Cancer Biomarkers for Early Detection and Prediction of Clinical Outcome

Strengthening translational research in cancer genetics at the Medical College of Wisconsin Cancer Center

Full Project Name:Cancer Biomarkers for Early Detection and Prediction of Clinical OutcomePrincipal Investigator:Liang Wang, MD, PhD, PathologyAward Amount:1,309,260
Award Date
April2012
Project Duration:60 months

Project Description Narrative:


Biomedical scientists have long sought to identify ways to diagnose cancers at an early, curable stage or to select the optimal therapy for individual patients. Many cancer patients are diagnosed at a stage in which the cancer is too advanced to be cured, and most cancer treatments are effective in only a minority of patients undergoing therapy. There is tremendous opportunity to improve the outcome for people with cancer by enhancing detection and treatment approaches. Biomarkers, which are molecular, cellular, tissue, or process-based alterations that provide indication of current or future cancer behavior, will be instrumental in making that transition.

In recent decades, knowledge about the basic biology and biochemical pathways underlying cancers has increased tremendously, but translation of that knowledge to more effective patient care and better outcomes remains a challenge. It is widely believed that biomarkers can and will be used to improve cancer screening and detection, to improve the drug development process, and to enhance the effectiveness and safety of cancer care by allowing physicians to tailor treatment for individual patients.

Through this award, a multidisciplinary team of investigators aim to identify and validate a group of biomarkers and translate the discovery into clinical practice.

Outcomes & Lessons Learned:


• Performed a comprehensive genetic and genomic analysis using plasma cell-free nucleic acids. Analysis has identified several genomic regions and genes that may serve as biomarkers for early diagnosis or significantly affect treatment responses and overall survival

• Utilized data to develop a plasma genomic abnormality score system to predict tumor burden in cancer patients

• Disseminated findings through more than 16 peer-reviewed publications and one patent

• Findings provided preliminary data to successfully apply for and receive an NIH R01 grant that will advance further study and impact on health outcomes

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