1 CCR-11-2535 Re-Revised Title: Integrated Analysis Reveals Critical

Author Manuscript Published OnlineFirst on January 24, 2012; DOI: 10.1158/1078-0432.CCR-11-2535 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited.

CCR-11-2535 Re-Revised

Title: Integrated Analysis Reveals Critical Genomic Regions in Prostate Tumor-

Microenvironment Associated with Clinico-pathologic Phenotypes

Authors: Shingo Ashida1, Mohammed S. Orloff1,3, Gurkan Bebek1,8,10, Li Zhang1,2, Pan

Zheng5,6, Donna M. Peehl7 and Charis Eng1,3,4,9,10

Affiliations: 1Genomic Medicine Institute and 2Section of Statistical Genetics and

Bioinformatics, Department of Quantitative Health Sciences, Lerner Research Institute,

3Taussig Cancer Institute, and 4Stanley Shalom Zielony Institute for Nursing Excellence,

Cleveland Clinic, Cleveland, Ohio; 5Department of Pathology, The Ohio State University,

Columbus, Ohio; 6Division of Immunotherapy, Department of Surgery, and Program of

Molecular Medicine, Comprehensive Cancer Center, University of Michigan Medical Center,

Ann Arbor, Michigan; 7Department of Urology, Stanford University School of Medicine,

Stanford, California; 8Center for Proteomics and Bioinformatics, 9Department of Genetics and

10CASE Comprehensive Cancer Center, Case Western Reserve University School of Medicine,

Cleveland, Ohio

Corresponding Author: Charis Eng, MD, PhD, Cleveland Clinic Genomic Medicine Institute,

9500 Euclid Avenue, Mailstop NE-50, Cleveland, OH 44195 (email: [email protected])

Running Title: Integrated genome-wide analyses for prostate cancer-stroma

Key Words: Prostate tumor-stroma, LOH, clinico-pathologic correlates

Downloaded from clincancerres.aacrjournals.org on September 30, 2021. © 2012 American Association for Cancer Research. Author Manuscript Published OnlineFirst on January 24, 2012; DOI: 10.1158/1078-0432.CCR-11-2535 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited.

ABSTRACT

Purpose: Recent studies suggest that tumor microenvironment (stroma) is important in carcinogenesis and progression. We sought to integrate global genomic structural and expressional alterations in prostate cancer epithelium and stroma and their association with clinico-pathologic features.

Experimental Design: We performed a genome-wide loss-of-heterozygosity/allelic-imbalance

(LOH/AI) scan of DNA from epithelium and stroma of 116 prostate cancers. LOH/AI hot- or cold-spots were defined as the markers with significantly higher or lower LOH/AI frequencies compared with the average frequency for markers along the same chromosome. These data were then integrated with publicly-available transcriptome datasets and our experimentally- derived data. Immunohistochemistry on an independent series was utilized for validation.

Results: Overall, we identified 43 LOH/AI hot-/cold-spots, 17 in epithelium and stroma

(p<0.001), 18 only in epithelium (p<0.001), and 8 only in stroma (p<0.001). Hierarchical clustering of expression data supervised by genes within LOH/AI hot-/cold-spots in both epithelium and stroma accurately separated samples into normal epithelium, primary-cancer, and metastatic-cancer groups, which could not be achieved with data from only epithelium.

Importantly, our experimental expression data of the genes within the LOH/AI hot-/cold-spots in stroma accurately clustered normal-stroma from cancer-stroma. We also identified 15

LOH/AI markers that were associated with Gleason score, which were validated functionally in each compartment by transcriptome data. Independent immunohistochemical validation of

STIM2 within a stromal significant LOH marker (identified as associated with Gleason grade) confirmed its down-regulation in the transition from moderate to high Gleason grade.

Conclusions: Compartment-specific genomic and transcriptomic alterations accurately distinguish clinical and pathological outcomes, suggesting new biomarkers for prognosis and

targeted therapeutics.

Abstract Word Count: 249

Translational Relevance

Genome-wide loss-of-heterozygosity/allelic-imbalance (LOH/AI) analysis of DNA from epithelium and stroma of 116 prostate cancers revealed 43 LOH/AI hot-/cold-spots, 17 in both epithelium and stroma (p<0.001), 18 only in epithelium (p<0.001), and 8 only in stroma

(p<0.001). Integration of experimentally-derived transcriptome data of genes within the significant LOH/AI hot-/cold-spots in stroma revealed 15 LOH/AI markers that were associated with Gleason score. Independent immunohistochemical validation of one of these identified genes STIM2 within a stromal significant LOH marker (identified as associated with

Gleason grade) confirmed its down-regulation in the transition from moderate to high Gleason grade. Stromal genomic and transcriptomic alterations may be helpful in pinpointing aggressive prostate cancers.

INTRODUCTION

Previous studies have mainly focused on changes in the epithelium, but recent investigations have highlighted the tumor microenvironment as equally important in carcinogenesis and progression. Genetic changes in tumor stroma have been reported by several independent groups working on a range of solid tumors (1-19) , although typically, only selected markers have been used in most of these studies to assess loss-of-heterozygosity (LOH)/allelic imbalance (AI).

