Simultaneously detection of genomic and expression alterations in prostate cancer using cDNA microarray

The Promise of Combination Therapies with FOXM1 Inhibitors for Cancer Treatment

Forkhead box M1 (FOXM1) is a transcription factor in the forkhead (FOX) family, which is required for cellular proliferation in normal and neoplastic cells. FOXM1 is highly expressed in many different cancers, and its expression is associated with a higher tumor stage and worse patient-related outcomes. Abnormally high expression of FOXM1 in cancers compared to normal tissue makes FOXM1 an attractive target for pharmacological inhibition. FOXM1-inhibiting agents and specific FOXM1-targeted small-molecule inhibitors have been developed in the lab and some of them have shown promising efficacy and safety profiles in mouse models. While the future goal is to translate FOXM1 inhibitors to clinical trials, potential synergistic drug combinations can maximize anti-tumor efficacy while minimizing off-target side effects. Hence, we discuss the rationale and efficacy of all previously studied drug combinations with FOXM1 inhibitors for cancer therapies.

Establishment of a Genomic-Clinicopathologic Nomogram for Predicting Early Recurrence of Hepatocellular Carcinoma After R0 Resection

BACKGROUND

A high rate of postoperative recurrence, especially early recurrence (ER) occurring within 1 year, seriously impedes patients with hepatocellular carcinoma (HCC) from achieving long-term survival. This study aimed to establish a genomic-clinicopathologic nomogram for precisely predicting ER in HCC patients after R0 resection.

METHODS

Two reliable datasets from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases were selected as the training and validation cohorts, respectively. The prognostic genes related to ER were screened out by univariate Cox regression analysis and differential expression analysis. The gene-based prognostic index was constructed using LASSO and Cox regression analyses, and its independent prognostic value was assessed by Kaplan-Meier and multivariate Cox analyses. Gene set enrichment analysis (GSEA) was performed to explore the biological pathways related to the prognostic index. Finally, the nomogram integrating all the independent prognostic factors was established and comprehensively evaluated by calibration plots, the C-index, receiver operating characteristic curves, and decision curve analysis.

RESULTS

Nine dysregulated and prognostic genes related to ER (ZNF131, TATDN2, TXN, DDX55, KPNA2, ZNF30, TIMELESS, SFRP1, and COLEC11) were identified (all P < 0.05). The prognostic index model based on the 9 genes was successfully constructed using the TCGA cohort and showed a certain capability to discriminate the ER group from the non-ER group (P < 0.05) and good independent prognostic value in terms of predicting poor early recurrence-free survival (P < 0.05). Eight biological pathways significantly related to ER were identified by GSEA, such as "cell cycle", "homologous recombination" and "p53 signaling pathway." The genomic-clinicopathologic nomogram integrating the 9-gene-based prognostic index and TNM stage displayed significantly higher predictive accuracy and clinical application value than that of TNM stage model both in the training and validation cohorts (all P < 0.05).

CONCLUSIONS

The novel genomic-clinicopathologic nomogram may be a convenient and powerful tool for accurately predicting ER in HCC patients after R0 resection.

Network analysis for count data with excess zeros

BACKGROUND

Undirected graphical models or Markov random fields have been a popular class of models for representing conditional dependence relationships between nodes. In particular, Markov networks help us to understand complex interactions between genes in biological processes of a cell. Local Poisson models seem to be promising in modeling positive as well as negative dependencies for count data. Furthermore, when zero counts are more frequent than are expected, excess zeros should be considered in the model.

METHODS

We present a penalized Poisson graphical model for zero inflated count data and derive an expectation-maximization (EM) algorithm built on coordinate descent. Our method is shown to be effective through simulated and real data analysis.

RESULTS

Results from the simulated data indicate that our method outperforms the local Poisson graphical model in the presence of excess zeros. In an application to a RNA sequencing data, we also investigate the gender effect by comparing the estimated networks according to different genders. Our method may help us in identifying biological pathways linked to sex hormone regulation and thus understanding underlying mechanisms of the gender differences.

