Comprehensive multiomics and in silico approach uncovers prognostic, immunological, and therapeutic roles of ANLN in lung adenocarcinoma.

The anillin actin-binding protein (ANLN) is immensely overexpressed in cancers, including lung cancer (LC). Phytocompounds have gained interest due to their broader potential and reduced unwanted effects. Screening numerous compounds presents a challenge, but in silico molecular docking is pragmatic. The present study aims to identify the role of ANLN in lung adenocarcinoma (LUAD), along with identification and interaction analysis of anticancer and ANLN inhibitory phytocompounds followed by molecular dynamics (MD) simulation. Using a systematic approach, we found that ANLN is significantly overexpressed in LUAD and mutated with a frequency of 3.73%. It is linked with advanced stages, clinicopathological parameters, worsening of relapse-free survival (RFS), and overall survival (OS), pinpointing its oncogenic and prognostic potential. High-throughput screening and molecular docking of phytocompounds revealed that kaempferol (flavonoid aglycone) interacts strongly with the active site of ANLN protein via hydrogen bonds, Vander Waals interactions, and acts as a potent inhibitor. Furthermore, we discovered that ANLN expression was found to be significantly higher (p) in LC cells compared to normal cells. This is a propitious and first study to demonstrate ANLN and kaempferol interactions, which might eventually lead to removal of rout from cell cycle regulation posed by ANLN overexpression and allow it to resume normal processes of proliferation. Overall, this approach suggested a plausible biomarker role of ANLN and the combination of molecular docking subsequently led to the identification of contemporary phytocompounds, bearing symbolic anticancer effects. The findings would be advantageous for pharmaceutics but require validation using in vitro and in vivo methods. HIGHLIGHTS: • ANLN is significantly overexpressed in LUAD. • ANLN is implicated in the infiltration of TAMs and altering plasticity of TME. • Kaempferol (potential ANLN inhibitor) shows important interactions with ANLN which could remove the alterations in cell cycle regulation, imposed by ANLN overexpression eventually leading to normal process of cell proliferation.

Global and local evolutionary dynamics of Dengue virus serotypes 1, 3, and 4.

Evolutionary studies on Dengue virus (DENV) in endemic regions are necessary since naturally occurring mutations may lead to genotypic variations or shifts in serotypes, which may lead to future outbreaks. Our study comprehends the evolutionary dynamics of DENV, using phylogenetic, molecular clock, skyline plots, network, selection pressure, and entropy analyses based on partial CprM gene sequences. We have collected 250 samples, 161 in 2017 and 89 in 2018. Details for the 2017 samples were published in our previous article and that of 2018 are presented in this study. Further evolutionary analysis was carried out using 800 sequences, which incorporate the study and global sequences from GenBank: DENV-1 (n = 240), DENV-3 (n = 374), and DENV-4 (n = 186), identified during 1944-2020, 1956-2020, and 1956-2021, respectively. Genotypes V, III, and I were identified as the predominant genotypes of the DENV-1, DENV-3, and DENV-4 serotypes, respectively. The rate of nucleotide substitution was found highest in DENV-3 (7.90 × 10-4 s/s/y), followed by DENV-4 (6.23 × 10-4 s/s/y) and DENV-1 (5.99 × 10-4 s/s/y). The Bayesian skyline plots of the Indian strains revealed dissimilar patterns amongst the population size of the three serotypes. Network analyses showed the presence of different clusters within the prevalent genotypes. The data presented in this study will assist in supplementing the measures for vaccine development against DENV.

Integrative multiomics and in silico analysis revealed the role of ARHGEF1 and its screened antagonist in mild and severe COVID-19 patients.

