Comprehensive analysis of stearoyl-coenzyme A desaturase in prostate adenocarcinoma: insights into gene expression, immune microenvironment and tumor progression.

Prostate adenocarcinoma (PRAD) is a prevalent global malignancy which depends more on lipid metabolism for tumor progression compared to other cancer types. Although Stearoyl-coenzyme A desaturase (SCD) is documented to regulate lipid metabolism in multiple cancers, landscape analysis of its implications in PRAD are still missing at present. Here, we conducted an analysis of diverse cancer datasets revealing elevated SCD expression in the PRAD cohort at both mRNA and protein levels. Interestingly, the elevated expression was associated with SCD promoter hypermethylation and genetic alterations, notably the L134V mutation. Integration of comprehensive tumor immunological and genomic data revealed a robust positive correlation between SCD expression levels and the abundance of CD8+ T cells and macrophages. Further analyses identified significant associations between SCD expression and various immune markers in tumor microenvironment. Single-cell transcriptomic profiling unveiled differential SCD expression patterns across distinct cell types within the prostate tumor microenvironment. The Gene Ontology and Kyoto Encyclopedia of Genes and Genome analyses showed that SCD enriched pathways were primarily related to lipid biosynthesis, cholesterol biosynthesis, endoplasmic reticulum membrane functions, and various metabolic pathways. Gene Set Enrichment Analysis highlighted the involvement of elevated SCD expression in crucial cellular processes, including the cell cycle and biosynthesis of cofactors pathways. In functional studies, SCD overexpression promoted the proliferation, metastasis and invasion of prostate cancer cells, whereas downregulation inhibits these processes. This study provides comprehensive insights into the multifaceted roles of SCD in PRAD pathogenesis, underscoring its potential as both a therapeutic target and prognostic biomarker.

Modeling of enzymatic transesterification for omega-3 fatty acids enrichment in fish oil.

Mathematical models of transesterification commonly assume that oil is a mixture of triacylglycerols, where each component has only one type of acid attached. This article aims to show how a different assumption on acid distribution affects the results of acylglycerols fraction composition. Experiments of fish oil ethanolysis have been performed at different enzyme loadings and ethanol concentrations, leading to enrichments from 35 % to 52 % of ω3 mass fraction in acylglycerols, by losing 12.1 % of ω3 as ethyl esters. A kinetic model is developed assuming both all acids of the same type on each acylglycerol and all acids randomly distributed on the available positions. The two different assumptions showed strong discrepancies on the acylglycerols fraction compositions predictions, demonstrating how the initial fatty acids distribution is important when an accurate description of the acylglycerols fraction is desired.

CIEC: Cross-tissue Immune Cell Type Enrichment and Expression Map Visualization for Cancer.

Single-cell transcriptome sequencing technology has been applied to decode the cell types and functional states of immune cells, revealing their tissue-specific gene expression patterns and functions in cancer immunity. Comprehensive assessments of immune cells within and across tissues will provide us with a deeper understanding of the tumor immune system in general. Here, we present Cross-tissue Immune cell type or state Enrichment analysis of gene lists for Cancer (CIEC), the first web-based application that integrates database and enrichment analysis to estimate the cross-tissue immune cell type or state. CIEC version 1.0 consists of 480 samples covering primary tumor, adjacent normal tissue, lymph node, metastasis tissue, and peripheral blood from 323 cancer patients. By applying integrative analysis, we constructed an immune cell-type/state map for each context and adopted our previously developed Kyoto Encyclopedia of Genes and Genomes (KEGG) Orthology Based Annotation System (KOBAS) algorithm to estimate the enrichment for context-specific immune cell type/state. In addition, CIEC also provides an easy-to-use online interface for users to comprehensively analyze the immune cell characteristics mapped across multiple tissues, including expression map, correlation, similar genes detection, signature score, and expression comparison. We believe that CIEC will be a valuable resource for exploring the intrinsic characteristics of immune cells in cancer patients and for potentially guiding novel cancer-immune biomarker development and immunotherapy strategies. CIEC is freely accessible at http://ciec.gene.ac/.

An explore method for quick screening biomarkers based on effective enrichment capacity and data mining.

