Koyuncu Can F, Lu Cheng, Bera Kaustav, Zhang Zelin, Xu Jun, Toro Paula, Corredor German, Chute Deborah, Fu Pingfu, Thorstad Wade L, Faraji Farhoud, Bishop Justin A, Mehrad Mitra, Castro Patricia D, Sikora Andrew G, Thompson Lester Dr, Chernock R D, Lang Kuhs Krystle A, Luo Jingqin, Sandulache Vlad, Adelstein David J, Koyfman Shlomo, Lewis James S, Madabhushi Anant
Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA.
Louis Stokes Cleveland Veterans Affairs (VA) Medical Center, Cleveland, Ohio, USA.
J Clin Invest. 2021 Apr 15;131(8). doi: 10.1172/JCI145488.
BACKGROUNDPatients 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.METHODSWe 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.RESULTSThe 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.CONCLUSIONMuNI 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.FUNDINGNational 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.
背景
p16阳性口咽鳞状细胞癌（OPSCC）患者有可能通过确定性治疗治愈。然而，目前尚无可靠的p16阳性OPSCC治疗失败生物标志物。基于病理学家对肿瘤细胞多核化（MN）的视觉评估已被证明可独立预测p16阳性OPSCC的无病生存期（DFS）。然而，其量化过程耗时、主观且存在观察者间差异的风险。
方法
我们提出了一种基于深度学习的指标，即多核化指数（MuNI），用于p16阳性OPSCC的预后评估。该方法通过对数字扫描的苏木精-伊红（H&E）染色切片中的肿瘤MN进行量化。从6家机构获取了1094例先前未经治疗的p16阳性OPSCC患者的代表性H&E染色全切片图像，用于MuNI的优化和验证。
结果
在多变量分析中，MuNI可预测p16阳性OPSCC的DFS、总生存期（OS）或无远处转移生存期（DMFS），其风险比（HR）分别为1.78（95%置信区间：1.37 - 2.30）、1.94（1.44 - 2.60）和1.88（1.43 - 2.47），独立于年龄、吸烟状态、治疗类型或肿瘤和淋巴结（T/N）分类。MuNI还分别对I期和III期OPSCC患者的DFS、OS和DMFS具有预后价值。
结论
MuNI有望成为一种低成本、非组织破坏性、基于H&E染色的数字生物标志物检测方法，用于p16阳性OPSCC患者的咨询、治疗和监测。这些数据支持在前瞻性试验中进一步验证MuNI。
资助
美国国立卫生研究院（NIH）国家癌症研究所（NCI）；NIH国家生物医学成像和生物工程研究所；NIH国家研究资源中心；美国退伍军人事务部生物医学实验室研究与发展服务部的VA功绩审查奖；美国国防部（DOD）乳腺癌研究计划突破一级奖；DOD前列腺癌创意发展奖；DOD肺癌研究者发起的转化研究奖；DOD同行评审癌症研究计划；俄亥俄州第三前沿技术验证基金；生物医学工程系的华莱士·H·库尔特基金会计划；凯斯西储大学的临床和转化科学奖（CTSA）计划；NIH NCI癌症中心支持拨款；美国退伍军人事务部临床科学研究与发展计划的职业发展奖；NIH丹·L·邓肯综合癌症中心支持拨款；以及凯斯综合癌症中心的癌症计算基因组流行病学计划。内容仅由作者负责，不一定代表NIH、美国退伍军人事务部、DOD或美国政府的官方观点。
