The Multifaceted Roles of STAT3 Signaling in the Progression of Prostate Cancer

Role of STAT3 pathway in genitourinary tumors

The STAT3 is often dysregulated in genitourinary tumors. In prostate cancer, STAT3 activation correlates with Gleason score and pathological stage and modulates cancer stem cells and epithelial-mesenchymal transition. In addition, STAT3 promotes the progression from carcinoma in situ to invasive bladder cancer and modulates renal cell carcinoma angiogenesis by increasing the expression of HIF1α and VEGF. STAT3 is also involved in the response to tyrosine kinase inhibitors sunitinib and axitinib, in patients with metastatic renal cell carcinoma, and to second-generation androgen receptor inhibitor enzalutamide in patients with advanced prostate cancer. In this review, we describe the role of STAT3 in genitourinary tumors, thus describing its potential for future therapeutic strategies.

Metformin represses androgen-dependent and androgen-independent prostate cancers by targeting androgen receptor

BACKGROUND

Metformin has been reported to inhibit the growth of different types of cancers, including prostate cancer. We were interested to understand if the effect of metformin on prostate cancer is AR-dependent and, if so, whether metformin could act synergistically with the other anti-AR agents to serve as a therapeutic regimen with high efficacy and low toxicity.

METHODS

Cell viabilities and apoptosis were determined by MTT assay and annexin V-FITC staining, respectively, when the two human prostate cancer cell lines, the androgen-dependent LNCaP and the androgen-independent 22RV1 were treated with metformin alone or in combination with bicalutamide. Quantitative RT-PCR and western blotting assays were conducted to examine metformin effects on AR mRNA and protein levels, respectively. Chromatin immunoprecipitation (ChIP) assays were conducted to confirm the recruitment of AR to the ARE(s) located on the promoter region of the AR target gene PSA.

RESULTS

Metformin treatment reduced cell viability and enhanced apoptosis for both cell lines and additive effects were observed when LNCaP cells were treated with combined metformin and bicalutamide. Metformin down-regulated full-length AR protein in LNCaP cells. Both full-length and the truncated AR (AR-v7) were down-regulated by metformin in CWR22Rv1 cells. In both LNCaP and CWR22Rv1 cells, metformin repressed AR signaling pathway not by affecting AR protein degradation/stability, but rather through down-regulating the levels of AR mRNAs.

CONCLUSIONS

Metformin represses prostate cancer cell viability and enhances apoptosis by targeting the AR signaling pathway. Combinations of metformin and other anti-AR agents pose a potentially promising therapeutic approach for treatment of prostate cancers, especially the castrate-resistant prostate cancer, with high efficacy and low toxicity.

The STAT3 Inhibitor Galiellalactone Effectively Reduces Tumor Growth and Metastatic Spread in an Orthotopic Xenograft Mouse Model of Prostate Cancer

Signal transducer and activator of transcription 3 (STAT3) is known to be involved in the progression of prostate cancer (PCa) and is a key factor in drug resistance and tumor immunoescape. As a result, it represents a promising target for PCa therapy. We studied the effects of the STAT3 inhibitor galiellalactone (GL) on tumor growth and metastatic spread in vitro and in vivo. The effect of GL on cell viability, apoptosis, and invasion was studied in vitro using androgen-independent DU145 and DU145-Luc cell lines. For in vivo studies, mice were injected orthotopically with DU145-Luc cells and treated with daily intraperitoneal injections of GL for 6 wk. GL significantly reduced the growth of the primary tumor and the metastatic spread of PCa cells to regional and distal lymph nodes in vivo. Treatment with GL also resulted in decreased cell proliferation and increased apoptosis compared with controls. In vitro, GL reduces the viability and invasive abilities of DU145-Luc cells and induces apoptosis. Our results showed that tumor growth and early metastatic dissemination of PCa can be significantly reduced by GL, indicating its potential use as a therapeutic compound in advanced metastatic PCa.

PATIENT SUMMARY

In this study, we tested the STAT3 inhibitor galiellalactone (GL) in an animal model of PCa. We found that mice treated with GL had smaller primary tumors and decreased lymph node metastases compared with mice treated with vehicle. GL has potential for treating advanced metastatic PCa.

Investigational therapies targeting signal transducer and activator of transcription 3 for the treatment of cancer

INTRODUCTION

Signal transducer and activator of transcription 3 (STAT3) mediates the expression of a variety of genes in response to cell stimuli and thus plays a key role in several cellular processes such as cell growth and apoptosis. Deregulation of the STAT3 activity has been shown in many malignancies, including breast, head and neck, prostate, pancreas, ovarian and brain cancers and melanoma. Thus, STAT3 may represent an ideal target for cancer therapy.

