International Agency for Research on Cancer

About: International Agency for Research on Cancer is a government organization based out in Lyon, France. It is known for research contribution in the topics: Population & Cancer. The organization has 2989 authors who have published 9010 publications receiving 929752 citations. The organization is also known as: IARC.

The 2021 WHO Classification of Tumors of the Central Nervous System: a summary.

Abstract: The fifth edition of the WHO Classification of Tumors of the Central Nervous System (CNS), published in 2021, is the sixth version of the international standard for the classification of brain and spinal cord tumors. Building on the 2016 updated fourth edition and the work of the Consortium to Inform Molecular and Practical Approaches to CNS Tumor Taxonomy, the 2021 fifth edition introduces major changes that advance the role of molecular diagnostics in CNS tumor classification. At the same time, it remains wedded to other established approaches to tumor diagnosis such as histology and immunohistochemistry. In doing so, the fifth edition establishes some different approaches to both CNS tumor nomenclature and grading and it emphasizes the importance of integrated diagnoses and layered reports. New tumor types and subtypes are introduced, some based on novel diagnostic technologies such as DNA methylome profiling. The present review summarizes the major general changes in the 2021 fifth edition classification and the specific changes in each taxonomic category. It is hoped that this summary provides an overview to facilitate more in-depth exploration of the entire fifth edition of the WHO Classification of Tumors of the Central Nervous System.

Genetic Heterogeneity and Penetrance Analysis of the BRCA1 and BRCA2 Genes in Breast Cancer Families

Abstract: The contribution of BRCA1 and BRCA2 to inherited breast cancer was assessed by linkage and mutation analysis in 237 families, each with at least four cases of breast cancer, collected by the Breast Cancer Linkage Consortium. Families were included without regard to the occurrence of ovarian or other cancers. Overall, disease was linked to BRCA1 in an estimated 52% of families, to BRCA2 in 32% of families, and to neither gene in 16% (95% confidence interval [CI] 6%-28%), suggesting other predisposition genes. The majority (81%) of the breast-ovarian cancer families were due to BRCA1, with most others (14%) due to BRCA2. Conversely, the majority of families with male and female breast cancer were due to BRCA2 (76%). The largest proportion (67%) of families due to other genes was found in families with four or five cases of female breast cancer only. These estimates were not substantially affected either by changing the assumed penetrance model for BRCA1 or by including or excluding BRCA1 mutation data. Among those families with disease due to BRCA1 that were tested by one of the standard screening methods, mutations were detected in the coding sequence or splice sites in an estimated 63% (95% CI 51%-77%). The estimated sensitivity was identical for direct sequencing and other techniques. The penetrance of BRCA2 was estimated by maximizing the LOD score in BRCA2-mutation families, over all possible penetrance functions. The estimated cumulative risk of breast cancer reached 28% (95% CI 9%-44%) by age 50 years and 84% (95% CI 43%-95%) by age 70 years. The corresponding ovarian cancer risks were 0.4% (95% CI 0%-1%) by age 50 years and 27% (95% CI 0%-47%) by age 70 years. The lifetime risk of breast cancer appears similar to the risk in BRCA1 carriers, but there was some suggestion of a lower risk in BRCA2 carriers <50 years of age.

HMDB 3.0—The Human Metabolome Database in 2013

Abstract: The Human Metabolome Database (HMDB) (www.hmdb.ca) is a resource dedicated to providing scientists with the most current and comprehensive coverage of the human metabolome. Since its first release in 2007, the HMDB has been used to facilitate research for nearly 1000 published studies in metabolomics, clinical biochemistry and systems biology. The most recent release of HMDB (version 3.0) has been significantly expanded and enhanced over the 2009 release (version 2.0). In particular, the number of annotated metabolite entries has grown from 6500 to more than 40,000 (a 600% increase). This enormous expansion is a result of the inclusion of both 'detected' metabolites (those with measured concentrations or experimental confirmation of their existence) and 'expected' metabolites (those for which biochemical pathways are known or human intake/exposure is frequent but the compound has yet to be detected in the body). The latest release also has greatly increased the number of metabolites with biofluid or tissue concentration data, the number of compounds with reference spectra and the number of data fields per entry. In addition to this expansion in data quantity, new database visualization tools and new data content have been added or enhanced. These include better spectral viewing tools, more powerful chemical substructure searches, an improved chemical taxonomy and better, more interactive pathway maps. This article describes these enhancements to the HMDB, which was previously featured in the 2009 NAR Database Issue. (Note to referees, HMDB 3.0 will go live on 18 September 2012.).

HMDB 4.0: the human metabolome database for 2018.

Abstract: The Human Metabolome Database or HMDB (www.hmdb.ca) is a web-enabled metabolomic database containing comprehensive information about human metabolites along with their biological roles, physiological concentrations, disease associations, chemical reactions, metabolic pathways, and reference spectra. First described in 2007, the HMDB is now considered the standard metabolomic resource for human metabolic studies. Over the past decade the HMDB has continued to grow and evolve in response to emerging needs for metabolomics researchers and continuing changes in web standards. This year's update, HMDB 4.0, represents the most significant upgrade to the database in its history. For instance, the number of fully annotated metabolites has increased by nearly threefold, the number of experimental spectra has grown by almost fourfold and the number of illustrated metabolic pathways has grown by a factor of almost 60. Significant improvements have also been made to the HMDB's chemical taxonomy, chemical ontology, spectral viewing, and spectral/text searching tools. A great deal of brand new data has also been added to HMDB 4.0. This includes large quantities of predicted MS/MS and GC-MS reference spectral data as well as predicted (physiologically feasible) metabolite structures to facilitate novel metabolite identification. Additional information on metabolite-SNP interactions and the influence of drugs on metabolite levels (pharmacometabolomics) has also been added. Many other important improvements in the content, the interface, and the performance of the HMDB website have been made and these should greatly enhance its ease of use and its potential applications in nutrition, biochemistry, clinical chemistry, clinical genetics, medicine, and metabolomics science.