Polo-like kinase (Plk) 1 as a target for prostate cancer management

Prostate cancer (PCa) is the most commonly occurring cancer in American men, next to skin cancer. Existing treatment options and surgical intervention are unable to effectively manage this cancer. Therefore, continuing efforts are ongoing to establish novel mechanism-based targets and strategies for its management. The serine/threonine kinases Polo-like kinase (Plk) 1 plays a key role in mitotic entry of proliferating cells and regulates many aspects of mitosis which are necessary for successful cytokinesis. Plk1 is over-expressed in many tumor types with aberrant elevation frequently constituting a prognostic indicator of poor disease outcome. This review discusses the studies which indicate that Plk1 could be an excellent target for the treatment as well as chemoprevention of prostate cancer.     

Emerging Significance and Therapeutic Potential of Extracellular vesicles

Extracellular vesicles (EVs), are membrane-bound vesicles that have many advantages over traditional nanocarriers for drug and gene delivery. Evidence from recent studies indicate that EVs have therapeutic capability with chemical or biological modification. Tumor-derived exosomes (TEXs) were used as a new type of antigens or tumor vaccines in anti-tumor immunotherapy. With superior characteristics, modified EVs were applied to loaded and delivered synthetic drugs, silencing RNA, and microRNA for treatment. Different surface functionalization strategies have been proposed to improve the therapeutic functions of EVs. Appropriately modified EVs for disease intervention provide new avenues for effective clinical treatment strategies. Therefore, this review aimed at elucidating the therapeutic functions of EVs to generate new ideas for treatment and to unlock their hidden potential in translational medicine.     

Proteomics in prostate cancer biomarker discovery

Despite advances in molecular medicine, genomics, proteomics and translational research, prostate cancer remains the second most common cause of cancer-related mortality for men in the Western world. Clearly, early detection, targeted treatment and post-treatment monitoring are vital tools to combat this disease. Tumor markers can be useful for diagnosis and early detection of cancer, assessment of prognosis, prediction of therapeutic effect and treatment monitoring. Such tumor markers include prostate-specific antigen (prostate), cancer antigen (CA)15.3 (breast), CA125 (ovarian), CA19.9 (gastrointestinal) and serum α-fetoprotein (testicular cancer). However, all of these biomarkers lack sensitivity and specificity and, therefore, there is a large drive towards proteomic biomarker discovery. Current research efforts are directed towards discovering biosignatures from biological samples using novel proteomic technologies that provide high-throughput, in-depth analysis and quantification of the proteome. Several of these studies have revealed promising biomarkers for use in diagnosis, assessment of prognosis, and targeting treatment of prostate cancer. This review focuses on prostate cancer proteomic biomarker discovery and its future potential.     

Androgen deficiency and aging in men.

Androgen levels decrease with age in men. Androgen deficiency in men older than 65 years leads to asthenia, a decrease in muscle mass, osteoporosis, and a decrease in sexual activity. Androgen deficiency has been reported to cause changes in mood and cognitive function. The combination of these factors results in impaired quality of life in older men. Androgen replacement therapy in hypogonadal men increases bone and muscle mass, enhances muscle and cardiovascular function, and improves sexual function and general well-being; whether elderly men experience benefits of androgen replacement is not known. These benefits have to be weighed against the possible adverse effects of prostate and cardiovascular diseases. Careful long-term studies are needed to assess the risk-to-reward ratios of androgen or other hormone replacement therapy before treatment strategies similar to estrogen therapy for postmenopausal women are implemented.     

