Identifying Oncogenic Missense Single Nucleotide Polymorphisms in Human SAT1 Gene Using Computational Algorithms and Molecular Dynamics Tools.

BACKGROUND: The human SAT1 gene encodes spermidine/spermine N1-acetyltransferase 1 (SSAT1), a regulatory biological catalyst of polyamine catabolism. Numerous essential biological processes, such as cellular proliferation, differentiation, and survival, depend on polyamines like spermidine and spermine. Thus, SSAT1 is involved in key cellular activities such as proliferation and survival of cells and mediates various diseases including cancer. A plethora of studies established the involvement of missense single nucleotide polymorphisms (SNPs) in numerous pathological conditions due to their ability to adversely affect the structure and subsequent function of the protein. AIMS: To date, an in silico study to identify the pathogenic missense SNPs of the human SAT1 gene has not been accomplished yet. This study aimed to filter the missense SNPs that were functionally detrimental and pathogenic. METHODS AND RESULTS: The rs757435207 (I21N) was ascertained to be the most deleterious and pathogenic by all algorithmic tools. Stability and evolutionary conservation analysis tools also stated that I21N variant decreased the stability and was located in the highly conserved residue. Molecular dynamics simulation revealed that I21N caused substantial alterations in the conformational stability and dynamics of the SSAT1 protein. Consequently, the I21N variant could disrupt the native functional roles of the SSAT1 enzyme. CONCLUSION: Therefore, the I21N variant was identified and concluded to be an oncogenic missense variant of the human SAT1 gene. Overall, the findings of this study would be a great directory of future experimental research to develop personalized medicine.

Identification and analysis of oncogenic non-synonymous single nucleotide polymorphisms in the human NRAS gene: An exclusive in silico study.

BACKGROUND: N-ras protein is encoded by the NRAS gene and operates as GDP-GTP-controlled on/off switching. N-ras interacts with cellular signaling networks that regulate various cellular activities including cell proliferation and survival. The nonsynonymous single nucleotide polymorphism (nsSNPs)-mediated alteration can substantially disrupt the structure and activity of the corresponding protein. N-ras has been reported to be associated with numerous diseases including cancers due to the nsSNPs. A comprehensive study on the NRAS gene to unveil the potentially damaging and oncogenic nsSNPs is yet to be accomplished. Hence, this extensive in silico study is intended to identify the disease-associated, specifically oncogenic nsSNPs of the NRAS gene. RESULTS: Out of 140 missense variants, 7 nsSNPs (I55R, G60E, G60R, Y64D, L79F, D119G, and V152F) were identified to be damaging utilizing 10 computational tools that works based on different algorithms with high accuracy. Among those, G60E, G60R, and D119G variants were further filtered considering their location in the highly conserved region and later identified as oncogenic variants. Interestingly, G60E and G60R variants were revealed to be particularly associated with lung adenocarcinoma, rhabdomyosarcoma, and prostate adenocarcinoma. Therefore, D119G could be subjected to detailed investigation for identifying its association with specific cancer. CONCLUSION: This in silico study identified the deleterious and oncogenic missense variants of the human NRAS gene that could be utilized for designing further experimental investigation. The outcomes of this study would be worthwhile in future research for developing personalized medicine.

Integrated bioinformatics analysis reveals upregulated extracellular matrix hub genes in pancreatic cancer: Implications for diagnosis, prognosis, immune infiltration, and therapeutic strategies.

BACKGROUND: Pancreatic cancer (PC) stands out as one of the most formidable malignancies and exhibits an exceptionally unfavorable clinical prognosis due to the absence of well-defined diagnostic indicators and its tendency to develop resistance to therapeutic interventions. The primary objective of this present study was to identify extracellular matrix (ECM)-related hub genes (HGs) and their corresponding molecular signatures, with the intent of potentially utilizing them as biomarkers for diagnostic, prognostic, and therapeutic applications. METHODS: Three microarray datasets were sourced from the NCBI database to acquire upregulated differentially expressed genes (DEGs), while MatrisomeDB was employed for filtering ECM-related genes. Subsequently, a protein-protein interaction (PPI) network was established using the STRING database. The created network was visually inspected through Cytoscape, and HGs were identified using the CytoHubba plugin tool. Furthermore, enrichment analysis, expression pattern analysis, clinicopathological correlation, survival analysis, immune cell infiltration analysis, and examination of chemical compounds were carried out using Enrichr, GEPIA2, ULCAN, Kaplan Meier plotter, TIMER2.0, and CTD web platforms, respectively. The diagnostic and prognostic significance of HGs was evaluated through the ROC curve analysis. RESULTS: Ten genes associated with ECM functions were identified as HGs among 131 DEGs obtained from microarray datasets. Notably, the expression of these HGs exhibited significantly (p < 0.05) higher in PC, demonstrating a clear association with tumor advancement. Remarkably, higher expression levels of these HGs were inversely correlated with the likelihood of patient survival. Moreover, ROC curve analysis revealed that identified HGs are promising biomarkers for both diagnostic (AUC > 0.75) and prognostic (AUC > 0.64) purposes. Furthermore, we observed a positive correlation between immune cell infiltration and the expression of most HGs. Lastly, our study identified nine compounds with significant interaction profiles that could potentially act as effective chemical agents targeting the identified HGs. CONCLUSION: Taken together, our findings suggest that COL1A1, KRT19, MMP1, COL11A1, SDC1, ITGA2, COL1A2, POSTN, FN1, and COL5A1 hold promise as innovative biomarkers for both the diagnosis and prognosis of PC, and they present as prospective targets for therapeutic interventions aimed at impeding the progression PC.

Serum creatinine phosphokinase: A potential prognostic marker in assessing clinical severity with organophosphorus poisoning.

