Obesity and prostate cancer: gene expression signature of human periprostatic adipose tissue

  • Ricardo Ribeiro1, 2, 3, 4Email author,

    Affiliated with

    • Cátia Monteiro1, 4,

      Affiliated with

      • Victoria Catalán3, 5,

        Affiliated with

        • Pingzhao Hu6,

          Affiliated with

          • Virgínia Cunha1, 4,

            Affiliated with

            • Amaia Rodríguez3, 5,

              Affiliated with

              • Javier Gómez-Ambrosi3, 5,

                Affiliated with

                • Avelino Fraga1, 2, 7,

                  Affiliated with

                  • Paulo Príncipe7,

                    Affiliated with

                    • Carlos Lobato8,

                      Affiliated with

                      • Francisco Lobo9,

                        Affiliated with

                        • António Morais9,

                          Affiliated with

                          • Vitor Silva9,

                            Affiliated with

                            • José Sanches-Magalhães9,

                              Affiliated with

                              • Jorge Oliveira9,

                                Affiliated with

                                • Francisco Pina10,

                                  Affiliated with

                                  • Carlos Lopes2,

                                    Affiliated with

                                    • Rui Medeiros1, 2, 4, 11 and

                                      Affiliated with

                                      • Gema Frühbeck3, 5, 12Email author

                                        Affiliated with

                                        BMC Medicine201210:108

                                        DOI: 10.1186/1741-7015-10-108

                                        Received: 27 April 2012

                                        Accepted: 25 September 2012

                                        Published: 25 September 2012

                                        Abstract

                                        Background

                                        Periprostatic (PP) adipose tissue surrounds the prostate, an organ with a high predisposition to become malignant. Frequently, growing prostatic tumor cells extend beyond the prostatic organ towards this fat depot. This study aimed to determine the genome-wide expression of genes in PP adipose tissue in obesity/overweight (OB/OW) and prostate cancer patients.

                                        Methods

                                        Differentially expressed genes in human PP adipose tissue were identified using microarrays. Analyses were conducted according to the donors' body mass index characteristics (OB/OW versus lean) and prostate disease (extra prostatic cancer versus organ confined prostate cancer versus benign prostatic hyperplasia). Selected genes with altered expression were validated by real-time PCR. Ingenuity Pathway Analysis (IPA) was used to investigate gene ontology, canonical pathways and functional networks.

                                        Results

                                        In the PP adipose tissue of OB/OW subjects, we found altered expression of genes encoding molecules involved in adipogenic/anti-lipolytic, proliferative/anti-apoptotic, and mild immunoinflammatory processes (for example, FADS1, down-regulated, and LEP and ANGPT1, both up-regulated). Conversely, in the PP adipose tissue of subjects with prostate cancer, altered genes were related to adipose tissue cellular activity (increased cell proliferation/differentiation, cell cycle activation and anti-apoptosis), whereas a downward impact on immunity and inflammation was also observed, mostly related to the complement (down-regulation of CFH). Interestingly, we found that the microRNA MIRLET7A2 was overexpressed in the PP adipose tissue of prostate cancer patients.

                                        Conclusions

                                        Obesity and excess adiposity modified the expression of PP adipose tissue genes to ultimately foster fat mass growth. In patients with prostate cancer the expression profile of PP adipose tissue accounted for hypercellularity and reduced immunosurveillance. Both findings may be liable to promote a favorable environment for prostate cancer progression.

                                        Keywords

                                        adipose tissue gene expression microarray, obesity periprostatic prostate cancer

                                        Background

                                        Prostate cancer is the most common solid neoplasm and the second cause of cancer death in men in Europe [1]. Age, ethnic background and family history are well-established risk factors. In addition, accumulating evidence over the last years has shown that obesity is a relevant risk factor for many types of malignancies, including aggressive prostate cancer [2, 3].

                                        Adipose tissue dysfunctional behavior, often seen in obesity, has been widely appreciated as a major cause underlying cancer [4]. The prostate has a capsular-like structure and is surrounded by adipose tissue. Frequently, prostate tumor cells infiltrate the periprostatic (PP) fat pad by transposing or infiltrating the capsule [5], resulting in immediate proximity to adipose tissue. Once cancer cells extend beyond the capsule, the PP adipose tissue-secreted factors, extracellular matrix components or direct cell-cell contact may influence the phenotypic behavior of malignant cells. In fact, recent findings in PP adipose tissue showed that tumor-derived factors influence its metabolic activity profile, and that increased local production of adipokines and PP fat thickness were associated with prostate cancer aggressiveness [69]. Furthermore, while the PP adipose tissue gene expression profile is currently unknown, it is well established that adipose tissue from distinct anatomical origins and obesity status has specific gene expression signatures [10, 11]. Knowledge of the PP adipose tissue genomic profile may uncover molecules and mechanisms linked either with obesity or prostate cancer that can influence prostate cancer progression.

                                        In this study, we aimed to determine the spectrum of genes differentially expressed in PP adipose tissue as well as relevant functional clustering, in order to evaluate the influence of obesity/overweight (OB/OW) on prostate cancer and vice versa.

                                        Methods

                                        Patients

                                        Patients scheduled for retropubic radical prostatectomy or partial open prostatectomy between May and October 2009, without major co-morbidities, were included in this study after they gave informed consent. Inclusion criteria were age (45 to 75 years) and absence of previous prostatic treatments. Exclusion criteria were: diabetes, family history of prostate cancer, transvesical partial open prostatectomy, other primary malignancies, or pharmacological treatment with drugs that may modify adipose tissue gene expression (for example, anti-dislipidemics or anti-diabetics).

                                        Anterior-lateral samples of PP adipose tissue were collected during surgery. Adipose tissue samples were immediately sectioned, cleaned and rinsed with pre-warmed PBS and immersed in RNAlater (Applied Biosystems, Foster City, CA, USA).