Review. Genetics of addictions: strategies for addressing heterogeneity and polygenicity of substance use disorders

Addictions are common psychiatric disorders that exert high cost to the individual and to society. Addictions are a result of the interplay of multiple genetic and environmental factors. They are characterized by phenotypic and genetic heterogeneity as well as polygenicity, implying a contribution of different neurobiological mechanisms to the clinical diagnosis. Therefore, treatments for most substance use disorders are often only partially effective, with a substantial proportion of patients failing to respond. To address heterogeneity and polygenicity, strategies have been developed to identify more homogeneous subgroups of patients and to characterize genes contributing to their phenotype. These include genetic linkage and association studies as well as functional genetic analysis using endophenotypes and animal behavioural experimentation. Applying these strategies in a translational context aims at improving therapeutic response by the identification of subgroups of addiction patients for individualized, targeted treatment strategies. This article aims to discuss strategies addressing heterogeneity and polygenicity of substance use disorders by presenting results of recent research on genetic and environmental components of addiction. It will also introduce the European IMAGEN study that aims to integrate methodical approaches discussed in order to identify the genetic and neurobiological basis of behavioural traits relevant to the development of addictions.     

Immunocompetent orthotopic isograft mouse model of ovarian cancer for high-intensity focused ultrasound (HIFU) treatment

Ovarian epithelial carcinoma is the most common form of ovarian cancer, causing more deaths than any other cancer in women with gynecologic malignancies in the United States. The poor outcome for women with late-stage ovarian cancer underscores the need for early detection strategies and for new treatment options to be developed. High-intensity focused ultrasound (HIFU) is a therapeutic modality that is safe and effective against various types of solid tumors, and has the potential to serve as a treatment for ovarian cancer. Use of an appropriate animal model is important in obtaining relevant data for translational research. The purpose of the study reported here was to modify and create an immunocompetent orthotopic tumor isograft model for evaluation of intra-operative HIFU application. This model would resemble the clinical presentation of human patients with late-stage ovarian cancer. We were able to consistently produce a surgical model that presented with a single large, intra-abdominal tumor nodule within the left ovarian bursa, as well as multiple small nodules on the surface of other organs and tissues. This technique may also be used to refine other tumor models, using the ovarian bursa as an implant site for heterotopic tumor isografts.     

Tissue biomarkers for prostate cancer radiation therapy

Prostate cancer is the most common cancer and second leading cause of cancer deaths among men in the United States. Most men have localized disease diagnosed following an elevated serum prostate specific antigen test for cancer screening purposes. Standard treatment options consist of surgery or definitive radiation therapy directed by clinical factors that are organized into risk stratification groups. Current clinical risk stratification systems are still insufficient to differentiate lethal from indolent disease. Similarly, a subset of men in poor risk groups need to be identified for more aggressive treatment and enrollment into clinical trials. Furthermore, these clinical tools are very limited in revealing information about the biologic pathways driving these different disease phenotypes and do not offer insights for novel treatments which are needed in men with poor-risk disease. We believe molecular biomarkers may serve to bridge these inadequacies of traditional clinical factors opening the door for personalized treatment approaches that would allow tailoring of treatment options to maximize therapeutic outcome. We review the current state of prognostic and predictive tissue-based molecular biomarkers which can be used to direct localized prostate cancer treatment decisions, specifically those implicated with definitive and salvage radiation therapy.     

Evaluation of plasma and tissue estrogen suppression with third-generation aromatase inhibitors: Of relevance to clinical understanding?

Development of aromatase inhibition and aromatase inhibitors as a therapeutic strategy was initiated through two different pathways. The one pathway went through systematic exploration of aromatase substrate analogues for enzyme inhibitions, subsequently leading to the development of steroidal agents for clinical use. The second involved clinical observation with an unsuccessful anti-epileptic compound named aminoglutethimide, attempting to achieve a “medical adrenalectomy”. Endocrine studies on patients treated with aminoglutethimide lead to direct assessment of in vivo aromatase inhibition in patients on treatment, thus identifying a novel therapeutic strategy. As such, both research programs represent different examples of pioneering translational work leading towards a successful therapeutic strategy. Subsequent studies with respect to total aromatase inhibition have led to successful development of more potent strategies. Most importantly, these studies have revealed a correlation between aromatase inhibition and clinical outcome. Ongoing studies exploring tissue estrogen levels as well as gene expression profiles on therapy may further improve this important therapeutic area.     

