Application of Weighted Gene Co-expression Network Analysis for Data from Paired Design

Investigating how genes jointly affect complex human diseases is important, yet challenging. The network approach (e.g., weighted gene co-expression network analysis (WGCNA)) is a powerful tool. However, genomic data usually contain substantial batch effects, which could mask true genomic signals. Paired design is a powerful tool that can reduce batch effects. However, it is currently unclear how to appropriately apply WGCNA to genomic data from paired design. In this paper, we modified the current WGCNA pipeline to analyse high-throughput genomic data from paired design. We illustrated the modified WGCNA pipeline by analysing the miRNA dataset provided by Shiah et al. (2014), which contains forty oral squamous cell carcinoma (OSCC) specimens and their matched non-tumourous epithelial counterparts. OSCC is the sixth most common cancer worldwide. The modified WGCNA pipeline identified two sets of novel miRNAs associated with OSCC, in addition to the existing miRNAs reported by Shiah et al. (2014). Thus, this work will be of great interest to readers of various scientific disciplines, in particular, genetic and genomic scientists as well as medical scientists working on cancer

New Prognostic and Predictive Markers in Cancer Progression

Biomarkers are of critical medical importance for oncologists, allowing them to predict and detect disease and to determine the best course of action for cancer patient care. Prognostic markers are used to evaluate a patient’s outcome and cancer recurrence probability after initial interventions such as surgery or drug treatments and, hence, to select follow-up and further treatment strategies. On the other hand, predictive markers are increasingly being used to evaluate the probability of benefit from clinical intervention(s), driving personalized medicine. Evolving technologies and the increasing availability of “multiomics” data are leading to the selection of numerous potential biomarkers, based on DNA, RNA, miRNA, protein, and metabolic alterations within cancer cells or tumor microenvironment, that may be combined with clinical and pathological data to greatly improve the prediction of both cancer progression and therapeutic treatment responses. However, in recent years, few biomarkers have progressed from discovery to become validated tools to be used in clinical practice. This Special Issue comprises eight review articles and five original studies on novel potential prognostic and predictive markers for different cancer types

Bioinformatic interpretation of microRNA role in three phenotypically related genodermatoses

The well-known regulatory function of microRNAs seems to play an important role in disease mechanism. Recent hypotheses have positioned them as a promising option for the study of genetic disorders. In this context, the microRNA profile of three phenotypically related rare genodermatoses, namely Recessive Dystrophic Epidermolysis Bullosa, Kindler Syndrome and Xeroderma Pigmentosum type C, is going to be analyzed taking as a reference healthy controls within the frame of network medicine concepts. Bioinformatics tools have proven to be essential to keep track of the alteration of the dysregulated microRNAs all over the organism. This thesis provides a direct correlation between the real and observable symptoms of the three conditions and the distortion at molecular level caused by pathogenic pathways. From the network analysis and functional enrichment analysis, a small selection of microRNAs and target genes are proposed as potential candidates for further research. Thus, with this project, it becomes evident the need of powerful predictive research tools previous to laboratory validation. In the considerably new field of microRNAs, the design and elaboration of more precise treatments as well as the discovery of biomarkers for early detection prevail among the possible different applications.Ingeniería Biomédic

Nanogenomics and Nanoproteomics Enabling Personalized, Predictive and Preventive Medicine

Since the discovery of the nucleic acid, molecular biology has made tremendous progresses, achieving a lot of results. Despite this, there is still a gap between the classical and traditional medical approach and the molecular world. Inspired by the incredible wealth of data generated by the "omics"-driven techniques and the “high-trouhgput technologies” (HTTs), I have tried to develop a protocol that could reduce the actually extant barrier between the phenomenological medicine and the molecular medicine, facilitating a translational shift from the lab to the patient bedside. I also felt the urgent need to integrate the most important omics sciences, that is to say genomics and proteomics. Nucleic Acid Programmable Protein Arrays (NAPPA) can do this, by utilizing a complex mammalian cell free expression system to produce proteins in situ. In alternative to fluorescent-labeled approaches a new label free method, emerging from the combined utilization of three independent and complementary nanobiotechnological approaches, appears capable to analyze gene and protein function, gene-protein, gene-drug, protein-protein and protein-drug interactions in studies promising for personalized medicine. Quartz Micro Circuit nanogravimetry (QCM), based on frequency and dissipation factor, mass spectrometry (MS) and anodic porous alumina (APA) overcomes indeed the limits of correlated fluorescence detection plagued by the background still present after extensive washes. Work is in progress to further optimize this approach a homogeneous and well defined bacterial cell free expression system able to realize the ambitious objective to quantify the regulatory gene and protein networks in humans. Implications for personalized medicine of the above label free protein array using different test genes and proteins are reported in this PhD thesis

