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Nephritis and osteoporosis are debilitating medical conditions that significantly impact human health and reduce quality of life. To develop potential therapeutic strategies for these disorders necessitates understanding the genetic and molecular mechanisms. Here, we employed bioinformatics techniques purposed to find key genes and associated pathways responsible for nephritis-osteoporosis comorbidity. Six microarray datasets of systemic lupus erythematosus (SLE) and osteoporosis were retrieved from the Gene Expression Omnibus (GEO) database. Post normalization of data sets LIMMA package was utilized for differential expression analysis, among the datasets 44 differentially expressed genes (DEGs) were identified. The identified 44 genes were further analyzed for gene ontology (GO) where it was found that these genes are involved in defense response, organism interactions, and response to external stimuli. In predicting the molecular function, they were involved in several biological processes including binding to lipopolysaccharides and having peptidase and hydrolase activities. Firstly, the identified genes were primarily associated with certain granules such as specific granules and secretory granules in the aspect of cellular components. Enrichment analysis pointed out the potential pathways linked to the immune system, neutrophil degranulation, innate immunity, and immune response to tuberculosis. To examine interactions among DEGs, a complex protein-protein interaction (PPI) network was built, resulting in the identification of seven hub genes, CXCL8, ELANE, LCN2, MMP8, IFIT1, MX1, and ISG15. The study suggests that these elucidated hub genes might have high potential to be exploited as promising biomarkers and therapeutic targets in nephritis-osteoporosis. Taken together, this study provided deeper insights into the genetic and molecular basis for the comorbidity of nephritis and osteoporosis., Competing Interests: Competing interests None., (Copyright © 2024 The International Society for Clinical Densitometry. Published by Elsevier Inc. All rights reserved.)

Purpose: To perform an extensive exploratory analysis to build a deeper insight into clinically relevant molecular biomarkers in Papillary, Follicular, and Anaplastic thyroid carcinomas (PTC, FTC, ATC)., Methods: Thirteen Thyroid Cancer (THCA) datasets incorporating PTC, FTC, and ATC were derived from the Gene Expression Omnibus. Genes differentially expressed (DEGs) between THCA and normal were identified and subjected to GO and KEGG analyses. Multiple topological properties were harnessed and protein-protein interaction (PPI) networks were constructed to identify the hub genes followed by survival analysis and validation., Results: There were 70, 87, and 377 DEGs, and 23, 27, and 53 hub genes for PTC, FTC, and ATC samples, respectively. Survival analysis detected 39 overall and 49 relapse-free survival-relevant hub genes. Six hub genes, BCL2, FN1, ITPR1, LYVE1, NTRK2, TBC1D4, were found common to more than one THCA type. The most significant hub genes found in the study were: BCL2, CD44, DCN, FN1, IRS1, ITPR1, MFAP4, MKI67, NTRK2, PCLO, TGFA. The most enriched and significant GO terms were Melanocyte differentiation for PTC, Extracellular region for FTC, and Extracellular exosome for ATC. Prostate cancer for PTC was the most significantly enriched KEGG pathway. The results were validated using TCGA data., Conclusions: The findings unravel potential biomarkers and therapeutic targets of thyroid carcinomas., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Circular RNAs (circRNAs) play a crucial regulatory role in malignant tumor metastasis. This study focused on the role of bone metastasis-related circRBMS3 in breast cancer. Two circRNA microarray datasets were obtained from the GEO database and overlapped bone metastasis-related circRNAs in breast cancer. CircRBMS3 expression was validated in bone metastasis tissues by RT-qPCR. Cellular CCK-8 assay and Transwell assays were performed to measure the effect of circRBMS3 in breast cancer cells. Bioinformatic analyses were performed to identify the binding miRNAs of circRBMS3 and downstream mRNAs. Online database STRING and Cytoscape software were used to analyze PPI interaction and conduct the ceRNA network. GEO database analysis showed that circRBMS3 was one of the upregulated circRNAs among all the metastatic cells. CircRBMS3 was increased in bone metastasis breast cancer tissues compared to non-bone metastasis tissues and associated with poor 3-year overall survival. CircRBMS3 knockdown repressed breast cancer cell proliferation, migration, and invasion, as well as bone resorption gene and osteoclast phenotype gene expression. CircRBMS3 was found to bind withmiR-654-3p. Subsequently, downstream mRNAs were predicted, and the circRBMS3 miR-654-3p-mRNA network was established. In conclusion, circRBMS3 expression was upregulated in bone metastasis breast cancer and might be a potential prognostic marker for patients. Silencing circRBMS3 restrained breast cancer cell proliferation, migration, and invasion, as well as associated with bone metastasis. The circRBMS3-miR-654-3p-mRNAs network elucidated potential mechanisms underlying bone metastasis in breast cancer., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Cytochrome c oxidase assembly factor 1 (COA1), a mitochondrial respiratory chain complex assembly factor protein of inner mitochondrial membrane (IMM), is involved in translating many mitochondrial components and assembling nuclear-encoded components within mitochondria. Given the lack of extensive research on COA1 in cancer, this study undertakes a comprehensive pan-cancer analysis of COA1, which is overexpressed across various cancer types, shedding light on its multifaceted role in tumorigenesis, prognosis, and tumor microenvironment (TME) modulation. Leveraging bioinformatics tools and public databases, we elucidated its potential as a diagnostic cancer biomarker as well as a target for novel anti-cancer therapeutics. Gene expression analysis using "TIMER2.0", "UALCAN" and "GEPIA2" platforms, supported by protein expression data, revealed a significant correlation between COA1 upregulation and poor prognosis in Kaplan-Meir analysis, underscoring its clinical relevance. Additionally, genetic mutation analysis of COA1 with the help of "cBioPortal" warrants further exploration into its functional significance. Moreover, our investigation of the tumor microenvironment unveiled the interplay of COA1 with fibroblast and T cell infiltration implicating the role of COA1 in the tumor immune microenvironment. Furthermore, COA1-related gene enrichment study in "GeneMANIA" and pathway cross-talk analysis with Gene Ontology (GO) gene sets established comprehensive clarifications about the molecular pathways and protein networks associated with COA1 deregulation. Overall, this study lays a sturdy foundation to support future research endeavors targeting COA1, unraveling the molecular mechanisms underlying COA1 deregulation, and exploring its therapeutic potential in cancer., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Multiple sclerosis (MS) is a leading cause of chronic neurological dysfunction in young to middle-aged adults, affecting approximately 2.5 million people worldwide. It is characterized by inflammation, multifocal demyelination, axonal loss, and white and gray matter gliosis. Autophagy is a highly conserved protein degradation pathway. Polymorphisms in autophagy-related genes have been implicated in a variety of autoimmune diseases, including systemic lupus erythematosus, rheumatoid arthritis, psoriasis and MS. However, the significance of autophagy in MS remains to be elucidated. This paper aims to explore the potential role of autophagy-related genes in MS diseases by using bioinformatics combined with machine learning methods. Finally, we obtained 9 autophagy genes with the highest correlation with MS, and further changes in these autophagy genes were verified in the experimental autoimmune encephalomyelitis (EAE) model and oligodendrocyte precursor cells (OPCs) engulfed myelin debris (MD). Combined with bioinformatic analysis and experimental data, Becn1 showed obvious expression abnormalities suggesting that this gene has vital functions in autophagy and MD engulfed by OPCs. This work will be of great significance for the further exploration of autophagy-related genes in demyelinating diseases., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Salmonella subsp. enterica (SE) presents a significant global health challenge in both developed and developing countries. Current SE vaccines have limitations, targeting specific strains and demonstrating moderate efficacy in adults, while also being unsuitable for young children and often unaffordable in regions with lower income levels where the disease is prevalent. To address these challenges, this study employed a computational approach integrating core proteomics, subtractive proteomics, and immunoinformatics to develop a universal SE vaccine and identify potential drug targets. Analysis of the core proteome of 185 SE strains revealed 1964 conserved proteins. Subtractive proteomics identified 9 proteins as potential vaccine candidates and 41 as novel drug targets. Using reverse vaccinology-based immunoinformatics, four multi-epitope-based subunit vaccine constructs (MESVCs) were designed, aiming to stimulate cytotoxic T lymphocyte, helper T lymphocyte, and linear B lymphocyte responses. These constructs underwent comprehensive evaluations for antigenicity, immunogenicity, toxicity, hydropathicity, and physicochemical properties. Predictive modeling, refinement, and validation were conducted to determine the secondary and tertiary structures of the SE-MESVCs, followed by docking studies with MHC-I, MHC-II, and TLR4 receptors. Molecular docking assessments showed favorable binding with all three receptors, with SE-MESVC-4 exhibiting the most promising binding energy. Molecular dynamics simulations confirmed the binding affinity and stability of SE-MESVC-4 with the TLR4/MD2 complex. Additionally, codon optimization and in silico cloning verified the efficient translation and successful expression of SE-MESVC-4 in Escherichia coli (E. coli) str. K12. Subsequent in silico immune simulation evaluated the efficacy of SE-MESVC-4 in triggering an effective immune response. These results suggest that SE-MESVC-4 may induce both humoral and cellular immune responses, making it a potential candidate for an effective SE vaccine. However, further experimental investigations are necessary to validate the immunogenicity and efficacy of SE-MESVC-4, bringing us closer to effectively combating SE infections., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

