Project 3: Inter-Relationships and Prognostic Significance of Breast Cancer Radiomic Risk Features, Tissue Microenvironment, and Adiposity

项目 3：乳腺癌放射风险特征、组织微环境和肥胖的相互关系和预后意义

• 批准号: 10716156
• 负责人: JOHN Alan SHEPHERD
• 金额: $ 29.07万
• 依托单位: UNIVERSITY OF HAWAII AT MANOA
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-19 至 2026-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10716156
• 关键词: 3-Dimensional; Abdomen; Adipose tissue; American; Architecture; Artificial Intelligence; Asian Americans; Biological Assay; Biological Markers; Blood; Body fat; Body mass index; Breast; Breast Cancer Model; Breast Cancer Patient; Breast Cancer Risk Factor; Breast Cancer gene; CD36 gene; CD8B1 gene; Calibration; Cancer Prognosis; Cd68; Cessation of life; Characteristics; Chinese; Clinical Markers; Cohort Studies; Disease; Disparity; ERBB2 gene; Early Diagnosis; Early treatment; Estrogen Receptors; Estrogens; Ethnic Origin; Ethnic Population; Evaluation; Fatty acid glycerol esters; Gene Expression Profile; Goals; Hawaii; Health; High Risk Woman; Image; Incidence; Japan; Japanese; Japanese American; Joints; Link; Machine Learning; Mammary Neoplasms; Mammographic Density; Mammographic screening; Mammography; Measures; Mediating; Minority; Minority Women; Molecular; Morbidity - disease rate; Native Hawaiian; Native Hawaiian or Other Pacific Islander; Obesity; Organ; Outcome; Pacific Islands; Participant; Pathology; Pattern; Personal Satisfaction; Phenotype; Population; Population Sciences; Postmenopause; Prevention; Primary Prevention; Progesterone Receptors; Prognosis; Race; Reporting; Research; Residual state; Resources; Risk; Risk Factors; Source; Subgroup; Survival Analysis; Therapeutic; Tissue Banks; Tissues; Translating; Tumor Markers; Visceral; Visceral fat; Visit; Woman; ZNF217 gene; anticancer research; breast cancer survival; breast density; breast imaging; cancer health disparity; cancer survival; clinically relevant; cohort; comparative; deep learning; ethnic difference; ethnic minority; experience; genetic risk factor; hormone receptor-positive; imaging biomarker; improved; individualized medicine; malignant breast neoplasm; mammography registry; migration; minority health; minority health disparity; modifiable risk; molecular modeling; molecular subtypes; mortality; multi-ethnic; nano-string; prognostic; prognostic model; prognostic significance; protein biomarkers; public health relevance; racial difference; racial diversity; racial population; radiomics; reproductive; risk prediction model; screening; subcutaneous; tissue biomarkers; tumor; tumor registry; virtual