COVID-19 is a sneaking deadly disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The rapid increase in the number of infected patients worldwide enhances the exigency for medicines. However, precise therapeutic drugs are not available for COVID-19; thus, exhaustive research is critically required to unscramble the pathogenic tools and probable therapeutic targets for the development of effective therapy. This study utilizes a chemogenomics strategy, including computational tools for the identification of viral-associated differentially expressed genes (DEGs), and molecular docking of potential chemical compounds available in antiviral, anticancer, and natural product-based libraries against these DEGs. We scrutinized the messenger RNA expression profile of SARS-CoV-2 patients, publicly available on the National Center for Biotechnology Information-Gene Expression Omnibus database, stratified them into different groups based on the severity of infection, superseded by identification of overlapping mild and severe infectious (MSI)-DEGs. The profoundly expressed MSI-DEGs were then subjected to trait-linked weighted co-expression network construction and hub module detection. The hub module MSI-DEGs were then exposed to enrichment (gene ontology + pathway) and protein-protein interaction network analyses where Rho guanine nucleotide exchange factor 1 (ARHGEF1) gene conjectured in all groups and could be a probable target of therapy. Finally, we used the molecular docking and molecular dynamics method to identify inherent hits against the ARHGEF1 gene from antiviral, anticancer, and natural product-based libraries. Although the study has an identified significant association of the ARHGEF1 gene in COVID19; and probable compounds targeting it, using in silico methods, these targets need to be validated by both in vitro and in vivo methods to effectively determine their therapeutic efficacy against the devastating virus.

Impact of length of replication competent genome of hepatitis B virus over the differential antigenic secretion.

Hepatitis B virus (HBV) genome consists of circular partially double stranded DNA of 3.2 kb size which gets converted into covalently closed circular DNA (cccDNA) during its life cycle. It then acts as a template for formation of pregenomicRNA (pgRNA) of 3.5 kb. Absence of appropriate animal models prompted a need to establish a better in vitro culture system to uncover the propagation and survival mechanisms of the virus. There is scarcity of data to represent the significance of varying length of replication competent viral genome on the secretion of viral secretory proteins/antigens and in turn on the overall effects on the accomplishment of the viral life cycle. The present study was undertaken to ascertain a suitable replication competent construct in which the viral life cycle of HBV with varying clinical relevance can be studied efficiently. Two constructs (pHBV 1.3 and pHBV 1X) of different sizes were used to transfect hepatoma cells and consequently the secretory antigens were monitored. In vector free approach (pHBV 1X), 3.2 kb viral DNA is directly transfected in the culture system whereas in vector mediated approach more than full length of viral genome is cloned in a vector (pHBV 1.3X) and transfected to obtain a 3.5 kb pgRNA intermediate. HBV secretes two important antigens; HBsAg and HBeAg. HBsAg is a hallmark of infection and is the first to be secreted in the blood stream whereas HBeAg is a secretory protein and remains associated with the viral replication. The construct pHBV 1.3X referring to as more than full length, by virtue of being capable of undergoing transcription without the synthesis of cccDNA intermediate (unlike the clinical situation where an intermediate step of cccDNA synthesis is an essential component to initiate the viral life cycle) appears to be better system for studying viral life cycle in in vitro culture system. The reasons could be assigned to the fact that as low as 100 ng of viral DNA was shown to quantify the replicative phenotypes with this construct. The better efficiency of this construct at prima facie, appears to be mediated through the significantly higher levels of pgRNA transcript during the viral life cycle.

Investigation of deleterious effects of nsSNPs in the POT1 gene: a structural genomics-based approach to understand the mechanism of cancer development.

Protection of telomere 1 (POT1) is one of the key components of shelterin complex, implicated in maintaining the telomere homeostasis, and thus stability of the eukaryotic genome. A large number of non-synonymous single nucleotide polymorphisms (nsSNPs) in the POT1 gene have been reported to cause varieties of human diseases, including cancer. In recent years, a number of mutations in POT1 has been markedly increased, and interpreting the effect of these large numbers of mutations to understand the mechanism of associated diseases seems impossible using experimental approaches. Herein, we employ varieties of computational methods such as PROVEAN, PolyPhen-2, SIFT, PoPMuSiC, SDM2, STRUM, and MAESTRO to identify the effects of 387 nsSNPs on the structure and function of POT1 protein. We have identified about 183 nsSNPs as deleterious and termed them as "high-confidence nsSNPs." Distribution of these high-confidence nsSNPs demonstrates that the mutation in oligonucleotide binding domain 1 is highly deleterious (one in every three nsSNPs), and high-confidence nsSNPs show a strong correlation with residue conservation. The structure analysis provides a detailed insights into the structural changes occurred in consequence of conserved mutations which lead to the cancer progression. This study, for the first time, offers a newer prospective on the role of POT1 mutations on the structure, function, and their relation to associated diseases.

