The Molecular Landscape of Lung Metastasis in Primary Head and Neck Squamous Cell Carcinomas

Background Lung metastasis in head and neck cancer (HNC) patients is a critical concern, often indicating an advanced disease stage and a poor prognosis. This study explores the molecular complexities of such metastases, identifying specific genes and pathways that may serve as valuable targets for diagnosis and treatment. The findings underscore the potential for significantly improved patient outcomes through targeted therapeutic strategies. Methodology In this research, we systematically collected raw gene expression data from head and neck squamous cell carcinoma (HNSCC) and lung squamous cell carcinoma (LSCC). By comparing tumorous and normal gene expression profiles from paired patient samples, we identified differentially expressed genes (DEGs). Network analysis helped visualize protein interactions and pinpoint crucial hub genes. Through validation and comparison across several datasets, we identified common DEGs. Additionally, we employed Kaplan-Meier analysis and log-rank testing to examine the relationship between gene expression patterns and patient survival. Result The study identified 145 overlapping DEGs in both HNSCC and LSCC, which are crucial for cancer progression and linked to lung metastasis, offering vital targets for personalized therapy by identifying key genes affecting disease development and patient survival. Pathway analyses linked these to lung metastasis, while protein-protein interaction network construction and hub gene identification highlighted genes crucial for development and patient survival, offering targets for personalized therapy. Conclusion Identifying key genes and pathways in lung metastasis from HNC, this study highlights potential targets for enhanced diagnosis and therapy. It underscores the crucial role of molecular insights in driving forward personalized treatment approaches and improving patient outcomes.

Systematic Evaluation of Aegle marmelos-Derived Compounds: Potential Therapeutic Agents Against Inflammation and Oxidative Stress

Aim This study aimed to evaluate the potential antioxidant and anti-inflammatory properties of Aegle marmelos active compounds through a multifaceted approach. The investigation encompasses molecular docking studies, computational pharmacokinetic predictions, and in vitro assessments, with a focus on understanding their physiochemical properties, pharmacokinetics, and molecular interactions. Materials and methods This study was conducted in the Research Department of Biochemistry, Saveetha Medical College & Hospital, Saveetha Institute of Medical and Technical Sciences (SIMATS), Tamilnadu, India. The study employed Soxhlet and methanol extraction techniques to obtain Aegle marmelos extracts, which were then subjected to antioxidant and anti-inflammatory assays. Antioxidant activity was assessed using the H2O2 assay, while anti-inflammatory potential was determined via the egg albumin denaturation assay. Molecular docking studies were conducted with human heme oxygenase 1 (HO-1) and human zanthine oxidoreductase (XO) proteins to elucidate potential therapeutic interactions. Furthermore, computational tools like SwissADME, pkCSM, and ADMETlab 2.0 were utilized to predict physiochemical and pharmacokinetic properties, providing insights into the compound absorption, distribution, metabolism, and excretion profiles. This integrated approach aimed to comprehensively evaluate the therapeutic potential of Aegle marmelos-derived compounds against inflammation and oxidative stress-related disorders, paving the way for future drug development endeavors. Results In the antioxidant assay, Aegle marmelos methanolic tuber extracts showed exceptional absorption of 87.4%, surpassing the reference standard. In the anti-inflammatory assay, the extracts displayed an absorption of approximately 79%, indicating significant anti-inflammatory potential. Auraptene, imperatorin, luvangetin, and psoralen exhibited favorable pharmacokinetic properties and adherence to the Lipinski rule of 5, suggesting promising drug development potential. In molecular docking, imperatorin demonstrated the highest binding affinity to HHO-1 and XO. Conclusion The study on Aegle marmelos highlights its potential as a therapeutic agent due to its potent antioxidant and anti-inflammatory properties. Phytochemical constituents, such as auraptene, imperatorin, luvangetin, and psoralen, show promising pharmacokinetic profiles, suggesting their suitability for drug development. Molecular docking analysis reveals imperatorin as the most effective binder to key enzymes, emphasizing its therapeutic potential against inflammation and oxidative stress-related disorders.

