Dataset Information

The role of the transcription factor SIM2 in prostate cancer.

ABSTRACT:

Background

Recent reports have suggested a possible involvement of Single-minded homolog 2 (SIM2) in human solid cancers, including prostate cancer. However, the exact role of SIM2 in cancer in general, and in prostate cancer in particular, remains largely unknown. This study was designed to elucidate the role of SIM2 in prostate cancer using a shRNA-based approach in the PC3 prostate cancer cell line.

Methods

Lentiviral shRNAs were used to inhibit SIM2 gene and protein levels in PC3 cells. Quantitative RT-PCR and branched DNA were performed to evaluate transcript expression. SIM2 protein expression level was measured by western blot. Profiling of gene expression spanning the whole genome, as well as polar metabolomics of several major metabolic pathways was performed to identify major pathway dysregulations.

Results

SIM2 gene and protein products were significantly downregulated by lenti-shRNA in PC3 cell line. This low expression of SIM2 affected gene expression profile, revealing significant changes in major signaling pathways, networks and functions. In addition, major metabolic pathways were affected.

Conclusion

Taken together, our results suggest an involvement of SIM2 in key traits of prostate tumor cell biology and might underlie a contribution of this transcription factor to prostate cancer onset and progression.

SUBMITTER: Lu B

PROVIDER: S-EPMC3235151 | biostudies-literature | 2011

REPOSITORIES: biostudies-literature

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Publications

The role of the transcription factor SIM2 in prostate cancer.

Lu Bin B Asara John M JM Sanda Martin G MG Arredouani Mohamed S MS

PloS one 20111209 12

<h4>Background</h4>Recent reports have suggested a possible involvement of Single-minded homolog 2 (SIM2) in human solid cancers, including prostate cancer. However, the exact role of SIM2 in cancer in general, and in prostate cancer in particular, remains largely unknown. This study was designed to elucidate the role of SIM2 in prostate cancer using a shRNA-based approach in the PC3 prostate cancer cell line.<h4>Methods</h4>Lentiviral shRNAs were used to inhibit SIM2 gene and protein levels in ...[more]

PMID: 22174909

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Project description:In prostate cancer (PCa), and many other hormone-dependent cancers, there is clear evidence for distorted transcriptional control as disease driver mechanisms. Defining which transcription factor (TF) and coregulators are altered and combine to become oncogenic drivers remains a challenge, in part because of the multitude of TFs and coregulators and the diverse genomic space on which they function. The current study was undertaken to identify which TFs and coregulators are commonly altered in PCa. We generated unique lists of TFs (n = 2662), coactivators (COA; n = 766); corepressors (COR; n = 599); mixed function coregulators (MIXED; n = 511), and to address the challenge of defining how these genes are altered we tested how expression, copy number alterations and mutation status varied across seven prostate cancer (PCa) cohorts (three of localized and four advanced disease). Testing of significant changes was undertaken by bootstrapping approaches and the most significant changes were identified. For one commonly and significantly altered gene were stably knocked-down expression and undertook cell biology experiments and RNA-Seq to identify differentially altered gene networks and their association with PCa progression risks. COAS, CORS, MIXED and TFs all displayed significant down-regulated expression (q.value < 0.1) and correlated with protein expression (r 0.4-0.55). In localized PCa, stringent expression filtering identified commonly altered TFs and coregulator genes, including well-established (e.g. ERG) and underexplored (e.g. PPARGC1A, encodes PGC1α). Reduced PPARGC1A expression significantly associated with worse disease-free survival in two cohorts of localized PCa. Stable PGC1α knockdown in LNCaP cells increased growth rates and invasiveness and RNA-Seq revealed a profound basal impact on gene expression (~ 2300 genes; FDR < 0.05, logFC > 1.5), but only modestly impacted PPARγ responses. GSEA analyses of the PGC1α transcriptome revealed that it significantly altered the AR-dependent transcriptome, and was enriched for epigenetic modifiers. PGC1α-dependent genes were overlapped with PGC1α-ChIP-Seq genes and significantly associated in TCGA with higher grade tumors and worse disease-free survival. These methods and data demonstrate an approach to identify cancer-driver coregulators in cancer, and that PGC1α expression is clinically significant yet underexplored coregulator in aggressive early stage PCa.