In prostate cancer (CaP), it has also been suggested that tumor microenvironment plays an important role in the progression, acquisition of androgen independence, and distant metastases (20-22). Tumor-microenvironment interactions through diffusible soluble factors such as transforming growth factor-beta (TGFB), as well as the extracellular matrix (ECM), likely lead to the development of metastasis (20). Nonetheless, little is known about the genetic basis of the human prostate tumor microenvironment; one report described genotypic heterogeneity in mesenchymal cells with a small number of markers (9) and another demonstrated allelic losses in the stromal component with a small number of samples and markers (23). These findings suggest that genetic alterations in CaP stroma exist and may be biologically relevant.

To attain a global perspective of epithelial- and stromal-specific LOH/AI changes for

CaP and further refine our understanding of the LOH/AI regions, we performed a genome-wide

LOH/AI scan using 381microsatellite markers, and subsequently integrated these structural data with publicly available and experimental expressional array analyses. We also sought to determine if compartment-specific LOH/AI could be correlated with clinico-pathologic

features. Finally, we performed two types of validation: functional genomic validation and immunohistochemistry in an independent series of CaP.

METHODS

Patients and Samples

We obtained 116 CaPs at any tumor classification with or without lymph node metastasis and analyzed them in accordance with the respective Institution’s Human Subjects Protection

Committees. All slides were re-reviewed by a single genito-urinary pathologist (P.Z.). Clinical information such as Gleason score, tumor volume, and the status of lymph node metastasis was noted (Suppl Table 1). An independent validation series of CaP are described under

Immunohistochemical Analysis.

Laser Capture Microdissection (LCM) and Genome-wide LOH/AI Scan

LCM of non-neoplastic normal tissue, epithelial carcinoma cells and tumor-associated stroma was performed from formalin-fixed paraffin-embedded tissue for all 116 cases, as previously described (7, 8, 17, 24, 25) and demonstrated at the link http://content.nejm.org/cgi/content/full/357/25/2543/DC2. Stromal fibroblasts resided in between aggregations of epithelial tumor cells or no more than 0.5 cm distant from tumor nodule. While epithelial-stromal cell cross-contamination is a possibility, we utilized standard and well-established protocols to minimize this, as reported previously (8, 18, 24, 25).

Corresponding normal DNA for each case was procured from normal tissue, located a distance away from the tumor or from a different tissue (formalin-fixed paraffin-embedded) block containing only normal tissue (latter first choice). Genomic DNA was extracted as previously

described, with the exception that incubation in proteinase K was done at 65°C for two days

(7). Primer sets for multiplex PCR defined 381 microsatellite markers in 72 multiplex panels

(Research Genetics, Invitrogen). Genotyping, analyses, and scoring of LOH/AI were done as reported (24, 26, 27). The methodological veracity of LOH/AI scan using multiplex-PCR on archived templates was extensively validated as published, i.e., by a series of control experiments using chromogenic in situ hybridization (CISH), quantitative PCR, etc., to eliminate the possibility of epithelial-stromal cell cross-contamination and to exclude any possibility of PCR artifact (24, 25).

Data Analysis

The dataset contains LOH/AI status at 381 microsatellite markers for 116 different samples, each with neoplastic epithelium, tumor stroma and normal tissue. The same 10 markers were never informative in at least one compartment and so excluded from further analyses. First, we sought to define regional LOH/AI hot-/cold-spots as the markers with significantly higher or lower frequency of LOH/AI compared with the average frequency of the markers along the same chromosome. We analyzed hot- and cold-spots of LOH/AI together with the concept that the genetic endpoint may be similar, eg, loss of a tumor suppressor gene and gain (cold spot) of an oncogenic event. Toward those ends, for each informative marker, the statistical significance of overall (across all samples) LOH/AI frequency compared with the respective chromosome average was analyzed using the exact binomial test (R base package binom.test; http://www.r-project.org). Second, the associations of LOH/AI across all informative markers

(not just hot/cold-spot markers) in epithelial and stromal samples with presenting clinico- pathologic features (i.e., Gleason score, tumor volume, and the status of lymph node

metastasis) were analyzed using a logistic model with LOH frequency as an outcome and each clinico-pathologic feature as a predictor (28, 29). Multiple testing adjustment was applied by controlling false positive report probability (FPRP) (30) with a prior probability of 0.05 or 0.01.

The FPRP indicates the probability that a statistically significant finding is a false positive by considering 3 factors: the P value magnitude, the statistical power, and the prior probability of true associations. Only those with P values<0.05 and estimated FPRP values less than 50%, indicating a small probability of being a false positive, are reported as statistically significant findings. An FPRP value with a prior probability of 0.05 and less than 50% is denoted as

FPRP0.05<0.5. We used more strict criteria, FPRP0.01<0.1, for LOH/AI hot-/cold-spots expecting higher significant regions. For the association of LOH/AI with clinico-pathologic features, we applied FPRP0.05<0.5. For the positive correlation of LOH/AI with Gleason score,

P value is obtained by one-side trend test (R, prop.trend.test) with false discovery rate (FDR) being controlled for correcting multiple testing.

