Biofluids such as blood and tumour effusions are routinely collected in clinical care and offer a minimally invasive window into disease biology, yet their protein content is dominated by a small number of highly abundant proteins that obscure the low-abundance signals most likely to contain diagnostic and predictive information.
Malignant ascites is a fluid that accumulates in the abdomen in over 90% of advanced ovarian cancer cases and is routinely discarded following drainage, making it an untapped, readily accessible source of tumour material. We have previously shown that ascites-derived multicellular spheroids carry proteomic signatures that correlate with clinical and laboratory-measured chemotherapy response, but the wide dynamic range of ascites has hindered quantification of low abundance proteins that promote disease.
To overcome this, we applied advanced nanoparticle-based protein enrichment to cell-free ascites from ovarian cancer patients (n=25), identifying 9,900 proteins — more than five-fold deeper coverage than achieved with standard protein depletion approaches. This depth allowed us to quantify 95 cytokines simultaneously from a 120 microlitre sample, with validation using ‘gold-standard’ ELISA detection demonstrating this method to be a rapid and affordable immune profiling tool. Extending the method to malignant pleural effusions from mesothelioma and to matched plasma samples demonstrated its value as a general tool for characterising tumour-associated fluids across cancer types.
Most importantly, combining proteome profiling with functional drug-response testing on ascitic spheroids allowed us to predict chemotherapy response within a clinically actionable timeframe. This positions mass spectrometry-based proteomics as a practical tool to move first-line treatment selection in ovarian cancer away from trial-and-error and towards a personalised proteomics approach.