TY - JOUR
T1 - Computerized tumor multinucleation index (MuNI) is prognostic in p16+ oropharyngeal carcinoma
AU - Koyuncu, Can F.
AU - Lu, Cheng
AU - Bera, Kaustav
AU - Zhang, Zelin
AU - Xu, Jun
AU - Toro, Paula
AU - Corredor, German
AU - Chute, Deborah
AU - Fu, Pingfu
AU - Thorstad, Wade L.
AU - Faraji, F.
AU - Bishop, Justin A.
AU - Mehrad, Mitra
AU - Castro, Patricia D.
AU - Sikora, Andrew G.
AU - Thompson, Lester D.R.
AU - Chernock, R. D.
AU - Lang Kuhs, Krystle A.
AU - Luo, Jingqin
AU - Sandulache, Vlad
AU - Adelstein, David J.
AU - Koyfman, Shlomo
AU - Lewis, James S.
AU - Madabhushi, Anant
N1 - Funding Information:
This work was supported by the NCI, NIH (1U24CA199374-01, R01CA202752-01A, R01CA208236-01A1, R01CA216579- 01A1, R01CA220581-01A1, 1U01CA239055-01); the National Institute for Biomedical Imaging and Bioengineering, NIH (1R43EB028736-01); the National Center for Research Resources, NIH (1C06RR12463-01); a VA Merit Review Award (IBX004121A) from the US Department of VA Biomedical Laboratory Research and Development Service; a US DOD Breast Cancer Research Program Breakthrough Level 1 Award (W81XWH-19-1-0668); a US DOD Prostate Cancer Idea Development Award (W81XWH-15-1-0558); a US DOD Lung Cancer Investigator-Initiated Translational Research Award (W81XWH-18-1-0440); the US DOD Peer Reviewed Cancer Research Program (W81XWH-16-1-0329); the Ohio Third Frontier Technology Validation Fund; the Wallace H. Coulter Foundation Program in the Department of Biomedical Engineering; a CTSA award to Case Western Reserve University; NCI Cancer Center Support Grant P30CA125123, NIH; Career Development Award 1 IK2 CX001953 from the US Department of VA Clinical Sciences Research and Development Program; Dan L. Duncan Comprehensive Cancer Center Support Grant (NCI-CA125123), NIH; and the Computational Genomic Epidemiology of Cancer Program at Case Comprehensive Cancer Center (T32CA094186). 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.
Funding Information:
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.
Funding Information:
This work was supported by the NCI, NIH (1U24CA199374-01, R01CA202752-01A, R01CA208236-01A1, R01CA216579-01A1, R01CA220581-01A1, 1U01CA239055-01); the National Institute for Biomedical Imaging and Bioengineering, NIH (1R43EB028736-01); the National Center for Research Resources, NIH (1C06RR12463-01); a VA Merit Review Award (IBX004121A) from the US Department of VA Biomedical Laboratory Research and Development Service; a US DOD Breast Cancer Research Program Breakthrough Level 1 Award (W81XWH-19-1-0668); a US DOD Prostate Cancer Idea Development Award (W81XWH-15-1-0558); a US DOD Lung Cancer Investigator-Initiated Translational Research Award (W81XWH-18-1-0440); the US DOD Peer Reviewed Cancer Research Program (W81XWH-16-1-0329); the Ohio Third Frontier Technology Validation Fund; the Wallace H. Coulter Foundation Program in the Department of Biomedical Engineering; a CTSA award to Case Western Reserve University; NCI Cancer Center Support Grant P30CA125123, NIH; Career Development Award 1 IK2 CX001953 from the US Department of VA Clinical Sciences Research and Development Program; Dan L. Duncan Comprehensive Cancer Center Support Grant (NCI-CA125123), NIH; and the Computational Genomic Epidemiology of Cancer Program at Case Comprehensive Cancer Center (T32CA094186). 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.
Funding Information:
Authorship note: CK and CL contributed equally to this work. Conflict of interest: AM is an equity holder in Elucid Bioimaging and in Inspirata Inc. In addition, he has served as a scientific advisory board member for Inspirata Inc, AstraZen-eca, Bristol Myers Squibb, and Merck. Currently he serves on the advisory board of Aiforia Inc. He also has sponsored research agreements with Philips and Bristol Myers Squibb. His technology has been licensed to Elucid Bioimaging. He is also involved in a NIH U24 grant with Pathcore Inc and 3 R01 grants with Inspirata Inc. SK is a consultant for Merck and Regeneron Pharmaceuticals Inc, he has sponsored research agreements with Bristol Myers Squibb and Merck, and he receives honoraria from UpToDate. Copyright: © 2021, American Society for Clinical Investigation. Submitted: November 4, 2020; Accepted: February 25, 2021; Published: April 15, 2021. Reference information: J Clin Invest. 2021;131(8):e145488. https://doi.org/10.1172/JCI145488.
Publisher Copyright:
© 2021, American Society for Clinical Investigation.
PY - 2021/4/15
Y1 - 2021/4/15
N2 - BACKGROUND. Patients with p16+ oropharyngeal squamous cell carcinoma (OPSCC) are potentially cured with definitive treatment. However, there are currently no reliable biomarkers of treatment failure for p16+ OPSCC. Pathologist-based visual assessment of tumor cell multinucleation (MN) has been shown to be independently prognostic of disease-free survival (DFS) in p16+ 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+ 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+ 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+ 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+ OPSCC. These data support further confirmation of the MuNI in prospective trials.
AB - BACKGROUND. Patients with p16+ oropharyngeal squamous cell carcinoma (OPSCC) are potentially cured with definitive treatment. However, there are currently no reliable biomarkers of treatment failure for p16+ OPSCC. Pathologist-based visual assessment of tumor cell multinucleation (MN) has been shown to be independently prognostic of disease-free survival (DFS) in p16+ 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+ 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+ 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+ 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+ OPSCC. These data support further confirmation of the MuNI in prospective trials.
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U2 - 10.1172/JCI145488
DO - 10.1172/JCI145488
M3 - Article
C2 - 33651718
AN - SCOPUS:85104191246
SN - 0021-9738
VL - 131
JO - Journal of Clinical Investigation
JF - Journal of Clinical Investigation
IS - 8
M1 - e145488
ER -