                                        Eighteen patients participated in the study and were divided into three groups based on post-surgical diagnosis and pathologic analyses. Six patients with benign prostatic hyperplasia (BPH) and twelve with prostate cancer (six with pT1-T2, organ confined prostate cancer (OCPCa) and six with pT3-T4, extra-prostatic prostate cancer (EPCa)) met the criteria for inclusion in this study. In each prostatic disease group, three patients were lean (body mass index, BMI <25 kg/m2) and three were obese/overweight (OB/OW, BMI ≥25 kg/m2), resulting in overall nine lean and nine OB/OW. Participants' clinicopathological characteristics and serum PSA concentration at diagnosis were reviewed from clinical charts and are presented in Table 1. The project was approved, from an ethical and scientific standpoint, by the Ethical Committees responsible for research at all institutions, namely the Portuguese Institute of Oncology, Porto Hospital Centre and Porto Military Hospital in Portugal, as well as that of the Clínica Universidad de Navarra in Spain. All reported investigations were carried out in accordance with the principles of the Declaration of Helsinki as revised in 2008.
                                        Table 1

                                        Characteristics of participants included in the study

                                         

                                        BPH (n = 6)

                                        OCPCa (n = 6)

                                        EPCa (n = 6)

                                        P

                                        Age (years)

                                        67.4 ± 3.9

                                        59.4 ± 2.9

                                        66.9 ± 2.3

                                        0.140a

                                        BMI (kg/m2)

                                        26.5 ± 1.5

                                        25.2 ± 1.3

                                        26.5 ± 1.6

                                        0.783a

                                        Serum total PSA (ng/mL)

                                        8.9 ± 4.7

                                        6.7 ± 1.6

                                        14.7 ± 3.0

                                        0.114b

                                        Prostate weight (g)

                                        107.0 ± 12.9

                                        40.8 ± 4.2

                                        71.2 ± 9.5

                                        0.001a, c

                                        Serum leptin (mg/mL)

                                        3.7 ± 1.0

                                        7.1 ± 2.5

                                        4.9 ± 1.8

                                        0.453a

                                        Combined Gleason score

                                            

                                        ≤7 (3+4), n (%)

                                        ---

                                        5 (83%)

                                        4 (67%)

                                        1.000d

                                        ≥7 (4+3), n (%)

                                        ---

                                        1 (17%)

                                        2 (33%)

                                         

                                        Continuous variables are presented as mean ± SE. aANOVA for independent measures; bKruskal-Wallis test; cLSD post-hoc analysis: BPH versus organ confined PCa, P <0.0001, BPH versus extra prostatic cancer, P = 0.018, extra prostatic cancer versus organ confined PCa, P = 0.040; dFisher exact test. Median (interquartile range) values for serum total PSA: BPH, 4.7 (3.7 to 18.4) ng/mL; organ confined cancer, 5.1 (4.1 to 10.2) ng/mL; extra-prostatic cancer, 14.7 (8.3 to 21.2) ng/mL. ANOVA, analysis of variance; BMI, body mass index; BPH, benign prostatic hyperplasia; EPCa, extra prostatic cancer; OCPCa, organ confined prostate cancer; PCa, prostate cancer; PSA, prostate specific antigen.

                                        RNA extraction, microarray hybridization and data processing

                                        Total RNA was extracted from PP adipose tissue samples after homogenization with an ULTRA-TURRAX T25 basic (IKA Werke GmbH, Staufen, Germany) in QIAzol reagent (Qiagen, Valencia, CA, USA) and purified through columns (RNeasy Lipid Tissue Mini kit, Qiagen) with DNase I treatment (RNase-free DNase set, Qiagen). Integrity and purity of RNA were assessed by on-chip electrophoresis using Experion (BioRad, Hercules, CA, USA).

                                        From 1 µg total RNA, cDNA and biotin-labeled antisense cRNA were obtained and hybridized to a high-density oligonucleotide human genome array HG-U133 Plus 2.0 Affymetrix GeneChip Arrays (Affymetrix, Santa Clara, CA, USA). Background correction and normalization were done using a robust multi-array average algorithm [12]. Calculation of fold change values was performed using the lean and the non-cancer or OCPCa as reference. We used Linear Models for Microarray Data [13] to identify differentially expressed genes. Briefly, it starts by fitting a linear model for each gene in the data; then an empirical Bayes method is used to moderate the standard errors for estimating the moderated t-statistics for each gene, which shrinks the standard errors towards a common value. This test is similar to a t-test method for each probe except that the residual standard deviations are moderated across genes to ensure a more stable inference for each gene. The moderated standard deviations are a compromise between the individual genewise standard deviations and an overall pooled standard deviation. We used False Discovery Rate [14] to evaluate the statistical significance of all genes.

                                        Enrichment analysis using Ingenuity Pathway Analysis software

                                        We evaluated the gene function and network enrichments for selected genes (unadjusted P <0.01) using Ingenuity Pathway Analysis (IPA) software (Ingenuity Systems, Redwood City, The OCPCa group of patients was not included in this analysis. Human Genome Organisation (HUGO)-approved gene symbols and their corresponding fold change were uploaded into the software. Networks of these genes were algorithmically generated based on their connectivity and assigned a score. The score takes into account the number of focus genes in the network and the size of the network to approximate its relevance to the original list of focus genes. The identified networks are presented as a figure indicating molecular relationships between genes/gene products. Canonical pathway analysis identified the pathways which were more significant to the input data set.

                                        Real-Time PCR

                                        To validate the microarray data, a number of representative genes and microRNAs were selected to be studied by real-Time PCR. For gene expression analysis, cDNA was generated using the ThermoScript RT-PCR system (Invitrogen, Carlsbad, CA, USA), whereas for microRNA expression we used the Taqman MicroRNA RT kit (Applied Biosystems), according to the manufacturer's instructions.

                                        Transcript levels of the selected genes and microRNAs were quantified by Real-Time PCR (StepOne, Foster City, CA, Applied Biosystems). The cDNA was amplified using the following conditions, both for genes (Taqman Gene Expression Master Mix, Applied Biosystems) and microRNAs (Taqman Universal Master Mix, Applied Biosystems): 95°C for 10 minutes, followed by 45 cycles of 15 seconds at 95°C and 1 minute at 60°C. Results were normalized to the levels of the 18S rRNA for genes and of mir-103 for microRNA, according to previous reports using adipose tissue [15, 16]. Assays' ID are available upon request to the authors. Gene and microRNA expression was calculated using the REST 2009 software, where relative expression was expressed as fold over the reference group. The products of the PCA3 gene amplification were verified by 1.5% agarose gel electrophoresis, and acquired using the GelDoc XR system (BioRad) and Quantity One software (BioRad).

