Personalized onco-genomics

http://dbpedia.org/resource/Personalized_onco-genomics

Personalized onco-genomics (POG) is the field of oncology and genomics that is focused on using whole genome analysis to make personalized clinical treatment decisions. The program was devised at British Columbia's BC Cancer Agency and is currently being led by Marco Marra and Janessa Laskin. Genome instability has been identified as one of the underlying hallmarks of cancer. The genetic diversity of cancer cells promotes multiple other cancer hallmark functions that help them survive in their microenvironment and eventually metastasise. The pronounced genomic heterogeneity of tumours has led researchers to develop an approach that assesses each individual's cancer to identify targeted therapies that can halt cancer growth. Identification of these "drivers" and corresponding medications us rdf:langString
rdf:langString Personalized onco-genomics
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rdf:langString Personalized onco-genomics (POG) is the field of oncology and genomics that is focused on using whole genome analysis to make personalized clinical treatment decisions. The program was devised at British Columbia's BC Cancer Agency and is currently being led by Marco Marra and Janessa Laskin. Genome instability has been identified as one of the underlying hallmarks of cancer. The genetic diversity of cancer cells promotes multiple other cancer hallmark functions that help them survive in their microenvironment and eventually metastasise. The pronounced genomic heterogeneity of tumours has led researchers to develop an approach that assesses each individual's cancer to identify targeted therapies that can halt cancer growth. Identification of these "drivers" and corresponding medications used to possibly halt these pathways are important in cancer treatment. With the oncogenomic databases that currently recognize mutation and abnormalities in the genomic structure of cancer cells, DNA, RNA, and protein analysis can be used to assess these changes and identify drivers of cancer growth. By decoding the genetic information inside cancer cells, researchers gather information which may help understand factors that promote tumour growth and develop strategies to stop it. Ideally, a catalogue of all somatic cancer mutations will be created in the future that can provide insight into the abnormal cellular pathways of cancer cells and the genetic patterns that drive specific cancer phenotypes. This information can help develop effective personalized treatment options for patients with resistant cancers and ideally prevent toxicities related to conventional chemotherapeutics.
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