TSSP4 - CMap – carcinogenome project

Description : The Connectivity Map, or CMap, is a resource that uses transcriptional expression data to probe relationships between diseases, cell physiology, and therapeutics. The changes in gene expression, or “signatures,” that arise from a disease, genetic perturbation (knockdown or overexpression of a gene) or treatment with a small molecule are compared for similarity to all perturbational signatures in the database. Perturbations that elicit highly similar, or highly dissimilar, expression signatures are termed “connected”; their related transcriptional effects suggest they confer related physiological effects on the cell. Our goal is to use these connections to uncover novel treatments for a variety of diseases, including cancers, neurological diseases, and infectious diseases. (https://clue.io/cmap) Exposure to environmental chemicals is known to play a significant role in carcinogenesis. While some chemicals are well-known carcinogens, only a small fraction of those in commercial use and to which the human population is exposed has undergone thorough carcinogenicity testing. Furthermore, many of the biological mechanisms of actions of chemical carcinogens are poorly understood. The current gold standard for chemical carcinogenicity testing is the 2-year rat bioassay, which is expensive and time-consuming, and its relevance to human carcinogenesis has been questioned. To date, about ~1500 chemicals have been tested for long-term carcinogenicity in rodent models by this approach, out of the ~85,000 chemicals used in common household products or industrial settings. We aim to develop a fast and scalable approach to carcinogenicity screening, one that takes advantage of short-term chemical exposures in human cell lines and high-throughput gene expression profiling. This approach will support the profiling of a large number of chemicals in a rapid and cost-effective fashion, and will allow us to thoroughly evaluate the hypothesis that short-term in-vitro assays can accurately predict long-term in-vivo carcinogenicity. (https://carcinogenome.org/)

Created : Jan. 27, 2022, 9:27 a.m.

Owner : tdarde