Performance of the MasSpec pen for rapid diagnosis of Ovarian cancer

Marta Sans, Jialing Zhang, John Q. Lin, Clara L. Feider, Noah Giese, Michael Breen, Katherine Sebastian, Jinsong Liu, Anil K. Sood, Livia Eberlin

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

BACKGROUND: Accurate tissue diagnosis during ovarian cancer surgery is critical to maximize cancer excision and define treatment options. Yet, current methods for intraoperative tissue evaluation can be time intensive and subjective. We have developed a handheld and biocompatible device coupled to a mass spectrometer, the MasSpec Pen, which uses a discrete water droplet for molecular extraction and rapid tissue diagnosis. Here we evaluated the performance of this technology for ovarian cancer diagnosis across different sample sets, tissue types, and mass spectrometry systems. METHODS: MasSpec Pen analyses were performed on 192 ovarian, fallopian tube, and peritoneum tissue samples. Samples were evaluated by expert pathologists to confirm diagnosis. Performance using an Orbitrap and a linear ion trap mass spectrometer was tested. Statistical models were generated using machine learning and evaluated using validation and test sets. RESULTS: High performance for high-grade serous carcinoma (n = 131; clinical sensitivity, 96.7%; specificity, 95.7%) and overall cancer (n = 138; clinical sensitivity, 94.0%; specificity, 94.4%) diagnoses was achieved using Orbitrap data. Variations in the mass spectra from normal tissue, low-grade, and high-grade serous ovarian cancers were observed. Discrimination between cancer and fallopian tube or peritoneum tissues was also achieved with accuracies of 92.6% and 87.9%, respectively, and 100% clinical specificity for both. Using ion trap data, excellent results for high-grade serous cancer vs normal ovarian differentiation (n = 40; clinical sensitivity, 100%; specificity, 100%) were obtained. CONCLUSIONS: The MasSpec Pen, together with machine learning, provides robust molecular models for ovarian serous cancer prediction and thus has potential for clinical use for rapid and accurate ovarian cancer diagnosis.

Original languageEnglish (US)
Pages (from-to)674-683
Number of pages10
JournalClinical Chemistry
Volume65
Issue number5
DOIs
StatePublished - May 1 2019

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Ovarian Neoplasms
Tissue
Peritoneum
Mass spectrometers
Learning systems
Fallopian Tube Neoplasms
Ions
Neoplasms
Molecular Models
Fallopian Tubes
Statistical Models
Surgery
Mass spectrometry
Mass Spectrometry
Technology
Carcinoma
Equipment and Supplies
Water

ASJC Scopus subject areas

  • Clinical Biochemistry
  • Biochemistry, medical

Cite this

Sans, M., Zhang, J., Lin, J. Q., Feider, C. L., Giese, N., Breen, M., ... Eberlin, L. (2019). Performance of the MasSpec pen for rapid diagnosis of Ovarian cancer. Clinical Chemistry, 65(5), 674-683. https://doi.org/10.1373/clinchem.2018.299289

Performance of the MasSpec pen for rapid diagnosis of Ovarian cancer. / Sans, Marta; Zhang, Jialing; Lin, John Q.; Feider, Clara L.; Giese, Noah; Breen, Michael; Sebastian, Katherine; Liu, Jinsong; Sood, Anil K.; Eberlin, Livia.

In: Clinical Chemistry, Vol. 65, No. 5, 01.05.2019, p. 674-683.

Research output: Contribution to journalArticle

Sans, M, Zhang, J, Lin, JQ, Feider, CL, Giese, N, Breen, M, Sebastian, K, Liu, J, Sood, AK & Eberlin, L 2019, 'Performance of the MasSpec pen for rapid diagnosis of Ovarian cancer', Clinical Chemistry, vol. 65, no. 5, pp. 674-683. https://doi.org/10.1373/clinchem.2018.299289
Sans, Marta ; Zhang, Jialing ; Lin, John Q. ; Feider, Clara L. ; Giese, Noah ; Breen, Michael ; Sebastian, Katherine ; Liu, Jinsong ; Sood, Anil K. ; Eberlin, Livia. / Performance of the MasSpec pen for rapid diagnosis of Ovarian cancer. In: Clinical Chemistry. 2019 ; Vol. 65, No. 5. pp. 674-683.
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