Biomarkers From Discovery to Clinical Application: In Silico Pre-Clinical Validation Approach in the Face of Lung Cancer.

Background: Clinical biomarkers, allow better classification of patients according to their disease risk, prognosis, and/or response to treatment. Although affordable omics-based approaches have paved the way for quicker identification of putative biomarkers, validation of biomarkers is necessary for translation of discoveries into clinical application.

Objective: Accordingly, in this study, we emphasize the potential of in silico approaches and have proposed and applied 3 novel sequential in silico pre-clinical validation steps to better identify the biomarkers that are truly desirable for clinical investment.

Exploring COVID-19 Pandemic Disparities with Transcriptomic Meta-analysis from the Perspective of Personalized Medicine.

Infection with SARS-CoV2, which is responsible for COVID-19, can lead to differences in disease development, severity and mortality rates depending on gender, age or the presence of certain diseases. Considering that existing studies ignore these differences, this study aims to uncover potential differences attributable to gender, age and source of sampling as well as viral load using bioinformatics and multi-omics approaches. Differential gene expression analyses were used to analyse the phenotypic differences between SARS-CoV-2 patients and controls at the mRNA level.

SVM-DO: identification of tumor-discriminating mRNA signatures via support vector machines supported by Disease Ontology.

Background/aim: The complicated nature of tumor formation makes it difficult to identify discriminatory genes. Recently, transcriptome-based supervised classification methods using support vector machines (SVMs) have become popular in this field. However, the inclusion of less significant variables in the construction of classification models can lead to misclassification.

Tumor Mutation Burden as a Cornerstone in Precision Oncology Landscapes: Effect of Panel Size and Uncertainty in Cutoffs.

Tumor mutation burden (TMB) has profound implications for personalized cancer therapy, particularly immunotherapy. However, the size of the panel and the cutoff values for an accurate determination of TMB are still controversial. In this study, a pan-cancer analysis was performed on 22 cancer types from The Cancer Genome Atlas.

Pharmacomicrobiomics-Guided Precision Oncology: A New Frontier of P4 (Predictive, Personalized, Preventive, and Participatory) Medicine and Microbiome-Based Therapeutics.

Pharmacomicrobiomics is a rapidly developing field that promises to make significant contributions to predictive, personalized, preventive, and participatory (P4) medicine. This is becoming evident particularly in the field of precision (P4) oncology by taking seriously the crucial role microbiome plays in health and disease. Several studies have already shown that clinicians can harness insights from the microbiome to better predict treatment response, reduce side effects, and improve overall outcomes for cancer patients.

Differential co-expression network analysis elucidated genes associated with sensitivity to farnesyltransferase inhibitor and prognosis of acute myeloid leukemia.

Acute myeloid leukemia (AML) is a heterogeneous disease and the most common form of acute leukemia with a poor prognosis. Due to its complexity, the disease requires the identification of biomarkers for reliable prognosis. To identify potential disease genes that regulate patient prognosis, we used differential co-expression network analysis and transcriptomics data from relapsed, refractory, and previously untreated AML patients based on their response to treatment in the present study.

A Differential Transcriptional Regulome Approach to Unpack Cancer Biology: Insights on Renal Cell Carcinoma Subtypes.

Cancer research calls for new approaches that account for the regulatory complexities of biology. We present, in this study, the differential transcriptional regulome (DIFFREG) approach for the identification and prioritization of key transcriptional regulators and apply it to the case of renal cell carcinoma (RCC) biology. Of note, RCC has a poor prognosis and the biomarker and drug discovery studies to date have tended to focus on gene expression independent from mutations and/or post-translational modifications.

Toward Precision Oncology in Glioblastoma with a Personalized Cancer Genome Reporting Tool and Genetic Changes Identified by Whole Exome Sequencing.

Precision/personalized medicine in oncology has two key pillars: molecular profiling of the tumors and personalized reporting of the results in ways that are clinically contextualized and triangulated. Moreover, neurosurgery as a field stands to benefit from precision/personalized medicine and new tools for reporting of the molecular findings. In this context, glioblastoma (GBM) is a highly aggressive brain tumor with limited treatment options and poor prognosis.

Three candidate anticancer drugs were repositioned by integrative analysis of the transcriptomes of species with different regenerative abilities after injury.

Regeneration is a homeostatic process that involves the restoration of cells and body parts. Most of the molecular mechanisms and signalling pathways involved in wound healing, such as proliferation, have also been associated with cancer cell growth, suggesting that cancer is an over/unhealed wound. In this study, we examined differentially expressed genes in spinal cord samples from regenerative organisms (axolotl and zebrafish) and nonregenerative organisms (mouse and rat) compared to intact control spinal cord samples using publicly available transcriptomics data and bioinformatics analyses.

The Versatility of Plectin in Cancer: A Pan-Cancer Analysis on Potential Diagnostic and Prognostic Impacts of Plectin Isoforms.

Plectin, encoded by , is a cytoskeletal and scaffold protein with a number of unique isoforms that act on various cellular functions such as cell adhesion, signal transduction, cancer cell invasion, and migration. While plectin has been shown to display high expression and mislocalization in tumor cells, our knowledge of the biological significance of plectin and its isoforms in tumorigenesis remain limited. In this study, we first performed pathway enrichment analysis to identify cancer hallmark proteins associated with plectin.