Incorporating short-term outcome information to predict long-term survival with discrete markers

In disease screening and prognosis studies, an important task is to determine useful markers for identifying high-risk subgroups. Once such markers are established, they can be incorporated into public health practice to provide appropriate strategies for treatment or disease monitoring based on each individual's predicted risk. In the recent years, genetic and biological markers have been examined extensively for their potential to signal progression or risk of disease. In addition to these markers, it has often been argued that short-term outcomes may be helpful in making a better prediction of disease outcomes in clinical practice. In this paper we propose model-free non-parametric procedures to incorporate short-term event information to improve the prediction of a long-term terminal event. We include the optional availability of a single discrete marker measurement and assess the additional information gained by including the short-term outcome. We focus on the semi-competing risk setting where the short-term event is an intermediate event that may be censored by the terminal event while the terminal event is only subject to administrative censoring. Simulation studies suggest that the proposed procedures perform well in finite samples. Our procedures are illustrated using a data set of post-dialysis patients with end-stage renal disease.     

Why the stroma matters in breast cancer

Survival and recurrence rates in breast cancer are variable for common diagnoses, and therefore the biological underpinnings of the disease that determine those outcomes are yet to be fully understood. As a result, translational medicine is one of the fastest growing arenas of study in tumor biology. With advancements in genetic and imaging techniques, archived biopsies can be examined for purposes other than diagnosis. There is a great deal of evidence that points to the stroma as the major regulator of tumor progression following the initial stages of tumor formation, and the stroma may also contribute to risk factors determining tumor formation. Therefore, aspects of stromal biology are well-suited to be a focus for studies of patient outcome, where statistical differences in survival among patients provide evidence as to whether that stromal component is a signpost for tumor progression. In this review we summarize the latest research done where breast cancer patient survival was correlated with aspects of stromal biology, which have been put into four categories: reorganization of the extracellular matrix (ECM) to promote invasion, changes in the expression of stromal cell types, changes in stromal gene expression, and changes in cell biology signaling cascades to and from the stroma.     

Why the stroma matters in breast cancer: Insights into breast cancer patient outcomes through the examination of stromal biomarkers

Survival and recurrence rates in breast cancer are variable for common diagnoses, and therefore the biological underpinnings of the disease that determine those outcomes are yet to be fully understood. As a result, translational medicine is one of the fastest growing arenas of study in tumor biology. With advancements in genetic and imaging techniques, archived biopsies can be examined for purposes other than diagnosis. There is a great deal of evidence that points to the stroma as the major regulator of tumor progression following the initial stages of tumor formation, and the stroma may also contribute to risk factors determining tumor formation. Therefore, aspects of stromal biology are well-suited to be a focus for studies of patient outcome, where statistical differences in survival among patients provide evidence as to whether that stromal component is a signpost for tumor progression. In this review we summarize the latest research done where breast cancer patient survival was correlated with aspects of stromal biology, which have been put into four categories: reorganization of the extracellular matrix (ECM) to promote invasion, changes in the expression of stromal cell types, changes in stromal gene expression, and changes in cell biology signaling cascades to and from the stroma.     

Protein kinases of PKD family as a potential object of translational research in oncology

Recent scientific research demonstrates that protein kinases of PKD family affect biological features of normal and malignant cells. Differential expression of PKD genes was found in tumors of different histogenesis. These protein kinases could be activated by growth factors, antigen stimulation, and oxidative stress, the processes that usually can be observed during tumor progression. PKD regulate cell-cell contacts by affecting cell adhesion. PKD are involved in the regulation of cell proliferation and apoptosis, and also participate in epigenetic regulation of gene expression. That is why studies of differential expression and activity of PKD1, PKD2 and PKD3 in the context of tumor spreading and prognosis could be the perspective subject of translational research in oncology. This will contribute to the development of new approaches to differential diagnostics of tumor and target therapy, and also reveal prognostic factors for the prediction of clinical outcome.     