                                        Plasma leptin measurement

                                        Plasma samples were obtained before surgery after an overnight fast. The concentrations of circulating leptin were quantified using microsphere-based multiplexing technology, as previously described [17]. The intra- and inter-assay precisions were 4.2% and 21.4%, respectively. The minimum leptin detectable concentration was 27.4 pg/mL.

                                        Statistical analysis

                                        Data are presented as mean ± standard error of the mean or median (interquartile range). Departure from normality was tested using the Kolmogorov-Smirnov test. Accordingly, one-way analysis of variance (ANOVA), Kruskal-Wallis or Fisher tests were used for comparisons of clinicopathological variables between prostatic disease groups, whereas differences between OB/OW and lean groups were tested by unpaired t-test, Mann-Whitney and chi-square tests. Data analyses were performed using the software SPSS version 17.0 (SPSS Inc., Chicago, USA) and a P <0.05 was considered statistically significant.

                                        Results

                                        Patient characteristics

                                        Clinicopathological characteristics of participants according to prostatic disease status are presented in Table 1. Age at diagnosis, BMI, serum leptin and prostate specific antigen (PSA) levels, and combined Gleason grade in subjects with cancer were similar between prostatic disease groups (P >0.05 for all comparisons). In this study, as expected, BPH subjects presented heavier prostates (P <0.05). The OB/OW had higher mean BMI (29.1 ± 1.8 versus 23.1 ± 1.2 kg/m2, P <0.0001) and serum leptin levels (8.6 ± 1.3 versus 1.9 ± 0.7 mg/mL, P = 0.001) than lean subjects. For each group of prostate disease (BPH, OCPCa and EPCa), significantly higher BMI was observed in OB/OW subjects compared with lean individuals (P = 0.016, P <0.0001 and P = 0.013, respectively).

                                        PCA3 gene expression in PP adipose tissue

                                        Frequently, prostate tumor cells infiltrate the PP fat; therefore, in order to analyze the PP adipose tissue gene expression signature, we needed to confirm the absence of tumor cells. To confirm whether PP adipose tissue samples were free from prostate cancer cells the expression of the PCA3 gene was examined. Lack of expression of this gene in the PP adipose tissue of cancer patients was demonstrated (Figure 1).
                                        http://static-content.springer.com/image/art%3A10.1186%2F1741-7015-10-108/MediaObjects/12916_2012_615_Fig1_HTML.jpg
                                        Figure 1

                                        Reverse transcription PCR analysis of PCA3 in PP adipose tissue samples. GR, gene ruler 100 bp; (+) positive control (prostate tumor sample); (-) negative control (without cDNA); 1-to-6, periprostatic adipose tissue samples of patients with extra prostatic cancer.

                                        Defining the PP adipose tissue gene expression signature in OB/OW subjects

                                        Comparison of overall transcriptional response revealed 148 of the analyzed gene probe sets as significantly changed (P <0.001 and absolute fold change ≥1.5). Among these gene probe sets, gene expression features of the overall OB/OW patients associated with six altered genes, whereas OB/OW subjects in restricted BPH, OCPCa and EPCa groups exhibited a specific panoply of altered genes for each condition, which is summarized in Table 2 showing the most representative ones (Table 2).
                                        Table 2

                                        Altered genes in microarray analysis in OB/OW PP adipose tissue (overall and by prostatic disease)

                                        Probe set

                                        Gene Name

                                        Gene Description

                                        Fold Change

                                        P

                                        All subjects

                                            

                                        8098146

                                        NPY5R

                                        neuropeptide Y receptor Y5

                                        1.80

                                        1.49E-05

                                        7948612

                                        FADS1

                                        fatty acid desaturase 1

                                        -1.73

                                        1.16E-04

                                        8103494

                                        NPY1R

                                        neuropeptide Y receptor Y1

                                        1.97

                                        1.56E-04

                                        7969050

                                        CYSLTR2

                                        cysteinyl leukotriene receptor 2

                                        1.89

                                        2.19E-04

                                        8073633

                                        PNPLA3

                                        patatin-like phospholipase domain containing 3

                                        -1.56

                                        5.74E-04

                                        7930181

                                        AS3MT

                                        arsenic (+3 oxidation state) methyltransferase

                                        1.53

                                        6.54E-04

                                        BPH

                                           

                                        8020343

                                        ANKRD20A5

                                        ankyrin repeat domain 20 family; member A5

                                        -1.51

                                        3.95E-05

                                        8152297

                                        ANGPT1

                                        angiopoietin 1

                                        1.63

                                        2.08E-04

                                        7937508

                                        CD151

                                        CD151 molecule (Raph blood group)

                                        1.69

                                        2.43E-04

                                        7959102

                                        HSPB8

                                        heat shock 22kDa protein 8

                                        1.51

                                        3.88E-04

                                        8047780

                                        SNORA41

                                        small nucleolar RNA; H/ACA box 41

                                        -1.77

                                        4.94E-04

                                        8098146

                                        NPY5R

                                        neuropeptide Y receptor Y5

                                        2.06

                                        7.86E-04

                                        8135909

                                        LEP

                                        leptin

                                        1.95

                                        8.00E-04

                                        OCPCa

                                           

                                        7997239

                                        PDXDC2

                                        pyridoxal-dependent decarboxylase domain containing 2

                                        1.99

                                        8.30E-06

                                        7994026

                                        NPIPL3

                                        nuclear pore complex interacting protein-like 3

                                        1.64

                                        1.52E-04

                                        8019280

                                        PCYT2

                                        phosphate cytidylyltransferase 2; ethanolamine

                                        -1.54

                                        7.55E-04

                                        EPCa

                                          

                                        7902400

                                        SNORD45B

                                        small nucleolar RNA; C/D box 45B

                                        -4.71

                                        2.29E-04

                                        7980861

                                        CATSPERB

                                        cation channel; sperm-associated; beta

                                        1.73

                                        5.81E-04

                                        8057004

                                        PDE11A

                                        phosphodiesterase 11A

                                        2.59

                                        6.68E-04

                                        8004325

                                        EIF5A

                                        eukaryotic translation initiation factor 5A

                                        -1.50

                                        7.72E-04

                                        7969050

                                        CYSLTR2

                                        cysteinyl leukotriene receptor 2

                                        2.50

                                        9.01E-04

                                        Fold change and the corresponding P-value for each significant gene are presented, using the lean group as reference. The bold ones with adjusted P <0.2.

