00019606-200712000-00001ArticleDiagnostic Molecular PathologyDiagnostic Molecular Pathology© 2007 by Lippincott Williams & Wilkins.16December 2007
p 189-197Global Expression Analysis of Prostate Cancer-associated Stroma and EpitheliaOriginal ArticlesRichardson, Annely M. BS* †; Woodson, Karen PhD‡; Wang, Yonghong PhD§; Rodriguez-Canales, Jaime MD*; Erickson, Heidi S. PhD*; Tangrea, Michael A. PhD*; Novakovic, Kristian MD∥; Gonzalez, Sergio MD¶; Velasco, Alfredo MD♯; Kawasaki, Ernest S. PhD**; Emmert-Buck, Michael R. MD, PhD*; Chuaqui, Rodrigo F. MD*; Player, Audrey PhD***Pathogenetics Unit†HHMI-NIH Research Scholar‡Methylation Lab§SAIC-Frederick, Inc, National Cancer Institute at Frederick, Frederick, MD∥Urologic Oncology Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD¶Pathology♯Urology, Catholic University, Santiago, Chile**Microarray FacilitySupplementary tables and figures are available at http://www.molecularpathology.com.Reprints: Annely M. Richardson, BS, Pathogenetics Unit/HHMI-NIH Research Scholar, Laboratory of Pathology, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892-4605 (e-mail:
[email protected]).AbstractCharacterization of gene expression profiles in tumor cells and the tumor microenvironment is an important step in understanding neoplastic progression. To date, there are limited data available on expression changes that occur in the tumor-associated stroma as either a cause or consequence of cancer. In the present study, we employed a 54,000 target oligonucleotide microarray to compare expression profiles in the 4 major components of the microenvironment: tumor epithelium, tumor-associated stroma, normal epithelium, and normal stroma. Cells from 5 human, whole-mount prostatectomy specimens were microdissected and the extracted and amplified mRNA was hybridized to an Affymetrix Human Genome U133 Plus 2.0 GeneChip. Using the intersection of 2 analysis methods, we identified sets of differentially expressed genes among the 4 components. Forty-four genes were found to be consistently differentially expressed in the tumor-associated stroma; 35 were found in the tumor epithelium. Interestingly, the tumor-associated stroma showed a predominant up-regulation of transcripts compared with normal stroma, in sharp contrast to the overall down-regulation seen in the tumor epithelium relative to normal epithelium. These data provide insight into the molecular changes occurring in tumor-associated stromal cells and suggest new potential targets for future diagnostic, imaging, or therapeutic intervention.ArticlePlusClick on the links below to access all the ArticlePlus for this article.Please note that ArticlePlus files may launch a viewer application outside of your web browser.http://links.lww.com/PDM/A2http://links.lww.com/PDM/A3Prostate carcinoma is the second most commonly diagnosed cancer in men and the second leading cause of cancer death in the United States. Although carcinomas are technically epithelial cancers, various other cellular components of the tumor microenvironment such as fibroblasts, endothelial cells, and inflammatory cells can be identified admixed with the epithelial tumor cells.Currently, it is thought that cells making up the microenvironment not only play a role in supporting tumor cells, but may be key in the maintenance and progression of the neoplasia itself.1–5 The “reactive stroma” that is frequently observed in prostate and other tumor types is characterized by myofibroblastic differentiation of stromal cells and an increase in extracellular matrix and vasculature.3,6–8 This milieu contains both inflammatory cells and myofibroblasts known to express growth factors and cytokines necessary for the survival and progression of tumor cells, as shown by numerous in vitro studies.3,9,10 Olumi et al11 showed that carcinoma-associated fibroblasts (CAFs or myofibroblasts), but not fibroblasts distal to the tumor, lead to augmentation of tumor progression and the cancerous conversion of nontumorous, immortalized cell lines. In vivo, transforming growth factor beta and infiltrating fibroblasts and/or myofibroblasts are thought to be principal contributors to these changes.12–14 Further, deciphering the biology of these various cell type interactions