microRNA 21 and long non-coding RNAs interplays underlie cancer pathophysiology: A narrative review

Non-coding RNAs (ncRNAs) are a diverse group of functional RNA molecules that lack the ability to code for proteins. Despite missing this traditional role, ncRNAs have emerged as crucial regulators of various biological processes and have been implicated in the development and progression of many diseases, including cancer. MicroRNAs (miRNAs) and long non-coding RNAs (lncRNAs) are two prominent classes of ncRNAs that have emerged as key players in cancer pathophysiology. In particular, miR-21 has been reported to exhibit oncogenic roles in various forms of human cancer, including prostate, breast, lung, and colorectal cancer. In this context, miR-21 overexpression is closely associated with tumor proliferation, growth, invasion, angiogenesis, and chemoresistance, whereas miR-21 inactivation is linked to the regression of most tumor-related processes. Accordingly, miR-21 is a crucial modulator of various canonical oncogenic pathways such as PTEN/PI3K/Akt, Wnt/β-catenin, STAT, p53, MMP2, and MMP9. Moreover, interplays between lncRNA and miRNA further complicate the regulatory mechanisms underlying tumor development and progression. In this regard, several lncRNAs have been found to interact with miR-21 and, by functioning as competitive endogenous RNAs (ceRNAs) or miRNA sponges, can modulate cancer tumorigenesis. This work presents and discusses recent findings highlighting the roles and pathophysiological implications of the miR-21-lncRNA regulatory axis in cancer occurrence, development, and progression. The data collected indicate that specific lncRNAs, such as MEG3, CASC2, and GAS5, are strongly associated with miR-21 in various types of cancer, including gastric, cervical, lung, and glioma. Indeed, these lncRNAs are well-known tumor suppressors and are commonly downregulated in different types of tumors. Conversely, by modulating various mechanisms and oncogenic signaling pathways, their overexpression has been linked with preventing tumor formation and development. This review highlights the significance of these regulatory pathways in cancer and their potential for use in cancer therapy as diagnostic and prognostic markers.

Expression analysis and mapping of Viral-Host Protein interactions of Poxviridae suggests a lead candidate molecule targeting Mpox

BACKGROUND

Monkeypox (Mpox) is an important human pathogen without etiological treatment. A viral-host interactome study may advance our understanding of molecular pathogenesis and lead to the discovery of suitable therapeutic targets.

METHODS

GEO Expression datasets characterizing mRNA profile changes in different host responses to poxviruses were analyzed for shared pathway identification, and then, the Protein-protein interaction (PPI) maps were built. The viral gene expression datasets of Monkeypox virus (MPXV) and Vaccinia virus (VACV) were used to identify the significant viral genes and further investigated for their binding to the library of targeting molecules.

RESULTS

Infection with MPXV interferes with various cellular pathways, including interleukin and MAPK signaling. While most host differentially expressed genes (DEGs) are predominantly downregulated upon infection, marked enrichments in histone modifiers and immune-related genes were observed. PPI analysis revealed a set of novel virus-specific protein interactions for the genes in the above functional clusters. The viral DEGs exhibited variable expression patterns in three studied cell types: primary human monocytes, primary human fibroblast, and HeLa, resulting in 118 commonly deregulated proteins. Poxvirus proteins C6R derived protein K7 and K7R of MPXV and VACV were prioritized as targets for potential therapeutic interventions based on their histone-regulating and immunosuppressive properties. In the computational docking and Molecular Dynamics (MD) experiments, these proteins were shown to bind the candidate small molecule S3I-201, which was further prioritized for lead development.

RESULTS

MPXV circumvents cellular antiviral defenses by engaging histone modification and immune evasion strategies. C6R-derived protein K7 binding candidate molecule S3I-201 is a priority promising candidate for treating Mpox.

A new horizon in the phosphorylated sites of AGA: the structural impact of C163S mutation in aspartylglucosaminuria through molecular dynamics simulation

Aspartylglucosaminuria (AGU) is a lysosomal storage disorder caused by insufficient aspartylglucosaminidase (AGA) activity leading to chronic neurodegeneration. We utilized the PhosphoSitePlus tool to identify the AGA protein's phosphorylation sites. The phosphorylation was induced on the specific residue of the three-dimensional AGA protein, and the structural changes upon phosphorylation were studied via molecular dynamics simulation. Furthermore, the structural behaviour of C163S mutation and C163S mutation with adjacent phosphorylation was investigated. We have examined the structural impact of phosphorylated forms and C163S mutation in AGA. Molecular dynamics simulations (200 ns) exposed patterns of deviation, fluctuation, and change in compactness of Y178 phosphorylated AGA protein (Y178-p), T215 phosphorylated AGA protein (T215-p), T324 phosphorylated AGA protein (T324-p), C163S mutant AGA protein (C163S), and C163S mutation with Y178 phosphorylated AGA protein (C163S-Y178-p). Y178-p, T215-p, and C163S mutation demonstrated an increase in intramolecular hydrogen bonds, leading to greater compactness of the AGA forms. Principle component analysis (PCA) and Gibbs free energy of the phosphorylated/C163S mutation structures exhibit transition in motion/orientation than Wild type (WT). T215-p may be more dominant among these than the other studied phosphorylated forms. It might contribute to hydrolyzing L-asparagine functioning as an asparaginase, thereby regulating neurotransmitter activity. This study revealed structural insights into the phosphorylation of Y178, T215, and T324 in AGA protein. Additionally, it exposed the structural changes of the C163S mutation and C163S-Y178-p of AGA protein. This research will shed light on a better understanding of AGA's phosphorylated mechanism.Communicated by Ramaswamy H. Sarma.

Rational design of a multivalent vaccine targeting arthropod-borne viruses using reverse vaccinology strategies

Viruses transmitted by arthropods, such as Dengue, Zika, and Chikungunya, represent substantial worldwide health threats, particularly in countries like India. The lack of approved vaccines and effective antiviral therapies calls for developing innovative strategies to tackle these arboviruses. In this study, we employed immunoinformatics methodologies, incorporating reverse vaccinology, to design a multivalent vaccine targeting the predominant arboviruses. Epitopes of B and T cells were recognized within the non-structural proteins of Dengue, Zika, and Chikungunya viruses. The predicted epitopes were enhanced with adjuvants β-defensin and RS-09 to boost the vaccine's immunogenicity. Sixteen distinct vaccine candidates were constructed, each incorporating epitopes from all three viruses. FUVAC-11 emerged as the most promising vaccine candidate through molecular docking and molecular dynamics simulations, demonstrating favorable binding interactions and stability. Its effectiveness was further evaluated using computational immunological studies confirming strong immune responses. The in silico cloning performed using the pET-28a(+) plasmid facilitates the future experimental implementation of this vaccine candidate, paving the way for potential advancements in combating these significant arboviral threats. However, further in vitro and in vivo studies are warranted to confirm the results obtained in this computational study, which highlights the effectiveness of immunoinformatics and reverse vaccinology in creating vaccines against major Arboviruses, offering a promising model for developing vaccines for other vector-borne diseases and enhancing global health security.

Genomic insights and advanced machine learning: characterizing autism spectrum disorder biomarkers and genetic interactions

Autism Spectrum Disorder (ASD) is a complex neurodevelopmental condition characterized by altered brain connectivity and function. In this study, we employed advanced bioinformatics and explainable AI to analyze gene expression associated with ASD, using data from five GEO datasets. Among 351 neurotypical controls and 358 individuals with autism, we identified 3,339 Differentially Expressed Genes (DEGs) with an adjusted p-value (≤ 0.05). A subsequent meta-analysis pinpointed 342 DEGs (adjusted p-value ≤ 0.001), including 19 upregulated and 10 down-regulated genes across all datasets. Shared genes, pathogenic single nucleotide polymorphisms (SNPs), chromosomal positions, and their impact on biological pathways were examined. We identified potential biomarkers (HOXB3, NR2F2, MAPK8IP3, PIGT, SEMA4D, and SSH1) through text mining, meriting further investigation. Additionally, ‎we shed light on the roles of RPS4Y1 and KDM5D genes in neurogenesis and neurodevelopment. Our analysis detected 1,286 SNPs linked to ASD-related conditions, of which 14 high-risk SNPs were located on chromosomes 10 and X. We highlighted potential missense SNPs associated with FGFR inhibitors, suggesting that it may serve as a promising biomarker for responsiveness to targeted therapies. Our explainable AI model identified the MID2 gene as a potential ASD biomarker. This research unveils vital genes and potential biomarkers, providing a foundation for novel gene discovery in complex diseases.

Management of chronic myeloid leukaemia: current treatment options, challenges, and future strategies

ABSTRACTSmall molecule therapy is a critical component of targeted anticancer treatment, with tyrosine kinase inhibitors (TKIs) being the first compounds to treat the clonal Chronic Myelogenous Leukaemia (CML) translocation t (9;22) (q34; q11) effectively since 2001. TKIs, such as imatinib, have improved the 10-year survival rate of CML patients to 80%. They bind the BCR::ABL1 kinase and inhibit downstream signaling pathways. However, therapy failure may be seen in 20-25% of CML patients due to intolerance or inadequacy related to BCR::ABL1 dependent or independent mechanisms. This review aimed to summarize current treatment options involving TKIs, resistance mechanisms and the prospective approaches to overcome TKI resistance. We highlight BCR::ABL1-dependent mechanisms of TKI resistance by reviewing clinically-documented BCR::ABL1 mutations and their consequences for TKI binding. In addition, we summarize BCR::ABL1 independent pathways, including the relevance of drug efflux, dysregulation of microRNA, and the involvement of alternative signaling pathways. We also discuss future approaches, such as gene-editing techniques in the context of CML, as potential therapeutic strategies.