Integration of Public Microarray Data with LOH/AI Data

Raw data from Gene Expression Omnibus (GEO) series GSE3325 at GEO platform GPL570

(Affymetrix HG-U133_Plus_2) were downloaded (31) and normalized using Robust Multi- array Averaging (RMA) (32). The GSE3325 data included 13 individual benign, primary and metastatic CaPs, and 6 pooled samples from benign, primary or metastatic CaPs. These specimens were grossly dissected maintaining at least 90% of the tissue of interest, based on examination of the frozen sections of each tissue block. We integrated microarray data of the genes residing within the regions that showed significant LOH/AI with our genetic data. We sought to utilize the expression microarray data in order to validate our LOH/AI hot-/cold-spots

and to identify the significant genes and pathways in prostate carcinogenesis or progression.

Throughout this study, we consistently selected all genes, that are located within 250kb upstream and downstream of the LOH/AI regions of interest (significant hot/coldspots), that have significant expression values and that are included in each microarray dataset, for hierarchical clustering analyses. All hierarchical clustering analyses in this study were performed using Cluster and TreeView softwares (http://rana.lbl.gov/EisenSoftware.htm) (33).

Genes belonging to hot-/cold-spots in both epithelium and stroma or in only epithelium were selected and hierarchical clustering was conducted to both genes and samples.

Generation of Prostatic Stroma Microarray and Integration with LOH/AI Data

We generated stromal microarray expression data for functional validation of our LOH/AI hot-

/cold-spots in stroma because we could not find appropriate public microarray datasets for prostatic stroma. Stromal cells cultured from normal peripheral zone tissues (F-PZ-64, F-PZ-79,

F-PZ-82, F-PZ-102, F-PZ-105) and from tumors (F-CA-31, F-CA-39, F-CA-52, F-CA-67, F-

CA-93) were established and grown as previously described (34). Total RNAs were extracted from semi-confluent cells (passages 4-5) one day after feeding fresh medium using RNeasy

Mini Kit (Qiagen) according to the manufacturer’s instructions and treated with TURBO DNA- free kit (Ambion). Hybridizations were performed according to Illumina protocols by the

Genomic Core, Lerner Research Institute, Cleveland Clinic. All samples were hybridized to the Illumina Sentrix Human-6_v3 Expression BeadChip, which contains 48,000 distinct oligonucleotide probes. These transcriptome data are deposited in GEO (GSE34312 [not publicly released yet]). After normalization using average normalization algorithm of

BeadStudio Gene Expression Module v3.4 (Illumina), we selected all the genes within +/- 250

kb of LOH/AI hot-/cold-spots in only stroma and applied a hierarchical clustering method to both genes and samples.

Integration of Microarray data with LOH/AI Regions Associated with Clinico-pathologic

Features

We selected all the genes lying within and +/-250 kb of the significant LOH/AI markers associated with Gleason score or tumor volume in both epithelium and stroma. With the genes associated with Gleason score or tumor volume, a hierarchical clustering was performed for epithelium using public microarray data, GSE3325 and for stroma using our stromal microarray data (31).

Immunohistochemical Analysis

Formalin-fixed and paraffin-embedded CaP sections from 49 independent cases were immunostained with a rabbit anti-STIM2 polyclonal antibody (Abcam Inc., Cambridge, MA) for STIM2 expression in CaP stroma. Both Gleason grade 3 (G3) and Gleason grade 4 and/or 5

(G4/5) lesions were examined for each case. Deparaffinized tissue sections were placed in 10 mM citrate buffer (pH 6.0) and were heated to 125°C in a Decloaking Chamber (Biocore

Medical, Concord, CA) for 30 seconds for antigen retrieval. These sections were then incubated with a 1:300 dilution of primary antibody overnight at 4°C, secondary antibody and the avidin-biotin complex (VECTASTAIN Elite ABC Kit; Vector Laboratories, Inc.,

Burlingame, CA), and developed with diaminobenzidine. Sections were counterstained with hematoxylin. For negative controls, primary antibody was omitted. Stromal expression of

STIM2 was determined by counting sum of intensities of positive stromal cells divided by area

of stroma, using Image-Pro Plus 7.0 (Media Cybernetics, Inc., Bethesda, MD). Five random fields were analyzed with a magnification of 40x. STIM2 expression in tumor stroma was divided by those in normal stroma for normalization. The statistical significance of STIM2 expression levels between G3 and G4/5 lesions was determined with Wilcoxon sign rank test.

RESULTS

LOH/AI Hot-/cold-spots in CaP

Overall, 371 markers across all chromosomes, ranging from 7 on chromosome 22 to 31 on chromosome 1, were analyzed: 38,460 PCR-reactions (19,639 for epithelium, 18,821 stroma) were informative for LOH/AI evaluation. We identified a total of 43 hot-/cold-spots, 17 occurring in both epithelium and stroma, 18 only in the epithelium, and 8 only in the stroma

(Table 1). No known genes were contained at 7 loci (D1S2134, D3S2427, D4S2417, D6S1277,

D9S922, D12S2078, and D14S606), however, we found ESTs at these loci (Table 1). Genes belonging to hot-/cold-spots common to both epithelium and stroma include HOXB1-HOXB9 cluster, HOXB13, ZNF554, ZNF555, ZNF556, ZNF57, and ZNF77 as well as 7 miRNA (Table

1). FGF12, ACVRIB, the KRT cluster and APOL1- APOL4 as well as 6 miRNAs were included in the genes lying in hot-/cold-spots of LOH/AI in epithelium only (Table 1), and TGFB1I1,

WFDC5, WFDC12 and TP53TG5 as well as 5 non-coding RNAs, notably miR-125b-1, were among the genes of hot-/cold-spots in stroma only (Table 1).

