MICRORNA FUNCTIONS IN UV-INDUCED CUTANEOUS SQUAMOUS CELL CARCINOMA

Cutaneous squamous cell carcinoma (cuSCC) is the second most common skin cancer, for which long term UV exposure and chronic wounding are the dominant risk factors. Despite these clinically established connections, little is understood about the early molecular response of human skin to UV exposure and its connection to acute wounding and cuSCC. Thus, our goal is to find common and specific signatures driven by UV-exposure and wounding as a means of developing new approaches for treating and preventing cuSCC. Here, we perform integrated analyses of RNA-seq and miR-seq on 3 datasets: (1) UV-unexposed and acute UV-exposed human skin, (2) public dataset on acute wound healing and (3) our previously published dataset on normal skin and cuSCC from humans. We find that biological signatures and processes regulated by acute UV exposure and wounding has profound similarity. Through RNA-seq and miR-seq on matched normal skin and cuSCC tumors from humans and a UV-driven mouse model, as well as acute UV-exposed human skin, we were able to identify a group of miRs that change both in cuSCC development and following UV exposure. We previously reported that miR-21-5p and miR-31-5p overexpression correlates with the development of UV-induced cuSCC in human. This is also true for our analysis where we find that these miRs as well as miR-21-3p are upregulated by more than 6-fold in cuSCC (compared to normal skin) and more than 2.5-fold in UV-exposed skin (compared to unexposed skin). In addition, we identify that miR-340-5p and let-7i-5p are novel candidates that have not been previously linked to either cuSCC development or the UV response of human skin. This suggests that these changes in miRNA-RNA are important early events that regulated by both UV-exposure and wounding which eventually can promote cuSCC initiation. Thus, our findings suggest that UV-exposed skin, wound and cuSCC share various common signatures, which can be potentially validated as chemopreventive targets for cuSCC

The roles of microRNAs in skin wound healing

Skin is an essential biological barrier of the human body, and wound healing is the fundamental physiological process to keep its integrity. Chronic non-healing wounds are growing socioeconomic and health concerns, which longs for more understanding of their pathophysiology to discover effective treatments. In this thesis, we focused on how microRNAs (miR) work together with their target protein-coding genes to regulate the complex wound healing process, and by exploring the roles they play in chronic wounds we aimed to discover potential therapeutic targets. In paper I, a distinct up-regulation of miR-31 in human acute wounds was identified from profiling analysis. We discovered miR-31 as a pivotal regulator in promoting keratinocyte proliferation and migration by targeting EMP1 during wound healing, emphasizing its importance in re-epithelialization. In paper II, miR-34 family, as a famous tumour suppressor, popped out amidst the top upregulated microRNAs in venous ulcer. In vitro, miR-34a and miR-34c enhanced inflammatory response of epidermal keratinocytes via targeting LGR4 and positively regulating NF-κB signalling pathway. In vivo, mouse model of either miR-34 local overexpression or Lgr4 knockout displayed impaired wound healing with excessive inflammation and suppressed cell growth. These suggest that miR-34 play a pathological role in chronic wounds by contributing to the excessive inflammation. In paper III, in continuity with our previous report that miR-132 displays anti-inflammatory and pro-proliferative roles in keratinocytes, we studied the function of miR-132 in another major skin resident cell type fibroblasts. By both overexpression and inhibition, miR-132 was proved to facilitate migration of primary human dermal fibroblasts, through targeting RASA1 and regulating Ras signalling. Since fibroblasts derived from chronic wounds are nonmigratory, our study suggests the miR-132-RASA1-Ras axis with potential therapeutic impact. In paper IV, we tested the therapeutic potential of microRNAs, taken miR-132 as an example. A significant downregulation of miR-132 was revealed in diabetic foot ulcer. Intradermal injection of liposome-encapsulated miR-132 mimics effectively accelerated wound healing. Moreover, ex vivo human model exhibited ameliorated re-epithelialization upon miR132 topical application, denoting that local treatment of miR-132 deserves further evaluation in a clinical trial as a potential target for treating chronic wounds. Conclusively, this thesis investigated the crucial functions of miR-31, miR-34 and miR-132 in different phases of normal skin wound healing process and in chronic wounds, and pointed out a promising potential of microRNA-based therapy in treating chronic wounds