Correlation of codon biases and potential secondary structures with mRNA translation efficiency in unicellular organisms

Gene expression is known to correlate with degree of codon bias in many unicellular organisms. However, such correlation is absent in some organisms. Recently we demonstrated that inverted complementary repeats within coding DNA sequence must be considered for proper estimation of translation efficiency, since they may form secondary structures that obstruct ribosome movement. We have developed a program for estimation of potential coding DNA sequence expression in defined unicellular organism using its genome sequence. The program computes elongation efficiency index. Computation is based on estimation of coding DNA sequence elongation efficiency, taking into account three key factors: codon bias, average number of inverted complementary repeats, and free energy of potential stem-loop structures formed by the repeats. The influence of these factors on translation is numerically estimated. An optimal proportion of these factors is computed for each organism individually. Quantitative translational characteristics of 384 unicellular organisms (351 bacteria, 28 archaea, 5 eukaryota) have been computed using their annotated genomes from NCBI GenBank. Five potential evolutionary strategies of translational optimization have been determined among studied organisms. A considerable difference of preferred translational strategies between Bacteria and Archaea has been revealed. Significant correlations between elongation efficiency index and gene expression levels have been shown for two organisms (S. cerevisiae and H. pylori) using available microarray data. The proposed method allows to estimate numerically the coding DNA sequence translation efficiency and to optimize nucleotide composition of heterologous genes in unicellular organisms. Availability: http://www.mgs.bionet.nsc.ru/mgs/programs/eei-calculator/.     

Integration of clinical and gene expression data has a synergetic effect on predicting breast cancer outcome

Breast cancer outcome can be predicted using models derived from gene expression data or clinical data. Only a few studies have created a single prediction model using both gene expression and clinical data. These studies often remain inconclusive regarding an obtained improvement in prediction performance. We rigorously compare three different integration strategies (early, intermediate, and late integration) as well as classifiers employing no integration (only one data type) using five classifiers of varying complexity. We perform our analysis on a set of 295 breast cancer samples, for which gene expression data and an extensive set of clinical parameters are available as well as four breast cancer datasets containing 521 samples that we used as independent validation.mOn the 295 samples, a nearest mean classifier employing a logical OR operation (late integration) on clinical and expression classifiers significantly outperforms all other classifiers. Moreover, regardless of the integration strategy, the nearest mean classifier achieves the best performance. All five classifiers achieve their best performance when integrating clinical and expression data. Repeating the experiments using the 521 samples from the four independent validation datasets also indicated a significant performance improvement when integrating clinical and gene expression data. Whether integration also improves performances on other datasets (e.g. other tumor types) has not been investigated, but seems worthwhile pursuing. Our work suggests that future models for predicting breast cancer outcome should exploit both data types by employing a late OR or intermediate integration strategy based on nearest mean classifiers.     

Sex differences in mood disorders: perspectives from humans and rodent models

Mood disorders are devastating, often chronic illnesses characterized by low mood, poor affect, and anhedonia. Notably, mood disorders are approximately twice as prevalent in women compared to men. If sex differences in mood are due to underlying biological sex differences, a better understanding of the biology is warranted to develop better treatment or even prevention of these debilitating disorders. In this review, our goals are to: 1) summarize the literature related to mood disorders with respect to sex differences in prevalence, 2) introduce the corticolimbic brain network of mood regulation, 3) discuss strategies and challenges of modeling mood disorders in mice, 4) discuss mechanisms underlying sex differences and how these can be tested in mice, and 5) discuss how our group and others have used a translational approach to investigate mechanisms underlying sex differences in mood disorders in humans and mice.     

Proteomics in prostate cancer research

The incidence of early prostate cancer (PCa) among middle-aged men has increased rapidly. For many of these men, curatively intended treatment does more harm than good. Established prognostic factors are tumor stage and grade. As a result of earlier detection a majority of patients now have nonpalpable tumors (T1c) of intermediate grade (Gleason score 6). Prostate specific antigen in serum in such cases is generally at a low level and not a reliable predictor of prognosis. Altogether there is an urgent need for adjunctive prognostic indicators. In the search for relevant tumor markers for improved patient selection an exploration of the proteome (the human proteins) could be fruitful. This paper critically reviews the use of 2-dimensional gel electrophoresis (2-DE) for proteome research. Additional steps such as image analysis and mass spectrometry are described. Techniques based on non-2-DE platforms: surface-enhanced laser desorption/ionization (SELDI), isotope coded affinity tags (ICAT) and array-based technologies are also summarized. Although labor-intensive and time-consuming, 2-DE is presently the most powerful method for analysis of cellular protein phenotype and may potentially reveal gene regulations that cannot be detected on a genetic level.     

