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1.  The KLK5 protease suppresses breast cancer by repressing the mevalonate pathway 
Oncotarget  2013;5(9):2390-2403.
Kallikrein-related peptidase 5 (KLK5) displays aberrant expression in cancer. However, any functional association is missing. Here, we show that reconstitution of KLK5 expression in non-expressing MDA-MB-231 breast cancer cells suppresses malignancy in vitro and in vivo dose-dependently. Reactivation of KLK5 suppressed key EMT genes. Unexpectedly, we identified altered expression of genes encoding enzymes of the mevalonate pathway typical of those observed upon cholesterol starvation. Consistently, we found that SREBF1, the master regulator of the mevalonate pathway was induced. KLK5 re-expression leads to reduced cellular cholesterol and fatty acid synthesis and enhanced uptake of LDL-cholesterol. Suppression of the mevalonate pathway in KLK5 transfectants was further shown by reduced synthesis of isoprenoids. Indeed, we found diminished levels of active RhoA, a signaling oncoprotein that requires prenylation for activation. We propose that reduced RhoA activation plays a dominant role in suppression of malignancy by KLK5, since geranylgeranyl pyrophosphate restored active RhoA in KLK5-reverted cells resulting in increased malignancy. For the first time, we suggest that a protease may suppress breast cancer by modulating the mevalonate pathway.
PMCID: PMC4058013  PMID: 24158494
Kallikrein-related peptidase 5 (KLK5); breast cancer; mevalonate pathway; oncogenic signaling
2.  HuR-Regulated mRNAs Associated with Nuclear hnRNP A1-RNP Complexes 
Post-transcriptional regulatory networks are dependent on the interplay of many RNA-binding proteins having a major role in mRNA processing events in mammals. We have been interested in the concerted action of the two RNA-binding proteins hnRNP A1 and HuR, both stable components of immunoselected hnRNP complexes and having a major nuclear localization. Specifically, we present here the application of the RNA-immunoprecipitation (RIP)-Chip technology to identify a population of nuclear transcripts associated with hnRNP A1-RNPs as isolated from the nuclear extract of either HuR WT or HuR-depleted (KO) mouse embryonic fibroblast (MEF) cells. The outcome of this analysis was a list of target genes regulated via HuR for their association (either increased or reduced) with the nuclear hnRNP A1-RNP complexes. Real time PCR analysis was applied to validate a selected number of nuclear mRNA transcripts, as well as to identify pre-spliced transcripts (in addition to their mature mRNA counterpart) within the isolated nuclear hnRNP A1-RNPs. The differentially enriched mRNAs were found to belong to GO categories relevant to biological processes anticipated for hnRNP A1 and HuR (such as transport, transcription, translation, apoptosis and cell cycle) indicating their concerted function in mRNA metabolism.
doi:10.3390/ijms141020256
PMCID: PMC3821614  PMID: 24152440
RNA-binding proteins (RBPs); ribonucleoprotein (hnRNP) complexes; post-transcriptional regulation; mRNA processing; RNA-immunoprecipitation (RIP)-Chip technology; mouse embryonic fibroblasts (MEFs)
3.  A Comparative Genomic Study in Schizophrenic and in Bipolar Disorder Patients, Based on Microarray Expression Profiling Meta-Analysis 
The Scientific World Journal  2013;2013:685917.
Schizophrenia affecting almost 1% and bipolar disorder affecting almost 3%–5% of the global population constitute two severe mental disorders. The catecholaminergic and the serotonergic pathways have been proved to play an important role in the development of schizophrenia, bipolar disorder, and other related psychiatric disorders. The aim of the study was to perform and interpret the results of a comparative genomic profiling study in schizophrenic patients as well as in healthy controls and in patients with bipolar disorder and try to relate and integrate our results with an aberrant amino acid transport through cell membranes. In particular we have focused on genes and mechanisms involved in amino acid transport through cell membranes from whole genome expression profiling data. We performed bioinformatic analysis on raw data derived from four different published studies. In two studies postmortem samples from prefrontal cortices, derived from patients with bipolar disorder, schizophrenia, and control subjects, have been used. In another study we used samples from postmortem orbitofrontal cortex of bipolar subjects while the final study was performed based on raw data from a gene expression profiling dataset in the postmortem superior temporal cortex of schizophrenics. The data were downloaded from NCBI's GEO datasets.
doi:10.1155/2013/685917
PMCID: PMC3608181  PMID: 23554570
4.  Application of an Integrative Computational Framework in Trancriptomic Data of Atherosclerotic Mice Suggests Numerous Molecular Players 
Advances in Bioinformatics  2012;2012:453513.
