Athanasia Pavlopoulou

Evolutionary History of Tissue Kallikreins

The gene family of human kallikrein-related peptidases (KLKs) encodes proteins with diverse and pleiotropic functions in normal physiology as well as in disease states. Currently, the most widely known KLK is KLK3 or prostate-specific antigen (PSA) that has applications in clinical diagnosis and monitoring of prostate cancer. The KLK gene family encompasses the largest contiguous cluster of serine proteases in humans which is not interrupted by non-KLK genes. This exceptional and unique characteristic of KLKs makes them ideal for evolutionary studies aiming to infer the direction and timing of gene duplication events. Previous studies on the evolution of KLKs were restricted to mammals and the emergence of KLKs was suggested about 150 million years ago (mya). In order to elucidate the evolutionary history of KLKs, we performed comprehensive phylogenetic analyses of KLK homologous proteins in multiple genomes including those that have been completed recently. Interestingly, we were able to identify novel reptilian, avian and amphibian KLK members which allowed us to trace the emergence of KLKs 330 mya. We suggest that a series of duplication and mutation events gave rise to the KLK gene family. The prominent feature of the KLK family is that it consists of tandemly and uninterruptedly arrayed genes in all species under investigation. The chromosomal co-localization in a single cluster distinguishes KLKs from trypsin and other trypsin-like proteases which are spread in different genetic loci. All the defining features of the KLKs were further found to be conserved in the novel KLK protein sequences. The study of this unique family will further assist in selecting new model organisms for functional studies of proteolytic pathways involving KLKs.

State-of-the-art bioinformatics protein structure prediction tools (Review)

Knowledge of the native structure of a protein could provide an understanding of the molecular basis of its function. However, in the postgenomics era, there is a growing gap between proteins with experimentally determined structures and proteins without known structures. To deal with the overwhelming data, a collection of automated methods as bioinformatics tools which determine the structure of a protein from its amino acid sequence have emerged. The aim of this paper is to provide the experimental biologists with a set of cutting-edge, carefully evaluated, user-friendly computational tools for protein structure prediction that would be helpful for the interpretation of their results and the rational design of new experiments.

Phylogenetic analysis of the eukaryotic RNA (cytosine-5)-methyltransferases

RNA (cytosine-5)-methyltransferases (RCMTs) have been characterized both in prokaryotic and eukaryotic organisms. The RCMT family, however, remains largely uncharacterized, as opposed to the family of DNA (cytosine-5)-methyltransferases which has been studied in depth. In the present study, an in silico identification of the putative 5-methylcytosine RNA-generating enzymes in the eukaryotic genomes was performed. A comprehensive phylogenetic analysis of the putative eukaryotic RCMT-related proteins has been performed in order to redefine subfamilies within the RCMT family. Five distinct eukaryotic subfamilies were identified, including the three already known (NOP2, NCL1 and YNL022c), one novel subfamily (RCMT9) and a fifth one which hitherto was considered to exist exclusively in prokaryotes (Fmu). The potential evolutionary relationships among the different eukaryotic RCMT subfamilies were also investigated. Furthermore, the results of this study add further support to a previous hypothesis that RCMTs represent evolutionary intermediates of RNA (uridine-5)-methyltransferases and DNA (cytosine-5)-methyltransferases.

Antiviral Stratagems Against HIV-1 Using RNA Interference (RNAi) Technology

The versatility of human immunodeficiency virus (HIV)-1 and its evolutionary potential to elude antiretroviral agents by mutating may be its most invincible weapon. Viruses, including HIV, in order to adapt and survive in their environment evolve at extremely fast rates. Given that conventional approaches which have been applied against HIV have failed, novel and more promising approaches must be employed. Recent studies advocate RNA interference (RNAi) as a promising therapeutic tool against HIV In this regard, targeting multiple HIV sites in the context of a combinatorial RNAi-based approach may efficiently stop viral propagation at an early stage. Moreover, large high-throughput RNAi screens are widely used in the fields of drug development and reverse genetics. Computer-based algorithms, bioinformatics, and biostatistical approaches have been employed in traditional medicinal chemistry discovery protocols for low molecular weight compounds. However, the diversity and complexity of RNAi screens cannot be efficiently addressed by these outdated approaches. Herein, a series of novel workflows for both wet- and dry-lab strategies are presented in an effort to provide an updated review of state-of-the-art RNAi technologies, which may enable adequate progress in the fight against the HIV-1 virus.