Identification of Potential Inhibitors Targeting GTPase-Kirsten RAt Sarcoma Virus (K-Ras) Driven Cancers via E-Pharmacophore-Based Virtual Screening and Drug Repurposing Approach

BACKGROUND

Mutations in the K-Ras gene are among the most frequent genetic alterations in various cancers, and inhibiting RAS signaling has shown promising results in treating solid tumors. However, finding effective drugs that can bind to the RAS protein remains challenging. This drove us to explore new compounds that could inhibit tumor growth, particularly in cancers that harbor K-Ras mutations.

METHODS

Our study used bioinformatic techniques such as E-pharmacophore virtual screening, molecular simulation, principal component analysis (PCA), extra precision (XP) docking, and ADMET analyses to identify potential inhibitors for K-Ras mutants G12C and G12D.

RESULTS

In our study, we discovered that inhibitors such as afatinib, osimertinib, and hydroxychloroquine strongly inhibit the G12C mutant. Similarly, hydroxyzine, zuclopenthixol, fluphenazine, and doxapram were potent inhibitors for the G12D mutant. Notably, all six of these molecules exhibit a high binding affinity for the H95 cryptic groove present in the mutant structure. These molecules exhibited a unique affinity mechanism at the molecular level, which was further enhanced by hydrophobic interactions. Molecular simulations and PCA revealed the formation of stable complexes within switch regions I and II. This was particularly evident in three complexes: G12C-osimertinib, G12D-fluphenazine, and G12D-zuclopenthixol. Despite the dynamic nature of switches I and II in K-Ras, the interaction of inhibitors remained stable. According to QikProp results, the properties and descriptors of the selected molecules fell within an acceptable range compared to sotorasib.

CONCLUSIONS

We have successfully identified potential inhibitors of the K-Ras protein, laying the groundwork for the development of targeted therapies for cancers driven by K-Ras mutations.

Single-cell transcriptomic analysis reveals crucial oncogenic signatures and its associative cell types involved in gastric cancer

The intricate association of oncogenic markers negatively impacts accurate gastric cancer diagnosis and leads to the proliferation of mortality rate. Molecular heterogeneity is inevitable in determining gastric cancer's progression state with multiple cell types involved. Identification of pathogenic gene signatures is imperative to understand the disease's etiology. This study demonstrates a systematic approach to identifying oncogenic gastric cancer genes linked with different cell types. The raw counts of adjacent normal and gastric cancer samples are subjected to a quality control step. The dimensionality reduction and multidimensional clustering are performed using Principal Component Analysis (PCA) and Uniform Manifold Approximation and Projection (UMAP) techniques. The adjacent normal and gastric cancer sample cell clusters are annotated with the Human Primary Cell Atlas database using the "SingleR." Cellular state transition between the distinct groups is characterized using trajectory analysis. The ligand-receptor interaction between Vascular Endothelial Growth Factor (VEGF) and cell clusters unveils crucial molecular pathways in gastric cancer progression. Chondrocytes, Smooth muscle cells, and fibroblast cell clusters contain genes contributing to poor survival rates based on hazard ratio during survival analysis. The GC-related oncogenic signatures are isolated by comparing the gene set with the DisGeNET database. Twelve gastric cancer biomarkers (SPARC, KLF5, HLA-DRB1, IGFBP3, TIMP3, LGALS1, IGFBP6, COL18A1, F3, COL4A1, PDGFRB, COL5A2) are linked with gastric cancer and further validated through gene set enrichment analysis. Drug-gene interaction found PDGFRB, interacting with various anti-cancer drugs, as a potential inhibitor for gastric cancer. Further investigations on these molecular signatures will assist the development of precision therapeutics, promising longevity among gastric cancer patients.

Potential Therapeutic Targets of Resveratrol in the Prevention and Treatment of Pulmonary Fibrosis

Pulmonary fibrosis (PF) is a feared component in over 200 interstitial pulmonary diseases, which are characterized by increased alveolar wall thickness, excessive scarring, and aberrant extracellular matrix restructuring that, ultimately, affect lung compliance and capacity. As a result of its broad range of biological activities, including antioxidant, anti-inflammatory, antiapoptotic, and many others, resveratrol has been shown to be an effective treatment for respiratory system diseases, including interstitial lung disease, infectious diseases, and lung cancer. This work reviews the known molecular therapeutic targets of resveratrol and its potential mechanisms of action in attenuating PF in respiratory diseases, including cancer, COVID-19, interstitial lung diseases (ILDs) of known etiologies, idiopathic interstitial pneumonia, and ILDs associated with systemic disorders, such as rheumatoid arthritis, systemic sclerosis, Schrödinger's syndrome, systemic lupus erythematosus, and pulmonary hypertension. The current issues and controversies related to the possible use of resveratrol as a pharmaceutical drug or supplement are also discussed.

Airway and Oral microbiome profiling of SARS-CoV-2 infected asthma and non-asthma cases revealing alterations-A pulmonary microbial investigation

New evidence strongly discloses the pathogenesis of host-associated microbiomes in respiratory diseases. The microbiome dysbiosis modulates the lung's behavior and deteriorates the respiratory system's effective functioning. Several exogenous and environmental factors influence the development of asthma and chronic lung disease. The relationship between asthma and microbes is reasonably understood and yet to be investigated for more substantiation. The comorbidities such as SARS-CoV-2 further exacerbate the health condition of the asthma-affected individuals. This study examines the raw 16S rRNA sequencing data collected from the saliva and nasopharyngeal regions of pre-existing asthma (23) and non-asthma patients (82) infected by SARS-CoV-2 acquired from the public database. The experiment is designed in a two-fold pattern, analyzing the associativity between the samples collected from the saliva and nasopharyngeal regions. Later, investigates the microbial pathogenesis, its role in exacerbations of respiratory disease, and deciphering the diagnostic biomarkers of the target condition. LEfSE analysis identified that Actinobacteriota and Pseudomonadota are enriched in the SARS-CoV-2-non-asthma group and SARS-CoV-2 asthma group of the salivary microbiome, respectively. Random forest algorithm is trained with amplicon sequence variants (ASVs) attained better classification accuracy, ROC scores on nasal (84% and 87%) and saliva datasets (93% and 97.5%). Rothia mucilaginosa is less abundant, and Corynebacterium tuberculostearicum showed higher abundance in the SARS-CoV-2 asthma group. The increase in Streptococcus at the genus level in the SARS-CoV-2-asthma group is evidence of discriminating the subgroups.

Helicobacter pylori and epithelial mesenchymal transition in human gastric cancers: An update of the literature

Gastric cancer, a multifactorial disease, is considered one of the most common malignancies worldwide. In addition to genetic and environmental risk factors, infectious agents, such as Epstein-Barr virus (EBV) and Helicobacter pylori (H.pylori) contribute to the onset and development of gastric cancer. H. pylori is a type I carcinogen that colonizes the gastric epithelium of approximately 50% of the world's population, thus increasing the risk of gastric cancer development. On the other hand, epithelial mesenchymal transition (EMT) is a fundamental process crucial to embryogenic growth, wound healing, organ fibrosis and cancer progression. Several studies associate gastric pathogen infection of the epithelium with EMT initiation, provoking cancer metastasis in the gastric mucosa through various molecular signaling pathways. Additionally, EMT is implicated in the progression and development of H. pylori-associated gastric cancer. In this review, we recapitulate recent findings elucidating the association between H. pylori infection in EMT promotion leading to gastric cancer progression and metastasis.

Association of single nucleotide polymorphisms with dyslipidemia and risk of metabolic disorders in the State of Qatar

BACKGROUND

Dyslipidemia is recognized as one of the risk factors of cardiovascular diseases (CVDs), type 2 diabetes mellitus (T2DM), and non-alcoholic fatty liver disease (NAFLD).

OBJECTIVE

The study aimed to investigate the association between selected single nucleotide polymorphisms (SNPs) with dyslipidemia and increased susceptibility risks of CVD, NAFLD, and/or T2DM in dyslipidemia patients in comparison with healthy control individuals from the Qatar genome project.

METHODS

A community-based cross-sectional study was conducted among 2933 adults (859 dyslipidemia patients and 2074 healthy control individuals) from April to December 2021 to investigate the association between 331 selected SNPs with dyslipidemia and increased susceptibility risks of CVD, NAFLD and/or T2DM, and covariates.

RESULTS

The genotypic frequencies of six SNPs were found to be significantly different in dyslipidemia patients subjects compared to the control group among males and females. In males, three SNPs were found to be significant, the rs11172113 in over-dominant model, the rs646776 in recessive and over-dominant models, and the rs1111875 in dominant model. On the other hand, two SNPs were found to be significant in females, including rs2954029 in recessive model, and rs1801251 in dominant and recessive models. The rs17514846 SNP was found for dominant and over-dominant models among males and only the dominant model for females. We found that the six SNPs linked to gender type had an influence in relation to disease susceptibility. When controlling for the four covariates (gender, obesity, hypertension, and diabetes), the difference between dyslipidemia and the control group remained significant for the six variants. Finally, males were three times more likely to have dyslipidemia in comparison with females, hypertension was two times more likely to be present in the dyslipidemia group, and diabetes was six times more likely to be in the dyslipidemia group.

CONCLUSION

The current investigation provides evidence of association for a common SNP to coronary heart disease and suggests a sex-dependent effect and encourage potential therapeutic applications.

