Project description:Using laser capture microdissection to isolate over 100 specific cell populations, we report the profiling of prostate cancer progression from benign epithelium to metastatic disease. By analyzing these expression signatures in the context of over 15,000 â??molecular conceptsâ??, or sets of biologically connected genes, we generated an integrative model of prostate cancer progression. Keywords: disease state analysis Experiment Design: â?¢ Type of experiment: This study used microarray experiments to profile prostate cancer progression through the isolation of pure cell populations using laser capture microdissection (LCM) and OmniPlex Whole Transcriptome (WTA) Amplification. â?¢ Experimental factors: This study profiled various pure cell populations isolated by LCM from prostate tissue. â?¢ The number of hybridizations performed in the experiment: A total of 104 hybridizations were performed. â?¢ The type of reference used for the hybridizations: A single commercially available pool of benign prostate tissue (CPP, Clontech) was used as the reference in all hybridizations. For the reference sample, 10 ng of CPP total RNA was converted into a WTA cDNA library in a volume of 25 Âµl and five 5 Âµl aliquots were amplified by WTA PCR and purified. Five ng aliquots of the pooled products were subjected to a second WTA PCR amplification in the presence of amino-allyl dUTP and all products were pooled before labeling to ensure equal representation across all of the hybridizations. â?¢ Hybridization design: For all hybridizations, the experimental prostate sample isolated by LCM was labeled with Cy5 and the common reference of benign pooled prostate as described above was labeled with Cy3. â?¢ Quality control steps taken: In order to assess biological and technical reproducibility, we captured identical regions from two specimens (PCA_11 and MET_HR_3) and subjected one sample, PCA_30, to two hybridizations. For PCA_11, adjacent regions of the same section were captured and treated as separate samples. For MET_HR_3, two separate foci of the liver metastasis (from separate frozen blocks) were captured and treated as separate samples. For PCA_30, two aliquots of the primary WTA PCR products were separately subjected to a second round of WTA PCR amplification. Replicates from PCA_30 and MET_HR_3 were also hybridized to arrays from each of the print runs utilized in this study. Samples used, extract preparation and labeling: â?¢ The origin of the biological sample (for instance, name of the organism, the provider of the sample) and its characteristics: All samples used were of human origin. The table in the MIAME Checklist (Supplmentary Methods) summarizes the samples used. Hybridizations are named according to the class of sample profiled and the background color is the same as shown in Figure S3. Two print runs were used during the course of the study and the indicated run for each hybridization is given. For prostate cancer samples, the Gleason patterns present on the sample section used are indicated, as well as the Gleason patterns of the actual cells isolated by LCM. A unique case number for all profiled samples is given. Descriptions of samples are given where applicable, including the location of metastatic foci. â?¢ Manipulation of biological samples and protocols used: Laser Capture Microdissection (LCM) was performed from frozen tissue sections with the SL Microtest device using ÂµCUT software (MMI). Approximately 10,000 cells were captured for each sample. Serial sections were used if cells could not be obtained from a single section. Total RNA was isolated from captured cells with the RNAqueous Micro kit (Ambion) and treated with DNAse I according to the manufacturer's instructions. RNA quantification was perfomed using Ribogreen (Molecular Probes). â?