CONCLUSIONS

We have presented a penalized version of zero inflated spatial Poisson regression and derive an efficient EM algorithm built on coordinate descent. We discuss possible improvements of our method as well as potential research directions associated with our findings from the RNA sequencing data.

Genomic deletion of chromosome 12p is an independent prognostic marker in prostate cancer

Deletion of 12p is a recurrent alteration in prostate cancer, but the prevalence and clinical consequences of this alteration have not been studied in detail. Dual labeling fluorescence in situ hybridization using probes for 12p13 (CDKN1B; p27) and centromere 12 as a reference was used to successfully analyze more than 3700 prostate cancers with clinical follow-up data assembled in a tissue microarray format. CDKN1B was selected as a probe because it is located in the center of the deletion, which spans > 10 Mb and includes > 50 genes in 80% of cancers with 12p deletion. Deletion of 12p was found in 13.7% of cancers and included 13.5% heterozygous and 0.2% homozygous deletions. 12p deletion were linked to advanced tumor stage (p < 0.0001), high Gleason grade (p < 0.0001), rapid tumor cell proliferation (p < 0.0001), lymph node metastasis (p = 0.0004), and biochemical recurrence (p = 0.0027). Multivariate analysis including pT stage (p < 0.0001), Gleason grade (p < 0.0001), pN status (p = 0.0001), preoperative PSA levels (p = 0.0001), and resection margin status (p = 0.0001) revealed an independent prognostic value of 12p deletion (p = 0.0014). Deletion of 12p was unrelated to the ERG fusion status. Deletion of 12p was only marginally linked to reduced p27 expression, which by itself was unrelated to clinical outcome. This argues against p27 as the key target gene of 12p deletions. In summary, the results of our study demonstrate that 12p deletion is frequent in prostate cancer and provides independent prognostic information. 12p deletion analysis alone, or in combination with other prognostic parameters may thus have clinical utility.

Corrections for mRNA extraction and sample normalization errors find increased mRNA levels may compensate for cancer haplo-insufficiency

The relative mRNA levels of differentially expressed (DE) and housekeeping (HK) genes of six aneuploid cancer lines with large-scale genomic changes identified by SNP/SKY analysis were compared with similar genes in diploid cells. The aneuploid cancer lines had heterogeneous genomic landscapes with subdiploid, diploid, and supradiploid regions and higher overall gene copy numbers compared with diploid cells. The mRNA levels of the haploid, diploid, and triploid HK genes were found to be higher after correction of easily identifiable mRNA measurement errors. Surprisingly, diploid and aneuploid HK gene mRNA levels were the same by standard expression array analyses, despite the higher copy numbers of the cancer cell HK genes. This paradoxical result proved to be due to inaccurate inputs of true intra-cellular mRNAs for analysis. These errors were corrected by analyzing the expression intensities of DE and HK genes in mRNAs extracted from equal cell numbers (50:50) of intact cancer cell and lymphocyte mixtures. Correction for both mRNA extraction/sample normalization errors and total gene copy numbers found the SUIT-2 and PC-3 cell lines' cancer genes both had ∼50% higher mRNA levels per single allele than lymphocyte gene alleles. These increased mRNA levels for single transcribed cancer alleles may restore functional mRNA levels to cancer genes rendered haplo-insufficient by the genetic instability of cancer. © 2013 Wiley Periodicals, Inc.

Integrative analysis of prostate cancer aggressiveness

BACKGROUND

Clinical management of prostate cancer (PC) is still highly demanding on the identification of robust biomarkers which will allow a more precise prediction of disease progression.

