Analysis of Somatic Mutations in the TCGA-LIHC Whole Exome Sequence to Identify the Neoantigen for Immunotherapy in Hepatocellular Carcinoma.

There are numerous clinically proven methods for treating cancer worldwide. Immunotherapy has been used to treat cancer with significant success in the current studies. The purpose of this work is to identify somatically altered target gene neoantigens and investigate liver cancer-related immune cell interaction and functional changes for potential immunotherapy in future clinical trials. Clinical patient data from the Cancer Genome Atlas (TCGA) database were used in this investigation. The R maf utility package was used to perform somatic analysis. The 17-mer peptide neoantigens were extracted using an in-house Python software called Peptide.py. Additionally, the epitope analysis was conducted using NetMHCpan4.1 program. Neopeptide immunogenicity was assessed using DeepCNN-Ineo, and tumor immune interaction, association with immune cells, correlation, and survival analysis were assessed using the TIMER web server. Based on somatic mutation analysis, we have identified the top 10 driver genes (TP53, TNN, CTNNB1, MUC16, ALB, PCLO, MUC4, ABCA13, APOB, and RYR2). From the superfamily of 20 HLA (Human leukocyte antigens) allele epitopes, we discovered 5653 neopeptides. Based on T cell receptor face hydrophobic analysis, these neopeptides were subjected to immunogenicity investigation. A mutation linked to tumor growth may have an impact on immune cells. According to this study's correlation and survival analysis, all driver genes may function as immune targets for liver cancer. These genes are recognized to be immune targets. In the future, immune checkpoint inhibitors may be developed to prolong patient survival times and prevent hepatocellular carcinoma (HCC) through immunotherapy.

COVID-19: comprehensive review on mutations and current vaccines.

Viral outbreaks had been a threat for the human race for a long time. Several epidemics and pandemics have been reported in the past with serious consequences on human health and subsequent social and economic aspects. According to WHO, viral infections continue to be a major health concern globally. Novel coronavirus, SARS-CoV-2 (Severe acute respiratory syndrome coronavirus-2) causes the most recent infectious pandemic disease, COVID-19 (Coronavirus disease-19). As of now, there were 249 million infections of COVID-19 worldwide with a high mortality of more than 5 million deaths reported; and the number of new additional cases is drastically increasing. Development of therapies to treat the infected cases and prophylactic agents including vaccines that are effective towards different variants are crucial to curtail the COVID-19 pandemic. Owing to the fact that there is a high mortality and morbidity rate along with the risk of virus causing further epidemic outbursts, development of additional effective therapeutic and preventive strategies are highly warranted. Prevention, early detection and treatment will reduce the spread of COVID-19 pandemic. The present review highlights the novel mutations and therapeutic updates associated with coronaviruses along with the clinical manifestations-diagnosis, clinical management and, prophylactic and therapeutic strategies of COVID-19 infection.

Hub gene identification and immune infiltration analysis in hepatocellular carcinoma: Computational approach.

In the case of hepatocellular carcinoma, there is a need to find novel immune biomarkers to predict cancer prognosis, which will help prolong patient survival. On the basis of these findings, we explored the role of the hub genes in hepatocellular carcinoma via computational analysis for future immunotherapy. To study this phenomenon, we selected three datasets downloaded from the GEO database (GSE25097, GSE76427 and GSE84402). The gene expression analysis platform (GEAP) online tool was used for the data analysis to identify the DEGs. Functional enrichment analysis was performed by GO and KEGG enrichment analysis. The genes associated with these genes were identified via Cytoscape software. Immune cell infiltration and correlation analysis were used to screen the hub genes. The results revealed that the PTTG1, NCAPG, RACGAP1, PBK, ASPM, AURKA, CDCA5, KIF20A, MELK and PRC1 genes were correlated with immune targets, and these hub gene biomarkers will aid in future cancer prognosis and immunotherapy targeting in hepatocellular carcinoma patients. Supplementary Information: The online version contains supplementary material available at 10.1007/s40203-024-00215-2.

Anti-atherogenic role of green tea (Camellia sinensis) in South Indian smokers.

ETHNOPHARMACOLOGICAL RELEVANCE: Green tea (Camellia sinensis) is a popular beverage consumed all over the world due to its health benefits. Many of these beneficial effects of green tea are attributed to polyphenols, particularly catechins. AIM OF THE STUDY: The present study focuses on underlying anti-platelet aggregation, anti-thrombotic, and anti-lipidemic molecular mechanisms of green tea in South Indian smokers. MATERIALS AND METHODS: We selected 120 South Indian male volunteers for this study to collect the blood and categorised them into four groups; control group individuals (Controls), smokers, healthy control individuals consuming green tea, and smokers consuming green tea. Smokers group subjects have been smoking an average 16-18 cigarettes per day for the last 7 years or more. The subjects (green tea consumed groups) consumed 100 mL of green tea each time, thrice a day for a one-year period. RESULTS: LC-MS analysis revealed the presence of multiple phytocompounds along with catechins in green tea extract. Increased plasma lipid peroxidation (LPO), protein carbonyls, cholesterol, triglycerides, and LDL-cholesterol with decreased HDL-cholesterol levels were observed in smokers compared to the control group and the consumption of green tea showed beneficial effect. Furthermore, docking studies revealed that natural compounds of green tea had high binding capacity with 3-hydroxy-3-methyl-glutaryl-CoA reductase (HMG-CoA) when compared to their positive controls, whereas (-) epigallocatechin-3-gallate (EGCG) and (-) epicatechin-gallate (ECG) had high binding capacity with sterol regulatory element-binding transcription factor 1 (SREBP1c). Further, our ex vivo studies showed that green tea extract (GTE) significantly inhibited platelet aggregation and increased thrombolytic activity in a dose dependent manner. CONCLUSION: In conclusion, in smokers, catechins synergistically lowered oxidative stress, platelet aggregation and modified the aberrant lipid profile. Furthermore, molecular docking studies supported green tea catechins' antihyperlipidemic efficacy through strong inhibitory activity on HMG-CoA reductase and SREBP1c. The mitigating effects of green tea on cardiovascular disease risk factors in smokers that have been reported can be attributed majorly to catechins or to their synergistic effects.