In Vitro Cytotoxicity and Interaction of Noscapine with Human Serum Albumin: Effect on Structure and Esterase Activity of HSA.

Noscapine is effective to inhibit cellular proliferation and induced apoptosis in nonsmall cell, lung, breast, lymphoma, and prostate cancer. It also shows good efficiency to skin cancer cells. In the current work, we studied the mechanism of interaction between the anticancer drug noscapine (NOS) and carrier protein human serum albumin (HSA) by using a variety of spectroscopic techniques (fluorescence spectroscopy, time-resolved fluorescence, UV-visible, fluorescence resonance energy transfer (FRET), Fourier transform infrared (FTIR), and circular dichroism (CD) spectroscopy), electrochemistry (cyclic voltammetry), and computational methods (molecular docking and molecular dynamic simulation). The steady-state fluorescence results showed that fluorescence intensity of HSA decreased in the presence of NOS via a static quenching mechanism, which involves ground state complex formation between NOS and HSA. UV-visible and FRET results also supported the fluorescence result. The corresponding thermodynamic result shows that binding of NOS with HSA is exothermic in nature, involving electrostatic interactions as major binding forces. The binding results were further confirmed through a cyclic voltammetry approach. The FRET result signifies the energy transfer from Trp214 of HSA to the NOS. Molecular site marker, molecular docking, and MD simulation results indicated that the principal binding site of HSA for NOS is site I. Synchronous fluorescence spectra, FTIR, 3D fluorescence, CD spectra, and MD simulation results reveal that NOS induced the structural change in HSA. In addition, the MTT assay study on a human skin cancer cell line (A-431) was also performed for NOS, which shows that NOS induced 80% cell death of the population at a 320 µM concentration. Moreover, the esterase-like activity of HSA with NOS was also done to determine the variation in protein functionality after binding with NOS.

Sequence, structure and evolutionary analysis of cold shock domain proteins, a member of OB fold family.

The cold shock domain (CSD) belongs to the oligosaccharide/oligonucleotide-binding fold superfamily which is highly conserved from prokaryotes to higher eukaryotes, and appears to function as RNA chaperones. CSD is involved in diverse cellular processes, including adaptation to low temperatures, nutrient stress, cellular growth and developmental processes. Structural Classification of Proteins (SCOP) database broadly classifies OB fold proteins into 18 different superfamilies, including nucleic acid-binding superfamily (NAB). The NAB is further divided into 17 families together with cold shock DNA-binding protein family (CSDB). The CSDB have more than 240 000 sequences in UniProt database consisting of 32 domains including CSD. Among these domains, CSD is the second largest sequence contributor (> 40 398 sequences). Herein, we have systematically analysed the relative abundance and distribution of CSD proteins based on sequences, structures, repeats and gene ontology (GO) molecular functions in all domains of life. Analysis of sequence distribution suggesting that CSDs are largely found in bacteria (83-94%) with single CSD repeat. However, repeat distribution in eukaryota varies from 1 to 5 in combination with other auxiliary domain that makes CSD proteins functionally more diverse compared to the bacterial counterparts. Further, analysis of repeats distributions on evolutionary scale suggest that existence of CSD in multiple repeats is mainly driven through speciation, gene shuffling and gene duplication events.

Screening of miRNAs as prognostic biomarkers and their associated hub targets across Hepatocellular carcinoma using survival-based bioinformatics approach.