Protein glycosylation acts as a crucial role in regulating protein function and maintaining cellular homeostasis. Efficient peptide enrichment can be utilized to effectively solve the inherent challenges of protein glycosylation analysis to search unknown cancer biomarkers. In this research, a low dimensional porous hydrophilic nanosheets with a multi-level porous structure (Co-MOF-SiO2@HA) was synthetized via an easy one-pot method for the efficient enrichment of the N-glycopeptides in the digests of complex biosamples. The synthetized nanosheets Co-MOF-SiO2@HA demonstrated excellent enriching performances including a high enrichment capacity (300 mg g-1 calculated), a spectacular selectivity (IgG digests and BSA digests at the molar ratio of 1/1200), and an excellent spatial confinement ability (IgG digests, IgG and BSA at the molar ratio of 1/1000/1000). As an explore result, after the enrichment of human colorectal cancer tissue and human healthy tissue by the nanosheets, several proteins related to cancers and one protein directly related to well-known human colorectal cancer were identified by detecting the corresponding glycopeptides. It presented the potential value of the feasibility of this analysis mode by nanosheets Co-MOF-SiO2@HA in proteomic analysis.

Adaptive enrichment trial designs using joint modelling of longitudinal and time-to-event data.

Adaptive enrichment allows for pre-defined patient subgroups of interest to be investigated throughout the course of a clinical trial. These designs have gained attention in recent years because of their potential to shorten the trial's duration and identify effective therapies tailored to specific patient groups. We describe enrichment trials which consider long-term time-to-event outcomes but also incorporate additional short-term information from routinely collected longitudinal biomarkers. These methods are suitable for use in the setting where the trajectory of the biomarker may differ between subgroups and it is believed that the long-term endpoint is influenced by treatment, subgroup and biomarker. Methods are most promising when the majority of patients have biomarker measurements for at least two time points. We implement joint modelling of longitudinal and time-to-event data to define subgroup selection and stopping criteria and we show that the familywise error rate is protected in the strong sense. To assess the results, we perform a simulation study and find that, compared to the study where longitudinal biomarker observations are ignored, incorporating biomarker information leads to increases in power and the (sub)population which truly benefits from the experimental treatment being enriched with higher probability at the interim analysis. The investigations are motivated by a trial for the treatment of metastatic breast cancer and the parameter values for the simulation study are informed using real-world data where repeated circulating tumour DNA measurements and HER2 statuses are available for each patient and are used as our longitudinal data and subgroup identifiers, respectively.

Predicting gene signature in breast cancer patients with multiple machine learning models.

AIMS: The aim of this study was to predict gene signatures in breast cancer patients using multiple machine learning models. METHODS: In this study, we first collated and merged the datasets GSE54002 and GSE22820, obtaining a gene expression matrix comprising 16,820 genes (including 593 breast cancer (BC) samples and 26 normal control (NC) samples). Subsequently, we performed enrichment analyses using Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Disease Ontology (DO). RESULTS: We identified 177 differentially expressed genes (DEGs), including 40 up-regulated and 137 down-regulated genes, through differential expression analysis. The GO enrichment results indicated that these genes are primarily involved in extracellular matrix organization, positive regulation of nervous system development, collagen-containing extracellular matrix, heparin binding, glycosaminoglycan binding, and Wnt protein binding, among others. KEGG enrichment analysis revealed that the DEGs were primarily associated with pathways such as focal adhesion, the PI3K-Akt signaling pathway, and human papillomavirus infection. DO enrichment analysis showed that the DEGs play a significant role in regulating diseases such as intestinal disorders, nephritis, and dermatitis. Further, through LASSO regression analysis and SVM-RFE algorithm analysis, we identified 9 key feature DEGs (CF-DEGs): ANGPTL7, TSHZ2, SDPR, CLCA4, PAMR1, MME, CXCL2, ADAMTS5, and KIT. Additionally, ROC curve analysis demonstrated that these CF-DEGs serve as a reliable diagnostic index. Finally, using the CIBERSORT algorithm, we analyzed the infiltration of immune cells and the associations between CF-DEGs and immune cell infiltration across all samples. CONCLUSIONS: Our findings provide new insights into the molecular functions and metabolic pathways involved in breast cancer, potentially aiding in the discovery of new diagnostic and immunotherapeutic biomarkers.

