Oral Cavity Quantitative Histomorphometric Risk Classifier (OHbIC) in Oral Cavity Squamous Cell Carcinoma (OC-SCC)

口腔鳞状细胞癌 (OC-SCC) 中的口腔定量组织形态风险分类器 (OHbIC)

• 批准号: 10726124
• 负责人: JAMES LEWIS
• 金额: $ 65.48万
• 依托单位: EMORY UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-12-30 至 2026-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10726124
• 关键词: Adjuvant; Adjuvant Chemotherapy; Adjuvant Therapy; Adoption; Adult; Age; American Cancer Society; American Joint Committee on Cancer; Architecture; Biological Assay; Cancer Center; Categories; Cells; Cessation of life; Classification; Clinic; Clinical; Clinical Trials; Clinical Trials Cooperative Group; Clinical stratification; Cloud Computing; Collaborations; Computer Assisted; Computer Vision Systems; Diagnosis; Disease; Eligibility Determination; European Organization for Research and Treatment of Cancer; Excision; Foundations; Head and neck structure; Hematoxylin and Eosin Staining Method; Histologic; Image; India; Institution; Invaded; Left; Malignant Neoplasms; Measurement; Measures; Modeling; Molecular; Morphology; Nuclear; Operative Surgical Procedures; Oral cavity; Outcome; Patient Selection; Patient risk; Patient-Focused Outcomes; Patients; Pattern; Pattern Recognition; Platinum; Postoperative Period; Prognostic Marker; Radiation; Radiation Therapy Oncology Group; Radiation therapy; Recurrence; Regimen; Relapse; Resources; Risk; Risk Marker; San Francisco; Shapes; Slide; Smoking; Staging; Stains; Standardization; Surgical Oncology; Surgical Pathology; System; Systemic Therapy; Testing; Texture; Therapeutic; Tissue Microarray; Tissue Stains; Tissues; Training; Tumor Cell Invasion; Tumor stage; Tumor-Infiltrating Lymphocytes; United States; United States National Institutes of Health; Universities; Validation; Visual; Woman; Work; advanced disease; behavioral outcome; chemoradiation; chemotherapy; cohort; collaborative trial; companion diagnostics; computerized; cost; density; diagnostic tool; digital; digital imaging; high risk; high risk population; improved; innovation; lymphatic Invasion; malignant mouth neoplasm; men; mouth squamous cell carcinoma; neoplastic cell; outcome prediction; patient prognosis; patient stratification; perineural; precision medicine; predict clinical outcome; predictive marker; predictive test; prognostic; prognostic assays; prognostic of survival; prognostication; progression risk; prospective; risk stratification; success; targeted treatment; tool; treatment choice; tumor; tumor behavior

SUMMARY: In 2018, nearly 34,000 adults in the US and over 275,000 worldwide were diagnosed with oral cavity squamous cell carcinoma (OC-SCC). In the US alone >6,600 died from the disease in 2018. In addition to stage, perineural invasion, lymphovascular invasion, depth of invasion, and close or frankly positive resection margins are used to help stratify patients into low-, intermediate-, or high risk categories. Currently, all OC-SCC patients are treated primarily by surgical resection. Post-operative treatment depends on patient risk category. Low-risk patients receive surgery alone and studies have shown the benefit of PORT (Post-operative radiation therapy) in selected patients. A retrospective analysis of 1467 patients with low-risk OC-SCC where 740 (50.4%) received PORT had improved overall survival compared to 727 patients treated with surgery alone. Identifying these patients and better stratifying their risk of progression is critical. Meanwhile, patients with loco-regionally advanced (i.e. intermediate and high risk) disease are treated with PORT as standard. Select high risk patients may be treated with concomitant chemoradiation or subsequent chemotherapy. There is thus an urgent need to develop companion diagnostic tools to better define which patients will benefit from PORT, or, if intermediate or high risk, who will benefit from systemic therapy intensification. Recently, our group has developed a OC-SCC histomorphometric based image risk classifier (OHbIC) that uses computerized measurements of nuclear orientation, texture, shape, architecture from digital images of H&E-stained tumor sections to identify patients who are likely to recur versus those who are not. OHbIC was trained and validated on N=115 OC-SCC patients, and it had a 2 and 7-fold higher-correlation with disease specific survival compared to the 7th edition AJCC N- and T-stage (clinical variables used in patient prognosis). In this NIH R01, we seek to further improve the prognostic and predictive accuracy of OHbIC by incorporating new classes of image features relating to stromal morphology, pattern of invasion at the tumor leading edge, density and patterns of tumor infiltrating lymphocytes, and tumor cell multi-nucleation, features now recognized as potential histopathological markers of prognostic relevance in OC-SCC. Additionally, we seek to 1) validate OHbIC as prognostic of survival in clinically defined low-risk patients and identify those low-risk patients who would benefit from PORT and 2) validate OHbIC as not only prognostic of survival but also predictive of benefit from chemotherapeutic intensification for patients with loco-regionally advanced disease. This partnership will leverage long-standing collaborations in (1) digital pathomics from the Madabhushi group at Case Western Reserve, (2) surgical pathology and oncology expertise in oral cancer from Vanderbilt University, Cleveland Clinic, San Francisco VA, and Tata Memorial Centre, Mumbai to establish OHbIC as a tissue non-destructive and Affordable Precision Medicine (APM) solution for OC-SCC patients.

