Delineating the mechanistic relevance of the TP53 gene and its mutational impact on gene expression and patients' survival in bladder cancer.

Bladder carcinoma (BLCA) is a widespread urological malignancy causing significant global mortality, often hindered by delayed diagnosis and limited treatments. BLCA frequently exhibits TP53 mutations, playing a pivotal role in its pathogenesis and underscoring the potential of targeting TP53 as a therapeutic approach for this prevalent urological malignancy. Tumor tissues from 50 bladder cancer patients were used for mutational analysis in TP53's mutation-rich exons (5, 7, & 8). The gene expression of the TP53 gene, along with a TP53-target gene B-cell translocation gene 2 (BTG2) was also assessed in the cDNA samples from the same BLCA tissues and 15 urine controls of healthy people. The analysis revealed 22 % of patients with somatic hotspot mutations, 18 % with pathogenic missense mutations, and 12 % with intronic variants. Patients with somatic mutations exhibited the worst prognosis, supported by survival analysis from The Cancer Genome Atlas (TCGA) BLCA data. Interestingly, H296Y missense mutation correlated with higher TP53 expression and improved survival, while intronic SNPs were linked to worse outcomes. Additionally, upregulated BTG2 expression in mutated patients was observed which was correlated with poor prognosis, emphasizing the role of TP53 mutations in bladder cancer progression. The multivariate analysis highlighted the predictive power of TP53 mutations, with a high frequency of high-grade tumors (78.57 %) in mutated patients, underscoring their role in cancer progression. In conclusion, this study emphasizes the crucial role of TP53 mutations in bladder cancer patients from Bangladesh.

Computational exploration of SLC14A1 genetic variants through structure modeling, protein-ligand docking, and molecular dynamics simulation.

The urea transporter UT-B1, encoded by the SLC14A1 gene, has been hypothesized to be a significant protein whose deficiency and dysfunction contribute to the pathogenesis of bladder cancer and many other diseases. Several studies reported the association of genetic alterations in the SLC14A1 (UT-B1) gene with bladder carcinogenesis, suggesting a need for thorough characterization of the UT-B1 protein's coding and non-coding variants. This study used various computational techniques to investigate the commonly occurring germ-line missense and non-coding SNPs (ncSNPs) of the SLC14A1 gene (UT-B1) for their structural, functional, and molecular implications for disease susceptibility and dysfunctionality. SLC14A1 missense variants, primarily identified from the ENSEMBL genome browser, were screened through twelve functionality prediction tools leading to two variants D280Y (predicted detrimental by maximum tools) and D280N (high global MAF) for rs1058396. Subsequently, the ConSurf and NetSurf tools revealed the D280 residue to be in a variable site and exposed on the protein surface. According to I-Mutant2.0 and MUpro, both variants are predicted to cause a significant effect on protein stability. Analysis of molecular docking anticipated these two variants to decrease the binding affinity of UT-B1 protein for the examined ligands to a significant extent. Molecular dynamics also disclosed the possible destabilization of the UT-B1 protein due to single nucleotide polymorphism compared to wild-type protein which may result in impaired protein function. Furthermore, several non-coding SNPs were estimated to affect transcription factor binding and regulation of SLC14A1 gene expression. Additionally, two ncSNPs were found to affect miRNA-based post-transcriptional regulation by creating new seed regions for miRNA binding. This comprehensive in-silico study of SLC14A1 gene variants may serve as a springboard for future large-scale investigations examining SLC14A1 polymorphisms.

Comprehensive characterization of coding and non-coding single nucleotide polymorphisms of the Myoneurin (MYNN) gene using molecular dynamics simulation and docking approaches.

