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Genotyping and copy number analysis of human renal epithelial neoplasms

ABSTRACT: Renal tumors with complex morphology require extensive workup for accurate classification. Chromosomal aberrations that define subtypes of renal epithelial neoplasms have been reported. We explored if whole-genome chromosome copy number and loss-of-heterozygosity analysis with single nucleotide polymorphism (SNP) arrays can be used to identify these aberrations. Experiment Overall Design: We analyzed 20 paraffin-embedded tissues representing conventional renal cell carcinoma (RCC), papillary RCC, chromophobe RCC, and oncocytoma with Affymetrix GeneChip 10K 2.0 Mapping arrays.

ORGANISM(S): Homo sapiens

SUBMITTER: Federico Monzon

PROVIDER: E-GEOD-9469 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Project description:Copy number variant (CNV) analysis was performed on renal cell carcinoma (RCC) specimens (chromophobe, clear cell, oncocytoma, papillary type 1, papillary type 2) using high resolution arrays (1.85 million probes). RCC samples exhibited diverse genomic changes within and across tumor types ranging from 106 CNV segments in a clear cell specimen to 2238 CNV segments in a papillary type 2 specimen. Despite the genomic heterogeneity, distinct CNV segments were common within each of 4 tumor classifications: chromophobe (7 segments), clear cell (3 segments), oncocytoma (9 segments), and papillary type 2 (2 segments). Shared segments ranged from a 6.1 Kb deletion among oncocytomas to a 208.3 Kb deletion common to chromophobes. Among common tumor type-specific variations, chromophobe, clear cell and oncocytomas comprised exclusively non-coding DNA. No CNV regions were common to papillary type 1 specimens although there were 12 amplifications and 12 deletions in 5 of 6 samples. Three microRNAs and 12 mRNA genes had M-bM-^IM-% 98% of their coding region contained within CNV regions including multiple gene families (chromophobe: amylase 1A, 1B, 1C; oncocytoma: general transcription factor 2H2, 2B, 2C, 2D). Gene deletions involved in histone modification and chromatin remodeling affected individual subtypes (clear cell: SFMBT, SETD2; papillary type 2: BAZ1A) as well as the collective RCC group (KDM4C). The genomic amplifications/deletions identified in each renal tumor type represent potential diagnostic and/or prognostic biomarkers. Tissue samples were obtained from the University of Pittsburgh Health Sciences Tissue Bank (HSTB) using an honest broker system and according to IRB approved protocol #970480. Samples were acquired as surgical specimens, flash-frozen in a 1.8 ml cryotube (NalgeNunc, Inc., Rochester, NY) followed by immediate storage at -80C. Each tumor sample (n=27) was classified into one of 5 renal cancer subtypes (chromophobe: n=5, clear cell: n=5, oncocytoma: n=5, papillary type 1: n=6, papillary type 2: n=6) by consensus evaluation of correlative hematoxylin and eosin stained slides performed independently by 3 anatomical pathologists. The three pathologists also confirmed the absence of pathological features in adjacent normal renal samples (n=9) and this normal reference group was expanded by inclusion of 14 normal thyroid samples and 8 normal lung specimens. DNA from each of these specimens was analyzed using genotyping microarrays (SNP 6.0, Affymetrix, Sunnyvale, CA).

Project description:Accurate diagnostic discrimination of benign renal oncocytoma (OC) and malignant renal cell carcinomas (RCC) is not only useful for planning appropriate treatment strategies of patients with renal masses but also for estimating prognosis. Classification of renal neoplasms solely by histopathology can often be challenging for a variety of reasons. The aim of this study was to develop and validate a genomic algorithm for molecular classification of renal cortical neoplasms that could be implemented in a routine clinical diagnostic setting. Using TCGA (The Cancer Genome Atlas) copy number profiles of over 600 RCC specimens, prior FISH studies and published literature, a classification algorithm was developed consisting of 15 genomic markers: loss of VHL, 3p21, 8p, and chromosomes 1, 2, 6, 10 and 17, and gain of 5qter, 16p, 17q, 20q, and chromosomes 3, 7, and 12. Criteria for scoring specimens for the presence of each genomic marker were established. As validation, 191 surgically resected formalin-fixed paraffin-embedded renal neoplasms were blindly submitted to targeted array-CGH and were classified according to the algorithm. Upon histologic re-review leading to exclusion of three specimens and using histology as the gold standard, the algorithm correctly classified 58 of 62 (93%) clear cell renal cell carcinoma, 51 of 56 (91%) papillary RCC, and 33 of 34 (97%) chromophobe RCC. Of the 36 OC specimens, 17 were classified as OC, two as a malignant subtype, 14 as benign, and three exhibited alterations not associated with a specific subtype. In ten of the latter two groups, CCND1-rearrangement was detected by fluorescence in situ hybridization, affording a classification as OC. Together, 33 of 36 (92%) OC were classified as OC or benign. For the entire validation cohort, an overall diagnostic sensitivity of 93% and above 97% specificity was achieved, suggesting that the implementation of genome-based molecular classification in a clinical diagnostic setting could impact the overall management and outcome of patients with renal tumors. A total of 191 RCC FFPE samples are analyzed including 63 clear cell RCC (ccRCC), 57 papillary RCC (pRCC), 35 chromophobe RCC (chrRCC) and 36 oncocytoma (OC). Two-color array-comparative genomic hybdrization on custom designed using RCC DNA as test and normal sex-matched DNA as reference.