Determining the impact of ancestry on oropharyngeal cancer biology and treatment response.

确定血统对口咽癌生物学和治疗反应的影响。

• 批准号: 10562456
• 负责人: GERMAN CORREDOR
• 金额: $ 26.32万
• 依托单位: BAYLOR COLLEGE OF MEDICINE
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-07-01 至 2025-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10562456
• 关键词: Address; African American; Biological; Cancer Biology; Cancer Patient; Characteristics; Classification; Clinical; Clinical Data; County Hospitals; Data; Data Set; Development; Disease; Disparity; Environmental Exposure; Equity; Exhibits; Frequencies; Gene Expression Profile; Genes; Genomics; Head and Neck Cancer; Health Services Accessibility; Human Papilloma Virus-Related Malignant Neoplasm; Human Papillomavirus; Immune checkpoint inhibitor; Inferior; Institution; Integration Host Factors; Link; Machine Learning; Malignant Neoplasms; Malignant neoplasm of cervix uteri; Malignant neoplasm of urinary bladder; Measures; Medical center; Metastatic/Recurrent; Molecular Analysis; Outcome; Patient Self-Report; Patients; Physicians; Population; Pre-Clinical Model; Progression-Free Survivals; Publishing; Race; Regional Cancer; Reproducibility; Risk; Single Nucleotide Polymorphism; Smoker; Smoking; Smoking History; Societies; Spatial Distribution; Specimen; T-cell inflamed; Testing; Time; Tissue-Specific Gene Expression; Tobacco; Tumor Biology; Tumor-Infiltrating Lymphocytes; United States; United States Department of Veterans Affairs; Validation; advanced disease; behavioral response; cancer care; cancer diagnosis; cancer survival; cancer therapy; care delivery; clinical translation; cohort; conventional therapy; design; differential expression; disparity reduction; effective therapy; high throughput analysis; histological slides; improved; malignant oropharynx neoplasm; neoplastic cell; non-smoker; novel; patient population; precision oncology; racial disparity; response; socioeconomics; standard of care; transcriptomics; treatment response; tumor; tumor-immune system interactions; tumorigenesis; Address; African American; Biological; Cancer Biology; Cancer Patient; Characteristics; Classification; Clinical; Clinical Data; County Hospitals; Data; Data Set; Development; Disease; Disparity; Environmental Exposure; Equity; Exhibits; Frequencies; Gene Expression Profile; Genes; Genomics; Head and Neck Cancer; Health Services Accessibility; Human Papilloma Virus-Related Malignant Neoplasm; Human Papillomavirus; Immune checkpoint inhibitor; Inferior; Institution; Integration Host Factors; Link; Machine Learning; Malignant Neoplasms; Malignant neoplasm of cervix uteri; Malignant neoplasm of urinary bladder; Measures; Medical center; Metastatic/Recurrent; Molecular Analysis; Outcome; Patient Self-Report; Patients; Physicians; Population; Pre-Clinical Model; Progression-Free Survivals; Publishing; Race; Regional Cancer; Reproducibility; Risk; Single Nucleotide Polymorphism; Smoker; Smoking; Smoking History; Societies; Spatial Distribution; Specimen; T-cell inflamed; Testing; Time; Tissue-Specific Gene Expression; Tobacco; Tumor Biology; Tumor-Infiltrating Lymphocytes; United States; United States Department of Veterans Affairs; Validation; advanced disease; behavioral response; cancer care; cancer diagnosis; cancer survival; cancer therapy; care delivery; clinical translation; cohort; conventional therapy; design; differential expression; disparity reduction; effective therapy; high throughput analysis; histological slides; improved; malignant oropharynx neoplasm; neoplastic cell; non-smoker; novel; patient population; precision oncology; racial disparity; response; socioeconomics; standard of care; transcriptomics; treatment response; tumor; tumor-immune system interactions; tumorigenesis