Genome-wide association studies (GWAS) identified a coding single nucleotide polymorphism, MYNN rs10936599, at chromosome 3q. MYNN gene encodes myoneurin protein, which has been associated with several cancer pathogenesis and disease development processes. However, there needed to be a more detailed characterization of this polymorphism's (and other coding and non-coding polymorphisms) structural, functional, and molecular impact. The current study addressed this gap and analyzed different properties of rs10936599 and non-coding SNPs of MYNN via a thorough computational method. The variant, rs10936599, was predicted functionally deleterious by nine functionality prediction approaches, like SIFT, PolyPhen-2, and REVEL, etc. Following that, structural modifications were estimated through the HOPE server and Mutation3D. Moreover, the mutation was found in a conserved and active residue, according to ConSurf and CPORT. Further, the secondary structures were predicted, followed by tertiary structures, and there was a significant deviation between the native and variant models. Similarly, molecular simulation also showed considerable differences in the dynamic pattern of the wildtype and mutant structures. Molecular docking revealed that the variant binds with better docking scores with ligand NOTCH2. In addition to that, non-coding SNPs located at the MYNN locus were retrieved from the ENSEMBL database. These were found to disrupt the transcription factor binding regulatory regions; nonetheless, only two affect miRNA target sites. Again, eight non-coding variants were detected in the testes with normalized expression, whereas HaploReg v4.1 unveiled annotations for non-coding variants. In summary, in silico comprehensive characterization of coding and non-coding single nucleotide polymorphisms of MYNN gene will assist researchers to work on MYNN gene and establish their association with certain types of cancers.

Identification and validation of prognostic signature genes of bladder cancer by integrating methylation and transcriptomic analysis.

Being a frequent malignant tumor of the genitourinary system, Bladder Urothelial Carcinoma (BLCA) has a poor prognosis. This study focused on identifying and validating prognostic biomarkers utilizing methylation, transcriptomics, and clinical data from The Cancer Genome Atlas Bladder Urothelial Carcinoma (TCGA BLCA) cohort. The impact of altered differentially methylated hallmark pathway genes was subjected to clustering analysis to observe changes in the transcriptional landscape on BLCA patients and identify two subtypes of patients from the TCGA BLCA population where Subtype 2 was associated with the worst prognosis with a p-value of 0.00032. Differential expression and enrichment analysis showed that subtype 2 was enriched in immune-responsive and cancer-progressive pathways, whereas subtype 1 was enriched in biosynthetic pathways. Following, regression and network analyses revealed Epidermal Growth Factor Receptor (EGFR), Fos-related antigen 1 (FOSL1), Nuclear Factor Erythroid 2 (NFE2), ADP-ribosylation factor-like protein 4D (ARL4D), SH3 domain containing ring finger 2 (SH3RF2), and Cadherin 3 (CDH3) genes to be the most significant prognostic gene markers. These genes were used to construct a risk model that separated the BLCA patients into high and low-risk groups. The risk model was also validated in an external dataset by performing survival analysis between high and low-risk groups with a p-value < 0.001 and the result showed the high group was significantly associated with poor prognosis compared to the low group. Single-cell analyses revealed the elevated level of these genes in the tumor microenvironment and associated with immune response. High-grade patients also tend to have a high expression of these genes compared to low-grade patients. In conclusion, this research developed a six-gene signature that is pertinent to the prediction of overall survival (OS) and might contribute to the advancement of precision medicine in the management of bladder cancer.

A transcriptome study of p53-pathway related prognostic gene signature set in bladder cancer.

p53 pathway is important in tumorigenesis. However, no study has been performed to specifically investigate the role of p53 pathway genes in bladder cancer (BLCA). In this study, transcriptomics data of muscle invasive bladder cancer patients (n = 411) from The Cancer Genome Atlas (TCGA) were investigated. Using the hallmark p53 pathway gene set, the Non-Negative Matrix factorization (NMF) analysis identified two subtypes (C1 and C2). Clinical, survival, and immunological analysis were done to validate distinct characteristics of the subtypes. Pathway enrichment analysis showed the subtype C1 with poor prognosis having enrichment in genes of the immunity related pathways, where C2 subtype with better prognosis being enriched in genes of the steroid synthesis and drug metabolism pathways. A signature gene set consisting of MDGA2, GNLY, GGT2, UGT2B4, DLX1, and DSC1 was created followed by a risk model. Their expressions were analyzed in RNA extracted from the blood and matched tumor tissues of BLCA patients (n = 10). DSC1 had significant difference of expression (p = 0.005) between the blood and tumor tissues in our BLCA samples. Contrary to the usual normal bladder tissue to blood ratio, DLX1 expression was lower (p = 0.02734) in tumor tissues than in blood. Being the first research of p53 pathway related signature gene set in bladder cancer, this study potentially has a substantial impact on the development of biomarkers for BLCA.

Simplex Droplet Digital PCR Assays for the Detection of TERT Promoter Mutations in Urine Samples for the Non-invasive Diagnosis of Urothelial Cancer.