The three-dimensional structure of proteins is traditionally organized into hierarchical levels, specifically secondary structures and domains. However, different studies suggest the existence of intermediate levels, such as Protein Units (PUs), which provide a refined understanding of protein architecture. PUs, characterized by their compactness and independence, serve as an intermediate organizational level, bridging the gap between secondary structures and domains. This new view not only enhances our comprehension of protein structure, folding, and evolutionary mechanisms but also provides a robust methodology for identifying and categorizing protein domains. Based on the concept of PUs, alternative structural partitioning solutions can be proposed that address the structural ambiguity of proteins, leading to more meaningful domain identification., (© 2025. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

The purpose of the research was to evaluate the diagnostic performance of microRNA-299-3p (miR-299-3p) in patients with coronary artery disease (CAD). The relative abundance of miR-299-3p in patients with CAD was verified by quantitative real time polymerase chain reaction (qRT-PCR) assay. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were used for analysis, and target genes were predicted and enriched by DAVID software. The protein-protein interaction (PPI) network was drawn by STRING database. Receiver operating characteristic (ROC) was adopted to appraise the diagnostic value of miR-299-3p in CAD. Bioinformatics analysis showed that the GO function of miR-299-3p target genes of miR-299-3p mainly focuses on specific granular membrane, regulation of apoptotic signaling pathway, growth factor binding and so on. KEGG analysis showed that the most abundant pathways involve fluid shear stress and atherosclerosis, as well as Notch signaling pathways. PPI network showed the seven predictive genes encoding the proteins play pivotal roles in maintaining the stability and interaction of the network, especially matrix metallopeptidase 2 (MMP2) and intercellular cell adhesion molecule-1 (ICAM1). Compared with the control group, serum miR-299-3p in the CAD group was distinctly up-regulated via qRT-PCR (p < 0.001). ROC analysis showed that miR-299-3p was an important index for detecting CAD patients and major adverse cardiovascular events (MACE) patients with an AUC of 0.931 and 0.758, respectively. MiR-299-3p is involved in the development of CAD, and might become a potential biomarker for monitoring CAD., Competing Interests: Compliance with Ethical Standards Conflict of Interest The authors declare no competing interests. Consent to Participate The guardians of each subject have provided written informed consents before the research. Ethical Approval The study was supported by the Ethics Committees of The Central Hospital of Wuhan., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