摘要：2018 年，美国近 34,000 名成年人和全球超过 275,000 名成年人被诊断患有口腔疾病 鳞状细胞癌（OC-SCC）。 2018 年，仅在美国就有超过 6,600 人死于该疾病。除了分期之外， 神经周围浸润、淋巴管浸润、浸润深度以及紧密或明显阳性的切除边缘 用于帮助将患者分为低、中或高风险类别。目前，所有 OC-SCC 患者 主要通过手术切除来治疗。术后治疗取决于患者的风险类别。低风险 患者仅接受手术，研究表明 PORT（术后放射治疗）的益处 在选定的患者中。对 1467 名低危 OC-SCC 患者的回顾性分析，其中 740 名 (50.4%) 接受了治疗 与 727 名仅接受手术治疗的患者相比，PORT 改善了总体生存率。识别这些 患者并更好地分层他们的进展风险至关重要。与此同时，局部区域患者 晚期（即中度和高风险）疾病以 PORT 作为标准治疗。选择高风险患者 可以同时进行放化疗或随后的化疗。因此迫切需要 开发伴随诊断工具，以更好地确定哪些患者将从 PORT 中受益，或者，如果是中间或 高风险，谁将从强化全身治疗中受益。 最近，我们组开发了一种基于OC-SCC组织形态计量学的图像风险分类器（OHbIC） 它使用来自数字图像的核取向、纹理、形状、结构的计算机测量 对肿瘤切片进行 H&E 染色，以识别可能复发的患者和不会复发的患者。 OHbIC 为 在 N=115 名 OC-SCC 患者上进行了训练和验证，与疾病的相关性分别提高了 2 倍和 7 倍 与第七版 AJCC N 和 T 分期（用于患者预后的临床变量）相比的特定生存率。 在此 NIH R01 中，我们寻求通过结合以下内容进一步提高 OHbIC 的预后和预测准确性： 与基质形态、肿瘤前缘侵袭模式相关的新类别图像特征， 肿瘤浸润淋巴细胞的密度和模式以及肿瘤细胞多核，这些特征现已得到认可 作为 OC-SCC 预后相关的潜在组织病理学标志物。此外，我们寻求 1) 验证 OHbIC 作为临床定义的低风险患者的生存预后，并确定那些低风险患者 将从 PORT 中受益，并且 2) 验证 OHbIC 不仅可以预测生存，还可以预测获益 来自局部区域晚期疾病患者的强化化疗。 此次合作将利用 Madabhushi 在 (1) 数字病理学方面的长期合作 凯斯西储大学团队，(2) 范德比尔特口腔癌的外科病理学和肿瘤学专业知识 大学、弗吉尼亚州旧金山克利夫兰诊所和孟买塔塔纪念中心将建立 OHbIC 作为 为 OC-SCC 患者提供组织无损且经济实惠的精准医疗 (APM) 解决方案。