                                        The IPA software was used to investigate functions and interactions among altered genes. This analysis revealed a broad spectrum of biological processes for OB/OW versus lean. Altered functions were predominantly related to nutritional disease, connective tissue development and function, cell death, cellular development and cellular growth and proliferation [See Additional file 1, Table S1]. Additional file 2 Figure S1) shows the most significant network in OB/OW men (P <0.0001). In human PP adipose tissue of OB/OW the most relevantly altered canonical pathways were associated with glycerolipid metabolism and leptin signaling (Table 3), and differentially expressed genes encoded proteins involved in immunity and inflammation, cell growth and proliferation, fat metabolism and apoptosis. When restricted to the group of subjects with BPH, being OB/OW was associated with changes in the expression of genes involved in cell-to-cell signaling, tissue development and cellular movement functions [See Additional file 1, Table S1].
                                        Table 3

                                        Significant canonical pathways (P <0

                                        Pathway

                                        - log10 (P)

                                        All (OB/OW versus lean)

                                         

                                        Glycerolipid metabolism

                                        2.20

                                        Lysine degradation

                                        2.08

                                        Leptin signaling in obesity

                                        1.78

                                        BPH (OB/OW versus lean)

                                         

                                        ERK5 signaling

                                        2.31

                                        β-alanine metabolism

                                        1.83

                                        AMPK signaling

                                        1.81

                                        Parkinson's signaling

                                        1.77

                                        C21-steroid hormone metabolism

                                        1.77

                                        EPCa (OB/OW versus lean)

                                         

                                        Histidine metabolism

                                        1.91

                                        Eicosanoid signaling

                                        1.77

                                        Linoleic acid metabolism

                                        1.73

                                        All (EPCa versus BPH)

                                         

                                        Antigen presentation pathway

                                        3.11

                                        Aminosugars metabolism

                                        2.09

                                        B cell development

                                        1.81

                                        OX40 signaling pathway

                                        1.77

                                        ERK5 signaling

                                        1.59

                                        p53 signaling

                                        1.55

                                        Lean (EPCa versus BPH)

                                         

                                        T helper cell differentiation

                                        2.24

                                        Galactose metabolism

                                        1.68

                                        Hereditary breast cancer signaling

                                        1.62

                                        Role of osteoblasts, osteoclasts and condrocytes in rheumatoid arthritis

                                        1.51

                                        OB/OW (EPCa versus BPH)

                                         

                                        Synaptic long term depression

                                        2.89

                                        Urea cycle and metabolism of aminogroups

                                        2.10

                                        p53 signaling

                                        2.10

                                        Amyothropic lateral sclerosis signaling

                                        2.02

                                        Aminosugars metabolism

                                        1.89

                                        Extrinsic prothrombin activation pathway

                                        1.73

                                        p70S6K signaling

                                        1.68

                                        Cardiac β-adrenegic signaling

                                        1.51

                                        BPH, benign prostatic hyperplasia; EPCa, extra prostatic cancer; OB/OW, obese/overweight.

                                        Defining the PP adipose tissue gene expression signature in prostate cancer patients

                                        Table 4 shows differentially expressed genes according to prostatic disease (P <0.001 and absolute fold change ≥1.5). We found that in the PP adipose tissue of EPCa patients eight genes were up-regulated compared to BPH, while in OCPCa versus BPH most of the genes were down-regulated; a predominance of up-regulated genes was observed in EPCa compared to OCPCa. The PP adipose tissue of cancer patients exhibited increased transcript levels of MIRLET7A2 and TC2N compared with BPH. Interestingly, MIRLET7A2 and MRPL42 were overexpressed in all analyses (overall, and within lean and OB/OW groups) in the PP adipose tissue of patients with EPCa. In OB/OW subjects three genes were consistently overexpressed (TC2N, MIRLET7A2 and CLDN10) in the PP adipose tissue of men with cancer (EPCa or OCPCa), compared to BPH.
                                        Table 4

                                        Altered genes in microarray according to prostatic disease status (overall, OB/OW or lean group)

                                        Probe set

                                        Gene Name

                                        Gene Description

                                        Fold Change

                                        P

                                        Extra Prostatic Cancer versus Benign Prostatic Hyperplasia

                                          

                                        All subjects

                                            

                                        7952313

                                        MIRLET7A2

                                        microRNA let-7a-2

                                        2.00

                                        4.26E-06

                                        7957540

                                        MRPL42

                                        mitochondrial ribosomal protein L42

                                        1.63

                                        5.49E-06

                                        7980891

                                        TC2N

                                        tandem C2 domains; nuclear

                                        2.25

                                        8.26E-06

                                        7915468

                                        CCDC23

                                        coiled-coil domain containing 23

                                        1.70

                                        1.93E-05

                                        8002020

                                        TPPP3

                                        tubulin polymerization-promoting protein family member 3

                                        1.66

                                        8.62E-05

                                        7980861

                                        CATSPERB

                                        cation channel; sperm-associated; beta

                                        1.84

                                        1.48E-04

                                        7964927

                                        TSPAN8

                                        tetraspanin 8

                                        1.91

                                        2.31E-04

                                        8168463

                                        FGF16

                                        fibroblast growth factor 16

                                        1.67

                                        2.93E-04

                                        Lean subjects

                                           

                                        7952313

                                        MIRLET7A2

                                        microRNA let-7a-2

                                        2.12

                                        9.04E-05

                                        8024485

                                        GADD45B

                                        growth arrest and DNA-damage-inducible; beta

                                        -1.56

                                        9.47E-04

                                        7957540

                                        MRPL42

                                        mitochondrial ribosomal protein L42

                                        1.60

                                        9.86E-04

                                        OB/OW subjects

                                           