Somatic mutations in the telomerase reverse transcriptase (TERT) promoter region are highly frequent in urothelial cancer (UC), and their detection in urine (cell-free DNA from the urine supernatant or DNA from exfoliated cells in the urine pellet) has demonstrated promising evidence as putative non-invasive biomarkers for UC detection and monitoring. However, detecting these tumour-derived mutations in urine requires highly sensitive methods, capable of measuring low-allelic fraction mutations. We developed sensitive droplet digital PCR (ddPCR) assays for detecting urinary TERT promoter mutations (uTERTpm), targeting the two most common mutations (C228T and C250T), as well as the rare A161C, C228A, and CC242-243TT mutations. Here, we described the step-by-step protocol uTERTpm mutation screening using simplex ddPCR assays and give some recommendations for isolation of DNA from urine samples. We also provide limits of detection for the two most frequent mutations and discuss advantages of the method for clinical implementation of the assays for the detection and monitoring of UC.

Dynamic antibody response in SARS-CoV-2 infected patients and COVID-19 vaccine recipients alongside vaccine effectiveness in comorbid and multimorbid groups.

Objectives: Underlying medical conditions are critical risk factors for COVID-19 susceptibility and its rapid clinical manifestation. Therefore, the preexisting burden of non-communicable diseases (NCDs) makes the preparedness for COVID-19 more challenging for low- and middle-income countries (LMICs). These countries have relied on vaccination campaigns as an effective measure to tackle COVID-19. In this study, we investigated the impact of comorbidities on humoral antibody responses against the specific receptor-binding domain (RBD) of SARS-CoV2. Methods: A total of 1005 patients were selected for the SARS-CoV-2 specific immunoglobulin G (IgG1, IgG2, IgG3, and IgG4 subclasses) and total antibody (TAb) tests (IgG and IgM), of which 912 serum samples were ultimately selected based on the specimen cutoff analyte value. Patients with multimorbidity (N = 60) were recruited for follow-up studies from the initial cohort, and their immune response (IgG and TAb) was measured at multiple time points after the second dose of vaccination. Siemens Dimension Vista SARS-CoV-2 IgG (CV2G) and SARS-CoV-2 TAb assay (CV2T) were used to carry out the serology test. Results: Out of a total of 912 participants, vaccinated individuals (N = 711) had detectable antibody responses up to 7-8 months. The synergistic effect of natural infection and vaccine response was also studied. Participants with breakthrough infections (N = 49) mounted a greater antibody response compared to individuals with normal vaccination response (N = 397) and those who were naturally infected before receiving the second dose of vaccine (N = 132). Investigation of the impact of comorbidities revealed that diabetes mellitus (DM) (N = 117) and kidney disease (N = 50) had a significant negative impact on the decline of the humoral antibody response against SARS-CoV-2. IgG and TAb declined more rapidly in diabetic and kidney disease patients compared to the other four comorbid groups. Follow-up studies demonstrated that antibody response rapidly declined within 4 months after receiving the second dose. Conclusion: The generalized immunization schedule for COVID-19 needs to be adjusted for high-risk comorbid groups, and a booster dose must be administered early within 4 months after receiving the second dose.

Association of Chronic Toxoplasma gondii Infection with Pro-Inflamatory Cytokine Interleukin (IL)-12 Responses in Type-2 Diabetes Mellitus Patients of Bangladesh.

Toxoplasma gondii is an intracellular protozoan parasite that causes toxoplasmosis in around one-third of the world population, particularly in pregnant women and immunocompromised individuals. Diabetes mellitus (DM) is one of the most severe global health challenges in the 21st century, and especially, type-2 diabetes mellitus (T2DM) accounts for 90% of the diabetes cases diagnosed globally. In Bangladesh, the rate of T2DM is rising gradually with the improvement in living standards. The aim of this study is to find out the correlation between latent toxoplasmosis and T2DM, emphasizing the pro-inflammatory cytokine immunity. For this, 100 (N = 100) patients with T2DM and 100 (N = 100) healthy controls were enrolled to determine the seroprevalence of toxoplasmosis using enzyme-linked immunosorbent assay (ELISA). In addition, ELISA was also performed to determine the level of pro-inflammatory cytokine, interleukin (IL)-12, to understand its role in the development of toxoplasmosis. In our study, 39.39% of the T2DM patients were positive with anti-T. gondii Immunoglobulin G by ELISA, whereas the rate of seropositivity in healthy controls was 39.73%. We did not find significant association between T. gondii infection and T2DM, but our data confirmed a high prevalence of chronic toxoplasmosis in Bangladeshi population. From hematology tests, it was found that the T2DM patients had significantly lower levels of total white blood cells (P = 0.0015), circulating eosinophils (P = 0.0026), and neutrophils (P = 0.0128) than the healthy controls. On the other hand, the levels of lymphocytes (P = 0.0204) and monocytes (P = 0.0067) were significantly higher in patients. Furthermore, T. gondii infected T2DM patients had significantly higher levels of IL-12 than the healthy controls (P = 0.026), suggesting a link between parasitic infection and IL-12 secretion. Further studies are to be performed to find out the exact cause of high prevalence of chronic T. gondii infection in Bangladeshi population.