METHODS

We profiled both mRNA expression and DNA copy number alterations (CNAs) from laser capture microdissected cells from 31 PC patients and 17 patients with benign prostatic hyperplasia using Affymetrix GeneChip® technology. PC patients were subdivided into an aggressive (Gleason Score 8 or higher, and/or T3/T4 and/or N+/M+) and non-aggressive (all others) form of PC. Furthermore, we correlated the two datasets, as genes whose varied expression is due to a chromosomal alteration, may suggest a causal implication of these genes in the disease. All statistical analyses were performed in R version 2.15.0 and Bioconductor version 1.8.1., respectively.

RESULTS

We confirmed several common altered chromosomal regions as well as recently discovered loci such as deletions on chromosomes 3p14.1-3p13 and 13q13.3-13q14.11 supporting a possible role for RYBP, RGC32, and ELF1 in tumor suppression. Integrative analysis of expression and CN data combined with data retrieved from online databases propose PTP4A3 and ELF1 as possible factors for tumor progression.

CONCLUSIONS

Copy number data analysis revealed some significant differences between aggressive and non-aggressive tumors, while gene expression data alone could not define an aggressive group of patients. The assessment of CNA may have diagnostic and prognostic value in PC.

Genetic heterogeneity in Finnish hereditary prostate cancer using ordered subset analysis

Prostate cancer (PrCa) is the most common male cancer in developed countries and the second most common cause of cancer death after lung cancer. We recently reported a genome-wide linkage scan in 69 Finnish hereditary PrCa (HPC) families, which replicated the HPC9 locus on 17q21-q22 and identified a locus on 2q37. The aim of this study was to identify and to detect other loci linked to HPC. Here we used ordered subset analysis (OSA), conditioned on nonparametric linkage to these loci to detect other loci linked to HPC in subsets of families, but not the overall sample. We analyzed the families based on their evidence for linkage to chromosome 2, chromosome 17 and a maximum score using the strongest evidence of linkage from either of the two loci. Significant linkage to a 5-cM linkage interval with a peak OSA nonparametric allele-sharing LOD score of 4.876 on Xq26.3-q27 (ΔLOD=3.193, empirical P=0.009) was observed in a subset of 41 families weakly linked to 2q37, overlapping the HPCX1 locus. Two peaks that were novel to the analysis combining linkage evidence from both primary loci were identified; 18q12.1-q12.2 (OSA LOD=2.541, ΔLOD=1.651, P=0.03) and 22q11.1-q11.21 (OSA LOD=2.395, ΔLOD=2.36, P=0.006), which is close to HPC6. Using OSA allows us to find additional loci linked to HPC in subsets of families, and underlines the complex genetic heterogeneity of HPC even in highly aggregated families.

Patient-specific data fusion defines prognostic cancer subtypes

Different data types can offer complementary perspectives on the same biological phenomenon. In cancer studies, for example, data on copy number alterations indicate losses and amplifications of genomic regions in tumours, while transcriptomic data point to the impact of genomic and environmental events on the internal wiring of the cell. Fusing different data provides a more comprehensive model of the cancer cell than that offered by any single type. However, biological signals in different patients exhibit diverse degrees of concordance due to cancer heterogeneity and inherent noise in the measurements. This is a particularly important issue in cancer subtype discovery, where personalised strategies to guide therapy are of vital importance. We present a nonparametric Bayesian model for discovering prognostic cancer subtypes by integrating gene expression and copy number variation data. Our model is constructed from a hierarchy of Dirichlet Processes and addresses three key challenges in data fusion: (i) To separate concordant from discordant signals, (ii) to select informative features, (iii) to estimate the number of disease subtypes. Concordance of signals is assessed individually for each patient, giving us an additional level of insight into the underlying disease structure. We exemplify the power of our model in prostate cancer and breast cancer and show that it outperforms competing methods. In the prostate cancer data, we identify an entirely new subtype with extremely poor survival outcome and show how other analyses fail to detect it. In the breast cancer data, we find subtypes with superior prognostic value by using the concordant results. These discoveries were crucially dependent on our model's ability to distinguish concordant and discordant signals within each patient sample, and would otherwise have been missed. We therefore demonstrate the importance of taking a patient-specific approach, using highly-flexible nonparametric Bayesian methods.

