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Expression profiling of renal epithelial neoplasms: a method for tumor classification and discovery of diagnostic molecular markers.

ABSTRACT: The expression patterns of 7075 genes were analyzed in four conventional (clear cell) renal cell carcinomas (RCC), one chromophobe RCC, and two oncocytomas using cDNA microarrays. Expression profiles were compared among tumors using various clustering algorithms, thereby separating the tumors into two categories consistent with corresponding histopathological diagnoses. Specifically, conventional RCCs were distinguished from chromophobe RCC/oncocytomas based on large-scale gene expression patterns. Chromophobe RCC/oncocytomas displayed similar expression profiles, including genes involved with oxidative phosphorylation and genes expressed normally by distal nephron, consistent with the mitochondrion-rich morphology of these tumors and the theory that both lesions are related histogenetically to distal nephron epithelium. Conventional RCCs underexpressed mitochondrial and distal nephron genes, and were further distinguished from chromophobe RCC/oncocytomas by overexpression of vimentin and class II major histocompatibility complex-related molecules. Novel, tumor-specific expression of four genes-vimentin, class II major histocompatibility complex-associated invariant chain (CD74), parvalbumin, and galectin-3-was confirmed in an independent tumor series by immunohistochemistry. Vimentin was a sensitive, specific marker for conventional RCCs, and parvalbumin was detected primarily in chromophobe RCC/oncocytomas. In conclusion, histopathological subtypes of renal epithelial neoplasia were characterized by distinct patterns of gene expression. Expression patterns were useful for identifying novel molecular markers with potential diagnostic utility.

SUBMITTER: Young AN

PROVIDER: S-EPMC1891957 | biostudies-literature | 2001 May

REPOSITORIES: biostudies-literature

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Expression profiling of renal epithelial neoplasms: a method for tumor classification and discovery of diagnostic molecular markers.

Young A N AN Amin M B MB Moreno C S CS Lim S D SD Cohen C C Petros J A JA Marshall F F FF Neish A S AS

The American journal of pathology 20010501 5

The expression patterns of 7075 genes were analyzed in four conventional (clear cell) renal cell carcinomas (RCC), one chromophobe RCC, and two oncocytomas using cDNA microarrays. Expression profiles were compared among tumors using various clustering algorithms, thereby separating the tumors into two categories consistent with corresponding histopathological diagnoses. Specifically, conventional RCCs were distinguished from chromophobe RCC/oncocytomas based on large-scale gene expression patter ...[more]

PMID: 11337362

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Project description:BackgroundThe new "Developmental lineage classification of neoplasms" was described in a prior publication. The classification is simple (the entire hierarchy is described with just 39 classifiers), comprehensive (providing a place for every tumor of man), and consistent with recent attempts to characterize tumors by cytogenetic and molecular features. A taxonomy is a list of the instances that populate a classification. The taxonomy of neoplasia attempts to list every known term for every known tumor of man.MethodsThe taxonomy provides each concept with a unique code and groups synonymous terms under the same concept. A Perl script validated successive drafts of the taxonomy ensuring that: 1) each term occurs only once in the taxonomy; 2) each term occurs in only one tumor class; 3) each concept code occurs in one and only one hierarchical position in the classification; and 4) the file containing the classification and taxonomy is a well-formed XML (eXtensible Markup Language) document.ResultsThe taxonomy currently contains 122,632 different terms encompassing 5,376 neoplasm concepts. Each concept has, on average, 23 synonyms. The taxonomy populates "The developmental lineage classification of neoplasms," and is available as an XML file, currently 9+ Megabytes in length. A representation of the classification/taxonomy listing each term followed by its code, followed by its full ancestry, is available as a flat-file, 19+ Megabytes in length. The taxonomy is the largest nomenclature of neoplasms, with more than twice the number of neoplasm names found in other medical nomenclatures, including the 2004 version of the Unified Medical Language System, the Systematized Nomenclature of Medicine Clinical Terminology, the National Cancer Institute's Thesaurus, and the International Classification of Diseases Oncolology version.ConclusionsThis manuscript describes a comprehensive taxonomy of neoplasia that collects synonymous terms under a unique code number and assigns each tumor to a single class within the tumor hierarchy. The entire classification and taxonomy are available as open access files (in XML and flat-file formats) with this article.

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Dataset Information

Expression profiling of renal epithelial neoplasms: a method for tumor classification and discovery of diagnostic molecular markers.

Publications

Expression profiling of renal epithelial neoplasms: a method for tumor classification and discovery of diagnostic molecular markers.

Similar Datasets

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