Proteomic characterization of ovarian cancer for improved diagnostics
Purpose and aims
The project aims at developing a new blood-based test for improved diagnostics of ovarian cancer (OC). OC is one of the most devastating forms of cancer affecting women worldwide. Being one of the most challenging gynecological malignancies it claims nearly 150000 lives annually1. OC is currently diagnosed through a combination of pelvic examinations, ultrasound or CT scans, and low specificity blood tests with a confirmatory diagnosis only possible after invasive surgery. Current technological advances in the mass spectrometry (MS)-based platforms have now enabled the identification of entire disease proteomes and targeted monitoring of even the lowest abundant proteins from patient biofluids. Furthermore, the integration of proteomics data with available clinical information allows cohort wide analysis of clinically significant markers2.
In the proposed study, we collaborate with the Swedish leading OC expert Prof. Karin Sundfeldt and have access to large cohorts of matched plasma, effusions, and solid tumors for benign and malignant ovarian cancer conditions. Thus, the major objective of the project is to identify plasma biomarkers via multilayered proteomics approaches that will enable discrimination between benign and malignant conditions. Thereafter we aim to develop a diagnostic test to guide clinical decisions on surgery for OC patients. The test will reduce the unnecessary over-surgery of benign cysts, to the benefit of both patients and the health care system.
State-of-the-art
Mass spectrometry is the method of choice for large scale analysis of proteins3,4. With modern MS instrumentation and workflows, it is today possible to quantify most, if not all, proteins in biological fluids such as plasma5.
References
- Whitwell, H.J. et al. Br. J. Cancer 122, 847–856 (2020).
- Liu, Y., Hüttenhain, R., Collins, B. & Aebersold, R. Expert Rev. Mol. Diagn. 13, 811–825 (2013).
- Han, X., Aslanian, A. & Yates, J.R. Curr. Opin. Chem. Biol. 12, 483–490 (2008).
- Aebersold, R. & Mann, M. Nature 537, 347–355 (2016).