Identification of an aggressive prostate cancer predisposing variant at 11q13

Prostate cancer is the most frequently diagnosed cancer in men; however, the genetic basis of susceptibility remains elusive. The EMSY gene is located in the prostate cancer linked chromosome region at 11q13.5. The aim of this study was to screen EMSY for sequence variants and to evaluate its association with the risk of prostate cancer. We performed a Finnish population-based case-control study with 923 controls, 184 familial prostate cancer cases and 2,301 unselected prostate cancer cases. Variants were screened using sequencing and validated using the TaqMan assay and High Resolution Melting analysis. A total of 27 sequence variants were found, and 17 of them were novel. A rare intronic variant, IVS6-43A>G (minor allele frequency of 0.004), increased the prostate cancer risk in familial cases (odds ratio [OR] = 7.5; 95% confidence interval [CI] = 1.3-45.5; p = 0.02). Further analysis with clinicopathological data revealed that the variant is associated with aggressive unselected cases (prostate specific antigen ≥ 20 μg/L or Gleason grade ≥ 7), based on both case-control (OR = 6.0; 95% CI = 1.3-26.4; p = 0.03) and case-case analyses (OR = 6.5; 95% CI = 1.5-28.4; p = 0.002). In addition, all variant-positive familial cases had aggressive cancer. Our results indicate that the intronic variant IVS6-43A>G increases the familial and unselected prostate cancer risk in a Finnish population and contributes to the aggressive progression of the disease in a high-penetrance manner. The potential role of the variant as a predictive genetic marker for aggressive prostate cancer should be further evaluated.

RNA and DNA microarrays

The development of microarray technology has revolutionized RNA and deoxyribonucleic acid (DNA) research. In contrast with traditional biological assays, microarrays allow the simultaneous measurement of tens of thousands of messenger RNA (mRNA) transcripts for gene expression or of genomic DNA fragments for copy number variation analysis. Over the past decade, genome-wide RNA or DNA microarray analysis has become an essential component of biology and biomedical research. The successful use of microarrays requires attention to unique issues of experimental design and execution. This chapter provides an overview of the methodology and applications of RNA and DNA microarrays in various areas of biological research.

Detection of chromosome copy number alterations in metanephric adenomas by array comparative genomic hybridization

Metanephric adenoma is a rare benign renal tumor typically found in adults. Previous cytogenetic analyses, including karyotyping, fluorescence in situ hybridization (FISH), and comparative genomic hybridization, have yielded conflicting results regarding the somatic genetic aberrations of these tumors. In this study, we investigated the genomic profile of nine cases of metanephric adenoma using array comparative genomic hybridization. Two cases revealed multiple chromosomal gains and losses. Three cases showed sporadic chromosomal imbalances involving no more than three chromosomes. Four cases showed normal chromosome copy numbers. The gain of chromosome 19 was the most common finding (five cases), and FISH using 19p and 19q telomeric probes further confirmed this finding. We did not observe consistent gains of chromosomes 7 and 17, which are common in papillary renal cell carcinoma, neither did we find chromosomal alterations frequently present in Wilms' tumors, including chromosome gains of 1q, 7q, and 12, and losses of 11p and 16q. Our series demonstrates that the genetic profile of metanephric adenoma is fundamentally distinct from those of papillary renal cell carcinoma and Wilms' tumor.

Copy number and gene expression differences between African American and Caucasian American prostate cancer

Background

The goal of our study was to investigate the molecular underpinnings associated with the relatively aggressive clinical behavior of prostate cancer (PCa) in African American (AA) compared to Caucasian American (CA) patients using a genome-wide approach.

