Molecular Pathology Research for Cancer Diagnostics and Biomarkers

癌症诊断和生物标志物的分子病理学研究

• 批准号: 9154300
• 负责人: Robert Simpson
• 金额: $ 133万
• 依托单位: DIVISION OF BASIC SCIENCES - NCI
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/9154300
• 关键词: Address; Algorithms; Animal Model; Applied Research; Area; Attention; Automated Pattern Recognition; BRAF gene; Benign; Biological Assay; Biological Markers; Biological Models; Cancer Diagnostics; Cancer Model; Canis familiaris; Cells; Characteristics; Client; Clinical; Collection; Comprehension; Cutaneous Melanoma; Development; Diagnosis; Diagnostic; Diagnostic Neoplasm Staging; Disease; Drug resistance; Emerging Technologies; Ensure; Epidemiology; Evaluation; Genetic Engineering; Germ Lines; Harvest; Histologic; Human; Image; Image Analysis; In Situ; Investigation; Laboratories; Lesion; MAP Kinase Gene; Malignant - descriptor; Malignant Neoplasms; Malignant neoplasm of lung; Manuals; Measures; Medical; Medicine; Melanocytic Neoplasm; Methods; Microdissection; Modeling; Molecular; Molecular Analysis; Morphologic artifacts; Mutation; Neoplasm Metastasis; Neoplasms; Nevus; Oral cavity; Pathologic; Pathologist; Pathology; Phenotype; Pre-Clinical Model; Problem Solving; Procedures; Proto-Oncogene Protein c-kit; Proto-Oncogene Proteins c-akt; Reagent; Reproducibility; Research; Research Personnel; Research Project Grants; Resources; Role; Signal Transduction; Site; Slide; Specimen; Techniques; Technology; The Sun; Tissue Preservation; Tissue Procurements; Tissues; Training; Tumor Tissue; Ultraviolet Rays; biobank; cancer type; carcinogenesis; clinically relevant; data mining; design; digital; human disease; improved; intraepithelial; macromolecule; melanocyte; melanoma; molecular pathology; non-invasive imaging; optical imaging; oral cavity melanoma; pre-clinical; quality assurance; spectrograph; targeted treatment; technology development; tissue processing; tool

Research is conducted to characterize and develop new animal models of human disease and to develop the means to better characterize a model's relevance, addressing critical barriers to research progress. Additional aims include the development of new research technologies for the evaluation and application of disease biomarkers. Progress was made in developing cancer diagnostics and in research resources useful in developing and characterizing new models of human cancer and for the proper development and utilization of tissue biobanks. This research project included developing capabilities in molecular diagnostics for cancer models, developing methods for automated morphometric image analysis of cancer specimens for quantitative pathology, investigating the role of S100 in cancer, and preclinical development of targeted therapy for mucosal melanoma. Continued advances and applications in developing quality assurance methods for tissue biobanking were also continued. Unique spatial-spectral image analysis algorithms were developed for applying automated pattern recognition morphometric image analysis to quantify histologic tumor and non-tumor tissue areas in biospecimen tissue sections. Additional progress was made in developing and validating algorithms for cancers of lung and cancer metastasis. Contributions to new models important for understanding mechanisms of drug resistance were developed and validated using quantitative optical imaging. Research resulted in contributions to development of biobank quality assurance procedures. Harmonization of pathology quality assurance procedures for biobank accessions has lagged behind other avenues of biospecimen research and biobank development. Comprehension of the cellular content of biorepository specimens is important for discovery of tissue-specific clinically relevant biomarkers for diagnosis and treatment. While rapidly emerging technologies in molecular analyses and data mining create focus on appropriate measures for minimizing pre-analytic artifact-inducing variables, less attention gets paid to annotating the constituent make up of biospecimens for more effective specimen selection by biobank clients. Both pre-analytic tissue processing and a specimen's composition influence acquisition of relevant macromolecules for downstream assays. Pathologist review of biorepository submissions, particularly tissues as part of quality assurance procedures, helps to ensure that the intended target cells are present and in sufficient quantity in accessioned specimens. This manual procedure can be tedious and subjective. Incorporating digital pathology into biobank quality assurance procedures, using automated pattern recognition morphometric image analysis to quantify tissue feature areas in digital whole slide images of tissue sections, can minimize variability and subjectivity associated with routine pathologic evaluations in biorepositories. Whole-slide images and pathologist-reviewed morphometric analyses can be provided to researchers to guide specimen selection. Harmonization of pathology quality assurance methods that minimize subjectivity and improve reproducibility among collections would facilitate research-relevant specimen selection by investigators and could facilitate information sharing in an integrated network approach to biobanking. Melanoma represents a significant malignancy in humans and dogs. Different from genetically engineered models, sporadic canine melanocytic neoplasms share several characteristics with human disease that could make dogs a more relevant pre-clinical model. Canine melanomas rarely arise in sun-exposed sites. Most occur in the oral cavity, with a subset having intraepithelial malignant melanocytes mimicking the in situ component of human mucosal melanoma. The spectrum of canine melanocytic neoplasia includes benign lesions with some analogy to nevi, as well as invasive primary melanoma, and widespread metastasis. Growing evidence ofdistinct subtypes in humans, differing in somatic and predisposing germ-line genetic alterations, cell of origin, epidemiology, relationship to ultraviolet radiation and progression from benign to malignant tumors, may also exist in dogs. Canine and human mucosal melanomas appear to harbor BRAF, NRAS and c-kit mutations uncommonly, compared to human cutaneous melanomas, although both species share AKT and MAPK signaling activation. We conclude that there is significant overlap in the clinical and histopathological features of canine and human mucosal melanomas. This represents opportunity to explore canine oral cavity melanoma as a pre-clinical model.