¢ Protocol for preparing the hybridization extract: For each sample, total RNA (~10ng) in a volume of 25 Âµl was converted into an OmniPlex WTA cDNA library and amplified by WTA PCR using reagents and protocols according to the beta-commercial TransPlex WTA kit (Rubicon Genomics, Ann Arbor, MI). For each sample, a single 10 Âµl aliquot of the WTA cDNA library was amplified by WTA PCR and products were purified. Four or five 5 ng aliquots of product were subjected to a second WTA PCR amplification in the presence of amino-allyl dUTP for post amplification labeling and products were pooled before proceeding with the hybridization. Yields after all WTA PCR amplifications were between 2 to 5 Î¼g per reaction, and reaction progress was monitored in real time using SYBR green I (Molecular Probes) on the iCycler IQ (BioRad) or ABI 7300 Real Time PCR system (Applied Biosystems). Real-time PCR amplifications were terminated at or before plateau phase as measured by fluorescence incorporation to preserve maximum representation. â?¢ Labeling protocol(s): For all WTA amplified cDNA samples with amino-allyl dUTP incorporated (10-20 ï?g), nuclease free water was added to 500 ï?l, the sample was transferred to a Microcon YM-30 filter, and centrifuged at 13,000 rcf at RT for 12 minutes. The spin column was inverted in a new collection tube and centrifuged at 13,000 rcf for 2 min at RT. The amount of sample was measured and the volume was adjusted to 5 ï?l with nuclease free water. For labeling, 5 ï?l of 1 M sodium bicarbonate (pH 9.0) was added and allowed to incubate at RT for 15 min. Nine ï?l of anhydrous DMSO were added to Mono Reactive Cy3 and Cy5 dye packs (Amersham, Buckinghamshire, England), mixed thoroughly, and 1 ï?l of the proper dye was added to each sample. The labeling mixture was incubated in the dark at RT for 1 hour. The reaction was stopped by the addition of 9 ï?l of 4 M Hydroxylamine for 15 min. For each labeling mixture, RNase free water was added to 100 ï?l, 500 ï?l of PB buffer was added and Cy3 and Cy5 mixtures were added to separate Qiaquick (Qiagen, Valencia, CA) spin columns and centrifuged at 13,000 rcf. Columns were washed twice with 700 ï?l of buffer PE, and centrifuged dry at 13,000 rcf for 2 min. To elute, 60 ï?l of EB buffer was placed on the column, incubated for 5 min and centrifuged at 13,000 rcf for 1 min. The Cy3 labeled and Cy5 labeled cDNA for each hybridization were mixed and 1.5 ï?l were used for analysis on a ND-1000 spectrophotometer. â?¢ External controls (spikes): Not utilized Hybridization procedures and parameters: â?¢ The protocol and conditions used during hybridization, blocking and washing: For hybridization, 40 ï?g of human Cot-1 DNA (Invitrogen, Carlsbad, CA) was added to 120 ï?l of labeled cDNA, the probe was transferred to a Microcon YM-30 filter and centrifuged at 13,000 rcf for 6 min at RT. The spin column was inverted in a new collection tube and centrifuged at 13,000 rcf for 2 min at RT. The eluted probe volume was adjusted to 18.6 ï?l with nuclease free water and the following were added: 4 ï?l of yeast tRNA (10 ï?g/ï?l, Invitrogen, Carlsbad, CA), 4.9 ï?l of 20X SSC and 0.84 ï?l of 10% SDS. The probe was denatured at 100 Co for 3 min and centrifuged at 13,000 rcf for 45 sec. The probe was added directly to the microarray and a cover slip was added. Slides were hybridized overnight in DIE-TECH 1 or 5 slide hybridization chambers in a 65 Co water bath. After hybridization, cover slips were removed by incubation in 2x SSC / 0.05% SDS. Slides were then washed in 2x SSC / 0.05% SDS for 5 min and 0.2x SSC / 0.05% SDS for five minutes. Slides were then washed in 0.2x SSC for 10 sec and centrifuged dry at 500 rpm for 5 min. Measurement data and specifications: â?¢ Type of scanning hardware and software used: Microarrays were scanned using a GenePix 4000B scanner (Axon Instruments, Union City, CA). â?¢ Type of image analysis software used: Images were gridded and spots were quantified using GenePix Pro 4.0 software (Axon Instruments, Union City, CA). â?¢ A description of the measurements produced by the image-analysis software and a description of which measurements were used in the analysis: The measurements made by GenePix Pro 4.0 are described in the sample files. For all hybridizations, the log2 normalized Median of Ratios (as described below) was used. â?¢ Data selection and transformation procedures: Arrays were auto-gridded by GenePix 4.0. Features flagged by GenePix as not found during grid