Methods

AA and CA patients treated with radical prostatectomy (RP) were frequency matched for age at RP, Gleason grade, and tumor stage. Array-CGH (BAC SpectralChip2600) was used to identify genomic regions with significantly different DNA copy number between the groups. Gene expression profiling of the same set of tumors was also evaluated using Affymetrix HG-U133 Plus 2.0 arrays. Concordance between copy number alteration and gene expression was examined. A second aCGH analysis was performed in a larger validation cohort using an oligo-based platform (Agilent 244K).

Results

BAC-based array identified 27 chromosomal regions with significantly different copy number changes between the AA and CA tumors in the first cohort (Fisher's exact test, P < 0.05). Copy number alterations in these 27 regions were also significantly associated with gene expression changes. aCGH performed in a larger, independent cohort of AA and CA tumors validated 4 of the 27 (15%) most significantly altered regions from the initial analysis (3q26, 5p15-p14, 14q32, and 16p11). Functional annotation of overlapping genes within the 4 validated regions of AA/CA DNA copy number changes revealed significant enrichment of genes related to immune response.

Conclusions

Our data reveal molecular alterations at the level of gene expression and DNA copy number that are specific to African American and Caucasian prostate cancer and may be related to underlying differences in immune response.

Cytogenetic and cDNA microarray expression analysis of MCF10 human breast cancer progression cell lines

We used a combination of spectral karyotyping, array comparative genomic hybridization, and cDNA microarrays to gain insights into the structural and functional changes of the genome in the MCF10 human breast cancer progression model cell lines. Spectral karyotyping data showed several chromosomal aberrations and array comparative genomic hybridization analysis identified numerous genomic gains and losses that might be involved in the progression toward cancer. Analysis of the expression levels of genes located within these genomic regions revealed a lack of correlation between chromosomal gains and losses and corresponding up-regulation or down-regulation for the majority of the approximately 1,000 genes analyzed in this study. We conclude that other mechanisms of gene regulation that are not directly related to chromosomal gains and losses play a major role in breast cancer progression.

Minimum altered regions in early prostate cancer progression identified by high resolution whole genome tiling path BAC array comparative hybridization

BACKGROUND

Carcinoma of the prostate (CaP) is a serious health problem. The altered molecular mechanisms that lead to this disease are poorly understood.

METHODS

Specimens from radical prostatectomies and blood were collected from 18 CaP surgery patients. For CGH studies, 20 CaP-related samples (16 Gleason grade 3, 3 higher grades, 1 BPH sample) and 18 samples of patient-matched normal epithelial cells were obtained by laser-assisted microdissection from frozen sections of the 18 prostatectomy specimens. High resolution SMRT aCGH was used to compare genomic profiles of prostatic samples to patient-matched blood and pooled female DNA. TMPRSS2-ERG fusion transcript analysis was performed by RT-PCR in relation to alterations detected at the TMPRSS2 locus.

RESULTS

Our comprehensive aCGH approach allowed us to define 35 regions of recurrent alterations while excluding germline copy number polymorphisms. Novel regions identified include 2q14.2, containing INHBB, and 17q21.31. The TMPRSS2 locus at 21q22.3 may be a hotspot for rearrangements with 75% of the alterations resulting in the expression of a TMPRSS2-ERG fusion transcript. Differences in fusion expression in different areas in an individual tumor focus and expression in adjacent normal epithelium supported intrafocal heterogeneity and field cancerization, respectively. Both features challenge our efforts to develop more objective markers for diagnosis and prediction of the severity of CaP.

CONCLUSION

The high-density array enabled precise mapping of genomic alterations and consequently definition of minimum altered regions smaller than previously reported thus facilitating identification of those genes that contribute to the cancer transformation process.