                                        7980861

                                        CATSPERB

                                        cation channel; sperm-associated; beta

                                        2.50

                                        1.91E-06

                                        7980891

                                        TC2N

                                        tandem C2 domains; nuclear

                                        2.98

                                        4.31E-06

                                        7908488

                                        CFHR1

                                        complement factor H-related 1

                                        1.88

                                        3.16E-05

                                        8078529

                                        STAC

                                        SH3 and cysteine rich domain

                                        1.50

                                        5.79E-05

                                        7902400

                                        SNORD45B

                                        small nucleolar RNA; C/D box 45B

                                        -5.18

                                        1.9E-04

                                        7908459

                                        CFH

                                        complement factor H

                                        1.70

                                        3.0E-04

                                        7952313

                                        MIRLET7A2

                                        microRNA let-7a-2

                                        1.88

                                        4.0E-04

                                        7957540

                                        MRPL42

                                        mitochondrial ribosomal protein L42

                                        1.65

                                        4.0E-04

                                        7958019

                                        DRAM1

                                        DNA-damage regulated autophagy modulator 1

                                        1.55

                                        5.3E-04

                                        7969640

                                        CLDN10

                                        claudin 10

                                        1.59

                                        6.3E-04

                                        8076586

                                        SCUBE1

                                        signal peptide; CUB domain; EGF-like 1

                                        -1.73

                                        7.2E-04

                                        8027862

                                        FFAR2

                                        free fatty acid receptor 2

                                        -1.58

                                        9.2E-04

                                        Organ Confined Prostate Cancer versus Benign Prostatic Hyperplasia

                                          

                                        All subjects

                                            

                                        7919349

                                        RNU1-1

                                        RNA; U1 small nuclear 1

                                        -2.18

                                        1.50E-07

                                        7919576

                                        RNU1-1

                                        RNA; U1 small nuclear 1

                                        -1.96

                                        2.47E-07

                                        7952313

                                        MIRLET7A2

                                        microRNA let-7a-2

                                        1.79

                                        6.21E-05

                                        7980891

                                        TC2N

                                        tandem C2 domains; nuclear

                                        1.98

                                        6.26E-05

                                        7978568

                                        RNU1-1

                                        RNA; U1 small nuclear 1

                                        -1.65

                                        9.43E-05

                                        7981964

                                        SNORD116-8

                                        small nucleolar RNA; C/D box 116-8

                                        -1.91

                                        1.07E-04

                                        8004184

                                        XAF1

                                        XIAP associated factor 1

                                        -1.64

                                        8.67E-04

                                        Lean subjects

                                           

                                        8001067

                                        HERC2P4

                                        hect domain and RLD 2 pseudogene 4

                                        -1.77

                                        1.22E-06

                                        7997239

                                        PDXDC2

                                        pyridoxal-dependent decarboxylase domain containing 2

                                        -2.12

                                        2.69E-06

                                        8000692

                                        BOLA2

                                        bolA homolog 2 (E, coli)

                                        -1.52

                                        3.41E-06

                                        8000651

                                        SMG1

                                        SMG1 homolog; phosphatidylinositol 3-kinase-related kinase (C. elegans)

                                        -1.61

                                        3.76E-06

                                        8019655

                                        TBC1D3B

                                        TBC1 domain family; member 3B

                                        -1.56

                                        1.26E-05

                                        7919349

                                        RNU1-1

                                        RNA; U1 small nuclear 1

                                        -2.30

                                        2.27E-05

                                        7927513

                                        FAM21C

                                        family with sequence similarity 21; member C

                                        -1.66

                                        2.31E-05

                                        7993359

                                        NPIP

                                        nuclear pore complex interacting protein

                                        -1.53

                                        4.30E-05

                                        8014633

                                        TBC1D3

                                        TBC1 domain family; member 3

                                        -1.55

                                        5.53E-05

                                        8014437

                                        TBC1D3G

                                        TBC1 domain family; member 3G

                                        -1.51

                                        6.27E-05

                                        7994026

                                        NPIPL3

                                        nuclear pore complex interacting protein-like 3

                                        -1.69

                                        9.02E-05

                                        OB/OW subjects

                                           

                                        7969640

                                        CLDN10

                                        claudin 10

                                        2.01

                                        7.04E-06

                                        7980891

                                        TC2N

                                        tandem C2 domains; nuclear

                                        2.31

                                        1.10E-04

                                        7952313

                                        MIRLET7A2

                                        microRNA let-7a-2

                                        2.06

                                        1.74E-04

                                        8021101

                                        HAUS1

                                        HAUS augmin-like complex; subunit 1

                                        1.61

                                        3.10E-04

                                        8165698

                                        MIR1977

                                        microRNA 1977

                                        -3.03

                                        3.46E-04

                                        8060854

                                        PLCB1

                                        phospholipase C; beta 1 (phosphoinositide-specific)

                                        1.53

                                        5.95E-04

                                        Extra Prostatic Cancer versus Organ Confined Prostate Cancer

                                          

                                        All subjects

                                            

                                        7919349

                                        RNU1-1

                                        RNA; U1 small nuclear 1

                                        1.71

                                        1.86E-05

                                        7981964

                                        SNORD116-8

                                        small nucleolar RNA; C/D box 116-8

                                        1.88

                                        1.85E-04

                                        7940287

                                        MS4A1

                                        membrane-spanning 4-domains; subfamily A; member 1

                                        -2.15

                                        2.74E-04

                                        Lean subjects

                                           

                                        8001067

                                        HERC2P4

                                        hect domain and RLD 2 pseudogene 4

                                        2.06

                                        5.14E-08

                                        8000692

                                        BOLA2

                                        bolA homolog 2 (E, coli)

                                        1.52

                                        3.37E-06

                                        7997239

                                        PDXDC2

                                        pyridoxal-dependent decarboxylase domain containing 2

                                        2.00

                                        6.36E-06

                                        8000651

                                        SMG1

                                        SMG1 homolog; phosphatidylinositol 3-kinase-related kinase (C. elegans)

                                        1.57

                                        6.75E-06

                                        7927513

                                        FAM21C

                                        family with sequence similarity 21; member C

                                        1.74

                                        8.44E-06

                                        7993359

                                        NPIP

                                        nuclear pore complex interacting protein

                                        1.51

                                        5.38E-05

                                        7994026

                                        NPIPL3

                                        nuclear pore complex interacting protein-like 3

                                        1.73

                                        5.61E-05

                                        8119595

                                        RPL7L1

                                        ribosomal protein L7-like 1

                                        1.63

                                        5.71E-05

                                        7990943

                                        GOLGA6L10

                                        golgin A6 family-like 10

                                        1.55

                                        6.08E-05

                                        7919349

                                        RNU1-1

                                        RNA; U1 small nuclear 1

                                        1.93

                                        2.25E-04

                                        OB/OW subjects

                                           

                                        7980861

                                        CATSPERB

                                        cation channel; sperm-associated; beta

                                        1.78

                                        2.92E-04

                                        7982006

                                        SNORD116-29

                                        small nucleolar RNA; C/D box 116-29

                                        1.77

                                        5.84E-04

                                        The bold ones with adjusted P <0.2

                                        In the analysis of prostate cancer versus BPH, OB/OW subjects presented more altered genes in PP adipose tissue. The IPA analysis identified interaction networks between EPCa versus BPH and found that functions were more frequently related to cellular growth and proliferation, cell cycle, apoptosis and cell death, cellular movement and to inflammation and immunity [See Additional file 3, Table S2] (P <0.0001). The altered canonical pathways (P <0.05) in the PP adipose tissue of EPCa are shown in Table 3.

