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Diagnostic Pathology and Laboratory Medicine in the Age of “Omics”

William G. Finn

Year
2007
Citations
18
Access
Open access

Abstract

Functional genomics and proteomics involve the simultaneous analysis of hundreds or thousands of expressed genes or proteins and have spawned the modern discipline of computational biology. Novel informatic applications, including sophisticated dimensionality reduction strategies and cancer outlier profile analysis, can distill clinically exploitable biomarkers from enormous experimental datasets. Diagnostic pathologists are now charged with translating the knowledge generated by the “omics” revolution into clinical practice. Food and Drug Administration-approved proprietary testing platforms based on microarray technologies already exist and will expand greatly in the coming years. However, for diagnostic pathology, the greatest promise of the “omics” age resides in the explosion in information technology (IT). IT applications allow for the digitization of histological slides, transforming them into minable data and enabling content-based searching and archiving of histological materials. IT will also allow for the optimization of existing (and often underused) clinical laboratory technologies such as flow cytometry and high-throughput core laboratory functions. The state of pathology practice does not always keep up with the pace of technological advancement. However, to use fully the potential of these emerging technologies for the benefit of patients, pathologists and clinical scientists must embrace the changes and transformational advances that will characterize this new era. Functional genomics and proteomics involve the simultaneous analysis of hundreds or thousands of expressed genes or proteins and have spawned the modern discipline of computational biology. Novel informatic applications, including sophisticated dimensionality reduction strategies and cancer outlier profile analysis, can distill clinically exploitable biomarkers from enormous experimental datasets. Diagnostic pathologists are now charged with translating the knowledge generated by the “omics” revolution into clinical practice. Food and Drug Administration-approved proprietary testing platforms based on microarray technologies already exist and will expand greatly in the coming years. However, for diagnostic pathology, the greatest promise of the “omics” age resides in the explosion in information technology (IT). IT applications allow for the digitization of histological slides, transforming them into minable data and enabling content-based searching and archiving of histological materials. IT will also allow for the optimization of existing (and often underused) clinical laboratory technologies such as flow cytometry and high-throughput core laboratory functions. The state of pathology practice does not always keep up with the pace of technological advancement. However, to use fully the potential of these emerging technologies for the benefit of patients, pathologists and clinical scientists must embrace the changes and transformational advances that will characterize this new era. The evolution of molecular biology from its birth as a distinct field of science in the 1960s through the present has seen a major shift in emphasis from the creation of novel data-generating methods to the creation of novel informatic systems for the analysis of high-dimensional datasets. The derivation of data previously was the rate-limiting step in biomedical scientific advancement. In past decades of scientific discovery, careers were made by generating data, often through novel laboratory methods. Indeed, Nobel prizes have been awarded to the inventors or discoverers of novel technical laboratory methods, and the discovery and characterization of a single human gene (through traditional methods of linkage analysis, cloning, etc) once was enough to consume the span of an investigator's entire career. Now, the sequence of the entire human genome resides in the public domain, and datasets derived from novel genomic and proteomic applications are being generated more qu

Keywords

HematopathologyPaceData scienceComputer scienceGenomicsPersonalized medicineOmicsProteomicsDigital pathologyPrecision medicine

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