Association of chromosome 8q variants with prostate cancer risk in Caucasian and Hispanic men

Genotyping of a 615 kb region within 8q24 with 49 haplotype-tagged single-nucleotide polymorphisms (SNPs) in 2109 samples (797 cases and 1312 controls) of two ethnic/racial groups found SNPs that are significantly associated with the risk for prostate cancer (PCa). The highest significance in Caucasian men was found for rs6983267; the AA genotype reduced the risk for PCa [odds ratio (OR) = 0.48, 95% confidence interval (CI) = 0.35-0.65, P = 2.74 x 10(-6)]. This SNP also had a significant independent effect from other SNPs in the region in this group. In Hispanic men, rs7837328 and rs921146 showed independent effects (OR = 2.55, 95% CI = 1.51-4.31, P = 4.33 x 10(-4), OR = 2.09, 95% CI = 1.40-3.12, P = 3.13 x 10(-4), respectively). Significant synergist effects for increasing numbers of high-risk alleles were found in both ethnicities. Haplotype analysis revealed major haplotypes, containing the non-risk alleles, conferred protection against PCa. We found high linkage disequilibrium between significant SNPs within the region and SNPs within the CUB and Sushi Multiple Domains 1 gene (CSMD1), on the short arm of chromosome 8 in both ethnicities. These data suggest that multiple interacting SNPs within 8q24, as well as different regions on chromosome 8 far beyond this 8q24 candidate region, may confer increased risk of PCa. This is the first report to investigate the involvement of 8q24 variants in the susceptibility for PCa in Hispanic men.

Genomic profiling of prostate cancers from African American men

African American (AA) men have a higher incidence and significantly higher mortality rates from prostate cancer than white men, but the biological basis for these differences are poorly understood. Few studies have been carried out to determine whether there are areas of allelic loss or gain in prostate cancers from AA men that are overrepresented in or specific to this group. To better understand the molecular mechanisms of prostate cancer in AA men, we have analyzed 20 prostate cancers from AA men with high-density single-nucleotide polymorphism arrays to detect genomic copy number alterations. We identified 17 regions showing significant loss and 4 regions with significant gains. Most of these regions had been linked to prostate cancer by previous studies of copy number alterations of predominantly white patients.We identified a novel region of loss at 4p16.3, which has been shown to be lost in breast, colon, and bladder cancers. Comparison of our primary tumors with tumors from white patients from a previously published cohort with similar pathological characteristics showed higher frequency of loss of at numerous loci including 6q13-22, 8p21, 13q13-14, and 16q11-24 and gains of 7p21 and 8q24, all of which had higher frequencies in metastatic lesions in this previously published cohort. Thus, the clinically localized cancers from AA men more closely resembled metastatic cancers from white men. This difference may in part explain the more aggressive clinical behavior of prostate cancer in AA men.

DNA fingerprinting tags novel altered chromosomal regions and identifies the involvement of SOX5 in the progression of prostate cancer

Identification of genomic alterations associated with the progression of prostate cancer may facilitate the better understanding of the development of this highly variable disease. Matched normal, premalignant high-grade prostatic intraepithelial neoplasia and invasive prostate carcinoma cells were procured by laser capture microdissection (LCM) from human radical prostatectomy specimens. From these cells, comparative DNA fingerprints were generated by a modified PCR-based technique called scanning of microdissected archival lesion (SMAL)-PCR. Recurrent polymorphic fingerprint fragments were used in tagging altered chromosomal regions. Altered regions were found at cytobands 1p31.3, 1q44, 2p23.1, 3p26.3, 3q22.3, 4q22.3, 4q35.2, 5q23.2, 8q22.3, 8q24.13, 9q21.3, 9q22.32, 10q11.21, 11p13, 12p12.1, 13q12.1, 16q12.2 and 18q21.31. Candidate genes in the surrounding area that may possibly harbor mutations that change normal prostatic cells to progress into their tumor stages were proposed. Of these fragments, a 420 bp alteration, absent in all 26 normal samples screened, was observed in 2 tumors. This fragment was cloned, sequenced and localized to chromosome 12p12.1. Within this region, candidate gene sex determining region Y-box 5 (SOX5) was proposed. Further studies of SOX5 in cell lines, xenografts and human prostate specimens, at both the RNA and protein levels, found overexpression of the gene in tumors. This overexpression was then subsequently found by fluorescent in situ hybridization to be caused by amplification of the region. In conclusion, our results suggest LCM coupled with SMAL-PCR DNA fingerprinting is a useful method for the screening and identification of chromosomal regions and genes associated with cancer development. Further, overexpression of SOX5 is associated with prostate tumor progression and early development of distant metastasis.