Construction of copy number variation landscape and characterization of associated genes in a Bangladeshi cohort of neurodevelopmental disorders.

Introduction: Copy number variations (CNVs) play a critical role in the pathogenesis of neurodevelopmental disorders (NDD) among children. In this study, we aim to identify clinically relevant CNVs, genes and their phenotypic characteristics in an ethnically underrepresented homogenous population of Bangladesh. Methods: We have conducted chromosomal microarray analysis (CMA) for 212 NDD patients with male to female ratio of 2.2:1.0 to identify rare CNVs. To identify candidate genes within the rare CNVs, gene constraint metrics [i.e., "Critical-Exon Genes (CEGs)"] were applied to the population data. Autism Diagnostic Observation Schedule-Second Edition (ADOS-2) was followed in a subset of 95 NDD patients to assess the severity of autism and all statistical tests were performed using the R package. Results: Of all the samples assayed, 12.26% (26/212) and 57.08% (121/212) patients carried pathogenic and variant of uncertain significance (VOUS) CNVs, respectively. While 2.83% (6/212) patients' pathogenic CNVs were found to be located in the subtelomeric regions. Further burden test identified females are significant carriers of pathogenic CNVs compared to males (OR = 4.2; p = 0.0007). We have observed an increased number of Loss of heterozygosity (LOH) within cases with 23.85% (26/109) consanguineous parents. Our analyses on imprinting genes show, 36 LOH variants disrupting 69 unique imprinted genes and classified these variants as VOUS. ADOS-2 subset shows severe social communication deficit (p = 0.014) and overall ASD symptoms severity (p = 0.026) among the patients carrying duplication CNV compared to the CNV negative group. Candidate gene analysis identified 153 unique CEGs in pathogenic CNVs and 31 in VOUS. Of the unique genes, 18 genes were found to be in smaller (<1 MB) focal CNVs in our NDD cohort and we identified PSMC3 gene as a strong candidate gene for Autism Spectrum Disorder (ASD). Moreover, we hypothesized that KMT2B gene duplication might be associated with intellectual disability. Conclusion: Our results show the utility of CMA for precise genetic diagnosis and its integration into the diagnosis, therapy and management of NDD patients.

TERT Promoter Mutations as Simple and Non-Invasive Urinary Biomarkers for the Detection of Urothelial Bladder Cancer in a High-Risk Region.

Bladder cancer (BC) is the 10th most common cancer in the world. While there are FDA-approved urinary assays to detect BC, none have demonstrated sufficient sensitivity and specificity to be integrated into clinical practice. Telomerase Reverse Transcriptase (TERT) gene mutations have been identified as the most common BC mutations that could potentially be used as non-invasive urinary biomarkers to detect BC. This study aims to evaluate the validity of these tests to detect BC in the Kerman province of Iran, where BC is the most common cancer in men. Urine samples of 31 patients with primary (n = 11) or recurrent (n = 20) bladder tumor and 50 controls were prospectively collected. Total urinary DNA was screened for the TERT promoter mutations (uTERTpm) by Droplet Digital PCR (ddPCR) assays. The performance characteristics of uTERTpm and the influence by disease stage and grade were compared to urine cytology results. The uTERTpm was 100% sensitive and 88% specific to detect primary BC, while it was 50% sensitive and 88% specific in detecting recurrent BC. The overall sensitivity and specificity of uTERTpm to detect bladder cancer were 67.7% and 88.0%, respectively, which were consistent across different tumor stages and grades. The most frequent uTERTpm mutations among BC cases were C228T (18/31), C250T (4/31), and C158A (1/31) with mutant allelic frequency (MAF) ranging from 0.2% to 63.3%. Urine cytology demonstrated a similar sensitivity (67.7%), but lower specificity (62.0%) than uTERTpm in detecting BC. Combined uTERTpm and urine cytology increased the sensitivity to 83.8%, but decreased the specificity to 52.0%. Our study demonstrated promising diagnostic accuracy for the uTERTpm as a non-invasive urinary biomarker to detect, in particular, primary BC in this population.