                                        Validation of selected genes by real-time PCR

                                        Validation experiments were performed to confirm the accuracy of array gene expression measurements. We selected a set of representative transcripts involved in cell proliferation, immunity and lipid metabolism. Results across the 18 study patients are shown in Figure 2. Overall, PCR results reflected the findings of microarrays.
                                        http://static-content.springer.com/image/art%3A10.1186%2F1741-7015-10-108/MediaObjects/12916_2012_615_Fig2_HTML.jpg
                                        Figure 2

                                        Validation of selected genes by real-time PCR. BPH, benign prostatic hyperplasia; EPCa, extra prostatic cancer (≥pT3); Lean (BMI <25 kg/m2); OB/OW, obese/overweight (BMI ≥25 kg/m2). ANGPT1, angiopoietin 1; CFH, complement factor H; CLDN10, claudin 10; FAS, fatty acid desaturase; LEP, leptin; MIRLET7A2, microRNA let-7a-2. The gene expression in lean subjects or BHP was assumed to be 1. *P <0.05 versus lean or BPH groups.

                                        Discussion

                                        Extra-capsular extension of prostate cancer cells into the PP adipose tissue is a common pathologic finding and a factor related with worst prognosis [5]. Once tumor cells extend beyond the prostatic capsule, the interactions with non-tumor cells in the PP adipose tissue may influence its phenotypic behavior. In fact, accumulating evidence shows that the microenvironment is decisive in determining whether cancer cells progress towards metastasis or whether they remain dormant [18]. To date, the scarce reports on PP adipose tissue support a mechanistic link with prostate cancer aggressiveness [69].

                                        In the present study, 46% of the well-characterized genes included in the array were expressed at detection level in PP adipose tissue, which is comparable to omental adipose tissue [11]. The comparison of PP adipose tissue gene expression of non-diabetic OB/OW men to lean men with prostatic disease identified, for the first time, 34 differentially expressed genes of which we focused our attention on 20 as the most relevant ones.

                                        Two important but opposed pathways, lipolysis and adipo/lipogenesis, have a significant role in energy balance. In our study, consistent with other reports on visceral adipose tissue [11], altered expression of genes involved in lipolysis were found in association with obesity and excess adiposity. NPY1R and NPY5R have anti-lipolytic effects [19], whereas LEP expression relates to adipo/lipogenesis despite leptin being also a lipolytic factor [20], with all of these overexpressed genes being in the PP adipose tissue of OB/OW men. Noteworthy, PDE11, which has been shown to be involved in adipocyte differentiation and cyclic nucleotides biology [21], was overexpressed in PP adipose tissue of OB/OW subjects. Downstream effects of altered genes reportedly up-regulate adipo/lipogenesis, including PNPLA3 (also known as adiponutrin), which encodes a triacylglycerol lipase that mediates triacylglycerol hydrolysis [22], FADS1, that regulates unsaturation of fatty acids and SREBP-1 expression [23] or PCYT2, that mediates phosphatidylethanolamine synthesis and the availability of di- and triacylglycerol [24]. The combined functional dysregulation of these genes suggests that PP adipose tissue from obese men exhibits an anti-lipolytic and adipo/lipogenic gene expression profile.

                                        The number and volume of adipocytes are determinants of fat mass, while proliferation/differentiation and apoptosis influence adipose tissue growth and regression. In our study, the anti-apoptotic genes ANGPT1 and HSPB8 were up-regulated in PP adipose tissue of OB/OW subjects [25, 26]. Furthermore, the expression of EIF5A, known to activate the intrinsic mitochondrial pathway [27], was repressed in OB/OW men. Besides altered genes in apoptosis pathways, we found an increased expression of genes involved in cell growth and differentiation, such as LEP and ANGPT1, whose products increase endothelial, mesenchymal and tumor cell growth and differentiation [25, 2830], and NPY1R that mediates a proliferative stimulus in progenitor adipose cells [31]. The data presented here suggest an increased cell growth and anti-apoptosis, extensive to endothelial, progenitor or adult lineages in the PP adipose tissue of OB/OW men.

                                        Taken together, these anti-lipolytic, adipo/lipogenic, proliferative and anti-apoptotic effects in the PP adipose tissue of OB/OW men likely result in fat mass expansion, conferring increased capacity for enlarged adipocytes to express adipokines and increase fatty acid supplies [32, 33], which might impact the local energy and availability of growth factors, thereby causing the local environment to allow cancer progression. This environment in the PP adipose tissue of OB/OW men may, at least partially, explain the described association of obesity and excess adiposity with the progression of prostate cancer [3] (Figure 3). In addition to a local paracrine effect of adipose tissue-derived factors, obesity-related systemic factors may also influence the development of an aggressive phenotype [34].
                                        http://static-content.springer.com/image/art%3A10.1186%2F1741-7015-10-108/MediaObjects/12916_2012_615_Fig3_HTML.jpg
                                        Figure 3

                                        Schematic summary diagram of PP adipose tissue changes in obese/overweight. Genes with altered expression are associated with the regulation of functional biological processes. Altered function likely results in chronic mild immunoinflammatory response and fat mass expansion, which ultimately impacts on prostate cancer progression. Down-regulated genes are depicted in green while up-regulated genes are shown in red. ASCs, adipose-derived stem cells; E-M-T, epithelial-to-mesenchymal transition.

