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Gene Expression Profiles of Ductal Versus Acinar Adenocarcinoma of the Prostate

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Gene Expression Profiles of Ductal Versus Acinar Adenocarcinoma of the Prostate Modern Pathology (2009) 22, 1273–1279 & 2009 USCAP, Inc. All rights reserved 0893-3952/09 $32.00 1273 Gene expression profiles of ductal versus acinar adenocarcinoma of the prostate Souzan Sanati1, Mark A Watson2, Andrea L Salavaggione2 and Peter A Humphrey1 1Department of Pathology and Immunology, Division of Anatomic and Molecular Pathology, Washington University School of Medicine, St Louis, MO, USA and 2Department of Pathology and Immunology, Division of Laboratory and Genomic Medicine, Washington University School of Medicine, St Louis, MO, USA Ductal adenocarcinoma is an uncommon variant of prostatic adenocarcinoma with a generally more aggressive clinical course than usual acinar adenocarcinoma. However, the molecular distinction between ductal and acinar adenocarcinomas is not well characterized. The aim of this investigation was to evaluate the relatedness of ductal versus acinar prostatic adenocarcinoma by comparative gene expression profiling. Archived, de- identified, snap frozen tumor tissue from 5 ductal adenocarcinomas, 3 mixed ductal–acinar adenocarcinomas, and 11 acinar adenocarcinomas cases were analyzed. All cases of acinar and ductal adenocarcinomas were matched by Gleason grade. RNA from whole tissue sections of the 5 ductal and 11 acinar adenocarcinomas cases were subjected to gene expression profiling on Affymetrix U133Plus2 microarrays. Independently, laser- capture microdissection was also performed on the three mixed ductal–acinar cases and five pure acinar cases to isolate homogeneous populations of ductal and acinar carcinoma cells from the same tumor. Seven of these laser-capture microdissected samples (three ductal and four acinar cell populations) were similarly analyzed on U133Plus2 arrays. Analysis of data from whole sections of ductal and acinar carcinomas identified only 25 gene transcripts whose expression was significantly and at least two-fold different between ductal and acinar adenocarcinomas. A similar analysis of microdissected cell populations identified 10 transcripts, including the prolactin receptor, with more significant differences in expression of 5- to 27-fold between ductal and acinar adenocarcinomas cells. Overexpression of prolactin receptor protein in ductal versus acinar adenocarcinoma was confirmed by immunohistochemistry in an independent set of tumors. We conclude that ductal and acinar adenocarcinomas of the prostate are strikingly similar at the level of gene expression. However, several of the genes identified in this study, including the prolactin receptor, represent targets for further investigations on the molecular basis for histomorphological and clinical behavioral differences between acinar and ductal adenocarcinomas. Modern Pathology (2009) 22, 1273–1279; doi:10.1038/modpathol.2009.103; published online 24 July 2009 Keywords: prostate; neoplasms; ductal; adenocarcinoma; gene; prolactin Ductal adenocarcinoma is the most common histo- such as cribriform growth and origin in the logic variant of prostatic carcinoma.1–10 Most studies peripheral zone. Yet, there are also differences in have shown a more aggressive clinical course for that ductal adenocarcinoma commonly arises in ductal adenocarcinoma compared with usual acinar large periurethral ducts, displays a papillary growth adenocarcinoma.6–14 There has been debate as to configuration, and characteristically is comprised of whether ductal adenocarcinoma is an entity that is tall pseudostratified columnar epithelial cells. De- distinct from acinar adenocarcinoma.1,5 Ductal spite these differences, it has been proposed that adenocarcinomas are often admixed with acinar ductal adenocarcinoma results from spread of adenocarcinoma and ductal and acinar adenocarci- typical acinar adenocarcinoma into large accommo- nomas can share certain histopathological attributes dating periurethral ducts and stroma,5 although this is a minority view. The World Health Organization 3 4 Correspondence: Dr PA Humphrey, MD, PhD, Department of tumor classification book and the AFIP fascicle Pathology and Immunology, Division of Anatomic and Molecular currently recognize ductal adenocarcinoma as a Pathology, Washington University Medical Center, 660 South variant and subtype of prostatic adenocarcinoma, Euclid Avenue, Campus Box 8118, St. Louis, MO 63110, USA. E-mail: [email protected] respectively. Received 14 April 2009; revised 23 June 2009; accepted 26 June The molecular relatedness of ductal and acinar 2009; published online 24 July 2009 adenocarcinomas of the prostate has been addressed www.modernpathology.org Prostatic ductal adenocarcinoma profiling 1274 S Sanati et al in only a few studies. Limited