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Analysis of the molecular networks in androgen dependent and independent prostate cancer revealed fragile and robust subsystems.

ABSTRACT: Androgen ablation therapy is currently the primary treatment for metastatic prostate cancer. Unfortunately, in nearly all cases, androgen ablation fails to permanently arrest cancer progression. As androgens like testosterone are withdrawn, prostate cancer cells lose their androgen sensitivity and begin to proliferate without hormone growth factors. In this study, we constructed and analyzed a mathematical model of the integration between hormone growth factor signaling, androgen receptor activation, and the expression of cyclin D and Prostate-Specific Antigen in human LNCaP prostate adenocarcinoma cells. The objective of the study was to investigate which signaling systems were important in the loss of androgen dependence. The model was formulated as a set of ordinary differential equations which described 212 species and 384 interactions, including both the mRNA and protein levels for key species. An ensemble approach was chosen to constrain model parameters and to estimate the impact of parametric uncertainty on model predictions. Model parameters were identified using 14 steady-state and dynamic LNCaP data sets taken from literature sources. Alterations in the rate of Prostatic Acid Phosphatase expression was sufficient to capture varying levels of androgen dependence. Analysis of the model provided insight into the importance of network components as a function of androgen dependence. The importance of androgen receptor availability and the MAPK/Akt signaling axes was independent of androgen status. Interestingly, androgen receptor availability was important even in androgen-independent LNCaP cells. Translation became progressively more important in androgen-independent LNCaP cells. Further analysis suggested a positive synergy between the MAPK and Akt signaling axes and the translation of key proliferative markers like cyclin D in androgen-independent cells. Taken together, the results support the targeting of both the Akt and MAPK pathways. Moreover, the analysis suggested that direct targeting of the translational machinery, specifically eIF4E, could be efficacious in androgen-independent prostate cancers.

SUBMITTER: Tasseff R

PROVIDER: S-EPMC2812491 | biostudies-literature | 2010

REPOSITORIES: biostudies-literature

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Analysis of the molecular networks in androgen dependent and independent prostate cancer revealed fragile and robust subsystems.

Tasseff Ryan R Nayak Satyaprakash S Salim Saniya S Kaushik Poorvi P Rizvi Noreen N Varner Jeffrey D JD

PloS one 20100128 1

Androgen ablation therapy is currently the primary treatment for metastatic prostate cancer. Unfortunately, in nearly all cases, androgen ablation fails to permanently arrest cancer progression. As androgens like testosterone are withdrawn, prostate cancer cells lose their androgen sensitivity and begin to proliferate without hormone growth factors. In this study, we constructed and analyzed a mathematical model of the integration between hormone growth factor signaling, androgen receptor activa ...[more]

PMID: 20126616

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Project description:Prostate cancer (PCa) is a heterogeneous disease and ranked as the second leading cause of cancer-related deaths in males worldwide. The global burden of PCa keeps rising regardless of the emerging cutting-edge technologies for treatment and drug designation. There are a number of treatment options which are effectively treating localised and androgen-dependent PCa (ADPC) through hormonal and surgery treatments. However, over time, these cancerous cells progress to androgen-independent PCa (AIPC) which continuously grow despite hormone depletion. At this particular stage, androgen depletion therapy (ADT) is no longer effective as these cancerous cells are rendered hormone-insensitive and capable of growing in the absence of androgen. AIPC is a lethal type of disease which leads to poor prognosis and is a major contributor to PCa death rates. A natural product-derived compound, curcumin has been identified as a pleiotropic compound which capable of influencing and modulating a diverse range of molecular targets and signalling pathways in order to exhibit its medicinal properties. Due to such multi-targeted behaviour, its benefits are paramount in combating a wide range of diseases including inflammation and cancer disease. Curcumin exhibits anti-cancer properties by suppressing cancer cells growth and survival, inflammation, invasion, cell proliferation as well as possesses the ability to induce apoptosis in malignant cells. In this review, we investigate the mechanism of curcumin by modulating multiple signalling pathways such as androgen receptor (AR) signalling, activating protein-1 (AP-1), phosphatidylinositol 3-kinases/the serine/threonine kinase (PI3K/Akt/mTOR), wingless (Wnt)/ß-catenin signalling, and molecular targets including nuclear factor kappa-B (NF-κB), B-cell lymphoma 2 (Bcl-2) and cyclin D1 which are implicated in the development and progression of both types of PCa, ADPC and AIPC. In addition, the role of microRNAs and clinical trials on the anti-cancer effects of curcumin in PCa patients were also reviewed.

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.

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Analysis of the molecular networks in androgen dependent and independent prostate cancer revealed fragile and robust subsystems.

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Analysis of the molecular networks in androgen dependent and independent prostate cancer revealed fragile and robust subsystems.

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