Association of LOH/AI with Presenting Clinico-pathologic Features

LOH/AI markers in association with clinico-pathologic features (Suppl Table 1) may reveal clues to clinical behavior and biological diversity and/or serve as biomarkers of prognosis or

therapeutic options. Using logistic regression, we analyzed our genome-wide LOH/AI scan across all informative markers in order to identify compartment-specific loci that were significantly associated with aggressiveness of disease as reflected by Gleason score, tumor volume, and regional nodal status. We identified 15 LOH/AI regions, 10 in epithelium and 5 in stroma, associated with Gleason score (Table 2), 11 (8 in epithelium and 3 in stroma) of which showed a positive correlation with increasing Gleason score (one-sided trend test, FDR<0.05;

Suppl Table 2). Among these 11 markers, 8 (6 in epithelium and 2 in stroma) remained significantly positively correlated with Gleason score even when a more rigorous method was applied (Bonferroni adjusted p<0.05). In association with tumor volume, 40 markers were identified in epithelium and 35 in stroma (Suppl Table 3). Interestingly, there were no significant LOH/AI markers correlated with regional nodal metastases.

Expression Profiling of Genes within LOH/AI Hot-/cold-spot Regions Using Publicly

Available Neoplastic Epithelial Microarray Data

We focused on genes of LOH/AI hot-/cold-spot regions and analyzed their expression profiles using publicly available microarray data (see METHODS). This served two purposes. First, this acts as a functional (transcript-expressional) validation of the genetic data. Second, integration of the genetic and expressional data would lend clues to the compartment-specific functions of the genes within the hot-/cold-spot regions as they relate to progression and prognosis. Hierarchical cluster analysis supervised by 87 genes found in LOH/AI hot-/cold- spot regions +/-250kb resulted in 3 distinct groups: normal epithelium, cancer, and metastatic cancer when considering genetic information from both epithelium and stroma (Figure 1A).

When we used 61 genes residing within the LOH/AI hot-/cold-spot +/-250kb regions occurring

specifically in epithelium, only two groups could be clearly distinguished, namely, normal epithelium and metastatic cancer groups (Figure 1B). Interestingly, the primary cancer samples were equally clustered with normal epithelium or with metastatic disease.

Expression Profiling of Genes within LOH/AI Hot-/cold-spot Regions Using Our

Experimentally Generated Stromal Microarray Data

We performed a hierarchical clustering of stromal cells, supervised by 28 genes of LOH/AI hot-/cold-spot +/- 250kb regions from stroma only (Figure 2). This accurately separated normal stromal cells and cancer-derived stromal cells.

Expression Profiling of Genes within LOH/AI Regions Associated with Clinico-pathologic

Features

We further focused on genes residing in proximity to our LOH/AI regions associated with

Gleason score and tumor volume, and analyzed their expression profiles using publicly available microarray data (see METHODS) for epithelial analysis as well as our experimentally generated expression data for stromal analysis. With only one exception, P3, in neoplastic epithelial analysis, samples were clearly separated into normal, primary cancer, and metastatic disease by 31 genes within the LOH/AI (+/- 250kb) regions in neoplastic epithelium associated with Gleason score (Suppl Figure 1A). Our stromal cell cultures derived from normal tissues and from CaP were accurately clustered supervised by the 18 genes belonging to our stroma- only LOH/AI (+/- 250kb) regions associated with Gleason score (Suppl Figure 1B). As for tumor volume, epithelial CaP samples were also successfully separated into normal, primary cancer and metastatic disease in epithelial analysis (Suppl Figure 2A). In contrast, our stromal

cell cultures did not cluster into tumor-derived stroma and normal stroma groups in stromal analysis for tumor volume (Suppl Figure 2B).

Independent Validation of Candidate Gene by Immunohistochemical Analysis

To further validate our genetic data, we selected our strongest candidate gene, STIM2, lying in

D4S2397, which is the most significant stromal-associated LOH marker correlated with

Gleason score (Suppl Table 2). We examined STIM2 expression in 49 independent primary

CaP samples that had both Gleason grade 3 and Gleason grade 4 and/or 5 lesions by immunohistochemical analysis (Figure 3). Stromal protein expression of STIM2 (Y-axis) showed significant down-regulation in the stroma of G4/5 lesions compared to that of G3 lesions (p<0.001; Figure 3A).

DISCUSSION

Recent molecular studies have provided a myriad of information about genetic changes in CaP and accumulating data over the last two decades have shown the importance of the tumor stroma in prostate carcinogenesis, with the latter based on mainly functional and cell biological studies. Here, we have completed a genome-wide LOH/AI scan and integrated these data with global expression array data for CaP epithelium and stroma, and correlated these with presenting clinico-pathologic features, and validated our observations via functional genomics approach and immunohistochemistry of a newly identified stromal-relevant gene associated with Gleason score.