The pharmacological mechanism of Phellodendri Chinensis cortex (PCC) against diseases, especially bladder cancer (BC), has never been reported systematically. This study was designed to explore potential mechanism of PCC in treatment of BC. First, we used network pharmacology to discover the potential mechanism of Phellodendri Chinensis cortex and phellodendrine against bladder cancer. Then, we used bioinformatics analysis to verify the correlation between gene expression analysis, survival analysis and common targets. Finally, molecular docking was used to calculate the binding energies of phellodendrine and common targets.A total of 264 targets for PCC were predicted, and 391 BC-related targets were obtained from 4 databases. There were 54 potential targets, 315 biological processes, and 120 signaling pathways involved for PCC against BC. The CDKN2A expression increased and the ESR1, JUN, IL6, AR, and PTGS2 levels decreased in BC according to Gene Expression Profiling Interactive Analysis version 2. The high expression of JUN, MYC, EGFR, and EGF and low expression of VEGFA and PPARG were associated with short overall survival (OS). The high expression of AKT1, EGFR, and EGF and low expression of IL1β were associated with poor disease-free survival (DFS). The search of the intersection of phellodendrine and BC targets yielded 11 common targets, 50 biological processes, and 13 signaling pathways involved. High AURKA and FASN and low ESR1, JUN, ABCB1, and PTGS1 were expressed in BC. The high expression of FASN, ABCC1, PTGS1, JUN, and PIK3CA was associated with short OS, the high expression of PIK3CA and ABCC1 was associated with poor DFS prognosis. Phellodendrine showed a better binding affinity for PTGS2 protein with a docking score of -7.183 and a MM-GBSA result of -46.47 kcal/mol. This study revealed potential mechanism of PCC and phellodendrine against BC through network pharmacology and bioinformatics., Competing Interests: Compliance with ethical standards Conflict of interest The authors declare no competing interests., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

The emergence of conflicting reports on the natural occurrence of Alzheimer's disease (AD) in non-human primates has prompted research on the comparison of the role of diet-associated changes in gene expression between humans and non-human primates. This article analyzes the effects of different human and chimpanzee diets and their link with apolipoproteins, lipid, and iron (Fe) metabolism, starting from available data, to find out any gap in the existing knowledge. By using a system biology approach, we have re-analyzed the liver and brain RNA seq data of mice fed with either human or chimpanzee diet for 2 weeks to look for genetic differences that may explain the differences in AD occurrence between those two classes. In liver samples of mice fed with the chimpanzee diet in comparison to the human diet, apolipoprotein A-1, ceruloplasmin, and 10 other genes were upregulated while 21 genes were downregulated. However, brain apolipoprotein E4 gene expression was not changed upon diet. Genetic, structural, and functional differences in apolipoprotein E protein, along with differences in Fe metabolisms and a longer lifespan of humans during evolution may account for the observed disparity., (© 2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Morindone, a natural anthraquinone compound, has been reported to have significant pharmacological properties in different cancers. However, its anticancer effects in colorectal cancer (CRC) and the underlying molecular mechanisms remain obscure. In this study, RNA sequencing was used to assess the differentially expressed genes (DEGs) following morindone treatment in two CRC cell lines, HCT116 and HT29 cells. Functional enrichment analysis of overlapping DEGs revealed that negative regulation of cell development from biological processes and the MAPK signalling pathway were the most significant Gene Ontology terms and Kyoto Encyclopaedia of Genes and Genome pathway, respectively. Seven hub genes were identified among the overlapping genes, including MCM5, MCM6, MCM10, GINS2, POLE2, PRIM1, and WDHD1. All hub genes were found downregulated and involved in DNA replication fork. Among these, GINS2 was identified as the most cancer-dependent gene in both cells with better survival outcomes. Validation was performed on seven hub genes with rt-qPCR, and the results were consistent with the RNA sequencing findings. Collectively, this study provides corroboration of the potential therapeutic benefits and suitable pharmacological targets of morindone in the treatment of CRC., (© 2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Inflammation and immunity play important roles in the pathogenesis of ischemic stroke. This study aimed to explore key regulatory genes in acute ischemic stroke (AIS) and their underlying mechanisms to provide new research targets for the diagnosis and treatment of ischemic stroke. We searched for differentially expressed mRNAs and miRNAs in patients with AIS and healthy populations in GEO databases, constructed a miRNA-mRNA network, and screened key miRNAs using least absolute shrinkage and selection operator regression and the support vector machine-recursive feature elimination model. Correlations between key miRNAs and infiltrating immune cells and inflammatory factors were analyzed using CIBERSORT and immunoassays and verified using clinical experiments. Bioinformatics analysis identified hsa-miR-877-5p as a key regulatory miRNA in AIS that can modulate immune and inflammatory responses. In clinical studies, it was verified by quantitative PCR analysis that the expression of hsa-miR-877-5p in the blood of AIS patients was higher than that of the healthy group. Then, enzyme-linked immunosorbent assay revealed that the expression of IL-23 and TNF-α related to inflammation in AIS patients was higher than that of the healthy. Quantitative PCR further found that the relative mRNA expression of IL-23, CXCR3, and TNF-α in AIS group was higher than that of the healthy group. This study may provide a basis for a more comprehensive understanding of the potential mechanism of the occurrence and development of AIS, and hsa-miR-877-5p and its downstream effectors IL-23, CXCR3, and TNF-α may be potential intervention targets in AIS., (© 2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Mycobacterium tuberculosis (Mtb) is the pathogen that causes tuberculosis and develops resistance to many of the existing drugs. The sole licensed TB vaccine, BCG, is unable to provide a comprehensive defense. So, it is crucial to maintain the immunological response to eliminate tuberculosis. Our previous in silico study reported five uncharacterized proteins as potential vaccine antigens. In this article, we considered the uncharacterized Mtb H37Rv regions of difference (RD-2) Rv1987 protein as a promising vaccine candidate. The vaccine quality of the protein was analyzed using reverse vaccinology and immunoinformatics-based quality-checking parameters followed by an ex vivo preliminary investigation. In silico analysis of Rv1987 protein predicted it as surface localized, secretory, single helix, antigenic, non-allergenic, and non-homologous to the host protein. Immunoinformatics analysis of Rv1987 by CD4 + and CD8 + T-cells via MHC-I and MHC-II binding affinity and presence of B-cell epitope predicted its immunogenicity. The docked complex analysis of the 3D model structure of the protein with immune cell receptor TLR-4 revealed the protein's capability for potential interaction. Furthermore, the target protein-encoded gene Rv1987 was cloned, over-expressed, purified, and analyzed by mass spectrometry (MS) to report the target peptides. The qRT-PCR gene expression analysis shows that it is capable of activating macrophages and significantly increasing the production of a number of key cytokines (TNF-α, IL-1β, and IL-10). Our in-silico analysis and ex vivo preliminary investigations revealed the immunogenic potential of the target protein. These findings suggest that the Rv1987 be undertaken as a potent subunit vaccine antigen and that further animal model immuno-modulation studies would boost the novel TB vaccine discovery and/or BCG vaccine supplement pipeline., (© 2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Spinal cord injury (SCI) is a common clinical problem in orthopedics with a lack of effective treatments and drug targets. In the present study, we performed bioinformatic analysis of SCI datasets GSE464 and GSE45006 in the Gene Expression Omnibus (GEO) public database and experimentally validated CCL2 expression in an animal model of SCI. This was followed by stimulation of PC-12 cells using hydrogen peroxide to construct a cellular model of SCI. CCL2 expression was knocked down using small interfering RNA (si-CCL2), and PI3K signaling pathway inhibitors and activators were used to validate and observe the changes in downstream inflammation. Through data mining, we found that the inflammatory chemokine CCL2 and PI3K/Akt signaling pathways after SCI expression were significantly increased, and after peroxide stimulation of PC-12 cells with CCL2 knockdown, their downstream cellular inflammatory factor levels were decreased. The PI3K/Akt signaling pathway was blocked by PI3K inhibitors, and the downstream inflammatory response was suppressed. In contrast, when PI3K activators were used, the inflammatory response was enhanced, indicating that the CCL2-PI3K/Akt signaling pathway plays a key role in the regulation of the inflammatory response. This study revealed that the inflammatory chemokine CCL2 can regulate the inflammatory response of PC-12 cells through the PI3K/Akt signaling pathway, and blocking the expression of the inflammatory chemokine CCL2 may be a promising strategy for the treatment of secondary injury after SCI., (© 2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