INTRODUCTION: Organophosphorus compound (OPC) poisoning undoubtedly being a major concern in cultivation sites of the developing world, including Bangladesh. Two potential biomarkers, for example, serum creatine phosphokinase (CPK) and lactate dehydrogenase (LDH), are widely used in OPC poisoning severity indicators in patients. In this study, we sought to correlate the severity score of acute OPC poisoning with CPK or LDH level and subsequently explore their prognostic value. METHODS: This study was performed on a total of 70 patients with OPC poisoning admitted to the inpatient care unit at a territory-based hospital in Bangladesh. Sociodemographics and poison types were recorded, and severity was assessed according to Peradeniya Organophosphorus Poisoning (POP) scale. Serum CPK and LDH levels were measured and recorded. RESULTS: A total of seventy OPC patients were included with male to female ratio of 1.33:1, respectively, with a mean age of 28.7 ± 12.8 years. Chlorpyrifos and methylparathion were the most commonly utilized OP compounds, accounting for 42.9% and 28.6%, respectively. Among the OPC patients, the majority were married homemakers from rural areas. According to POP score, 55.7% and 37.1% of patients were categorized as mild and moderate, whereas very few were found to be severe. The mean serum CPK and LDH of OPC-patients at admission time were 235.6 ± 79.8 IU/L and 348.3 ± 154.1 IU/L, respectively. Serum CPK, atropine dose and hospital stay strongly correlated with clinical severity. CONCLUSION: We conclude that the serum CPK level strongly correlates with the degree of OPC poisoning and can be used as a predictor of the clinical intervention approaches.

RLLB/Alb ratio: a promising noninvasive diagnostic marker in assessing esophageal varices in cirrhotic patients.

BACKGROUND: Endoscopy has long been widely used to screen for esophageal varices (EV) in cirrhotic patients. Recurrent endoscopy is a significant burden for the healthcare system of the endoscopic unit as well as uncomfortable and high costs for patients. This study intended to prognosticate Right Liver Lobe Diameter/Serum Albumin Ratio (RLLD/Alb) as a non-invasive approach in the early diagnosis of EV among chronic liver disease (CLD) Bangladeshi patients enrolled in a specific hospital. PARTICIPANTS AND METHODS: A total of 150 admitted patients with CLD were included in the study. Patients were subjected through a comprehensive biochemical checkup and upper digestive endoscopic or ultrasonographic inspection. The correlation was evaluated between the RLLD/Alb ratio and esophageal varices grades. RESULTS: The upper digestive endoscopy demonstration among 150 patients resulted in no EV in 18%, while 24% of patients was identified as EV grade I, 20% as grade II, 20% as grade III, and 18% patients as grade IV. The mean value of the RLLD/Alb ratio was 4.89 ± 1.49 (range from 2.30 to 8.45). The RLLD/Alb ratio diagnosed the EV employing the cut-off value of 4.01 with 85.3% sensitivity and 68.8% specificity. Furthermore, it was positively correlated with the grading of EV, when this ratio increased the grading of EV increases and vice versa (r = 0.630, p < 0.001). CONCLUSION: The RLLD/Alb ratio is a non-invasive parameter giving exact guidance relevant to the ascertainment of the existence of EV and their grading in chronic liver disease patients.

Computational algorithmic and molecular dynamics study of functional and structural impacts of non-synonymous single nucleotide polymorphisms in human DHFR gene.

Human dihydrofolate reductase (DHFR) is a conserved enzyme that is central to folate metabolism and is widely targeted in pathogenic diseases as well as cancers. Although studies have reported the fact that genetic mutations in DHFR leads to a rare autosomal recessive inborn error of folate metabolism and drug resistance, there is a lack of an extensive study on how the deleterious non-synonymous SNPs (nsSNPs) disrupt its phenotypic effects. In this study, we aim at discovering the structural and functional consequences of nsSNPs in DHFR by employing a combined computational approach consisting of ten recently developed in silico tools for identification of damaging nsSNPs and molecular dynamics (MD) simulation for getting deeper insights into the magnitudes of damaging effects. Our study revealed the presence of 12 most deleterious nsSNPs affecting the native phenotypic effects, with three (R71T, G118D, Y122D) identified in the co-factor and ligand binding active sites. MD simulations also suggested that these three SNPs particularly Y122D, alter the overall structural flexibility and dynamics of the native DHFR protein which can provide more understandings into the crucial roles of these mutants in influencing the loss of DHFR function.

CRISPR is a useful biological tool for detecting nucleic acid of SARS-CoV-2 in human clinical samples.

The recent pandemic of novel coronavirus disease (COVID-19) has spread globally and infected millions of people. The quick and specific detection of the nucleic acid of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) remains a challenge within healthcare providers. Currently, quantitative reverse transcription-polymerase chain reaction (RT-qPCR) is the widely used method to detect the SARS-CoV-2 from the human clinical samples. RT-qPCR is expensive equipment and needs skilled personnel as well as lengthy detection time. RT-qPCR limitation needed an alternative healthcare technique to overcome with a fast and cheaper detection method. By applying the principles of CRISPR technology, several promising detection methods giving hope to the healthcare community. CRISPR-based detection methods include SHERLOCK-Covid, STOP-Covid, AIOD-CRISPR, and DETECTR platform. These methods have comparative advantages and drawbacks. Among these methods, AIOD-CRISPR and DETECTR are reasonably better diagnostic methods than the others if we compare the time taken for the test, the cost associated with each test, and their capability of detecting SARS-CoV-2 in the clinical samples. It may expect that the promising CRISPR-based methods would facilitate point-of-care (POC) applications in the CRISPR-built next-generation novel coronavirus diagnostics.