Ontario Institute for Cancer Research

About: Ontario Institute for Cancer Research is a nonprofit organization based out in Toronto, Ontario, Canada. It is known for research contribution in the topics: Cancer & Population. The organization has 4586 authors who have published 6540 publications receiving 586903 citations.

A global reference for human genetic variation.

Abstract: The 1000 Genomes Project set out to provide a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations. Here we report completion of the project, having reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-genome sequencing, deep exome sequencing, and dense microarray genotyping. We characterized a broad spectrum of genetic variation, in total over 88 million variants (84.7 million single nucleotide polymorphisms (SNPs), 3.6 million short insertions/deletions (indels), and 60,000 structural variants), all phased onto high-quality haplotypes. This resource includes >99% of SNP variants with a frequency of >1% for a variety of ancestries. We describe the distribution of genetic variation across the global sample, and discuss the implications for common disease studies.

Identification of human brain tumour initiating cells

Abstract: The cancer stem cell (CSC) hypothesis suggests that neoplastic clones are maintained exclusively by a rare fraction of cells with stem cell properties. Although the existence of CSCs in human leukaemia is established, little evidence exists for CSCs in solid tumours, except for breast cancer. Recently, we prospectively isolated a CD133+ cell subpopulation from human brain tumours that exhibited stem cell properties in vitro. However, the true measures of CSCs are their capacity for self renewal and exact recapitulation of the original tumour. Here we report the development of a xenograft assay that identified human brain tumour initiating cells that initiate tumours in vivo. Only the CD133+ brain tumour fraction contains cells that are capable of tumour initiation in NOD-SCID (non-obese diabetic, severe combined immunodeficient) mouse brains. Injection of as few as 100 CD133+ cells produced a tumour that could be serially transplanted and was a phenocopy of the patient's original tumour, whereas injection of 10(5) CD133- cells engrafted but did not cause a tumour. Thus, the identification of brain tumour initiating cells provides insights into human brain tumour pathogenesis, giving strong support for the CSC hypothesis as the basis for many solid tumours, and establishes a previously unidentified cellular target for more effective cancer therapies.

The Reactome Pathway Knowledgebase.

Abstract: The Reactome Knowledgebase (www.reactome.org) provides molecular details of signal transduction, transport, DNA replication, metabolism and other cellular processes as an ordered network of molecular transformations-an extended version of a classic metabolic map, in a single consistent data model. Reactome functions both as an archive of biological processes and as a tool for discovering unexpected functional relationships in data such as gene expression pattern surveys or somatic mutation catalogues from tumour cells. Over the last two years we redeveloped major components of the Reactome web interface to improve usability, responsiveness and data visualization. A new pathway diagram viewer provides a faster, clearer interface and smooth zooming from the entire reaction network to the details of individual reactions. Tool performance for analysis of user datasets has been substantially improved, now generating detailed results for genome-wide expression datasets within seconds. The analysis module can now be accessed through a RESTFul interface, facilitating its inclusion in third party applications. A new overview module allows the visualization of analysis results on a genome-wide Reactome pathway hierarchy using a single screen page. The search interface now provides auto-completion as well as a faceted search to narrow result lists efficiently.

Comprehensive molecular characterization of gastric adenocarcinoma

Abstract: Gastric cancer was the world’s third leading cause of cancer mortality in 2012, responsible for 723,000 deaths1. The vast majority of gastric cancers are adenocarcinomas, which can be further subdivided into intestinal and diffuse types according to the Lauren classification2. An alternative system, proposed by the World Health Organization, divides gastric cancer into papillary, tubular, mucinous (colloid) and poorly cohesive carcinomas3. These classification systems have little clinical utility, making the development of robust classifiers that can guide patient therapy an urgent priority. The majority of gastric cancers are associated with infectious agents, including the bacterium Helicobacter pylori4 and Epstein–Barr virus (EBV). The distribution of histological subtypes of gastric cancer and the frequencies of H. pylori and EBV associated gastric cancer vary across the globe5. A small minority of gastric cancer cases are associated with germline mutation in E-cadherin (CDH1)6 or mismatch repair genes7 (Lynch syndrome), whereas sporadic mismatch repair-deficient gastric cancers have epigenetic silencing of MLH1 in the context of a CpG island methylator phenotype (CIMP)8. Molecular profiling of gastric cancer has been performed using gene expression or DNA sequencing9–12, but has not led to a clear biologic classification scheme. The goals of this study by The Cancer Genome Atlas (TCGA) were to develop a robust molecular classification of gastric cancer and to identify dysregulated pathways and candidate drivers of distinct classes of gastric cancer.