Eckel‐Passow, Jeanette E.

Abstract Background: Based upon the association between pathologic response and disease free survival, the neoadjuvant setting is increasingly being used for drug development. NGS has identified unique and recurrent genetic alterations in breast cancer (BC) that are potentially targetable; however, the clinical implications are mostly unknown. We developed a prospective neoadjuvant study (BEAUTY) in high risk BC patients (pts) using weekly T followed by anthracycline-based chemo wherein percutaneous tumor biopsies (PTB) are obtained before/during/after chemo for NGS and PDX. Our goal is to identify novel biomarkers/pathways and develop PDX to test new therapeutic approaches. Methods: Pts underwent PTB at baseline and after 12 wks of T. Response to T was defined based upon 12 week Ki-67: responder (<15%) vs non-responder (≥15%). Pts with histologic response and absence of invasive BC at 12 wks were classified as responders. NGS was performed using PTB/blood DNA (exome) and PTB (RNA seq). MRI response was classified using RECIST criteria. NGS data were used to identify somatic copy number variants (cnvs) and expressed single nucleotide variants (eSNVs). Non-SCID mice (estrogen supplemented) were implanted ≤ 30 minutes with PTB samples. Results: Of the first 78 pts, 44 have completed T. Here we focus on 18 pts with either triple negative or luminal B BC. Clinical characteristics according to Ki-67 response are shown in Table 1. Comparison of genomic alterations in BEAUTY pts with TCGA identified a greater overlap with copy number gains (73%) compared to deletions (40%), along with similar observations of mutations in TP53, PTEN, RYR2, and AKT1 genes. Association analysis of CNVs and eSNVs between responders/non-responders identified 33 genes (predominantly located in chromosomes 1, 8, 13) and 580 eSNVs (corresponding to 497 genes) with a p < 0.05. Differential gene expression (DGE) analysis of responders/non-responders identified 198 genes with a p-value < 0.05. Integrated analysis of 539 genes (CNVs, eSNVs and DGE) identified pathways such as TGF-beta, Jak-Stat, WNT and NOTCH signalling. PDX take rate was 44% [triple negative (6/10); Luminal B (2/8)]. PDX growth rate was significantly associated with clinical baseline Ki-67 (p = 0.00014). Conclusion: This is the first prospective study to demonstrate the feasibility of using PTB to obtain both NGS data and PDX in the neoadjuvant setting. PDX take rate is associated with BC subtype and baseline Ki-67. Studies are ongoing to 1) validate genes/pathways associated with treatment response in subsequent BEAUTY pts; 2) genomically characterize and assess PDX in vivo response to T and 3) Use NGS data to prioritize new drugs/drug combinations in PDX. Funded by Mayo Clinic Center for Individualized Medicine and MC Cancer Center. Clinical CharacteristicsOverallResponders: 12 week Ki-67 < 15% (n = 9)Non-Responders: 12 week Ki-67 ≥ 15% (n = 9)Median Age495345T stage T2/T314 (78%)7 (78%)7 (78%)Node Positive8 (44%)4 (44%)4 (44%)Triple negative10 (56%)6 (67%)4 (44%)Luminal B8 (44%)3 (33%)5 (56%)Ki-67 after 12 Weeks of T Median 5% (0-11%)Median 35% (17-60%)Complete/Partial MRI Response after T 6 (67%)2 (22%) Citation Information: Cancer Res 2013;73(24 Suppl): Abstract nr P1-08-10.

