Circulating tumor cell and cell-free RNA capture and expression analysis identify platelet-associated genes in metastatic lung cancer
PublisherBioMed Central Ltd.
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AbstractBackground: Circulating tumor cells (CTC) and plasma cell-free RNA (cfRNA) can serve as biomarkers for prognosis and treatment response in lung cancer. One barrier to the selected or routine use of CTCs and plasma cfRNA in precision oncology is the limited quantity of both, and CTCs are only seen in metastatic disease. As capture of CTCs and plasma cfRNA presents an opportunity to monitor and assess malignancies without invasive procedures, we compared two methods for CTC capture and identification, and profiled mRNA from CTCs and plasma cfRNA to identify potential tumor-associated biomarkers. Methods: Peripheral blood was collected from ten patients with small cell lung cancer (SCLC), ten patients with non-small cell lung cancer (NSCLC) and four healthy volunteers. Two methods were used for CTC capture: the standard epithelial cell adhesion molecule (EpCam) CellSearch kit (unicapture) and EpCAM plus HER2, EGFR and MUC-1 specific combined ferrofluid capture (quadcapture). For the quadcapture, anti-cytokeratin 7 (CK7) was additionally used to assist in CTC identification. NanoString analysis was performed on plasma cfRNA and on mRNA from combined ferrofluid isolated CTCs. Expression data was analyzed using STRING and Reactome. Results: Unicapture detected CTCs in 40% of NSCLC and 60% of SCLC; whereas, quadcapture/CK7 identified CTCs in 20% of NSCLC and 80% of SCLC. Bioinformatic analysis of NanoString data identified high expression of a platelet factor 4 (PF4)-related group of transcripts. Conclusions: Quadcapture ferrofluid reagent did not significantly improve CTC capture efficacy. NanoString analysis based on CTC and plasma cfRNA data highlighted an intriguing PF-4-centric network in patients with metastatic lung cancer. Copyright 2019 The Author(s).
SponsorsThe authors were supported by the Ruth L. Kirschstein National Research Service Award F30 fellowship (F30 CA180607) from the National Institutes of Health, the NIH R01 CA218802 NIH R21 CA223394 grants and V Foundation translation award program T2018-013, and NCI Core Grant P30 CA006927. Bioinformatics analysis performed by I. S and R.V. was in part supported by the Russian Science Foundation (grant #15-15-20032).
Identifier to cite or link to this itemhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85067603297&doi=10.1186%2fs12885-019-5795-x&partnerID=40&md5=0d346005c330fcd5cc46f9c08c633b38; http://hdl.handle.net/10713/10574
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