The status and analysis of common mutations found in the SARS-CoV-2 whole genome sequences from Bangladesh.

Rapid emergence of covid-19 variants by continuous mutation made the world experience continuous waves of infections and as a result, a huge number of death-toll recorded so far. It is, therefore, very important to investigate the diversity and nature of the mutations in the SARS-CoV-2 genomes. In this study, the common mutations occurred in the whole genome sequences of SARS-CoV-2 variants of Bangladesh in a certain timeline were analyzed to better understand its status. Hence, a total of 78 complete genome sequences available in the NCBI database were obtained, aligned and further analyzed. Scattered Single Nucleotide Polymorphisms (SNPs) were identified throughout the genome of variants and common SNPs such as: 241:C>T in the 5'UTR of Open Reading Frame 1A (ORF1A), 3037: C>T in Non-structural Protein 3 (NSP3), 14,408: C>T in ORF6 and 23,402: A>G, 23,403: A>G in Spike Protein (S) were observed, but all of them were synonymous mutations. About 97% of the studied genomes showed a block of tri-nucleotide alteration (GGG>AAC), the most common non-synonymous mutation in the 28,881-28,883 location of the genome. This block results in two amino acid changes (203-204: RG>KR) in the SR rich motif of the nucleocapsid (N) protein of SARS-CoV-2, introducing a lysine in between serine and arginine. The N protein structure of the mutant was predicted through protein modeling. However, no observable difference was found between the mutant and the reference (Wuhan) protein. Further, the protein stability changes upon mutations were analyzed using the I-Mutant2.0 tool. The alteration of the arginine to lysine at the amino acid position 203, showed reduction of entropy, suggesting a possible impact on the overall stability of the N protein. The estimation of the non-synonymous to synonymous substitution ratio (dN/dS) were analyzed for the common mutations and the results showed that the overall mean distance among the N-protein variants were statistically significant, supporting the non-synonymous nature of the mutations. The phylogenetic analysis of the selected 78 genomes, compared with the most common genomic variants of this virus across the globe showed a distinct cluster for the analyzed Bangladeshi sequences. Further studies are warranted for conferring any plausible association of these mutations with the clinical manifestation.

Comprehensive Characterization of the Coding and Non-Coding Single Nucleotide Polymorphisms in the Tumor Protein p63 (TP63) Gene Using In Silico Tools.

Single nucleotide polymorphisms (SNPs) help to understand the phenotypic variations in humans. Genome-wide association studies (GWAS) have identified SNPs located in the tumor protein 63 (TP63) locus to be associated with the genetic susceptibility of cancers. However, there is a lack of in-depth characterization of the structural and functional impacts of the SNPs located at the TP63 gene. The current study was designed for the comprehensive characterization of the coding and non-coding SNPs in the human TP63 gene for their functional and structural significance. The functional and structural effects of the SNPs were investigated using a wide variety of computational tools and approaches, including molecular dynamics (MD) simulation. The deleterious impact of eight nonsynonymous SNPs (nsSNPs) affecting protein stability, structure, and functions was measured by using 13 bioinformatics tools. These eight nsSNPs are in highly conserved positions in protein and were predicted to decrease protein stability and have a deleterious impact on the TP63 protein function. Molecular docking analysis showed five nsSNPs to reduce the binding affinity of TP63 protein to DNA with significant results for three SNPs (R319H, G349E, and C347F). Further, MD simulations revealed the possible disruption of TP63 and DNA binding, hampering the essential protein function. PolymiRTS study found five non-coding SNPs in miRNA binding sites, and the GTEx portal recognized five eQTLs SNPs in single tissue of the lung, heart (LV), and cerebral hemisphere (brain). Characterized nsSNPs and non-coding SNPs will help researchers to focus on TP63 gene loci and ascertain their association with certain diseases.

A computational in silico approach to predict high-risk coding and non-coding SNPs of human PLCG1 gene.