SUMMARY / ABSTRACT The risk of breast cancer among U.S. women dramatically differs across racial and ethnic populations. Nonetheless, Asian American and Native Hawaiian/Pacific Islander (AANHPI) ethnic minority women have been historically underrepresented in breast cancer research. Consequently, there are major gaps in understanding the basis of disparities in these populations including high incidence and mortality among Native Hawaiians and a steadily rising incidence with comparatively favorable outcomes among Japanese Americans. Obesity and breast density, established breast cancer risk factors, vary widely across AANHPI women and have direct implications for mammographic screening and primary prevention. Our research to date provides strong evidence that body fat distribution, including visceral adipose tissue (VAT), is an important predictor of breast cancer risk. The influence of adiposity on breast density and other aspects of breast architecture that can be discerned through mammographic screening (e.g. radiomic features) is not well understood. Our long-term goal is to elucidate the breast cancer disparities seen in understudied minority AANHPI subgroups (Native Hawaiian, Micronesian, Japanese, Chinese, Filipina) that can be translated to improved prevention, early detection, and therapeutic strategies. Our central hypothesis is that established radiomic risk features have unique associations with breast cancer incidence in AANHPI subgroups and that they are correlated with tissue biomarkers of risk and prognosis and with obesity, especially VAT. Study resources include the statewide Hawai`i Pacific Islands Mammography Registry linked to the SEER Hawai`i Tumor Registry and its Residual Tissue Repository (RTR), and to the Hawai`i component of the Multiethnic Cohort Study (MEC). Our study is focused on the minority health of AANHPI, with the following aims: 1) Characterize the relationships of established breast imaging radiomic risk features with tissue protein biomarker expression profiles reflecting the tissue microenvironment and breast cancer prognosis and with disease-specific survival; 2) Characterize the joint relationships of breast radiomic risk features and different measures of adiposity, including VAT, with post-menopausal breast cancer risk among Native Hawaiian, Japanese American, and White MEC participants. 3) Calibrate commonly used risk prediction models for breast cancer by including established breast radiomic (AI and machine learning) risk features from 2D and 3D mammography in AAPHI and White women overall and by estrogen/progesterone receptor and HER-2 status. The expected outcome of the proposed study is to further our understanding of unique relationships between imaging biomarkers derived from advanced machine learning approaches and race/ethnicity, tissue molecular characteristics and adiposity phenotypes, which will improve risk and prognosis model accuracy and better identify high risk women for further assessment or tailored therapy.

总结/摘要 美国女性患乳腺癌的风险在种族和民族人群中有很大差异。 尽管如此，亚裔美国人和夏威夷土著/太平洋岛民（AANHPI）少数民族妇女一直受到歧视， 在乳腺癌研究中的代表性历来不足。因此，在理解方面存在重大差距， 这些人群的差异，包括夏威夷土著人的高发病率和死亡率， 日裔美国人的发病率稳步上升，结果相对有利。肥胖和 乳腺密度，确定的乳腺癌危险因素，在AANHPI妇女中差异很大， 对乳腺X线筛查和初级预防的影响。我们迄今为止的研究提供了强大的 有证据表明，包括内脏脂肪组织（VAT）在内的体脂分布是乳腺癌的重要预测因素。 癌症风险。肥胖对乳房密度和乳房结构的其他方面的影响， 通过乳房X线摄影筛查辨别的乳房X线特征（例如，放射组学特征）还没有被很好地理解。我们的长期目标 是为了阐明在未充分研究的少数AANHPI亚组（夏威夷土著人， 印度尼西亚语、日语、汉语、菲律宾语），可以转化为更好的预防、早期发现和 治疗策略我们的中心假设是，已建立的放射组学风险特征具有独特的 与AANHPI亚组中乳腺癌发病率的相关性及其与组织相关 风险和预后的生物标志物和肥胖，特别是VAT。研究资源包括全州 夏威夷太平洋岛屿乳腺X线摄影登记处链接到SEER夏威夷肿瘤登记处及其残留 组织储存库（RTR）和多种族队列研究（MEC）的夏威夷组成部分。我们的研究是 重点关注AANHPI的少数群体健康，目标如下：1）描述 建立乳腺成像放射组学风险特征，组织蛋白生物标志物表达谱反映 组织微环境与乳腺癌预后及与疾病特异性生存的关系; 2）表征 乳腺放射学风险特征和不同肥胖指标（包括VAT）与 夏威夷原住民、日裔美国人和白色MEC中绝经后乳腺癌风险 参与者3)校准常用的乳腺癌风险预测模型， AAPHI和白色人群中2D和3D乳腺X射线摄影的乳腺放射组学（AI和机器学习）风险特征 女性总体和雌激素/孕激素受体和HER-2状态。的预期成果 拟议的研究是为了进一步了解成像生物标志物之间的独特关系， 从先进的机器学习方法和种族/民族，组织分子特征和肥胖 表型，这将提高风险和预后模型的准确性，并更好地识别高风险妇女，以进一步 评估或定制治疗。