Molecular Classification of Renal Tumors by Gene Expression Profiling

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Molecular Classification of Renal Tumors by Gene Expression Profiling Journal of Molecular Diagnostics, Vol. 7, No. 2, May 2005 Copyright © American Society for Investigative Pathology and the Association for Molecular Pathology Molecular Classification of Renal Tumors by Gene Expression Profiling Audrey N. Schuetz,* Qiqin Yin-Goen,*† Renal cell carcinoma (RCC) is the most common malig- Mahul B. Amin,*‡§ Carlos S. Moreno,*‡ nancy of the adult kidney, comprising 3% of all human 1 Cynthia Cohen,* Christopher D. Hornsby,* cancers. Localized tumors can be detected by abdom- 2 Wen Li Yang,*† John A. Petros,*†‡§ inal imaging and cured by surgery. However, 25 to 40% of cases present with extrarenal growth or metastases,3 Muta M. Issa,†§ John G. Pattaras,§ § § and one-third of apparently localized lesions develop Kenneth Ogan, Fray F. Marshall, and metastases during the postoperative course.4,5 Ad- † Andrew N. Young* vanced RCC responds poorly to systemic therapy and From the Departments of Pathology and Laboratory Medicine* has a 5-year survival rate of less than 10%.6,7 and Urology,§ and the Winship Cancer Institute,‡ Emory Important predictors of outcome for RCC include tumor University School of Medicine, Atlanta; and the Atlanta Veterans stage, Fuhrman nuclear grade, histopathological classi- 3,8–10 Affairs Medical Center,† Decatur, Georgia fication, and perioperative thrombocytosis. The cur- rent renal tumor classification system is based on mor- phology, as well as underlying genetic differences.3,11,12 More than 90% of clinically significant lesions can be diagnosed as one of the common subtypes of renal ep- Renal tumor classification is important because his- ithelial tumor: clear cell (conventional) RCC, papillary topathological subtypes are associated with distinct RCC, chromophobe RCC, and renal oncocytoma. Mes- clinical behavior. However, diagnosis is difficult be- enchymal renal tumors are more rare and include angio- cause tumor subtypes have overlapping microscopic myolipoma. Recent clinicopathological surveys have in- characteristics. Therefore, ancillary methods are dicated that clear cell RCC has the highest rate of needed to optimize classification. We used oligonucle- metastasis and poorest survival among common renal otide microarrays to analyze 31 adult renal tumors, malignancies.3 Papillary and chromophobe carcinomas including clear cell renal cell carcinoma (RCC), pap- are relatively indolent but exhibit potential for metastasis illary RCC, chromophobe RCC, oncocytoma, and an- and transformation to high-grade, sarcomatoid tumors. In giomyolipoma. Expression profiles correlated with contrast, typical oncocytomas and angiomyolipomas are histopathology; unsupervised algorithms clustered 30 considered benign neoplasms. of 31 tumors according to appropriate diagnostic sub- Renal tumor subtypes exhibit several common mor- types while supervised analyses identified significant, phological characteristics, making diagnosis difficult and subtype-specific expression markers. Clear cell RCC subjective in many cases. For instance, eosinophilic vari- overexpressed proximal nephron, angiogenic, and ants of clear cell and chromophobe RCC can closely immune response genes, chromophobe RCC oncocy- resemble the benign oncocytoma histologically. There- toma overexpressed distal nephron and oxidative fore, ancillary molecular methods are needed for optimal phosphorylation genes, papillary RCC overexpressed diagnosis and clinical management. In several types of serine protease inhibitors, and extracellular matrix human cancer, gene expression microarrays have products, and angiomyolipoma overexpressed mus- proved to be effective tools for classifying tumors and cle developmental, lipid biosynthetic, melanocytic, identifying novel molecular biomarkers.13–16 Previously, and distinct angiogenic factors. Quantitative reverse we used microarrays to profile gene expression in clear transcriptase-polymerase chain reaction and immu- cell RCC, papillary RCC, chromophobe RCC, and onco- nohistochemistry of formalin-fixed renal tumors con- firmed overexpression of proximal nephron markers (megalin/low-density lipoprotein-related protein 2, Supported by a Veterans Affairs merit review grant (to A.N.Y.). ␣ -methylacyl CoA racemase) in clear cell and papil- A.N.S. and Q.Y.-G. contributed equally to this study. ␤ lary RCC and distal nephron markers ( -defensin 1, Accepted for publication November 17, 2004. claudin 7) in chromophobe RCC/oncocytoma. In Supplementary material for this article can be found at http://jmd. summary, renal tumor subtypes were classified by amjpathol.org. distinct gene expression profiles, illustrating tumor Address reprint requests to Andrew N. Young, M.D., Ph.D., Department pathobiology and translating into novel molecular of Pathology and Laboratory Medicine, Emory University/Atlanta VA Med- bioassays using fixed tissue. (J Mol Diagn 2005, ical Center, 1670 Clairmont Rd., Decatur, GA 30033. E-mail: andrew. 