Syntaphilin Ubiquitination Regulates Mitochondrial Dynamics and Tumor Cell Movements.

Syntaphilin (SNPH) inhibits the movement of mitochondria in tumor cells, preventing their accumulation at the cortical cytoskeleton and limiting the bioenergetics of cell motility and invasion. Although this may suppress metastasis, the regulation of the SNPH pathway is not well understood. Using a global proteomics screen, we show that SNPH associates with multiple regulators of ubiquitin-dependent responses and is ubiquitinated by the E3 ligase CHIP (or STUB1) on Lys111 and Lys153 in the microtubule-binding domain. SNPH ubiquitination did not result in protein degradation, but instead anchored SNPH on tubulin to inhibit mitochondrial motility and cycles of organelle fusion and fission, that is dynamics. Expression of ubiquitination-defective SNPH mutant Lys111!Arg or Lys153!Arg increased the speed and distance traveled by mitochondria, repositioned mitochondria to the cortical cytoskeleton, and supported heightened tumor chemotaxis, invasion, and metastasis in vivo. Interference with SNPH ubiquitination activated mitochondrial dynamics, resulting in increased recruitment of the fission regulator dynamin-related protein-1 (Drp1) to mitochondria and Drp1-dependent tumor cell motility. These data uncover nondegradative ubiquitination of SNPH as a key regulator of mitochondrial trafficking and tumor cell motility and invasion. In this way, SNPH may function as a unique, ubiquitination-regulated suppressor of metastasis

A neuronal network of mitochondrial dynamics regulates metastasis.

The role of mitochondria in cancer is controversial. Using a genome-wide shRNA screen, we now show that tumours reprogram a network of mitochondrial dynamics operative in neurons, including syntaphilin (SNPH), kinesin KIF5B and GTPase Miro1/2 to localize mitochondria to the cortical cytoskeleton and power the membrane machinery of cell movements. When expressed in tumours, SNPH inhibits the speed and distance travelled by individual mitochondria, suppresses organelle dynamics, and blocks chemotaxis and metastasis, in vivo. Tumour progression in humans is associated with downregulation or loss of SNPH, which correlates with shortened patient survival, increased mitochondrial trafficking to the cortical cytoskeleton, greater membrane dynamics and heightened cell invasion. Therefore, a SNPH network regulates metastatic competence and may provide a therapeutic target in cancer

Non-Small Cell Lung Carcinoma Cell Motility, Rac Activation and Metastatic Dissemination Are Mediated by Protein Kinase C Epsilon

Background: Protein kinase C (PKC) e, a key signaling transducer implicated in mitogenesis, survival, and cancer progression, is overexpressed in human primary non-small cell lung cancer (NSCLC). The role of PKCe in lung cancer metastasis has not yet been established. Principal Findings: Here we show that RNAi-mediated knockdown of PKCe in H358, H1299, H322, and A549 NSCLC impairs activation of the small GTPase Rac1 in response to phorbol 12-myristate 13-acetate (PMA), serum, or epidermal growth factor (EGF). PKCe depletion markedly impaired the ability of NSCLC cells to form membrane ruffles and migrate. Similar results were observed by pharmacological inhibition of PKCe with eV1-2, a specific PKCe inhibitor. PKCe was also required for invasiveness of NSCLC cells and modulated the secretion of extracellular matrix proteases and protease inhibitors. Finally, we found that PKCe-depleted NSCLC cells fail to disseminate to lungs in a mouse model of metastasis. Conclusions: Our results implicate PKCe as a key mediator of Rac signaling and motility of lung cancer cells, highlighting its potential as a therapeutic target

Combination treatment with doxorubicin and gamitrinib synergistically augments anticancer activity through enhanced activation of Bim

Background: A common approach to cancer therapy in clinical practice is the combination of several drugs to boost the anticancer activity of available drugs while suppressing their unwanted side effects. In this regard, we examined the efficacy of combination treatment with the widely-used genotoxic drug doxorubicin and the mitochondriotoxic Hsp90 inhibitor gamitrinib to exploit disparate stress signaling pathways for cancer therapy.Methods: The cytotoxicity of the drugs as single agents or in combination against several cancer cell types was analyzed by MTT assay and the synergism of the drug combination was evaluated by calculating the combination index. To understand the molecular mechanism of the drug synergism, stress signaling pathways were analyzed after drug combination. Two xenograft models with breast and prostate cancer cells were used to evaluate anticancer activity of the drug combination in vivo. Cardiotoxicity was assessed by tissue histology and serum creatine phosphokinase concentration.Results: Gamitrinib sensitized various human cancer cells to doxorubicin treatment, and combination treatment with the two drugs synergistically increased apoptosis. The cytotoxicity of the drug combination involved activation and mitochondrial accumulation of the proapoptotic Bcl-2 family member Bim. Activation of Bim was associated with increased expression of the proapoptotic transcription factor C/EBP-homologous protein and enhanced activation of the stress kinase c-Jun N-terminal kinase. Combined drug treatment with doxorubicin and gamitrinib dramatically reduced in vivo tumor growth in prostate and breast xenograft models without increasing cardiotoxicity.Conclusions: The drug combination showed synergistic anticancer activities toward various cancer cells without aggravating the cardiotoxic side effects of doxorubicin, suggesting that the full therapeutic potential of doxorubicin can be unleashed through combination with gamitrinib.open