Global gene expression analysis reveals reduced abundance of putative microRNA targets in human prostate tumours

BACKGROUND

Recently, microRNAs (miRNAs) have taken centre stage in the field of human molecular oncology. Several studies have shown that miRNA profiling analyses offer new possibilities in cancer classification, diagnosis and prognosis. However, the function of miRNAs that are dysregulated in tumours remains largely a mystery. Global analysis of miRNA-target gene expression has helped illuminate the role of miRNAs in developmental gene expression programs, but such an approach has not been reported in cancer transcriptomics.

RESULTS

In this study, we globally analysed the expression patterns of miRNA target genes in prostate cancer by using several public microarray datasets. Intriguingly, we found that, in contrast to global mRNA transcript levels, putative miRNA targets showed a reduced abundance in prostate tumours relative to benign prostate tissue. Additionally, the down-regulation of these miRNA targets positively correlated with the number of types of miRNA target-sites in the 3' untranslated regions of these targets. Further investigation revealed that the globally low expression was mainly driven by the targets of 36 specific miRNAs that were reported to be up-regulated in prostate cancer by a miRNA expression profiling study. We also found that the transcript levels of miRNA targets were lower in androgen-independent prostate cancer than in androgen-dependent prostate cancer. Moreover, when the global analysis was extended to four other cancers, significant differences in transcript levels between miRNA targets and total mRNA backgrounds were found.

CONCLUSION

Global gene expression analysis, along with further investigation, suggests that miRNA targets have a significantly reduced transcript abundance in prostate cancer, when compared with the combined pool of all mRNAs. The abnormal expression pattern of miRNA targets in human cancer could be a common feature of the human cancer transcriptome. Our study may help to shed new light on the functional roles of miRNAs in cancer transcriptomics.

Epithelial to mesenchymal transition of a primary prostate cell line with switches of cell adhesion modules but without malignant transformation

BACKGROUND

Epithelial to mesenchymal transition (EMT) has been connected with cancer progression in vivo and the generation of more aggressive cancer cell lines in vitro. EMT has been induced in prostate cancer cell lines, but has previously not been shown in primary prostate cells. The role of EMT in malignant transformation has not been clarified.

METHODOLOGY/PRINCIPAL FINDINGS

In a transformation experiment when selecting for cells with loss of contact inhibition, the immortalized prostate primary epithelial cell line, EP156T, was observed to undergo EMT accompanied by loss of contact inhibition after about 12 weeks in continuous culture. The changed new cells were named EPT1. EMT of EPT1 was characterized by striking morphological changes and increased invasion and migration compared with the original EP156T cells. Gene expression profiling showed extensively decreased epithelial markers and increased mesenchymal markers in EPT1 cells, as well as pronounced switches of gene expression modules involved in cell adhesion and attachment. Transformation assays showed that EPT1 cells were sensitive to serum or growth factor withdrawal. Most importantly, EPT1 cells were not able to grow in an anchorage-independent way in soft agar, which is considered a critical feature of malignant transformation.

CONCLUSIONS/SIGNIFICANCE

This work for the first time established an EMT model from primary prostate cells. The results show that EMT can be activated as a coordinated gene expression program in association with early steps of transformation. The model allows a clearer identification of the molecular mechanisms of EMT and its potential role in malignant transformation.