Exome sequence analysis of rare frequency variants in Late-Onset Alzheimer Disease

Alzheimer disease (AD) is a leading cause of dementia in elderly patients who continue to live between 3 and 11 years of diagnosis. A steep rise in AD incidents is observed in the elderly population in East-Asian countries. The disease progresses through several changes, including memory loss, behavioural issues, and cognitive impairment. The etiology of AD is hard to determine because of its complex nature. The whole exome sequences of late-onset AD (LOAD) patients of Korean origin are investigated to identify rare genetic variants that may influence the complex disorder. Computational annotation was performed to assess the function of candidate variants in LOAD. The in silico pathogenicity prediction tools such as SIFT, Polyphen-2, Mutation Taster, CADD, LRT, PROVEAN, DANN, VEST3, fathmm-MKL, GERP +  + , SiPhy, phastCons, and phyloP identified around 17 genes harbouring deleterious variants. The variants in the ALDH3A2 and RAD54B genes were pathogenic, while in 15 other genes were predicted to be variants of unknown significance. These variants can be potential risk candidates contributing to AD. In silico computational techniques such as molecular docking, molecular dynamic simulation and steered molecular dynamics were carried out to understand the structural insights of RAD54B with ATP. The simulation of mutant (T459N) RAD54B with ATP revealed reduced binding strength of ATP at its binding site. In addition, lower binding free energy was observed when compared to the wild-type RAD54B. Our study shows that the identified uncommon variants are linked to AD and could be probable predisposing genetic factors of LOAD.

Therapeutic and diagnostic applications of exosomal circRNAs in breast cancer

Circular RNAs (circRNAs) are regulatory elements that are involved in orchestrating gene expression and protein functions and are implicated in various biological processes including cancer. Notably, breast cancer has a significant mortality rate and is one of the most common malignancies in women. CircRNAs have been demonstrated to contribute to the pathogenesis of breast cancer including its initiation, progression, metastasis, and resistance to drugs. By acting as miRNA sponges, circRNAs can indirectly influence gene expression by disrupting miRNA regulation of their target genes, ultimately altering the course of cancer development and progression. Additionally, circRNAs can interact with proteins and modulate their functions including signaling pathways involved in the initiation and development of cancer. Recently, circRNAs can encode peptides that play a role in the pathophysiology of breast cancer and other diseases and their potential as diagnostic biomarkers and therapeutic targets for various cancers including breast cancer. CircRNAs possess biomarkers that differentiate, such as stability, specificity, and sensitivity, and can be detected in several biological specimens such as blood, saliva, and urine. Moreover, circRNAs play an important role in various cellular processes including cell proliferation, differentiation, and apoptosis, all of which are integral factors in the development and progression of cancer. This review synthesizes the functions of circRNAs in breast cancer, scrutinizing their contributions to the onset and evolution of the disease through their interactions with exosomes and cancer-related intracellular pathways. It also delves into the potential use of circRNA as a biomarker and therapeutic target against breast cancer. It discusses various databases and online tools that offer crucial circRNA information and regulatory networks. Lastly, the challenges and prospects of utilizing circRNAs in clinical settings associated with breast cancer are explored.

Evolving strategies and application of proteins and peptide therapeutics in cancer treatment

Several proteins and peptides have therapeutic potential and can be used for cancer therapy. By binding to cell surface receptors and other indicators uniquely linked with or overexpressed on tumors compared to healthy tissue, protein biologics enhance the active targeting of cancer cells, as opposed to the passive targeting of cells by conventional small-molecule chemotherapeutics. This study focuses on peptide medications that exist to slow or stop tumor growth and the spread of cancer, demonstrating the therapeutic potential of peptides in cancer treatment. As an alternative to standard chemotherapy, peptides that selectively kill cancer cells while sparing healthy tissue are developing. A mountain of clinical evidence supports the efficacy of peptide-based cancer vaccines. Since a single treatment technique may not be sufficient to produce favourable results in the fight against cancer, combination therapy is emerging as an effective option to generate synergistic benefits. One example of this new area is the use of anticancer peptides in combination with nonpeptidic cytotoxic drugs or the combination of immunotherapy with conventional therapies like radiation and chemotherapy. This review focuses on the different natural and synthetic peptides obtained and researched. Discoveries, manufacture, and modifications of peptide drugs, as well as their contemporary applications, are summarized in this review. We also discuss the benefits and difficulties of potential advances in therapeutic peptides.

An updated overview of cyanidins for chemoprevention and cancer therapy

Anthocyanins are colored polyphenolic compounds that belong to the flavonoids family and are largely present in many vegetables and fruits. They have been used in traditional medicine in many cultures for a long time. The most common and abundant anthocyanins are those presenting an O-glycosylation at C-3 (C ring) of the flavonoid skeleton to form -O-β-glucoside derivatives. The present comprehensive review summarized recent data on the anticancer properties of cyanidings along with natural sources, phytochemical data, traditional medical applications, molecular mechanisms and recent nanostrategies to increase the bioavailability and anticancer effects of cyanidins. For this analysis, in vitro, in vivo and clinical studies published up to the year 2022 were sourced from scientific databases and search engines such as PubMed/Medline, Google scholar, Web of Science, Scopus, Wiley and TRIP database. Cyanidins' antitumor properties are exerted during different stages of carcinogenesis and are based on a wide variety of biological activities. The data gathered and discussed in this review allows for affirming that cyanidins have relevant anticancer activity in vitro, in vivo and clinical studies. Future research should focus on studies that bring new data on improving the bioavailability of anthocyanins and on conducting detailed translational pharmacological studies to accurately establish the effective anticancer dose in humans as well as the correct route of administration.

Unraveling the Dysbiosis of Vaginal Microbiome to Understand Cervical Cancer Disease Etiology-An Explainable AI Approach

Microbial Dysbiosis is associated with the etiology and pathogenesis of diseases. The studies on the vaginal microbiome in cervical cancer are essential to discern the cause and effect of the condition. The present study characterizes the microbial pathogenesis involved in developing cervical cancer. Relative species abundance assessment identified Firmicutes, Actinobacteria, and Proteobacteria dominating the phylum level. A significant increase in Lactobacillus iners and Prevotella timonensis at the species level revealed its pathogenic influence on cervical cancer progression. The diversity, richness, and dominance analysis divulges a substantial decline in cervical cancer compared to control samples. The β diversity index proves the homogeneity in the subgroups' microbial composition. The association between enriched Lactobacillus iners at the species level, Lactobacillus, Pseudomonas, and Enterococcus genera with cervical cancer is identified by Linear discriminant analysis Effect Size (LEfSe) prediction. The functional enrichment corroborates the microbial disease association with pathogenic infections such as aerobic vaginitis, bacterial vaginosis, and chlamydia. The dataset is trained and validated with repeated k-fold cross-validation technique using a random forest algorithm to determine the discriminative pattern from the samples. SHapley Additive exPlanations (SHAP), a game theoretic approach, is employed to analyze the results predicted by the model. Interestingly, SHAP identified that the increase in Ralstonia has a higher probability of predicting the sample as cervical cancer. New evidential microbiomes identified in the experiment confirm the presence of pathogenic microbiomes in cervical cancer vaginal samples and their mutuality with microbial imbalance.

Integrated gene network analysis sheds light on understanding the progression of Osteosarcoma

Introduction

Osteosarcoma is a rare disorder among cancer, but the most frequently occurring among sarcomas in children and adolescents. It has been reported to possess the relapsing capability as well as accompanying collateral adverse effects which hinder the development process of an effective treatment plan. Using networks of omics data to identify cancer biomarkers could revolutionize the field in understanding the cancer. Cancer biomarkers and the molecular mechanisms behind it can both be understood by studying the biological networks underpinning the etiology of the disease.

Methods

In our study, we aimed to highlight the hub genes involved in gene-gene interaction network to understand their interaction and how they affect the various biological processes and signaling pathways involved in Osteosarcoma. Gene interaction network provides a comprehensive overview of functional gene analysis by providing insight into how genes cooperatively interact to elicit a response. Because gene interaction networks serve as a nexus to many biological problems, their employment of it to identify the hub genes that can serve as potential biomarkers remain widely unexplored. A dynamic framework provides a clear understanding of biological complexity and a pathway from the gene level to interaction networks.

Results

Our study revealed various hub genes viz. TP53, CCND1, CDK4, STAT3, and VEGFA by analyzing various topological parameters of the network, such as highest number of interactions, average shortest path length, high cluster density, etc. Their involvement in key signaling pathways, such as the FOXM1 transcription factor network, FAK-mediated signaling events, and the ATM pathway, makes them significant candidates for studying the disease. The study also highlighted significant enrichment in GO terms (Biological Processes, Molecular Function, and Cellular Processes), such as cell cycle signal transduction, cell communication, kinase binding, transcription factor activity, nucleoplasm, PML body, nuclear body, etc.

Conclusion

To develop better therapeutics, a specific approach toward the disease targeting the hub genes involved in various signaling pathways must have opted to unravel the complexity of the disease. Our study has highlighted the candidate hub genes viz. TP53, CCND1 CDK4, STAT3, VEGFA. Their involvement in the major signaling pathways of Osteosarcoma makes them potential candidates to be targeted for drug development. The highly enriched signaling pathways include FOXM1 transcription pathway, ATM signal-ling pathway, FAK mediated signaling events, Arf6 signaling events, mTOR signaling pathway, and Integrin family cell surface interactions. Targeting the hub genes and their associated functional partners which we have reported in our studies may be efficacious in developing novel therapeutic targets.

Identification of potential circadian genes and associated pathways in colorectal cancer progression and prognosis using microarray gene expression analysis

Colorectal cancer (CRC) is third cancer causing death in the world. CRC is associated with disrupting the circadian rhythm (CR), closely associating the CRC progression and the dysregulation of genes involved in the biological clock. In this study, we aimed to understand the circadian rhythm changes in patients diagnosed with CRC. We used the GEO database with the ID GSE46549 for our analysis, which consists of 32 patients with CRC and one as normal control. Our study has identified five essential genes involved in CRC, HAPLN1, CDH12, IGFBP5, DCHS2, and DOK5, and had different enriched pathways, such as the Wnt-signaling pathway, at different time points of study. As a part of our study, we also identified various related circadian genes, such as CXCL12, C1QTNF2, MRC2, and GLUL, from the Circadian Gene Expression database, that played a role in circadian rhythm and CRC development. As circadian timing can influence the host tissue's ability to tolerate anticancer medications, the genes reported can serve as a potential drug target for treating CRC and become beneficial to translational settings.