HPV16 status predicts potential protein biomarkers and therapeutics in head and neck squamous cell carcinoma.

Human papillomavirus (HPV) infection, especially HPV16, is one of the causative factors for the development of head and neck squamous cell (HNSC) carcinoma. HPV-positive and HPV-negative HNSC patients differ significantly in their molecular profiles and clinical features, so they should be evaluated differently depending on their HPV status. Given the tremendous variation in HNSC cancers depending on HPV, our goal in this study was to present biomarkers and treatment options tailored to the patient's HPV status.

Potential Early Markers for Breast Cancer: A Proteomic Approach Comparing Saliva and Serum Samples in a Pilot Study.

Breast cancer is the second leading cause of death for women in the United States, and early detection could offer patients the opportunity to receive early intervention. The current methods of diagnosis rely on mammograms and have relatively high rates of false positivity, causing anxiety in patients. We sought to identify protein markers in saliva and serum for early detection of breast cancer.

A Transcriptomic and Reverse-Engineering Strategy Reveals Molecular Signatures of Arachidonic Acid Metabolism in 12 Cancers.

Cancer and arachidonic acid (AA) have important linkages. For example, AA metabolites regulate several critical biological functions associated with carcinogenesis: angiogenesis, apoptosis, and cancer invasion. However, little is known about the comparative changes in metabolite expression of the arachidonic acid pathway (AAP) in carcinogenesis.

Drug repositioning host-pathogen protein-protein interactions for the treatment of cervical cancer.

Introduction: Integrating interaction data with biological knowledge can be a critical approach for drug development or drug repurposing. In this context, host-pathogen-protein-protein interaction (HP-PPI) networks are useful instrument to uncover the phenomena underlying therapeutic effects in infectious diseases, including cervical cancer, which is almost exclusively due to human papillomavirus (HPV) infections. Cervical cancer is one of the second leading causes of death, and HPV16 and HPV18 are the most common subtypes worldwide.

Estimates and Forecasts on the Burden of Prediabetes and Diabetes in Adult and Elderly Population in Turkiye.

Aims: Diabetes mellitus is a chronic disease that limits the quality and duration of life. We aimed to estimate the impact of demographic change on the burden of prediabetes and diabetes between 2010 and 2021, and the projections to 2030 and 2045 in Turkiye.

Materials And Methods: Prediabetes and diabetes estimates were calculated by direct standardization method using age- and sex-specific prevalence data from the previous 'Turkish Epidemiology Survey of Diabetes, Hypertension, Obesity and Endocrine Disease' (TURDEP-II) as reference.

A Pan-Cancer Atlas of Differentially Interacting Hallmarks of Cancer Proteins.

Cancer hallmark genes and proteins orchestrate and drive carcinogenesis to a large extent, therefore, it is important to study these features in different cancer types to understand the process of tumorigenesis and discover measurable indicators. We performed a pan-cancer analysis to map differentially interacting hallmarks of cancer proteins (DIHCP). The TCGA transcriptome data associated with 12 common cancers were analyzed and the differential interactome algorithm was applied to determine DIHCPs and DIHCP-centric modules (i.

Epigenomic and transcriptomic landscaping unraveled candidate repositioned therapeutics for non-functioning pituitary neuroendocrine tumors.

Purpose: Non-functioning pituitary neuroendocrine tumors are challengingly diagnosed tumors in the clinic. Transsphenoidal surgery remains the first-line treatment. Despite the development of state-of-the-art techniques, no drug therapy is currently approved for the treatment.

Differential Interactome Based Drug Repositioning Unraveled Abacavir, Exemestane, Nortriptyline Hydrochloride, and Tolcapone as Potential Therapeutics for Colorectal Cancers.

There is a critical requirement for alternative strategies to provide the better treatment in colorectal cancer (CRC). Hence, our goal was to propose novel biomarkers as well as drug candidates for its treatment through differential interactome based drug repositioning. Differentially interacting proteins and their modules were identified, and their prognostic power were estimated through survival analyses.

Human oncogenic viruses: an overview of protein biomarkers in viral cancers and their potential use in clinics.

Introduction: Although the idea that carcinogenesis might be caused by viruses was first voiced about 100 years ago, today's data disappointingly show that we have not made much progress in preventing and/or treating viral cancers in a century. According to recent studies, infections are responsible for approximately 13% of cancer development in the world. Today, it is accepted and proven by many authorities that Epstein-Barr virus (EBV), Hepatitis B virus (HBV), Hepatitis C virus (HCV), Human Herpesvirus 8 (HHV8), Human T-cell Lymphotropic virus 1 (HTLV1) and highly oncogenic Human Papillomaviruses (HPVs) cause or/and contribute to cancer development in humans.

Integrative Analysis of Motor Neuron and Microglial Transcriptomes from SOD1 Mice Models Uncover Potential Drug Treatments for ALS.

Amyotrophic lateral sclerosis (ALS) is a fatal disease of motor neurons that mainly affects the motor cortex, brainstem, and spinal cord. Under disease conditions, microglia could possess two distinct profiles, M1 (toxic) and M2 (protective), with the M2 profile observed at disease onset. SOD1 (superoxide dismutase 1) gene mutations account for up to 20% of familial ALS cases.