BACKGROUND: The hepatocellular carcinoma (HCC) incident rate is gradually increasing yearly despite all the research and efforts taken by scientific communities and governing bodies. Approximately 90% of all liver cancer cases belong to HCC. Usually, HCC patients approach the treatment in the late stages of this malignancy which becomes the primary cause of high mortality rate. The knowledge about molecular pathogenesis of HCC is limited and needs more attention from researchers to identify the driver genes and miRNAs, which causes to translate this information into clinical practice. Therefore, the key regulators identification of miRNA-mRNA regulatory network is essential to identify HCC-associated genes. METHODOLOGY: We extracted microRNA (miRNA) and messenger RNA (mRNA) expression datasets of normal and tumor HCC patient samples from UCSC Xena followed by identifying differentially expressed genes (DEGs) and differentially expressed miRNAs (DEMs). Univariate and multivariate cox-proportional hazard models were utilized to identify DEMs having significant association with overall survival (OS). Kaplan-Meier (KM) plotter was used to validate the presence of prognostic DEMs. A risk-score model was used to evaluate the effectiveness of KM-plotter validated DEMs combination on risk of samples. Target DEGs of prognostic miRNAs were identified via sources such as miRTargetLink and miRWalk followed by their validation in an external microarray cohort and enrichment analysis. RESULTS: 562 DEGs and 388 DEMs were identified followed by seven prognostic miRNAs (i.e., miR-19a, miR-19b, miR-30d-5p, miR-424-5p, miR-3677-5p, miR-3913-5p, miR-7705) post univariate, multivariate, risk-score model evaluation and KM-plotter analyses. ANLN, MRO, CPEB3 were their targets and were also validated in GSE84005 dataset. CONCLUSIONS: The findings of this study decipher that most significant miRNAs and their identified target genes have association with apoptosis, inflammation, cell cycle regulation and cancer-related pathways, which appear to contribute to HCC pathogenesis and therefore, the discovery of new targets.

Nitric oxide as a double-edged sword in pulmonary viral infections: Mechanistic insights and potential therapeutic implications.

In the face of the global pandemic caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), researchers are tirelessly exploring novel therapeutic approaches to combat coronavirus disease 2019 (COVID-19) and its associated complications. Nitric oxide (NO) has appeared as a multifaceted signaling mediator with diverse and often contrasting biological activities. Its intricate biochemistry renders it a crucial regulator of cardiovascular and pulmonary functions, immunity, and neurotransmission. Perturbations in NO production, whether excessive or insufficient, contribute to the pathogenesis of various diseases, encompassing cardiovascular disease, pulmonary hypertension, asthma, diabetes, and cancer. Recent investigations have unveiled the potential of NO donors to impede SARS-CoV- 2 replication, while inhaled NO demonstrates promise as a therapeutic avenue for improving oxygenation in COVID-19-related hypoxic pulmonary conditions. Interestingly, NO's association with the inflammatory response in asthma suggests a potential protective role against SARS-CoV-2 infection. Furthermore, compelling evidence indicates the benefits of inhaled NO in optimizing ventilation-perfusion ratios and mitigating the need for mechanical ventilation in COVID-19 patients. In this review, we delve into the molecular targets of NO, its utility as a diagnostic marker, the mechanisms underlying its action in COVID-19, and the potential of inhaled NO as a therapeutic intervention against viral infections. The topmost significant pathway, gene ontology (GO)-biological process (BP), GO-molecular function (MF) and GO-cellular compartment (CC) terms associated with Nitric Oxide Synthase (NOS)1, NOS2, NOS3 were arginine biosynthesis (p-value = 1.15 x 10-9) regulation of guanylate cyclase activity (p-value = 7.5 x 10-12), arginine binding (p-value = 2.62 x 10-11), vesicle membrane (p-value = 3.93 x 10-8). Transcriptomics analysis further validates the significant presence of NOS1, NOS2, NOS3 in independent COVID-19 and pulmonary hypertension cohorts with respect to controls. This review investigates NO's molecular targets, diagnostic potentials, and therapeutic role in COVID-19, employing bioinformatics to identify key pathways and NOS isoforms' significance.