Computational functional prediction of novel long noncoding RNA in TCGA Glioblastoma multiforme sample

According to international human genome sequencing consortium 2004[43], it was known that only less than 2% of the total human genome code for proteins. This ignited quite a surprise in the scientific community. Since then, a lot of researchers are attracted towards the noncoding part of the genome. There are explosion of researches addressing the role of the 98% of the human untranslated regions of the genome. This shows that the transcription is not only limited to the protein coding regions of the genome rather more than 90% of the genome are likely to be transcribed. [43] This will result in the transcription of tens and thousands of the long noncoding RNAs (lncRNAs) with little or no coding potential. However, the molecular mechanism and function of long noncoding RNAs are still an open research topic. Although the functions of limited lncRNAs are identified, there is still a gap in identifying the function of novel lncRNAs. This project implements different computational methods to predict the function of novel lncRNAs identified from TCGA glioblastoma multiforme samples. The methods used in this functional prediction include both expression and sequence-based analysis approach. In expression-based analysis, the co-expressing genes with lncRNAs are used to predict the possible functional relation. In sequence based analysis, the gene-protein and lncRNA-protein interactions together with miRNA-lncRNA interactions are considered towards the possible functional predictions. The result from the integrated functional prediction on the novel lncRNAs show that TCGA_gbm3-153501 novel lncRNA which is co-expressed together with the THBS1 gene with correlation coefficient of more that 0.5 is predicted to function in cell-cell and cell-to-matrix interactions, platelet aggregation, angiogenesis, and tumorigenesis. [202] MSI1, RBM3 and RBM8A are RNA binding proteins (RBPs) that have binding site on both the first top five differentially expressed lncRNAs which are TCGA_gbm-2-104096501, TCGA_gbm-3-153501, TCGA_gbm-5-63687001 and TCGA_gbm-17-10671251 and IGF2 which is among the top 10 differentially expressed genes. Therefore, these lncRNAs are predicted to have functional role in cell proliferation and maintenance of stem cells in the central nervous system

Computational functional prediction of novel long noncoding RNA in TCGA Glioblastoma multiforme sample

According to international human genome sequencing consortium 2004[43], it was known that only less than 2% of the total human genome code for proteins. This ignited quite a surprise in the scientific community. Since then, a lot of researchers are attracted towards the noncoding part of the genome. There are explosion of researches addressing the role of the 98% of the human untranslated regions of the genome. This shows that the transcription is not only limited to the protein coding regions of the genome rather more than 90% of the genome are likely to be transcribed. [43] This will result in the transcription of tens and thousands of the long noncoding RNAs (lncRNAs) with little or no coding potential. However, the molecular mechanism and function of long noncoding RNAs are still an open research topic. Although the functions of limited lncRNAs are identified, there is still a gap in identifying the function of novel lncRNAs. This project implements different computational methods to predict the function of novel lncRNAs identified from TCGA glioblastoma multiforme samples. The methods used in this functional prediction include both expression and sequence-based analysis approach. In expression-based analysis, the co-expressing genes with lncRNAs are used to predict the possible functional relation. In sequence based analysis, the gene-protein and lncRNA-protein interactions together with miRNA-lncRNA interactions are considered towards the possible functional predictions. The result from the integrated functional prediction on the novel lncRNAs show that TCGA_gbm3-153501 novel lncRNA which is co-expressed together with the THBS1 gene with correlation coefficient of more that 0.5 is predicted to function in cell-cell and cell-to-matrix interactions, platelet aggregation, angiogenesis, and tumorigenesis. [202] MSI1, RBM3 and RBM8A are RNA binding proteins (RBPs) that have binding site on both the first top five differentially expressed lncRNAs which are TCGA_gbm-2-104096501, TCGA_gbm-3-153501, TCGA_gbm-5-63687001 and TCGA_gbm-17-10671251 and IGF2 which is among the top 10 differentially expressed genes. Therefore, these lncRNAs are predicted to have functional role in cell proliferation and maintenance of stem cells in the central nervous system