Elucidating the mechanism of antimicrobial resistance in Mycobacterium tuberculosis using gene interaction networks

Antimicrobial resistance (AMR) in microorganisms is an urgent global health threat. AMR of Mycobacterium tuberculosis is associated with significant morbidity and mortality. It is of great importance to underpin the resistance pathways involved in the mechanisms of AMR and identify the genes that are directly involved in AMR. The focus of the current study was the bacteria M. tuberculosis, which carries AMR genes that give resistance that lead to multidrug resistance. We, therefore, built a network of 43 genes and examined for potential gene-gene interactions. Then we performed a clustering analysis and identified three closely related clusters that could be involved in multidrug resistance mechanisms. Through the bioinformatics pipeline, we consistently identified six-hub genes (dnaN, polA, ftsZ, alr, ftsQ, and murC) that demonstrated the highest number of interactions within the clustering analysis. This study sheds light on the multidrug resistance of MTB and provides a protocol for discovering genes that might be involved in multidrug resistance, which will improve the treatment of resistant strains of TB.

Molecular characterization of circadian gene expression and its correlation with survival percentage in colorectal cancer patients

Colorectal cancer (CRC) is a form of cancer characterized by many symptoms and readily metastasizes to different organs in the body. Circadian rhythm is one of the many processes that is observed to be dysregulated in CRC-affected patients. In this study, we aim to identify the dysregulated physiological processes in CRC-affected patients and correlate the expression profiles of the circadian clock genes with CRC-patients' survival rates. We performed an extensive microarray gene expression pipeline, whereby 471 differentially expressed genes (DEGs) were identified, following which, we streamlined our search to 43 circadian clock affecting DEGs. The Circadian Gene Database was accessed to retrieve the circadian rhythm-specific genes. The DEGs were then subjected to multi-level functional annotation, i.e., preliminary analysis using ClueGO/CluePedia and pathway enrichment using DAVID. The findings of our study were interesting, wherein we observed that the survival percentage of CRC-affected patients dropped significantly around the 100th-month mark. Furthermore, we identified hormonal activity, xenobiotic metabolism, and PI3K-Akt signaling pathway to be frequently dysregulated cellular functions. Additionally, we detected that the ZFYVE family of genes and the two genes, namely MYC and CDK4 were the significant DEGs that are linked to the pathogenesis and progression of CRC. This study sheds light on the importance of bioinformatics to simplify our understanding of the interactions of different genes that control different phenotypes.

Implications and theragnostic potentials of circular RNAs in rheumatic diseases

Circular RNAs (circRNAs), a class of non-coding RNAs (ncRNAs), are highly stable and ubiquitous molecules that exhibit tissue-specific expression. Accumulating evidence has shown that aberrant expression of circRNAs can play a role in the pathogenesis of several diseases. Rheumatic diseases are a varied group of autoimmune and inflammatory disorders affecting mainly the musculoskeletal system. Notably, circRNAs, which are essential immune system gene modulators, are strongly linked to the occurrence and progression of autoimmune disorders. Here, we present and discuss the current findings concerning the roles, implications and theragnostic potentials of circRNAs in common rheumatic diseases, including ankylosing spondylitis (AS), osteoarthritis (OA), osteoporosis (OP), rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), Crohn's disease (CD), and gout. This review aims to provide new insights to support the development of novel diagnostic and therapeutic strategies for these disabling diseases.

Bioinformatics investigation on blood-based gene expressions of Alzheimer's disease revealed ORAI2 gene biomarker susceptibility: An explainable artificial intelligence-based approach

The progressive, chronic nature of Alzheimer's disease (AD), a form of dementia, defaces the adulthood of elderly individuals. The pathogenesis of the condition is primarily unascertained, turning the treatment efficacy more arduous. Therefore, understanding the genetic etiology of AD is essential to identifying targeted therapeutics. This study aimed to use machine-learning techniques of expressed genes in patients with AD to identify potential biomarkers that can be used for future therapy. The dataset is accessed from the Gene Expression Omnibus (GEO) database (Accession Number: GSE36980). The subgroups (AD blood samples from frontal, hippocampal, and temporal regions) are individually investigated against non-AD models. Prioritized gene cluster analyses are conducted with the STRING database. The candidate gene biomarkers were trained with various supervised machine-learning (ML) classification algorithms. The interpretation of the model prediction is perpetrated with explainable artificial intelligence (AI) techniques. This experiment revealed 34, 60, and 28 genes as target biomarkers of AD mapped from the frontal, hippocampal, and temporal regions. It is identified ORAI2 as a shared biomarker in all three areas strongly associated with AD's progression. The pathway analysis showed that STIM1 and TRPC3 are strongly associated with ORAI2. We found three hub genes, TPI1, STIM1, and TRPC3, in the network of the ORAI2 gene that might be involved in the molecular pathogenesis of AD. Naive Bayes classified the samples of different groups by fivefold cross-validation with 100% accuracy. AI and ML are promising tools in identifying disease-associated genes that will advance the field of targeted therapeutics against genetic diseases.

Non-coding RNAs as biomarkers of myocardial infarction

Non-coding RNAs (ncRNAs) encompass a family of ubiquitous RNA molecules that lack protein-coding potential and have tissue-specific expression. A significant body of evidence indicates that ncRNA's aberrant expression plays a critical role in disease onset and development. NcRNAs' biochemical characteristics such as disease-associated concentration changes, structural stability, and high abundance in body fluids make them promising prognostic and diagnostic biomarkers. Myocardial infarction (MI) is a leading cause of mortality worldwide. Acute myocardial infarction (AMI), the term in use to describe MI's early phase, is generally diagnosed by physical examination, electrocardiogram (ECG), and the presence of specific biomarkers. In this regard, compared to standard MI biomarkers, such as the cardiac troponin isoforms (cTnT & cTnI) and the Creatinine Kinase (CK), ncRNAs appears to provide better sensitivity and specificity, ensuring a rapid and correct diagnosis, an earlier treatment, and consequently a good prognosis for the patients. This review aims to summarize and discuss the most promising and recent data on the potential clinical use of circulating ncRNAs as MI biomarkers. Specifically, we focused primarily on miRNAs and lncRNAs, highlighting their significant specificity and sensitivity, discussing their limitations, and suggesting possible overcoming approaches.

Effect of Resveratrol on Pregnancy, Prenatal Complications and Pregnancy-Associated Structure Alterations

Adverse pregnancy outcomes are considered significant health risks for pregnant women and their offspring during pregnancy and throughout their lifespan. These outcomes lead to a perturbated in-utero environment that impacts critical phases of the fetus's life and correlates to an increased risk of chronic pathological conditions, such as diabetes, obesity, and cardiovascular diseases, in both the mother's and adult offspring's life. The dietary intake of naturally occurring antioxidants promotes health benefits and disease prevention. In this regard, maternal dietary intake of polyphenolic antioxidants is linked to a reduced risk of maternal obesity and cardio-metabolic disorders, positively affecting both the fetus and offspring. In this work, we will gather and critically appraise the current literature highlighting the effect/s of the naturally occurring polyphenol antioxidant resveratrol on oxidative stress, inflammation, and other molecular and physiological phenomena associated with pregnancy and pregnancy conditions, such as gestational diabetes, preeclampsia, and preterm labor. The resveratrol impact on prenatal complications and pregnancy-associated structures, such as the fetus and placenta, will also be discussed. Finally, we will draw conclusions from the current knowledge and provide future perspectives on potentially exploiting resveratrol as a therapeutic tool in pregnancy-associated conditions.

Identification of dysregulated canonical pathways associated with pathogenesis and progression of Amyotrophic Lateral Sclerosis-An integrated bioinformatics approach

The mechanisms responsible for the pathogenesis and progression of Amyotrophic Lateral Sclerosis (ALS) remain poorly understood, making the diagnosis of ALS challenging. We aimed to find the novel gene biomarkers via computationally analyzing microarray expression studies, in three different cell lineages, namely myotube cells, astrocyte cells and oligodendrocyte cells. Microarray gene expression profiles were obtained and analyzed for three cell types: myotube cell lineage (GSE122261), astrocyte, and oligodendrocyte cell lineage (GSE87385). A comprehensive computational pipeline, tailored explicitly for microarray gene expression profiling studies, was devised to analyze the sample groups, wherein the myotube sample group comprised of six control (GSM3462697, GSM3462698, GSM3462699, GSM3462700, GSM3462701, GSM3462702) & six diseased (GSM3462691, GSM3462692, GSM3462693, GSM3462694, GSM3462695, GSM3462696) samples were considered. Similarly, for the astrocyte sample group two samples each for the control (GSM2330040, GSM2330042) and the diseased (GSM2330039, GSM2330041), and for the oligodendrocyte sample group, 2 control (GSM2330043, GSM2330045) samples and two diseased (GSM2330044, GSM2330046) samples were considered for the current study. The in-depth interaction of these DEGs was studied using MCODE and subjected to preliminary functional analysis using ClueGO/CluePedia plug-in. Qiagen's IPA software was employed for enrichment analysis, which generated the key canonical pathways and a list of potential biomarker molecules specific to each sample group. The preliminary analysis yielded 512 DEGs across all 3-sample groups, wherein 139 DEGs belonged to the myotube sample group, 216 DEGs for the astrocyte sample group, and 157 DEGs for the oligodendrocytes sample group. The data suggests growth hormone signaling and its activity, ErbB signaling pathway, and JAK/STAT signaling pathway are some of the pathways that are significantly dysregulated and play a crucial role in the development and progression of ALS. KISS1R and CSHL1 are potential genes that could act as diagnostic biomarkers in myotube cell types. Also, KRAS, TGFB2, JUN, and SMAD6 genes may be used as prognostic biomarkers to differentiate between early and late-stage ALS-diseased patients.

