Five projects by members of the UBC Faculty of Medicine have received funding from a national competition for bioinformatics-related research.
Genome Canada, in partnership with the Canadian Institutes of Health Research (CIHR), distributed $6.2 million through the Bioinformatics and Computational Biology Competition. The projects will be conducted over three years. Expected outcomes include improved analytical approaches to detecting variations and mutations in DNA and RNA that are related to cancer diagnosis and care, as well as easy-to-use bioinformatics and genomic tools to enable health care workers to better manage communicable diseases.
The UBC faculty members to receive funding are:
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Inanc Birol, Associate Professor, Medical Genetics; Steven Jones, Professor, Medical Genetics; Aly Karsan, Professor, Pathology and Laboratory Medicine: Next generation bioinformatics for clinical genomics using de novo assembly in personalized medicine
Genomics technologies that detect variations and mutations in DNA and RNA can advance cancer care and reduce health care costs by improving preventive care, diagnosis and treatment. High-throughput DNA and RNA sequencing technologies can help realize this vision by generating large amounts of sequence data rapidly and at low cost. However, solid analysis of the generated data is essential to reach its full potential and will provide the backbone to application.
Dr. Birol, Dr. Jones and Dr. Karsan are developing an analytical approach to detect variations and mutations in DNA and RNA related to cancer diagnosis and care. This approach could lead to more efficient and effective clinical testing for various types of cancers across Canada.
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Sohrab Shah, Assistant Professor, Pathology and Laboratory Medicine, and Paul C. Boutros: Computational interpretation of cancer genomes: defining mutational landscapes for translational genomics
Tumours develop through the accumulation of mutations in DNA. Recent advances in high‐throughput DNA sequencing allow researchers rapid identification of mutations in a genome. This has increased understanding of the biology of cancer cells, and has led to more effective drugs and better predictions of patient outcomes. However, maximizing the clinical use of next‐generation sequencing data requires sophisticated software to improve the analysis of genomes and identification of mutant sequences related to tumours.
Dr. Shah and Boutros are developing innovative software that will improve patient care by identifying and analyzing the mutations involved in cancer progression.
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Wyeth Wasserman, Professor, Medical Genetics: Applied bioinformatics of Cis‐regulation for disease exploration (ABC4DE)
The goal of personalized medicine is to treat patients in the manner that is most appropriate for each individual. Before this can happen, doctors will need software that can perform detailed high‐speed and low‐cost analyses of patients’ specific genetic mutations.
Dr. Wasserman, of the Centre for Molecular Medicine and Therapeutics, is developing software that will understand and categorize the pieces of DNA that help turn genes on or off. These small sequences of DNA are spread throughout the human genome and serve a critical role in controlling when and where genes are turned on. Mutations in these on/off switches can cause birth defects, disease risk and adverse drug reactions. The software will help physicians analyze patients’ genetic mutations and pave the way for personalized medicine.
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Joerg Gsponer, Assistant Professor, Biochemistry and Molecular Biology: Tool for proteome‐wide identification of regulatory switches
Despite significant progress in diagnosis and treatment, cancer remains Canada’s leading cause of death. Although scientists have made major efforts in identifying mutations in some cancers, it is still not known how these mutations cause cancer. Cancer is often related to the disruption of regulatory mechanisms in the cell, including auto‐inhibition, a process that allows proteins to switch their functions on and off. Mutations can alter these protein switches, which can lead to changes in cell behaviour and ultimately cancer. However, there is no easy way to determine when cancer‐causing mutations affect auto‐inhibitory switches.
Dr. Gsponer is developing a new method to identify auto‐inhibitory switches through the use of genomic and proteomic information.
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Sohrab Shah, Assistant Professor, Pathology and Laboratory Medicine: Measuring and modeling tumour evolution from next generation sequencing data — enabling clinical study of clonal diversity in cancer patients
Breast and ovarian cancers are significant causes of disease and death among North American women. Tumours in these cancers can acquire different mutations, resulting in cells that may respond differently to therapy. However, this genetic diversity within tumours is rarely considered when it comes to treatment, even though it is believed to contribute to drug resistance and disease progression. While new sequencing technologies have provided some insight into the nature of tumour evolution, it is still unclear how evolutionary processes contribute to cancer.
Dr. Shah is using sequencing data gathered from breast and ovarian cancer patient samples to create software that will improve understanding of tumour evolution and help predict clinical results.