Methods in and Applications of the Sequencing of Short Non-Coding RNAs

Short non-coding RNAs are important for all domains of life. With the advent of modern molecular biology their applicability to medicine has become apparent in settings ranging from diagonistic biomarkers to therapeutics and fields ranging from oncology to neurology. In addition, a critical, recent technological development is high-throughput sequencing of nucleic acids. The convergence of modern biotechnology with developments in RNA biology presents opportunities in both basic research and medical settings. Here I present two novel methods for leveraging high-throughput sequencing in the study of short non-coding RNAs, as well as a study in which they are applied to Alzheimer\u27s Disease (AD). The computational methods presented here include High-throughput Annotation of Modified Ribonucleotides (HAMR), which enables researchers to detect post-transcriptional covalent modifications to RNAs in a high-throughput manner. In addition, I describe Classification of RNAs by Analysis of Length (CoRAL), a computational method that allows researchers to characterize the pathways responsible for short non-coding RNA biogenesis. Lastly, I present an application of the study of non-coding RNAs to Alzheimer\u27s disease. When applied to the study of AD, it is apparent that several classes of non-coding RNAs, particularly tRNAs and tRNA fragments, show striking changes in the dorsolateral prefrontal cortex of affected human brains. Interestingly, the nature of these changes differs between mitochondrial and nuclear tRNAs, implicating an association between Alzheimer\u27s disease and perturbation of mitochondrial function. In addition, by combining known genetic factors of AD with genes that are differentially expressed and targets of regulatory RNAs that are differentially expressed, I construct a network of genes that are potentially relevant to the pathogenesis of the disease. By combining genetics data with novel results from the study of non-coding RNAs, we can further elucidate the molecular mechanisms that underly Alzheimer\u27s disease pathogenesis

Local microRNAs in peritoneal dialysis-related peritonitis

Infection remains a major cause of morbidity, mortality and technique failure in PD patients. Identification of peritonitis episodes and the causative organism is slow and unreliable. The immune system has evolved to be specific for different pathogens, suggesting a pathogen specific “immune fingerprint” may be able to distinguish distinct pathogens to guide more accurate treatment decisions. microRNAs are post-transcriptional regulators of most human genes and have roles in the majority of biological processes and pathways. They are stable, accurate and specific biomarkers in biological fluids. My work aimed to combine the immune fingerprint model with specific microRNAs in PD effluent to identify peritonitis episodes and ascertain the role of extracellular microRNAs in the acute immune response. Approach The microRNA profile of PD effluent was analysed in peritonitis patients with different infectious organisms to identify candidate biomarkers. The cellular source of these microRNAs was identified, and the functional release of one microRNA (miR-223) into the extracellular space was analysed for functional stabilisation in extracellular vesicles. Results microRNA profiles are altered in infected compared to uninfected PD effluent, which may have diagnostic value in acute peritonitis. Four microRNAs were identified as candidate biomarkers (miR-223, miR-27a, miR-21 and miR-31), with distinct cell-specific expression patterns. Potential mRNA targets of these microRNAs were identified. miR-223 was found to be functionally stabilised in PD effluent from peritonitis patients, with a proportion likely to be incorporated into neutrophil-derived exosomes. Conclusions My studies prove that microRNAs are useful biomarkers of infection in PD-related peritonitis and have the potential to contribute to a pathogen-specific immune fingerprint. Exosome-encapsulated microRNAs may have a functional role in intercellular signalling between immune cells responding to the infection and the local tissue, to help clear the infection and resolve the inflammation

Transcriptome regulation network in Multiple sclerosis: Role of circular RNAs.