First, genome-wide LOH/AI scan revealed LOH/AI hot-/cold-spots that were important in each compartment alone and in both compartments. Among the 225 genes in proximity to

the 43 LOH/AI hot-/cold-spot regions germane to epithelium and/or stroma, several candidate tumor suppressor genes, such as HOXB13 (epithelium and stroma), the APOL1-4 cluster and

ACVR1B (epithelium), and TP53TG5 (stroma), are notable. The APOL family of genes

(APOL1-6) encodes programmed cell death proteins that can initiate apoptosis or autophagic cell death, as well as belong to a multi-component innate immunity complex-building platform

(35). Thus, loss-of-function of the APOL1-4 region will lead to loss of apoptosis and autophagic cell death regulation as well as potential decreased innate immunity locally. Our observations here, ie, loss of APOL1-4 function leading to loss of autophagic cell death and consequent loss of essential nutrients and energy to tumor epithelial cells in a paracrine fashion are consistent with the autophagic tumor stroma model of cancer metabolism underscored by

Lisanti’s body of work (36). Furthermore, the relevance to innate immunity lends credence to early hypotheses of metabiomic relationships in initiating various neoplasias (35, 37), including that of the prostate. Of note, the activin-TGFB signaling sub-network has already been acknowledged to be important in prostate carcinogenesis (38). We have shown that D12S297 harbors the human activin receptor, ACVR1B, which has been described as having somatic mutations and deletions in at least 4 other types of cancers, and which is expressed in prostate epithelium (39). ACVR1B encodes an activin receptor that signals via the TGFB pathway as well.

Second, we found 15 specific loci of LOH/AI in the epithelium or stroma associated with Gleason score (Table 2). We suspect that these regions and genes are relevant to invasion and progression and focused especially on stroma. Two loci (4p15.2 and 19p13.3) harbored significant LOH/AI in the stroma, correlated with Gleason score. One of the genes located in the 4p15.2, which is the most significant region, is STIM2 (stromal interaction molecule 2).

Our immunohistochemical analysis of 49 independent CaP samples has given us an in-principle validation of our genetic and functional-genomic studies. STIM1 was originally proposed as a candidate tumor suppressor and regulates intracellular calcium (40, 41). STIM2 is also a transmembrane protein, that, in limited studies, has been shown to mediate cellular proliferation (42). In view of our observations, further studies on the role of STIM2 in different cancers, especially in different compartments, are required. The 19p13.3 region contains AES which is known to be associated with Wnt signaling pathway and MAPK/ERK1, which is an upstream kinase for NF-kappaB activation (43, 44). The cluster of ZNFs including ZNF77 also at the 19p13.3 region was previously associated with different cancers, and ZNF77 status has been used as a prognostic marker in early stage renal cell carcinomas and stage I breast cancers to predict recurrence (45, 46).

We subsequently integrated global transcriptome data from public archives and those we experimentally derived with our LOH/AI hot-/cold-spots. Importantly, these provided functional validation of our genomic data. The gene expression profile using neoplastic epithelium from public sources with only genes from our epithelium-related LOH hot-/cold- spots, which is not the entire epithelium gene expression profile, could not accurately cluster the samples. Similarly, we also attempted the cluster analysis supervised by the genes from only stromal hot-/cold-spots, and as expected, it resulted in failure to cluster the samples (data not shown). In contrast, these samples could be accurately clustered when taking into account the genes from the stromal hot-/cold-spots, indicating that genomic alterations with consequent expressional alterations in the stroma are necessary and play an important role in prostate carcinogenesis and progression. Equally important is a notable negative. The genes within the

LOH hot/coldspot regions identified as important in correlating with tumor volume were

germane only in the epithelium. This was validated when expression data supervised by the genes within the LOH hot/coldspot regions relevant to tumor volume could not accurately classify normal stroma from tumor stroma (Suppl Figure 2B). In other words, at least in CaP, tumor volume does not appear to be influenced by stromal genomic or expressional alterations of genes located within tumor volume-associated stromal LOH regions in this study. This makes teleological logic given that the genes playing roles in tumor stroma are almost certainly relevant to invasion, progression and metastasis, as noted above.

By integrating genomic and global expression data for the epithelium and stroma of

CaP, we were able to detect significant regions and candidate genes important in the tumor- microenvironment crosstalk that leads to carcinogenesis and progression. Importantly, we have performed functional genomic validation of the genes in the regions associated with Gleason score as well as tumor volume, in a compartment-specific manner, as well as validated a stromal gene associated with Gleason score in an independent series of tumors using a different technique, namely, immunohistochemistry for STIM2, as proof of principle. Parenthetically, we also noted that the epithelial expression of STIM2 (D4S2397 is also a significant epithelial- associated LOH marker correlated with Gleason score as well) was down-regulated in G4/5 over G3. However, we did not formally analyze the epithelial expression in this study because the effect size did not appear as marked as for stroma. These data provide fundamental insights into compartment-specific roles in prostate carcinogenesis or progression and may also reveal the solid tumor microenvironment as a novel compartment for important biomarkers of prognosis as well as targeted therapy.

Acknowledgements and Grant Support

We thank the members of the Eng laboratory over the years for technical assistance and helpful discussion. This work was funded in part by the Department of Defense US Army Prostate

Cancer Research Program (to CE). CE holds the Sondra J. and Stephen R. Hardis Endowed

Chair of Cancer Genomic Medicine at the Cleveland Clinic, and the ACS Clinical Research

Program, funded in part by the F.M. Kirby Foundation.