Analysis of signaling cascades from myeloma cells treated with pristimerin

Multiple myeloma (MM) is the 2nd most frequently diagnosed blood cancer after non-Hodgkin's lymphoma. The present study aimed to identify the differentially expressed genes (DEGs) between the control and pristimerin-treated MM cell lines. We examined the GSE14011 microarray dataset and screened DEGs with GEO2R statistical tool using the inbuilt limma package. We used a bioinformatics pipeline to identify the differential networks, signaling cascades, and the survival of the hub genes. We implemented two different enrichment analysis including ClueGO and Metacore™, to get accurate annotation for most significant DEGs. We screened the most significant 408 DEGs from the dataset based on p-values and logFC values. Using protein network analysis, we found the genes UBC, HSP90AB1, HSPH1, HSPA1B, HSPA1L, HSPA6, HSPD1, DNAJB1, HSPE1, DNAJC10, BAG3, and DNAJC7 had higher node degree distribution. In contrast, the functional annotation provided that the DEGs were predominantly enriched in B-cell receptor signaling, unfolded protein response, positive regulation of phagocytosis, HSP70, and HSP40-dependent folding, and ubiquitin-proteasomal proteolysis. Using network algorithms, and comparing enrichment analysis, we found the hub genes enriched were INHBE, UBC, HSPA1A, HSP90AB1, IKBKB, and BAG3. These DEGs were further validated with overall survival and gene expression analysis between the tumor and control groups. Finally, pristimerin effects were validated independently in a cell line model consisting of IM9 and U266 MM cells. Pristimerin induced in vitro cytotoxicity in MM cells in a dose-dependent manner. Pristimerin inhibited NF-κB, induced accumulation of ubiquitinated proteins and inhibited HSP60 in the validation of bioinformatics findings, while pristimerin-induced caspase-3 and PARP cleavage confirmed cell death. Taken together, we found that the identified DEGs were strongly associated with the apoptosis induced in MM cell lines due to pristimerin treatment, and combinatorial therapy derived from pristimerin could act as novel anti-myeloma multifunctional agents.

Controlling cell proliferation by targeting cyclin-dependent kinase 6 using drug repurposing approach

Cyclin-dependent kinase 6 (CDK6) is an essential kinase in cell cycle progression, which is a viable target for inhibitors in various malignancies, including breast cancer. This study aimed to virtually screen efficient compounds as new leads in treating breast cancer using a drug repurposing approach. Apoptosis regulatory compounds were taken from the seleckchem database. Molecular docking experiments were carried out in the presence of abemaciclib, a routinely used FDA drug. Compared to conventional drugs, the two compounds demonstrated a higher binding affinity for CDK6. Compounds (N-benzyl-6-[(4-hydroxyphenyl)methyl]-8-(naphthalen-1-ylmethyl)-4,7-dioxo-3,6,9,9a-tetrahydro-2H-pyrazino[1,2-a]pyrimidine-1-carboxamide) and (1'-[4-[1-(4-fluorophenyl)indol-3-yl]butyl]spiro[1H-2-benzofuran-3,4'-piperidine]) were discovered to have an inhibitory effect against CDK6 at -8.49 and -6.78kcal/mol, respectively, compared to -8.09kcal/mol of the control molecule, the interacting residues of these two new compounds were found to fall within the binding site of the CDK6 molecule. Both compounds exhibited equal ADME features compared with abemaciclib and would be well distributed and metabolized by the body with an appropriate druglikeness range. Lastly, molecular dynamics was initiated for 200ns for the selected potent inhibitors and abemaciclib as complexed with CDK6. The RMSD, RMSF, Rg, H-Bond interactions, SASA, PCA, FEL, and MM/PBSA analysis were performed for the complexes to assess the stability, fluctuations, radius of gyration, hydrogen bond interaction, solvent accessibility, essential dynamics, free energy landscape, and MM/PBSA. The selected two compounds are small molecules in the appropriate druglikeness range. The results observed in molecular docking and molecular dynamics simulations were most promising for two compounds, suggesting their potent inhibitory effect against CDK6. We propose that these candidate compounds can undergo in vitro validation and in vivo testing for their further use against cancer.

Genetic epidemiology of male infertility (MI) in Arabs: a systematic review

Although Male Infertility (MI) in Arabs is fairly common, there is a dearth in published reports of genetic epidemiology of MI among Arabs. This study aimed to review the existing literature reporting the variants that are associated with MI in the 22 Arab countries. We searched four literature databases (PubMed, Science Direct, Scopus, and Web of Science) from the time of inception until April 2021 using broad search terms to capture all reported genetic data related to Arab patients with MI. Our search strategy identified 3488 articles, of these 34 were eligible for this systemic review. We retrieved data from nine Arab Countries (Tunisia, Algeria, Morocco, Syria, Jordan, Yemen, Iraq, Egypt and Lebanon). Only 2597 patients and 10 families with MI were identified and compared to 3721 controls. Our search strategy identified 25 genes, including 89 variants: 52.7% are shared with other ethnic groups, 41.7% are unique to Arab patients, and 5.6% are common among Arabs. Azoospermia (41.18%) was the most frequently reported phenotype. This is the first systematic review to capture reported variants associated with MI among the Arab populations. Although Arabs seem to share genetic profiles with other ethnicities, they have distinctive genotype-phenotype correlations for some of genetic variants.

Integrative ontology and pathway-based approach identifies distinct molecular signatures in transcriptomes of esophageal squamous cell carcinoma

Esophageal squamous cell carcinoma (ESCC) remains a serious concern globally due to many factors that including late diagnosis, lack of an ideal biomarker for diagnosis and prognosis, and high rate of mortality. In this study, we aimed to identify the essential dysregulated genes and molecular signatures associated with the progression and development of ESCC. The dataset with 15 ESCCs and the 15 adjacent normal tissue samples from the surrounding histopathologically tumor-free mucosa was selected. We applied bioinformatics pipelines including various topological parameters from MCODE, CytoNCA, and cytoHubba to prioritize the most significantly associated DEGs with ESCC. We performed functional enrichment annotation for the identified DEGs using DAVID and MetaCore™ GeneGo platforms. Furthermore, we validated the essential core genes in TCGA and GTEx datasets between the normal mucosa and ESCC for their expression levels. These DEGs were primarily enriched in positive regulation of transferase activity, negative regulation of organelle organization, cell cycle mitosis/S-phase transition, spindle organization/assembly, development, and regulation of angiogenesis. Subsequently, the DEGs were associated with the pathways such as oocyte meiosis, cell cycle, and DNA replication. Our study identified the eight-core genes (AURKA, AURKB, MCM2, CDC20, TPX2, PLK1, FOXM1, and MCM7) that are highly expressed among the ESCC, and TCGA dataset. The multigene comparison and principal component analysis resulted in elevated signals for the AURKA, MCM2, CDC20, TPX2, PLK1, and FOXM1. Overall, our study reported GO profiles and molecular signatures that might help researchers to grasp the pathological mechanisms underlying ESCC development and eventually provide novel therapeutic and diagnostic strategies.

A review of bioinformatics tools and web servers in different microarray platforms used in cancer research

Over the past decade, conventional lab work strategies have gradually shifted from being limited to a laboratory setting towards a bioinformatics era to help manage and process the vast amounts of data generated by omics technologies. The present work outlines the latest contributions of bioinformatics in analyzing microarray data and their application to cancer. We dissect different microarray platforms and their use in gene expression in cancer models. We highlight how computational advances empowered the microarray technology in gene expression analysis. The study on protein-protein interaction databases classified into primary, derived, meta-database, and prediction databases describes the strategies to curate and predict novel interaction networks in silico. In addition, we summarize the areas of bioinformatics where neural graph networks are currently being used, such as protein functions, protein interaction prediction, and in silico drug discovery and development. We also discuss the role of deep learning as a potential tool in the prognosis, diagnosis, and treatment of cancer. Integrating these resources efficiently, practically, and ethically is likely to be the most challenging task for the healthcare industry over the next decade; however, we believe that it is achievable in the long term.

Whole-exome sequencing analysis of NSCLC reveals the pathogenic missense variants from cancer-associated genes

BACKGROUND

Non-small-cell lung cancer (NSCLC) is the most common type of lung cancer. NSCLC accounts for 84% of all lung cancer cases. In recent years, advances in pathway understanding, methods for discovering novel genetic biomarkers, and new drugs designed to inhibit the signaling cascades have enabled clinicians to personalize therapy for NSCLC.

OBJECTIVES

The primary aim of this study is to identify the genes associated with NSCLC that harbor pathogenic variants that could be causative for NSCLC. The second aim is to investigate their roles in different pathways that lead to NSCLC.

METHODS

We examined exome-sequencing datasets from 54 NSCLC patients to characterize the variants associated with NSCLC.

RESULTS

Our findings revealed that 17 variants in 14 genes were considered highly pathogenic, including CDKN2A, ERBB2, FOXP1, IDH1, JAK3, KMT2D, K-Ras, MSH3, MSH6, POLE, RNF43, TCF7L2, TP53, and TSC1. Gene set enrichment analysis revealed the involvement of transmembrane receptor protein tyrosine kinase activity, protein binding, ATP binding, phosphatidylinositol-4,5-bisphosphate 3-kinase, and Ras guanyl-nucleotide exchange factor activity. Pathway analysis of these genes yielded different cancer-related pathways, including colorectal, prostate, endometrial, pancreatic, PI3K-Akt signaling pathways, and signaling pathways regulating pluripotency of stem cells. Module 1 from protein-protein interactions (PPIs) identified genes that harbor pathogenic SNPs. Three of the most deleterious SNPs are ERBB2 (rs1196929947), K-Ras (rs121913529), and POLE (rs751425952). Interestingly, one patient has a pathogenic K-Ras variant (rs121913529) co-occurred with the missense variant (rs752054698) inTSC1 gene.

