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Mapping Cancer Markers
Towards Precision Medicine
  • Highlights
  • the Top 100 AI in Oncology leaders list,
    (Deep Knowledge Analytics)
  • Tavasolian F, Lively S, Pastrello C, Tang M, Lim M, Pacheco A, Qaiyum Z, Yau E, Baskurt Z, Jurisica I, Kapoor M, Inman RD. Proteomic and genomic profiling of plasma exosomes from patients with ankylosing spondylitis, Ann Rheum Dis, ard-2022-223791, 2023. doi: 10.1136/ard-2022-223791. Epub ahead of print.
  • Wong SWH, Pastrello C, Kotlyar M, Faloutsos C, Jurisica I. USNAP: Fast unique dense region detection and its application to lung cancer, Bioinformatics, 39(8):btad477, 2023.
    Read more
  • van Gogh M et al. Tumor cell-intrinsic c-Myb upregulation stimulates antitumor immunity in a murine colorectal cancer model. Cancer Immunol Res. 2023 Jul 21:CIR-22-0912.
    Read more
  • Cente M et al. Association of Nonconcussive Repetitive Head Impacts and Intense Physical Activity With Levels of Phosphorylated Tau181 and Total Tau in Plasma of Young Elite Soccer Players. JAMA Netw Open. 6(3):e236101, 2023.
    Read more
  • D'Angelo E et al. An integrated multiomics analysis of rectal cancer patients identified POU2F3 as a putative druggable target and entinostat as a cytotoxic enhancer of 5-fluorouracil. Int J Cancer. 2023 Feb 23. doi: 10.1002/ijc.34478. Epub ahead of print.
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  • Prado CAS et al. Integrative systems immunology uncovers molecular networks of the cell cycle that stratify COVID-19 severity. J Med Virol.95(2):e28450, 2023.
    Read more
  • Hauschild AC et al. MirDIP 5.2: tissue context annotation and novel microRNA curation. Nucleic Acids Res. 51(D1):D217-D225, 2023.
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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.
September 2023 Update

Since the ovarian cancer results were dishomogeneous, we will begin running additional ovarian work units starting September 25th.
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September 2023 Update

We continue our work on characterizing lung cancer biomarkers identified in the MCM1 project. This update focuses on ADH6, a gene associated with smoking status and lung cancer prognosis.
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July 2023 Update

We continue our work on characterizing lung cancer biomarkers identified in the MCM1 project. This update focuses on GSDMB, a gene associated with lung cancer survival and differentially expressed across multiple cancer types compared to normal tissues.
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April 2023 Update

Continuing research into putative lung cancer biomarkers, we have identified 26 genes that are present with top scores across all the signature sizes considered. This update focuses on a gene called FARP1, which is linked to lung cancer metastasis.
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March 2023 Update

We have identified 26 genes that are present with top scores across all the signature sizes considered. This update focuses on VAMP1, a gene linked to patient survival and differentially expressed in normal lung compared to lung cancer.
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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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Donations are vital
for supporting WCG work
and are greatly appreciated.
  • Our Vision: A healthier world.
  • Our Mission: Accelerating science by creating a supercomputer empowered by a global community of volunteers.
  • “WCG continues to support open-source and opendata research and helps reduce computational time to empower scientists to address the world’s most pressing questions at no cost to the researchers”. Dr. Igor Jurisica
  • “By its very nature, World Community Grid is a collaborative effort involving individuals and institutions from around the world working towards innovative advancements in science that benefit humanity. Distributive is proud to be a part of this mission.” Dr. Dan Desjardins, co-founder & CEO, Distributive Corp., Kingston, Ontario, Canada
  • “This work has demonstrated the importance of the integration of computational and experimental approaches, as well as the potential of large-scale collaborative networks to advance drug discovery projects for neglected diseases and emerging viruses, despite the lack of available direct antiviral activity and cytoprotective effect data, that reflects on the assertiveness of the computational predictions.” Dr. Carolina Horta Andrade; Open Zika project
  • “With the help of volunteers, partners, and institutions, the WCG will continue to grow as the world's largest volunteer-driven supercomputer, enabling seemingly impossible scientific research to come to life”.
Make a one Time Donation Make a Monthly Donation

In the fall of 2004 IBM launched the World Community Grid (WCG). The WCG was funded and run by IBM as a philanthropic project until February 2022. Over the past year, the WCG has been transferred to the Krembil Research Institute, University Health Network (UHN), located in Toronto, Canada. The WCG is now managed by Dr. Igor Jurisica and his team at UHN.

We are exceptionally grateful to IBM for their many years of financial and operational support. WCG continues to support open-source and open-data research and helps reduce computational time to allow scientists to address the world’s most pressing questions at no cost to the researchers. As an academic group, we face a significant financial challenge in providing the same level of support to the global research community.

Across 18 years of life, over 800,000 volunteers like you have provided their unused computing resources to support the work of the WCG researchers who in turn have conducted ground-breaking medical and environment-related research that is changing the world. We thank everyone who has contributed the spare compute cycles of their devices at home, and hope that you will continue to support WCG as we expand the number of projects and grow the size of the grid.

Together, there is much more we can do. But I cannot do it with my own research funding alone. As an academic resource, WCG faces significant financial and technical challenges in providing the necessary level of support to the global research community. WCG needs your help! If you are already contributing your computing resources, we thank you. If you haven’t yet, you can sign up:

Join WCG as a Volunteer

Also, if you can, please consider donating to WCG – any amount of assistance is appreciated. While the WCG is exceedingly efficient in terms of operational cost, we still need funding for software development and maintaining the infrastructure of the grid. If you, your friends and family, or your organization can help with a donation, this will go a long way to enabling WCG to continue and grow as the world’s largest volunteer-driven supercomputer, enabling seemingly impossible scientific research to come to life.

There are three options:

  • For a one-time donation with a Canadian tax receipt automatically generated, please use the following link (default amount can be changed by clicking and typing it in the "other"): Click here to donate directly to the World Community Grid via UHN Foundation.
  • There is also an option for monthly, recurring donations - but a proper selection needs to be made to ensure funds are directed to WCG. Please ensure you select the “direct my gift to” field to "other" and enter "World Community Grid". (default amount can be changed by clicking and typing it in the "other")
    • Click here to setup recurring monthly donation directly to the World Community Grid via UHN Foundation.
  • Should you wish to receive a US tax receipt, please call UHN Foundation at 416-603-5300 or toll free at 1-877-846-4483 (UHN-GIVE). (sorry for the manual step - unfortunately, UHN Foundation does not have the means to automate the process at this time.)

Thank you for your support,

Dr. Igor Jurisica