Selection of reliable biomarkers from PCR array analyses using relative distance computational model: Methodology and proof-of-concept study

10.1371/journal.pone.0083954PLoS ONE812-POLN

Cancer Biomarker Discovery: The Entropic Hallmark

Background: It is a commonly accepted belief that cancer cells modify their transcriptional state during the progression of the disease. We propose that the progression of cancer cells towards malignant phenotypes can be efficiently tracked using high-throughput technologies that follow the gradual changes observed in the gene expression profiles by employing Shannon's mathematical theory of communication. Methods based on Information Theory can then quantify the divergence of cancer cells' transcriptional profiles from those of normally appearing cells of the originating tissues. The relevance of the proposed methods can be evaluated using microarray datasets available in the public domain but the method is in principle applicable to other high-throughput methods. Methodology/Principal Findings: Using melanoma and prostate cancer datasets we illustrate how it is possible to employ Shannon Entropy and the Jensen-Shannon divergence to trace the transcriptional changes progression of the disease. We establish how the variations of these two measures correlate with established biomarkers of cancer progression. The Information Theory measures allow us to identify novel biomarkers for both progressive and relatively more sudden transcriptional changes leading to malignant phenotypes. At the same time, the methodology was able to validate a large number of genes and processes that seem to be implicated in the progression of melanoma and prostate cancer. Conclusions/Significance: We thus present a quantitative guiding rule, a new unifying hallmark of cancer: the cancer cell's transcriptome changes lead to measurable observed transitions of Normalized Shannon Entropy values (as measured by high-throughput technologies). At the same time, tumor cells increment their divergence from the normal tissue profile increasing their disorder via creation of states that we might not directly measure. This unifying hallmark allows, via the the Jensen-Shannon divergence, to identify the arrow of time of the processes from the gene expression profiles, and helps to map the phenotypical and molecular hallmarks of specific cancer subtypes. The deep mathematical basis of the approach allows us to suggest that this principle is, hopefully, of general applicability for other diseases

Regulation of Transcriptional Networks by PKC Isozymes: Identification of c-Rel as a Key Transcription Factor for PKC-Regulated Genes

<div><p>Background</p><p>Activation of protein kinase C (PKC), a family of serine-threonine kinases widely implicated in cancer progression, has major impact on gene expression. In a recent genome-wide analysis of prostate cancer cells we identified distinctive gene expression profiles controlled by individual PKC isozymes and highlighted a prominent role for PKCδ in transcriptional activation.</p><p>Principal Findings</p><p>Here we carried out a thorough bioinformatics analysis to dissect transcriptional networks controlled by PKCα, PKCδ, and PKCε, the main diacylglycerol/phorbol ester PKCs expressed in prostate cancer cells. Despite the remarkable differences in the patterns of transcriptional responsive elements (REs) regulated by each PKC, we found that c-Rel represents the most frequent RE in promoters regulated by all three PKCs. In addition, promoters of PKCδ-regulated genes were particularly enriched with REs for CREB, NF-E2, RREB, SRF, Oct-1, Evi-1, and NF-κB. Most notably, by using transcription factor-specific RNAi we were able to identify subsets of PKCδ-regulated genes modulated by c-Rel and CREB. Furthermore, PKCδ-regulated genes condensed under the c-Rel transcriptional regulation display significant functional interconnections with biological processes such as angiogenesis, inflammatory response, and cell motility.</p><p>Conclusion/Significance</p><p>Our study identified candidate transcription factors in the promoters of PKC regulated genes, in particular c-Rel was found as a key transcription factor in the control of PKCδ-regulated genes. The deconvolution of PKC-regulated transcriptional networks and their nodes may greatly help in the identification of PKC effectors and have significant therapeutics implications.</p></div

Candidate Interaction Matrix for statistically enriched REs for each PKC isozyme, as determined by PAINT.

<p><i>Columns</i> correspond to the TRANSFAC identifiers for each over-represented RE. <i>Rows</i> represent the Entrez Gene IDs of genes from the input list. (A) Feasnet based on the raw <i>p</i>-values of over-represented REs in the promoter of PKCα (<i>left</i>), PKCδ (<i>middle</i>) and PKCε (<i>right</i>). (B) FDR-adjusted <i>p</i>-value based Feasnet of over-represented REs in the promoter of PKCδ-regulated genes. No significantly enriched REs were found in this comparison for either PKCα or PKCε.</p

GeneMANIA analysis of c-Rel transcriptionally regulated genes.

<p>GeneMANIA analysis for correlation of Gene Ontology annotations with expression status of c-Rel transcriptionally regulated genes. The gene sets are presented with their associated FDR. <i>Coverage</i> represents the number of genes present in the network over the total number of genes annotated for that Gene Ontology.</p

ChIP analysis for c-Rel in PKCδ-regulated genes used for validation.

<p>ChIP analysis was performed in LNCaP cells using an anti-c-Rel antibody, and IgG as a negative control. PCR primers were designed to flank known c-Rel binding sites in the BCL2A1 and SERPINB2 promoters. <i>Mw</i>, molecular weight marker. Two independent samples for c-Rel and IgG were run in the gel. Similar results were observed in three separate experiments.</p