To explore diagnostic genes associated with cuproptosis in Parkinson's disease (PD) and to characterize immune cell infiltration by comprehensive bioinformatics analysis, three PD datasets were downloaded from the GEO database, two of which were merged and preprocessed as the internal training set and the remaining one as the external validation set. Based on the internal training set, differential analysis was performed to obtain differentially expressed genes (DEGs), and weighted gene co-expression network analysis (WGCNA) was conducted to obtain significant module genes. The genes obtained here were intersected to form the intersecting genes. The intersecting genes obtained from DEGs and WGCNA were intersected with cuproptosis-related genes (CRGs) to generate cuproptosis-related disease signature genes, and functional enrichment analysis was performed on Disease Ontology (DO), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG). Subsequently, LASSO analysis of the cuproptosis-related disease signature genes was performed to identify key genes and construct a diagnostic and predictive model. Then, single sample gene set enrichment analysis (ssGSEA) was performed on the internal training set to further analyze the correlation between key genes and immune cells. Lastly, the results were validated using an external validation set. A total of 405 DEGs were obtained by differential analysis, and 6 gene modules were identified by WGCNA analysis. The genes in the most significant modules were intersected with the DEGs to obtain 21 intersecting genes. The functions of the intersecting genes were mainly enriched in neurotransmitter transport, GABA-ergic synapse, synaptic vesicle cycle, serotonergic synapse, phenylalanine metabolism, tyrosine metabolism, tryptophan metabolism, etc. Subsequently, the intersecting genes were intersected with CRGs, and LASSO regression analysis was performed to screen 3 key cuproptosis-related disease signature genes, namely, SLC18A2, SLC6A3, and SV2C. The calibration curve of the nomogram model constructed based on these 3 key genes to predict PD showed good agreement, with a C-index of 0.944 and an area under the ROC (AUC) of 0.944 (0.833-1.000). It was also validated by the external dataset that the model constructed with these 3 key genes had good diagnostic and predictive power for PD. The ssGSEA analysis revealed that neutrophils might be the potential core immune cells and that SLC18A2, SLC6A3, and SV2C were significantly negatively correlated with neutrophils, which was also verified in the validation set. PD diagnosis and prediction model based on CRGs (SLC18A2, SLC6A3, and SV2C) has good diagnostic and predictive performance and could be a useful tool in the diagnosis of PD., (© 2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

The objective of this study is to investigate the potential biomarkers and therapeutic target genes for Parkinson's disease (PD). We analyzed four datasets (GSE8397, GSE20292, GSE20163, GSE20164) from the Gene Expression Omnibus database. We employed weighted gene co-expression network analysis and differential expression analysis to select genes and perform functional analysis. We applied three algorithms, namely, random forest, support vector machine recursive feature elimination, and least absolute shrinkage and selection operator, to identify hub genes, perform functional analysis, and assess their clinical diagnostic potential using receiver operating characteristic (ROC) curve analysis. We employed the xCell website to evaluate differences in the composition patterns of immune cells in the GEO datasets. We also collected serum samples from PD patients and established PD cell model to validate the expression of hub genes using enzyme-linked immunosorbent assay and quantitative real-time polymerase chain reaction. Our findings identified SV2C and DENR as two hub genes for PD and decreased in PD brain tissue compared with controls. ROC analysis showed effectively value of SV2C and DENR to diagnose PD, and they were downregulated in the serum of PD patients and cell model. Functional analysis revealed that dopamine vesicle transport and synaptic vesicle recycling are crucial pathways in PD. Besides, the differences in the composition of immune cells, especially basophils and T cells, were discovered between PD and controls. In summary, our study identifies SV2C and DENR as potential biomarkers for diagnosing PD and provides a new perspective for exploring the molecular mechanisms of PD., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

The role of circulating tumor cell (CTC) clusters in the metastatic dissemination process is gaining increased attention. Besides homotypic clusters, heterotypic clusters that contain tumor cells admixed with normal cells are frequently observed in patients with solid tumors. Current methods used for cluster detection and enumeration do not allow an accurate estimation of the relative fractions of tumor cells. Here we describe a method for estimating tumor fraction of clusters including isolation and collection of single clusters, assessment of copy number alterations of single clusters by low-pass whole genome sequencing, and bioinformatic analysis of sequencing data., (© 2024. Springer Science+Business Media, LLC, part of Springer Nature.)