within the native tissue environment will be a critical step forward in developing a more complete understanding of the cancer process.Recently, it has been suggested that cells associated with the reactive stroma may serve as unique “therapeutic targets” toward disrupting the neoplastic milieu and slowing down tumor progression and dissemination.8,15 Kammertoens and colleagues16 showed that, in addition to direct tumor cell killing, T-cell–mediated tumor rejection also alters stromal infrastructure. Disruption of this epithelial-stromal relationship has been demonstrated to decrease carcinoma cell proliferation when it is accomplished through chemotherapeutic agents,17 suggesting that other methods of microenvironment alteration could obtain similar results. Further, molecular targeting of specific stromal candidates could prove an effective enhancement of current diagnostic and/or therapeutic techniques.18 Toward that end, the present study focuses on a transcriptional analysis of prostatic fibromuscular stroma from within tumor foci versus stroma away from tumor foci. This nonepithelial cell component of the tumor microenvironment may represent a key source of clinically useful molecular markers.MATERIALS AND METHODSTissue SpecimensSpecimens were collected anonymously from patients undergoing radical prostatectomy at the Catholic University Hospital in Santiago, Chile. Patients had no therapy preceding prostatectomy. The excised prostates were processed mainly for diagnosis, but a portion of the fresh tissue was cross-sectioned and flash-frozen at −80°C and embedded in OCT medium. The frozen tissue blocks were shipped to the National Cancer Institute. Two pathologists (R.F.C and J.R.C.) evaluated the whole-mount sections from the frozen blocks and agreed on the Gleason scores. Five localized primary prostate cancer cases with low to moderate Gleason grades were selected: 2+1=3 (1 case), 3+3=6 (1 case), 3+4=7 (1 case), and 4+3=7 (2 cases). Adequate areas of tumor, tumor-associated stroma, and tumor-free tissue were present in all cases to allow laser-capture microdissection (LCM). Dissection areas were carefully selected by the above pathologists with special emphasis being placed on avoiding contamination by infiltrating tumor cells or clusters of inflammatory cells (Fig. 1) in the stromal areas.JOURNAL/dimp/04.03/00019606-200712000-00001/figure1-1/v/2021-02-17T195940Z/r/image-jpeg
Frozen whole-mount hematoxylin and eosin section from a prostate specimen with cancer. A Gleason 3+4=7 carcinoma, with crowded small glands and cribriform patterns, can be recognized. Between the tumor glands, areas of tumor-associated stroma free of infiltrating cells can be seen (asterisks).LCMFrozen whole-mounts were cut into 8-μm sections using a Leica Cryostat and placed onto uncharged glass slides. Every sixth slide was stained using hematoxylin and eosin and the histology confirmed by a pathologist (R.F.C. or J.R.C.). The remaining slides were stored at −80°C until dissection, not to exceed 2 weeks' storage at −80°C. Before dissection, the appropriate slides were removed from storage and placed on dry ice to maintain freezing until ensuing dissection. Immediately before LCM, slides were stained as follows:Seventy percent ethanol for 15 seconds, Meyer's hematoxylin (Sigma-Aldrich, St Luis, MO) for 15 seconds, deionized water, and bluing solution (Sigma-Aldrich) for 10 seconds each, and eosin (Sigma-Aldrich) for 5 seconds followed by dehydration using increased concentrations of ethanol (95%, 95%, 100%, and 100%) for 10 seconds each. Tissue was then placed in xylene for 20 seconds to complete the dehydration process.For each clinical sample, 2 different regions within the whole-mount were selected: a focus of prostate adenocarcinoma and another remote area of normal appearing tissue taken as far away from the tumor focus as possible, with a minimum distance of 1.5 cm. At the center of the tumor focus, an epithelial dissection and a stromal dissection were selectively performed using LCM. An epithelial and a separate stromal dissection were also conducted within the remote, normal-appearing region. LCM was performed using the PixCell IIe (Arcturus Engineering, Inc, Mountain View, CA). Time from