A Multiplexed Cytokeratin Analysis Using Targeted Mass Spectrometry Reveals Specific Profiles in Cancer-Related Pleural Effusions12

• Published in: Neoplasia (New York, N.Y.) N.Y.), 2016-06, Vol.18 (7), p.399-412
• Main Authors: Domanski, Dominik, Perzanowska, Anna, Kistowski, Michal, Wojtas, Grzegorz, Michalak, Agata, Krasowski, Grzegorz, Dadlez, Michal
• Format: Article
• Language: English
• Subjects: Original article
• ISSN: 1522-8002; 1476-5586
• DOI: 10.1016/j.neo.2016.06.002

Pleural effusion (PE), excess fluid in the pleural space, is often observed in lung cancer patients and also forms due to many benign ailments. Classifying it quickly is critical, but this remains an analytical challenge often lengthening the diagnosis process or exposing patients to unnecessary risky invasive procedures. We tested the analysis of PE using a multiplexed cytokeratin (CK) panel with targeted mass spectrometry–based quantitation for its rapid classification. CK markers are often assessed in pathological examinations for cancer diagnosis and guiding treatment course. We developed methods to simultaneously quantify 33 CKs in PE using peptide standards for increased analytical specificity and a simple CK enrichment method to detect their low amounts. Analyzing 121 PEs associated with a variety of lung cancers and noncancerous causes, we show that abundance levels of 10 CKs can be related to PE etiology. CK-6, CK-7, CK-8, CK-18, and CK-19 were found at significantly higher levels in cancer-related PEs. Additionally, elevated levels of vimentin and actin differentiated PEs associated with bacterial infections. A classifier algorithm effectively grouped PEs into cancer-related or benign PEs with 81% sensitivity and 79% specificity. A set of undiagnosed PEs showed that our method has potential to shorten PE diagnosis time. For the first time, we show that a cancer-relevant panel of simple-epithelial CK markers currently used in clinical assessment can also be quantitated in PEs. Additionally, while requiring less invasive sampling, our methodology demonstrated a significant ability to identify cancer-related PEs in clinical samples and thus could improve patient care in the future.