274 p.Multiple sclerosis (MS) is a chronic autoimmune disease of the central nervous system, that leads to neurological disability. The disease course and clinical phenotype are highly variable and therefore, biomarkers that can aid in the clinical practice are needed. Previous studies have shown a dysregulation in the coding and non-coding RNAs and proposed some as biomarkers. However, still none of them have reached the clinical practice. Recently, circular RNAs (circRNAs) have emerged as new players in the transcriptome that hold a great potential as biomarkers thanks to the features endowed by their circularity. In this thesis, we have performed different approaches to characterise the circRNA expression in leukocytes, peripheral blood mononuclear cells and extracellular vesicles from MS patients. Results have revealed hundreds of circRNAs whose expression is changed in the disease, and we have proposed eleven of them as potential minimally-invasive biomarkers. Finally, our functional experiments indicate that circRNAs may act as regulators of the immune response. This thesis opens a new research line in MS for future investigations to further evaluate the biomarker potential and the function of circRNAs in MS

Methods in and Applications of the Sequencing of Short Non-Coding RNAs

Short non-coding RNAs are important for all domains of life. With the advent of modern molecular biology their applicability to medicine has become apparent in settings ranging from diagonistic biomarkers to therapeutics and fields ranging from oncology to neurology. In addition, a critical, recent technological development is high-throughput sequencing of nucleic acids. The convergence of modern biotechnology with developments in RNA biology presents opportunities in both basic research and medical settings. Here I present two novel methods for leveraging high-throughput sequencing in the study of short non-coding RNAs, as well as a study in which they are applied to Alzheimer\u27s Disease (AD). The computational methods presented here include High-throughput Annotation of Modified Ribonucleotides (HAMR), which enables researchers to detect post-transcriptional covalent modifications to RNAs in a high-throughput manner. In addition, I describe Classification of RNAs by Analysis of Length (CoRAL), a computational method that allows researchers to characterize the pathways responsible for short non-coding RNA biogenesis. Lastly, I present an application of the study of non-coding RNAs to Alzheimer\u27s disease. When applied to the study of AD, it is apparent that several classes of non-coding RNAs, particularly tRNAs and tRNA fragments, show striking changes in the dorsolateral prefrontal cortex of affected human brains. Interestingly, the nature of these changes differs between mitochondrial and nuclear tRNAs, implicating an association between Alzheimer\u27s disease and perturbation of mitochondrial function. In addition, by combining known genetic factors of AD with genes that are differentially expressed and targets of regulatory RNAs that are differentially expressed, I construct a network of genes that are potentially relevant to the pathogenesis of the disease. By combining genetics data with novel results from the study of non-coding RNAs, we can further elucidate the molecular mechanisms that underly Alzheimer\u27s disease pathogenesis

Genetic landscape of multiple sclerosis susceptibility by leveraging multi-omics data

The main objective of the research studies presented in this thesis is to study the genetic variants and the expression of genes that relate to Multiple Sclerosis (MS). MS is a polygenic disease with HLA-DRB1*15:01 allele as a strong risk factor. Currently there are more than 200 non-HLA regions identified for MS. However, most of the risk loci identified in those studies are primarily driven by the relapsing-remitting form of MS (RRMS). To identify risk factors specific for the primary progressive form of MS (PPMS) which is a smaller group of MS patients, we have examined the exomes of PPMS and RRMS patients matching to population based controls in a case-control study setting and reported risk variants and mutations that are associated to PPMS and RRMS. The context of this study is during the ‘post-GWAS’ era, when researchers are primarily focused to understand the functional consequences of the genetic risk factors. Using the possibilities of transcriptomic and genotyping data, genes that correlate to the risk loci are identified in relevant cell types of MS. Several statistical methods are implemented to characterize the risk loci and replicate the findings in the context of disease. MicroRNAs (miRNAs), small non-coding RNAs which regulate gene expression at post-transcriptional level, have been identified dysregulated in autoimmune diseases, including MS. We used experimental autoimmune encephalomyelitis (EAE), a commonly used animal model for MS to understand the role of miRNA in the immune activation of EAE. Next generation sequencing (NGS) methods were widely applied in all of these studies specifically at transcriptomic and genomic level of the disease. NGS methods are data intensive but have higher reliability. To test the reliability, we compared reported gene expression measurements for ostensibly similar tissue samples collected from different RNA-seq studies. We found an overall consistency on expression data obtained from different studies and identified the factors contributing to systematic differences. This thesis gives an overview of progresses happening in the area of MS genetics, EAE model for neuroinflammation and omics data analysis to address genetic regulation of disease