Unraveling the genetic and singaling landscapes of pediatric cancer.

Pediatric cancer (PAEC) arises from gene mutations and their disrupted pathways, often driven by genetic instability affecting cell signaling. These pathways can help identify cancer triggers. Genomic studies have examined PAEC gene etiologies and disorders, but further analysis is needed to understand tumor progression mechanisms. We systematically analyzed PAEC datasets from cBioPortal, encompassing thirteen studies with 6568 samples. We identified 827 PAEC genes with mutation frequencies over fifteen across four tiers (I-IV). Tier I (mutation frequency ≥1 %) includes 40 genes, while Tier II(0.90-0.70 %), Tier III(0.60-0.50 %), and Tier IV(0.40-0.10 %) comprise 126, 336, and 325 genes, respectively. Key Tier I genes include TP53(5 %), NRAS(2.2 %), KRAS(1.8 %), CTNNB1(1.4 %), ATM(1.3 %), CREBBP(1.2 %), JAK2 (1.1 %), PIK3CA(1 %), PTEN(1 %), BRAF(0.9 %), EGFR(0.9 %), PIK3R1(0.8 %), and PTPN11(0.8 %). These genes participate in various signaling pathways (PI3K/AKT/mTOR, RAS/RAF/MAPK, JAK/STAT, and WNT/ß-catenin), which are interconnected. We compared several PAEC panels with Tier I genes, and we found that the most shared across PAEC panels were TP53 (8), PTEN (7), and ATM (4). We further examined roles of TP53 in normal cells versus PEAC tumors using digital cellular and pathological imaging data supported by Human Protein Atlas. TP53 is expressed in cytosol, nucleosol, and vesicles and during cell-cycle TP53 protein in key regulator and it is present during all major cell-cycle events. Balancing of TP53WT and TP53MUT is the hallmark of the TP53 pathophysiology with severe functional implications. Notably, genes linked to insulin metabolism disorders may be PAEC risk factors, suggesting metabolic pathways as key research targets. This study highlights the therapeutic, prognostic, and diagnostic significance of these genes and pathways, emphasizing the need for ongoing PAEC research.

Investigation of impact of siderophore and process variables on production of iron enriched Saccharomyces boulardii by Plackett-Burman design.

The primary cause of anemia worldwide is due to poor diet and iron deficiency. Iron (Fe) enriched yeast can be the most effective way to manage anemia because of the capability for biotransformation of mineral to organic and bioavailable iron. To overcome the low richness of yeast, the use of siderophore as cellular iron carriers is a new approach. In this research, for the first time the potential of siderophore in increasing the Fe enrichment of Saccharomyces boulardii (S. boulardii), which is important because of its probiotic properties and resistance to different stresses, has been investigated to produce of potential iron supplements. For this purpose, siderophore was produced by Pseudomonas aeruginosa (P. aeruginosa). Siderophore impact, along with ten other independent process variables, has been studied on the efficiency of iron biotransformation by the Plackett-Burman design (PBD). The results showed that the highest biotransformation yield was 17.77 mg Fe/g dry cell weight (DCW) in the highest biomass weight of 9 g/l. Iron concentration is the most important variable, with contributions of 46% and 70.79% for biomass weight and biotransformation, respectively, followed by fermentation time, agitation speed, and KH2PO4 concentration. But increasing the level of siderophore and zinc led to a significant negative effect. siderophore inefficiency may be attributed to the absence of membrane receptors for pyoverdine (Pvd) and pyochelin (Pch) siderophores. Also, the steric hindrance of the cell wall mannan, the stickiness and sediment ability of the yeast, can create limitations in the absorption of elements. Such yeast can be used as a potential source of iron even for vegetarians and vegans in the form of medicinal and fortified food products to improve the treatment of anemia. It is recommended that further research be focused on increasing the iron enrichment of yeast by overcoming the structural barrier of the cell wall, investigating factors affecting membrane permeability and iron transport potential of other types of siderophores.

Impact of Acute or Chronic Acidosis and Hypoxia on Gene Expression Patterns in Tumour Cells: Potential Functional Implications.