进行研究是为了描述和开发新的人类疾病动物模型，并开发更好地描述模型相关性的方法，解决研究进展的关键障碍。其他目标包括为评估和应用疾病生物标记物开发新的研究技术。在开发癌症诊断学和研究资源方面取得了进展，这些资源有助于开发和表征新的人类癌症模型，并有助于适当开发和利用组织生物库。这项研究项目包括开发癌症模型的分子诊断能力，开发用于定量病理学的癌症标本的自动形态图像分析方法，调查S100在癌症中的作用，以及针对粘膜黑色素瘤的临床前靶向治疗的开发。在开发组织生物库的质量保证方法方面也在继续取得进展和应用。开发了独特的空间光谱图像分析算法，用于应用自动模式识别形态测量图像分析来量化组织学组织切片中的肿瘤和非肿瘤组织区域。在开发和验证肺癌和癌症转移的算法方面取得了更多进展。对新模型的贡献对了解耐药机制非常重要，并使用定量光学成像进行了验证。研究结果对生物库质量保证程序的开发做出了贡献。生物库材料的病理学质量保证程序的协调已经落后于生物样品研究和生物库发展的其他途径。理解生物信息库标本的细胞内容对于发现诊断和治疗的组织特异性临床相关生物标记物非常重要。虽然分子分析和数据挖掘中的快速新兴技术将重点放在适当的措施上，以最大限度地减少分析前人工产物诱导的变量，但较少注意到注释生物样本的组成成分，以便生物库客户更有效地选择样本。分析前的组织处理和样品的成分都会影响下游分析所需的相关大分子的获取。作为质量保证程序的一部分，病理学家审查提交的生物信息库，特别是组织，有助于确保预期的目标细胞存在，并在加入的标本中有足够的数量。这种手动操作可能会很繁琐，也很主观。将数字病理学与生物库质量保证程序相结合，使用自动模式识别形态图像分析来量化组织切片的数字完整切片图像中的组织特征区域，可以最大限度地减少与生物信息库常规病理评估相关的可变性和主观性。可以向研究人员提供完整的幻灯片图像和病理学家评审的形态计量分析，以指导标本选择。统一病理学质量保证方法，最大限度地减少主观性并提高收集之间的重复性，将有助于研究人员选择与研究有关的标本，并可促进以综合网络办法共享信息。黑色素瘤是人类和狗的一种重要的恶性肿瘤。与基因工程模型不同，散发性犬黑素细胞肿瘤与人类疾病有几个共同特征，这些特征可能使狗成为更相关的临床前模型。犬类黑色素瘤很少出现在阳光暴晒的地方。大多数发生在口腔，有一亚群具有上皮内恶性黑素细胞，类似于人类粘膜黑色素瘤的原位成分。犬类黑素细胞瘤包括类似痣的良性病变，以及侵袭性原发黑色素瘤，以及广泛的转移。越来越多的证据表明，人类不同的亚型，在体细胞和易感生殖系遗传变化、细胞起源、流行病学、与紫外线辐射的关系以及从良性到恶性肿瘤的进展方面，也可能存在于狗身上。与人类皮肤黑色素瘤相比，犬和人粘膜黑色素瘤似乎罕见地含有BRAF、NRAS和c-kit突变，尽管这两个物种都有AKT和MAPK信号激活。我们的结论是，狗和人类粘膜黑色素瘤的临床和组织病理学特征有显著的重叠。这为探索犬口腔黑色素瘤作为临床前模型提供了机会。