CONCLUSION

This study maps highly pathogenic variants associated with NSCLC and investigates their contributions to the pathogenesis of NSCLC. This study sheds light on the potential applications of precision medicine in patients with NSCLC.

AB0424 A RANDOMIZED, DOUBLE-BLIND, PLACEBO CONTROLLED STUDY OF THE SAFETY, TOLERABILITY, PHARMACOKINETICS, AND PHARMACODYNAMICS OF ALPN-303, A POTENT DUAL BAFF/APRIL INHIBITOR, IN ADULT HEALTHY VOLUNTEERS

Background

Therapeutic agents targeting the B-cell cytokines BAFF and/or APRIL, including the wild-type (WT) TACI-Fc fusion proteins atacicept and telitacicept, have demonstrated promising clinical potential in rheumatic diseases like systemic lupus erythematosus (SLE) and/or other B-cell-related diseases such as autoantibody-related nephritides. ALPN-303 is an Fc fusion protein of a variant, engineered TACI domain which mediates significantly more potent inhibitory activity in vitro as compared to WT TACI-Fc or BAFF- or APRIL-specific monoclonal antibodies, along with enhanced pharmacokinetic (PK) and immunomodulatory properties in preclinical studies1,2. ALPN-303 may therefore significantly improve clinical outcomes in SLE and other B-cell-related diseases.

Objectives

To evaluate the safety, tolerability, PK, and pharmacodynamics (PD) of ALPN-303 in adult healthy volunteers (HV).

Methods

In this first-in-human study (NCT05034484), adult HVs are enrolled in single ascending dose cohorts of intravenously (IV) or subcutaneously (SC) administered ALPN-303. For each IV cohort, the first 2 subjects are randomized 1:1 to receive ALPN-303 or placebo, followed by the remaining 4 subjects randomized 3:1 to receive ALPN-303 or placebo. For each SC cohort, HVs are randomized 4:2 to receive a single SC dose of ALPN-303 or placebo. All subjects are followed to assess safety and PK of ALPN-303, to measure levels of circulating immunoglobulins (Ig), and to characterize leukocyte populations in peripheral blood by flow cytometry.

Results

ALPN-303 has been well tolerated and overall exhibits dose-dependent PK and expected PD effects on circulating Ig levels. Dose escalation is expected to be completed by the time of the meeting; the presentation will include all available safety, PK, and PD (circulating Ig and B-cell population) data.

Conclusion

In this first-in-human study, ALPN-303 demonstrates acceptable preliminary safety and tolerability, and exhibits expected PD effects on circulating Ig and B-cell populations. These findings support future clinical development of ALPN-303 in patients with SLE or other B-cell-mediated diseases.

References

[1]Dillon SR, Evans LS, Lewis KE, et al. OP0039 ALPN-303, an enhanced, potent dual BAFF/APRIL antagonist engineered by directed evolution for the treatment of systemic lupus erythematosus (SLE) and other B cell related autoimmune diseases. Annals of the Rheumatic Diseases 2021;80:21.

[2]Dillon SR, Evans LS, Lewis KE, et al. ALPN-303, an enhanced, potent dual BAFF/APRIL antagonist engineered by directed evolution for the treatment of systemic lupus erythematosus (SLE) and other B cell-related diseases. Arthritis Rheumatol. 2021; 73 (suppl 10).

Disclosure of Interests

Pille Harrison Employee of: Alpine Immune Sciences Inc, Jason Lickliter Consultant of: ENA Oncology and Amplia. Neither of these were developing drugs for rheumatological diseases., Stacey R. Dillon Employee of: Alpine Immune Sciences Inc, Kristi Manjarrez Employee of: Alpine Immune Sciences Inc, Alina Smith Employee of: Alpine Immune Sciences Inc, Melody Dossey Employee of: Alpine Immune Sciences Inc, Lori Blanchfield Employee of: Alpine Immune Sciences Inc, Allison Chunyk Employee of: Alpine Immune Sciences Inc, Hany Zayed Employee of: Alpine Immune Sciences Inc, Stanford L. Peng Employee of: Alpine Immune Sciences Inc

Computational structural assessment of BReast CAncer type 1 susceptibility protein (BRCA1) and BRCA1-Associated Ring Domain protein 1 (BARD1) mutations on the protein-protein interface

Breast cancer type 1 susceptibility protein (BRCA1) is closely related to the BRCA2 (breast cancer type 2 susceptibility protein) and BARD1 (BRCA1-associated RING domain-1) proteins. The homodimers were formed through their RING fingers; however they form more compact heterodimers preferentially, influencing BRCA1 residues 1-109 and BARD1 residues 26-119. We implemented an integrative computational pipeline to screen all the mutations in BRCA1 and identify the most significant mutations influencing the Protein-Protein Interactions (PPI) in the BRCA1-BARD1 protein complex. The amino acids involved in the PPI regions were identified from the PDBsum database with the PDB ID: 1JM7. We screened 2118 missense mutations in BRCA1 and none in BARD1 for pathogenicity and stability and analyzed the amino acid sequences for conserved residues. We identified the most significant mutations from these screenings as V11G, M18K, L22S, and T97R positioned in the PPI regions of the BRCA1-BARD1 protein complex. We further performed protein-protein docking using the ZDOCK server. The native protein-protein complex showed the highest binding score of 2118.613, and the V11G mutant protein complex showed the least binding score of 1992.949. The other three mutation protein complexes had binding scores between the native and V11G protein complexes. Finally, a molecular dynamics simulation study using GROMACS was performed to comprehend changes in the BRCA1-BARD1 complex's binding pattern due to the mutation. From the analysis, we observed the highest deviation with lowest compactness and a decrease in the intramolecular h-bonds in the BRCA1-BARD1 protein complex with the V11G mutation compared to the native complex or the complexes with other mutations.

Understanding Gene Expression and Transcriptome Profiling of COVID-19: An Initiative Towards the Mapping of Protective Immunity Genes Against SARS-CoV-2 Infection

The COVID-19 pandemic has created an urgent situation throughout the globe. Therefore, it is necessary to identify the differentially expressed genes (DEGs) in COVID-19 patients to understand disease pathogenesis and the genetic factor(s) responsible for inter-individual variability. The DEGs will help understand the disease's potential underlying molecular mechanisms and genetic characteristics, including the regulatory genes associated with immune response elements and protective immunity. This study aimed to determine the DEGs in mild and severe COVID-19 patients versus healthy controls. The Agilent-085982 Arraystar human lncRNA V5 microarray GEO dataset (GSE164805 dataset) was used for this study. We used statistical tools to identify the DEGs. Our 15 human samples dataset was divided into three groups: mild, severe COVID-19 patients and healthy control volunteers. We compared our result with three other published gene expression studies of COVID-19 patients. Along with significant DEGs, we developed an interactome map, a protein-protein interaction (PPI) pattern, a cluster analysis of the PPI network, and pathway enrichment analysis. We also performed the same analyses with the top-ranked genes from the three other COVID-19 gene expression studies. We also identified differentially expressed lncRNA genes and constructed protein-coding DEG-lncRNA co-expression networks. We attempted to identify the regulatory genes related to immune response elements and protective immunity. We prioritized the most significant 29 protein-coding DEGs. Our analyses showed that several DEGs were involved in forming interactome maps, PPI networks, and cluster formation, similar to the results obtained using data from the protein-coding genes from other investigations. Interestingly we found six lncRNAs (TALAM1, DLEU2, and UICLM CASC18, SNHG20, and GNAS) involved in the protein-coding DEG-lncRNA network; which might be served as potential biomarkers for COVID-19 patients. We also identified three regulatory genes from our study and 44 regulatory genes from the other investigations related to immune response elements and protective immunity. We were able to map the regulatory genes associated with immune elements and identify the virogenomic responses involved in protective immunity against SARS-CoV-2 infection during COVID-19 development.

A computational overview on phylogenetic characterization, pathogenic mutations, and drug targets for Ebola virus disease

The World Health Organization declared Ebola virus disease (EVD) as the major outbreak in the 20th century. EVD was first identified in 1976 in South Sudan and the Democratic Republic of the Congo. EVD was transmitted from infected fruit bats to humans via contact with infected animal body fluids. The Ebola virus (EBOV) has a genome size of ∼18,959 bp. It encodes seven distinct proteins: nucleoprotein (NP), glycoprotein (GP), viral proteins VP24, VP30, VP35, matrix protein VP40, and polymerase L is considered a prime target for potential antiviral strategies. The current US FDA-approved anti-EVD vaccine, ERVERBO, and the other equally effective anti-EBOV combinations of three fully human monoclonal antibodies such as REGN-EB3, primarily target the envelope glycoprotein. This work elaborates on the EBOV's phylogenetic structure and the crucial mutations associated with viral pathogenicity.

Comparison of potential inhibitors and targeting fat mass and obesity-associated protein causing diabesity through docking and molecular dynamics strategies

Genome-wide association studies (GWAS) have identified an association between polymorphisms in the FTO gene and obesity. The FTO: rs9939609, an intronic variant, is considered a risk allele for developing diabesity in homozygous and heterozygous forms. This study aimed to investigate the molecular structure of the available inhibitors specific to the FTO mutations along with the rs9939609 variant. We identified the best-suited inhibitor molecules for each mutant type containing the rs9939609 risk allele. Missense mutations unique to obesity and containing the risk allele of rs9939609 were retrieved from dbSNP for this study. Further stability testing for the mutations were carried out using DynaMut and iStable tools. Three mutations (G187A, M223V, and I492V) were highly destabilizing the FTO structure. These three mutants and native FTO were docked with each of the nine-inhibitor molecules collected from literature studies with the help of PyRx and AutoDock. Further structural behavior of the mutants and native FTO were identified with molecular dynamics simulations and MM-PBSA analyses, along with the 19complex inhibitor compound. We found the compound 19complex exhibited better binding interactions and is the top candidate inhibitor for the M223V and I492V mutants. This study provided insights into the structural changes caused due to mutations in FTO, and the binding mechanism of the inhibitor molecules. It could aid in developing antiobesity drugs for treating patients with mutations and risk alleles predisposing to obesity.

