Publication

Measurement of circulating tumor cells in squamous cell carcinoma of the head and neck and patient outcomes

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Last modified
  • 05/21/2025
Type of Material
Authors
    Tiffany M. Morgan, Emory UniversityXu Wang, Emory UniversityXimei Qian, Emory UniversityJeffrey Switchenko, Emory UniversityShuming Nie, Emory UniversityKirtesh Patel, Emory UniversityRJ Cassidy, Emory UniversityDong Shin, Emory UniversityJonathan Beitler, Emory University
Language
  • English
Date
  • 2019-03-01
Publisher
  • Springer (part of Springer Nature): Springer Open Choice Hybrid Journals
Publication Version
Copyright Statement
  • © 2018, Federación de Sociedades Españolas de Oncología (FESEO).
Final Published Version (URL)
Title of Journal or Parent Work
ISSN
  • 1699-048X
Volume
  • 21
Issue
  • 3
Start Page
  • 342
End Page
  • 347
Grant/Funding Information
  • Research reported in this publication was supported in part by the Biostatistics and Bioinformatics Shared Resource of Winship Cancer Institute of Emory University and NIH/NCI under award number P30CA138292.
Abstract
  • Objectives: We report the outcomes of patients with squamous cell carcinoma of the head and neck (HNSCC) whose circulating tumor cells (CTCs) were quantified using surface-enhanced Raman scattering (SERS) nanotechnology. Methods: SERS tagged with EGF was used to directly measure targeted CTCs. Patient charts were retrospectively reviewed. An optimal cut point for CTCs in 7.5 ml of peripheral blood predictive of for distant metastasis-free survival (DMFS) was identified by maximizing the log-rank statistic. An ROC analysis was also performed. Results: Of 82 patients, 13 experienced metastatic progression. The optimal cut point for DMFS was 675 CTCs (p = 0.047). For those with distant recurrence (n = 13) versus those without distant recurrence (n = 69), the CTC cut point which results in the largest combined sensitivity and specificity values is also 675 (sensitivity = 69%, specificity = 68%). Conclusion: Liquid biopsy techniques in HNSCC show promise as a means of identifying patients at greater risk of disease progression.
Author Notes
Keywords
Research Categories
  • Engineering, Biomedical
  • Biology, Biostatistics
  • Health Sciences, Oncology

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