At the "Kick Off" meeting for CompBioMed (compbiomed.eu), which was first funded in October 2016, I had no idea that one single sentence ("I wish I could teach this to medical students") would lead to a dedicated program of work to engage the clinicians and biomedical researchers of the future with supercomputing. This program of work which, within the CompBiomed Centre of Excellence, we have been calling "the CompBioMed Education and Training Programme," is a holistic endeavor that has been developed by and continues to be delivered with the expertise and support from experimental researchers, computer scientists, clinicians, HPC centers, and industrial partners within or associated with CompBioMed. The original description of the initial educational approach to training has previously been published (Townsend-Nicholson Interface Focus 10:20200003, 2020). In this chapter, I describe the refinements to the program and its delivery, emphasizing the highs and lows of delivering this program over the past 6 years. I conclude with suggestions for feasible measures that I believe will help overcome the barriers and challenges we have encountered in bringing a community of users with little familiarity of computing beyond the desktop to the petascale and beyond., (© 2024. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

In this chapter, we describe a computational pipeline for the in silico detection of plant viruses by high-throughput sequencing (HTS) from total RNA samples. The pipeline is designed for the analysis of short reads generated using an Illumina platform and free-available software tools. First, we provide advice for high-quality total RNA purification, library preparation, and sequencing. The bioinformatics pipeline begins with the raw reads obtained from the sequencing machine and performs some curation steps to obtain long contigs. Contigs are blasted against a local database of reference nucleotide viral sequences to identify the viruses in the samples. Then, the search is refined by applying specific filters. We also provide the code to re-map the short reads against the viruses found to get information on sequencing depth and read coverage for each virus. No previous bioinformatics background is required, but basic knowledge of the Unix command line and R language is recommended., (© 2024. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

The orientation of membrane proteins within the lipid bilayer is key to understanding their molecular function. Similarly, the proper topology of multispanning membrane proteins is crucial for their function. Although bioinformatics tools can predict these parameters assessing the presence of hydrophobic protein domains sufficiently long to span the membrane and other structural features, the predictions from different algorithms are often inconsistent. Therefore, experimental analysis becomes mandatory. Redox-based topology analysis exploits the steep gradient in the glutathione redox potential (E GSH ) across the ER membrane of about 80 mV to visualize the orientation of ER membrane proteins by fusing the E GSH biosensor roGFP2 to either the N- or the C-termini of the investigated protein sequence. Transient expression of these fusion proteins in tobacco leaves allows direct visualization of orientation and topology of ER membrane proteins in planta. The protocol outlined here is based on either a simple merge of the two excitation channels of roGFP2 or a colocalization analysis of the two channels and thus avoids ratiometric analysis of roGFP2 fluorescence., (© 2024. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

This paper presents a comprehensive protocol for predicting the three-dimensional (3D) structure of DNA aptamers and performing in silico docking calculations. The protocol includes steps for sequence input, structure prediction, sequence modification, structure minimization, and docking. The procedure is executed on a Mac environment utilizing bioinformatics tools such as mfold, RNA Composer, PyMOL, and Hdock. The protocol is intended to provide a guide for researchers in structural biology and drug design., (© 2024. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

Comprehensive profiling of the transcriptome reflects the dynamic changes in complex regulator interactions between genes and proteins in the pathological processes of autoimmune disease. To enable real-time adaptive sampling and run rapid sequencing with maximal expected readings of 50 Gb of data with accessibility to clinicians, basic researchers, and even students, a portable and affordable sequencing device, MinION, was employed in our laboratory for both basic and clinical studies. Here, the workflow of bulk RNA-seq in murine spleen using MinION is introduced. The methodology of both laboratory library preparation and the establishment of a bioinformatic pipeline are included in this chapter., (© 2024. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

The identification of T-cell epitopes is a critical step in the understanding of the immunologic mechanisms such as food allergy. Epitope screening in silico by bioinformatic tools can be used to identify T-cell epitopes, which can save time and resources. In this chapter, a multiparametric approach to predict and assess major histocompatibility complex (MHC) class II binding T-cell epitopes using bioinformatics was introduced for food allergens. Furthermore, the ability of predicted T-cell epitopes to induce interleukin (IL)-4, as well as the allergenicity potential based on the sequence analysis and population coverage of epitopes were also determined. The molecular docking approach was further used to explore the binding ability between epitopes and human leukocyte antigen (HLA) class II molecules. The amino acids that might be responsible for binding to HLA class II molecules and their binding interactions were analyzed., (© 2024. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

Mechanisms underlying food allergy are not well understood. Mass cytometry is a technique that allows the multiple analysis of cell surface markers and intracellular proteins by using the spectrum of rare metal isotopes of different atomic masses without channel overlap. Bioinformatic approaches are implemented to combine and reduce the information of more than 60 parameters to define immune cell subpopulations. To date, mass cytometry has revealed a great heterogeneity in human response to food antigens and that subpopulations of basophils and mononuclear cells might be mechanistically implicated in food allergy. This chapter reviews some fundamentals of mass cytometry and the contributions of this technique in elucidating the immune basis of food allergy, oral tolerance, food desensitization, phenotypes, and the cellular events occurring upon allergen-specific immunotherapy., (© 2024. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

An in-depth analysis of phage genomic sequences is essential for the proposal of a cocktail for therapeutic uses. With the burst of publications on phage isolation and genetic studies during the last decade, several different bioinformatics programs have been used. Here we describe our studies on the genetic organization of phages infecting Staphylococcus aureus, a pathogen of human importance, by using an assembly of tools for gene annotation, identification of expression components, and phylogeny analysis., (© 2024. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

