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sector_ico_Health_trans Human Health

A compressed sensing framework for identifying differentially expressed isoforms and transcriptomic aberrations in cancer samples

176ISO
  • Project Leaders: Cenk Sahinalp, Colin Collins
  • Institutions: Simon Fraser University (SFU)
  • Budget: $249250
  • Program/Competition: Bioinformatics and Computational Biology Competitions
  • Genome Centre(s): Genome Canada
  • Fiscal Year: 2013
  • Status: Closed

New technology provides fast and accurate ways to analyze RNAs (which act as messengers carrying instructions from DNA) that code protein in a tissue. While there are many potential RNA products in a gene, it is believed that it is only necessary to identify and quantify a small number of RNA products in order to get information about a sample’s RNA content. The research team aimed to use a computing technique called compressed sensing to find the smallest possible number of RNA products from each gene. The approach also aimed to help pinpoint the essential differences between samples of RNA products from the same gene, which could potential enable drug development and personalized medicine. They developed and published ORMAM and CompreS, validated them with four patient sample cohorts: Vancouver Prostate Centre, Beltran (previously published prostate tumors), Janssen (contact research), and CPC-GENE (Canadian Prostate Cancer Genome Network, ~200 patient tumors, a ~$20M project). The analysis of the splice variants predicted in the VPC and Beltran cohorts has led to one slice factor potentially driving neuroendocrine differentiation in castration-resistant tumors with its functional role being validated both in vitro and in vivo.