Computerized tumor multinucleation index (MuNI) is prognostic in [p16.sup.+] oropharyngeal carcinoma.

Citation metadata

Date: Apr. 15, 2021
From: Journal of Clinical Investigation(Vol. 131, Issue 8)
Publisher: American Society for Clinical Investigation
Document Type: Report
Length: 6,510 words
Lexile Measure: 1380L

Document controls

Main content

Abstract :

BACKGROUND. Patients with [p16.sup.+] oropharyngeal squamous cell carcinoma (OPSCC) are potentially cured with definitive treatment. However, there are currently no reliable biomarkers of treatment failure for [p16.sup.+] OPSCC. Pathologist-based visual assessment of tumor cell multinucleation (MN) has been shown to be independently prognostic of disease-free survival (DFS) in [p16.sup.+] OPSCC. However, its quantification is time intensive, subjective, and at risk of interobserver variability. METHODS. We present a deep-learning-based metric, the multinucleation index (MuNI), for prognostication in [p16.sup.+] OPSCC. This approach quantifies tumor MN from digitally scanned H&E-stained slides. Representative H&E-stained whole-slide images from 1094 patients with previously untreated [p16.sup.+] OPSCC were acquired from 6 institutions for optimization and validation of the MuNI. RESULTS. The MuNI was prognostic for DFS, overall survival (OS), or distant metastasis-free survival (DMFS) in [p16.sup.+] OPSCC, with HRs of 1.78 (95% CI: 1.37-2.30), 1.94 (1.44-2.60), and 1.88 (1.43-2.47), respectively, independent of age, smoking status, treatment type, or tumor and lymph node (T/N) categories in multivariable analyses. The MuNI was also prognostic for DFS, OS, and DMFS in patients with stage I and stage III OPSCC, separately. CONCLUSION. MuNI holds promise as a low-cost, tissue-nondestructive, H&E stain-based digital biomarker test for counseling, treatment, and surveillance of patients with [p16.sup.+] OPSCC. These data support further confirmation of the MuNI in prospective trials. FUNDING. National Cancer Institute (NCI), NIH; National Institute for Biomedical Imaging and Bioengineering, NIH; National Center for Research Resources, NIH; VA Merit Review Award from the US Department of VA Biomedical Laboratory Research and Development Service; US Department of Defense (DOD) Breast Cancer Research Program Breakthrough Level 1 Award; DOD Prostate Cancer Idea Development Award; DOD Lung Cancer Investigator-Initiated Translational Research Award; DOD Peer-Reviewed Cancer Research Program; Ohio Third Frontier Technology Validation Fund; Wallace H. Coulter Foundation Program in the Department of Biomedical Engineering; Clinical and Translational Science Award (CTSA) program, Case Western Reserve University; NCI Cancer Center Support Grant, NIH; Career Development Award from the US Department of VA Clinical Sciences Research and Development Program; Dan L. Duncan Comprehensive Cancer Center Support Grant, NIH; and Computational Genomic Epidemiology of Cancer Program, Case Comprehensive Cancer Center. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH, the US Department of VA, the DOD, or the US Government.

Source Citation

Source Citation   

Gale Document Number: GALE|A659258529