News | Mammography | November 13, 2015

Joint Texas-Chicago team will combine mammography features with blood-based biomarkers to more precisely predict breast cancer risk

breast cancer subtypes, early detection, risk prediction, biomarkers, Houston Methodist, Randa El-Zein

Image courtesy of Barco


November 13, 2015 — The National Cancer Institute awarded Houston Methodist investigator Randa El-Zein, M.B., Ch.B., Ph.D., a $2.8 million, five-year U01 grant to combine mammography features with blood-based biomarkers to more precisely predict a woman’s risk for breast cancer-specific subtypes.

El-Zein and a team from The University of Texas MD Anderson Cancer Center and University of Chicago believe that high-risk breast cancer patients have an increased amount of genetic instabilities that often can be detected by measuring changes in specific biomarkers. The investigators will use unique features computationally determined from mammograms to identify and develop subtype-specific premalignant signatures for early detection. They then will use molecular blood biomarkers to further improve the precision of those imaging signatures.

Mammography has been the mainstay for early detection of breast cancer for more than four decades, but a substantial number of patients with image-detected breast cancer still die from the disease or receive unnecessary intervention. Researchers hope to identify the premalignant signatures of any given breast cancer subtype, even prior to disease detection. While one in eight women will be diagnosed with breast cancer in her lifetime, these cancers present in distinct subtypes, based on genomic alterations.

If successful, this approach would expand mammography from a tool that screens for the presence of cancer to a true early detection device that identifies parenchymal hallmarks of precancerous changes. The investigative team also includes Isabelle Bedrosian, M.D., F.A.C.S., MD Anderson and Maryellen Giger, Ph.D., University of Chicago.

For more information: www.houstonmethodist.org


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