Project description:In our investigations of the molecular pathways of prostate tumorigenesis in Nkx3.1; Pten mutant mice using gene expression profiling, we now find that the AP-1 transcription factors, c-Jun and c-Fos, are significantly up-regulated during cancer progression. Forced expression of c-Fos and c-Jun in prostate cancer cells results in increased tumorigenicity, activation of Erk MAP kinase, and enhanced survival in the absence of androgens, which are hallmarks of disease progression. In humans, Jun and Fos proteins are significantly up-regulated during prostate cancer progression and significantly correlated with activation of Erk MAP kinase. Most notably, expression of Jun is associated with disease recurrence independent of other currently used prognostic indicators. These analyses reveal a hitherto unappreciated role for AP-1 transcription factors in prostate cancer progression vis-Ã -vis Erk MAP kinase signaling, as well as the identification of a novel marker of disease recurrence, namely c-Jun. Experiment Overall Design: Mouse prostate was collected from wild-type or the Nkx3.1; Pten compound mutant mice at the age of 8-16 months. One lobe of dosolateral prostate was snap-frozen in OCT and stored at -80ÂºC for laser capture microdissection (LCM). To obtain androgen-independent lesions, mice were castrated at 7 to 14 months of age. Mice were sacrificed for analysis at 8 to 16 months of age and one dosolateral prostatic lobe was snap-frozen in OCT and stored at -80ÂºC for LCM. Approximate 1000 Prostate epithelial cells were isolated from normal prostate, dysplasia, prostatic intraepithelial neoplasia (PIN) or cancer lesions using PixCell IIE LCM system (Arcturus), followed by RNA linear amplification and labeling using Small Sample Labeling Protocol VII (Affymetrix). Samples were labeled using a BioArray High Yield RNA transcript labeling kit (Enzo Life Scientific) and were hybridized to MOE430A GeneChips containing 22,690 well characterized mouse genes/ESTs (Affymetrix).

Project description:TMPRSS2-ERG gene fusions that are frequently identified in prostate cancer can be generated either through chromosomal translocation or via interstitial deletion. The latter mechanism deletes an interstitial region of ~3Mb and it remains largely unanswered whether genes deleted within this region contribute to prostate cancer. By characterizing two knockin mouse models recapitulating TMPRSS2-ERG fusions with or without the interstitial deletion, we found that only those with deletion developed poorly differentiated adenocarcinomas with epithelial-to-mesenchymal transition, when under a Pten-null background. We identified several interstitial genes, including ETS2 and BACE2, whose reduced expression correlates with worse disease-free survival and lethal disease. By using an Ets2 conditional knockout allele, we demonstrated that loss of one copy of Ets2 was sufficient for prostate cancer progression when under a Pten-null background. Collectively, our data suggest that ETS2 is a prostate tumor suppressor and haploinsufficiency of one or more interstitial genes contributes to prostate cancer progression. Genotyped male mice were euthanized at 12 months of age and prostates isolated. Prostates were fixed overnight in 10% formalin and stored in 70% ethanol until tissue processing and paraffin embedding. Serial sections were cut from paraffin blocks which were stained for H&E and analyzed by a trained rodent histopathologist. Using these sections as a visual guide for specific types of lesions, the sequential sections were stained with hematoxylin and used for laser capture microdissection on ArcturusXT system. Epithelial cells within notable high grade prostate intraepithelial neoplasia (HG-PIN) lesions were microdissected from 3 mice from each corresponding genotype. In addition, poorly differentiated adenocarcinomas from PbCre;T-3Mb-Erg/+;PtenL/L mice were also dissected. RNA was isolated from the microdissected tissue using the Qiagen RNeasy FFPE kit and subjected to Nugen Amplification before microarray analysis on an Affymetrix Mouse Gene 2.0 ST chip.