AREAS COVERED

The authors review recent data on the role of STAT3 in tumor initiation and progression, as well as the ongoing clinical trials in cancer patients. The content includes information derived from trial databases, regulatory authorities and scientific literature.

EXPERT OPINION

Targeting STAT3 activation leads to the inhibition of tumor growth and metastasis both in vitro and in vivo without affecting normal cells; this suggests that STAT3 could be a valid molecular target for cancer therapy. Extensive clinical research is trying to find anti-STAT3 agents with high single-agent activity. The identification and development of novel drugs that can target deregulated STAT3 activation effectively is both a scientific and clinical challenge that needs to be addressed in the near future.

Beyond immune checkpoint blockade: new approaches to targeting host-tumor interactions in prostate cancer: report from the 2014 Coffey-Holden prostate cancer academy meeting

INTRODUCTION

The 2014 Coffey-Holden Prostate Cancer Academy Meeting, held in La Jolla, CA from June 26 to 29, 2014, was themed: "Beyond Immune Checkpoint Blockade: New Approaches to Targeting Host-Tumor Interactions in Prostate Cancer."

METHODS

Sponsored by the Prostate Cancer Foundation (PCF), this annual, invitation-only meeting is structured as an action-tank, and brought together 72 investigators with diverse academic backgrounds to discuss the most relevant topics in the fields of prostate cancer immunotherapy and the tumor microenvironment.

RESULTS

The questions addressed at the meeting included: mechanisms underlying the successes and failures of prostate cancer immunotherapies, how to trigger an effective immune response against prostate cancer, the tumor microenvironment and its role in therapy resistance and tumor metastasis, clinically relevant prostate cancer mouse models, how host-tumor interactions affect current therapies and tumor phenotypes, application of principles of precision medicine to prostate cancer immunotherapy, optimizing immunotherapy clinical trial design, and complex multi-system interactions that affect prostate cancer and immune responses including the effects of obesity and the potential role of the host microbiome.

DISCUSSION

This article highlights the most significant recent progress and unmet needs that were discussed at the meeting toward the goal of speeding the development of optimal immunotherapies for the treatment of prostate cancer.

Dual high expression of STAT3 and cyclinD1 is associated with poor prognosis after curative resection of esophageal squamous cell carcinoma

BACKGROUND

Signal transducer of activator of transcription 3 (STAT3) and cyclinD1 are overexpressed in various human cancers, and their overexpression positively correlates to tumor progression and poor prognosis. However, the clinical significance of dual high expression of these two proteins in esophageal squamous cell carcinoma (ESCC) has yet to be determined.

METHODS

The expression of STAT3 and cyclinD1 was analyzed in tissue microarrays containing tumor and adjacent tissue samples from 82 patients who had undergone curative resection for histologically proven ESCC. Kaplan-Meier plots and Cox proportional hazards regression model were used to analyze the prognostic value of STAT3 and cyclinD1 expression.

RESULTS

We discovered that expressions of STAT3 and cyclinD1 in cancer tissues were significantly higher than that in adjacent tissues. High expression of STAT3 and cyclinD1 was associated with malignant behaviors. Moreover, the expression of STAT3 was positively associated with the expression of cyclinD1. High STAT3 or cyclinD1 expression alone was associated with lower overall survival (OS) rates. Furthermore, dual high expression of STAT3 and cyclinD1 expression predict even worse survival outcome in both univariate and multivariate analysis.

CONCLUSION

STAT3 and cyclinD1 correlate with more aggressive tumor behavior in ESCC. When STAT3 and cyclinD1 are considered together, they serve as effective prognostic markers in patients with surgically resected ESCC.

A behavioral study of healthy and cancer genes by modeling electrical network

In recent years, gene network modeling is gaining popularity in genomics to monitor the activity profile of genes. More specifically, the objective of the network modeling concept is to study the genetic behavior associated with disease. Previous researchers have designed network model at nucleotide level which produces more complexity for designing circuits mostly in case of gene expression studies. Whereas the authors have designed the present network model, based on amino acid level which is simpler as well as more appropriate for prediction of the genetic abnormality. In the present concept, SISO continuous and discrete system models of genes are realized using Foster network. The model is designed based on hydropathy index value of amino acids to study the biological system behavior. The time and phase response in continuous (s) domain and pole-zero distribution in discrete (z) domain are used as measurement metric in the present study. The simulated responses of the system show genetic instability for cancer genes which truly reflects the medical reports. The proposed modeling concept can be used, to accurately identify or separate out the diseased genes from healthy genes.