Multimodal Biomarkers For Oropharyngeal Cancer

口咽癌的多模式生物标志物

• 批准号: 10453653
• 负责人: Hua Li
• 金额: $ 38.23万
• 依托单位: WASHINGTON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-02-01 至 2024-11-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10453653
• 关键词: Achievement; Automobile Driving; Biological Markers; Cancer Patient; Cancer Prognosis; Clinical; Clinical Treatment; Code; Computer Models; Data; Decision Making; Dimensions; Disease; Disease Progression; Family; Future; Genes; Genetic; Goals; HPV oropharyngeal cancer; Habitats; Head and Neck Cancer; Heterogeneity; Human Papillomavirus; Image; Imaging Techniques; Incidence; International; Machine Learning; Medical Imaging; Methodology; MicroRNAs; Modeling; Nature; Oncogenic; Oropharyngeal Neoplasms; Oropharyngeal Squamous Cell Carcinoma; Outcome; Patients; Phenotype; Play; Prognosis; Prognostic Marker; Proteins; Research; Retrospective Studies; Risk; Role; Site; Survival Rate; Techniques; Testing; Therapeutic; Treatment Failure; Treatment outcome; Uncertainty; United States; Untranslated RNA; Validation; Variant; biomarker identification; cancer biomarkers; cancer epidemiology; cancer therapy; cancer type; clinical application; clinical biomarkers; clinical decision-making; clinically relevant; cohort; effective therapy; high dimensionality; high risk; imaging biomarker; improved; individualized medicine; malignant oropharynx neoplasm; microRNA biomarkers; mortality risk; multimodality; non-invasive imaging; novel; outcome prediction; patient biomarkers; patient prognosis; patient stratification; patient subsets; precision oncology; predictive modeling; prognostic; prognostic model; prognostic value; response; tool; treatment strategy; tumor

Abstract Head and neck cancers are the fifth most common cancer type in the United States, with an overall survival rate lower than 50%. Although the incidence of other sub-sites of head and neck cancer has decreased steadily in past decades, the number of oropharyngeal squamous cell carcinoma (OPSCC) cases has increased significantly. Most OPSCC patients receive standard cancer therapy.4 However, the clinical outcomes vary significantly and are difficult to predict. Predicting early in treatment whether a tumor is likely to respond to treatment is one of the most difficult yet important tasks in providing individualized cancer care. Human papillomavirus (HPV) is a known driving oncogenic factor in oropharyngeal cancer, as well as a significant prognostic biomarker for patient survival. Retrospective studies conducted by the International Head and Neck Cancer Epidemiology Consortium (INHANCE) have demonstrated that clinical biomarkers have prognostic value in helping stratify OPSCC patients into groups with differing risks of death or disease progression. However, HPV-positive oropharyngeal cancer patients have similar rates of metastatic spread to HPV-negative patients. The same is true for patient groups stratified with other clinical biomarkers. More robust prognostic biomarkers are needed to accurately stratify patients for optimally effective treatment. MicroRNAs (miRNAs) are a family of small non-coding RNA molecules that collectively control the expression of thousands of protein-coding genes. Multiple studies indicate that miRNAs are promising cancer biomarkers and play critical regulatory roles in oropharyngeal cancer. Imaging features extracted from medical images are an exciting new class of cancer biomarkers for characterizing tumor habitats. For several tumor sites, imaging biomarkers have shown promise in accurately separating favorable and unfavorable prognosis patients. However, current efforts to utilize high-dimensional multimodal biomarkers for treatment outcome prediction have been compromised by small patient numbers relative to the feature space dimensionality; feature redundancy, heterogeneity, and uncertainty; and patient cohorts with unbalanced outcomes. The correlation, independence, and complementary nature of multimodal biomarkers (imaging, miRNA, HPV, clinical, and histopathologic biomarkers) remains unexplored as well. The major goal of this research is to develop a multimodal biomarker-based model that can reliably predict subsets of OPSCC patients with low and high risks for treatment failure. The model will serve as a clinical decision-making tool. Specifically, we propose a novel principle and systematic machine learning-based strategy to effectively identify and seamlessly combine prognostic information carried by multimodal biomarkers. Aim 1: Identify prognostic multimodal biomarkers, given OPSCC patient data. Aim 2: Develop and test a comprehensive multimodal biomarker-based model for predicting OPSCC treatment outcomes. Aim 3: Assess the clinical benefit of the model for OPSCC patient stratification and individualized treatment.

抽象的 头颈癌是美国第五大常见癌症类型，总体生存率 率低于50%。尽管头颈癌其他亚部位的发病率有所下降 过去几十年来，口咽鳞状细胞癌（OPSCC）病例数量稳步增长 显着增加。大多数 OPSCC 患者接受标准癌症治疗。4 然而，临床 结果差异很大且难以预测。在治疗早期预测肿瘤是否可能 对治疗的反应是提供个体化癌症护理中最困难但最重要的任务之一。 人乳头瘤病毒 (HPV) 是口咽癌的已知驱动致癌因素，也是一种 患者生存的重要预后生物标志物。国际主管进行的回顾性研究 和颈癌流行病学联盟 (INHANCE) 已证明临床生物标志物已 帮助将 OPSCC 患者分为具有不同死亡或疾病风险的组的预后价值 进展。然而，HPV 阳性口咽癌患者的转移扩散率与 HPV 阴性患者。对于用其他临床生物标志物分层的患者组也是如此。更坚固 需要预后生物标志物来准确对患者进行分层，以获得最佳有效的治疗。 MicroRNA (miRNA) 是一类小非编码 RNA 分子，共同控制 数千个蛋白质编码基因的表达。多项研究表明 miRNA 有望用于癌症治疗 生物标志物并在口咽癌中发挥关键的调节作用。从医学中提取的成像特征 图像是一类令人兴奋的新型癌症生物标志物，用于表征肿瘤栖息地。对于多种肿瘤 地点，成像生物标志物已显示出准确区分有利和不利预后的希望 患者。然而，目前利用高维多模式生物标志物来治疗结果的努力 相对于特征空间维度而言，患者数量较少会影响预测； 特征冗余、异质性和不确定性；以及结果不平衡的患者群体。这 多模式生物标志物（成像、miRNA、HPV、 临床和组织病理学生物标志物）也仍未得到探索。 这项研究的主要目标是开发一种基于多模式生物标记的模型，可以可靠地预测 治疗失败风险低和高的 OPSCC 患者亚群。该模型将作为临床 决策工具。具体来说，我们提出了一种新颖的原理和系统的基于机器学习的 有效识别并无缝组合多模式携带的预后信息的策略 生物标志物。目标 1：根据 OPSCC 患者数据确定预后多模式生物标志物。目标 2：开发和 测试基于多模态生物标志物的综合模型来预测 OPSCC 治疗结果。目标 3： 评估 OPSCC 患者分层和个体化治疗模型的临床益处。