[1][2] The program was devised at British Columbia's BC Cancer Agency and is currently being led by Marco Marra and Janessa Laskin.
This information can help develop effective personalized treatment options for patients with resistant cancers and ideally prevent toxicities related to conventional chemotherapeutics.
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.
[6] A second round of RET inhibitors (sorafenib and sulindac) administration provided an additional 3 months of disease stabilization before the cancer progressed again.
[7] Genomic and transcriptomic sequence datasets from the 2020 Nature publication encompassing the first 570 "POG" patients[7] 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 OncoTree classification (http://oncotree.mskcc.org) are also accessible from https://www.personalizedoncogenomics.org/cbioportal/.
OMICS technologies are high-throughput methods that help evaluate and unbiased investigate characteristics of the genome, epigenome, transcriptome, proteome, and metabolome.
The majority of somatic mutations are mere byproducts of the unstable cancer genome and do not enhance the tumour cell growth.
Systematically analyzing more than 50,000 tumour genomes has elucidated new cancer genes and pathways, opening up new pursuits for pharmaceutical companies.
Researchers have also discovered general trends on different types of cancer that may inform public education on proactive preventative measures.
In 2018, Zhang and colleagues analyzed 930 tumour whole genomes with associated transcriptomes (collection of mRNA transcripts) to show mutations in 193 non-coding sequences disrupt normal gene expression.
[17] Notably, they repetitively found noncoding mutations affected DAAM1, MTG2, and HYI transcription wherein DAAM1 expression initiate invasive cell migration in the tumour.
[17] Since the core somatic gene expression network is defective in 88% tumours, Zhang et al. suggested that noncoding mutation may have a widespread impact in cancer.
The genetic information collected from the tumour helps health-care professionals make rational clinical decisions regarding treatment strategies.
These strategies may be used to target the growth of the tumour, identify potential clinical trials that patients could enrol in, and find more effective and less toxic drug options.
[21] The success of this drug in treating CML has highlighted the importance of personalized treatment options and identification of molecular pathways to be targeted.
Zuri Scrivens was enrolled in the POGs program at the BC Cancer agency to help devise a personalized novel therapy based on her tumour mutations.
[23] From the results of her tumour genome sequencing analysis, a drug that is most commonly used in the treatment of type 2 diabetes was selected to treat her recurrence along with a standard chemotherapy medication.
Genomic data can provide valuable information regarding each individuals’ cancer and guide clinical decision-making from health-care professionals.
[26][27] Patients may experience either short-lived or long-term benefits from the medication, but since cancer is constantly evolving, it often develops even more genetic changes that allow it to adapt and survive against the drug.