Uncovering the role of aquaporin and chromobox family members as potential biomarkers in head and neck squamous cell carcinoma via integrative multiomics and in silico approach.

Head and neck squamous cell carcinoma (HNSC) is a diverse group of tumors arising from oral cavity, oropharynx, larynx, and hypopharynx squamous epithelium, posing significant morbidity. Aquaporins (AQPs) are membrane proteins forming water channels, some associated with carcinomas. Chromobox (CBX) family is known to modulate physiological and oncological processes. In our study, we analyzed AQPs and CBXs having significant expression followed by their prognostic and mutational assessment. Next, we performed enrichment and tumor infiltration analysis followed by HPA validation. Lastly, we established a 3-node miRNA-TF-mRNA regulatory network and performed protein-protein docking of the highest-degree subnetwork motif between TF and mRNA. Significant upregulation of CBX3/2 and downregulation of AQP3/5/7 correlated with poor overall survival (OS) in HNSC patients. The most significant pathway, GO-BP, GO-MF, and GO-CC terms associated with AQP3 and CBX3 were passive transport by aquaporins, response to vitamin, glycerol channel activity, and condensed chromosome, centromeric region. AQP3 negatively correlated with [Formula: see text] T cells, positively with [Formula: see text] T cells and B cells, and negatively with tumor purity, whereas CBX3 positively correlated with [Formula: see text] T cells, negatively with [Formula: see text] T cells and B cells, and positively with tumor purity. Three-node miRNA-TF-mRNA regulatory network revealed a highest-degree subnetwork motif comprising one TF (SMAD3), one miRNA (miR-423-5p), and one mRNA (AQP3). Protein-protein interaction studies suggested a direct interaction between AQP3 and Smad3 proteins. We concluded that AQP3 and CBX3 hold potential as treatment strategies and individual prognostic biomarkers, while further protein-protein interaction studies of AQP3 could offer insights into its interactions with Smad3 proteins.

Identification of potential therapeutic targets for COVID-19 through a structural-based similarity approach between SARS-CoV-2 and its human host proteins.

Background: The COVID-19 pandemic caused by SARS-CoV-2 has led to millions of deaths worldwide, and vaccination efficacy has been decreasing with each lineage, necessitating the need for alternative antiviral therapies. Predicting host-virus protein-protein interactions (HV-PPIs) is essential for identifying potential host-targeting drug targets against SARS-CoV-2 infection. Objective: This study aims to identify therapeutic target proteins in humans that could act as virus-host-targeting drug targets against SARS-CoV-2 and study their interaction against antiviral inhibitors. Methods: A structure-based similarity approach was used to predict human proteins similar to SARS-CoV-2 ("hCoV-2"), followed by identifying PPIs between hCoV-2 and its target human proteins. Overlapping genes were identified between the protein-coding genes of the target and COVID-19-infected patient's mRNA expression data. Pathway and Gene Ontology (GO) term analyses, the construction of PPI networks, and the detection of hub gene modules were performed. Structure-based virtual screening with antiviral compounds was performed to identify potential hits against target gene-encoded protein. Results: This study predicted 19,051 unique target human proteins that interact with hCoV-2, and compared to the microarray dataset, 1,120 target and infected group differentially expressed genes (TIG-DEGs) were identified. The significant pathway and GO enrichment analyses revealed the involvement of these genes in several biological processes and molecular functions. PPI network analysis identified a significant hub gene with maximum neighboring partners. Virtual screening analysis identified three potential antiviral compounds against the target gene-encoded protein. Conclusion: This study provides potential targets for host-targeting drug development against SARS-CoV-2 infection, and further experimental validation of the target protein is required for pharmaceutical intervention.

Integrative multiomics and weighted network approach reveals the prognostic role of RPS7 in lung squamous cell carcinoma pathogenesis.