Tumours often exhibit pronounced hypoxia and hereby extracellular acidosis due to intensified glycolysis. Since metabolic parameters can modulate gene expression, the aim of the study was to analyse changes in gene expression patterns induced by acute (24 h) acidosis or hypoxia and also in tumour cells adapted to long-term acidosis (5 weeks). Three tumour cell lines (AT1 prostate carcinoma, MCF-7, and MDA-MB-231 breast carcinoma) were exposed to acidosis (pH 6.6) or hypoxia (pO2 1.5 mmHg) for 24 h. For long-term acidosis, AT1 tumour cells were continuously cultured at pH 6.6 for 5 weeks. Gene expression was examined by total RNA-sequencing and the functional significance was assessed by gene set enrichment analysis using the Gene Ontology database. Under short-term acidosis (24 h), AT1 and MCF-7 cells showed comparable changes. 714 genes were acidosis-dependently regulated in AT1 cells (275 up, 439 down), and 221 genes in MCF-7 cells (95 up, 126 down). MDA-MB-231 cells almost did not respond to low pH (13 regulated genes). Hypoxia affected MCF-7 cells the most (1498 regulated genes), whereas fewer genes were regulated in AT1 and MDA-MB-231 cells. Concerning the function of the regulated genes by short-term acidosis, RNA processing, cell cycle regulation, DNA synthesis, and mitochondrial function were negatively affected. Chronic acidosis showed a different picture. In AT1 cells, 1160 genes were differentially expressed (638 up, 522 down) when cells exposed to low pH for 5 weeks. The putatively acidosis-induced changes in functions included tissue structural development, RNA processing, and mitochondrial activity. This study shows that both acute and chronic acidosis of tumour cells lead to altered gene expression and thus affect cell function. Long-term acidosis leads to fundamentally different changes, indicating an adaptation process of the tumour cells.

SHH Signaling as a Key Player in Endometrial Cancer: Unveiling the Correlation with Good Prognosis, Low Proliferation, and Anti-Tumor Immune Milieu.

Endometrial Cancer (EC) is one of the most common gynecological malignancies. Despite its prevalence, molecular pathways, such as the Sonic Hedgehog (SHH) pathway, have not been extensively studied in the context of EC. This study aims to explore the clinical implications of SHH expression in EC, potentially uncovering new insights into the disease's pathogenesis and offering valuable insights for therapeutic strategies in EC. We utilized data from The Cancer Genome Atlas (TCGA) to divide the dataset into 'High SHH' and 'Low SHH' groups based on a gene signature score derived from SHH pathway-related genes. We explored the clinical and tumor characteristics of these groups, focusing on key cancer hallmarks, including stemness, proliferation, cytolytic activity, tumor micro-environment, and genomic instability. 'High SHH' tumors emerged as a distinct category with favorable clinical and molecular features. These tumors exhibited lower proliferation rates, reduced angiogenesis, and diminished genomic instability, indicating a controlled and less aggressive tumor growth pattern. Moreover, 'High SHH' tumors displayed lower stemness, highlighting a less invasive phenotype. The immune micro-environment in 'High SHH' tumors was enriched with immune cell types, such as macrophage M0, monocytes, B cells, CD8 T cells, CD4 T cells, follicular helper T cells, and natural killer cells. This immune enrichment, coupled with higher cytolytic activity, suggested an improved anti-tumor immune response. Our study sheds light on the clinical significance of Sonic signaling in EC. 'High SHH' tumors exhibit a unique molecular and clinical profile associated with favorable cancer hallmarks, lower grades, and better survival. These findings underscore the potential utility of SHH expression as a robust prognostic biomarker, offering valuable insights for tailored therapeutic strategies in EC. Understanding the SHH pathway's role in EC contributes to our growing knowledge of this cancer and may pave the way for more effective treatment strategies in the future.

Key genes and immune pathways in T-cell mediated rejection post-liver transplantation identified via integrated RNA-seq and machine learning.