Protein-ligand blind docking is a widely used method for studying the binding sites and poses of ligands and receptors in pharmaceutical and biological research. Recently, our new blind docking server named CB-Dock2 has been released and is currently being utilized by researchers worldwide. CB-Dock2 outperforms state-of-the-art methods due to its accuracy in binding site identification and binding pose prediction, which are enabled by its knowledge-based docking engine. This highly automated server offers interactive and intuitive input and output web interfaces, making it an efficient and user-friendly tool for the bioinformatics and cheminformatics communities. This chapter provides a brief overview of the methods, followed by a detailed guide on using the CB-Dock2 server. Additionally, we present a case study that evaluates the performance of protein-ligand blind docking using this tool., (© 2024. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

Advancements in high-throughput technologies, genomics, transcriptomics, and metabolomics play an important role in obtaining biological information about living organisms. The field of computational biology and bioinformatics has experienced significant growth with the advent of high-throughput sequencing technologies and other high-throughput techniques. The resulting large amounts of data present both opportunities and challenges for data analysis. Big data analysis has become essential for extracting meaningful insights from the massive amount of data. In this chapter, we provide an overview of the current status of big data analysis in computational biology and bioinformatics. We discuss the various aspects of big data analysis, including data acquisition, storage, processing, and analysis. We also highlight some of the challenges and opportunities of big data analysis in this area of research. Despite the challenges, big data analysis presents significant opportunities like development of efficient and fast computing algorithms for advancing our understanding of biological processes, identifying novel biomarkers for breeding research and developments, predicting disease, and identifying potential drug targets for drug development programs., (© 2024. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

The greatest challenge in drug discovery remains the high rate of attrition across the different phases of the process, which cost the industry billions of dollars every year. While all phases remain crucial to ensure pharmaceutical-level safety, quality, and efficacy of the end product, streamlining these efforts toward compounds with success potential is pivotal for a more efficient and cost-effective process. The use of artificial intelligence (AI) within the pharmaceutical industry aims at just this, and has applications in preclinical screening for biological activity, optimization of pharmacokinetic properties for improved drug formulation, early toxicity prediction which reduces attrition, and pre-emptively screening for genetic changes in the biological target to improve therapeutic longevity. Here, we present a series of in silico tools that address these applications in small molecule development and describe how they can be embedded within the current pharmaceutical development pipeline., (© 2024. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

Teratogenesis testing can be challenging due to the limitations of both in vitro and in vivo models. Test-systems, based especially on human embryonic cells, have been helping to overcome the difficulties when allied to omics strategies, such as transcriptomics. In these test-systems, cells exposed to different compounds are then analyzed in microarray or RNA-seq platforms regarding the impacts of the potential teratogens in the gene expression. Nevertheless, microarray and RNA-seq dataset processing requires computational resources and bioinformatics knowledge. Here, a pipeline for microarray and RNA-seq processing is presented, aiming to help researchers from any field to interpret the main transcriptome results, such as differential gene expression, enrichment analysis, and statistical interpretation. This chapter also discusses the main difficulties that can be encountered in a transcriptome analysis and the better alternatives to overcome these issues, describing both programming codes and user-friendly tools. Finally, specific issues in the teratogenesis field, such as time-course analysis, are also described, demonstrating how the pipeline can be applied in these studies., (© 2024. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

Nanopore sequencing of full-length cDNAs offers unprecedented details of the plastid RNA metabolism. After the generation of the nanopore reads, several bioinformatic steps are required to analyze the data. In this chapter, we describe in a few simple command lines the processing and mapping of the reads as well as the generation of virtual Northern blots as a simple and familiar way to visualize Nanopore sequencing data., (© 2024. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

Genes encoding small secreted peptides are widely distributed among plant genomes but their detection and annotation remains challenging. The bioinformatics protocol described here aims to identify as exhaustively as possible secreted peptide precursors belonging to a family of interest. First, homology searches are performed at the protein and genome levels. Next, multiple sequence alignments and predictions of a secretion signal are used to define a set of homologous proteins sharing features of secreted peptide precursors. These protein sequences are then used as input of motif detection and profile-based tools to build representative matrices and profiles that are used iteratively as guides to scan again the proteome and genome until family completion., (© 2024. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

The viral fraction of human and experimental animal fecal matter is increasingly attracting research interest due to its newfound influence on the gut microbiome and host health. During the past decade, high-throughput sequencing techniques have seen massive improvements, and in recent years, bioinformatics pipelines for virome analysis have also vastly improved with respect to both user-friendliness and output quality. Yet, the shape and quality of such data are highly dependent on how the viruses are isolated and their genomes extracted and processed to build sequencing libraries.Here we describe a simple protocol for virus isolation from fecal samples suitable for further propagation/characterization or sequencing efforts. It is based on two filtration steps: one for removing large particles such as bacteria and one for removing free DNA and up-concentrating phages and other viruses in the solution. The method is highly scalable, adaptable to a long range of sample types including low-input samples, and has a quantifiable output suitable for both plaquing and sequencing., (© 2024. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

Advanced technology innovations allow cost-effective, high-throughput profiling of biological systems. It enabled genome sequencing in days using advanced technologies (e.g., next-generation sequencing, microarrays, and mass spectrometry). Since technology has been developed, massive biological data (e.g., genomics, proteomics) has been produced cheaply, allowing the "big data" era to create new opportunities to solve medical and biological complications in many disciplines-preventive medicine, biology, Personalized Medicine, gene sequencing, healthcare, and industry. Computational biology and bioinformatics are interdisciplinary fields that develop and apply computational methods (e.g., analytical methods, mathematical modeling, and simulation) to analyze large collections of biological data, such as genetic sequences, cell populations, or protein samples, to make new predictions or discover new biology. Biological data storage, mining, and analysis have challenges because data is much more heterogeneous. In this study, the big data resources of genomics, proteomics, and metabolomics have been explored to solve biological problems using big data analysis approaches. The goal is to build a network of relationship-based gene-disease associations to prioritize phenotypes common to epilepsy and seizure disease. Through network analysis, The 10 seed genes, 22 associated genes, 132 microRNAs, and 38 transcription factors have been identified that have a direct effect on all forms of epilepsy and seizures. The majority of seed genes, according to the results of a functional analysis of seed genes, are involved in the acetylcholine-gated channel complex (10%) and the heterotrimeric G-protein complex (10%) pathways related to cellular components, followed by a role in the regulation of action potential (20%) and positive regulation of vascular endothelial growth factor production (20%) in Epilepsy and Seizures pathways related to biological processes. This study might provide insight into the workings of the disease and shows the importance of continued research into epilepsy and other conditions that can trigger seizure activity., (© 2024. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