                                        Recent developments in obesity and cancer immunological pathways suggest a previously unappreciated complexity of cancer cell-adipose tissue cell-immunoinflammatory cell cross-talk [35]. We found altered genes in PP adipose tissue of OB/OW men that are involved in immunity and inflammation. Overexpressed genes engaged in innate and adaptive components of the immune system, include LEP, that up-regulates both innate and adaptive immunoinflammatory response [36], NPY1R, that has been shown to inhibit T cell activation [37], and CYSTLR2, that increases pro-inflammatory cytokine expression [38]. FADS1, known to mediate the formation of inflammatory mediators (for example, prostaglandin E2, PGE2, thromboxane A2, TXA2, and leukotriene B4, LTB4) [39], and EIF5A that is essential for NOS2 translation [40], are both down-regulated in the PP adipose tissue of OB/OW men. Thus, the enhanced local mild immunoinflammatory environment, observed in PP adipose tissue of OB/OW men might further influence tissue remodeling and contribute towards tumor progression.

                                        The LEP and ANGPT1 encoded proteins may have roles beyond adipose tissue itself. Prostate cancers express the leptin receptor [41] and leptin staining is significantly increased in malignant prostates and poorly differentiated tumors [41]. Also angiopoietin 1 and its receptor Tie-2 were found in both prostate tumor cells and capillaries [42], where they can induce sprouting angiogenesis [43]. These findings along with our own suggest that PP adipose tissue may modulate prostate cancer progression via production of growth factors that favor proliferative and angiogenic events that in turn are needed for tumor development.

                                        Herein, we showed that the PP adipose tissue gene expression profile of OB/OW subjects may contribute to increased local adiposity, a mild immunoinflammatory environment and production of molecules with oncogenic potential (Figure 3).

                                        The PP adipose tissue gene expression signature of men with prostate cancer was determined, in order to determine if functional alterations are associated with prostate cancer besides the previously reported PP thickness and protein measurements [912]. In the present study, when the PP adipose tissues of age- and BMI-matched nondiabetic men with different prostatic diseases were compared, 119 altered genes were found. Representative genes and functions are shown in Figure 4. Noteworthy, our findings reveal that altered gene networks pertain to cell cycle and proliferation regulation. Overexpressed genes in the PP adipose tissue of cancer patients that are involved in cell cycle and proliferation include PLCB1, that modulates cyclin D3 and CDK4 in response to the IGF-1 mitogenic stimulus [44] or TPPP3, that regulates G2-M and G1-S transitions [45]. Furthermore, HAUS1, a component of the augmin complex involved in spindle microtubule generation in mitosis [46] and TSPAN8 (also known as CO-029), that encodes for an integrin-binding glycoprotein that stimulates endothelial cell proliferation [47], are also up-regulated in cancer patients. Noteworthy, the FGF16 gene that encodes a mitogenic growth factor [48] was overexpressed in the PP adipose tissue of men with prostate cancer. These findings, together with the down-regulation of XAF1, which influences G2/M arrest through modulation of checkpoint kinase 1 and Cdc2-cyclin B complex [49], support a positive cell cycle regulation and a permissive stimulus for growth and proliferation in PP adipose tissue cells. Cumulatively, pro-apoptotic genes, such as XAF1 and GADD45B [50, 51] were down-regulated, whereas DRAM1 was up-regulated in the adipose tissue of prostate cancer patients [52]. Canonical analysis showed involvement of the p53 pathway in adipose tissue of cancer subjects, possibly reflecting the relationship of the altered genes XAF1, DRAM1 and SMG1 with the p53 pathway. In adipose tissue biology, cell differentiation also plays an important role in increasing fat mass. Here we show altered expression of genes that associate with cellular differentiation of overall (for example, PLCB1, GADD45B), adipocyte (for example, PLCB1, FFAR2) and endothelial lineages (for example, SCUBE1) [44]. Thus, particularly the adipocyte and vascular biology of PP adipose tissue seems to be committed towards the differentiated state in men with prostate cancer. Consistent with gene expression findings, we observed overexpression of the microRNA MIRLETA2 in the PP adipose tissue of prostate cancer patients. The involvement of the let-7 microRNA in adipocyte differentiation has been described earlier [53]. Moreover, canonical pathways analysis showed that ERK5 signaling, an evolutionary conserved pathway involved in hypertrophic signaling that regulates adipogenic differentiation [54], was altered in PP adipose tissue of cancer patients. Previously, in vitro studies showed that tumor-derived factors induce preadipocyte differentiation [55], supporting a tumor-educated regulation of the adipose tissue differentiation program. Taken together, the impact of these gene expression results on cell cycle and proliferation, in apoptosis and differentiation of PP adipose tissue cellular components, supports fat mass accrual, which agrees with findings showing increased PP fat pad thickness in prostate cancer patients [6]. Furthermore, bulky adipocytes predispose to increased adipokine secretion and availability of fatty acids, which may influence prostate cancer progression [32, 33].
                                        http://static-content.springer.com/image/art%3A10.1186%2F1741-7015-10-108/MediaObjects/12916_2012_615_Fig4_HTML.jpg
                                        Figure 4

                                        Schematic summary diagram of changes in PP adipose tissue of patients with prostate cancer. Periprostatic adipose tissue of patients bearing prostate cancer likely reveals the interactions between tumor cells and adipose tissue cells. The functional repercussions of altered genes in patients with prostate cancer prompt PP adipose tissue to increased hypercellularity and decreased immunosurveillance. The resulting influence of this favorable microenvironment is to foster prostate cancer progression. Down-regulated genes are depicted in green while up-regulated genes are shown in red. ASCs, adipose-derived stem cells.

                                        Immunoinflammatory mechanisms drive both obesity and cancer. Canonical analysis showed that the PP adipose tissue of prostate cancer patients presents altered pathways associated with immunity and inflammation, including antigen presentation, B cell development and T helper cell differentiation. The complement system is important in immunosurveillance against tumors, albeit malignant cells are usually resistant to complement-mediated lysis [56]. The products of CFH and CFHR1 are soluble complement regulators essential for preventing complement activation and, therefore, responsible for complement inhibition [56]. Interestingly, we and others report on the expression of CFH and CFHR1 in adipose tissue [57]. The finding of CFH and CFHR1 up-regulation in PP adipose tissue of subjects with prostate cancer suggests increased inhibitory modulation of the complement activity in prostate tumor cells and evasion to attack. Other altered genes in the PP adipose tissue of prostate cancer patients with repercussion in the local immunoinflammatory environment include MS4A1 (also known as CD20) that plays a functional role in B-cell activation [58] and FFAR2 that encodes a protein reported to modulate the differentiation and/or activation of leukocytes [59]. Taken together, these altered genes in PP adipose tissue might contribute to an environment with immunological cellular dormancy and reduced immunosurveillance, which may facilitate prostate cancer progression (Figure 4).