BACKGROUND The majority of patients diagnosed with clear cell renal cell carcinoma (ccRCC) have low‐risk disease with a < 10% chance of ccRCC‐specific death. DNA sequencing revealed that mutations in BAP1 (BRCA1 associated protein‐1) occur in 5% to 15% of ccRCC cases and are associated with poor outcomes. The vast majority of BAP1 mutations abolish protein expression. In this study, we used a highly sensitive and specific immunohistochemistry (IHC) assay to test whether BAP1 expression is an independent marker of ccRCC‐specific survival, particularly in patients with low‐risk disease. METHODS BAP1 expression was assessed, using IHC, in 1479 patients who underwent nephrectomy to treat clinically localized ccRCC. A centralized pathologist dichotomized patients as either BAP1‐positive or BAP1‐negative. The authors employed Kaplan‐Meier and Cox regression models to associate BAP1 expression with cancer‐specific survival. RESULTS A total of 10.5% of tumors were BAP1‐negative, 84.8% of tumors were BAP1‐positive, and 4.6% of tumors had ambiguous staining for BAP1. Patients with BAP1‐negative tumors have an increased risk of ccRCC‐related death (hazard ratio [HR] = 3.06; 95% confidence interval [CI] = 2.28‐4.10; P = 6.77 × 10 −14 ). BAP1 expression remained an independent marker of prognosis after adjusting for the UCLA integrated staging system (UISS) (HR = 1.67; 95% CI = 1.24‐2.25; P < .001). Finally, BAP1 was an independent prognostic marker in low‐risk patients with a Mayo Clinic stage, size, grade, and necrosis (SSIGN) score of ≤ 3 (HR = 3.24; 95% CI = 1.26‐8.33; P = .015). CONCLUSIONS This study used a large patient cohort to demonstrate that BAP1 expression is an independent marker of prognosis in patients with low‐risk (SSIGN≤ 3) ccRCC. Cancer 2014;1059–1067 . © 2014 American Cancer Society .

Abstract Increased angiogenesis and tumor-induced immune evasion are two mechanisms by which clear cell renal cell carcinoma (ccRCC) proliferate and metastasize; however, the relationship between these pathways in human ccRCC is poorly understood. We conducted a nested case–control study using 98 archived tumor samples from patients diagnosed with primary ccRCC between 1990 and 2006, half of which were identified by immunohistochemistry (IHC) as either programmed death ligand 1 (PDL-1)–positive or PDL-1–negative. RNAs were extracted from the formalin-fixed paraffin-embedded tumor slides and the expression of the VEGFA, VEGFR1, VEGFR2, and PDL-1 genes was quantified. We assessed the presence of tumor-infiltrating lymphocytes (TIL) by IHC for CD3, and then analyzed the relationship among VEGFA, VEGFR1, VEGFR2, CD3, and PDL-1. When analyzed as a continuous variable, PDL-1 protein expression by IHC inversely correlates with the expression of the three VEGF-related genes: VEGFA (r = −0.23; P = 0.01), VEGFR1 (r = −0.34; P &lt; 0.001), and VEGFR2 (r = −0.23; P = 0.01). When dichotomized, the PDL-1–positive cohort trended toward a lower expression of VEGFA (fold change = 0.72; P = 0.056) and VEGFR1 (fold change = 0.69; P = 0.057). In addition, there was a significant and positive relationship between the presence of TIL as assessed by IHC for CD3 and PDL-1 by IHC (r = 0.25; P = 0.015), and there was a trend toward an inverse relationship between TIL and VEGFA gene expression (r = −0.18; P = 0.089). In conclusion, this is the first demonstration of an inverse association between the angiogenesis and PDL-1 pathways in tumor samples from primary ccRCC, and this relationship may be related to the immunosuppressive effects of VEGF signaling. Cancer Immunol Res; 1(6); 378–85. ©2013 AACR.

Abstract Motivation: Batch effects are due to probe-specific systematic variation between groups of samples (batches) resulting from experimental features that are not of biological interest. Principal component analysis (PCA) is commonly used as a visual tool to determine whether batch effects exist after applying a global normalization method. However, PCA yields linear combinations of the variables that contribute maximum variance and thus will not necessarily detect batch effects if they are not the largest source of variability in the data. Results: We present an extension of PCA to quantify the existence of batch effects, called guided PCA (gPCA). We describe a test statistic that uses gPCA to test whether a batch effect exists. We apply our proposed test statistic derived using gPCA to simulated data and to two copy number variation case studies: the first study consisted of 614 samples from a breast cancer family study using Illumina Human 660 bead-chip arrays, whereas the second case study consisted of 703 samples from a family blood pressure study that used Affymetrix SNP Array 6.0. We demonstrate that our statistic has good statistical properties and is able to identify significant batch effects in two copy number variation case studies. Conclusion: We developed a new statistic that uses gPCA to identify whether batch effects exist in high-throughput genomic data. Although our examples pertain to copy number data, gPCA is general and can be used on other data types as well. Availability and implementation: The gPCA R package (Available via CRAN) provides functionality and data to perform the methods in this article. Contact: reesese@vcu.edu or eckel@mayo.edu Supplementary information: Supplementary data are available at Bioinformatics online.

