Novel Image-Based Screening of Mammary Tumors

基于图像的新型乳腺肿瘤筛查

• 批准号: 7489517
• 负责人: David W. Knowles
• 金额: $ 29.36万
• 依托单位: UNIVERSITY OF CALIF-LAWRENC BERKELEY LAB
• 依托单位国家: 美国
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-09-27 至 2011-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7489517
• 关键词: Automation; Award; Behavior; Benign; Biological Markers; Biopsy; Breast; Breast Cancer Early Detection; Cancer Patient; Cancer Research Project; Cell Nucleus; Cell physiology; Cells; Characteristics; Chromatin; Class; Classification; Clinical; Cluster Analysis; Core Biopsy; Cultured Cells; Department of Defense; Detection; Disease; Epigenetic Process; Epithelial; Epithelial Cells; Epithelium; Future; Gene Expression; Goals; Health Benefit; Heterochromatin; Histological Techniques; Histones; Histopathology; Human; Human Mammary Epithelium; Image; Image Analysis; Individual; Interdisciplinary Study; Invasive; Lesion; Lysine; Malignant - descriptor; Malignant Neoplasms; Mammary Gland Parenchyma; Mammary Neoplasms; Mammary gland; Mammography; Maps; Measures; Methodology; Methods; Mitotic Spindle Apparatus; Modeling; Molecular; Morphology; Needles; Normal Cell; Nuclear; Nuclear Protein; Nuclear Proteins; Operative Surgical Procedures; Pathologist; Patients; Phase; Phenotype; Play; Population; Population Heterogeneity; Premalignant; Process; Proteins; Public Health; Range; Reporting; Research; Research Personnel; Resolution; Risk; Role; Screening procedure; Shapes; Staging; Staining method; Stains; Statistical Methods; Structure; System; Techniques; Technology; Testing; Tissues; Universities; Variant; Work; base; cancer cell; fluorescence imaging; follow-up; human CCDC6 protein; malignant breast neoplasm; malignant phenotype; mixed cell culture; neoplastic; novel; programs; size; tool; tumor

DESCRIPTION (provided by applicant): Breast tumors are detected by self exam, clinical exam, and mammogram and suspicious lesions are biopsied. The ensuing histological classification plays a determining role in the treatment decision but the associated risk of malignancy, the appropriate treatment, and the risk of reoccurrence are difficult to determine. As a consequence, patient treatment is based on epidemiological findings rather than individual needs. Non- invasive imaging provides some information but early breast cancer detection by routine screening is not currently feasible. However, once a tumor has been detected and biopsied, there is urgent need for novel methods to aid in the detection and classification of sub-classes of lesions. One key epigenetic marker of cell phenotype is the organization of nuclear proteins which direct and reflect normal cell function. Based on the hypothesis that the redistribution of chromatin-related proteins reflects changes in gene expression that accompany alterations in cell phenotype, we have developed image analysis methodologies to quantify the nuclear distribution of specific chromatin-associated proteins from three-dimensional, high-resolution, fluorescently immunostained images. By applying these methods to culture models that mimic normal and malignant breast epithelial tissue, we have demonstrated that the distribution of nuclear mitotic apparatus protein (NuMA) and heterochromatin related protein histone-4 methylated on lysine-20 (H4-K20m) are biomarkers capable of clearly distinguishing non-neoplastic and malignant human mammary epithelial cells. The goal of this project is to quantify the distribution of specific nuclear proteins in culture models that mimic premalignant and malignant tissue to uncover epigenetic characteristics of premalignant disease. Our image-based methodologies will be expanded to produce a novel technique, the phenotype tissue-map, capable of resolving local tissue phenotype at cellular resolution and uncovering subtle differences in tissue morphology and behavior. The technology, which will work alongside the usual H&E staining and histological techniques, will be tested on needle-core biopsies of a variety of premalignant tumors with the aim of defining sub-classes of graded lesions. The results will be correlated with the histopathology of the initial needle-core and the follow-up surgical biopsy with the hope of predicting more aggressive phenotypes missed by the initial screen. The future public health benefit of this research is to aid the treatment decision process of breast cancer patients. By better understanding the organization of molecular components within the cell and how the organization of these components is altered during the progression to cancer, we can develop and provide pathologists with novel image analysis tools to aid and support the histological classification of biopsied breast tissue.

描述（由申请人提供）：通过自我检查、临床检查和乳房X光检查检测乳腺肿瘤，并对可疑病变进行活检。随后的组织学分类在治疗决策中起决定性作用，但相关的恶性肿瘤风险、适当的治疗和复发风险难以确定。 因此，病人的治疗是基于流行病学的调查结果，而不是个人的需要。非侵入性成像提供了一些信息，但通过常规筛查进行早期乳腺癌检测目前尚不可行。然而，一旦肿瘤被检测和活检，就迫切需要新的方法来帮助检测和分类病变的亚类。细胞表型的一个关键表观遗传标记是指导和反映正常细胞功能的核蛋白的组织。基于染色质相关蛋白的重新分布反映了伴随细胞表型改变的基因表达变化的假设，我们开发了图像分析方法，以从三维，高分辨率，荧光免疫染色图像中量化特定染色质相关蛋白的核分布。通过将这些方法应用于模拟正常和恶性乳腺上皮组织的培养模型，我们已经证明了核有丝分裂器蛋白（NuMA）和赖氨酸-20（H4-K20 m）上甲基化的异染色质相关蛋白组蛋白-4（H4-K20 m）的分布是能够清楚地区分非肿瘤性和恶性人类乳腺上皮细胞的生物标志物。该项目的目标是量化模拟癌前和恶性组织的培养模型中特定核蛋白的分布，以揭示癌前疾病的表观遗传特征。我们的基于图像的方法将被扩展到产生一种新的技术，表型组织图，能够解决局部组织表型在细胞分辨率和揭示组织形态和行为的细微差异。 该技术将与通常的H&E染色和组织学技术一起工作，将在各种癌前肿瘤的针芯活检中进行测试，目的是定义分级病变的亚类。结果将与初始针芯的组织病理学和后续手术活检相关，希望预测初始筛选遗漏的更具侵袭性的表型。这项研究的未来公共卫生效益是帮助乳腺癌患者的治疗决策过程。通过更好地了解细胞内分子组分的组织以及这些组分的组织在癌症进展过程中如何改变，我们可以开发并为病理学家提供新的图像分析工具，以帮助和支持活检乳腺组织的组织学分类。

项目成果

Phenotype clustering of breast epithelial cells in confocal images based on nuclear protein distribution analysis.

• DOI: 10.1186/1471-2121-8-s1-s3
• 发表时间: 2007-07-10
• 期刊: BMC CELL BIOLOGY
• 作者: Long, Fuhui;Peng, Hanchuan;Sudar, Damir;Lelievre, Sophie A.;Knowles, David W.
• 通讯作者: Knowles, David W.