<unk>  (POG) is the field of<unk> logy and<unk>  that is focused on using whole genome analysis to make<unk>  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<unk> 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<unk><unk> databases that currently recognize mutation and abnormalities in the<unk> 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<unk>  treatment options for patients with resistant cancers and ideally prevent toxicities related to conventional chemotherapeutics. History == The novel approach of comparing a patient's tumour versus normal tissue was first identified in 2010 when assessing the genetic evolution of adenocarcinomas of tongue before and after treatment was received. This study presented evidence that the genetic information from these tumours have potential to influence the treatment options for cancers. After identifying the driver mutations of tumour was the RET<unk> gene, the patient was administered with a RET inhibitor (sunitinib), which stabilized the disease for 4 months. A second round of RET inhibitors (sorafenib and sulindac) administration provided an additional 3 months of disease stabilization before the cancer progressed again. The observed mutations and amplification in the recurring metastasis were identified to be consistent with resistance to the RET inhibitors. The evolution of the adenocarcinoma after treatment with RET inhibitors demonstrated with possibility for<unk>  cancer therapy. This approach was then successfully replicated in other cancer types and resulted in the formation of the<unk>  Program at the BC Cancer Agency. This program has now analyzed over 570 adult cancer patients with incurable disease, which were published in a landmark study in 2020. Data availability ==<unk> and transcriptomic sequence datasets from the 2020 Nature publication encompassing the first 570 "POG" patients have been deposited at the European Genome–phenome Archive (EGA, http://www.ebi.ac.uk/ega/) as part of the study EGAS00001001159. Data on mutations, copy changes and expression from tumour samples in the POG program organized by<unk> Tree classification (http://oncotree.mskcc.org) are also accessible from https://www.personalizedoncogenomics.org/cbioportal/. The complete small mutation catalog and gene expression TPMs are available for download from http://bcgsc.ca/downloads/POG570/.
Personalized onco-genomics
Predictive medicine
Individualized cancer immunotherapy
Cancer systems biology
Neoadjuvant therapy
Regenerative medicine
Stem cell tourism
Personal genomics