slide removal from dry ice to completion of LCM did not exceed 30 minutes. On average, epithelial dissections required about 4000 shots (Laser spot specifications: 15 μm spot size, 45 to 55 mW power, 3.0 to 4.0 ms duration), whereas stromal dissections required 20,000. The 5-fold shot increase for stroma was necessary to gain enough material for downstream analysis. Upon completion of LCM, total RNA was isolated with the PicoPure RNA Isolation kit (Arcturus Engineering), as suggested by the manufacturer. RNA quantity was assessed using a NanoDrop Spectrophotomer (NanoDrop Technologies, Wilmington, DE). RNA quality, both 28S/18S ratio and RNA integrity number, was measured using the 2100 Bioanalyzer (Agilent Technologies, Inc, Palo Alto, CA).RNA Amplification and Microarray HybridizationTo ensure that all samples contained a similar overall representation of mRNA, equivalent RNA concentrations were used for all analyses. Per clinical sample, 20 ng of total RNA was used to generate cDNA, using the MessageAmpII antisense RNA (aRNA) (Ambion, Inc, Austin, TX), as suggested by the manufacturer. After generation of the initial first strand cDNA, half of the sample was removed and stored at −80°C for later validation experiments. The remaining half was used to generate aRNA for Genechip analysis. The approximate 10 ng total RNA sample was taken through 2 rounds of amplification using the MessageAmpII kit, until the final biotin incorporation, in vitro transcription step. For this final step, MessageAmp II-Biotin Enhanced kit (Ambion) was used to generate biotin-UTP aRNA, according to the manufacturer's suggestions. aRNA yield was used as a quality control metric; 10 ng samples yielding less than 30 μg aRNA after 2 rounds of amplification were discarded and LCM repeated. Allowing for technical replicates per sample, 30 μg of biotin-labeled aRNA was fragmented and processed for hybridization to 2 Affymetrix U133 plus 2.0 Genechips (Affymetrix, Inc, Santa Clara, CA), according to the Expression Manual (Affymetrix.com). Genechips with less than 38%-genes-present and scaling factors above 10.0 were discarded and the corresponding LCMs repeated. Enough RNA was amplified to run 2 Affymetrix GeneChips per sample.Data AnalysesGene expression signatures were identified by comparing intratumoral stroma to extra/nontumoral stroma; similarly, tumor epithelia were compared with nontumor epithelia. Stromal or epithelial compartments were independently examined using both the Genechip Operating System (GCOS) Batch analysis function, as suggested by Affymetrix, and a Perfect Match (PM)-only method. As a brief description, the modified PM-only method is similar to Robust Multiarray Average (RMA)19 and dCHip20 in that only PM signal intensities are used to determine transcript expression levels. However, for the modified PM-only method, all probe level sequence annotations were verified by comparing the annotation of each individual probe with NCBI database sequences. Incorrectly assigned probesets were excluded from analysis. A one sample t test (P value <0.05) was performed between technical replicates to ensure reproducibility of transcript signal intensities. Minimum acceptable strength (MAS) background subtraction was performed using the BioConductor MAS19,21 function, and, for each probe set, the final gene expression intensity is computed as a weighted median using the Tukey Biweight method. All data manipulations and statistical calculations were performed using Perl scripts and R (http://cran.r-project.org/).22 Cyclic LOESS regression normalization23 was then conducted and the corresponding log ratio of gene expression for each probeset computed. Differentially expressed transcripts were identified using the z-score test to calculate the 95% cut off interval. Only candidates who were common to both the GCOS and modified PM-only methods were retained for final analysis. From this work we developed a final candidate list of transcripts commonly dysregulated in all 5 of the cases for tumor epithelium and tumor-associated stroma.Quantitative PCR ValidationValidation of GeneChip differential expression findings was conducted using quantitative reverse transcription TaQman polymerase chain reaction. qRT-PCR