Lung cancer is one of the most commonly occurring malignant cancers with the highest rate of mortality globally. Difference between lung squamous cell carcinoma (LUSC) and lung adenocarcinoma (LUAD) and their treatment strategies according to genetic markers may be helpful in reducing the cancer progression and increasing the overall survival (OS) in patients. LUSC is known for comparatively less typical onco-drivers, target therapy resistance, marked genomic complexity, and a reasonably higher mutation rate. The mRNA-seq data and clinical information of LUAD and LUSC cohorts from UCSC Xena comprising 437 and 379 patient samples were extracted. Differential expression and weighted network analyses revealed 47 and 18 hub differentially expressed genes (DEGs) corresponding to LUAD and LUSC cohorts. These hub DEGs were further subjected to protein-protein interaction network (PPIN) and OS analyses. Lower mRNA expression levels of both RPS15A and RPS7 worsened the OS of LUSC patients. Additionally, both these prognostic biomarkers were validated via external sources such as UALCAN, cBioPortal, TIMER, and HPA. RPS7 had higher mutation frequency compared to RPS15A and showed significant negative correlations with infiltrating levels of CD4+ T cells, CD8+ T cells, neutrophils, and macrophages. Our findings provided novel insights into biomarker discovery and the critical role of ribosomal biogenesis especially smaller ribosomal subunit in pathogenesis of LUSC.

Unravelling hub genes as potential therapeutic targets in lung cancer using integrated transcriptomic meta-analysis and in silico approach.

Lung cancer (LC) is the leading cause of cancer-related deaths worldwide. Smoking has been identified as the main contributing cause of the disease's development. The study aimed to identify the key genes in small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC), the two major types of LC. Meta-analysis was performed with two datasets GSE74706 and GSE149507 obtained from Gene Expression Omnibus (GEO). Both the datasets comprised samples from cancerous and adjacent non-cancerous tissues. Initially, 633 differentially expressed genes (DEGs) were identified. To understand the underlying molecular mechanism of the identified genes, pathway enrichment, gene ontology (GO) and protein-protein interaction (PPI) analyses were done. A total of 9 hub genes were identified which were subjected to mutation study analysis in LC patients using cBioPortal. These  9 genes (i.e. AURKA, AURKB, KIF23, RACGAP1, KIF2C, KIF20A, CENPE, TPX2 and PRC1) have shown overexpression in LC patients and can be explored as potential candidates for prognostic biomarkers. TPX2 reported a maximum mutation of 4%. This was followed with high throughput screening and docking analysis to identify the potential drug candidates following competitive inhibition of the AURKA-TPX2 complex. Four compounds, CHEMBL431482, CHEMBL2263042, CHEMBL2385714, and CHEMBL1206617 were identified. The results signify that the selected 9 genes can be explored as biomarkers in disease prognosis and targeted therapy. Also, the identified 4 compounds can be further analyzed as promising therapeutic candidates.Communicated by Ramaswamy H. Sarma.

Breast Cancer Prognostic Hub Genes Identified by Integrated Transcriptomic and Weighted Network Analysis: A Road Toward Personalized Medicine.

Breast cancer (BC) is the second-most common type and among the leading causes of worldwide cancer-related deaths. There is marked person-to-person variability in susceptibility to, and phenotypic expression and prognosis of BC, a predicament that calls for personalized medicine and individually tailored therapeutics. In this study, we report new observations on prognostic hub genes and key pathways involved in BC. We used the data set GSE109169, comprising 25 pairs of BC and adjacent normal tissues. Using a high-throughput transcriptomic approach, we selected data on 293 differentially expressed genes to establish a weighted gene coexpression network. We identified three age-linked modules where the light-gray module strongly correlated with BC. Based on the gene significance and module membership features, peptidase inhibitor 15 (PI15) and KRT5 were identified as our hub genes from the light-gray module. These genes were further verified at transcriptional and translational levels across 25 pairs of BC and adjacent normal tissues. Their promoter methylation profiles were assessed based on various clinical parameters. In addition, these hub genes were used for Kaplan-Meier survival analysis, and their correlation with tumor-infiltrating immune cells was investigated. We found that PI15 and KRT5 may be potential biomarkers and potential drug targets. These findings call for future research in a larger sample size, which could inform diagnosis and clinical management of BC, thus paving the way toward personalized medicine.