Network pharmacology is an emerging pioneering approach in the drug discovery process, which is used to predict the therapeutic mechanism of compounds using various bioinformatic tools and databases. Emerging studies have indicated the use of network pharmacological approaches in various research fields, particularly in the identification of possible mechanisms of herbal compounds/ayurvedic formulations in the management of various diseases. These techniques could also play an important role in the prediction of the possible mechanisms of neuroprotective compounds. The first part of the chapter includes an introduction on neuroprotective compounds based on literature. Further, network pharmacological approaches are briefly discussed. The use of network pharmacology in the prediction of the neuroprotective mechanism of compounds is discussed in detail with suitable examples. Finally, the chapter concludes with the current challenges and future prospectives., (© 2024. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

This chapter describes protocols suitable for the detection and identification of RNA viruses infecting oomycetes (so-called water molds of Kingdom Heterokonta, Stramenopila), focusing on species of Phytophthora and exemplified by P. fragariae. The protocol includes laboratory procedures for oomycete cultivation and total RNA extraction from harvested mycelia, followed by instructions on suitable parameters given for sequencing companies on ribosomal RNA depletion, cDNA library preparation, and total RNA-sequencing (RNA-Seq). We also describe the bioinformatics steps needed for de novo assembly of raw reads into contigs, removal of host-associated contigs, and virus identification by database searches, as well as host validation by RT-PCR. All steps are described using an exemplar RNA-Seq library containing a yet undescribed fusagravirus hosted by a P. fragariae isolate., (© 2024. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

