Mapping the landscape of human cancer chromatin
Mapping the landscape of human cancer chromatin
By mapping the largely unexplored landscape of chromatin from human primary cancers, researchers have revealed new insights into the regulation of different genes related to cancer.
Their study provides a valuable resource for researchers seeking to understand the regulatory dynamics in a number of cancer types, which may one day help divide populations of cancer patients to obtain more effective therapies for each. Cancer constitutes a very diverse collection of diseases characterized by multiple different types of tumors, clinical characteristics, patient outcomes and therapeutic responses.
Using large-scale genomic and molecular analyzes, the Cancer Genome Atlas (TCGA) has documented many of the genetic mutations responsible for cancer. However, while publicly available TCGA data document a rich collection of genomic information on human cancers, a more systematic investigation of the DNA-protein complex where the genes are located, a material known as chromatin, could help to better localize the switches that affect different genes related to cancer, in ways that may have consequences on the prognosis and treatment of cancer.
A recent breakthrough in the study of accessible chromatin, developed by Stanford researchers, including those from this new study, known as ATAC-seq, has allowed the comprehensive profiling of chromatin in small samples. The ATAC-seq technique uses an enzyme to reveal accessible segments of chromatin, which in turn shows active DNA regulatory elements.
On this occasion, M. Ryan Corces and colleagues have used ATAC-seq to map the chromatin accessibility landscape of 23 primary cancer types in humans using 410 samples derived from TCGA. By identifying more than 500,000 accessible DNA elements, Corces et al. they greatly expand the scope of the known DNA regulatory elements of cancer genomes.
His work provides new insights into genetic loci inherited at cancer risk. In the opinion of the authors, the results of the study also suggest that a systematic approach to understanding non-coding genomics in cancer will be needed, with the goal of actually advancing the effective diagnosis and therapy for the disease. In a related Perspective study, Jussi Taipale writes the following: "Given the scale of the data set and its multimode character, there is great potential for new discoveries." (Source: AAAS)
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