Liver transplantation is the definitive treatment for end-stage liver disease, yet T-cell mediated rejection (TCMR) remains a major challenge. This study aims to identify key genes associated with TCMR and their potential biological processes and mechanisms. The GSE145780 dataset was subjected to differential expression analysis, weighted gene co-expression network analysis (WGCNA), and machine learning algorithms to pinpoint key genes associated with TCMR. Gene Set Enrichment Analysis (GSEA), immune infiltration analysis, and regulatory networks were constructed to ascertain the biological relevance of these genes. Expression validation was performed using single-cell RNA-seq (scRNA-seq) data and liver biopsy tissues from patients. We identified 5 key genes (ITGB2, FCER1G, IL-18, GBP1, and CD53) that are associated with immunological functions, such as chemotactic activity, antigen processing, and T cell differentiation. GSEA highlighted enrichment in chemokine signaling and antigen presentation pathways. A lncRNA-miRNA-mRNA network was delineated, and drug target prediction yielded 26 potential drugs. Evaluation of expression levels in non-rejection (NR) and TCMR groups exhibited significant disparities in T cells and myeloid cells. Tissue analyses from patients corroborated the upregulation of GBP1, IL-18, CD53, and FCER1G in TCMR cases. Through comprehensive analysis, this research has identified 4 genes intimately connected with TCMR following liver transplantation, shedding light on the underlying immune activation pathways and suggesting putative targets for therapeutic intervention.

Enrichment and separation technology for evaluation of circulating tumor cells.

Circulating tumor cells (CTCs) are tumor cells that exist in human peripheral blood, which could spread to other tissues or organs via the blood circulation system and develop into metastatic foci, leading to tumor recurrence or metastasis in postoperative patients and thereby increasing the mortality of malignant tumor patients. Evaluation of CTC levels can be used for tumor metastasis prediction, prognosis evaluation, drug exploitation, individualized treatment, liquid biopsy, etc., which exhibit outstanding clinical application prospects. In recent years, accurately capturing and analyzing CTCs has become a research hotspot in the early diagnosis and precise treatment of tumors. This review summarized various enrichment and isolation technologies for evaluating CTCs based on the design principle and discussed the challenges and perspectives in this field.

Ecological characteristics of tall fescue and spatially organized communities: Their contribution to mitigating cadmium damage.

The threat of cadmium (Cd) stress to agricultural soil environments, as well as their productivity attracting growing global interest. Tall fescue (Festuca arundinacea Schreb.) is a strong candidate for the remediation of heavy metals in soil. However, the joint analysis of Cd tolerance, physiological responses, and multifaceted plant microbiomes in tall fescue fields has not been extensively researched. Therefore, this study employed microbial sequencing (i.e., 16S and ITS sequencing) to investigate the differences in microbial community structure among various plant compartments of Cd-resistant tall fescue (cv. 'Arid3') and Cd-sensitive tall fescue (cv. 'Barrington'). Furthermore, we examined the mechanism of resistance to Cd by introducing three different bacteria and a fungus that were isolated from the 'Arid3' rhizosheath soil. It highlighted the potential application of enriched taxa such as Delftia, Novosphingobium, Cupriavidus and Torula in enhancing the activity of antioxidant defense systems, increasing the production of osmotic regulatory substances, and stimulating the expression of Cd-resistance genes. This ultimately promoted plant growth and enhanced phytoremediation efficiency. This study shed light on the response mechanism of the tall fescue microbiome to Cd stress and underscored the potential of tall fescue-microbe co-culture in the remediation of heavy metal-contaminated areas.

Effects of Selenium, Iron, and Zinc Enrichment on Cultured Sea Cucumber (Apostichopus Japonicus).

Selenium, iron, and zinc (Se, Fe, Zn) are essential trace elements crucial for animal growth, development, and immune protection, but they can be detrimental in excess. This study evaluates the impacts of Se, Fe and Zn on Apostichopus japonicus over a period of nine days, utilizing concentrations ranging from low to high: Se (0.20 µmol/L and 0.82 µmol/L), Fe (4.74 µmol/L and 18.96 µmol/L), Zn (1.88 µmol/L and 7.51 µmol/L). Concentrations of these trace elements in sea cucumbers increased with exposure time. Activities of CAT, SOD, and GSH-PX enzymes were enhanced. Transcriptomic analyses of sea cucumber body wall revealed significant gene expression changes, with differentially expressed genes (DEGs) numbering 294 at high and 945 at low Se concentrations, 906 at high and 210 at low Fe concentrations, and 423 at high and 123 at low Zn concentrations. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses highlighted DEGs enrichment in critical metabolic and immune-related pathways, including DNA replication, arachidonic acid metabolism, and oxidative phosphorylation. These results suggest that energy metabolism and immune regulation are pivotal in managing these elements, potentially enhancing sea cucumber immunity. This study enhances our comprehension of the physiological responses of sea cucumbers to trace elements and provides a theoretical basis for their use in aquaculture.