Recent Developments in Cancer Systems Biology

This ebook includes original research articles and reviews to update readers on the state of the art systems approach to not only discover novel diagnostic and prognostic biomarkers for several cancer types, but also evaluate methodologies to map out important genomic signatures. In addition, therapeutic targets and drug repurposing have been emphasized for a variety of cancer types. In particular, new and established researchers who desire to learn about cancer systems biology and why it is possibly the leading front to a personalized medicine approach will enjoy reading this book

MicroRNA and Cancer

MicroRNAs (miRs) are small noncoding RNAs that function as post-transcriptional regulators of gene expression and have important roles in almost all biological pathways. Deregulated miR expression has been detected in numerous cancers, where miRs act as both oncogene and tumor suppressors. Due to their important roles in tumorigenesis, miRs have been investigated as prognostic and diagnostic biomarkers and as useful targets for therapeutic intervention. From a therapeutic point of view, two modalities can serve to rectify gene networks in cancer cells. For oncomiRs, a rational means is downregulation through antagomirs. Moreover, observations of the pathological reductions in tumor-suppressive miRs have inspired the concept of “miR replacement therapy” to enhance the amount of these miRs, thereby restoring them to normal levels. However, the clinical applicability of miR-based therapies is severely limited by the lack of effective delivery systems. Therefore, to understand the role of this new class of regulators, we need to identify the mRNA targets regulated by individual miRs as well as to develop specific, efficient, and safe delivery systems for therapeutic miRs

Role of miRNAs in Cancer

MicroRNAs are the best representatives of the non-coding part of the genome and their functions are mostly linked to their target genes. During the process of carcinogenesis, both dysregulation of microRNAs and their target genes can explain the development of the disease. However, most of the target genes of microRNAs have not yet been elucidated. In this book, we add new information related to the functions of microRNAs in various tumors and their associated targetome

Prognostic biomarkers in uveal melanoma: the status quo, recent advances and future directions

Uveal melanoma (UM) is the most common malignant intraocular tumour in the adult population. It is a rare cancer with an incidence of nearly five cases per million inhabitants per year, which develops from the uncontrolled proliferation of melanocytes in the choroid (≈90%), ciliary body (≈6%) or iris (≈4%). Patients initially present either with symptoms like blurred vision or photopsia, or without symptoms, with the tumour being detected in routine eye exams. Over the course of the disease, metastases, which are initially dormant, develop in nearly 50% of patients, preferentially in the liver. Despite decades of intensive research, the only approach proven to mildly control disease spread are early treatments directed to ablate liver metastases, such as surgical excision or chemoembolization. However, most patients have a limited life expectancy once metastases are detected, since there are limited therapeutic approaches for the metastatic disease, including immunotherapy, which unlike in cutaneous melanoma, has been mostly ineffective for UM patients. Therefore, in order to offer the best care possible to these patients, there is an urgent need to find robust models that can accurately predict the prognosis of UM, as well as therapeutic strategies that effectively block and/or limit the spread of the metastatic disease. Here, we initially summarized the current knowledge about UM by compiling the most relevant epidemiological, clinical, pathological and molecular data. Then, we revisited the most important prognostic factors currently used for the evaluation and follow-up of primary UM cases. Afterwards, we addressed emerging prognostic biomarkers in UM, by comprehensively reviewing gene signatures, immunohistochemistry-based markers and proteomic markers resulting from research studies conducted over the past three years. Finally, we discussed the current hurdles in the field and anticipated the future challenges and novel avenues of research in UM.N.J.L. would like to thank all members of the Laboratory of Clinical and Experi-mental Pathology (LPCE), Centre Hospitalier Universitaire de Nice, Nice, France; and all members of the Anatomic Pathology Service, Pathology Department, Centro Hospitalar e Universitario do Porto,Porto, Portugal, especially to JoseRamon Vizcaino (Head of Service), Joana Raposo Alves (Advisor ofPathology Training), Andre Coelho, David Tente and Francisca Emanuel Costa for their continuous support and help in the developmen