Renal epithelial neoplasms: diagnostic applications of gene expression profiling.
Renal cell carcinoma (RCC) is the most common form of kidney cancer in adults. RCC is a significant challenge for pathologic diagnosis and clinical management. The primary approach to diagnosis is by light microscopy, using the World Health Organization (WHO) classification system, which defines histopathologic tumor subtypes with distinct clinical behavior and underlying genetic mutations. However, light microscopic diagnosis of RCC subtypes can be difficult due to variable histology, morphologic features shared by tumor subtypes, and a growing frequency of small tumor biopsies with limited morphologic information. In addition to these diagnostic problems, the clinical behavior of RCC is highly variable, and therapeutic response rates are poor. Few clinical assays are available to predict outcome in RCC or correlate behavior with histology. Therefore, novel RCC classification systems based on gene expression should be useful for diagnosis, prognosis, and treatment. Recent microarray studies have shown that renal tumors are characterized by distinct gene expression profiles, which can be used to discover novel diagnostic and prognostic biomarkers. Here, we review clinical features of kidney cancer, the WHO classification system, and the growing role of molecular classification for diagnosis, prognosis, and therapy of this disease.
D002292:Carcinoma, Renal Cell / Q000175:diagnosis* / Q000235:genetics*; D004273:DNA, Neoplasm / Q000235:genetics; D020869:Gene Expression Profiling / Q000379:methods*; D006801:Humans; D007680:Kidney Neoplasms / Q000175:diagnosis* / Q000235:genetics*; D009367:Neoplasm Staging / Q000379:methods; D009375:Neoplasms, Glandular and Epithelial / Q000145:classification / Q000175:diagnosis / Q000235:genetics; D011379:Prognosis; D014944:World Health Organization
D004273:DNA, Neoplasm