Modifying the Ambient Light Spectrum Using LED Lamps Alters the Phenolic Profile of Hydroponically Grown Greenhouse Lettuce Plants without Affecting Their Agronomic Characteristics.

The growth and development of green lettuce plants can be modulated by the prevailing light conditions around them. The aim of this study was to evaluate the effect of ambient light enrichment with different LED light spectra on agronomic characteristics, polyphenol concentration and relative gene expression of enzymes associated with polyphenol formation in 'Levistro' lettuce grown hydroponically in a Nutrient Film Technique (NFT) system for 28 days in a greenhouse. The spectra (blue:green:red:far-red) and red:blue (R:B) ratios obtained by enriching ambient light with Blue (B), White (W), Blue-Red (BR) and Red (R) LED light were B: 47:22:21:10, 0.5:1; W: 30:38:23:9, 0.8:1; BR: 33:15:44:8, 1.3:1 and R: 16:16:60:8, 3.8:1, respectively, and photosynthetically active radiation (PAR) under the different treatments, measured at midday, ranged from 328 to 336 µmoles m-2 s-1. The resulting daily light integral (DLI) was between 9.1 and 9.6 mol m-2 day-1. The photoperiod for all enrichment treatments was 12 h of light. The control was ambient greenhouse light (25:30:30:15; R:B = 1.2:1; PAR = 702 µmoles m-2 s-1; DLI = 16.9 mol m-2 day-1; photoperiod = 14.2 h of light). Fresh weight (FW) and dried weight percentage (DWP) were similar among the enrichment treatments and the control. The leaf number increased significantly under BR and R compared to B lights. The relative index of chlorophyll concentration (RIC) increased as plants grew and was similar among the enrichment treatments and the control. On the other hand, the concentration of chlorogenic acid and chicoric acid increased under BR and B lights, which was consistent with the higher relative expression of the coumarate 3-hydroxylase enzyme gene. In view of the results, it is inferred that half of the PAR or DLI is sufficient to achieve normal growth and development of 'Levistro' lettuce plants, suggesting a more efficient use of light energy under the light enrichment treatments. On the other hand, the blue and combined blue-red lights promoted the accumulation of phenolic compounds in the leaves of 'Levistro' lettuce plants.

Tumor and α-SMA-expressing stromal cells in pancreatic neuroendocrine tumors have a distinct RNA profile depending on tumor grade.

Alpha-smooth muscle actin (α-SMA) expression in the stroma is linked to the presence of cancer-associated fibroblasts and is known to correlate with worse outcomes in various tumors. In this study, using a GeoMx digital spatial profiling approach, we characterized the gene expression of the tumor and α-SMA-expressing stromal cell compartments in pancreatic neuroendocrine tumors (PanNETs). The profiling was performed on tissues from eight retrospective cases (three grade 1, four grade 2, and one grade 3). Selected regions of interest were segmented geometrically based on tissue morphology and fluorescent signals from synaptophysin and α-SMA markers. The α-SMA-expressing stromal-cell-associated genes were involved in pathways of extracellular matrix modification, whereas, in tumor cells, the gene expression profiles were associated with pathways involved in cell proliferation. The comparison of gene expression profiles across all three PanNET grades revealed that the differences between grades are not only present at the level of the tumor but also in the α-SMA-expressing stromal cells. Furthermore, the tumor cells from regions with a rich presence of adjacent α-SMA-expressing stromal cells revealed an upregulation of matrix metalloproteinase-9 (MMP9) expression in grade 3 tumors. This study provides an in-depth characterization of gene expression profiles in α-SMA-expressing stromal and tumor cells, and outlines potential crosstalk mechanisms.

