Gene Ontology Consortium: going forward

A Novel Mitochondrial-Related Gene Signature for the Prediction of Prognosis and Therapeutic Efficacy in Lower-Grade Glioma

Lower-grade glioma (LGG) is a common primary brain tumor with a highly heterogeneous clinical presentation, and its prognosis cannot be accurately predicted by current histopathology. It has been found that mitochondria play an important role in hypoxia, angiogenesis, and energy metabolism in glioma, and mitochondrial function may have an important impact on LGG prognosis. The goal of this study was to develop a novel prognostic model based on Mitochondrial-related genes (MRGs). We first analyzed the somatic alterations profiles of MRGs in patients with LGG and found that somatic alterations were common in LGG and correlated with prognosis. Using RNA-seq data from TCGA and CGGA, 12 prognosis-related MRGs were identified to construct a mitochondrial activation score (MiAS) model by combining univariate regression and LASSO regression analysis. The model and nomogram were evaluated using the area under the ROC curve with AUC = 0.910. The model was closely correlated with the clinical characteristics of LGG patients and performed well in predicting the prognosis of LGG patients with significantly shorter overall survival (OS) time in the high-MiAS group. GSVA and GSEA results showed that oxidative stress, pro-cancer, and immune-related pathways were significantly enriched in the high-MiAS group. CIBERSORT results showed that MiAS was significantly associated with immune cell infiltration in LGG. Macrophage M1 and follicular helper T cells had increased infiltration in the high-MiAS group. TIDE predicted a better immunotherapy outcome in patients in the low-MiAS group. Finally, using data from the CTRPv2 and GDSC2 datasets to assess chemotherapy response in LGG, it was predicted that the chemotherapeutic agents AZD6482, MG-132, and PLX-4720 might be potential agents for patients in the high-MiAS group of LGG. In addition, we performed in vitro experiments and found that knockdown of OCIAD2 expression reduced the abilities of glioma cells to proliferate, migrate, and invade. In contrast, overexpression of OCIAD2 enhanced these abilities of glioma cells. This study found that MRGs were correlated with LGG patient prognosis, which is expected to provide new treatment strategies for LGG patients with different MiAS.

Magnetic-field-driven targeting of exosomes modulates immune and metabolic changes in dystrophic muscle

Exosomes are promising therapeutics for tissue repair and regeneration to induce and guide appropriate immune responses in dystrophic pathologies. However, manipulating exosomes to control their biodistribution and targeting them in vivo to achieve adequate therapeutic benefits still poses a major challenge. Here we overcome this limitation by developing an externally controlled delivery system for primed annexin A1 myo-exosomes (Exomyo). Effective nanocarriers are realized by immobilizing the Exomyo onto ferromagnetic nanotubes to achieve controlled delivery and localization of Exomyo to skeletal muscles by systemic injection using an external magnetic field. Quantitative muscle-level analyses revealed that macrophages dominate the uptake of Exomyo from these ferromagnetic nanotubes in vivo to synergistically promote beneficial muscle responses in a murine animal model of Duchenne muscular dystrophy. Our findings provide insights into the development of exosome-based therapies for muscle diseases and, in general, highlight the formulation of effective functional nanocarriers aimed at optimizing exosome biodistribution.

Identification of autophagy-related signatures in doxorubicin-induced cardiotoxicity

PURPOSE

Doxorubicin is an antibiotic drug used clinically to treat infectious diseases and tumors. Unfortunately, it is cardiotoxic. Autophagy is a cellular self-decomposition process that is essential for maintaining homeostasis in the internal environment. Accordingly, the present study was proposed to characterize the autophagy-related signatures of doxorubicin-induced cardiotoxicity.

METHODS

Datasets related to doxorubicin-induced cardiotoxicity were retrieved by searching the GEO database and differentially expressed genes (DEGs) were identified. DEGs were taken to intersect with autophagy-related genes to obtain autophagy-related signatures, and Gene Ontology (GO)/Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis and protein-protein interaction (PPI) network were performed on them. Further, construction of miRNA-hub gene networks and identification of target drugs to reveal potential molecular mechanisms and therapeutic strategies. Animal models of doxorubicin-induced cardiotoxicity were constructed to validate differences in gene expression for autophagy-related signatures.