Developments in the scientific and clinical understanding of the spondyloarthritides

Major advances have been achieved over the last 10 years both in the clinical and scientific understanding of the spondyloarthritides (SpA), which can be separated in predominantly axial and predominantly peripheral SpA. The clinical progress includes the development of classification criteria, strategies for early diagnosis, definition of outcome criteria for clinical studies, and the conduction of a series of clinical studies with a focus on tumor necrosis factor (TNF) blockers. The proven high efficacy of TNF blocker treatment has meant a breakthrough for SpA patients, who until recently had only quite limited treatment options. More and more data have accumulated over recent years in regard to long-term efficacy and safety, prediction of response, and the relevance of extrarheumatic manifestations such as uveitis, psoriasis, and inflammatory bowel disease for treatment decisions with TNF blockers. A better understanding of the interaction of the immune system and inflammation with bone degradation/new bone formation is crucial for the development of optimal treatment strategies to prevent structural damage. Recent results from genetic studies could show that, besides HLA-B27, the interleukin-23 receptor and the ARTS1 enzyme are associated with ankylosing spondylitis. Only when the exact pathogenesis is clarified will a curative treatment be possible.     

A Modified Heterotopic Swine Hind Limb Transplant Model for Translational Vascularized Composite Allotransplantation (VCA) Research

Vascularized Composite Allotransplantation (VCA) such as hand and face transplants represent a viable treatment option for complex musculoskeletal trauma and devastating tissue loss. Despite favorable and highly encouraging early and intermediate functional outcomes, rejection of the highly immunogenic skin component of a VCA and potential adverse effects of chronic multi-drug immunosuppression continue to hamper widespread clinical application of VCA. Therefore, research in this novel field needs to focus on translational studies related to unique immunologic features of VCA and to develop novel immunomodulatory strategies for immunomodulation and tolerance induction following VCA without the need for long term immunosuppression.This article describes a reliable and reproducible translational large animal model of VCA that is comprised of an osteomyocutaneous flap in a MHC-defined swine heterotopic hind limb allotransplantation. Briefly, a well-vascularized skin paddle is identified in the anteromedial thigh region using near infrared laser angiography. The underlying muscles, knee joint, distal femur, and proximal tibia are harvested on a femoral vascular pedicle. This allograft can be considered both a VCA and a vascularized bone marrow transplant with its unique immune privileged features. The graft is transplanted to a subcutaneous abdominal pocket in the recipient animal with a skin component exteriorized to the dorsolateral region for immune monitoring.Three surgical teams work simultaneously in a well-coordinated manner to reduce anesthesia and ischemia times, thereby improving efficiency of this model and reducing potential confounders in experimental protocols. This model serves as the groundwork for future therapeutic strategies aimed at reducing and potentially eliminating the need for chronic multi-drug immunosuppression in VCA.     

Development of structural organization of protein-synthesizing machinery from prokaryotes to eukaryotes

Though the mechanisms of protein biosynthesis are similar in the cells of prokaryotes and eukaryotes, the eukaryotic translational machinery in the cell is arranged more intricately. One of the most striking characteristic features of the eukaryotic translational machinery is that the eukaryotic proteins involved in the translational process, such as initiation factors, elongation factors and aminoacyl-tRNA synthetases, in contrast to their prokaryotic analogs, possess a non-specific affinity for RNA. Due to the RNA-binding ability, these eukaryotic proteins can be compartmentalized on polyribosomes. In addition to the proteins of the translational apparatus, several other eukaryotic RNA-binding proteins can be also compartmentalized on polyribosomes; these proteins include glycolytic enzymes, steroid hormone receptors and intermediate filament proteins. Thus, the eukaryotic polyribosome is an element of the cytoplasmic labile structure on which various proteins can be compartmentalized and, consequently, different biochemical pathways can be integrated.