Formononetin inhibits IgE by huPlasma/PBMCs and mast cells/basophil activation via JAK/STAT/PI3-Akt pathways.

Rationale: Food allergy is a prevalent disease in the U.S., affecting nearly 30 million people. The primary management strategy for this condition is food avoidance, as limited treatment options are available. The elevation of pathologic IgE and over-reactive mast cells/basophils is a central factor in food allergy anaphylaxis. This study aims to comprehensively evaluate the potential therapeutic mechanisms of a small molecule compound called formononetin in regulating IgE and mast cell activation. Methods: In this study, we determined the inhibitory effect of formononetin on the production of human IgE from peripheral blood mononuclear cells of food-allergic patients using ELISA. We also measured formononetin's effect on preventing mast cell degranulation in RBL-2H3 and KU812 cells using beta-hexosaminidase assay. To identify potential targets of formononetin in IgE-mediated diseases, mast cell disorders, and food allergies, we utilized computational modeling to analyze mechanistic targets of formononetin from various databases, including SEA, Swiss Target Prediction, PubChem, Gene Cards, and Mala Cards. We generated a KEGG pathway, Gene Ontology, and Compound Target Pathway Disease Network using these targets. Finally, we used qRT-PCR to measure the gene expression of selected targets in KU812 and U266 cell lines. Results: Formononetin significantly decreased IgE production in IgE-producing human myeloma cells and PBMCs from food-allergic patients in a dose-dependent manner without cytotoxicity. Formononetin decreased beta-hexosaminidase release in RBL-2H3 cells and KU812 cells. Formononetin regulates 25 targets in food allergy, 51 in IgE diseases, and 19 in mast cell diseases. KEGG pathway and gene ontology analysis of targets showed that formononetin regulated disease pathways, primary immunodeficiency, Epstein-Barr Virus, and pathways in cancer. The biological processes regulated by formononetin include B cell proliferation, differentiation, immune response, and activation processes. Compound target pathway disease network identified NFKB1, NFKBIA, STAT1, STAT3, CCND1, TP53, TYK2, and CASP8 as the top targets regulated at a high degree by formononetin. TP53, STAT3, PTPRC, IL2, and CD19 were identified as the proteins mostly targeted by formononetin. qPCR validated genes of Formononetin molecular targets of IgE regulation in U266 cells and KU812 cells. In U266 cells, formononetin was found to significantly increase the gene expression of NFKBIA, TP53, and BCL-2 while decreasing the gene expression of BTK TYK, CASP8, STAT3, CCND1, STAT1, NFKB1, IL7R. In basophils KU812 cells, formononetin significantly increased the gene expression of NFKBIA, TP53, and BCL-2 while decreasing the gene expression of BTK, TYK, CASP8, STAT3, CCND1, STAT1, NFKB1, IL7R. Conclusion: These findings comprehensively present formononetin's mechanisms in regulating IgE production in plasma cells and degranulation in mast cells.

Construction of store-operated calcium entry-related gene signature for predicting prognosis and indicates immune microenvironment infiltration in stomach adenocarcinomas.

