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Mapping Cancer Markers
Towards Precision Medicine
  • Highlights
  • Pastrello C et al. Osteoarthritis Data Integration Portal (OsteoDIP): A web-based gene and non-coding RNA expression database, Osteoarthritis and Cartilage Open, 4(1): 100237, 2022.
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  • Sandmo SB et al. Changes in circulating microRNAs following head impacts in soccer, Brain Inj. 2022 Feb 16:1-12.
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  • Tokar T et al. miRAnno—network-based functional microRNA annotation, Bioinformatics, 38(2):592–593, 2022.
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  • Kotlyar M et al. IID 2021: Towards context-specific protein interaction analyses by increased coverage, enhanced annotation and enrichment analysis. Nucl Acids Res, 50(D1):D640-D647, 2022.
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  • Schimke LF et al. Severe COVID-19 shares a common neutrophil activation signature with other acute inflammatory states, Cells, 11(5):847, 2022.
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  • Bhat M et al. Estrogen Receptor 1 Inhibition of Wnt/Beta-catenin Signaling Contributes to Sex Differences in Hepatocarcinogenesis, Front Oncol. 11:777834, eCollection, 2021.
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  • Ali SA et al. A Network Biology Approach to Understanding the Tissue-Specific Roles of Non-Coding RNAs in Arthritis, Front Endocrinol (Lausanne), 12:744747, eCollection, 2021.
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  • Agapito G et al. Comprehensive pathway enrichment analysis workflows: Covid-19 case study, Briefings Bioinform, 22(2): 676-689, 2021.
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Cancer development is a multi-step process that leads to uncontrolled tumour cell growth caused by and resulting in complex changes: many genes are amplified, deleted, mutated, up- or down-regulated; many proteins and pathways are activated or suppressed. Estimating across 1.9 million patients from 31 countries and 5 continents, current treatments achieve a 5-year survival rate for less than 50% of diagnosed cancer (Coleman et al. Cancer survival in five continents: a worldwide population-based study (CONCORD). Lancet Oncol 9(8): 730-756, 2008).

Years of research improved survival in breast and prostate cancers by finding molecular markers for early diagnosis and by individualized treatment. However, pancreatic cancer remains almost 100% lethal, and the overall survival rate for lung cancer has improved barely during the past decades, having only moved from 13% to 16%.

The Mapping Cancer Markers (MCM) project aims to comprehensively and systematically discover clinically useful markers to aid early cancer detection, identification of high-risk patients, and prediction of treatment response.

To power this research, we rely on World Community Grid volunteers who donate their computers' spare capacity to carry out this extensive analysis. Finding all clinically useful markers would require processing thousands of patient samples and testing an astronomical number of marker combinations, which is not feasible even on World Community Grid. Instead, we use heuristics to reduce the search space, enabling us to tackle this challenge with the computing resources donated by volunteers like you.

Support our research and join World Community Grid today!

Thank you for your support
Igor Jurisica

Principal Investigator
Scientific Director
Dylan Bethune-Waddell

Research Programmer
Chiara Pastrello

Research Associate / Lab Manager
Christian Anders Cumbaa

Research Associate
Max Kotlyar

Research Associate
Richard Lu

SA/DBA/Research Programmer
Mark Abovsky

Research Programmer
Renatas Minkstinas

Research Programmer
Cancer Challenge
Cancer development is a multi-step process that leads to uncontrolled tumour cell growth caused by and resulting in complex changes: many genes are amplified, deleted, mutated, up- or down-regulated, many pathways are activated or suppressed.Estimating from the CONCORD study across 1.9 million patients from 31 countries and 5 continents, current treatments achieve a 5-year survival rate for less than 50% of diagnosed cancer (Coleman, 2008). Approximately 12.7 million new cancer cases were diagnosed worldwide in 2008. Lung, female breast, colorectal & stomach cancers account for more than 40% of all cases. Almost 8 million deaths from cancer occurred worldwide in 2008. Lung, stomach, liver, colorectal & female breast cancers account for more than 50% of all cancer deaths (http://www.cancerresearchuk.org/cancer-info/cancerstats/world/).