7:206–218) [email protected]. 206 Molecular Classification of Renal Tumors 207 JMD May 2005, Vol. 7, No. 2 cytoma; based on distinct expression patterns, we devel- CA) according to the manufacturer’s recommendations. oped a novel immunohistochemical panel for renal tumor RNA was quantified and assessed for integrity using a subtyping.17,18 Other groups have confirmed these find- 2100 Bioanalyzer (Agilent Technologies, Palo Alto, CA). ings in larger studies.5,19–21 We extended our observa- Expression profiles of all specimens were compared to a tions in the current experiments, using oligonucleotide commercial universal reference RNA (Clontech, Palo microarrays to profile the expression of several thousand Alto, CA). Probe synthesis and microarray hybridization genes in a cohort of clear cell RCC, papillary RCC, chro- were performed according to standard Affymetrix proto- mophobe RCC, oncocytoma, and angiomyolipoma. We cols, described in detail at the Internet site http://www. validated the microarray data for selected, differentially affymetrix.com/community/academic/grant.affx. Briefly, to- expressed gene products in an independent cohort of tal RNA (5 ␮g per specimen) was reverse-transcribed fixed tissues, using quantitative reverse transcriptase- into double-stranded cDNA, and biotin-labeled cRNA polymerase chain reaction (RT-PCR) and immunohisto- was produced by in vitro transcription. Labeled cRNA chemistry, and thereby confirmed these gene products was fragmented and digested by DNase I before hybrid- as potential expression markers for renal tumor ization. Hybridization cocktails were prepared by com- classification. bining fragmented targets, probe array controls, bovine serum albumin, and herring sperm DNA. Cocktails were applied to HG Focus oligonucleotide microarrays (Af- Materials and Methods fymetrix, Santa Clara, CA) for 16 hours, followed by au- tomated washing and staining on an Affymetrix worksta- Experimental Specimens tion. After staining, microarrays were scanned and analyzed with Affymetrix Microarray Suite 5.0 software, to Microarray experiments were performed on frozen spec- define probe cells, compute signal intensities in each imens from 13 clear cell RCC, 5 papillary RCC, 4 chro- cell, and calculate signal log expression ratios for each mophobe RCC, 3 oncocytoma, and 6 angiomyolipoma. 2 gene in tumor versus reference specimens. The HG Fo- Clinicopathological characteristics of this tumor cohort cus arrays produced data for 8746 genes. All hybridiza- are described in Supplementary Table 1 at http://jmd. tion experiments met the following quality control criteria: amjpathol.org. Quantitative RT-PCR experiments were average background, Ͻ100 U; noise, Ͻ5U;3Ј:5Ј ratio of performed on formalin-fixed paraffin-embedded tissue control genes, Ͻ3; and RNA spikes present with appro- from an independent cohort of 10 clear cell RCC, 6 priate signal intensities. Scaling factors and transcript papillary RCC, 5 chromophobe RCC, and 7 renal onco- presence rates varied less than 20% among tumor cytoma. Immunohistochemistry was performed on a fixed samples. tissue microarray that included 33 clear cell RCC, 19 papillary RCC, 6 chromophobe RCC, and 6 oncocytoma. The Emory University and Atlanta Veterans Affairs Medi- cal Center Departments of Pathology and Laboratory Data Analysis Medicine diagnosed tumors using published criteria:3 Affymetrix data sets were normalized with a robust mul- clear cell RCC– neoplastic clear cells with an anastomos- tiarray algorithm22 accounting for GC sequence informa- ing vascular network; papillary RCC– circumscription tion (GCRMA algorithm), encoded in GeneTraffic soft- with a fibrous capsule, papillary growth pattern, foam ware (Iobion Informatics, La Jolla, CA). Expression cells, and necrosis; chromophobe RCC– broad alveolar profiles were filtered to exclude genes with fewer than or nested growth pattern, neoplastic cells with irregular two observations of absolute value log ratio Ͼ2, or with nuclei and perinuclear halos, clear flocculent or granular 2 mean log ratio range (maximum Ϫ minimum) Ͻ 2. This eosinophilic cytoplasm; renal oncocytoma– circumscrip- 2 procedure selected 4030 differentially expressed genes tion with a central scar, nested or tubulocystic growth from the total of 8746. To compare global expression pattern, and neoplastic oncocytes with small round nuclei patterns among renal tumor subtypes, the filtered expres- and granular eosinophilic cytoplasm; angiomyolipoma– sion profiles were analyzed by unsupervised hierarchical mesenchymal tumor containing mature adipose, spindle, average linkage clustering, using Pearson correlation
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