Cell cycle, oncogenic and tumor suppressor pathways regulate numerous long and macro non-protein-coding RNAs.

BACKGROUND: The genome is pervasively transcribed but most transcripts do not code for proteins, constituting non-protein-coding RNAs. Despite increasing numbers of functional reports of individual long non-coding RNAs (lncRNAs), assessing the extent of functionality among the non-coding transcriptional output of mammalian cells remains intricate. In the protein-coding world, transcripts differentially expressed in the context of processes essential for the survival of multicellular organisms have been instrumental in the discovery of functionally relevant proteins and their deregulation is frequently associated with diseases. We therefore systematically identified lncRNAs expressed differentially in response to oncologically relevant processes and cell-cycle, p53 and STAT3 pathways, using tiling arrays. RESULTS: We found that up to 80% of the pathway-triggered transcriptional responses are non-coding. Among these we identified very large macroRNAs with pathway-specific expression patterns and demonstrated that these are likely continuous transcripts. MacroRNAs contain elements conserved in mammals and sauropsids, which in part exhibit conserved RNA secondary structure. Comparing evolutionary rates of a macroRNA to adjacent protein-coding genes suggests a local action of the transcript. Finally, in different grades of astrocytoma, a tumor disease unrelated to the initially used cell lines, macroRNAs are differentially expressed. CONCLUSIONS: It has been shown previously that the majority of expressed non-ribosomal transcripts are non-coding. We now conclude that differential expression triggered by signaling pathways gives rise to a similar abundance of non-coding content. It is thus unlikely that the prevalence of non-coding transcripts in the cell is a trivial consequence of leaky or random transcription events.

Analysis of the STAT3 interactome using in-situ biotinylation and SILAC.

Signal transducer and activator of transcription 3 (STAT3) is activated by a variety of cytokines and growth factors. To generate a comprehensive data set of proteins interacting specifically with STAT3, we applied stable isotope labeling with amino acids in cell culture (SILAC). For high-affinity pull-down using streptavidin, we fused STAT3 with a short peptide tag allowing biotinylation in situ (bio-tag), which did not affect STAT3 functions. By this approach, 3642 coprecipitated proteins were detected in human embryonic kidney-293 cells. Filtering using statistical and functional criteria finally extracted 136 proteins as putative interaction partners of STAT3. Both, a physical interaction network analysis and the enrichment of known and predicted interaction partners suggested that our filtering criteria successfully enriched true STAT3 interactors. Our approach identified numerous novel interactors, including ones previously predicted to associate with STAT3. By reciprocal coprecipitation, we were able to verify the physical association between STAT3 and selected interactors, including the novel interaction with TOX4, a member of the TOX high mobility group box family. Applying the same method, we next investigated the activation-dependency of the STAT3 interactome. Again, we identified both known and novel interactions. Thus, our approach allows to study protein-protein interaction effectively and comprehensively. BIOLOGICAL SIGNIFICANCE: The location, activity, function, degradation, and synthesis of proteins are significantly regulated by interactions of proteins with other proteins, biopolymers and small molecules. Thus, the comprehensive characterization of interactions of proteins in a given proteome is the next milestone on the path to understanding the biochemistry of the cell. In order to generate a comprehensive interactome dataset of proteins specifically interacting with a selected bait protein, we fused our bait protein STAT3 with a short peptide tag allowing biotinylation in situ (bio-tag). This bio-tag allows an affinity pull-down using streptavidin but affected neither the activation of STAT3 by tyrosine phosphorylation nor its transactivating potential. We combined SILAC for accurate relative protein quantification, subcellular fractionation to increase the coverage of interacting proteins, high-affinity pull-down and a stringent filtering method to successfully analyze the interactome of STAT3. With our approach we confirmed several already known and identified numerous novel STAT3 interactors. The approach applied provides a rapid and effective method, which is broadly applicable for studying protein-protein interactions and their dependency on post-translational modifications.

Co-activator SRC-1 is dispensable for transcriptional control by STAT3.

SRC (steroid receptor co-activator)-1 has been reported to interact with and to be an essential co-activator for several members of the STAT (signal transducer and activator of transcription) family, including STAT3, the major signal transducer of IL (interleukin)-6. We addressed the question of whether SRC-1 is crucial for IL-6- and STAT3-mediated physiological responses such as myeloma cell survival and acute-phase protein induction. In fact, silencing of SRC-1 by RNA interference rapidly induced apoptosis in IL-6-dependent INA-6 human myeloma cells, comparable with what was observed upon silencing of STAT3. Using chromatin immunoprecipitation at STAT3 target regions of various genes, however, we observed constitutive binding of SRC-1 that decreased when INA-6 cells were treated with IL-6. The same held true for STAT3 target genes analysed in HepG2 human hepatocellular carcinoma cells. SRC-1-knockdown studies demonstrated that STAT3-controlled promoters require neither SRC-1 nor the other p160 family members SRC-2 or SRC-3 in HepG2 cells. Furthermore, microarray expression profiling demonstrated that the responsiveness of IL-6 target genes is not affected by SRC-1 silencing. In contrast, co-activators of the CBP [CREB (cAMP-response element-binding protein)-binding protein]/p300 family proved functionally important for the transactivation potential of STAT3 and bound inducibly to STAT3 target regions. This recruitment did not depend on the presence of SRC-1. Altogether, this suggests that functional impairment of STAT3 is not involved in the induction of myeloma cell apoptosis by SRC-1 silencing. We therefore conclude that STAT3 transactivates its target genes by the recruitment of CBP/p300 co-activators and that this process generally does not require the contribution of SRC-1.