Association of Genetic Variants with Colorectal Cancer in the Extended MENA Region: A Systematic Review

BACKGROUND

Colorectal cancer (CRC) is the third most common cancer worldwide and the third leading cause of cancer-related death. It is a heterogeneous disease that develops through different genetic and epigenetic mechanisms. To date, no comprehensive systematic review investigating genetic risk factors for familial and sporadic CRC has been performed on the extended MENA (eMENA) region.

AIMS

This study aimed to systematically analyze genetic variations significantly associated with CRC in the eMENA region.

METHODS

We searched four literature databases (PubMed, Scopus, Science Direct, and Web of Science) from the time of inception until May 2019 using broad search terms to obtain all reported genetic data related to eMENA patients with CRC. Variants with an OR>1 that are associated with CRC were identified.

RESULTS

A total of 1,200 studies were obtained from our search method, 27 of which met the inclusion criteria for our systematic review, with a total of 8,230 CRC patients and 7,611 controls. Of these, 1,941 patients distributed throughout nine eMENA countries were found to carry 46 variants in 33 different genes. Interestingly, 19 variants were unique to CRC patients in the eMENA region.

INTERPRETATION

This is the first systematic review to capture the spectrum of variants significantly associated with CRC in the eMENA region. There appears to be a distinctive clinical picture for eMENA patients with CRC, and the range and distribution of variants among patients from the eMENA region differ from those noted in other ethnic groups.

Immunogenetics of Celiac Disease: A Focus on Arab Countries

Celiac Disease (CD) is a complex immunogenic disease mainly triggered by gluten intake in genetically susceptible individuals with a prevalence of 1 in 100-300. CD results from the interplay between genetic and environmental factors. Genetic susceptibility is believed to play a prominent role in the pathogenicity of CD, mainly due to human leukocyte antigen (HLA)-related class II genes. Although CD is wellrecognized among Arab populations, there are few studies on the genetic epidemiology and prevalence of CD in the Arab countries. Therefore, the aim of this review was to highlight the importance of studying this disease in the Arab world in the context of a global perspective. Within the few studies published so far, it was found that Arab populations have a distinctive susceptibility genetic profile from other ethnic groups with the DQ2.5 and DQ8 genotypes that are considered the major genotypes that confer susceptibility among Arab patients with CD. Our findings will pave the way to perform further epidemiological studies that will help identify potential therapeutic targets against CD among Arab patients that are diagnosed with CD.

Tumor reversion: a dream or a reality

Reversion of tumor to a normal differentiated cell once considered a dream is now at the brink of becoming a reality. Different layers of molecules/events such as microRNAs, transcription factors, alternative RNA splicing, post-transcriptional, post-translational modifications, availability of proteomics, genomics editing tools, and chemical biology approaches gave hope to manipulation of cancer cells reversion to a normal cell phenotype as evidences are subtle but definitive. Regardless of the advancement, there is a long way to go, as customized techniques are required to be fine-tuned with precision to attain more insights into tumor reversion. Tumor regression models using available genome-editing methods, followed by in vitro and in vivo proteomics profiling techniques show early evidence. This review summarizes tumor reversion developments, present issues, and unaddressed challenges that remained in the uncharted territory to modulate cellular machinery for tumor reversion towards therapeutic purposes successfully. Ongoing research reaffirms the potential promises of understanding the mechanism of tumor reversion and required refinement that is warranted in vitro and in vivo models of tumor reversion, and the potential translation of these into cancer therapy. Furthermore, therapeutic compounds were reported to induce phenotypic changes in cancer cells into normal cells, which will contribute in understanding the mechanism of tumor reversion. Altogether, the efforts collectively suggest that tumor reversion will likely reveal a new wave of therapeutic discoveries that will significantly impact clinical practice in cancer therapy.

Acute kidney injury following endovascular intervention for peripheral artery disease

BACKGROUND

The incidence of, and risk factors for, acute kidney injury (AKI) after endovascular intervention for peripheral artery disease (PAD) remain unknown. The aim of this study was to assess the proportion of patients who develop AKI and explore the risk factors.

METHODS

Prospectively collected data on patients undergoing femoropopliteal endovascular intervention for symptomatic PAD across three vascular centres were analysed. The proportion of patients developing AKI (according to the Kidney Disease Improving Global Outcomes definition) within 48 h, and the proportion developing the composite Major Adverse Kidney Events (MAKE) endpoints (death, dialysis, drop in estimated glomerular filtration rate at least 25 per cent) at 30 days (MAKE30) and remains 90 days (MAKE90) were calculated. Multivariable regression analysis was used to assess predictors of AKI, and the association between AKI and death.

RESULTS

Some 2041 patients were included in the analysis. AKI developed in 239 patients (11.7 per cent), with 47 (2.3 per cent) requiring dialysis within 30 days, and 18 (0.9 per cent) requiring ongoing dialysis. The MAKE30 and MAKE90 composite endpoints were reached in 358 (17.5 per cent) and 449 (22.0 per cent) patients respectively. Risk factors for AKI were age, sex, congestive heart failure, chronic limb-threatening ischaemia, emergency procedure, and pre-existing chronic kidney disease. AKI, dementia, congestive heart failure, and major amputation were risk factors for medium-term mortality.

CONCLUSION

AKI is a common complication after intervention for PAD and is associated with medium-term mortality.

An integrative analysis to distinguish between emphysema (EML) and alpha-1 antitrypsin deficiency-related emphysema (ADL)-A systems biology approach

Lung Emphysema is an abnormal enlargement of the air sacs followed by the destruction of alveolar walls without any prominent fibrosis. This study primarily identifies the differentially expressed genes (DEGs), interactions between them, and their significant involvement in the activated signaling cascades. The dataset with ID GSE1122 (five normal lung tissue samples, five of usual emphysema, and five of alpha-1 antitrypsin deficiency-related emphysema) from the gene expression omnibus (GEO) was analyzed using the GEO2R tool. The physical association between the DEGs were mapped using the STRING tool and was visualized in the Cytoscape software. The enriched functional processes were identified with the ClueGO plugin's help from Cytoscape. Further integrative functional annotation was performed by implying the GeneGo Metacore™ to distinguish the enriched pathway maps, process networks, and GO processes. The results from this analysis revealed the critical signaling cascades that have been either activated or inhibited due to identified DEGs. We found the activated pathways such as immune response IL-1 signaling pathway, positive regulation of smooth muscle migration, BMP signaling pathway, positive regulation of leukocyte migration, NIK/NF-kappB signaling, and cytochrome-c oxidase activity. Finally, we mapped four crucial genes (CCL5, ALK, TAC1, CD74, and HLA-DOA) by comparing the functional annotations that could be significantly influential in emphysema molecular pathogenesis. Our study provides insights into the pathogenesis of emphysema and helps in developing potential drug targets against emphysema.

Structure-Based Virtual Screening to Identify Novel Potential Compound as an Alternative to Remdesivir to Overcome the RdRp Protein Mutations in SARS-CoV-2

The number of confirmed COVID-19 cases is rapidly increasing with no direct treatment for the disease. Few repurposed drugs, such as Remdesivir, Chloroquine, Hydroxychloroquine, Lopinavir, and Ritonavir, are being tested against SARS-CoV-2. Remdesivir is the drug of choice for Ebola virus disease and has been authorized for emergency use. This drug acts against SARS-CoV-2 by inhibiting the RNA-dependent-RNA-polymerase (RdRp) of SARS-CoV-2. RdRp of viruses is prone to mutations that confer drug resistance. A recent study by Pachetti et al. in 2020 identified the P323L mutation in the RdRp protein of SARS-CoV-2. In this study, we aimed to determine the potency of lead compounds similar to Remdesivir, which can be used as an alternative when variants of SARS-CoV-2 develop resistance due to RdRp mutations. The initial screening yielded 704 compounds that were 90% similar to the control drug, Remdesivir. On further evaluation through drugability and antiviral inhibition percentage analyses, we shortlisted 32 and seven compounds, respectively. These seven compounds were further analyzed for their molecular interactions, which revealed that all seven compounds interacted with RdRp with higher affinity than Remdesivir under native conditions. However, three compounds failed to interact with the mutant protein with higher affinity than Remdesivir. Dynamic cross-correlation matrix (DCCM) and vector field collective motions analyses were performed to identify the precise movements of docked complexes' residues. Furthermore, the compound SCHEMBL20144212 showed a high affinity for native and mutant proteins and might provide an alternative against SARS-CoV-2 variants that might confer resistance to Remdesivir. Further validations by in vitro and in vivo studies are needed to confirm the efficacy of our lead compounds for their inhibition against SARS-CoV-2.