The pathology of spinal cord injury (SCI), including primary and secondary injuries, primarily involves hemorrhage, ischemia, edema, and inflammatory responses. Cell transplantation has been the most promising treatment for SCI in recent years; however, its specific molecular mechanism remains unclear. In this study, bioinformatics analysis verified by experiment was used to elucidate the hub genes associated with SCI and to discover the underlying molecular mechanisms of cell intervention. GSE46988 data were downloaded from the Gene Expression Omnibus dataset. In our study, differentially expressed genes (DEGs) were reanalyzed using the "R" software (R v4.2.1). Functional enrichment and protein-protein interaction network analyses were performed, and key modules and hub genes were identified. Network construction was performed for the hub genes and their associated miRNAs. Finally, a semi-quantitative analysis of hub genes and pathways was performed using quantitative real-time polymerase chain reaction. In total, 718 DEGs were identified, mainly enriched in immune and inflammation-related functions. We found that Cd4, Tp53, Rac2, and Akt3 differed between vehicle and transplanted groups, suggesting that these genes may play an essential role in the transplantation of olfactory ensheathing cells, while a toll-like receptor signaling pathway was significantly enriched in Gene set enrichment analysis, and then, the differences were statistically significant by experimentally verifying the expression of their associated molecules (Tlr4, Nf-κb, Ikkβ, Cxcl2, and Tnf-α). In addition, we searched for upstream regulatory molecules of these four central genes and constructed a regulatory network. This study is the first to construct a regulatory network for olfactory ensheathing cell transplantation in treating SCI, providing a new idea for SCI cell therapy., (© 2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Epstein-Barr virus (EBV) is a global lymphotropic virus and has been associated with various malignancies, among which colorectal cancer (CRC) is the prevalent one causing mortality worldwide. In the recent past, numerous research efforts have been made to develop a potential vaccine against this virus; however, none is effective possibly due to their low throughput, laboriousness, and lack of sensitivity. In this study, we designed a multi-epitope subunit vaccine that targets latent membrane protein (LMP-2B) of EBV using pan-genome and reverse vaccinology approaches. Twenty-three major histocompatibility complex (MHC) epitopes (five class-I and eighteen class-II) and eight B-cell epitopes, which have been found to be antigenic, immunogenic, and non-toxic, were selected for the vaccine construction. Furthermore, 24 vaccine constructs (VCs) were designed from the predicted epitopes and out of which VC1 was selected and finalized based on its structural parameters. The functionality of VC1 was validated through molecular docking with different immune receptors (MHC class-I, MHC class-II, and TLRs). The binding affinity, molecular and immune simulation revealed that the VC1 had more stable interaction and is believed to elicit good immune responses against EBV. HIGHLIGHTS: Pan-genome and reverse vaccinology approaches were used to design a multi-epitope subunit vaccine against LMP-2B protein of EBV. Epitopes were selected based on the antigenic, immunogenic, and non-toxic properties. Twenty-four vaccine constructs (VCs) were designed from the predicted epitopes. Designed vaccine VC1 has shown good binding affinity and molecular and immune simulation. VC1 was validated using molecular docking with different immune receptors., (© 2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Ferroptosis and immune cell infiltration are important pathological events in spinal cord injury (SCI), but links between ferroptosis and immune microenvironment after SCI were rare reported. In our study, 77 FRDEGs were screened at 7 days after SCI. GO analysis of FRDEGs showed that aging (GO:0007568; P-value = 1.11E-05) was the most remarkable enriched for biological process, protein binding (GO:0005515; adjusted P-value = 4.44E-06) was the most significantly enriched for molecular function, cytosol (GO:0005829; adjusted P-value = 1.51E-04) was the most prominent enriched for cellular component. Meanwhile, Ferroptosis was significantly enriched both in KEGG (rno04216; adjusted P-value = 0.001) and GSEA (NES = 1.35; adjusted P-value = 0.004) analysis. Next, Hmox1 (Log 2 Fold change = 6.52; adjusted P-value = 0.004) was identified as one of hub genes in SCI-induced ferroptosis. In the results of immune cell infiltration analysis, proportion of microglia/macrophage was significantly increased after SCI, and Hmox1 was found to positively correlate to the M1 type microglia/macrophage abundance. Finally, effects of Hmox1 on ferroptosis and M1 type polarization were validated in vivo and in vitro. Summarily, we found that Hmox1 was the hub gene in SCI-induced ferroptosis and associated with the M1 type polarization., (© 2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Ferroptosis plays crucial roles in the pathology of spinal cord injury (SCI). The purpose of this study was to identify differentially expressed ferroptosis-related genes (DE-FRGs) in human acute SCI by bioinformatics analysis and validate the hub DE-FRGs in non-SCI and SCI patients. The GSE151371 dataset was downloaded from the Gene Expression Omnibus and difference analysis was performed. The differentially expressed genes (DEGs) in GSE151371 overlapped with the ferroptosis-related genes (FRGs) obtained from the Ferroptosis Database. A total of 41 DE-FRGs were detected in 38 SCI samples and 10 healthy samples in GSE151371. Then, enrichment analyses of these DE-FRGs were performed for functional annotation. The GO enrichment results showed that upregulated DE-FRGs were mainly associated with reactive oxygen species and redox reactions, and the KEGG enrichment analysis indicated involvement in some diseases and ferroptosis pathways. Protein-protein interaction (PPI) analysis and lncRNA-miRNA-mRNA regulatory network were performed to explore the correlations between genes and regulatory mechanisms. The relationship between DE-FRGs and differentially expressed mitochondria-related genes (DE-MRGs) was also analyzed. Finally, quantitative real-time polymerase chain reaction (qRT-PCR) was used to verify the hub DE-FRGs in clinical blood samples from acute SCI patients and healthy controls. Consistent with the bioinformatics results, qRT-PCR of the clinical samples indicated similar expression levels of TLR4, STAT3, and HMOX1. This study identified DE-FRGs in blood samples from SCI patients, and the results could improve our understanding of the molecular mechanisms of ferroptosis in SCI. These candidate genes and pathways could be therapeutic targets for SCI., (© 2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Vanadium exposure has the adverse effect on lung function in human, whereas the detailed mechanisms of vanadium exposure-induced pulmonary toxicity are limited. Hence, the present study aimed to investigate the hub genes and signaling pathways related to sodium metavanadate (SMV)-induced pulmonary toxicity. The transcript expression profile GSE36684 downloaded from Gene Expression Omnibus contained eight human bronchial epithelial cell (HBEC) samples including five SMV-treated and three control HBEC samples. Totally 455 differentially expressed genes (DEGs) were screened, especially 201 and 254 genes were up- and down-regulated in the HBECs treated with SMV. Gene ontology analysis suggested that the DEGs were mainly involved in signal transduction, the response to drug, cell proliferation, adhesion, and migration. Pathway analysis demonstrated that the DEGs were primarily participated in NF-κB, Wnt, MAPK, and PI3K-Akt signaling pathways. Moreover, the hub genes, including ITGA5, ITGB3, ITGA2, LAMC2, MMP2, and ITGA4, might contribute to SMV-induced pulmonary toxicity. Our study improves the understanding of the molecular mechanisms by which SMV induced the pulmonary toxicity., (© 2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Human polyomavirus type 1, or BK virus (BKV), is a ubiquitous pathogen belonging to the polyomaviridae family mostly known for causing BKV-associated nephropathy (BKVN) and allograft rejection in kidney transplant recipients (KTRs) following the immunosuppression regimens recommended in these patients. Reduction of the immunosuppression level and anti-viral agents are the usual approaches for BKV clearance, which have not met a desired outcome yet. There are also debating matters such as the effect of this pathogen on emerging various comorbidities and the related malignancies in the human population. In this study, a reverse vaccinology approach was implemented to design a mRNA vaccine against BKV by identifying the most antigenic proteins of this pathogen. Potential immunogenic T and B lymphocyte epitopes were predicted through various immunoinformatic tools. The final epitopes were selected according to antigenicity, toxicity, allergenicity, and cytokine inducibility scores. According to the obtained results, the designed vaccine was antigenic, neutral at the physiological pH, non-toxic, and non-allergenic with a world population coverage of 93.77%. Since the mRNA codon optimization ensures the efficient expression of the vaccine in a host cell, evaluation of different parameters showed our designed mRNA vaccine has a stable structure. Moreover, it had strong interactions with toll-like receptor 4 (TLR4) according to the molecular dynamic simulation studies. The in silico immune simulation analyses revealed an overall increase in the immune responses following repeated exposure to the designed vaccine. Based on our findings, the vaccine candidate is ready to be tested as a promising novel mRNA therapeutic vaccine against BKV., (© 2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

This study aims to explore key prognostic and diagnostic biomarkers involved in the pathogenesis of papillary thyroid cancer (PTC) which is one of the most common endocrine cancers and whose occurrence is rapidly increasing. Papillary thyroid cancer datasets containing normal and tumor samples were collected from Gene Expression Omnibus. Protein-protein interaction (PPI) network for common upregulated differentially expressed genes (DEGs) was constructed, and hub genes were studied. Gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis were performed to identify the vital biological behaviors and pathways involved in PTC. PPI network analysis demonstrated the interaction between 134 common upregulated DEGs, and top 15 pivotal genes with highest degree of connectivity were retrieved. Three of the hub genes (DPP4, ITGA2, FN1) were linked to the prognosis of PTC patients and considered clinically relevant core genes via survival analysis. We suggest that the identification of key genes associated with PTC development help us in understanding molecular mechanisms related to disease. These genes could also be considered the diagnostic biomarkers or as therapeutic targets in the future treatment for PTC., (© 2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)