RESULTS

PBMC and heart samples from the GSE37260 dataset were selected for analysis. There were 995 and 2357 DEGs in PBMC and heart samples, respectively, and they had 23 intersecting genes with autophagy-related genes. RT-qPCR confirmed the differential expression of 23 intersecting genes in doxorubicin-induced cardiotoxicity animal models in general agreement with the bioinformatics results. An autophagy-related signatures consisting of 23 intersecting genes is involved in mediating processes and pathways such as autophagy, oxidative stress, apoptosis, protein ubiquitination and phosphorylation. Moreover, Akt1, Hif1a and Mapk3 are hub genes in autophagy-associated signatures and their upstream miRNAs are mainly rno-miR-1188-5p, rno-miR-150-3p and rno-miR-326-3p, and their drugs are mainly CHEMBL55802, Carboxyamidotriazole and 3-methyladenine.

CONCLUSION

This study identifies for the first-time autophagy-related signatures in doxorubicin's cardiotoxicity, which could provide potential molecular mechanisms and therapeutic strategies for doxorubicin-induced cardiotoxicity.

An atlas of genetic effects on cellular composition of the tumor microenvironment

Deciphering the composition of the tumor microenvironment (TME) is critical for understanding tumorigenesis and to design immunotherapies. In the present study, we mapped genetic effects on cell-type proportions using single-cell and bulk RNA sequencing data, identifying 3,494 immunity quantitative trait loci (immunQTLs) across 23 cancer types from The Cancer Genome Atlas. Functional annotation revealed regulatory potential and we further assigned 1,668 genes that regulate TME composition. We constructed a combined immunQTL map by integrating data from European and Chinese colorectal cancer (CRC) samples. A polygenic risk score that incorporates these immunQTLs and hits on a genome-wide association study outperformed in CRC risk stratification within 447,495 multiethnic individuals. Using large-scale population cohorts, we identified that the immunQTL rs1360948 is associated with CRC risk and prognosis. Mechanistically, the rs1360948-G-allele increases CCL2 expression, recruiting regulatory T cells that can exert immunosuppressive effects on CRC progression. Blocking the CCL2-CCR2 axis enhanced anti-programmed cell death protein 1 ligand therapy. Finally, we have established a database (CancerlmmunityQTL2) to serve the research community and advance our understanding of immunogenomic interactions in cancer pathogenesis.

Expression and prognostic impact of VDAC3 in colorectal adenocarcinoma

Background

Colorectal adenocarcinoma (COAD) is a malignant tumor with high mortality and low 5-year survival rate. Voltage-dependent anion channel 3 (VDAC3) is the least understood isoform of voltage-dependent anion-selective channels in the mitochondrial outer membrane. In this thesis, we aimed to investigate the prognostic value of VDAC3 and provide new insights into colon adenocarcinoma.

Methods

We utilized The Cancer Genome Atlas (TCGA) database, Gene Expression Omnibus (GEO) database, Human Protein Atlas online database, and the University of ALabama at Birmingham CANcer data analysis Portal (UALCAN) database to analyze VDAC3 expression in COAD and assess patient survival rates. Univariate and multivariate Cox regression analyses were employed to evaluate VDAC3's prognostic significance for COAD. Gene set variation analysis (GSVA) was utilized to explore COAD-related signaling pathways associated with VDAC3. Additionally, we predicted the relationship between VDAC3 expression and anticancer drug sensitivity using the CellMiner database.

Results

In the TCGA database, VDAC3 demonstrated elevated expression levels in COAD, which was further validated by findings from the GEO database. Survival analysis conducted using Kaplan-Meier (K-M) curves highlighted that the patients with decreased VDAC3 expression exhibited significantly shorter overall survival durations. VDAC3 expression demonstrated correlation with COAD pathological stage. VDAC3 gene mutation was linked to COAD outcomes. Cox regression analysis showed that VDAC3 was an independent predictor. In addition, GSVA analysis showed that VDAC3 was closely related to mitochondria-related biological processes and involved in the occurrence and development of mitochondria-related diseases. Finally, analysis of the CellMiner database predicted that VDAC3 expression was positively correlated with chelerythrine and cladribine, but negatively correlated with Ergenyl.

Conclusions

Our study suggests that VDAC3 may be a potential biomarker for early diagnosis, prognosis, and treatment of COAD.