was performed on original dissection samples saved after first strand cDNA synthesis at −80°C. Folate hydrolase 1 (FOLH1) and cartilage oligomeric matrix protein (COMP) were selected on the basis of differential expression in the tumor versus normal epithelium and/or stroma. All 5 cases were tested for these 2 genes. Beta-actin (ACTB), a known housekeeping gene, was used for purposes of normalization. In addition, 2 transcription factors, Storkhead box 2 (STOX2) and Fibronectin leucine-rich transmembrane protein 3 (FLRT3), were also tested in the technical repeat sample. TaQman primer/probe sets and master mix reagents were procured from Applied Biosystems (Foster City, CA). Each reaction was conducted in a 20 μL volume using a Stratagene Mx3000p quantitative PCR machine (Garden Grove, CA).Clustering AnalysesRaw array data and final transcript lists were uploaded into the National Cancer Institutes microarray analysis program, mAdb (http://nciarray.nci.nih.gov, National Institutes of Health, Bethesda, MD). Allowing for technical replicates, there were 10 microarrays representing the nontumor samples and 10 representing the tumor-associated samples. Hierarchical clustering was performed and a heatmap graphical depiction of expression analysis generated for the most consistently dysregulated transcripts, where red and green denote increased and decreased transcript expression levels, respectively. The heatmap step was performed both to visualize and to confirm differential expression of the transcripts determined above through a separate NCI analysis program.Global expression profiles between tumor and remote nontumor samples were also analyzed using Multidimensional Scaling (MDS). This algorithm reduces such variances to 3-dimensional eigenvectors, which can then be plotted graphically. For the 3-dimensional plots, each point represents one tissue sample, where points clustering more tightly together denote similar expression patterns.RESULTSTechnical ParametersSamples of stroma and epithelium were laser-capture microdissected from tumor and nontumor regions within each of 5 whole-mount, frozen prostate cases. Distance between the 2 sample regions averaged 2.0 cm. Microarray expression data confirmed that stromal markers such as vimentin were more highly expressed in stromal versus epithelial samples, whereas the keratins were more highly expressed in the epithelial dissection groups. This expression pattern held true for all cases except one. Consistent quality and quantity of RNA was maintained for all samples. Average RNA yield per sample (stromal or epithelial) was 6.57 ng/μL (SD: 2.08). Average ribosomal RNA 28S/18S ratio and RNA integrity number of the samples was 1.12 and 6.34, respectively (SDs: 0.33 and 0.81). GeneChip quality assessment showed a mean background of 45.6, noise of 1.4, scale factors of 4.4, % present of 41.8, and 3′/5′ ratios of 21.2 (Table 1).JOURNAL/dimp/04.03/00019606-200712000-00001/table1-1/v/2021-02-17T195940Z/r/image-tiff Affymetrix GeneChip Quality AssessmentDifferential Gene Expression in Tumor Region Versus Nontumor RegionDifferential expression in tumor versus nontumor regions, both for epithelium and stroma, was evaluated using 2 different methods, GCOS and the PM-only method. The use of 2 different methods to determine the final, common candidate lists reduced noise within the lists by removing those transcripts that appeared in only one of the analysis methods. Final lists included transcripts that were consistently up-regulated or consistently down-regulated in all 5 patient cases. The number of consistently up-regulated and down-regulated genes for the intratumoral stroma and tumor epithelium (vs. normal) are listed in Table 2. Forty-four transcripts were consistently dysregulated in the intratumoral stroma, whereas 35 were consistently dysregulated in the tumor epithelium. A complete list of dysregulated transcripts found in each group is presented in Table 3.JOURNAL/dimp/04.03/00019606-200712000-00001/table2-1/v/2021-02-17T195940Z/r/image-tiff Number of Differentially Expressed Transcripts in Tumor Area SamplesJOURNAL/dimp/04.03/00019606-200712000-00001/table3-1/v/2021-02-17T195940Z/r/image-tiff Differentially Expressed Transcripts in