Mechanisms of disease: Insights into the emerging role of signal transducers and activators of transcription in cancer.
ABSTRACT Members of the signal transducers and activators of transcription (STAT) pathway, which were originally identified as key components linking cytokine signals to transcriptional events in cells, have recently been demonstrated to have a major role in cancer. They are cytoplasmic proteins that form functional dimers with each other when activated by tyrosine phosphorylation. Activated STAT proteins translocate to the nucleus to regulate expression of genes by binding to specific elements within gene promoters. Constitutive activation of the STAT family members Stat3 and Stat5, and/or loss of Stat1 signaling, is found in a large group of diverse tumors. Increasing evidence demonstrates that STAT proteins can regulate many pathways important in oncogenesis including cell-cycle progression, apoptosis, tumor angiogenesis, tumor-cell invasion and metastasis, and tumor-cell evasion of the immune system. Based on these findings, a growing effort is underway to target STAT proteins directly and indirectly for cancer therapy. This review will highlight STAT signaling pathways, STAT target genes involved in cancer, evidence for STAT activation in human cancers, and therapeutic strategies to target STAT molecules for anticancer therapy.
Article: High nuclear expression of STAT3 is associated with unfavorable prognosis in diffuse large B-cell lymphoma.[show abstract] [hide abstract]
ABSTRACT: The purpose of the study was to investigate the expression and prognostic value of STAT3 in diffuse large B-cell lymphoma (DLBCL). Seventy-four DLBCL patients from 2001 to 2007 were reviewed in the study. The STAT3 expression in their tumor tissues was examined using the immunohistochemistry (IHC) method, and evaluated for its association with clinicopathological parameters. Strong nuclear staining of STAT3 and phosphorylated-STAT3tyr705 (P-STAT3) were observed in 19 cases (25.7%) and 24 cases (32.4%), respectively, and the expression levels were highly consistent between them (P = 0.001). The high nuclear expression of STAT3 was more frequent in the non-germinal center B cell-like (non-GCB) DLBCL than that in the GCB subtype, but not reaching significance (P < 0.061). The high nuclear expression of STAT3 was found to be correlated with poor overall survival (OS) (P = 0.005). Multivariate Cox regression analysis showed that the STAT3 expression was an independent prognostic factor for DLBCL patients regardless of CHOP or R-CHOP regimen used as the first-line therapy. STAT3 is more frequently expressed in non-GCB DLBCL than that in GCB subtype, and its strong nuclear expression is correlated with poor OS in DLBCL.Journal of Hematology & Oncology 08/2011; 4(1):31. · 3.99 Impact Factor
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ABSTRACT: Signal transducer and activator of transcription 3 (STAT3) plays a central role in the activation of multiple oncogenic pathways. Splicing variant STAT3β uses an alternative acceptor site within exon 23 that leads to a truncated isoform lacking the C-terminal transactivation domain. Depending on the context, STAT3β can act as a dominant-negative regulator of transcription and promote apoptosis. We show that modified antisense oligonucleotides targeted to a splicing enhancer that regulates STAT3 exon 23 alternative splicing specifically promote a shift of expression from STAT3α to STAT3β. Induction of endogenous STAT3β leads to apoptosis and cell-cycle arrest in cell lines with persistent STAT3 tyrosine phosphorylation compared with total STAT3 knockdown obtained by forced splicing-dependent nonsense-mediated decay (FSD-NMD). Comparison of the molecular effects of splicing redirection to STAT3 knockdown reveals a unique STAT3β signature, with a down-regulation of specific targets (including lens epithelium-derived growth factor, p300/CBP-associated factor, CyclinC, peroxisomal biogenesis factor 1, and STAT1β) distinct from canonical STAT3 targets typically associated with total STAT3 knockdown. Furthermore, similar in vivo redirection of STAT3 alternative splicing leads to tumor regression in a xenograft cancer model, demonstrating how pharmacological manipulation of a single key splicing event can manifest powerful antitumorigenic properties and validating endogenous splicing reprogramming as an effective cancer therapeutic approach.Proceedings of the National Academy of Sciences 10/2011; 108(43):17779-84. · 9.68 Impact Factor
Article: A race between tumor immunoescape and genome maintenance selects for optimum levels of (epi)genetic instability.[show abstract] [hide abstract]
ABSTRACT: The human immune system functions to provide continuous body-wide surveillance to detect and eliminate foreign agents such as bacteria and viruses as well as the body's own cells that undergo malignant transformation. To counteract this surveillance, tumor cells evolve mechanisms to evade elimination by the immune system; this tumor immunoescape leads to continuous tumor expansion, albeit potentially with a different composition of the tumor cell population ("immunoediting"). Tumor immunoescape and immunoediting are products of an evolutionary process and are hence driven by mutation and selection. Higher mutation rates allow cells to more rapidly acquire new phenotypes that help evade the immune system, but also harbor the risk of an inability to maintain essential genome structure and functions, thereby leading to an error catastrophe. In this paper, we designed a novel mathematical framework, based upon the quasispecies model, to study the effects of tumor immunoediting and the evolution of (epi)genetic instability on the abundance of tumor and immune system cells. We found that there exists an optimum number of tumor variants and an optimum magnitude of mutation rates that maximize tumor progression despite an active immune response. Our findings provide insights into the dynamics of tumorigenesis during immune system attacks and help guide the choice of treatment strategies that best inhibit diverse tumor cell populations.PLoS Computational Biology 02/2012; 8(2):e1002370. · 5.22 Impact Factor