FIGURE LEGENDS

Figure 1. Dendrogram and heatmap of hierarchical clustering analysis using 19 prostatic samples from public microarray database. A, Supervised by 87 genes within LOH/AI hot-/cold-spots +/- 250 kb in epithelium and stroma. In the sample axis, samples were clearly separated into three classes. In the gene axis, the genes were clustered in different branches according to similarities in relative expression. B, Supervised by 61 genes within LOH/AI hot-/cold-spots +/- 250 kb in only epithelium. Note that supervision only by the genes within epithelial hot-/cold-spots resulted in the primary tumors not being able to be classified correctly and were instead sorted equally as normal prostate or metastatic disease. This is in contrast to A where genomic information from both epithelium and stroma was integrated with expression array data. N, benign prostate; P, primary CaP; W, metastatic CaP samples; NX, PX, or WX, respective mixtures of benign, primary, or metastatic CaP samples (i.e. NX1 indicates the mixture of N1-4 and NX2 is the duplicate of NX1). Red, the transcript level is above the median for that gene across all samples; green, below the median for that gene across all samples; black, unchanged expression; gray, no detectable expression.

Figure 2. Dendrogram and heatmap of hierarchical clustering analysis supervised by 28 genes within stromal LOH/AI hot-/cold-spots +/- 250 kb across 10 stromal cell cultures derived from normal tissues (F-PZ) or tumors (F-CA). Note that cell cultures were accurately clustered into each group according to origin. VKORC1 and ROCK2 that appear twice and show different profiles represent probe sets that recognize different splice isoforms. Colors, sample names, and the other conditions are the same as those of Figure 1.

Figure 3. Immunohistochemical Analysis reveals decreased STIM2 expression in the stroma of Gleason grade 4 and/or 5 (G4/5) regions compared to that of Gleason 3 regions. A, The evaluation in immunohistochemical staining of CaP stroma with anti-STIM2 antibody, indicating that STIM2 gene expressions were significantly down-regulated in G4/5 in comparison with G3 (Wilcoxon sign rank test, p<0.001). X axis shows Gleason grade and Y axis indicates stromal expression of STIM2 (see METHODS). B, Representative staining lesions of G3 and G4/5 for the same case are shown (400x).

Table 1. LOH/AI Hot-/cold-spots in Prostate Cancer

In Epithelium and Stroma P Valuea Genes miRNAs Markers Loci Ep St (within ±250kb of markers) (within ±2Mb) FCRL1, FCRL2, CD5L, KIRREL, D1S1653 1q23.1 <0.001 <0.001 CD1D mir-9-1 TPO 2p25.3 <0.001 <0.001 SNTG2, TPO, PXDN ZBBX, SERPINI2, WDR49, PDCD10, D3S1763 3q26.1 <0.001 <0.001 SERPINI1 DGKG, CRYGS, TBCCD1, DNAJB11, D3S1262 3q27.3 <0.001 <0.001 AHSG, FETUB, HRG, KNG1 PRKAA1, RPL37, SNORD72, CARD6, D5S1457 5p13.1 <0.001 <0.001 C6, C7, HEATR7B2 ARSB, DMGDH, BHMT, BHMT2, JMY, D5S1501 5q14.1 <0.001 <0.001 HOMER1 ARPC5L, GOLGA1, C9orf126, PPP6C, mir-181a, mir-181b- D9S1825 9q33.3 <0.001 <0.001 RABEPK, HSPA5, GAPVD1 2 D12S269 12p13.1 <0.001 <0.001 EMP1, C12orf36, GRIN2B CCDC60, LOC387890, PRKAB1, CIT, D12S395 12q24.23 <0.001 <0.001 CCDC64 D12S2078 12q24.32 <0.001 <0.001 ESTs D13S285 13q34 <0.001 <0.001 SOX1, C13orf28 D14S588 14q24.1 <0.001 <0.001 KIAA0247, SFRS5, SLC10A1, SMOC1 D15S816 15q26.2 <0.001 <0.001 MCTP2 D16S764 16p13.11 <0.001 <0.001 LOC339047 SKAP1, HOXB1 through HOXB9, mir-10a, mir-196-1, D17S2180 17q21.32 <0.001 <0.001 HOXB13, PRAC2, C17orf92, TTLL6 mir-152 CALCOCO2 ZNF554, ZNF555, ZNF556, ZNF57, D19S591 19p13.3 <0.001 <0.001 ZNF77, TLE2, TLE6, AES, GNA11 mir-7-3 GNA15, S1PR4, NCLN, BRUNOL5 SOX12, NRSN2, TRIB3, RBCK1, D20S103 20p13 <0.001 <0.001 TBC1D20, CSNK2A1, TCF15, SRXN1 SCRT2, C20orf54

In Epithelium Only miRNAs Markers Loci P Valuea Genes (within ±250kb of markers) (within ±2Mb) D1S1612 1p36.23 <0.001 PER3, UTS2, TNFRSF9, PARK7, ERRFI1 mir-34a D1S2134 1p33 <0.001 ESTs ZRANB3, R3HDM1, UBXN4, LCT, MCM6, D2S1334 2q21.3 <0.001 DARS mir-128a D3S1286 3p24.3 <0.001 HACL1, BTD, ANKRD28 D3S1746 3q25.1 <0.001 AADAC, SUCNR1 D3S2427 3q26.31 <0.001 ESTs D3S2418 3q28 <0.001 FGF12, C3orf59 D4S2417 4q34.3 <0.001 ESTs D6S437 6q25.3 <0.001 SYNJ2, SERAC1, GTF2H5, TULP4,