Project description:BACKGROUND: Prostate cancer is one of the leading causes of cancer death in men. Androgen ablation, the most commonly-used therapy for progressive prostate cancer, is ineffective once the cancer cells become androgen-independent. The regulatory mechanisms that cause this transition (from androgen-dependent to androgen-independent) remain unknown. In this study, based on the microarray data comparing global gene expression patterns in the prostate tissue between androgen-dependent and -independent prostate cancer patients, we identify a set of transcription factors and microRNAs that potentially cause such difference, using a model-based computational approach. RESULTS: From 335 position weight matrices in the TRANSFAC database and 564 microRNAs in the microRNA registry, our model identify 5 transcription factors and 7 microRNAs to be potentially responsible for the level of androgen dependency. Of these transcription factors and microRNAs, the estimated function of all the 5 transcription factors are predicted to be inhibiting transcription in androgen-independent samples comparing with the dependent ones. Six out of 7 microRNAs, however, demonstrated stimulatory effects. We also find that the expression levels of three predicted transcription factors, including AP-1, STAT3 (signal transducers and activators of transcription 3), and DBP (albumin D-box) are significantly different between androgen-dependent and -independent patients. In addition, microRNA microarray data from other studies confirm that several predicted microRNAs, including miR-21, miR-135a, and miR-135b, demonstrate differential expression in prostate cancer cells, comparing with normal tissues. CONCLUSION: We present a model-based computational approach to identify transcription factors and microRNAs influencing the progression of androgen-dependent prostate cancer to androgen-independent prostate cancer. This result suggests that the capability of transcription factors to initiate transcription and microRNAs to facilitate mRNA degradation are both decreased in androgen-independent prostate cancer. The proposed model-based approach indicates that considering combinatorial effects of transcription factors and microRNAs in a unified model provides additional transcriptional and post-transcriptional regulatory mechanisms on global gene expression in the prostate cancer with different hormone-dependency.

Project description:The incidence and mortality rates of prostate cancer (PCa) are increasing, and PCa is almost the second?leading cause of cancer?associated mortality in men. During tumor progression, epithelial cells decrease the number of adhesion molecules, change their polarity and position, rearrange their cytoskeleton and increase their migratory and invasive capacities. These changes are known under the concept of epithelial?mesenchymal transition (EMT). EMT is characterized by an upregulation of certain transcription factors, including SNAIL1, which represses genes that are characteristic of an epithelial phenotype, including E?cadherin, and indirectly increase the expression levels of genes, which are associated with the mesenchymal phenotype. It has been suggested that the transcription factor, SNAIL1, decreases the proliferation and increases the migratory and invasive capacities of PCa cell lines. The present study was performed using LNCaP and PC3 cell lines, in which the expression levels of SNAIL1 were increased or silenced through the use of lentiviral vectors. The expression levels of EMT markers were quantified using reverse transcription?quantitative polymerase chain reaction and western blot analysis. In addition, cell survival was analyzed using an MTS assay; cell proliferation was examined using an antibody targeting Ki?67; migration on plates with 8 µm pores to allow the passage of cells; and invasiveness was analyzed using a membrane chamber covered in dried basement membrane matrix solution. The levels of apoptosis were determined using a Caspase 3/7 assay containing a substrate modified by caspases 3 and 7. The results demonstrated that the overexpression and silencing of SNAIL1 decreased cell proliferation and survival. However, the overexpression of SNAIL1 decreased apoptosis, compared with cells with the SNAIL1?silenced cells, in which cell apoptosis increased. The migration and invasive capacities increased in the cells overexpressing SNAIL1, and decreased when SNAIL1 was silenced. In conclusion, PCa cells overexpressing SNAIL1 exhibited characteristics of an EMT phenotype, whereas the silencing of the SNAIL1 transcriptional repressor promoted an epithelial?like phenotype, with decreased migration and invasion, characteristic of mesenchymal cells.

Dataset Information

The role of the transcription factor SIM2 in prostate cancer.

Background

Methods

Results

Conclusion

Publications

The role of the transcription factor SIM2 in prostate cancer.

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