Tumor Versus Nontumor Regions of Epithelium or Stroma Common to all 5 CasesThere was a pattern to the direction of differential expression for both sample types where intratumoral stroma showed a trend toward increased expression relative to the normal stroma, whereas the tumor epithelium itself exhibited a predominance of decreased expression compared with the normal epithelium. For example, all 44 intratumoral stromal targets were up-regulated. In contrast, in tumor epithelial samples 76% (26 of 35) were consistently down-regulated.Cluster/Heatmap AnalysisHierarchical clustering of the most consistently dysregulated genes in tumor versus nontumor regions was performed using the NCI mAdb microarray analysis program for both stromal and epithelial samples (Figs. 2, 3, respectively). As expected, technical replicates for each of the 5 patient samples clustered together, followed by clustering on the basis of dissection region (ie, tumor vs. nontumor). Similarly, heatmaps generated by the NCI mAdb program visually corroborated differential expression findings of final candidate transcripts (Figs. 2, 3) and was performed as another method to verify the accuracy of our candidate list.JOURNAL/dimp/04.03/00019606-200712000-00001/figure2-1/v/2021-02-17T195940Z/r/image-jpeg
Analysis of dysregulated genes in the intratumoral stroma group. A, Heatmap of differential gene expression in intratumoral (red) versus extratumoral (yellow) stroma. Red squares denote up-regulation, green denote down-regulation. B, Hierarchical clustering of differentially expressed genes common to all 5 cases. C, MDS depicts clustering of intratumoral stroma (red) separate from extratumoral stroma (green).JOURNAL/dimp/04.03/00019606-200712000-00001/figure3-1/v/2021-02-17T195940Z/r/image-jpeg
Analysis of dysregulated genes in the tumor epithelium. A, Heatmap of differential gene expression of tumor versus nontumor epithelium. Red squares denote up-regulation, green denote down-regulation. B, Hierarchical clustering of differentially expressed genes common to all 5 cases. C, MDS depicts clustering of tumor (red) epithelial samples apart from nontumor (green) region epithelial samples.MDS compresses differences between sample expression profiles into 3 eigenvectors for plotting in 3-dimensional space. Upon this analysis, stroma samples clearly group according to dissection region, tumor, or nontumor (Fig. 2C). The same pattern holds true for epithelial samples (Fig. 3c). No cross-over of samples between these groups was evident.ValidationAs validation of our entire process, 1 patient sample was chosen and a complete start-to-finish technical repeat of the experiment performed, starting with frozen sectioning and LCM through data analysis and generation of the final lists of differentially expressed genes. The final candidate lists, intratumoral stroma, and tumor epithelium, for the repeat sample, demonstrated over 90% concordance with results of the original experiment (data not shown).Gene expression was validated using quantitative PCR. Two genes of interest (FOLH1 and COMP), in addition to 1 housekeeping gene (ACTB), were assessed for technical validation of the original frozen cDNA sample saved from chip hybridization. For both the FOLH1 and COMP genes, quantitative PCR validated 8 out of 10 samples (Fig. 4). FLRT3 and STOX2, down-regulated in the tumor epithelium by GeneChip data, were tested in a replicate of one of the tumor versus normal cases, and the qRT-PCR results also validated the array data.JOURNAL/dimp/04.03/00019606-200712000-00001/figure4-1/v/2021-02-17T195940Z/r/image-jpeg
qRT-PCR validation results for 2 selected transcripts, FOLH1 and COMP. GeneChip signal intensity is shown with diagonal hatch-marks; qRT-PCR ΔΔCt is shown in black.DISCUSSIONWithin the last 20 years, there has been a paradigm shift away from the idea that the stromal compartment in tissues acts merely as a passive support for epithelial cells toward the view that it comprises an interactive environment that plays a central role in normal and pathologic processes, including cancer. Mechanistic studies using cell lines and limited tissue studies of a handful of genes might benefit from a more comprehensive picture of the changes occurring