Grant: Doctoral: Vanier Canada Graduate Scholarships
University of British Columbia
$150,000.00
Personalised treatment of glioblastoma using machine-learning driven network analysis of drug sensitivity data
EF 2013-14
Résumé
Glioblastoma (GBM) is a common type of aggressive brain tumor for which treatment remains an incredible challenge. With the current treatment methods, patients survive on average only 15 months. Due to the invasive and variable nature of GBM tumors, treatment options are limited and surgery is impossible. In an effort to fully understand GBM, research from the University of Calgary has discovered a way to grow brain tumor cells from patients in the laboratory. Although, these laboratory cell samples have been tested with a variety of established and new drugs, no drug has successfully treated all samples.
Interestingly, some drugs are shown to treat some cell samples while other drugs have success with others. Currently it is unclear what causes this variety in drug response. Using genome sequencing analysis, we hope to understand these different responses by identifying cancer-causing mutations in the cells.
The most challenging aspect of the project is identifying which mutations are key to the drug resistance and which mutations have no effect on the cancer growth. Newer techniques are beginning to bring together existing knowledge about cancer-causing genes with newer biochemistry knowledge and artificial intelligence to predict which mutations are driving the cancer.
The intersection of this set of drug response and mutation data and the development of new analysis techniques offers a unique opportunity for a greater understanding of the genes and the gene interactions which drive cancer. Our ability to test new drugs through collaborators at the University of Toronto means that this project realistically could offer a new direction in the treatment of glioblastoma.
Programme
Doctoral: Vanier Canada Graduate Scholarships
Bénéficiaire
Emplacement
British Columbia, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
CIHR Funding Decisions Database
Tel que publié
Id
300282
Name
Lever Jake
Region
British Columbia
Country
Canada
Orgtype
Institution Paid; Research Institution
Instname2
Cancer Research
Theme2
Biomedical
Prcname2
Vanier Canada Graduate Scholarships CIHR
Projecttitle
Personalised treatment of glioblastoma using machine-learning driven network analysis of drug sensitivity data
Programtype2
Studentship Programs
Orgnameinp2
University of British Columbia
Cihramount2
$150,000
Cihrequipment2
$0
Programname2
Doctoral: Vanier Canada Graduate Scholarships
Keyworddelim
Bioinformatics; Drug Repositioning; Glioblastoma; Machine Learning; Network Analysis; Oncogenomics; Pathway Analysis; Personalised Cancer Therapy
Abstract
Glioblastoma (GBM) is a common type of aggressive brain tumor for which treatment remains an incredible challenge. With the current treatment methods, patients survive on average only 15 months. Due to the invasive and variable nature of GBM tumors, treatment options are limited and surgery is impossible. In an effort to fully understand GBM, research from the University of Calgary has discovered a way to grow brain tumor cells from patients in the laboratory. Although, these laboratory cell samples have been tested with a variety of established and new drugs, no drug has successfully treated all samples.
Interestingly, some drugs are shown to treat some cell samples while other drugs have success with others. Currently it is unclear what causes this variety in drug response. Using genome sequencing analysis, we hope to understand these different responses by identifying cancer-causing mutations in the cells.
The most challenging aspect of the project is identifying which mutations are key to the drug resistance and which mutations have no effect on the cancer growth. Newer techniques are beginning to bring together existing knowledge about cancer-causing genes with newer biochemistry knowledge and artificial intelligence to predict which mutations are driving the cancer.
The intersection of this set of drug response and mutation data and the development of new analysis techniques offers a unique opportunity for a greater understanding of the genes and the gene interactions which drive cancer. Our ability to test new drugs through collaborators at the University of Toronto means that this project realistically could offer a new direction in the treatment of glioblastoma.
Competitiondate
201311
Approvedterm2
3 yrs 0 mth
Pinamesdelim
Lever, Jake
Approvedterm
3 ans 0 mois
Cihrcontribution2
~ $150,000~ $0~