PLCG1 gene is responsible for many T-cell lymphoma subtypes, including peripheral T-cell lymphoma (PTCL), angioimmunoblastic T-cell lymphoma (AITL), cutaneous T-cell lymphoma (CTCL), adult T-cell leukemia/lymphoma along with other diseases. Missense mutations of this gene have already been found in patients of CTCL and AITL. The non-synonymous single nucleotide polymorphisms (nsSNPs) can alter the protein structure as well as its functions. In this study, probable deleterious and disease-related nsSNPs in PLCG1 were identified using SIFT, PROVEAN, PolyPhen-2, PhD-SNP, Pmut, and SNPS&GO tools. Further, their effect on protein stability was checked along with conservation and solvent accessibility analysis by I-mutant 2.0, MUpro, Consurf, and Netsurf 2.0 server. Some SNPs were finalized for structural analysis with PyMol and BIOVIA discovery studio visualizer. Out of the 16 nsSNPs which were found to be deleterious, ten nsSNPs had an effect on protein stability, and six mutations (L411P, R355C, G493D, R1158H, A401V and L455F) were predicted to be highly conserved. Among the six highly conserved mutations, four nsSNPs (R355C, A401V, L411P and L455F) were part of the catalytic domain. L411P, L455F and G493D made significant structural change in the protein structure. Two mutations-Y210C and R1158H had post-translational modification. In the 5' and 3' untranslated region, three SNPs, rs139043247, rs543804707, and rs62621919 showed possible miRNA target sites and DNA binding sites. This in silico analysis has provided a structured dataset of PLCG1 gene for further in vivo researches. With the limitation of computational study, it can still prove to be an asset for the identification and treatment of multiple diseases associated with the target gene.

An in-depth in silico and immunoinformatics approach for designing a potential multi-epitope construct for the effective development of vaccine to combat against SARS-CoV-2 encompassing variants of concern and interest.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the latest of the several viral pathogens that have acted as a threat to human health around the world. Thus, to prevent COVID-19 and control the outbreak, the development of vaccines against SARS-CoV-2 is one of the most important strategies at present. The study aimed to design a multi-epitope vaccine (MEV) against SARS-CoV-2. For the development of a more effective vaccine, 1549 nucleotide sequences were taken into consideration, including the variants of concern (B.1.1.7, B.1.351, P.1 and, B.1.617.2) and variants of interest (B.1.427, B.1.429, B.1.526, B.1.617.1 and P.2). A total of 11 SARS-CoV-2 proteins (S, N, E, M, ORF1ab polyprotein, ORF3a, ORF6, ORF7a, ORF7b, ORF8, ORF10) were targeted for T-cell epitope prediction and S protein was targeted for B-cell epitope prediction. MEV was constructed using linkers and adjuvant beta-defensin. The vaccine construct was verified, based on its antigenicity, physicochemical properties, and its binding potential, with toll-like receptors (TLR2, TLR4), ACE2 receptor and B cell receptor. The selected vaccine construct showed considerable binding with all the receptors and a significant immune response, including elevated antibody titer and B cell population along with augmented activity of TH cells, Tc cells and NK cells. Thus, immunoinformatics and in silico-based approaches were used for constructing MEV which is capable of eliciting both innate and adaptive immunity. In conclusion, the vaccine construct developed in this study has all the potential for the development of a next-generation vaccine which may in turn effectively combat the new variants of SARS-CoV-2 identified so far. However, in vitro and animal studies are warranted to justify our findings for its utility as probable preventive measure.

Structure analysis of deleterious nsSNPs in human PALB2 protein for functional inference.

Partner and Localizer of BRCA2 or PALB2 is a typical tumor suppressor protein, that responds to DNA double stranded breaks through homologous recombination repair. Heterozygous mutations in PALB2 are known to contribute to the susceptibility of breast and ovarian cancer. However, there is no comprehensive study characterizing the structural and functional impacts of SNPs located in the PALB2 gene. Therefore, it is of interest to document a comprehensive analysis of coding and non-coding SNPs located at the PALB2 loci using in silico tools. The data for 1455 non-synonymous SNPs (nsSNPs) located in the PALB2 loci were retrieved from the dbSNP database. Comprehensive characterization of the SNPs using a combination of in silico tools such as SIFT, PROVEAN, PolyPhen, PANTHER, PhD-SNP, Pmut, MutPred 2.0 and SNAP-2, identified 28 functionally important SNPs. Among these, 16 nsSNPs were further selected for structural analysis using conservation profile and protein stability. The most deleterious nsSNPs were documented within the WD40 domain of PALB2. A general outline of the structural consequences of each variant was developed using the HOPE project data. These 16 mutant structures were further modelled using SWISS Model and three most damaging mutant models (rs78179744, rs180177123 and rs45525135) were identified. The non-coding SNPs in the 3' UTR region of the PALB2 gene were analyzed for altered miRNA target sites. The comprehensive characterization of the coding and non-coding SNPs in the PALB2 locus has provided a list of damaging SNPs with potential disease association. Further validation through genetic association study will reveal their clinical significance.

