John Gilbertson

Differences in gene expression in prostate cancer, normal appearing prostate tissue adjacent to cancer and prostate tissue from cancer free organ donors

BackgroundTypical high throughput microarrays experiments compare gene expression across two specimen classes – an experimental class and baseline (or comparison) class. The choice of specimen classes is a major factor in the differential gene expression patterns revealed by these experiments. In most studies of prostate cancer, histologically malignant tissue is chosen as the experimental class while normal appearing prostate tissue adjacent to the tumor (adjacent normal) is chosen as the baseline against which comparison is made. However, normal appearing prostate tissue from tumor free organ donors represents an alterative source of baseline tissue for differential expression studies.MethodsTo examine the effect of using donor normal tissue as opposed to adjacent normal tissue as a baseline for prostate cancer expression studies, we compared, using oligonucleotide microarrays, the expression profiles of primary prostate cancer (tumor), adjacent normal tissue and normal tissue from tumor free donors.ResultsStatistical analysis using Significance Analysis of Microarrays (SAM) demonstrates the presence of unique gene expression profiles for each of these specimen classes. The tumor v donor expression profile was more extensive that the tumor v adjacent normal profile. The differentially expressed gene lists from tumor v donor, tumor v adjacent normal and adjacent normal v donor comparisons were examined to identify regulated genes. When donors were used as the baseline, similar genes are highly regulated in both tumor and adjacent normal tissue. Significantly, both tumor and adjacent normal tissue exhibit significant up regulation of proliferation related genes including transcription factors, signal transducers and growth regulators compared to donor tissue. These genes were not picked up in a direct comparison of tumor and adjacent normal tissues.ConclusionsThe up-regulation of these gene types in both tissue types is an unexpected finding and suggests that normal appearing prostate tissue can undergo genetic changes in response to or in expectation of morphologic cancer. A possible field effect surrounding prostate cancers and the implications of these findings for characterizing gene expression changes in prostate tumors are discussed.

Information requirements of cancer center researchers focusing on human biological samples and associated data

This study was undertaken to characterize the information requirements of cancer researchers who were specifically interested in human biological specimens at a comprehensive cancer center, and to determine if existing information systems could meet those needs. Information required by the cancer center researchers at the University of Pittsburgh Cancer Institute (UPCI, Pittsburgh, PA) was identified through interviews, query analysis, and analysis of publications. For topical matters, the study found that the most frequent types of questions were the following: clinical (50.18%), prognosis (17.87%), diagnosis/disorder-based (50.72%), and research-oriented (51.9%) queries. In terms of the required data elements, pathology data (17.32%) was the most frequently required, followed by clinical history and outcomes (15.18%). In addition, the study identified the 10 main questions, concerning human biological samples, and the majority of the questions were represented in a fairly discrete set of information spaces that could be well mapped into the conceptual data model created through the study. The results found in this study can be used for an initial data modeling, when creating a biomedical research data warehouse that would support the majority of the transitional research requirements of the UPCI.

An online analysis and information fusion platform for heterogeneous biomedical informatics data

Current research in biomedical informatics involves analysis of multiple heterogeneous data sets. This includes patient demographics, clinical and pathology data, treatment history, patient outcomes as well as gene expression, DNA sequences and other information sources such as gene ontologies. Analysis of these data sets could lead to better disease diagnosis, prognosis, treatment and drug discovery. However, the extent of knowledge that can be extracted from individual data sets is limited Recently, there has been a lot of focus on techniques that analyze genomic data sources in an integrated manner through information fusion. This places a need for an online platform to analyze biomedical informatics data sets using these techniques. We present here an online data warehouse to perform data exploration and analysis across heterogeneous biomedical informatics data sets with the aid of information fusion. The prototype platform is available at http://biogeowarehouse.cse.psu.edu.

Speed, Resolution, Focus, and Depth of Field in Clinical Whole Slide Imaging Applications

The process of digital imaging in microscopy can be thought of as a series of operations each of which contributes to the quality of the final image displayed on the computer monitor. The operations include sample preparation and staining by histology, optical image formation by the microscope, digital image sampling by the CCD and camera, postprocessing and compression, transmission on the network and display on the monitor. Over the years, an extensive literature has developed on digital imaging, and each step of the process is fairly well understood. However, the development of automated, whole slide imaging systems for clinical applications has forced us to re-examine the relative significance of different parts of the digital imaging process. An obvious example is in the importance of compression. In a traditional single frame digital imaging environment, where a typical uncompressed image file may be one to several megabytes, efficient compression is a convenience. On the other hand, in a clinical whole slide imaging system which could generate several hundred, multi-gigabyte images a day, efficient compression is absolutely required for effective management. Another area in which today’s highspeed, automated whole slide imaging systems cause us to re-examine traditional thought is in the relationship between focus, optical (lateral) resolution and digital image sampling. In particular, today’s high-speed whole slide imaging systems have traded precise field by field focus in exchange for overall capture speed. This trade off is highly appropriate given the requirements of high-speed image capture; however, it does force us to re-examine the nature and description of resolution and image quality in the context of whole slide imaging. This chapter does this by discussing the relationships between focus, image formation, image sampling and depth of field in the creation of high-quality images by high-speed image capture devices.

Implementation and evaluation of a negation tagger in a pipeline-based system for information extraction from pathology reports

We have developed a pipeline-based system for automated annotation of Surgical Pathology Reports with UMLS terms that builds on GATE – an open-source architecture for language engineering. The system includes a module for detecting and annotating negated concepts, which implements the NegEx algorithm – an algorithm originally described for use in discharge summaries and radiology reports. We describe the implementation of the system, and early evaluation of the Negation Tagger. Our results are encouraging. In the key Final Diagnosis section, with almost no modification of the algorithm or phrase lists, the system performs with precision of 0.84 and recall of 0.80 against a gold-standard corpus of negation annotations, created by modified Delphi technique by a panel of pathologists. Further work will focus on refining the Negation Tagger and UMLS Tagger and adding additional processing resources for annotating freetext pathology reports.

High-throughput high-resolution microscopic slide digitization for pathology

Pathologist study tissue samples to determine the presence and nature of diseases. Morphology is a critical component to identifying cellular and tissue structures and the functional changes produced by disease. Technical advances in the field of pathology have primarily been in the areas of tissue preparation and the staining process that enhances the pathologists identification of these structures. Pathologists primary tool for diagnosis has remained the same for over a century--the optical microscope. Radiology has made tremendous advances with digitization and the ease of exchange and image analysis that comes with digital data and todays computer technology. Pathology is primed to enter the digital era as well. The major hurdles to wide spread acceptance of conversion to digital pathological imaging have been image resolution, scanner throughput, image file size and image display rates. InterScope Technologies, Inc. has developed a high-throughput, high-resolution microscopic slide digitization system that is well suited for pathological examination and diagnosis. This system is fully automated, captures at 0.3 μm per pixel, and can capture a slide in under 3 minutes, and has the potential to capture much faster. This paper will present the technical challenges associated with digital pathological imaging and how InterScope has addressed these challenges in the development of their digital scanner.