Collagen structural changes as an early biomarker for breast carcinoma

胶原蛋白结构变化作为乳腺癌的早期生物标志物

• 批准号: 9344562
• 负责人: Matthew W Conklin
• 金额: $ 43.11万
• 依托单位: UNIVERSITY OF WISCONSIN-MADISON
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-01 至 2020-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9344562
• 关键词: Address; Adoption; Age; Archives; Aspirate substance; Attention; Benign; Biological Markers; Biometry; Biopsy; Breast; Breast Cancer Detection; Breast Carcinoma; Breast Diseases; Cells; Clinical; Collagen; Collagen Fiber; Computer software; Data; Deposition; Diagnosis; Disease; Disease Progression; Early Diagnosis; Epithelial Cells; Extracellular Matrix; Fiber; Freezing; Future; Generations; Gland; Global Change; Glycoproteins; Goals; Heterogeneity; Image; Image Analysis; Image Guided Biopsy; Incidence; Knowledge; Length; Lesion; Life; Link; Machine Learning; Malignant Neoplasms; Mammary Gland Parenchyma; Mammographic Density; Mammography; Mass Spectrum Analysis; Measures; Menopause; Microscopy; Needles; Noise; Noninfiltrating Intraductal Carcinoma; Normal Range; Normal tissue morphology; Patient-Focused Outcomes; Patients; Physicians; Post-Translational Protein Processing; Procedures; Proteins; Proteomics; Recurrence; Risk; Risk Marker; Roentgen Rays; Sampling; Screening for cancer; Signal Transduction; Slide; Staining method; Stains; Statutes and Laws; Stromal Neoplasm; Structure; Techniques; Time; Tissue Banks; Tissue Sample; Tissues; Width; Woman; base; breast density; breast surgery; cohort; density; experimental study; high risk; imaging biomarker; improved; indexing; malignant breast neoplasm; milk secretion; minimally invasive; mortality; non-invasive imaging; obesity risk; outcome prediction; population health; protein expression; public health relevance; scaffold; screening; second harmonic; second harmonic generation imaging; support network; tumor; tumor microenvironment; tumor progression; volunteer

 DESCRIPTION (provided by applicant): We propose that collagen features, such as alignment, fiber straightness and width, and other features of extracellular matrix composition can be used as an early biomarker of breast cancer. It is the goal of this proposal to determine the range of collagen structural features that characterize normal, benign and early disease, to determine how these features relate to mammographic density, and to identify the features that best predict risk, recurrence, and progression. This proposal leverages a diverse collaborative team that includes experts in imaging and understanding the tumor microenvironment, breast surgery, experts in population health and biostatistics, and an expert in proteomic analysis of the ECM. This team will analyze a set of patient cohorts to develop imaging and analysis of collagen structure and ECM composition as a potential early biomarker for breast cancer. Aims: 1) Characterize collagen features that define heterogeneity of the normal state. 2) Characterize collagen features in pre- and early breast cancer lesions. 3) Characterize the proteomics of biopsies representing benign, at risk, and invasive breast cancer. Significance: This project meets the goals of the RFA to develop and validate combined imaging and biomarker approaches to improve early cancer detection and the diagnosis of early-stage cancers. Our findings have the potential to reduce overdiagnosis and false positives and discern lethal from non-lethal disease.

 描述（由申请人提供）：我们建议胶原蛋白特征，例如排列、纤维直线度和宽度，以及细胞外基质成分的其他特征可以用作乳腺癌的早期生物标志物。该提案的目标是确定表征正常、良性和早期疾病的胶原蛋白结构特征的范围，确定这些特征与乳房X线照相密度的关系，并确定最能预测风险、复发和进展的特征。该提案利用了多元化的协作团队，其中包括肿瘤微环境成像和理解、乳腺外科专家、人口健康和生物统计学专家以及 ECM 蛋白质组分析专家。该团队将分析一组患者队列，以开发胶原蛋白结构和 ECM 成分的成像和分析，作为乳腺癌的潜在早期生物标志物。目的： 1) 表征定义正常状态异质性的胶原蛋白特征。 2) 表征乳腺癌前期和早期病变中的胶原蛋白特征。 3) 表征良性、高风险和浸润性乳腺癌活检组织的蛋白质组学特征。意义：该项目实现了 RFA 的目标，即开发和验证联合成像和生物标志物方法，以改善早期癌症检测和早期癌症诊断。我们的研究结果有可能减少过度诊断和误报，并区分致命疾病和非致命疾病。