in the tumor microenvironment. To date, gene expression analysis of tumor-associated stroma has been limited to cell culture and xenograft experiments, not from the tissue source directly because of difficulties in obtaining quality frozen whole-mount tissue and in fine extraction techniques. This study represents the first comprehensive transcriptome analysis of laser-capture microdissected stroma from matched normal and tumor foci of whole-mount clinical prostatectomy cases. A large set of differentially expressed transcripts were discovered between stromal cells within and outside a tumor foci (Table 2), cataloging some of the main changes in this tumor-influenced region.Assessing overall gene expression within the intratumoral stroma and the tumor epithelium, a statistically significant trend of gene up-regulation in intratumoral stroma was noted, where of the genes consistently deregulated in all 5 patients, 100% were up-regulated. This finding was in contrast to the tumor epithelium, which showed consistent down-regulation in 76% of the genes common to all 5 patients.Other studies have also shown a pattern of down-regulation associated with prostate cancer development, such as a microdissection-based study comparing epithelial samples of PIN versus prostate cancer done by Ashida et al. In this study, LCM was performed on normal epithelium, PIN and tumor epithelium, and cDNA microarrays used to identify differentially expressed genes. Of these genes, 75% were down-regulated in the first group, and 70.5% were down-regulated in the latter.24–33 Many of the transcripts noted in their study also appeared in our own, including the down-regulated transcripts ATF3, CAV2, PDK4, SFN, and STOM and up-regulated AMACR, DNMT3A, MYBPC1, and SIM2. Moreover, previous prostate cancer expression projects by our laboratory also overlap with many of the transcripts identified in the present study.34,35Of the most consistently dysregulated genetic transcripts in both the intratumoral stroma and tumor epithelium, FOLH1 [also known as prostate-specific membrane antigen (PSMA)], is up-regulated in both groups across all 5 patient cases. Previously, PSMA has been shown to be up-regulated in primary and metastatic prostate tumor epithelium,36,37 in tumor neovasculature,38,39 and has been identified in postprostatectomy patients as a serum marker of clinical progression.40,41 To determine if stromal PSMA signal stemmed from endothelial cells, 3 well-known endothelial markers (CD34, Factor VIII, and CD31) were specifically assessed in all data sets, but none were found to be differentially expressed. Since its original discovery over 10 years ago, PSMA has been employed as an immunotherapeutic and diagnostic target with an FDA approved pendetide for soft-tissue imaging.42–44 Our new finding of its up-regulation in the intratumoral stroma, in addition to previous reports of PSMA up-regulation in tumor and tumor neovasculature, lends even more support to the use of PSMA as a local imaging target. As expected, alpha-methylacyl-CoA racemase (AMACR) up-regulation45,46 was observed in the tumor epithelium and within intratumoral stroma for 4 of the 5 cases. AMACR can be expressed in different splice variants. To date, 5 have been characterized by Shen-Ong et al.47 It is possible that the stroma might possess an AMACR protein with alternative splicing or posttranslational modifications altering the epitope recognized by the P504S monoclonal antibody typically used for AMACR immunohistochemistry studies.Two thrombospondin candidates, thrombospondin 4 and 5, also surfaced in our analysis as being consistently up-regulated in intratumoral stroma. Both thrombospondins are extracellular matrix targets associated with cellular adhesion.48,49 Thrombospondin 5, more commonly known as COMP, has been demonstrated in the extracellular matrix of cartilage, tendon, ligament, and bone.50 Transforming growth factor-beta pathway up-regulation, associated with fibroblast to myofibroblast transition,10,24 stimulates an excess of extracellular matrix deposition, including the overexpression of COMP.13,51 Although the role of COMP in the carcinogenic process has yet to be elucidated, it has been employed as a biomarker for