Proteogenomic landscape of human pancreatic ductal adenocarcinoma in an Asian population reveals tumor cell-enriched and immune-rich subtypes

We report a proteogenomic analysis of pancreatic ductal adenocarcinoma (PDAC). Mutation-phosphorylation correlations identified signaling pathways associated with somatic mutations in significantly mutated genes. Messenger RNA-protein abundance correlations revealed potential prognostic biomarkers correlated with patient survival. Integrated clustering of mRNA, protein and phosphorylation data identified six PDAC subtypes. Cellular pathways represented by mRNA and protein signatures, defining the subtypes and compositions of cell types in the subtypes, characterized them as classical progenitor (TS1), squamous (TS2-4), immunogenic progenitor (IS1) and exocrine-like (IS2) subtypes. Compared with the mRNA data, protein and phosphorylation data further classified the squamous subtypes into activated stroma-enriched (TS2), invasive (TS3) and invasive-proliferative (TS4) squamous subtypes. Orthotopic mouse PDAC models revealed a higher number of pro-tumorigenic immune cells in TS4, inhibiting T cell proliferation. Our proteogenomic analysis provides significantly mutated genes/biomarkers, cellular pathways and cell types as potential therapeutic targets to improve stratification of patients with PDAC.

An effective universal protocol for the extraction of fructooligosaccharide from the different agricultural byproducts

Alternative bio-refinery technologies are required to promote the commercial utilization of plant biomass components. The fructooligosaccharide (FOS) obtained after hydrolysis of the hemicellulose fractions was mainly applied in the pharmaceutical and food industries. Agricultural bi-product is a rich constituent in dietary fibres, which have prebiotic effects on the intestinal microbiota and the host. Herein we explored the impact of FOS on microbiota modulation and the gut homeostasis effect. High fructooligosaccharide recovery was obtained using alkaline extraction techniques. The enzymatic method produced fructooligosaccharides with minor contamination from fructan and glucan components, although it had a low yield. But combining the alkaline and enzymatic process provides a higher yield ratio and purity of fructooligosaccharides. The structure of the fructooligosaccharide was confirmed, according to FTIR, ¹³C NMR, ¹H NMR and 2D-NMR data. Our results could be applied to the development of efficient extraction of valuable products from agricultural materials using enzyme-mediated methods, which were found to be a cost-effective way to boost bio-refining value. Fructooligosaccharides with varying yields, purity, and structure can be obtained.

Identification of potential inhibitor targeting KRAS mutation in Papillary Thyroid Carcinoma through molecular docking and dynamic simulation analysis

Thyroid cancer is a predominant form of endocrine malignancy, which destabilizes the metabolic rate of the body. The rapid increase in the incidence rate of thyroid cancer in recent years has aroused great concern to be investigated and diagnosed at an early stage. This study aimed to analyze the pathogenic mutations in thyroid cancer to identify their potential inhibitors for therapeutic targets. RAS genes are the most common oncogenes, which encode proteins that play an essential role in cell signaling and have been frequently mutated in different cancer types. The mutation in these genes causes abnormal cell growth and fails to respond to death signals. In this study, we identified the most significant mutations in the RAS genes; thus, the highly pathogenic mutations were curated from thyroid cancer patients and analyzed for their pathogenicity effect. The physicochemical analysis predicted mutation in wild-type KRAS protein had adapted negative charge on single base substitution of G12D that may easily cause loss of interactions and result in critical differences in the structure and function of the protein. Furthermore, the native KRAS protein was mutated and screened against a library of druggable compounds from the ZINC drug repository. The molecular docking analysis revealed that G12D mutant KRAS protein form best-docked complex with Naldemedine with the highest binding affinity. The dynamic simulation results further justified the stability of Naldemedine as a potential inhibitor with high efficiency in MMPBSA value of -45.4867 kcal/mol of being treated as a potential drug for papillary thyroid carcinoma. Further in vivo and in vitro validation of Naldemedine and its efficiency as a drug for the targeted pathogenic KRAS mutation is required.