Atherosclerosis is a multifactorial disease involving a lot of genes and proteins recruited throughout its manifestation. The present study aims to exploit bioinformatic tools in order to analyze microarray data of atherosclerotic aortic lesions of ApoE knockout mice, a model widely used in atherosclerosis research. In particular, a dynamic analysis was performed among young and aged animals, resulting in a list of 852 significantly altered genes. Pathway analysis indicated alterations in critical cellular processes related to cell communication and signal transduction, immune response, lipid transport, and metabolism. Cluster analysis partitioned the significantly differentiated genes in three major clusters of similar expression profile. Promoter analysis applied to functional related groups of the same cluster revealed shared putative cis-elements potentially contributing to a common regulatory mechanism. Finally, by reverse engineering the functional relevance of differentially expressed genes with specific cellular pathways, putative genes acting as hubs, were identified, linking functionally disparate cellular processes in the context of traditional molecular description.
doi:10.1155/2012/453513
PMCID: PMC3502768  PMID: 23193398
5.  A transcriptomic computational analysis of mastic oil-treated Lewis lung carcinomas reveals molecular mechanisms targeting tumor cell growth and survival 
BMC Medical Genomics  2009;2:68.
Background
Mastic oil from Pistacia lentiscus variation chia, a blend of bioactive terpenes with recognized medicinal properties, has been recently shown to exert anti-tumor growth activity through inhibition of cancer cell proliferation, survival, angiogenesis and inflammatory response. However, no studies have addressed its mechanisms of action at genome-wide gene expression level.
Methods
To investigate molecular mechanisms triggered by mastic oil, Lewis Lung Carcinoma cells were treated with mastic oil or DMSO and RNA was collected at five distinct time points (3-48 h). Microarray expression profiling was performed using Illumina mouse-6 v1 beadchips, followed by computational analysis. For a number of selected genes, RT-PCR validation was performed in LLC cells as well as in three human cancer cell lines of different origin (A549, HCT116, K562). PTEN specific inhibition by a bisperovanadium compound was applied to validate its contribution to mastic oil-mediated anti-tumor growth effects.
Results
In this work we demonstrated that exposure of Lewis lung carcinomas to mastic oil caused a time-dependent alteration in the expression of 925 genes. GO analysis associated expression profiles with several biological processes and functions. Among them, modifications on cell cycle/proliferation, survival and NF-κB cascade in conjunction with concomitant regulation of genes encoding for PTEN, E2F7, HMOX1 (up-regulation) and NOD1 (down-regulation) indicated some important mechanistic links underlying the anti-proliferative, pro-apoptotic and anti-inflammatory effects of mastic oil. The expression profiles of Hmox1, Pten and E2f7 genes were similarly altered by mastic oil in the majority of test cancer cell lines. Inhibition of PTEN partially reversed mastic oil effects on tumor cell growth, indicating a multi-target mechanism of action. Finally, k-means clustering, organized the significant gene list in eight clusters demonstrating a similar expression profile. Promoter analysis in a representative cluster revealed shared putative cis-elements suggesting a common regulatory transcription mechanism.
Conclusions
Present results provide novel evidence on the molecular basis of tumor growth inhibition mediated by mastic oil and set a rational basis for application of genomics and bioinformatic methodologies in the screening of natural compounds with potential cancer chemopreventive activities.
doi:10.1186/1755-8794-2-68
PMCID: PMC2801511  PMID: 20003503

Results 1-5 (5)