Gastric adenocarcinoma (STAD) is the most prevalent malignancy of the human digestive system and the fourth leading cause of cancer-related death. Calcium pools, especially Ca2+ entry (SOCE) for storage operations, play a crucial role in maintaining intracellular and extracellular calcium balance, influencing cell activity, and facilitating tumor progression. Nevertheless, the prognostic and immunological value of SOCE in STAD has not been systematically studied. The objective of this study was to develop a risk model for SOCE signature and to explore its correlation with clinical characteristics, prognosis, tumor microenvironment (TME), as well as response to immunotherapy, chemotherapy, and targeted drugs. We used the TCGA, GEO (GSE84437 and GSE159929), cBioPortal and TIMER databases to acquire mRNA expression data for STAD, along with patient clinical indicators, single-cell sequencing data, genomic variation information, and correlations of immune cell infiltration. An analysis of SOCE genes based on tumor vs. normal tissue comparisons, pan-cancer dimension, single-cell sequencing, DNA mutation, and copy number variation revealed that SOCE genes significantly impact the survival of STAD patients and are differentially involved in the immune response. SOCE co-expressed genes were identified by Pearson analysis, and subsequently protein-protein interaction (PPI) and gene function enrichment analysis indicated that coexpressed genes were associated with multicellular pathways. Based on TCGA and GSE84437 datasets, a multifactor Cox proportional hazard regression analysis was conducted to identify SOCE co-expressed genes associated with overall survival in STAD patients. Several mRNA prognostic genes, including PTPRJ, GPR146, LTBP3, FBLN1, EFEMP2, ADAMTS7 and LBH, were identified, which could be used as effective prognostic predictors for STAD patients. In both training and test datasets, receiver operating characteristic (ROC) curves were utilized to evaluate and illustrate the predictive capability of this characteristic in forecasting overall survival of STAD patients. The qPCR and human protein atlas (HPA) were employed to assess mRNA expression and protein levels. Furthermore, the ESTIMATE, TIMER, CIBERSORT, QUANTISEQ, MCPCOUNTER, xCell and EPIC algorithms were utilized to perform immune score and analyze immune cell infiltration. It effectively revealed the difference in prognosis and immune cell infiltration in TME between high-risk and low-risk groups based on the risk signature associated with SOCE. Notably, significant differences in tumor immune dysfunction and rejection (TIDE) scores between the two groups, suggesting that patients in the low-risk group may exhibit a more favorable response to ICIS treatment. The GDSC database and R packages for predictive analysis were utilized to analyze responses to chemotherapy and targeted drugs in high-risk and low-risk groups. In summary, the 7-gene signature associated with SOCE serves as a significant biomarker for evaluating the TME and predicting the prognosis of STAD patients. In addition, it may provide valuable insights for developing effective immunotherapy and chemotherapy regiments for patients with STAD.

Combining rVAR2 and Anti-EpCAM to Increase the Capture Efficiency of Non-Small-Cell Lung Cancer Cell Lines in the Flow Enrichment Target Capture Halbach (FETCH) Magnetic Separation System.

Circulating tumor cells (CTCs) are detected in approximately 30% of metastatic non-small-cell lung cancer (NSCLC) cases using the CellSearch system, which relies on EpCAM immunomagnetic enrichment and Cytokeratin detection. This study evaluated the effectiveness of immunomagnetic enrichment targeting oncofetal chondroitin sulfate (ofCS) using recombinant VAR2CSA proteins (rVAR2) to improve the recovery of different NSCLC cell lines spiked into lysed blood samples. Four NSCLC cell lines-NCI-H1563, A549, NCI-H1792, and NCI-H661-were used to assess capture efficiency. The results demonstrated that the combined use of anti-EpCAM antibody and rVAR2 significantly enhanced the capture efficiency to an average of 88.2% compared with 40.6% when using only anti-EpCAM and 56.6% when using only rVAR2. These findings suggest that a dual-marker approach using anti-EpCAM and rVAR2 can provide a more robust and sensitive method for CTC enrichment in NSCLC, potentially leading to better diagnostic and prognostic outcomes.

Rapid Characterization of Phospholipids from Biological Matrix Enabled by Indium Tin Oxide (ITO) Coated Slide Assisted Enrichment MALDI Mass Spectrometry.

Lipidomic analysis of human serum is essential to monitor the individual's health status. Herein, we develop a facile strategy for rapid characterization of phospholipids in human serum via indium tin oxide (ITO) coated glass slide solid phase extraction MALDI mass spectrometry (ITO-SPE-MALDI-MS). Phospholipid species are retained on ITO slide via solid phase extraction owing to the unique property of the ITO material; the measurement of phospholipid species from 1 µl human serum within 2 min is achievable. A comparison of ITO-SPE strategy with conventional extraction methods was further carried out using liquid chromatography-mass spectrometry (LC-MS) and ion-mobility mass spectrometry (IM-MS), resulting in a comparable enrichment performance for the phospholipid analysis. Furthermore, rapid lipidomic profiling of serum samples from human colorectal cancer patients and cell lines was demonstrated. Our results indicate that ITO-SPE-MALDI-MS provides a higher throughput strategy for the analysis of phospholipid species in complex biological mixtures, showcasing its potential for applications in the analysis of clinical biofluids.