Abstract The determination of HER2 amplification is critical to selecting appropriate patients for HER2 targeted therapy in breast cancer. Dual in situ hybridization (DISH), an alternative to fluorescence in situ hybridization (FISH) and immunohistochemistry, is now available. To compare the FISH and DISH methods, we tested 251 samples enriched for common or difficult-to-assess HER2 anomalies. Seven samples failed DISH testing. There was a 64% (156/244) concordance between FISH and DISH by anomaly (κ = 0.58, 95% confidence interval, 0.51-0.65; P &lt; .0001) and an 83% (203/244) concordance by amplification status (κ = 0.58; 95% confidence interval, 0.47-0.69; P &lt; .0001). DISH resulted in lower estimates of HER2/ centromere 17 ratios than FISH, and many cases that were equivocal with FISH were normal with DISH. DISH did not detect any case with coamplification of HER2 and centromere 17. Using a cohort of difficult specimens, we observed less than 95% concordance between FISH and DISH. DISH may underestimate the HER2/chromosome 17 ratio, or FISH may overestimate this ratio.

Genomewide association studies (GWAS) and candidate‐gene studies have implicated single‐nucleotide polymorphisms (SNPs) in at least 45 different genes as putative glioma risk factors. Attempts to validate these associations have yielded variable results and few genetic risk factors have been consistently replicated. We conducted a case‐control study of Caucasian glioma cases and controls from the University of California San Francisco (810 cases, 512 controls) and the Mayo Clinic (852 cases, 789 controls) in an attempt to replicate previously reported genetic risk factors for glioma. Sixty SNPs selected from the literature (eight from GWAS and 52 from candidate‐gene studies) were successfully genotyped on an Illumina custom genotyping panel. Eight SNPs in/near seven different genes (TERT, EGFR, CCDC26, CDKN2A, PHLDB1, RTEL1, TP53) were significantly associated with glioma risk in the combined dataset (P < 0.05), with all associations in the same direction as in previous reports. Several SNP associations showed considerable differences across histologic subtype. All eight successfully replicated associations were first identified by GWAS, although none of the putative risk SNPs from candidate‐gene studies was associated in the full case‐control sample (all P values > 0.05). Although several confirmed associations are located near genes long known to be involved in gliomagenesis (e.g., EGFR, CDKN2A, TP53), these associations were first discovered by the GWAS approach and are in noncoding regions. These results highlight that the deficiencies of the candidate‐gene approach lay in selecting both appropriate genes and relevant SNPs within these genes.

Abstract Background: Estrogen receptor (ER) expression in breast caner is an important biomarker for targeted therapy and outcome prediction. Nevertheless, the molecular mechanism that controls the phenotypic difference is little known. We used deep sequence technology to profile the transcriptome, gene copy number, and CpG island methylation simultaneously in eight commonly used breast cell lines to develop a model for how these genomic features are integrated in ER+ and ER- breast cancer. Materials and methods: Total mRNA sequence (mRNA-seq), gene copy number (DNA-seq), and genomic CpG island methylation (Methyl-seq) were carried out using the Illumina Genome Analyzer. Sequences were mapped to the human genome (hg18) to obtain digitized gene expression data, DNA copy number in reference to the non-tumor cell line (MCF10A), and methylation status of 21,570 CpG islands; differentially expressed genes between ER+ and ER- cell lines were selected and then correlated with methylation status of these genes’ CpG islands within 5kb of transcript start or copy number changes. The genes that appeared controlled by methylation or copy number changes in cell lines were further evaluated for their expression in the dataset of 129 primary breast tumors. Results: ER+ breast cancer cells had very different gene expression pattern from ER- cancer cells. The two cell line types formed two distinct clusters in unsupervised cluster and 1,873 genes were differentially expressed by moderated t statistics. We identified 149 differentially expressed genes that exhibited differential methylation of one or more CpG islands within 5kb of the 5’ end of the gene and for which mRNA abundance was inversely correlated with CpG island methylation status. Eighty nine of these 149 genes were also differentially expressed in the primary tumor samples and 84 of them were consistent with cell line gene expression and methylation data. The set of 149 genes were significantly enriched in the ER+ tumors by Gene Set Enrichment Analysis. Part of chromosome 8 was deleted in all ER- cells and part of chromosome 17 amplified in all ER+ cells. These loci encoded 30 genes that were overexpressed in ER+ cells; however, only 9 of these genes were overexpressed in ER+ tumors. Many of the methylation or CNA affected genes were functionally significant and some are known to be associated with breast cancer outcome such as GATA3 and LYN. Conclusions: A global pattern of differential CpG island methylation influences expression of a cohort of genes that contribute to the transcriptome landscape of ER+ and ER- breast cancer cells and tumors. The role of gene amplification/deletion in defining the transcriptome landscape of ER+ and ER- cells appears to more modest, although several potentially significant genes appear to be globally regulated by copy number aberrations. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 4908. doi:10.1158/1538-7445.AM2011-4908

