Amine Containing Analogs of Sulindac for Cancer Prevention

Background: Sulindac belongs to the chemically diverse family of Non-Steroidal Anti-Inflammatory Drugs (NSAIDs) that effectively prevent adenomatous colorectal polyps and colon cancer, especially in patients with familial adenomatous polyposis. Sulindac sulfide amide (SSA), an amide analog of sulindac sulfide, shows insignificant COX-related activity and toxicity while enhancing anticancer activity in vitro and demonstrating in vivo xenograft activity. Objective: Develop structure-activity relationships in the sulindac amine series and identify analogs with promising anticancer activities. Method: A series of sulindac amine analogs were designed and synthesized and then further modified in a “libraries from libraries” approach to produce amide, sulfonamide and N,N-disubstituted sulindac amine sub-libraries. All analogs were screened against three cancer cell lines (prostate, colon and breast). Results: Several active compounds were identified viain vitro cancer cell line screening with the most potent compound (26) in the nanomolar range. Conclusion: Compound 26 and analogs showing the most potent inhibitory activity may be considered for further design and optimization efforts as anticancer hit scaffolds

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

Fauna of euglossina (Hymenoptera: Apidae) from southwestern Amazonia, Acre, Brazil

Male orchid bees were collected between December 2005 and September 2006 in 11 forest areas of different sizes in the region of Rio Branco, Acre, Southwestern Amazonia, Brazil. The bees were attracted by 6 aromatic compounds and collected by insect nets and scent baited traps. A total of 3,675 males of Euglossina in 4 genera and 36 species were collected. Eulaema cingulata (Fabricius) was the most common (24.6%), followed by Eulaema meriana (Olivier) (14.6%), Euglossa amazonica Dressler (10.5%), Eulaema nigrita Lepeletier (10.5%) and Eulaema pseudocingulata (Oliveira) (7.2%). Cineole was the scent that attracted the greatest number of individuals (23.8%) and methyl salicylate the greatest number of species (28) for both methods of sampling. Thirty one bees of 9 species with pollinar orchid attached to their bodies were collected. The accumulative number of species stabilized after the 48th collection. Few species were abundant; the great majority were represented by less than 50 bees. The lack of standardized sample protocols limited very much the conclusions derived from comparisons among the majority of studies on Euglossina assemblages. However, the results presented here suggest that the State of Acre is very rich in those bees compared to other regions.Machos de abelhas Euglossina foram coletados entre dezembro de 2005 e setembro de 2006 em 11 áreas florestais de diferentes tamanhos na região de Rio Branco, Acre, Amazônia Sul-Ocidental. As abelhas foram atraídas por 6 substâncias odoríferas e coletadas com rede entomológica e armadilhas. Um total de 3.675 machos de Euglossina pertencentes a 4 gêneros e 36 espécies foi coletado. Eulaema cingulata (Fabricius) foi a espécie mais comum (24,6%), seguida por Eulaema meriana (Olivier) (14,6%), Euglossa amazonica Dressler (10,5%), Eulaema nigrita Lepeletier (10,5%) e Eulaema pseudocingulata (Oliveira) (7,2%). Cineol foi a substância que atraiu maior número de indivíduos (23,8%) e metil salicilato o maior número de espécies (28) para ambos os métodos de coleta. Foram coletados 31 indivíduos pertencentes a 9 espécies portando polinários. O número acumulado de espécies coletadas na região estabilizou a partir da 48ª coleta. Poucas espécies foram abundantes, a maioria representada por menos que 50 indivíduos. A falta de um protocolo amostral padronizado tem limitado comparações entre trabalhos realizados em diferentes regiões. Contudo, os resultados aqui apresentados indicam que o Acre apresenta elevada riqueza dessas abelhas

A Comprehensive Pan-Cancer Molecular Study of Gynecologic and Breast Cancers

We analyzed molecular data on 2,579 tumors from The Cancer Genome Atlas (TCGA) of four gynecological types plus breast. Our aims were to identify shared and unique molecular features, clinically significant subtypes, and potential therapeutic targets. We found 61 somatic copy-number alterations (SCNAs) and 46 significantly mutated genes (SMGs). Eleven SCNAs and 11 SMGs had not been identified in previous TCGA studies of the individual tumor types. We found functionally significant estrogen receptor-regulated long non-coding RNAs (lncRNAs) and gene/lncRNA interaction networks. Pathway analysis identified subtypes with high leukocyte infiltration, raising potential implications for immunotherapy. Using 16 key molecular features, we identified five prognostic subtypes and developed a decision tree that classified patients into the subtypes based on just six features that are assessable in clinical laboratories. By performing molecular analyses of 2,579 TCGA gynecological (OV, UCEC, CESC, and UCS) and breast tumors, Berger et al. identify five prognostic subtypes using 16 key molecular features and propose a decision tree based on six clinically assessable features that classifies patients into the subtypes

lncRNA Epigenetic Landscape Analysis Identifies EPIC1 as an Oncogenic lncRNA that Interacts with MYC and Promotes Cell-Cycle Progression in Cancer

We characterized the epigenetic landscape of genes encoding long noncoding RNAs (lncRNAs) across 6,475 tumors and 455 cancer cell lines. In stark contrast to the CpG island hypermethylation phenotype in cancer, we observed a recurrent hypomethylation of 1,006 lncRNA genes in cancer, including EPIC1 (epigenetically-induced lncRNA1). Overexpression of EPIC1 is associated with poor prognosis in luminal B breast cancer patients and enhances tumor growth in vitro and in vivo. Mechanistically, EPIC1 promotes cell-cycle progression by interacting with MYC through EPIC1's 129\u2013283 nt region. EPIC1 knockdown reduces the occupancy of MYC to its target genes (e.g., CDKN1A, CCNA2, CDC20, and CDC45). MYC depletion abolishes EPIC1's regulation of MYC target and luminal breast cancer tumorigenesis in vitro and in vivo. Wang et al. characterize the epigenetic landscape of lncRNAs genes across a large number of human tumors and cancer cell lines and observe recurrent hypomethylation of lncRNA genes, including EPIC1. EPIC1 RNA promotes cell-cycle progression by interacting with MYC and enhancing its binding to target genes

Scalable Open Science Approach for Mutation Calling of Tumor Exomes Using Multiple Genomic Pipelines

The Cancer Genome Atlas (TCGA) cancer genomics dataset includes over 10,000 tumor-normal exome pairs across 33 different cancer types, in total >400 TB of raw data files requiring analysis. Here we describe the Multi-Center Mutation Calling in Multiple Cancers project, our effort to generate a comprehensive encyclopedia of somatic mutation calls for the TCGA data to enable robust cross-tumor-type analyses. Our approach accounts for variance and batch effects introduced by the rapid advancement of DNA extraction, hybridization-capture, sequencing, and analysis methods over time. We present best practices for applying an ensemble of seven mutation-calling algorithms with scoring and artifact filtering. The dataset created by this analysis includes 3.5 million somatic variants and forms the basis for PanCan Atlas papers. The results have been made available to the research community along with the methods used to generate them. This project is the result of collaboration from a number of institutes and demonstrates how team science drives extremely large genomics projects