Biomineralization associated alkaline phosphatase as a potential marker of bone metastasis in the patients with invasive breast cancer

Breast Cancer is the most predominant form of cancer among women worldwide. It has been rigorously studied for biomarker identifications and therapeutic targets. However, various potential genes and their clinical relevance to breast cancer remain unexplored. The heterogeneity of breast cancer is one of the major challenges in early detection. Several studies have reported the significant role of alkaline phosphate (ALP) in the regulation of tumor growth and overall free survival in the pathogenesis of different cancer, including breast cancer which may offer unique therapeutic targets. Therefore, these findings demand a comprehensive study for the biogenesis of ALP genes. This study aims to expression profiling of alkaline phosphate genes in breast cancer and to identify the key pathways and molecular mechanisms underlying breast cancer proliferation and progression. In this study, the transcriptome profiling of invasive breast carcinoma samples was performed and analyzed. We identified that all the ALP genes were downregulated in both Invasive Lobular and Invasive Ductal Carcinoma patients. To understand the underlying molecular mechanism and the clinical significance for these genes in breast cancer, the expression values of genes were measured in adjacent normal and tumor tissues of patients followed by network analysis and functional enrichment analysis. The overall analysis revealed the highly aberrant expression of ALPL gene among all four ALP genes. We identified the functional significance of RUNX2 and WNT3A in deregulating ALPL. Therefore, our findings suggests that downregulation of ALPL could be a potential marker gene for invasive breast carcinoma progression towards bone metastasis.

A review on the application of bioinformatics tools in food microbiome studies

There is currently a transformed interest toward understanding the impact of fermentation on functional food development due to growing consumer interest on modified health benefits of sustainable foods. In this review, we attempt to summarize recent findings regarding the impact of Next-generation sequencing and other bioinformatics methods in the food microbiome and use prediction software to understand the critical role of microbes in producing fermented foods. Traditionally, fermentation methods and starter culture development were considered conventional methods needing optimization to eliminate errors in technique and were influenced by technical knowledge of fermentation. Recent advances in high-output omics innovations permit the implementation of additional logical tactics for developing fermentation methods. Further, the review describes the multiple functions of the predictions based on docking studies and the correlation of genomic and metabolomic analysis to develop trends to understand the potential food microbiome interactions and associated products to become a part of a healthy diet.

In Vitro and In Silico Screening and Characterization of Antimicrobial Napin Bioactive Protein in Brassica juncea and Moringa oleifera

The study aimed to investigate the antibacterial activity of Mustard (Brassica juncea) and Moringa (Moringa oleifera) leaf extracts and coagulant protein for their potential application in water treatment. Bacterial cell aggregation and growth kinetics studies were employed for thirteen bacterial strains with different concentrations of leaf extracts and coagulant protein. Moringa oleifera leaf extract (MOS) and coagulant protein showed cell aggregation against ten bacterial strains, whereas leaf extract alone showed growth inhibition of five bacterial strains for up to 6 h and five bacterial strains for up to 3 h. Brassica juncea leaf extract (BJS) showed growth inhibition for up to 6 h, and three bacterial strains showed inhibition for up to 3 h. The highest inhibition concentration with 2.5 mg/mL was 19 mm, and furthermore, the minimum inhibitory concentration (MIC) (0.5 mg/mL) and MBC (1.5 mg/mL) were determined to have a higher antibacterial effect for <3 KDa peptides. Based on LCMS analysis, napin was identified in both MOS and BJS; furthermore, the mode of action of napin peptide was determined on lipoprotein X complex (LpxC) and four-chained structured binding protein of bacterial type II topoisomerase (4PLB). The docking analysis has exhibited moderate to potent inhibition with a range of dock score -912.9 Kcal/mol. Thus, it possesses antibacterial-coagulant potential bioactive peptides present in the Moringa oleifera purified protein (MOP) and Brassica juncea purified protein (BJP) that could act as an effective antimicrobial agent to replace currently available antibiotics. The result implies that MOP and Brassica juncea purified coagulant (BJP) proteins may perform a wide degree of antibacterial functions against different pathogens.