Intestinal flora and inflammatory bowel disease: Causal relationships and predictive models

Background

Inflammatory bowel disease (IBD), including Crohn's disease and ulcerative colitis, is significantly influenced by intestinal flora. Understanding the genetic and microbiotic interplay is crucial for IBD prediction and treatment.

Methods

We used Mendelian randomization (MR), transcriptomic analysis, and machine learning techniques, integrating data from the MiBioGen Consortium and various GWAS datasets. SNPs associated with intestinal flora were mapped to genes, with LASSO regression refining gene selection. Differentially expressed genes (DEGs) and immune infiltration patterns were identified through transcriptomic analysis. Six machine learning models were used for predictive modeling.

Findings

MR analysis identified 25 gut microbiota classifications causally related to IBD. SNP mapping and gene expression analysis highlighted 24 significant genes. Drug target MR and colocalization validated these genes' causal relationships with IBD. Key pathways identified included the PI3K-Akt signaling pathway and epithelial-mesenchymal transition. Immune infiltration analysis revealed distinct patterns between high and low LASSO score groups. Machine learning models demonstrated high predictive value, with soft voting enhancing reliability.

Interpretation

By integrating MR, transcriptomic analysis, and sophisticated machine learning approaches, this study elucidates the causal relationships between intestinal flora and IBD. The application of machine learning not only enhanced predictive modeling but also offered new insights into IBD pathogenesis, highlighted potential therapeutic targets, and established a robust framework for predicting IBD onset.

Molecular profiling of a rat model of vascular dementia: Evidences from proteomics, metabolomics and experimental validations

Decrease of cerebral blood flow is the primary cause of vascular dementia (VD), but its pathophysiological mechanisms are still not known. This study aims to profile the molecular changes of a rat model of VD induced by bilateral common carotid artery ligation. The Morris water maze and new object recognition tasks were used to test the cognitive function of rats. Hematoxylin and Eosin (HE) staining was used to detect pathological changes in the hippocampus. After confirming the model, proteomics was used to detect differentially expressed proteins in the hippocampus, and metabolomics was used to detect differential metabolites in rat serum. Thereafter, bioinformatics were used to integrate and analyze the potential molecular profile. The results showed that compared with the sham control group, the spatial and recognition memory of the rats were significantly reduced, and pathological changes were observed in the hippocampal CA1 region of the model group. Proteomic analysis suggested 206 differentially expressed proteins in the hippocampus of VD rats, with 117 proteins upregulated and 89 downregulated. Protein-protein interaction network analysis suggested that those differentially expressed proteins might play crucial roles in lipid metabolism, cell adhesion, intracellular transport, and signal transduction. Metabolomics analysis identified 103 differential metabolites, and comparison with the human metabolome database revealed 22 common metabolites, which predicted 265 potential targets. Afterwards, by intersecting the predicted results from metabolomics with the differentially expressed proteins from proteomics, we identified five potential targets, namely ACE, GABBR1, Rock1, Abcc1 and Mapk10. Furthermore, western blotting confirmed that compared with control group, hippocampal GABBR1 and Rock1 were enhanced in the model group. Together, this study showed the molecular profile of VD rats through a combination of proteomics, metabolomics, and experimental confirmation methods, offering crucial molecular targets for the diagnosis and treatment of VD.

Metabolomics and network pharmacology reveal partial insights into the hypolipidemic mechanisms of ferulic acid in a dyslipidemia mouse model

Introduction

Hyperlipidemia is a condition characterized by abnormal levels of lipids and lipoproteins in the plasma, posing significant health risks. Ferulic acid (FA) is an organic acid with therapeutic properties for diabetes and hyperlipidemia.

Methods

To explore biomarkers for FA treatment of hyperlipidemia and elucidate the mechanisms of lipid-lowering-related changes in metabolic pathways by metabolomics and network pharmacology. Initially, a hyperlipidemic mouse model induced by triton WR-1339 was established to evaluate the therapeutic effects of FA. Subsequently, serum metabolomics was utilized to identify differential metabolites, and metabolic pathway analysis was performed using MetaboAnalyst 6.0. Thirdly, network pharmacology was employed to identify potential targets of FA for hyperlipidemia. Finally, the compound-target-metabolite (C-T-M) network obtained core targets and validated them with molecular docking.