Structural analogues of existing anti-viral drugs inhibit SARS-CoV-2 RNA dependent RNA polymerase: A computational hierarchical investigation.

The Coronavirus Disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) became a pandemic, resulting in an exponentially increased mortality globally and scientists all over the world are struggling to find suitable solutions to combat it. Multiple repurposed drugs have already been in several clinical trials or recently completed. However, none of them shows any promising effect in combating COVID-19. Therefore, developing an effective drug is an unmet global need. RdRp (RNA dependent RNA polymerase) plays a pivotal role in viral replication. Therefore, it is considered as a prime target of drugs that may treat COVID-19. In this study, we have screened a library of compounds, containing approved RdRp inhibitor drugs that were or in use to treat other viruses (favipiravir, sofosbuvir, ribavirin, lopinavir, tenofovir, ritonavir, galidesivir and remdesivir) and their structural analogues, in order to identify potential inhibitors of SARS-CoV-2 RdRp. Extensive screening, molecular docking and molecular dynamics show that five structural analogues have notable inhibitory effects against RdRp of SARS-CoV-2. Importantly, comparative protein-antagonists interaction revealed that these compounds fit well in the pocket of RdRp. ADMET analysis of these compounds suggests their potency as drug candidates. Our identified compounds may serve as potential therapeutics for COVID-19.

Non-coding Single Nucleotide Variants of Renin and the (Pro)renin Receptor are Associated with Polygenic Diseases in a Bangladeshi Population.

Non-coding variants or single-nucleotide polymorphisms (SNPs) play pivotal roles in orchestrating pathogeneses of polygenic diseases, including hypertension (HTN) and diabetes. Renin-angiotensin system (RAS) components-renin and (pro)renin receptor [(P)RR]-maintain homeostasis of body fluids. Genetic variants of RAS components are associated with risk of HTN and type 2 diabetes (T2D) in different ethnic groups. We identified associations of SNPs within the renin and (P)RR genes with HTN, T2D, and T2D-associated hypertension in 911 unrelated Bangladeshi individuals. Five non-coding SNPs were involved in modulating regulatory elements in diverse cell types when tagged with other SNPs. rs61827960 was not associated with any disease; rs3730102 was associated with increased risk of HTN and T2D while under dominant model, it showed protective role against T2D-associated HTN. SNP rs11571079 was associated with increased risk of HTN and T2D-associated HTN and decreased risk of T2D, exerting a protective effect. Renin haplotypes GCA and GTG were related to increased risk of T2D and T2D-associated HTN, respectively. Heterogeneous linkage of genotypic and allelic frequencies of rs2968915 and rs3112298 of (P)RR was observed. The (P)RR haplotype GA was associated with increased risk of HTN and significantly decreased risk of T2D. These findings highlight important roles of non-coding variants of renin and (P)RR genes in the etiology of several polygenic diseases.

Association study of leukocyte telomere length and genetic polymorphism within hTERT promoter with type 2 diabetes in Bangladeshi population.

Telomeres are protective cap on the ends of DNA of non-coding tandem repeats of TTAGGG. Human telomerase reverse transcriptase (hTERT) is a catalytic subunit of telomerase that maintains the structure of telomeres. Type 2 diabetes (T2D) affects multi-organ and telomere length by altering telomerase activity. We aimed to evaluate the relative telomere length (RTL) and risk association of rs2853669 with T2D in Bangladeshi population. RTL was measured in 408 unrelated Bangladeshi (224 T2D and 184 healthy) using primers for target gene and reference gene albumin. Genotypic frequencies for rs2853669 were determined using TaqMan® probes. The mean level of age adjusted RTL (AARTL) varied significantly between the healthy and individuals with T2D for all the genotypes with respect to rs2853669. Moreover, healthy individuals had significantly higher AARTL than T2D. Similar findings were observed when study participants were stratified based on their gender. Association studies revealed that under codominant model of inheritance, TC genotype showed protective role against development of type 2 diabetes. This study suggests a possible role of telomere biology in T2DM, but their association needs to be evaluated further with a larger series and matched healthy controls.