TMEM181 D6S1277 6q26 <0.001 ESTs D9S922 9q21.31 <0.001 ESTs D10S2470 10q23.31 <0.001 HTR7 mir-107 ACVR1B, GRASP, NR4A1, C12orf44, KRT80 D12S297 12q13.13 <0.001 through KRT86 mir-196-2 KRT7, KRT75, KRT6B, KRT6C D13S800 13q22.1 <0.001 KLF5 JPH3, LOC100129637, KLHDC4, SLC7A5, D16S2621 16q24.2 <0.001 CA5A, BANP D17S1294 17q11.2 <0.001 SSH2, EFCAB5, CCDC55, SLC6A4, BLMH mir-193, mir-144 GSTT2, GSTT2B, DDTL, DDT, GSTTP1, D22S345 22q11.23 <0.001 GSTT1, GSTTP2 CABIN1, SUSD2, GGT5, POM121L9P, SPECC1L D22S683 22q12.3 <0.001 RBM9, APOL1 through APOL4, MYH9

In Stroma Only a miRNAs Markers Loci P Value Genes (within ±250kb of markers) (within ±2Mb) D1S1594 1q43 <0.001 FMN2, GREM2, RGS7 D2S1400 2p25.1 <0.001 ROCK2, E2F6, GREB1, NTSR2 D2S434 2q35 <0.001 DIRC3, TNS1 mir-26b, mir-153-1 GRAMD1B, SCN3B, ZNF202, OR6X1, mir-100, let-7a-2, D11S4464 11q24.1 <0.001 OR6M1 mir-125b-1 PMP22CD, OR8D4, OR4D5, OR6T1, OR10S1 D12S1045 12q24.33 <0.001 TMEM132D, LOC100190940, FZD10 D14S606 14q31.1 <0.001 ESTs STX4, ZNF668, ZNF646, POL3S, VKORC1, D16S753 16p11.2 <0.001 BCKDK MYST1, PRSS8, PRSS36, FUS, PYCARD, TRIM72 PYDC1, ITGAM, ITGAX, ITGAD, COX6A2, ZNF843 ARMC5, TGFB1I1, SLC5A2, C16orf58 YWHAB, PABPC1L, TOMM34, STK4, D20S481 20q13.12 <0.001 KCNS1, WFDC5 WFDC12, PI3, SEMG1, SEMG2, SLPI, MATN4, RBPJL SDC4, SYS1, DBNDD2, TP53TG5 aMultiple testing adjustment is based on FPRP0.01<0.1

Table 2. LOH/AI in Epithelium and Stroma Associated with Gleason Score

Gleason Score and LOH/AI in Epithelium Gleason<=6 Gleason=7 Gleason>=8 Markersa Loci ROH LOH ROH LOH ROH LOH P Valueb D1S1612 1p36.23 42 5 14 7 2 5 0.001 D1S1597 1p36.21 33 15 7 15 2 2 0.014 D4S2397 4p15.2 36 9 7 12 2 3 0.002 D5S1470 5p13.3 31 22 4 17 2 5 0.004 D5S1462 5q15 28 20 4 16 4 2 0.008 D8S1477 8p12 30 17 6 15 2 7 0.005 D13S317 13q31.1 23 16 4 16 4 3 0.012 D15S659 15q21.1 32 23 5 18 1 6 0.002 D16S2624 16q22.3 38 11 3 15 6 3 <0.001 D22S277 22q12.3 38 18 6 17 3 5 0.002

Gleason Score and LOH/AI in Stroma Gleason<=6 Gleason=7 Gleason>=8 Marker Loci ROH LOH ROH LOHROH LOH P Valueb D2S1400 2p25.1 41 12 10 12 6 2 0.028 D4S2397 4p15.2 31 13 5 14 1 4 0.001 D4S1647 4q23 31 22 5 16 4 4 0.023 D9S1825 9q33.3 41 10 11 11 6 4 0.028 D19S591 19p13.3 45 8 15 4 3 6 0.007 aThree markers, which are associated with Gleason score, were excluded because missing in more than half. bMultiple testing adjustment is based on FPRP0.05<0.5 ROH, retention of heterozygosity; LOH, loss of heterozygosity