Interleukin-6 dependent survival of multiple myeloma cells involves the Stat3-mediated induction of microRNA-21 through a highly conserved enhancer.

Signal transducer and activator of transcription 3 (Stat3) is implicated in the pathogenesis of many malignancies and essential for IL-6-dependent survival and growth of multiple myeloma cells. Here, we demonstrate that the gene encoding oncogenic microRNA-21 (miR-21) is controlled by an upstream enhancer containing 2 Stat3 binding sites strictly conserved since the first observed evolutionary appearance of miR-21 and Stat3. MiR-21 induction by IL-6 was strictly Stat3 dependent. Ectopically raising miR-21 expression in myeloma cells in the absence of IL-6 significantly reduced their apoptosis levels. These data provide strong evidence that miR-21 induction contributes to the oncogenic potential of Stat3.

Interleukin-6-dependent gene expression profiles in multiple myeloma INA-6 cells reveal a Bcl-2 family-independent survival pathway closely associated with Stat3 activation.

Interleukin 6 (IL-6) is a growth and survival factor for multiple myeloma cells. As we report here, the IL-6-dependent human myeloma cell line INA-6 responds with a remarkably rapid and complete apoptosis to cytokine withdrawal. Among the antiapoptotic members of the B-cell lymphoma-2 (Bcl-2) family of apoptosis regulators, only myeloid cell factor-1 (Mcl-1) was slightly induced by IL-6. Overexpression studies demonstrated, however, that IL-6 does not exert its survival effect primarily through this pathway. The IL-6 signal transduction pathways required for survival and the target genes controlled by them were analyzed by using mutated receptor chimeras. The activation of signal transducer and activator of transcription 3 (Stat3) turned out to be obligatory for the survival of INA-6 cells. The same held true for survival and growth of XG-1 myeloma cells. Gene expression profiling of INA-6 cells by using oligonucleotide microarrays revealed many novel IL-6 target genes, among them several genes coding for transcriptional regulators involved in B-lymphocyte differentiation as well as for growth factors and receptors potentially implicated in autocrine or paracrine growth control. Regulation of most IL-6 target genes required the activation of Stat3, underscoring its central role for IL-6 signal transduction. Taken together, our data provide evidence for the existence of an as yet unknown Stat3-dependent survival pathway in myeloma cells.

Analysis of Stat3 (signal transducer and activator of transcription 3) dimerization by fluorescence resonance energy transfer in living cells.

Signal transducer and activator of transcription 3 (Stat3) dimerization is commonly thought to be triggered by its tyrosine phosphorylation in response to interleukin-6 (IL-6) or other cytokines. Accumulating evidence from in vitro studies, however, suggests that cytoplasmic Stat3 may be associated with high-molecular-mass protein complexes and/or dimerize prior to its activation. To directly study Stat3 dimerization and subcellular localization upon cytokine stimulation, we used live-cell fluorescence spectroscopy and imaging microscopy combined with fluorescence resonance energy transfer (FRET). Stat3 fusion proteins with spectral variants of green fluorescent protein (GFP), cyan fluorescent protein (CFP) and yellow fluorescent protein (YFP) were constructed and expressed in human hepatoma cells (HepG2) and human embryonic kidney cells (HEK-293). Like wild-type Stat3, the fusion proteins redistributed from a preferentially cytoplasmic to nuclear localization upon IL-6 stimulation and supported IL-6-dependent target gene expression. FRET studies in cells co-expressing Stat3-CFP and Stat3-YFP demonstrated that Stat3 dimers exist in the absence of tyrosine phosphorylation. IL-6 induced a 2-fold increase of this basal FRET signal, indicating that tyrosine phosphorylation either increases the dimer/monomer ratio of Stat3 or induces a conformational change of the dimer yielding a higher FRET efficiency. Studies using a mutated Stat3 with a non-functional src-homology 2 (SH2) domain showed that the SH2 domain is essential for dimer formation of phosphorylated as well as non-phosphorylated Stat3. Furthermore, our data show that visualization of normalized FRET signals allow insights into the spatiotemporal dynamics of Stat3 signal transduction.