Identification of marker genes in Alzheimer's disease using a machine-learning model

Alzheimer's Disease (AD) is one of the most common causes of dementia, mostly affecting the elderly population. Currently, there is no proper diagnostic tool or method available for the detection of AD. The present study used two distinct data sets of AD genes, which could be potential biomarkers in the diagnosis. The differentially expressed genes (DEGs) curated from both datasets were used for machine learning classification, tissue expression annotation and co-expression analysis. Further, CNPY3, GPR84, HIST1H2AB, HIST1H2AE, IFNAR1, LMO3, MYO18A, N4BP2L1, PML, SLC4A4, ST8SIA4, TLE1 and N4BP2L1 were identified as highly significant DEGs and exhibited co-expression with other query genes. Moreover, a tissue expression study found that these genes are also expressed in the brain tissue. In addition to the earlier studies for marker gene identification, we have considered a different set of machine learning classifiers to improve the accuracy rate from the analysis. Amongst all the six classification algorithms, J48 emerged as the best classifier, which could be used for differentiating healthy and diseased samples. SMO/SVM and Logit Boost further followed J48 to achieve the classification accuracy.

An effective datasets describing antimicrobial peptide produced from Pediococcus acidilactici - purification and mode of action determined by molecular docking

Most of the probiotics Bacterial cells, express native antibacterial genes, resulting in the production of, antimicrobial peptides, which have various applications in biotechnology and drug development. But the identification of antibacterial peptide, structural characterization of antimicrobial peptide and prediction on mode of action. Regardless of the significance of protein manufacturing, three individual factors are required for the production method: gene expression, stabilization and specific peptide purification. Our protocol describes a straightforward technique of detecting and characterizing particular extracellular peptides and enhancing the antimicrobial peptide expression we optimized using low molecular weight peptides. This protocol can be used to improve peptide detection and expression. The following are the benefits of this method, (DOI – https://doi.org/10.1016/j.ijbiomac.2019.10.196 [1]).

The data briefly describe a simple method in detection identification, characterization of antimicrobial extracellular peptide, predicating the mode of action of peptide in targeting pathogens (In-silico method), brief method on profiling of antimicrobial peptide and its mode of action [1]. Further the protocol can be used to enhance the specific peptide expressions, detection of peptides. The advantages of this technique are presented below:•

Characterization protocol of specific antimicrobial peptide

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The folded antimicrobial peptide expression were less expressed or non-expressed peptides.

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Besides being low cost, less time-consuming, easy to handle, universal and fast to execute, the suggested technique can be used for multiple proteins expressed in probiotics (Lactobacillus species) expression system.

Towards the early detection of ductal carcinoma (a common type of breast cancer) using biomarkers linked to the PPAR(γ) signaling pathway

Breast cancer is a leading cause of morbidity and mortality among women comprising about 12% females worldwide. The underlying alteration in the gene expression, molecular mechanism and metabolic pathways responsible for incidence and progression of breast tumorigenesis are yet not completely understood. In the present study, potential biomarker genes involved in the early progression for early diagnosis of breast cancer has been detailed. Regulation and Gene profiling of Ductal Carcinoma In-situ (DCIS), Invasive Ductal Carcinoma (IDC) and healthy samples have been analyzed to follow their expression pattern employing normalization, statistical calculation, DEGs annotation and Protein-Protein Interaction (PPI) network. We have performed a comparative study on differentially expressed genes among Healthy vs DCIS, Healthy vsIDC and DCIS vs IDC. We found MCM102 and SLC12A8as consistently over-expressed and LEP, SORBS1, SFRP1, PLIN1, FABP4, RBP4, CD300LG, ID4, CRYAB, ECRG4, G0S2, FMO2, ADAMTS5, CAV1, CAV2, ABCA8, MAMDC2, IGFBP6, CLDN11, TGFBR3as under-expressed genes in all the 3 conditions categorized for pre-invasive and invasive ductal breast carcinoma. These genes were further studied for the active pathways where PPAR(γ) signaling pathway was found to be significantly involved. The gene expression profile database can be a potential tool in the early diagnosis of breast cancer.

