RNA Interference and cyclooxygenase-2 (COX-2) regulation in colon cancer cells

Despite new methods and combined strategies, conventional cancer chemotherapy still lacks specificity and induces drug resistance. Gene therapy can offer the potential to obtain the success in the clinical treatment of cancer and this can be achieved by replacing mutated tumour suppressor genes, inhibiting gene transcription, introducing new genes encoding for therapeutic products, or specifically silencing any given target gene. Concerning gene silencing, attention has recently shifted onto the RNA interference (RNAi) phenomenon. Gene silencing mediated by RNAi machinery is based on short RNA molecules, small interfering RNAs (siRNAs) and microRNAs (miRNAs), that are fully o partially homologous to the mRNA of the genes being silenced, respectively. On one hand, synthetic siRNAs appear as an important research tool to understand the function of a gene and the prospect of using siRNAs as potent and specific inhibitors of any target gene provides a new therapeutical approach for many untreatable diseases, particularly cancer. On the other hand, the discovery of the gene regulatory pathways mediated by miRNAs, offered to the research community new important perspectives for the comprehension of the physiological and, above all, the pathological mechanisms underlying the gene regulation. Indeed, changes in miRNAs expression have been identified in several types of neoplasia and it has also been proposed that the overexpression of genes in cancer cells may be due to the disruption of a control network in which relevant miRNA are implicated. For these reasons, I focused my research on a possible link between RNAi and the enzyme cyclooxygenase-2 (COX-2) in the field of colorectal cancer (CRC), since it has been established that the transition adenoma-adenocarcinoma and the progression of CRC depend on aberrant constitutive expression of COX-2 gene. In fact, overexpressed COX-2 is involved in the block of apoptosis, the stimulation of tumor-angiogenesis and promotes cell invasion, tumour growth and metastatization. On the basis of data reported in the literature, the first aim of my research was to develop an innovative and effective tool, based on the RNAi mechanism, able to silence strongly and specifically COX-2 expression in human colorectal cancer cell lines. In this study, I firstly show that an siRNA sequence directed against COX-2 mRNA (siCOX-2), potently downregulated COX-2 gene expression in human umbilical vein endothelial cells (HUVEC) and inhibited PMA-induced angiogenesis in vitro in a specific, non-toxic manner. Moreover, I found that the insertion of a specific cassette carrying anti-COX-2 shRNA sequence (shCOX-2, the precursor of siCOX-2 previously tested) into a viral vector (pSUPER.retro) greatly increased silencing potency in a colon cancer cell line (HT-29) without activating any interferon response. Phenotypically, COX-2 deficient HT-29 cells showed a significant impairment of their in vitro malignant behaviour. Thus, results reported here indicate an easy-to-use, powerful and high selective virus-based method to knockdown COX-2 gene in a stable and long-lasting manner, in colon cancer cells. Furthermore, they open up the possibility of an in vivo application of this anti-COX-2 retroviral vector, as therapeutic agent for human cancers overexpressing COX-2. In order to improve the tumour selectivity, pSUPER.retro vector was modified for the shCOX-2 expression cassette. The aim was to obtain a strong, specific transcription of shCOX-2 followed by COX-2 silencing mediated by siCOX-2 only in cancer cells. For this reason, H1 promoter in basic pSUPER.retro vector [pS(H1)] was substituted with the human Cox-2 promoter [pS(COX2)] and with a promoter containing repeated copies of the TCF binding element (TBE) [pS(TBE)]. These promoters were choosen because they are partculary activated in colon cancer cells. COX-2 was effectively silenced in HT-29 and HCA-7 colon cancer cells by using enhanced pS(COX2) and pS(TBE) vectors. In particular, an higher siCOX-2 production followed by a stronger inhibition of Cox-2 gene were achieved by using pS(TBE) vector, that represents not only the most effective, but also the most specific system to downregulate COX-2 in colon cancer cells. Because of the many limits that a retroviral therapy could have in a possible in vivo treatment of CRC, the next goal was to render the enhanced RNAi-mediate COX-2 silencing more suitable for this kind of application. Xiang and et al. (2006) demonstrated that it is possible to induce RNAi in mammalian cells after infection with engineered E. Coli strains expressing Inv and HlyA genes, which encode for two bacterial factors needed for successful transfer of shRNA in mammalian cells. This system, called “trans-kingdom” RNAi (tkRNAi) could represent an optimal approach for the treatment of colorectal cancer, since E. Coli in normally resident in human intestinal flora and could easily vehicled to the tumor tissue. For this reason, I tested the improved COX-2 silencing mediated by pS(COX2) and pS(TBE) vectors by using tkRNAi system. Results obtained in HT-29 and HCA-7 cell lines were in high agreement with data previously collected after the transfection of pS(COX2) and pS(TBE) vectors in the same cell lines. These findings suggest that tkRNAi system for COX-2 silencing, in particular mediated by pS(TBE) vector, could represent a promising tool for the treatment of colorectal cancer. Flanking the studies addressed to the setting-up of a RNAi-mediated therapeutical strategy, I proposed to get ahead with the comprehension of new molecular basis of human colorectal cancer. In particular, it is known that components of the miRNA/RNAi pathway may be altered during the progressive development of colorectal cancer (CRC), and it has been already demonstrated that some miRNAs work as tumor suppressors or oncomiRs in colon cancer. Thus, my hypothesis was that overexpressed COX-2 protein in colon cancer could be the result of decreased levels of one or more tumor suppressor miRNAs. In this thesis, I clearly show an inverse correlation between COX-2 expression and the human miR- 101(1) levels in colon cancer cell lines, tissues and metastases. I also demonstrate that the in vitro modulating of miR-101(1) expression in colon cancer cell lines leads to significant variations in COX-2 expression, and this phenomenon is based on a direct interaction between miR-101(1) and COX-2 mRNA. Moreover, I started to investigate miR-101(1) regulation in the hypoxic environment since adaptation to hypoxia is critical for tumor cell growth and survival and it is known that COX-2 can be induced directly by hypoxia-inducible factor 1 (HIF-1). Surprisingly, I observed that COX-2 overexpression induced by hypoxia is always coupled to a significant decrease of miR-101(1) levels in colon cancer cell lines, suggesting that miR-101(1) regulation could be involved in the adaption of cancer cells to the hypoxic environment that strongly characterize CRC tissues.