Canadian cancer statistics (2012) indicates that lung cancer accounts for almost 14% of all cancer cases in Canada, leading to the highest number of deaths (20,100, 27% of all cancers). Years of research improved relative survival by 6% for all cancers since 1992. Highest improvements are for non-Hodgkin lymphoma & leukemias. Success in breast and prostate cancers has been achieved by finding molecular markers for early diagnosis and by individualized treatment. Highest survival is for thyroid, prostate & testicular cancers. However, pancreatic cancer remains almost 100% lethal, and the overall survival rate for lung cancer has improved barely during the past decades, having only moved from 13% to 16%.

Cancer is caused by genetic changes or environmental effects that interfere with the mechanisms that control cell growth. These changes, as well as normal cell activities, can be detected in tissue samples through the presence of unique indicators, such as DNA and proteins, which together are known as “markers.” Specific combinations of these markers may be associated with a given type of cancer, indicate patient's risk of cancer recurrence, or indicate probability of patient's response to treatment. While several markers are already known to be associated with certain cancers, there are many more to be discovered, as cancer is highly heterogeneous.

The discovery and validation of biomarkers is complex and computationally intensive process. It involves analyzing hundreds of thousands of parameters (clinical variables, gene, protein, microRNA, activity, etc.) to identify subsets that best describe patients, their prognosis and response to treatment. Finding all clinically useful markers and selecting the best subset represents a challenging computational optimization task as we would need to compare all possible parameter combinations.
Approach
The Mapping Cancer Markers (MCM) project focuses on clinical application - discovering specific groups of markers that can be used to improve detection, diagnosis, prognosis and treatment of cancer. As a second goal, the comprehensive analysis of existing molecular profiles of cancer samples will lead to unraveling characteristics of such groups of markers - and in turn improving our understanding how to find them more efficiently.

Our strategy to reduce mortality includes three steps:
  • Increase number of cases diagnosed at earlier stage
    • We need to identify biomarkers for early cancer detection
  • Individualized treatment
    • We need to find biomarkers for treatment selection and response monitoring
  • Improved treatment
    • We need to improve our understanding of disease mechanism and drug mechanism of action
    • We need to identify useful drug combinations and design new medicines
References
  • Coleman, M. P., M. Quaresma, et al. (2008). "Cancer survival in five continents: a worldwide population-based study (CONCORD)." Lancet Oncol 9(8): 730-756.
  • Ein-Dor, L., I. Kela, et al. (2005). "Outcome signature genes in breast cancer: is there a unique set?" Bioinformatics 21(2): 171-178.
  • Ein-Dor, L., O. Zuk, et al. (2006). "Thousands of samples are needed to generate a robust gene list for predicting outcome in cancer." Proc Natl Acad Sci U S A 103(15): 5923-5928.
November 2021 Update

Volunteers tested 15 trillion signatures for Mapping Cancer Markers project
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June 2021 Update

Code update for the Mapping Cancer Markers application
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December 2019 update

The effectiveness of each biomarker depends on the signature size, affecting each biomarker differently.
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July 2018 update

Multiple groups of biomarkers exist primarily due to redundancy and complex wiring of the biological system.
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November 2017 update

After 17+ years at Ontario Cancer Institute (now Princess Margaret Cancer Centre) we have joined Krembil Research Institute (KRI) to work on a more complex approach to chronic diseases.
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March 2017 update

Characterizing 45 million high-performing signatures derived from World-Community-Grid-computed MCM results.
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September 2016 update

Exploring ovarian cancer-associated miRNAs and genes to decipher possible regulatory mechanism.
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November 2015 update

Third phase of lung cancer analysis underway: targeting high-scoring, uncorrelated biomarkers.
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June 2015 update

We used results from the first phase to narrow the field of potential biomarkers from 22,000+ to a subset of 223.
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February 2015 update

Starting a gradual and seamless transition to the new phase of MCM, with no interruption in the supply of work units, and no changes to the visualization or code.
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October 2014 update

To further analyze the nature of our top performing genes, we can identify their inter-relations in biological networks.
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May 2014 update

Identifying how many times a gene occurred within top scoring signatures.
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