Abstract Background: Gene expression profiling is an important tool in prediction, prognosis, and cancer modeling. The DASL® assay (cDNA –mediated Annealing, extension, Selection, and Ligation; Illumina; San Diego, CA) is a gene expression profiling system designed for degraded RNAs such as those derived from formalin-fixed paraffin-embedded (FFPE) tumor samples. FFPE tumor samples are invaluable resources for cancer research, being the most widely available materials for which patient outcomes are known. Purpose: The objective of this study was to evaluate the performance of Illumina's Whole Genome DASL platform (24,526; 24K) at distinguishing HER2-positive (HER2+) from HER2-negative (HER2-) FFPE breast tumors. Methods: We measured the relative gene expression of biological and technical replicates using nine HER2+ and 11 HER2- primary breast tumors from patients that were all node-positive and estrogen receptor-positive. The HER2 status of the tumors was determined using the Dako Hercept Test following the 2007 ASCO/CAP guidelines for HER2 positivity. The non-background corrected probe-expression data were exported from Illumina BeadStudio software and normalized using the software R and the function fastlo. Log2 transformed expression values were used to obtain the relative gene expression per probe. Spearman correlations were calculated between both types of replicates. Unequal-variance t-tests were conducted to test for differences in expression levels between HER2+ and HER2- tumors. An overall ERBB2 gene expression level was calculated by taking the average of the three ERBB2 probes for each tumor across all replicates. To simulate the possible outcome if only one replicate of each tumor was measured for gene expression, differential expression was tested for all possible combinations of single replicate probe expression values. Results: Spearman correlations for technical and biological replicates within tumor samples ranged from 0.9804 – 0.9946, and 0.9822 – 0.9945, respectively. The overall ERBB2 gene expression was significantly lower in HER2- tumors than in HER2+ tumors (p = 0.0000018). The top five most differentially expressed genes (p &lt; 0.0005) included ERBB2, GRB7, C17ORF37, PERLD1, and ASF1B. For each of the three ERBB2 probes, there were 65,536 possible ways to combine the individual probe expression values. The p-values for testing differential expression in each of these 65,536 combinations of HER2+ tumors versus HER2- tumors ranged from 0.00029 – 0.0091 for ILMN_1717902, 0.0000078 – 0.00026 for ILMN_1728761, and 0.000000002 – 0.0000032 for ILMN-2352131. Conclusions: Illumina's Whole Genome Platform provided highly reproducible gene expression values among biological and technical replicates of breast tumors. This platform also demonstrated significant differential ERBB2 gene expression between HER2+ and HER- breast tumors, which correctly classified the breast tumors as HER2+ and HER2-. Citation Information: Cancer Res 2009;69(24 Suppl):Abstract nr 6127.

Abstract The canonical Wnt signaling pathway is pathogenic in a variety of cancers. We previously identified aberrant expression of the Wnt pathway transcription factor and target gene lymphoid enhancer binding factor-1 (LEF1) in chronic lymphocytic leukemia (CLL). This suggested that the Wnt signaling pathway has a role in the biology of CLL. In this study, we performed a Wnt pathway analysis using gene expression profiling and identified aberrant regulation of Wnt pathway target genes, ligands, and signaling members in CLL cells. Furthermore, we identified aberrant protein expression of LEF-1 specifically in CLL but not in normal mature B-cell subsets or after B-cell activation. Using the T cell–specific transcription factor/LEF (TCF/LEF) dual luciferase reporter assay, we demonstrated constitutive Wnt pathway activation in CLL, although the pathway was inactive in normal peripheral B cells. Importantly, LEF-1 knockdown decreased CLL B-cell survival. We also identified LEF-1 expression in CD19+/CD5+ cells obtained from patients with monoclonal B-cell lymphocytosis, suggesting a role for LEF-1 early in CLL leukemogenesis. This study has identified the constitutive activation and prosurvival function of LEF-1 and the Wnt pathway in CLL and uncovered a possible role for these factors in the preleukemic state of monoclonal B-cell lymphocytosis.