Human cancer databases (Review)

Cancer is one of the four major non-communicable diseases (NCD), responsible for ~14.6% of all human deaths. Currently, there are >100 different known types of cancer and >500 genes involved in cancer. Ongoing research efforts have been focused on cancer etiology and therapy. As a result, there is an exponential growth of cancer-associated data from diverse resources, such as scientific publications, genome-wide association studies, gene expression experiments, gene-gene or protein-protein interaction data, enzymatic assays, epigenomics, immunomics and cytogenetics, stored in relevant repositories. These data are complex and heterogeneous, ranging from unprocessed, unstructured data in the form of raw sequences and polymorphisms to well-annotated, structured data. Consequently, the storage, mining, retrieval and analysis of these data in an efficient and meaningful manner pose a major challenge to biomedical investigators. In the current review, we present the central, publicly accessible databases that contain data pertinent to cancer, the resources available for delivering and analyzing information from these databases, as well as databases dedicated to specific types of cancer. Examples for this wealth of cancer-related information and bioinformatic tools have also been provided.

Determinants of resistance to chemotherapy and ionizing radiation in breast cancer stem cells

Breast cancer cells are suggested to be organized in a hierarchical manner with a subpopulation of stem cells, termed as breast cancer stem cells (BCSCs), which contribute significantly to tumorigenesis, cancer recurrence and metastasis. BCSCs have been demonstrated to exhibit significant resistance to conventional chemo- and radiotherapy. Recent evidence suggests that treatment of breast cancers with radiation or chemotherapy agents induces stem cell-like properties in non-stem cells. Herein, we provide an overview of the key determinants of resistance to chemotherapy and radiation in BCSCs. To this end and by the use of bioinformatics, the molecular pathways, the defining markers, as well as the microenvironmental and genetic factors, which are implicated in the maintenance of stemness, chemo- and radioresistance in BCSCs, are identified and presented. Our findings could provide the foundation for the design of targeted chemo- or radiotherapeutic regimens in order to eliminate or sensitize BCSCs to cytotoxic therapies and prevent tumor relapse and metastasis.

An Integrated In Silico Approach to Design Specific Inhibitors Targeting Human Poly(A)-Specific Ribonuclease

Poly(A)-specific ribonuclease (PARN) is an exoribonuclease/deadenylase that degrades 3′-end poly(A) tails in almost all eukaryotic organisms. Much of the biochemical and structural information on PARN comes from the human enzyme. However, the existence of PARN all along the eukaryotic evolutionary ladder requires further and thorough investigation. Although the complete structure of the full-length human PARN, as well as several aspects of the catalytic mechanism still remain elusive, many previous studies indicate that PARN can be used as potent and promising anti-cancer target. In the present study, we attempt to complement the existing structural information on PARN with in-depth bioinformatics analyses, in order to get a hologram of the molecular evolution of PARNs active site. In an effort to draw an outline, which allows specific drug design targeting PARN, an unequivocally specific platform was designed for the development of selective modulators focusing on the unique structural and catalytic features of the enzyme. Extensive phylogenetic analysis based on all the publicly available genomes indicated a broad distribution for PARN across eukaryotic species and revealed structurally important amino acids which could be assigned as potentially strong contributors to the regulation of the catalytic mechanism of PARN. Based on the above, we propose a comprehensive in silico model for the PARN’s catalytic mechanism and moreover, we developed a 3D pharmacophore model, which was subsequently used for the introduction of DNP-poly(A) amphipathic substrate analog as a potential inhibitor of PARN. Indeed, biochemical analysis revealed that DNP-poly(A) inhibits PARN competitively. Our approach provides an efficient integrated platform for the rational design of pharmacophore models as well as novel modulators of PARN with therapeutic potential.

Functions, divergence and clinical value of TAp73 isoforms in cancer.