Unveiling the potentials of bacteriocin (Pediocin L50) from Pediococcus acidilactici with antagonist spectrum in a Caenorhabditis elegans model

Human-milk-based probiotics play a major role in the early colonization and protection of infants against gastrointestinal infection. We investigated potential probiotics in human milk. Among 41 Lactic acid bacteria (LAB) strains, four strains showed high antimicrobial activity against Escherichia coli 0157:H7, Listeria monocytogenes ATCC 15313, Bacillus cereus ATCC 14576, Staphylococcus aureus ATCC 19095, and Helicobacter pylori. The selected LAB strains were tested in simulated gastrointestinal conditions for their survival. Four LAB strains showed high resistance to pepsin (82%-99%), bile with pancreatine stability (96%-100%), and low pH (80%-94%). They showed moderate cell surface hydrophobicity (22%-46%), auto-aggregation abilities (12%-34%), and 70%-80% co-aggregation abilities against L. monocytogenes ATCC 15313, S. aureus ATCC 19095, B. cereus ATCC 14576, and E. coli 0157:H7. All four selected isolates were resistant to gentamicin, imipenem, novobiocin, tetracycline, clindamycin, meropenem, ampicillin, and penicillin. The results show that Pediococcus acidilatici is likely an efficient probiotic strain to produce < 3 Kda pediocin-based antimicrobial peptides, confirmed by applying amino acid sequences), using liquid chromatography mass spectrometry and HPLC with the corresponding sequences from class 2 bacteriocin, and based on the molecular docking, the mode of action of pediocin was determined on LipoX complex, further the ¹³C nuclear magnetic resonance structural analysis, which confirmed the antimicrobial peptide as pediocin.

Knockdown of CD-74 in the Proliferative and Apoptotic Activity of Breast Cancer Cells

BACKGROUND

The cluster of differentiation (CD) 74 is known for its immunological functions and its elevated level was reported in various cancer cells.

AIM

The aim of the present study was to investigate the expression and potential roles of CD74 in the proliferative and apoptotic activity of breast cancer.

METHODS

Expression of CD74, macrophage migration inhibitory factor (MIF) and CD44 was assayed in CAMA-1 and MDA-MB-231 cell lines using flow cytometry. CD74 was knocked down using CD74 siRNA-transfection in CAMA-1, and MDA-MB-231 cells and proliferation and apoptosis were determined in the transfected breast cancer cells.

RESULTS

The data showed that CD74, MIF and CD44 were expressed in breast cancer cell lines and were associated with cell proliferation and apoptosis. Correlation analysis revealed that CD74 was positively correlated and colocalised with MIF on the cell-surface of CAMA-1 and MDA-MB-231. The knockdown of CD74 significantly reduced CAMA-1 and MDA-MB-231 cell proliferation and increased the level of apoptotic cells.

CONCLUSION

We concluded that the interactions of CD74 with MIF and CD74 with CD44 could be a potential tumour marker for breast cancer cells. Moreover, the level of co-expression of MIF and CD74 or CD44 could be a surrogate marker for the efficacy of anti-angiogenic drugs, particularly in breast cancer tumours. In short, the study revealed the potential roles of CD74 in the proliferation and apoptosis of breast cancer which may serve as a potential therapeutic target for breast cancer.

Measurements of heterotypic associations between cluster of differentiation CD74 and CD44 in human breast cancer-derived cells

Interactions between pairs of membrane-bound receptors can enhance tumour development with implications for targeted therapies for cancer. Here we demonstrate clear heterotypic interaction between CD74 and CD44, which might act in synergy and hence contribute to breast cancer progression. CD74, a type II transmembrane glycoprotein, is a chaperone for MHC class II biosynthesis and a receptor for the MIF. CD44 is the receptor for hyaluronic acid and is a Type I transmembrane protein. Interactions between CD74, MIF and the intra-cytoplasmic domain of CD44 result in activation of ERK1/2 pathway, leading to increased cell proliferation and decreased apoptosis. The level of CD44 in the breast tumor cell lines CAMA-1, MDA-MB-231, MDA-MB-435 and the immortalized normal luminal cell line 226LDM was higher than that of CD74. It was also observed that CD74 and CD44 exhibit significant variation in expression levels across the cells. CD74 and CD44 were observed to accumulate in cytoplasmic compartments, suggesting they associate with each other to facilitate tumour growth and metastasis. Use of a novel and validated colocalisation and image processing approach, coupled with co-immunoprecipitation, confirmed that CD74 and CD44 physically interact, suggesting a possible role in breast tumour growth. This is the first time that CD74 and CD44 colocalization has been quantified in breast cancer cells using a non-invasive and validated bioimaging procedure. Measuring the co-expression levels of CD74 and CD44 could potentially be used as a ‘biomarker signature’ to monitor different stages of breast cancer.

