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Tami Geiger

Tami Geiger

Talk Title: Microvesicle-based identification of cancer biomarkers for early detection of ovarian cancer

Bio:

Position: Associate professor, Department of Human Molecular Genetics and Biochemistry, Sackler Faculty of Medicine, Tel Aviv University

Contact details: Tel Aviv University, Tel Aviv 69978, Israel
E-mail – geiger@tauex.tau.ac.il

Tamar Geiger studied biology at the Hebrew University of Jerusalem, Israel, where she also completed her master’s and doctoral degrees in biochemistry. She carried out her Ph.D. research under the supervision of Prof. Alexander Levitzki. In 2008 she moved to the laboratory of Prof. Matthias Mann at the Max Planck Institute of Biochemistry to specialize in proteomics technology and to apply it to cancer research. In October 2011 Tamar moved back to Israel and opened her own research laboratory at the Sackler Faculty of Medicine at the Tel Aviv University. She is proceeding with clinical proteomic research of breast cancer, melanoma, ovarian cancer and pancreatic cancer with emphasis on the metabolic changes that occur during cancer development and drug treatment. She also works toward cancer biomarker discovery in plasma and develops proteomic techniques for cancer research and biomarker discovery.

Abstract:

Microvesicle-based identification of cancer biomarkers for early detection of ovarian cancer

Gerogina Barnabas1, Michal Harel1, Keren Bahar-Shany2, Keren Levanon2 and Tamar Geiger1

1Department of Human Molecular Genetics and Biochemistry, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel; 2Sheba Cancer Research Center, Chaim Sheba Medical Center, Ramat Gan, Israel.

Mass spectrometry-based identification of cancer biomarkers in body fluids, has great potential to develop into non-invasive diagnostic tests. However, the tremendous dynamic range of proteins in the plasma hampers identification of low abundant biomarkers. To overcome this challenge we isolate plasma microvesicles, which are largely devoid of these highly abundant proteins. Using this method, we identified 3638 plasma-derived proteins in triplicate runs, and quantified disease biomarkers in cancer-patient plasma specimens1. We applied this technology to early detection of ovarian cancer, but rather than examining plasma, we analyzed uterine lavage fluid, which has the potential to contain tumor markers at an early stage. Proteomic analysis of purified microvesicles from 134 samples identified >8000 proteins, and yielded a minimal diagnostic signature of 21 proteins, which provided high specificity (91%) and correctly identified stage IA lesions. Altogether, this platform enables high throughput identification of biomarkers to allow early diagnosis and personalized treatment.

1Harel, M., Oren-Giladi, P., Kaidar-Person, O., Shaked, Y., & Geiger, T. PROMIS-Quan: a novel proteomic method for plasma biomarker quantification. Mol Cell Proteomics, mcp-M114 (2015).

tami