Christin Sciulli

Multicenter Validation of a 1,550-Gene Expression Profile for Identification of Tumor Tissue of Origin

PURPOSE Malignancies found in unexpected locations or with poorly differentiated morphologies can pose a significant challenge for tissue of origin determination. Current histologic and imaging techniques fail to yield definitive identification of the tissue of origin in a significant number of cases. The aim of this study was to validate a predefined 1,550-gene expression profile for this purpose. METHODS Four institutions processed 547 frozen specimens representing 15 tissues of origin using oligonucleotide microarrays. Half of the specimens were metastatic tumors, with the remainder being poorly differentiated and undifferentiated primary cancers chosen to resemble those that present as a clinical challenge. RESULTS In this blinded multicenter validation study the 1,550-gene expression profile was highly informative in tissue determination. The study found overall sensitivity (positive percent agreement with reference diagnosis) of 87.8% (95% CI, 84.7% to 90.4%) and overall specificity (negative percent agreement with reference diagnosis) of 99.4% (95% CI, 98.3% to 99.9%). Performance within the subgroup of metastatic tumors (n = 258) was found to be slightly lower than that of the poorly differentiated and undifferentiated primary tumor subgroup, 84.5% and 90.7%, respectively (P = .04). Differences between individual laboratories were not statistically significant. CONCLUSION This study represents the first adequately sized, multicenter validation of a gene-expression profile for tissue of origin determination restricted to poorly differentiated and undifferentiated primary cancers and metastatic tumors. These results indicate that this profile should be a valuable addition or alternative to currently available diagnostic methods for the evaluation of uncertain primary cancers.

Whole genome SNP arrays as a potential diagnostic tool for the detection of characteristic chromosomal aberrations in renal epithelial tumors

Renal tumors with complex or unusual 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 and classify renal epithelial tumors. We analyzed 20 paraffin-embedded tissues representing clear cell, papillary renal and chromophobe renal cell carcinoma, as well as oncocytoma with Affymetrix GeneChip 10K 2.0 Mapping arrays. SNP array results were in concordance with known genetic aberrations for each renal tumor subtype. Additional chromosomal aberrations were detected in all renal cell tumor types. The unique patterns allowed 19 out of 20 tumors to be readily categorized by their chromosomal copy number aberrations. One papillary renal cell carcinoma type 2 did not show the characteristic 7/17 trisomies. Clustering using the median copy number of each chromosomal arm correlated with histological class when using a restricted set of chromosomes. In addition, three morphologically challenging tumors were analyzed to explore the potential clinical utility of this method. In these cases, the SNP array-based copy number evaluation yielded information with potential clinical value. These results show that SNP arrays can detect characteristic chromosomal aberrations in paraffin-embedded renal tumors, and thus offer a high-resolution, genome-wide method that can be used as an ancillary study for classification and potentially for prognostic stratification of these tumors.

Optimization of the Affymetrix GeneChip Mapping 10K 2.0 Assay for routine clinical use on formalin-fixed paraffin-embedded tissues.

The use of chromosomal copy number changes as markers for tumor behavior or as prognostic markers for patient outcome has been suggested. However, current clinically used technologies cannot perform genome-wide assessment of chromosome copy number and analysis of loss of heterozygosity in the same assay for paraffin-embedded tissue. We have optimized the Affymetrix GeneChip Mapping Assay for the 10K 2.0 array for use with formalin-fixed, paraffin-embedded (FFPE) tissues. This technology uses single nucleotide polymorphism (SNP) arrays to assess the changes in chromosomal copy number and loss of heterozygosity. DNA from 3 paired tumor/normal samples of adrenal tumors and 4 samples of renal tumors were processed with modifications to the manufacturers protocol. Modifications at different steps were evaluated for their effects on SNP signal-detection and call rates. Frozen samples showed 99.6%±0.3% signal-detection rates and 94.7%±3.0% SNP call rates. FFPE samples labeled with the original protocol failed to produce enough polymerase chain reaction products for hybridization, whereas the same samples processed with the optimized protocol had signal-detection rates of 97.4%±0.018% and SNP call rates of 90.9%±0.034%. The average SNP call concordance between fresh and matching FFPE samples was 96%. Chromosomal aberrations detected in the frozen tumors were also detected in the FFPE tissues. Our optimized protocol significantly improves the performance of the FFPE samples in the Affymetrix GeneMapping Assay with the 10K 2.0 SNP array. This optimized protocol opens up the potential for the GeneChip Mapping assay to be used in the development of clinical test assays.

The degree of segmental aneuploidy measured by total copy number abnormalities predicts survival and recurrence in superficial gastroesophageal adenocarcinoma.

Background Prognostic biomarkers are needed for superficial gastroesophageal adenocarcinoma (EAC) to predict clinical outcomes and select therapy. Although recurrent mutations have been characterized in EAC, little is known about their clinical and prognostic significance. Aneuploidy is predictive of clinical outcome in many malignancies but has not been evaluated in superficial EAC. Methods We quantified copy number changes in 41 superficial EAC using Affymetrix SNP 6.0 arrays. We identified recurrent chromosomal gains and losses and calculated the total copy number abnormality (CNA) count for each tumor as a measure of aneuploidy. We correlated CNA count with overall survival and time to first recurrence in univariate and multivariate analyses. Results Recurrent segmental gains and losses involved multiple genes, including: HER2, EGFR, MET, CDK6, KRAS (recurrent gains); and FHIT, WWOX, CDKN2A/B, SMAD4, RUNX1 (recurrent losses). There was a 40-fold variation in CNA count across all cases. Tumors with the lowest and highest quartile CNA count had significantly better overall survival (p = 0.032) and time to first recurrence (p = 0.010) compared to those with intermediate CNA counts. These associations persisted when controlling for other prognostic variables. Significance SNP arrays facilitate the assessment of recurrent chromosomal gain and loss and allow high resolution, quantitative assessment of segmental aneuploidy (total CNA count). The non-monotonic association of segmental aneuploidy with survival has been described in other tumors. The degree of aneuploidy is a promising prognostic biomarker in a potentially curable form of EAC.

Renal Cell Neoplasms Contain Shared Tumor Type–Specific Copy Number Variations

Copy number variant (CNV) analysis was performed on renal cell carcinoma (RCC) specimens (chromophobe, clear cell, oncocytoma, papillary type 1, and papillary type 2) using high-resolution arrays (1.85 million probes). The RCC samples exhibited diverse genomic changes within and across tumor types, ranging from 106 to 2238 CNV segments in a clear-cell specimen and in a papillary type 2 specimen, respectively. Despite this heterogeneity, distinct CNV segments were common within each tumor classification: chromophobe (seven segments), clear cell (three segments), oncocytoma (nine segments), and papillary type 2 (two segments). Shared segments ranged from a 6.1-kb deletion (oncocytomas) to a 208.3-kb deletion (chromophobes). Among common tumor type-specific variations, chromophobes, clear-cell tumors, and oncocytomas were composed exclusively of noncoding DNA. No CNV regions were common to papillary type 1 specimens, although there were 12 amplifications and 12 deletions in five of six samples. Three microRNAs and 12 mRNA genes had a ≥98% coding region contained within CNV regions, including multiple gene families (chromophobe: amylases 1A, 1B, and 1C; oncocytoma: general transcription factors 2H2, 2B, 2C, and 2D). Gene deletions involved in histone modification and chromatin remodeling affected individual subtypes (clear cell: SFMBT and SETD2; papillary type 2: BAZ1A) and the collective RCC group (KDM4C). The genomic amplifications/deletions identified herein represent potential diagnostic and/or prognostic biomarkers.