Exploring the role of miR-200 family in regulating CX3CR1 and CXCR1 in lung adenocarcinoma tumor microenvironment: implications for therapeutic intervention.

Lung adenocarcinoma (LUAD) is the most common malignant subtype of lung cancer (LC). miR-200 family is one of the prime miR regulators of epithelial-mesenchymal transition (EMT) and worst overall survival (OS) in LC patients. The study aimed to identify and validate the key differentially expressed immune-related genes (DEIRGs) regulated by miR-200 family which may serve for therapeutic aspects in LUAD tumor microenvironment (TME) by affecting cancer progression, invasion, and metastasis. The study identified differentially expressed miRNAs (DEMs) in LUAD, consisting of hsa-miR-200a-3p and hsa-miR-141-5p, respectively. Two highest-degree subnetwork motifs identified from 3-node miRNA FFL were: (i) miR-200a-3p-CX3CR1-SPIB and (ii) miR-141-5p-CXCR1-TBX21. TIMER analysis showed that the expression levels of CX3CR1 and CXCR1 were significantly positively correlated with infiltrating levels of M0-M2 macrophages and natural killer T (NKT) cells. The OS of LUAD patients was significantly affected by lower expression levels of hsa-miR-200a-3p, CX3CR1 and SPIB. These DEIRGs were validated using the human protein atlas (HPA) web server. Further, we validated the regulatory role of hsa-miR-200a-3p in an in-vitro indirect co-culture model using conditioned media from M0, M1 and M2 polarized macrophages (THP-1) and LUAD cell lines (A549 and H1299 cells). The results pointed out the essential role of hsa-miR-200a-3p regulated CX3CL1 and CX3CR1 expression in progression of LC TME. Thus, the study augments a comprehensive understanding and new strategies for LUAD treatment where miR-200 family regulated immune-related genes, especially chemokine receptors, which regulate the metastasis and invasion of LUAD, leading to the worst associated OS.

Investigating the link between miR-34a-5p and TLR6 signaling in sepsis-induced ARDS.

Acute lung injury (ALI)/acute respiratory distress syndrome (ARDS) are lung complications diagnosed by impaired gaseous exchanges leading to mortality. From the diverse etiologies, sepsis is a prominent contributor to ALI/ARDS. In the present study, we retrieved sepsis-induced ARDS mRNA expression profile and identified 883 differentially expressed genes (DEGs). Next, we established an ARDS-specific weighted gene co-expression network (WGCN) and picked the blue module as our hub module based on highly correlated network properties. Later we subjected all hub module DEGs to form an ARDS-specific 3-node feed-forward loop (FFL) whose highest-order subnetwork motif revealed one TF (STAT6), one miRNA (miR-34a-5p), and one mRNA (TLR6). Thereafter, we screened a natural product library and identified three lead molecules that showed promising binding affinity against TLR6. We then performed molecular dynamics simulations to evaluate the stability and binding free energy of the TLR6-lead molecule complexes. Our results suggest these lead molecules may be potential therapeutic candidates for treating sepsis-induced ALI/ARDS. In-silico studies on clinical datasets for sepsis-induced ARDS indicate a possible positive interaction between miR-34a and TLR6 and an antagonizing effect on STAT6 to promote inflammation. Also, the translational study on septic mice lungs by IHC staining reveals a hike in the expression of TLR6. We report here that miR-34a actively augments the effect of sepsis on lung epithelial cell apoptosis. This study suggests that miR-34a promotes TLR6 to heighten inflammation in sepsis-induced ALI/ARDS. Supplementary Information: The online version contains supplementary material available at 10.1007/s13205-023-03700-1.

Investigating the role of Kinesin family in lung adenocarcinoma via integrated bioinformatics approach.