osteoarthritis.52Targets such as COMP or thrombospondin-4, in addition to helping to elucidate the role of the stroma in carcinogenic progression, may also serve for diagnostic and therapeutic purposes. Molecular targets in the stroma may, in some instances, be better suited for clinical use than those of the epithelium. As blood vessels travel through and are intimately associated with the stromal cells and extracellular matrix, vascular-delivered agents may more readily reach this compartment. Thus, molecular targets within the intratumoral stroma may be particularly amenable to molecular targeting.As prostate adenocarcinoma exhibits a complex, heterogeneous pattern of invasion, obtaining pure populations of cellular subtypes is problematic. One drawback to this study was the inability to histologically confirm specific cell populations to be dissected by targeted immunohistochemistry, as this method compromises RNA integrity.53 Instead, 2 pathologists identified appropriate dissection areas based on hematoxylin and eosin staining in serial slides, with a concerted effort to avoid areas of infiltrating tumor, lymphocytic cells, and/or morphologically reactive stroma. Also, an expansion of the number of cases assessed would greatly aid in the generalizability of the study. Obtaining frozen whole-mount tissue, as opposed to plugs or whole-mount formalin-fixed, paraffin-embedded tissue, is very difficult as the first priority of a radical prostatectomy is tumor excision and thorough pathologic evaluation, including tumor volume estimation, fine histopathologic assessment, and surgical margin status, required for clinical and therapeutic purposes.54 Such a detailed evaluation requires formalin-fixed, paraffin-embedded tissue as the gold standard for histologic quality (which, unfortunately, severely compromises RNA quality55) and the majority of the tissue to ensure the best patient care possible.In summary, we were able to show for the first time that a comprehensive analysis of the transcriptome is able to discriminate between intratumoral versus extratumoral prostate stroma in clinical samples, despite the fact that both are phenotypically non-neoplastic. 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Frozen whole-mount hematoxylin and eosin section from a prostate specimen with cancer. A Gleason 3+4=7 carcinoma, with crowded small glands and cribriform patterns, can be recognized. Between the tumor glands, areas of tumor-associated stroma free of infiltrating cells can be seen (asterisks). Affymetrix GeneChip Quality Assessment Number of Differentially Expressed Transcripts in Tumor Area Samples Differentially Expressed Transcripts in Tumor Versus Nontumor Regions of Epithelium or Stroma Common to all 5 Cases
Analysis of dysregulated genes in the intratumoral stroma group. A, Heatmap of differential gene expression in intratumoral (red) versus extratumoral (yellow) stroma. Red squares denote up-regulation, green denote down-regulation. B, Hierarchical clustering of differentially expressed genes common to all 5 cases. C, MDS depicts clustering of intratumoral stroma (red) separate from extratumoral stroma (green).
Analysis of dysregulated genes in the tumor epithelium. A, Heatmap of differential gene expression of tumor versus nontumor epithelium. Red squares denote up-regulation, green denote down-regulation. B, Hierarchical clustering of differentially expressed genes common to all 5 cases. C, MDS depicts clustering of tumor (red) epithelial samples apart from nontumor (green) region epithelial samples.
qRT-PCR validation results for 2 selected transcripts, FOLH1 and COMP. GeneChip signal intensity is shown with diagonal hatch-marks; qRT-PCR ΔΔCt is shown in black.Supplemental Figure 1.Supplemental Figure 2.Supplemental Figure 3a.Supplemental Figure 3b.Global Expression Analysis of Prostate Cancer-associated Stroma and EpitheliaRichardson Annely M. BS; Woodson, Karen PhD; Wang, Yonghong PhD; Rodriguez-Canales, Jaime MD; Erickson, Heidi S. PhD; Tangrea, Michael A. PhD; Novakovic, Kristian MD; Gonzalez, Sergio MD; Velasco, Alfredo MD; Kawasaki, Ernest S. PhD; Emmert-Buck, Michael R. MD, PhD; Chuaqui, Rodrigo F. MD; Player, Audrey PhDOriginal ArticlesOriginal Articles416p 189-197