Influence of PCOS in Obese vs. Non-Obese women from Mesenchymal Progenitors Stem Cells and Other Endometrial Cells: An in silico biomarker discovery

Polycystic ovary syndrome (PCOS) is endocrine system disease which affect women ages 18 to 44 where the women’s hormones are imbalance. Recently it has been reported to occur in early age. Alteration of normal gene expression in PCOS has shown negative effects on long-term health issues. PCOS has been the responsible factor for the infertility in women of reproductive age group. Early diagnosis and treatment can improve the women’s health suffering from PCOS. Earlier Studies shows correlation of PCOS upon insulin resistance with significant outcome, Current study shows the linkage between PCOS with obesity and non-obese patients. Gene expression datasets has been downloaded from GEO (control and PCOS affected patients). Normalization of the datasets were performed using R based on RMA and differentially expressed gene (DEG) were selected on the basis of p-value 0.05 followed by functional annotation of selected gene using Enrich R and DAVID. The DEGs were significantly related to PCOS with obesity and other risk factors involved in disease. The Gene Enrichment Analysis suggests alteration of genes and associated pathway in case of obesity. Current study provides a productive groundwork for specific biomarkers identification for the accurate diagnosis and efficient target for the treatment of PCOS.

Multiplexed Post-Experimental Monoisotopic Mass Refinement (mPE-MMR) to Increase Sensitivity and Accuracy in Peptide Identifications from Tandem Mass Spectra of Cofragmentation

Mass spectrometry (MS)-based proteomics, which uses high-resolution hybrid mass spectrometers such as the quadrupole-orbitrap mass spectrometer, can yield tens of thousands of tandem mass (MS/MS) spectra of high resolution during a routine bottom-up experiment. Despite being a fundamental and key step in MS-based proteomics, the accurate determination and assignment of precursor monoisotopic masses to the MS/MS spectra remains difficult. The difficulties stem from imperfect isotopic envelopes of precursor ions, inaccurate charge states for precursor ions, and cofragmentation. We describe a composite method of utilizing MS data to assign accurate monoisotopic masses to MS/MS spectra, including those subject to cofragmentation. The method, "multiplexed post-experiment monoisotopic mass refinement" (mPE-MMR), consists of the following: multiplexing of precursor masses to assign multiple monoisotopic masses of cofragmented peptides to the corresponding multiplexed MS/MS spectra, multiplexing of charge states to assign correct charges to the precursor ions of MS/MS spectra with no charge information, and mass correction for inaccurate monoisotopic peak picking. When combined with MS-GF+, a database search algorithm based on fragment mass difference, mPE-MMR effectively increases both sensitivity and accuracy in peptide identification from complex high-throughput proteomics data compared to conventional methods.

An in silico analytical study of lung cancer and smokers datasets from gene expression omnibus (GEO) for prediction of differentially expressed genes

Smoking is the leading cause of lung cancer development and several genes have been identified as potential biomarker for lungs cancer. Contributing to the present scientific knowledge of biomarkers for lung cancer two different data sets, i.e. GDS3257 and GDS3054 were downloaded from NCBI׳s GEO database and normalized by RMA and GRMA packages (Bioconductor). Diffrentially expressed genes were extracted by using and were R (3.1.2); DAVID online tool was used for gene annotation and GENE MANIA tool was used for construction of gene regulatory network. Nine smoking independent gene were found whereas average expressions of those genes were almost similar in both the datasets. Five genes among them were found to be associated with cancer subtypes. Thirty smoking specific genes were identified; among those genes eight were associated with cancer sub types. GPR110, IL1RN and HSP90AA1 were found directly associated with lung cancer. SEMA6A differentially expresses in only non-smoking lung cancer samples. FLG is differentially expressed smoking specific gene and is related to onset of various cancer subtypes. Functional annotation and network analysis revealed that FLG participates in various epidermal tissue developmental processes and is co-expressed with other genes. Lung tissues are epidermal tissues and thus it suggests that alteration in FLG may cause lung cancer. We conclude that smoking alters expression of several genes and associated biological pathways during development of lung cancers.