Molecular Pathology Research for Cancer Diagnostics and Biomarkers

在这个项目中，进行研究是为了确定和开发新的人类疾病动物模型，并开发更好地确定模型相关性的手段，解决研究进展的关键障碍。其他目标包括开发新的研究技术，以评估和应用疾病生物标志物。在开发癌症诊断方法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。该研究项目包括开发癌症模型的分子诊断能力，开发用于定量病理的癌症标本的自动形态测量图像分析方法，研究S100在癌症中的作用，开发用于有限组织（如活组织检查或模型动物）的质谱新方法。在组织生物库质量保证方法开发方面的持续进展和应用也在继续。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学图像分析来量化生物标本组织切片中的组织学肿瘤和非肿瘤组织区域。在开发和验证血液和血管组织、肺和结缔组织间充质组织（软组织肉瘤）癌症的算法方面取得了额外进展。定量图像分析自动化有望通过帮助指导选择适合研究的标本来增强生物标志物的发现。研究成果有助于生物库质量保证程序的发展。生物库最佳实践的标准化将提高利用患者来源的生物库标本的转化生物医学研究的质量。生物样本库加入的病理质量保证程序的统一落后于生物标本研究和生物样本库开发的其他途径。了解生物库标本的细胞含量对于发现用于诊断和治疗的组织特异性临床相关生物标志物非常重要。虽然分子分析和数据挖掘领域的快速发展技术将重点放在了减少分析前伪影诱发变量的适当措施上，但对生物样本组成的注释却很少得到关注，从而使生物样本库客户能够更有效地选择样本。分析前的组织处理和标本的组成都会影响下游分析中相关大分子的获取。病理学家审查生物库提交，特别是组织作为质量保证程序的一部分，有助于确保预期的靶细胞存在，并在加入的标本中有足够的数量。这个手工过程可能是乏味和主观的。将数字病理学纳入生物库质量保证程序，使用自动模式识别形态学图像分析来量化组织切片数字整张幻灯片图像中的组织特征区域，可以最大限度地减少生物库中常规病理评估的可变性和主观性。整个幻灯片图像和病理审查的形态计量学分析可以提供给研究人员指导标本选择。病理学质量保证方法的统一将最大限度地减少主观性，提高标本的可重复性，这将有助于研究人员选择与研究相关的标本，并有助于在生物库的综合网络方法中促进信息共享。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，散发性犬黑色素细胞肿瘤与人类疾病有几个共同的特征，这可能使狗成为更相关的临床前模型。犬黑色素瘤很少出现在阳光照射的部位。大多数发生在口腔，其中一个亚群有上皮内恶性黑色素细胞，模仿人粘膜黑色素瘤的原位成分。犬黑色素细胞瘤包括与痣相似的良性病变，也包括侵袭性原发性黑色素瘤和广泛转移。越来越多的证据表明，人类中不同的亚型，在体细胞和易感生殖系遗传改变、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存在差异，也可能存在于狗中。与人类皮肤黑色素瘤相比，犬和人粘膜黑色素瘤似乎不常见BRAF、NRAS和c-kit突变，尽管这两个物种都具有AKT和MAPK信号激活。我们得出结论，犬和人的粘膜黑色素瘤的临床和组织病理学特征有显著的重叠。这代表了探索犬口腔黑色素瘤作为临床前模型的机会。

In this project 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, developing new methods in mass spectrometry for limited tissue such as biopsies or model animals. 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 the blood and vascular tissues, lung, and connective mesenchymal tissues (soft tissue sarcoma). Quantitative image analysis automation is anticipated to enhance biomarker discovery by helping to guide the selection of study-appropriate specimens. Research resulted in contributions to development of biobank quality assurance procedures . Standardization of biorepository best practices will enhance the quality of translational biomedical research utilizing patient-derived biobank specimens. 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 of distinct 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.