Lung cancer is the leading cause of mortality from cancer worldwide. Lung adenocarcinoma (LUAD) is a type of non-small cell lung cancer (NSCLC) with highest prevalence. Kinesins a class of motor proteins are shown to be involved in carcinogenesis. We conducted expression, stage plot and survival analyses on kinesin superfamily (KIF) and scrutinized the key prognostic kinesins. Genomic alterations of these kinesins were studied thereafter via cBioPortal. A protein-protein interaction network (PPIN) of selected kinesins and 50 closest altering genes was constructed followed by gene ontology (GO) term and pathway enrichment analyses. Multivariate survival analysis based on CpG methylation of selected kinesins was performed. Lastly, we conducted tumor immune infiltration analysis. Our results found KIF11/15/18B/20A/2C/4A/C1 to be significantly upregulated and correlated with poor survival in LUAD patients. These genes also showed to be highly associated with cell cycle. Out of our seven selected kinesins, KIFC1 showed the highest genomic alteration with highest number of CpG methylation. Also, CpG island (CGI) cg24827036 was discovered to be linked to LUAD prognosis. Therefore, we deduced that reducing the expression of KIFC1 could be a feasible treatment strategy and that it can be a wonderful individual prognostic biomarker. CGI cg24827036 can also be used as a therapy site in addition to being a great prognostic biomarker.

Combined Multiomics and In Silico Approach Uncovers PRKAR1A as a Putative Therapeutic Target in Multi-Organ Dysfunction Syndrome.

Despite all epidemiological, clinical, and experimental research efforts, therapeutic concepts in sepsis and sepsis-induced multi-organ dysfunction syndrome (MODS) remain limited and unsatisfactory. Currently, gene expression data sets are widely utilized to discover new biomarkers and therapeutic targets in diseases. In the present study, we analyzed MODS expression profiles (comprising 13 sepsis and 8 control samples) retrieved from NCBI-GEO and found 359 differentially expressed genes (DEGs), among which 170 were downregulated and 189 were upregulated. Next, we employed the weighted gene co-expression network analysis (WGCNA) to establish a MODS-associated gene co-expression network (weighted) and identified representative module genes having an elevated correlation with age. Based on the results, a turquoise module was picked as our hub module. Further, we constructed the PPI network comprising 35 hub module DEGs. The DEGs involved in the highest-confidence PPI network were utilized for collecting pathway and gene ontology (GO) terms using various libraries. Nucleotide di- and triphosphate biosynthesis and interconversion was the most significant pathway. Also, 3 DEGs within our PPI network were involved in the top 5 significantly enriched ontology terms, with hypercortisolism being the most significant term. PRKAR1A was the overlapping gene between top 5 significant pathways and GO terms, respectively. PRKAR1A was considered as a therapeutic target in MODS, and 2992 ligands were screened for binding with PRKAR1A. Among these ligands, 3 molecules based on CDOCKER score (molecular dynamics simulated-based score, which allows us to rank the binding poses according to their quality and to identify the best pose for each system) and crucial interaction with human PRKAR1A coding protein and protein kinase-cyclic nucleotide binding domains (PKA RI alpha CNB-B domain) via active site binding residues, viz. Val283, Val302, Gln304, Val315, Ile327, Ala336, Ala337, Val339, Tyr373, and Asn374, were considered as lead molecules.

Mathematical modeling in perspective of vector-borne viral infections: a review.

Background: Viral diseases are highly widespread infections caused by viruses. These viruses are passing from one human to other humans through a certain medium. The medium might be mosquito, animal, reservoir and food, etc. Here, the population of both human and mosquito vectors are important. Main body of the abstract: The main objectives are here to introduce the historical perspective of mathematical modeling, enable the mathematical modeler to understand the basic mathematical theory behind this and present a systematic review on mathematical modeling for four vector-borne viral diseases using the deterministic approach. Furthermore, we also introduced other mathematical techniques to deal with vector-borne diseases. Mathematical models could help forecast the infectious population of humans and vectors during the outbreak. Short conclusion: This study will be helpful for mathematical modelers in vector-borne diseases and ready-made material in the review for future advancement in the subject. This study will not only benefit vector-borne conditions but will enable ideas for other illnesses.