Project description:Current prostate cancer prognostic models are based on pre-treatment prostate-specific antigen (PSA) levels, biopsy Gleason score, and clinical staging but in practice are inadequate to accurately predict clinical disease progression. Hence, we sought to develop a molecular panel for prostate cancer progression by reasoning that molecular profiles might further improve current clinical models. We analyzed a Swedish Watchful Waiting cohort (1977â1999) with up to 30 years of clinical follow up using a novel method for gene expression profiling. This cDNA-mediated annealing, selection, ligation, and extension (DASL) method enabled the use of formalin-fixed paraffin-embedded transurethral resection of prostate (TURP) samples taken at the time of the initial diagnosis. We determined the expression profiles of 6100 genes for 281 men divided in two extreme groups: men who died of prostate cancer or developed metastases and men who survived more than 10 years without metastases (lethals and indolents, respectively). Several models using clinical and molecular features were evaluated for their ability to distinguish lethal from indolent cases. Surprisingly, none of the predictive models using molecular profiles significantly improved over models using clinical variables only. We reasoned that tumor sampling might preclude the identification of the dominant metastatic nodule. Additional computational analysis confirmed that molecular heterogeneity within both the lethal and indolent classes is widespread in prostate cancer as compared to other types of tumors. Thus the determination of the molecularly dominant tumor nodule may be limited by sampling at time of initial diagnosis, may not be present at time of initial diagnosis, or may occur as the disease progresses preventing the development of molecular biomarkers for prostate cancer progression. 281 cases from the population-based Swedish-Watchful Waiting cohort. The cohort consists of men with localized prostate cancer (clinical stage T1-T2, Mx, N0); Training set: first 186 samples; Validation cohort: remaining 95 cases from the same population.

Project description:Androgen receptor (AR) orchestrates an intricate transcriptional regulatory network that governs prostate cancer initiation, development and progression. To understand this network in detail, we generated genome-wide maps of AR occupancy by ChIP-seq in LNCaP cells. We found NKX3-1, an androgen-dependent homeobox protein well-characterized for its role in prostate development and differentiation, being recruited to AR binding sites (ARBS) in response to androgen signaling. We identified 6,359 NKX3-1 binding sites, most of which overlapped with AR. In addition to its novel collaborative transcriptional role at well-known prostate cancer model genes, our binding and knockdown studies further suggested that NKX3-1 potentially regulates AR in a feed-forward manner. Integrative analysis of Oncomine molecular concepts showed that these androgen-regulated AR and NKX3-1 associated genes are significantly overexpressed in prostate carcinoma as well as advanced and recurrent prostate tumors. From our transcriptomic profiling and Gene Ontology analysis, we observed that AR and NKX3-1 co-regulate genes involved in "protein trafficking" processes, which are mandatory events in the integration of oncogenic signaling pathways leading to prostate cancer development and progression. Interestingly, we found that AR and NKX3-1 co-regulate several members of the RAB GTPase family of secretory/trafficking proteins via the involvement of FoxA1 in a ternary complex and we believe that these AR/NKX3-1/FoxA1 co-regulated RAB genes could serve as expression signatures in prostate carcinogenesis. More specifically, through functional analyses, we showed that NKX3-1, together with AR and FoxA1, could promote prostate cancer cell survival through activation of RAB3B expression. Collectively, our study has provided important insights into the hierarchical transcriptional regulatory network established between AR and NKX3-1 and sought to elucidate the important genetic-molecular-phenotypic paradigm in androgen-dependent prostate cancer. Genome-wide binding analyses of AR, NKX3-1 and FoxA1 in LNCaP with or without DHT (5alpha-dihydrotestosterone) stimulation using ChIP-Seq.

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Integrative Molecular Concepts Modeling of Prostate Cancer Progression

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