Our Science – Simpson Website
R. Mark Simpson, D.V.M., Ph.D.
The Molecular Pathology initiative includes both applied research and collaborations aimed at developing new reagents, methods, and technologies in preclinical diagnostic medicine. Thus, efforts are aimed at enhancing capabilities to integrate molecular and systemic aspects of disease mechanisms. Designing and employing state of the art medical and pathology investigative tools to the study of animal models and patient tissue will help promote translational phenotype comprehension, and therefore improve model predictability for human cancer diseases. The Unit also operates a PhD-granting research training program in comparative molecular pathology through a university- NCI graduate partnership program. Through its training program, the MPU both extends comparative pathology expertise provided by veterinarians to the CCR and it conducts research, which serves as a source of research training experience for its GPP molecular pathologist trainees. The program's vision of comparative biomedical scientist training includes pathologist as investigator and collaborator, vertically-integrated from basic discovery to translational research application.
The molecular pathology unit, headed by Dr. Simpson, serves as a CCR resource with 4 main spheres of activity focused on translational research within the NCI Center for Cancer Research:
- Developing molecular diagnostics for research
- Training in comparative and molecular pathology
- Research investigation and animal model validation
- Noninvasive diagnostic and molecular medical imaging
Applied research includes studies to evaluate use of an ovarian cancer animal model to pilot discovery of protein biomarkers with potential clinical diagnostic utility. Among gynecological cancers, ovarian cancer is a significant cause of death in women. Due to the occult nature of early disease and the vague nonspecific symptoms caused, ovarian cancer diagnosis is often delayed until the disease has spread within the abdomen. Additional challenges exist in managing patients due to recurrence of cancer following initial treatments. A means to detect ovarian cancer, or its recurrence, in patient serum would be a significant benefit to current diagnostic paradigms. Diagnosis based upon serum CA125 tests is hampered due to less than optimal sensitivity and specificity, thus new tests to diagnose ovarian cancer are needed. Current research is aimed at validating serum proteins that can be localized to cancer cell origin, and in investigating their validity for diagnostic or staging use. Biomarker correlates of ovarian cancer burden are particularly challenging in a clinical setting due to the way ovarian cancer spreads throughout the abdominal cavity. Animal models are an important adjunct to the ovarian cancer diagnosis research field. In this research, candidate proteins are detected in serum of mice with staged abdominal carcinomatosis using mass spectrometry. Putative biomarkers are validated. Correlations with tumor burden can be attempted in the carcinomatosis model using human cancers engineered with reporter markers that permits cancer cells to be tracked longitudinally during experimental disease. This model is permitting efforts to link cancer detection methods with ovarian cancer burden. A protein of cancer origin has been identified, related to tumor burden in the model, and shown to correlate with amount present in serum with advanced stage disease in ovarian cancer patients.
Additional lines of inquiry aimed at furthering disease biomarker discovery research revolve around technology development and application, and the development and characterization of model systems. Determination of disease-relevant proteomic profiles from limited tissue specimens, such as pathological biopsies and tissues from small model organisms, remains an analytical challenge and a much needed clinical goal. A transgenic mouse model of cardiac-specific H-Ras-G12V induced hypertrophic cardiomyopathy developed within the lab provides a system to explore the potential of using mass spectrometry (MS)-based proteomics to obtain a disease-relevant molecular profile from amount-limited specimens that are routinely used in pathological diagnosis. More importantly, the MS identification and subsequent cross-validation of Wnt3a and β-catenin, in conjunction with immunohistochemical identification of phosphorylated GSK-3β and nuclear localization of β-catenin, provided evidence of Wnt/β-catenin canonical pathway activation secondary to Ras activation in the course of pathogenic myocardial hypertrophic transformation. Developing methods indicates that the proteomic approach permits molecular discovery and assessment of differentially expressed proteins regulating H-Ras induced hypertrophic cardiomyopathy. Selected proteins and pathways can be further investigated using immunohistochemical techniques applied to serial tissue sections of similar or different origin.
Development of digital pathology capabilities provides new means to archive, share, analyze and consult on pathological specimens of importance to disease research. The MPU has created an initiative to support investigator application of digital pathology for research, and to implement quantitative image analysis algorithms in pathology research. Biorepository-supported translational research depends on high-quality, well-annotated specimens. Histopathology assessment contributes insight into how representative lesions are for research objectives. Feasibility of documenting histological proportions of tumor and stroma is under development in an effort to enhance information regarding biorepository tissue heterogeneity. Unique automated pattern recognition morphometric image analysis algorithms are developed and applied to quantify histologic tumor and nontumor tissue areas in biospecimen tissue sections. Quantitative image analysis automation minimizes variability associated with routine biorepository pathologic evaluations and is anticipated to enhance biomarker discovery by helping to guide the selection of study-appropriate specimens.
This page was last updated on 3/5/2013.