                                        In the present study, we found increased CLDN10 mRNA transcript abundance in the PP adipose tissue of prostate cancer patients using both microarray and real-time PCR analyses. To the best of our knowledge CLDN10 expression in adipose tissue has not been previously reported. This gene encodes an important tight junction component with an intriguing role in adipose tissue considering its functions in the stroma arrangement and cellular connections [60]. Further studies are required to obtain insight regarding the cells involved and the functional implications of CLDN10 expression in PP adipose tissue.

                                        A global gene expression profiling in PP adipose tissue has been applied for the first time in the present study to unravel genes and regulatory pathways associated with OB/OW and with prostate cancer. Subjects included in this study had histopathological confirmation of prostatic disease, pathology tumor grade and stage, while contamination with prostate tumor cells in the collected PP adipose tissue samples was excluded by the absence of PCA3 expression. The high-quality GeneChip data set from RNA specimens of PP adipose tissue, careful patient selection for matching by age, race, BMI and clinical variables underscore the strength of the major findings of this study. However, further research is warranted to uncover the PP adipose tissue gene expression profile in association with distinct obesity grades.

                                        Our findings likely represent the effects of excess adiposity or cancer and the bi-directional interactions between all cell types that influence adipose tissue function and might affect or be influenced by prostate cancer progression. These hypotheses are grounded on the crosstalk between PP adipose tissue and tumor cells, which ultimately may induce an environment favorable to cancer progression. A better understanding of the mechanisms underlying the association between obesity and aggressive prostate cancer is warranted to gain more insight into the specific contribution of each PP adipose tissue cell type to cancer development in order to foster the development of new treatment options and, at the same time, to help identify malignancies with the worst prognosis and encourage the implementation of adjuvant chemoprevention strategies.

                                        Conclusions

                                        The present study, the first in human PP adipose tissue in which OB/OW and prostate cancer-associated gene expression changes are analyzed by microarrays, provides valuable new insight on how local adipose tissue pathophysiology may favor prostate cancer. We identified altered gene expression that might impact on elements of white adipose tissue overgrowth, including anti-lipolytic, anti-apoptotic, proliferative, and mild local immunoinflammatory stimuli in PP fat of OB/OW subjects. The overexpression of LEP and ANGPT1 by PP adipose tissue in OB/OW men may contribute towards a favorable environment for prostate cancer progression.

                                        The gene expression signature of PP adipose tissue from prostate cancer patients seems to provide evidence of altered gene expression across distinct cell types, with repercussions on stimuli for cell cycle regulation, cell proliferation and differentiation, as well as anti-apoptosis. Additionally, we found altered genes involved in immunological cell dormancy and reduced immunosurveillance, namely complement-related CFH and CFHR1 genes. Our findings suggest that the PP adipose tissue gene expression profile of both OB/OW and prostate cancer subjects is likely to cause a local environment favorable to prostate cancer progression. Confirmation of the role of PP adipose tissue in prostate cancer progression together with untangling its mechanisms will become increasingly important in the development of adjuvant therapeutic and lifestyle measures.

                                        Abbreviations

                                        BMI: 

                                        body mass index

                                        BPH: 

                                        benign prostatic hyperplasia

                                        EPCa: 

                                        extra-prostatic cancer

                                        IPA: 

                                        Ingenuity Pathway Analysis

                                        OB/OW: 

                                        obese/overweight

                                        OCPCa: 

                                        organ confined prostate cancer

                                        PBS: 

                                        phosphate-buffered saline

                                        PCR: 

                                        polymerase chain reaction

                                        PP: 

                                        periprostatic.

                                        Declarations

                                        Acknowledgements

                                        The authors acknowledge the Portuguese Foundation for Science and Technology (PTDC/SAL-FCF/71552/2006 and PTDC/SAU-ONC/112511/2009), the Research Centre on Environment, Genetics and Oncobiology of the University of Coimbra (CIMAGO 07/09), the Portuguese League Against Cancer - North Centre as well as the Spanish Institute of Science and CIBERobn. This project was partially sponsored by an unrestricted educational grant for basic research in Molecular Oncology from Novartis Oncology Portugal. RR was the recipient of a PhD grant from POPH/FSE (SFRH/BD/30021/2006) and a UICC-ICRETT Fellowship (ICR/10/079/2010). This work was supported in part by a project grant of the Spanish Fondo de Investigación Sanitaria (FIS PI09/02330) to GF. Funders had no role in the design, collection, analysis, and interpretation of data, in the writing of the manuscript, and in the decision to submit the manuscript for publication.

                                        Authors’ Affiliations

                                        (1)
                                        Molecular Oncology Group, Portuguese Institute of Oncology
                                        (2)
                                        ICBAS, Abel Salazar Biomedical Sciences Institute, University of Porto, Rua de Jorge Viterbo Ferreira nº 228
                                        (3)
                                        Metabolic Research Laboratory, Clínica Universidad de Navarra
                                        (4)
                                        LPCC - Portuguese League Against Cancer (NRNorte)
                                        (5)
                                        CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III
                                        (6)
                                        The Center for Applied Genomics, Hospital for Sick Children, MaRS Centre
                                        (7)
                                        Urology Department, Porto Hospital Centre
                                        (8)
                                        Urology Department, D. Pedro V Military Hospital
                                        (9)
                                        Urology Department, Portuguese Institute of Oncology
                                        (10)
                                        Urology Department, S. João Hospital
                                        (11)
                                        CEBIMED, Faculty of Health Sciences of Fernando Pessoa University
                                        (12)
                                        Department of Endocrinology & Nutrition, Clínica Universidad de Navarra

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                                        61. Pre-publication history

                                          1. The pre-publication history for this paper can be accessed here:http://​www.​biomedcentral.​com/​1741-7015/​10/​108/​prepub

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