Memorial Sloan Kettering Cancer Center
New York, New York
Assistant Attending Physician
Breast Medicine Service
Developing a minimally invasive blood test that can detect and classify early-stage breast cancer and predict response to treatment.
Mammography is the gold standard for breast cancer screening but does not distinguish between a benign mass and one that is malignant. A tissue biopsy is then needed to determine the presence or extent of breast cancer. Traditional biopsy is painful, time-consuming, and only gives a snapshot of the disease in a specific area at a moment in time. Major progress has been made in developing techniques, including liquid biopsy, that can detect tumor biomarkers in blood. Liquid biopsy has the potential to identify breast cancer in its earliest stages, before a lump or tumor is detectable, and in later stages, to monitor how the cancer is responding to therapy in real time.
Drs. Comen and Tavazoie are working to identify circulating biomarkers shed by tumor cells that can be used to augment mammography when a suspicious lesion is found, predict the likelihood of a breast cancer to metastasize, or monitor response to therapy. This year, the team performed analyses on blood samples from hundreds of patients with different types of breast diseases to train and test machine learning algorithms to identify predictive markers. This resulted in a cohort of samples that are highly representative of patients with breast diseases in the general population, which strengthens the applicability and potential generalizability of the algorithms for use in a clinical setting. Drs. Comen and Tavazoie found that the machine learning methods were able to distinguish benign from malignant disease, as well as localized (in the breast only) from metastatic disease with high accuracy.
Drs. Comen and Tavazoie plan to further refine their algorithm and continue to extend their analysis to other types of circulating genetic material that play critical roles in breast cancer progression. Additionally, they will test whether combining genetic signatures from tumors such as multiple small RNAs can further enhance diagnostic and predictive capacity. The team believes that the combination will provide a more comprehensive picture of the molecular changes that occur in patients with breast cancer, and ultimately be a valuable tool to inform personalized treatment decisions.
Elizabeth Comen, MD is a medical oncologist at Memorial Sloan Kettering Cancer Center with a practice devoted to the study and treatment of patients with all stages of breast cancer. Dr. Comen earned her BA from Harvard College and her MD from Harvard Medical School. She completed residency at Mount Sinai Hospital and her fellowship at Memorial Sloan Kettering Cancer Center. She has presented her research many times at the American Society of Clinical Oncology (ASCO) Annual Meeting and the San Antonio Breast Cancer Symposium. She has also been awarded several peer-reviewed grants, including the Young Investigator Award from the Conquer Cancer Foundation of ASCO.
Dr. Comen’s research focuses on the mechanisms by which breast cancer metastasizes and spreads to distant organs. In particular, she collaborates with several laboratories to help translate laboratory discoveries regarding metastasis into clinically meaningful treatments for patients at risk for and with metastatic breast cancer. With her laboratory collaborators, Dr. Comen aims to identify unique biomarkers that can help identify new diagnosis of breast cancer as well as identify those women with early-stage breast cancer who are at increased risk for metastasis. For metastatic patients, the team is using laboratory methods to gain a better understanding of metastasis to develop more effective and less toxic treatments.
The Lampert Foundation Award
The Rockefeller University
New York, New York
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