Targeting cytokine storm as the potential anti-viral therapy: Implications in regulating SARS-CoV-2 pathogenicity.

The latest global pandemic corona virus disease - 2019 (COVID-19) caused by the virus SARS-CoV-2 is still a matter of worrying concern both for the scientific communities and health care organizations. COVID-19 disease is proved to be a highly contagious disease transmitted through respiratory droplets and even close contact with affected individuals. COVID-19 disease is also understood to exhibit diverse symptoms of ranging severities i.e., from mild fatigue to death. Affected individuals' susceptibility to induce immunologic dysregulation phenomena termed 'cytokine storm' seems to be playing the damaging role of escalating the disease manifestation from mild to severe. Cytokine storm in patients with severe symptoms is understood to be characterized by enhanced serum levels of many cytokines including interleukin-1ß, interleukin-6, IP-10/CXCL10, TNF, interferon-γ, MIP-1α, MIP-1ß and VEGF. Since cytokine production in general is the most important antiviral defense response, understanding the COVID-19 associated cytokine storm in particular and differentiating it from the regular cytokine production response becomes crucial in developing an effective therapeutic strategy.This review focuses on the potential targeting of COVID-19 associated cytokine storm and its challenges.

Mutational analysis in international isolates and drug repurposing against SARS-CoV-2 spike protein: molecular docking and simulation approach.

The novel SARS-CoV-2 (severe acute respiratory syndrome coronavirus-2) is spreading, as the causative pathogen of coronavirus disease-19 (COVID-19). It has infected more than 1.65 billion people all over the world since it was discovered and reported 3.43 million deaths by mid of May 2021. SARS-CoV-2 enters the host cell by binding to viral surface glycoprotein (S protein) with human ACE2 (angiotensin-converting enzyme2). Spike protein (contains S1 and S2 sub-domains) molecular interaction with the host cells is considered as a major step in the viral entry and disease initiation and progression and this identifies spike protein as a promising therapeutic target against antiviral drugs. Currently, there are no efficient antiviral drugs for the prevention of COVID-19 infection. In this study, we have analyzed global 8719 spike protein sequences from patients infected with SAR-CoV-2. These SAR-CoV-2 genome sequences were downloaded from the GISAID database. By using an open reading frame (ORF) tool we have identified the spike protein sequence. With these, all spike protein amino acid sequences are subjected to multiple sequence alignment (MSA) with Wuhan strain spike protein sequence as a query sequence, and it shows all SAR-CoV strain spike proteins are 99.8% identical. In the mutational analysis, we found 639 mutations in the spike protein sequence of SARS-CoV-2 and identified/highlighted 20 common mutations L5F, T22I, T29I, H49Y, L54F, V90F, S98F, S221L, S254F, V367F, A520S, T572I, D614G, H655Y, P809S, A879S, D936Y, A1020S, A1078S, and H1101Y. Further, we have analyzed the crystal structure of the 2019-nCoV chimeric receptor-binding complex with ACE2 (PDB ID: 6VW1) as a major target protein. The spike receptor binding protein (RBD) used as target region for our studies with FDA-approved drugs for repurposing, and identified few anti-SARS-CoV2 potential drugs (Silmitasertib, AC-55541, Merimepodib, XL413, AZ3451) based on their docking score and binding mode calculations expected to strongly bind to motifs of ACE2 receptor and may show impart relief in COVID-19 patients.

Molecular Modeling, Docking, Dynamics and Simulation of Gefitinib and its Derivatives with EGFR in Non-small Cell Lung Cancer.

BACKGROUND: Gefitinib (lressa) is the most prescribed drug, highly effective to treat nonsmall cell lung cancer; primarily it was considered that targeted therapy is a kinase inhibitor. The nonsmall cell lung cancer is caused by mutation in the Epithelial Growth Factor Receptor (EGFR) gene. Iressa works by blocking the EGFR protein that helps the cancer cell growth. EGFR protein has lead to the development of anticancer therapeutics directed against EGFR inhibitor including Gefitinib for non-small cell lung cancer. METHODS: To explore the interaction between Gefitinib and its derivatives with crystal structure of EGFR to understand the better molecular insights interaction strategies. Molecular modeling of ligands (Gefitinib and its derivatives) was carried out by Avogadro software till atomic angle stable confirmation was obtained. The partial charges for the ligands were assigned as per standard protocol for molecular docking. All docking simulations were performed with AutoDockVina. Virtual screening was carried out based on binding energy and hydrogen bonding affinity. Molecular dynamics (MD) and Simulation EGFR were done using GROMACS 5.1.1 software to explore the interaction stability in a cell. RESULTS: The stable conformation for EGFR protein trajectories were captured at various time intervals 0-20ns. Few compounds screen based on high affinity as the inhibitor for EGFR may inhibit the cell cycle signaling in non-small cell lung cancer. CONCLUSION: These result suggested a computer-aided screening approach of Gefitinib derivatives with regard to their binding to EGFR for identifying novel drugs for the treatment of non-small cell lung cancer.