ABSTRACT Oropharyngeal cancer (OPC) is now the most common malignancy of the head and neck region, and OPC associated with the human papillomavirus (HPV) has overtaken cervical cancer as the most common HPV- associated malignancy in the United States. African American (AA) patients demonstrate inferior OPC oncologic outcomes to their non-AA counterparts even when adjusting for HPV effect. It is not known whether reduced treatment response and survival in AA OPC patients is driven solely by unequitable access to care and other socio-economic variables or whether it is impacted at least partially by the interaction between ancestry and cancer biology. No previous study has addressed this question using an adequate OPC clinical dataset with correlative genomic and transcriptomic data in order to address this translationally important question. Therefore, it is not possible to determine whether OPC treatment response and survival in AA patients is partially linked to differential tumor biology using existing datasets. In this application, we will utilize two unique OPC cohorts enriched for AA patients to test the hypothesis that OPC development in AA patients is accompanied by more aggressive tumor biology facilitated by an immunosuppressive tumor immune microenvironment (TIME). In Aim 1 we will correlate self-reported race and calculated ancestry to intrinsic OPC tumor biology and treatment response. Specifically, we will test the correlation between tumor cell multi-nucleation (a feature of aggressive OPC biology recently validated by our team in a multi-institutional OPC cohort), survival, and differential gene expression in AA OPC patients matched to their non-AA counterparts for T classification, HPV status, and smoking history. In Aim 2 we will correlate self- reported race and calculated ancestry to changes in TIME and treatment response in previously untreated AA OPC patients as well as immune checkpoint inhibitor response in AA OPC patients with recurrent/metastatic disease. For both sets of analyses, we will deploy novel, validated machine learning approaches to analysis of conventional histologic slides designed to facilitate rapid clinical translation across multiple other institutions. Completion of the proposed studies will, for the first time, establish the link between race/ancestry, OPC biological behavior, and treatment response. Successful validation of our hypothesis will provide a unique opportunity for the development of precision oncology approaches to AA OPC management aimed at reversing the disparities noted in cancer specific survival for this understudied patient population.

抽象的 口咽癌（OPC）现在是头颈部最常见的恶性肿瘤， 与人乳头瘤病毒（HPV）相关的OPC已超过宫颈癌，是最常见的HPV- 在美国相关的恶性肿瘤。非裔美国人（AA）患者表现出较低的OPC肿瘤学 即使调整了HPV效应，即使其非AA的结果也是如此。尚不清楚是否减少 AA OPC患者的治疗反应和生存仅由不平等的获得护理和其他驱动 社会经济变量，还是至少部分受祖先相互作用的影响 癌症生物学。以前没有研究使用足够的OPC临床数据集解决了这个问题 相关基因组和转录组数据，以解决这个翻译重要的问题。所以， 无法确定AA患者的OPC治疗反应和生存是否部分相关 使用现有数据集的差异肿瘤生物学。 在此应用程序中，我们将利用两个富含AA患者的独特的OPC队列来检验假设 AA患者的OPC发育伴随着更具侵略性的肿瘤生物学 免疫抑制肿瘤免疫微环境（时间）。在AIM 1中，我们将与自我报告的种族相关联 计算了固有的OPC肿瘤生物学和治疗反应的血统。具体来说，我们将测试 肿瘤细胞多核之间的相关性（侵略性OPC生物学的特征最近通过我们的 在AA OPC患者中，在多机构OPC队列中的团队，生存和差异基因表达匹配 与他们的非AA对应物进行T分类，HPV状态和吸烟史。在AIM 2中，我们将使自我关联 报告的种族和计算的祖先是以前未经治疗的AA的时间和治疗响应的变化 AA反复/转移性AA OPC患者的OPC患者以及免疫检查点抑制剂反应 疾病。对于两组分析，我们将部署新颖的，经过验证的机器学习方法来分析 常规的组织学载玻片旨在促进其他多个机构的快速临床翻译。 拟议研究的完成将首次建立种族/祖先之间的联系 生物行为和治疗反应。成功验证我们的假设将提供独特的 开发精确肿瘤学方法的机会，旨在逆转 该研究不足的患者人群的癌症特异性生存中指出的差异。