Development of Sensitive Droplet Digital PCR Assays for Detecting Urinary TERT Promoter Mutations as Non-Invasive Biomarkers for Detection of Urothelial Cancer.

Somatic mutations in the telomerase reverse transcriptase (TERT) promoter regions are frequent events in urothelial cancer (UC) and their detection in urine (supernatant cell-free DNA or DNA from exfoliated cells) could serve as putative non-invasive biomarkers for UC detection and monitoring. However, detecting these tumor-borne mutations in urine requires highly sensitive methods, capable of measuring low-level mutations. In this study, we developed sensitive droplet digital PCR (ddPCR) assays for detecting TERT promoter mutations (C228T, C228A, CC242-243TT, and C250T). We tested the C228T and C250T ddPCR assays on all samples with sufficient quantity of urinary DNA (urine supernatant cell-free DNA (US cfDNA) or urine pellet cellular DNA (UP cellDNA)) from the DIAGURO (n = 89/93 cases and n = 92/94 controls) and from the IPO-PORTO (n = 49/50 cases and n = 50/50 controls) series that were previously screened with the UroMuTERT assay and compared the performance of the two approaches. In the DIAGURO series, the sensitivity and specificity of the ddPCR assays for detecting UC using either US cfDNA or UP cellDNA were 86.8% and 92.4%. The sensitivity was slightly higher than that of the UroMuTERT assay in the IPO-PORTO series (67.4% vs. 65.3%, respectively), but not in the DIAGURO series (86.8% vs. 90.7%). The specificity was 100% in the IPO-PORTO controls for both the UroMuTERT and ddPCR assays, whereas in the DIAGURO series, the specificity dropped for ddPCR (92.4% versus 95.6%). Overall, an almost perfect agreement between the two methods was observed for both US cfDNA (n = 164; kappa coefficient of 0.91) and UP cellDNA (n = 280; kappa coefficient of 0.94). In a large independent series of serial urine samples from DIAGURO follow-up BC cases (n = 394), the agreement between ddPCR and UroMuTERT was (i) strong (kappa coefficient of 0.87), regardless of urine DNA types (kappa coefficient 0.89 for US cfDNA and 0.85 for UP cellDNA), (ii) the highest for samples with mutant allelic fractions (MAFs) > 2% (kappa coefficient of 0.99) and (iii) only minimal for the samples with the lowest MAFs (< 0.5%; kappa coefficient 0.32). Altogether, our results indicate that the two methods (ddPCR and UroMuTERT) for detecting urinary TERT promoter mutations are comparable and that the discrepancies relate to the detection of low-allelic fraction mutations. The simplicity of the ddPCR assays makes them suitable for implementation in clinical settings.

Urinary TERT promoter mutations are detectable up to 10 years prior to clinical diagnosis of bladder cancer: Evidence from the Golestan Cohort Study.

BACKGROUND: Detecting pre-clinical bladder cancer (BC) using urinary biomarkers may provide a valuable opportunity for screening and management. Telomerase reverse transcriptase (TERT) promoter mutations detectable in urine have emerged as promising BC biomarkers. METHODS: We performed a nested case-control study within the population-based prospective Golestan Cohort Study (50,045 participants, followed up to 14 years) and assessed TERT promoter mutations in baseline urine samples from 38 asymptomatic individuals who subsequently developed primary BC and 152 matched controls using a Next-Generation Sequencing-based single-plex assay (UroMuTERT) and droplet digital PCR assays. FINDINGS: Results were obtained for 30 cases and 101 controls. TERT promoter mutations were detected in 14 pre-clinical cases (sensitivity 46·67%) and none of the controls (specificity 100·00%). At an estimated BC cumulative incidence of 0·09% in the cohort, the positive and negative predictive values were 100·00% and 99·95% respectively. The mutant allelic fractions decreased with the time interval from urine collection until BC diagnosis (p = 0·033) but the mutations were detectable up to 10 years prior to clinical diagnosis. INTERPRETATION: Our results provide the first evidence from a population-based prospective cohort study of the potential of urinary TERT promoter mutations as promising non-invasive biomarkers for early detection of BC. Further studies should validate this finding and assess their clinical utility in other longitudinal cohorts. FUNDING: French Cancer League, World Cancer Research Fund International, Cancer Research UK, Tehran University of Medical Sciences, the International Agency for Research on Cancer, and the U.S. National Cancer Institute.