A review of novel coronavirus disease (COVID-19): based on genomic structure, phylogeny, current shreds of evidence, candidate vaccines, and drug repurposing

Coronavirus disease (COVID-19) pandemic is instigated by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). As of March 13, 2021, more than 118.9 million cases were infected with COVID-19 worldwide. SARS-CoV-2 is a positive-sense single-stranded RNA beta-CoV. Most COVID-19 infected individuals recover within 1-3 weeks. Nevertheless, approximately 5% of patients develop acute respiratory distress syndrome and other systemic complications, leading to death. Structural genetic analyses of SARS-CoV-2 have shown genomic resemblances but a low evolutionary correlation to SARS-CoV-1 responsible for the 2002-2004 outbreak. The S glycoprotein is critical for cell adhesion and the entrance of the virus into the host. The process of cell entry uses the cellular receptor named angiotensin-converting enzyme 2. Recent evidence proposed that the CD147 as a SARS-CoV-2's potential receptor. The viral genome is mainly held by two non-structural proteins (NSPs), ORF1a and ORF1ab, along with structural proteins. Although NSPs are conserved among the βCoVs, mutations in NSP2 and NSP3 may play critical roles in transmitting the virus and cell tropism. To date, no specific/targeted anti-viral treatments exist. Notably, more than 50 COVID-19 candidate vaccines in clinical trials, and a few being administered. Preventive precautions are the primary strategy to limit the viral load transmission and spread, emphasizing the urgent need for developing significant drug targets and vaccines against COVID-19. This review provides a cumulative overview of the genomic structure, transmission, phylogeny of SARS-CoV-2 from Indian clusters, treatment options, updated discoveries, and future standpoints for COVID-19.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s13205-021-02749-0.

Genetic Variants Associated With Alzheimer Disease in the 22 Arab Countries: A Systematic Review

BACKGROUND AND AIMS

Alzheimer disease (AD) is a progressive and complex neurodegenerative disease. Approximately 70% of AD risk is attributed to genetic risk factors, including variants in amyloid precursor protein (APP), presenilin 1 (PSEN1), and presenilin 2 (PSEN2) genes. Several studies have revealed a considerable number of candidate loci and genes for AD among different ethnic populations. However, the outcomes of these studies have been inconsistent. In this study, we aimed to investigate the spectrum of variants that are associated with the onset and development of AD among 22 Arab countries.

METHODOLOGY

We systematically searched 4 literature databases (Science Direct, Scopus, PubMed, and Web of Science) from the date of inception until July 2020 using various search terms to obtain all the reported genetic data on Arab AD cases.

RESULTS

In total, 18 studies were included, comprising a total of 2173 individuals, of whom 888 were clinically diagnosed AD patients and were genetically tested for genes and variants associated with AD. A total of 27 variants in 8 genes were found to be associated with AD. Of these variants, 17 were unique to the Arab population and 10 were shared with other ethnic groups.

CONCLUSIONS

There is a dearth of studies on the genetics of AD in the Arab world. There seems to be distinctive genetic and clinical susceptibility profiles for Arab patients with AD.

A systemic approach to explore the mechanisms of drug resistance and altered signaling cascades in extensively drug-resistant tuberculosis

BACKGROUND AND AIM

The persistence of extensively drug-resistant (XDR) strains of Mycobacterium tuberculosis (MTB) continue to pose a significant challenge to the treatment and control of tuberculosis infections worldwide. XDR-MTB strains exhibit resistance against first-line anti-TB drugs, fluoroquinolones, and second-line injectable drugs. The mechanisms of drug resistance of MTB remains poorly understood. Our study aims at identifying the differentially expressed genes (DEGs), associated gene networks, and signaling cascades involved in rendering this pathogen resistant to multiple drugs, namely, isoniazid, rifampicin, and capreomycin.

METHODS

We used the microarray dataset GSE53843. The GEO2R tool was used to prioritize the most significant DEGs (top 250) of each drug exposure sample between XDR strains and non-resistant strains. The validation of the 250 DEGs was performed using volcano plots. Protein-protein interaction networks of the DEGs were created using STRING and Cytoscape tools, which helped decipher the relationship between these genes. The significant DEGs were functionally annotated using DAVID and ClueGO. The concomitant biological processes (BP) and molecular functions (MF) were represented as dot plots.

RESULTS AND CONCLUSION

We identified relevant molecular pathways and biological processes, such as cell wall biogenesis, lipid metabolic process, ion transport, phosphopantetheine binding, and triglyceride lipase activity. These processes indicated the involvement of multiple interconnected mechanisms in drug resistance. Our study highlighted the impact of cell wall permeability, with the dysregulation of the mur family of proteins, as essential factors in the inference of resistance. Additionally, upregulation of genes responsible for ion transport such as ctpF, arsC, and nark3, emphasizes the importance of transport channels and efflux pumps in potentially driving out stress-inducing compounds. This study investigated the upregulation of the Lip family of proteins, which play a crucial role in triglyceride lipase activity. Thereby illuminating the potential role of drug-induced dormancy and subsequent resistance in the mycobacterial strains. Multiple mechanisms such as carboxylic acid metabolic process, NAD biosynthetic process, triglyceride lipase activity, phosphopantetheine binding, organic acid biosynthetic process, and growth of symbiont in host cell were observed to partake in resistance of XDR-MTB. This study ultimately provides a platform for important mapping targets for potential therapeutics against XDR-MTB.

Genetic Epidemiology of Primary Congenital Glaucoma in the 22 Arab Countries: A Systematic Review

PURPOSE

Primary congenital glaucoma (PCG) is a rare glaucoma type that develops in early infantile period and contributes to an elevated pressure on ocular cavity. Variants in CYP1B1 gene are the most encountered in PCG cases. The prevalence of PCG is relatively high among Arabs, however its genetic epidemiology remains understudied. This study aims to systematically identify all reported PCG disease-causing variants in the Arab population and investigate their potential genotype-phenotype correlations.

METHODS

We searched four different databases (PubMed, ScienceDirect, Google Scholar, and Scopus) from the time of inception until July 2020. Broad search terms were used to capture all possible information about the genetic epidemiology of PCG among Arabs.

RESULTS

We identified a total of 77 disease-causing variants in 361 patients and 88 families; of these, 33 were unique to Arabs. Sixty-nine variants were identified in the CYP1B1 gene, five variants were in the MYOC gene and single variants were reported in NTF4, FOXC1, and WDR36 genes. The most common reported variant was the c.182 G > A in the CYP1B1 gene. All identified variants were from ten Arab Countries (Saudi Arabia, Kuwait, Oman, Egypt, Morocco, Lebanon, Tunisia, Iraq, Algeria, and Mauritania). We identified 44 shared variants with other ethnicities demonstrated a distinctive genotype-phenotype correlation. Consanguinity was observed in the majority of Arab PCG patients, ranging from 45% to 100%.

CONCLUSION

PCG causing variants were identified in 10 Arab countries, which were mostly detected in the CYB1P1 gene. Arab patients with PCG seem to have distinctive genotype-phenotype correlations.

Molecular dynamics, residue network analysis, and cross-correlation matrix to characterize the deleterious missense mutations in GALE causing galactosemia III

Epimerase-deficiency galactosemia (EDG) is caused by mutations in the UDP-galactose 4'-epimerase enzyme, encoded by gene GALE. Catalyzing the last reaction in the Leloir pathway, UDP-galactose-4-epimerase catalyzes the interconversion of UDP-galactose and UDP-glucose. This study aimed to use in-depth computational strategies to prioritize the pathogenic missense mutations in GALE protein and investigate the systemic behavior, conformational spaces, atomic motions, and cross-correlation matrix of the GALE protein. We searched four databases (dbSNP, ClinVar, UniProt, and HGMD) and major biological literature databases (PubMed, Science Direct, and Google Scholar), for missense mutations that are associated with EDG patients, our search yielded 190 missense mutations. We applied a systematic computational prediction pipeline, including pathogenicity, stability, biochemical, conservational, protein residue contacts, and structural analysis, to predict the pathogenicity of these mutations. We found three mutations (p.K161N, p.R239W, and p.G302D) with a severe phenotype in patients with EDG that correlated with our computational prediction analysis; thus, they were selected for further structural and simulation analyses to compute the flexibility and stability of the mutant GALE proteins. The three mutants were subjected to molecular dynamics simulation (MDS) with native protein for 200 ns using GROMACS. The MDS demonstrated that these mutations affected the beta-sheets and helical region that are responsible for the catalytic activity; subsequently, affects the stability and flexibility of the mutant proteins along with a decrease and more deviations in compactness when compared to that of a native. Also, three mutations created major variations in the combined atomic motions of the catalytic and C-terminal regions. The network analysis of the residues in the native and three mutant protein structures showed disturbed residue contacts occurred owing to the missense mutations. Our findings help to understand the structural behavior of a protein owing to mutation and are intended to serve as a platform for prioritizing mutations, which could be potential targets for drug discovery and development of targeted therapeutics.

Assessment of lung cancer risk factors and mortality in Qatar: A case series study

BACKGROUND

The global burden of cancer has exponentially increased over the last few years. In 2018 alone, approximately more than half of the 18.1 million individuals who had cancer succumbed to it. Lung cancer cases and fatalities are particularly on the rise. Therefore, exploring the factors surrounding lung cancer mortality is of utmost importance.

AIMS

We investigate the clinicopathological and epidemiological characteristics of patients with lung cancer undergoing treatments, and their 5-year survival rates from a case series study in Qatar.

METHODS AND RESULTS

All patients' data (between January 2010 and December 2014) in this case series study were retrieved from Al-Amal Hospital database. Kaplan-Meier survival plots, life tables and Cox regression were utilized for the statistical analysis. A total of 229 lung cancer patients were included in this study; of which 23.6% are Qatari (40 males and 14 females) and 76.4% non-Qatari (133 males and 42 females). Approximately 57.6% of our patients received at least one type of treatment. We observe a 5-year survival rate of 9.4% in our patient cohort. We also observe other predictive factors, such as distant metastasis (adjusted hazards ratio, HR = 2.414, 95% CI: 1.035-5.632), smoking status (adjusted HR = 3.909, 95% CI: 1.664-9.180) and the treatment history (adjusted HR = 0.432, 95% CI: 0.270-0.691), to be significant.

CONCLUSION

Lung cancer is a prevalent health condition in Qatar, particularly owing to the rising use of tobacco in the country. The survival rate for lung cancer patients in this country is lower, compared to the global average. Moreover, several factors such as distant metastasis, smoking status, and treatment history are associated with lung cancer survival in Qatar.