PTEN, APC, or BRAF alterations, suggesting that MYC is a distinct oncogenic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such as immune response and growth factor signaling; chromatin, translation, and DNA replication/repair were conserved pan-cancer. This analysis reveals insights into MYC biology and is a reference for biomarkers and therapeutics for cancers with alterations of MYC or the PMN. We present a computational study determining the frequency and extent of alterations of the MYC network across the 33 human cancers of TCGA. These data, together with MYC, positively correlated pathways as well as mutually exclusive cancer genes, will be a resource for understanding MYC-driven cancers and designing of therapeutics

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dysregulated in tumors, but only a handful are known to play pathophysiological roles in cancer. We inferred lncRNAs that dysregulate cancer pathways, oncogenes, and tumor suppressors (cancer genes) by modeling their effects on the activity of transcription factors, RNA-binding proteins, and microRNAs in 5,185 TCGA tumors and 1,019 ENCODE assays. Our predictions included hundreds of candidate onco- and tumor-suppressor lncRNAs (cancer lncRNAs) whose somatic alterations account for the dysregulation of dozens of cancer genes and pathways in each of 14 tumor contexts. To demonstrate proof of concept, we showed that perturbations targeting OIP5-AS1 (an inferred tumor suppressor) and TUG1 and WT1-AS (inferred onco-lncRNAs) dysregulated cancer genes and altered proliferation of breast and gynecologic cancer cells. Our analysis indicates that, although most lncRNAs are dysregulated in a tumor-specific manner, some, including OIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergistically dysregulate cancer pathways in multiple tumor contexts. Chiu et al. present a pan-cancer analysis of lncRNA regulatory interactions. They suggest that the dysregulation of hundreds of lncRNAs target and alter the expression of cancer genes and pathways in each tumor context. This implies that hundreds of lncRNAs can alter tumor phenotypes in each tumor context

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

Perspective on Oncogenic Processes at the End of the Beginning of Cancer Genomics

The Cancer Genome Atlas (TCGA) has catalyzed systematic characterization of diverse genomic alterations underlying human cancers. At this historic junction marking the completion of genomic characterization of over 11,000 tumors from 33 cancer types, we present our current understanding of the molecular processes governing oncogenesis. We illustrate our insights into cancer through synthesis of the findings of the TCGA PanCancer Atlas project on three facets of oncogenesis: (1) somatic driver mutations, germline pathogenic variants, and their interactions in the tumor; (2) the influence of the tumor genome and epigenome on transcriptome and proteome; and (3) the relationship between tumor and the microenvironment, including implications for drugs targeting driver events and immunotherapies. These results will anchor future characterization of rare and common tumor types, primary and relapsed tumors, and cancers across ancestry groups and will guide the deployment of clinical genomic sequencing