scale data do exist on nanograms of RNA from microdissected cell popu- comparative protein expression in ductal versus lations was independently converted to biotiny- acinar adenocarcinoma,7,12,14–25 but comparative lated, antisense cRNA target, using the Affymetrix global gene expression profiling has not been two-cycle labeling method. All biotinylated targets performed. The aim of this study was to examine were fragmented and 15 mg of each was hybridized the gene expression profiles of ductal versus acinar to HG-U133Plus 2.0 GeneChip microarrays follow- adenocarcinoma to assess the molecular relatedness ing the manufacturer’s protocol. Scanned array of ductal and acinar adenocarcinomas and to images were reviewed and converted to signal data identify potential molecular differences that may using the Affymetrix MAS 5.0 algorithm, scaling explain the different histopathological features and each array set (total tissue RNA and microdissected disparate clinical behavior of ductal adenocarcino- RNA) independently to a target intensity of 1500. ma of the prostate. Scaled data for each array were exported to the Siteman Cancer Center Bioinformatics server (http:// bioinformatics.wustl.edu), merged with the updated Materials and methods gene annotation data for each probe set on the array, Human Tissues and downloaded for further data visualization and analysis. The completely annotated, minimum in- After IRB/human studies approval, archived, de- formation about a microarray experiment–compliant identified, snap frozen tumor tissue from 5 cases of dataset can be found at the above noted URL ductal adenocarcinoma and 11 cases of acinar and also at Gene Expression Omnibus (http:// adenocarcinoma matched for Gleason grade (mean www.ncbi.nlm.nih.gov/geo/). Gleason score of 8 for ductal cases and 8.2 for acinar cases) were obtained from the Siteman Cancer Data Analysis Center Tissue Procurement Core Facility for RNA isolation and gene expression microarray analysis. Basic microarray data visualization, data filtering, Frozen sections of banked tissue were reviewed for ANOVA analysis, and hierarchical clustering were tumor cellularity, Gleason grade, and histological done using Spotfire DecisionSite for Functional type. Whole tissue sections used for RNA extraction Genomics (Somerville, MA, USA). The P-values had a mean of 65% (range 25–100%) of the tissue obtained from ANOVA were corrected for multiple cellularity involved by carcinoma. Formalin-fixed, testing based on the method of Benjamini–Hoch- paraffin-embedded blocks of ductal and acinar berg.27 Data sets from whole tissue sections and adenocarcinomas used for immunohistochemistry microdissected cell populations were treated inde- were identified by a computerized search of the pendently, as they involved two different methods surgical pathology files at Barnes–Jewish Hospital. of target preparation. Microarray probe sets that were scored ‘absent’ RNA Isolation from Frozen Tissues and Microarray across all arrays and Affymetrix control probe sets Analysis were removed from further analysis. For unsuper- vised hierarchical clustering using Ward’s method, Serial 50 mm sections were homogenized in TRIzol signal values for each probe set across arrays were reagent (Invitrogen, Carlsbad, CA, USA) to extract normalized by the Z-score method and relative total RNA from whole tissue ductal (n ¼ 5) and acinar expression was used to generate clusters. For tumor samples (n ¼ 11). Laser-capture microdissec- comparative analysis, the significance analysis tion from frozen sections of three additional mixed of microarrays algorithm28 was used to identify acinar and ductal adenocarcinomas cases and four differentially expressed transcripts between two, Gleason grade matched acinar adenocarcinomas was unpaired classes (acinar and ductal) with the performed using the Arcturus Pixcell II instrument. minimum possible false discover rate. Secondarily, We did not separately identify and microdissect a simple two-class ANOVA analysis was performed intraductal components of ductal adenocarcinomas. to calculate P-values, which were subsequently RNA isolation from microdissected ductal and acinar corrected for multiple comparisons. Lists of signifi- cell populations was performed using the RNA Micro cantly different transcripts were further filtered by Isolation kit (Stratagene, La Jolla, CA, USA) as the criteria that expression values (signal levels) described earlier.26 All RNA was quantified by were at least two-fold different, in anticipation of Nanodrop spectrophotometry (Thermo Fisher Scien- the need to confirm results using less quantitative tific) and qualitatively assessed using an Agilent immunohistochemistry. Bioanalyzer (Agilent, Santa Clara, CA, USA). Five micrograms of RNA from each whole tumor Immunohistochemistry section was converted to biotinylated, antisense cRNA target by
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