The p73 gene encodes the tumour suppressive full-length TAp73 and N-terminal-truncated DNp73 isoforms that act as dominant negative inhibitors of TAp73. The overall effect of p73 in oncogenesis is thought to depend on the TAp73 to DNp73 isoforms’ ratio. TAp73 isoforms include a number of C-terminal variants as a result of alternative splicing in 3′-end. TAp73 isoforms protect cells from oncogenic alterations in a multifaceted way since they are implicated in the suppression of all demonstrated hallmarks and enabling characteristics of cancer. Their best established role is in apoptosis, a process which seems to be differently affected by each TAp73 C-terminal variant. Based on previous findings and our thorough bioinformatics analysis, we highlight that TAp73 variants are functionally non-equivalent, since they present major differences in their transactivation efficiencies, protein interactions, response to DNA damage and apoptotic effects that are attributable to the primary structure of their C terminus. In this review, we summarise these differences and we unveil the link between crucial C-terminal motifs/residues and the oncosuppressive potential of TAp73 isoforms, emphasising on the importance of considering C terminus during the development of p73-based anticancer biologics.

Gold nanoparticles, radiations and the immune system: Current insights into the physical mechanisms and the biological interactions of this new alliance towards cancer therapy

&NA; Considering both cancers serious impact on public health and the side effects of cancer treatments, strategies towards targeted cancer therapy have lately gained considerable interest. Employment of gold nanoparticles (GNPs), in combination with ionizing and non‐ionizing radiations, has been shown to improve the effect of radiation treatment significantly. GNPs, as high‐Z particles, possess the ability to absorb ionizing radiation and enhance the deposited dose within the targeted tumors. Furthermore, they can convert non‐ionizing radiation into heat, due to plasmon resonance, leading to hyperthermic damage to cancer cells. These observations, also supported by experimental evidence both in vitro and in vivo systems, reveal the capacity of GNPs to act as radiosensitizers for different types of radiation. In addition, they can be chemically modified to selectively target tumors, which renders them suitable for future cancer treatment therapies. Herein, a current review of the latest data on the physical properties of GNPs and their effects on GNP circulation time, biodistribution and clearance, as well as their interactions with plasma proteins and the immune system, is presented. Emphasis is also given with an in depth discussion on the underlying physical and biological mechanisms of radiosensitization. Furthermore, simulation data are provided on the use of GNPs in photothermal therapy upon non‐ionizing laser irradiation treatment. Finally, the results obtained from the application of GNPs at clinical trials and pre‐clinical experiments in vivo are reported.

Progression of mouse skin carcinogenesis is associated with the orchestrated deregulation of miR-200 family members, miR-205 and their common targets

MicroRNAs are small, non‐coding RNAs which regulate post‐transcriptionally hundreds of target mRNAs. Given that their expression is deregulated in several cancer types, they represent potential diagnostic, prognostic, and predictive biomarkers, as well as next‐generation therapeutic targets. Nevertheless, the involvement of miRNAs in non‐melanoma skin cancer, a cancer type with increasing prevalence, is not extensively studied, and their comprehensive characterization as regard to the initiation, promotion, and progression stages is missing. To this end, we exploited a well‐established multistage mouse skin carcinogenesis model in order to identify miRNAs consistently implicated in different stages of skin carcinogenesis. The cell lines comprising this model were subjected to miRNA expression profiling using microarrays, followed by bioinformatics analysis and validation with Q‐PCR, as well as treatment with miRNA modulators. We showed that among all deregulated miRNAs in our system, only a functionally coherent group consisting of the miR‐200 family members and miR‐205‐5p displays a pattern of progressive co‐downregulation from the early toward the most aggressive stages of carcinogenesis. Their overlapping, co‐regulated putative targets are potentially inter‐associated and, of these, the EMT‐related Rap1a is overexpressed toward aggressive stages. Ectopic expression of miR‐205‐5p in spindle cancer cells reduces Rap1a, mitigates cell invasiveness, decreases proliferation, and delays tumor onset. We conclude that deregulation of this miRNA group is primarily associated with aggressive phenotypes of skin cancer cells. Restoration of the miR‐205‐5p member of this group in spindle cells reduces the expression of critical, co‐regulated targets that favor cancer progression, thus reversing the EMT characteristics.