A novel phase variation mechanism in the meningococcus driven by a ligand-responsive repressor and differential spacing of distal promoter elements

Phase variable expression, mediated by high frequency reversible changes in the length of simple sequence repeats, facilitates adaptation of bacterial populations to changing environments and is frequently important in bacterial virulence. Here we elucidate a novel phase variable mechanism for NadA expression, an adhesin and invasin of Neisseria meningitidis. The NadR repressor protein binds to operators flanking the phase variable tract of the nadA promoter gene and contributes to the differential expression levels of phase variant promoters with different numbers of repeats, likely due to different spacing between operators. It is shown that IHF binds between these operators, and may permit looping of the promoter, allowing interaction of NadR at operators located distally or overlapping the promoter. The 4-hydroxyphenylacetic acid, a metabolite of aromatic amino acid catabolism that is secreted in saliva, induces nadA expression by inhibiting the DNA binding activity of the NadR repressor. When induced, only minor differences are evident between NadR-independent transcription levels of promoter phase variants, which are likely due to differential RNA polymerase contacts leading to altered promoter activity. These results suggest that NadA expression is under both stochastic and tight environmental-sensing regulatory control, and both regulations are mediated by the NadR repressor that and may be induced during colonization of the oropharynx where it plays a major role in the successful adhesion and invasion of the mucosa. Hence, simple sequence repeats in promoter regions may be a strategy used by host-adapted bacterial pathogens to randomly switch between expression states that may nonetheless still be induced by appropriate niche-specific signals.

A clustering method for robust and reliable large scale functional and structural protein sequence annotation

Bioinformatics, in the last few decades, has played a fundamental role to give sense to the huge amount of data produced. Obtained the complete sequence of a genome, the major problem of knowing as much as possible of its coding regions, is crucial. Protein sequence annotation is challenging and, due to the size of the problem, only computational approaches can provide a feasible solution. As it has been recently pointed out by the Critical Assessment of Function Annotations (CAFA), most accurate methods are those based on the transfer-by-homology approach and the most incisive contribution is given by cross-genome comparisons. In the present thesis it is described a non-hierarchical sequence clustering method for protein automatic large-scale annotation, called “The Bologna Annotation Resource Plus” (BAR+). The method is based on an all-against-all alignment of more than 13 millions protein sequences characterized by a very stringent metric. BAR+ can safely transfer functional features (Gene Ontology and Pfam terms) inside clusters by means of a statistical validation, even in the case of multi-domain proteins. Within BAR+ clusters it is also possible to transfer the three dimensional structure (when a template is available). This is possible by the way of cluster-specific HMM profiles that can be used to calculate reliable template-to-target alignments even in the case of distantly related proteins (sequence identity < 30%). Other BAR+ based applications have been developed during my doctorate including the prediction of Magnesium binding sites in human proteins, the ABC transporters superfamily classification and the functional prediction (GO terms) of the CAFA targets. Remarkably, in the CAFA assessment, BAR+ placed among the ten most accurate methods. At present, as a web server for the functional and structural protein sequence annotation, BAR+ is freely available at http://bar.biocomp.unibo.it/bar2.0.

Differential expression analysis for sequence count data via mixtures of negative binomials

The recent advent of Next-generation sequencing technologies has revolutionized the way of analyzing the genome. This innovation allows to get deeper information at a lower cost and in less time, and provides data that are discrete measurements. One of the most important applications with these data is the differential analysis, that is investigating if one gene exhibit a different expression level in correspondence of two (or more) biological conditions (such as disease states, treatments received and so on). As for the statistical analysis, the final aim will be statistical testing and for modeling these data the Negative Binomial distribution is considered the most adequate one especially because it allows for "over dispersion". However, the estimation of the dispersion parameter is a very delicate issue because few information are usually available for estimating it. Many strategies have been proposed, but they often result in procedures based on plug-in estimates, and in this thesis we show that this discrepancy between the estimation and the testing framework can lead to uncontrolled first-type errors. We propose a mixture model that allows each gene to share information with other genes that exhibit similar variability. Afterwards, three consistent statistical tests are developed for differential expression analysis. We show that the proposed method improves the sensitivity of detecting differentially expressed genes with respect to the common procedures, since it is the best one in reaching the nominal value for the first-type error, while keeping elevate power. The method is finally illustrated on prostate cancer RNA-seq data.