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Utility of a ready-to-use PCR system for neuroendocrine tumor diagnosis

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Listed:
  • Mark Kidd
  • Ignat A Drozdov
  • Somer Matar
  • Nicole Gurunlian
  • Nicholas J Ferranti
  • Anna Malczewska
  • Philip Bennett
  • Lisa Bodei
  • Irvin M Modlin

Abstract

Background: Multigene-based PCR tests are time-consuming and limiting aspects of the protocol include increased risk of operator-based variation. In addition, such protocols are complex to transfer and reproduce between laboratories. Aims: Evaluate the clinical utility of a pre-spotted PCR plate (PSP) for a novel multigene (n = 51) blood-based gene expression diagnostic assay for neuroendocrine tumors (NETs). Methods: A pilot study (n = 44; 8 controls and 36 NETs) was undertaken to compare CQ, normalized gene expression and algorithm-based output (NETest score). Gene expression was then evaluated between matched blood:tumor tissue samples (n = 7). Thereafter, two prospective sets (diagnostic: n = 167; clinical validation: n = 48, respectively) were evaluated for diagnostic and clinical utility value. Two independent molecular diagnostics facilities were used to assess assay reproducibility and inter-laboratory metrics. Samples were collected (per CLIA protocol) processed to mRNA and cDNA and then either run per standard assay (liquid primers) or on PSPs. Separately, matching plasma samples were analyzed for chromogranin A (CgA). Statistics included non-parametric testing, Pearson-concordance, Predictive Modeling and AUROC analyses. Results: In the pilot study (n = 44), CQ values were highly concordant (r: 0.82, p 96%) scores and was significantly better (p 96%) NETest results. Moreover, it functions significantly more accurately than CgA.

Suggested Citation

  • Mark Kidd & Ignat A Drozdov & Somer Matar & Nicole Gurunlian & Nicholas J Ferranti & Anna Malczewska & Philip Bennett & Lisa Bodei & Irvin M Modlin, 2019. "Utility of a ready-to-use PCR system for neuroendocrine tumor diagnosis," PLOS ONE, Public Library of Science, vol. 14(6), pages 1-18, June.
    • Handle: RePEc:plo:pone00:0218592
    DOI: 10.1371/journal.pone.0218592
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    1. Laura J. van 't Veer & Hongyue Dai & Marc J. van de Vijver & Yudong D. He & Augustinus A. M. Hart & Mao Mao & Hans L. Peterse & Karin van der Kooy & Matthew J. Marton & Anke T. Witteveen & George J. S, 2002. "Gene expression profiling predicts clinical outcome of breast cancer," Nature, Nature, vol. 415(6871), pages 530-536, January.
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