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Downloaded from clincancerres.aacrjournals.org on September 30, 2021. © 2012 American Association for Cancer Research. Fig 1A N2 N1 N3 N4 NX1 NX2 P3 P4 P1 P2 PX1 PX2 P5 W1 W2 WX1 WX2 W3 W4 C7 C6 FCRL1 EMP1 EMP1 EMP1 ZNF554 CARD6 CD1D RPL37 CSNK2A1 CSNK2A1 CSNK2A1 ARSB GOLGA1 ZNF555 DGKG CALCOCO2 CALCOCO2 CSNK2A1 CSNK2A1 SRXN1 TBC1D20 HOXB13 HOXB13 PRKAA1 PRKAA1 PRKAA1 TBC1D20 C17orf92 MCTP2 MCTP2 SFRS5 SFRS5 C20orf54 HSPA5 SERPINI1 DMGDH BHMT2 BHMT2 KIRREL SMOC1 FCRL1 SMOC1 ZNF555 KNG1 NRSN2 PRKAB1 RABEPK ARSB FCRL2 FCRL2 ARSB HRG Author Manuscript Published OnlineFirst on January 24, 2012; DOI: 10.1158/1078-0432.CCR-11-2535CD5L Author manuscripts have been peer reviewed and accepted for publicationHOMER1 but have not yet been edited. CCDC60 ARSB PXDN PXDN CCDC64 HRG GRIN2B FCRL2 RABEPK GRIN2B AES GNA11 GNA11 GNA11 ZNF554 SOX12 FETUB SOX1 ARPC5L ARPC5L ARPC5L ARPC5L DNAJB11 HOXB5 C9orf126 CIT HOXB7 HOXB7 HOXB6 HOXB2 HOXB3 ZBBX HOXB7 TLE6 HOXB9 PRKAB1 HOXB4 CCDC64 TRIB3 BRUNOL5 HOXB5 SOX12 TTLL6 ZNF77 ZNF77 BHMT BRUNOL5 GAPVD1 HOXB8 HOMER1 KIAA0247 HOMER1 SOX1 SERPINI2 WDR49 WDR49 SKAP1 SNTG2 TLE6 GAPVD1 PDCD10 GAPVD1 GAPVD1 TBCCD1 TLE2 TLE2 GOLGA1 PPP6C PPP6C ZNF57 AHSG CRYGS FCRL2 GNA15 AHSG KNG1 NCLN HOXB3 TCF15 ZNF556 HOXB8 S1PR4 EMP1 HOXB1 KIRREL SLC10A1 KIRREL C20orf54 TPO C13orf28 ZNF555 HOXB9 ZNF555 RBCK1 Downloaded from clincancerres.aacrjournals.org on September 30, 2021. © 2012RBCK1 American Association for Cancer Research. TRIB3 Fig 1B N2 N1 N3 N4 NX1 NX2 P2 P5 PX1 PX2 P1 P4 P3 W1 W2 W3 W4 WX1 WX2 BANP BANP BANP ACVR1B SSH2 CA5A ANKRD28 ERRFI1 Author Manuscript Published OnlineFirst on January 24, 2012; DOI: 10.1158/1078-0432.CCR-11-2535KRT75 Author manuscripts have been peer reviewed and accepted for publicationAADAC but have not yet been edited. SSH2 C12orf44 SSH2 HTR7 KRT83 KRT86 KLF5 ANKRD28 ANKRD28 SLC7A5 TMEM181 BLMH MCM6 SSH2 KRT80 MCM6 JPH3 TULP4 TULP4 TULP4 KLHDC4 DDT SUCNR1 LCT GRASP JPH3 APOL2 SYNJ2 SLC6A4 ZRANB3 CABIN1 CABIN1 KRT81 NR4A1 EFCAB5 KRT82 SUSD2 SUSD2 UTS2 APOL1 APOL3 GGT5 BTD APOL2 GSTT1 HTR7 ACVR1B ACVR1B SYNJ2 APOL4 APOL4 SYNJ2 GTF2H5 SERAC1 SYNJ2 SYNJ2 KRT85 MYH9 FGF12 FGF12 FGF12 EFCAB5 SLC6A4 HTR7 JPH3 HTR7 SLC6A4 ACVR1B GSTT2 BTD NR4A1 SPECC1L APOL4 KRT7 PARK7 HACL1 UBXN4 UBXN4 UBXN4 C3orf59 RBM9 DARS DARS CCDC55 RBM9 PER3 RBM9 PER3 ZRANB3 KLF5 R3HDM1 TNFRSF9 UTS2 KRT6B Downloaded from clincancerres.aacrjournals.org on September 30, 2021. © PER32012 American Association for Cancer Research. TNFRSF9 Author Manuscript Published OnlineFirst on January 24, 2012; DOI: 10.1158/1078-0432.CCR-11-2535 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited.

Fig 2 F-PZ-64 F-PZ-79 F-PZ-82 F-PZ-102 F-PZ-105 F-CA-31 F-CA-93 F-CA-52 F-CA-39 F-CA-67 BCKDK C16orf58 POL3S MYST1 STK4 ROCK2 STX4 TGFB1I1 ZNF668 ARMC5 SYS1 VKORC1 SDC4 FMN2 KCNS1 TOMM34 SLPI ZNF202 DBNDD2 TGFB1I1 TNS1 FUS GREB1 SEMG1 ZNF646 GREM2 ROCK2 PYCARD PYCARD E2F6 YWHAB Downloaded from clincancerres.aacrjournals.org onYWHAB September 30, 2021. © 2012 American Association for Cancer VKORC1Research. Author Manuscript Published OnlineFirst on January 24, 2012; DOI: 10.1158/1078-0432.CCR-11-2535 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited.

Integrated Analysis Reveals Critical Genomic Regions in Prostate Tumor-Microenvironment Associated with Clinico-pathologic Phenotypes

Shingo Ashida, Mohammed Orloff, Gurkan Bebek, et al.

Clin Cancer Res Published OnlineFirst January 24, 2012.

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