Results

Biochemical analysis and histological examination showed that FA had lipid-lowering effects on hyperlipidemic mice. It identified 31 potential biomarkers for FA against hyperlipidemia by metabolomics involving lipid and amino acid metabolism. Lipid and atherosclerosis signaling pathways were identified as the key signaling pathways of FA against hyperlipidemia by KEGG analysis. Conjoint analysis showed that FA against hyperlipidemia was associated with 18 core targets and six biomarkers. Molecular docking results showed that FA has a high binding affinity to these core targets.

Discussion

Through the synergy of network pharmacology and metabolomics, this study provides insights into how FA regulates endogenous metabolites, underscoring its promise as a treatment for hyperlipidemia.

Identification and Validation of Oxidative Stress-Related Biomarkers for Bronchopulmonary Dysplasia

The objective of this study was to identify and characterize oxidative stress (OS)-related biomarkers in bronchopulmonary dysplasia (BPD) through a combination of bioinformatics analyses and wet experiments. The study utilized the Gene Expression Omnibus database to obtain the mRNA expression profile dataset GSE32472. Differential expression analysis and functional enrichment analysis were employed to investigate the role of OS-related genes in BPD. Gene Ontology Function Enrichment Analysis and Gene Set Enrichment Analysis were conducted to understand the mechanisms behind the signature. Protein-protein interaction analysis to identify hub genes in BPD, and predictions were made for microRNAs (miRNAs), transcription factors (TFs), and potential medications targeting these genes. CIBERSORT was utilized to investigate the correlation between hub genes and the infiltration of immune cells. Hub genes were ultimately determined and confirmed using expression analysis, correlation analysis, receiver operating characteristic (ROC) analysis, and quantitative real-time PCR (qRT-PCR). A novel OS-related gene signature (ARG1, CSF3R, IL1R1, IL1R2, MMP9, RETN, S100A12, and SOCS3) was constructed for the prediction of BPD. We identified 18 miRNAs, 14 TFs, and 30 potential medications targeting these genes. ROC analysis further validated that these genes could diagnose BPD with high specificity and sensitivity. The qRT-PCR revealed that IL1R1 and ARG1 were highly expressed in the lung tissue of the model group, while the expressions of RETN, SOCS3, IL1R2, and MMP9 were decreased. This study demonstrated that ARG1, CSF3R, IL1R1, IL1R2, MMP9, RETN, S100A12, and SOCS3 may serve as potential diagnostic biomarkers in BPD. Furthermore, a significant association between IL1R1 and the pathogenesis of BPD is observed.

Radiomics predicts the prognosis of patients with clear cell renal cell carcinoma by reflecting the tumor heterogeneity and microenvironment

PURPOSE

We aimed to develop and externally validate a CT-based deep learning radiomics model for predicting overall survival (OS) in clear cell renal cell carcinoma (ccRCC) patients, and investigate the association of radiomics with tumor heterogeneity and microenvironment.

METHODS

The clinicopathological data and contrast-enhanced CT images of 512 ccRCC patients from three institutions were collected. A total of 3566 deep learning radiomics features were extracted from 3D regions of interest. We generated the deep learning radiomics score (DLRS), and validated this score using an external cohort from TCIA. Patients were divided into high and low-score groups by the DLRS. Sequencing data from the corresponding TCGA cohort were used to reveal the differences of tumor heterogeneity and microenvironment between different radiomics score groups. What's more, univariate and multivariate Cox regression were used to identify independent risk factors of poor OS after operation. A combined model was developed by incorporating the DLRS and clinicopathological features. The SHapley Additive exPlanation method was used for interpretation of predictive results.

RESULTS

At multivariate Cox regression analysis, the DLRS was identified as an independent risk factor of poor OS. The genomic landscape of different radiomics score groups was investigated. The heterogeneity of tumor cell and tumor microenvironment significantly varied between both groups. In the test cohort, the combined model had a great predictive performance, with AUCs (95%CI) for 1, 3 and 5-year OS of 0.879(0.868-0.931), 0.854(0.819-0.899) and 0.831(0.813-0.868), respectively. There was a significant difference in survival time between different groups stratified by the combined model. This model showed great discrimination and calibration, outperforming the existing prognostic models (all p values < 0.05).

CONCLUSION

The combined model allowed for the prognostic prediction of ccRCC patients by incorporating the DLRS and significant clinicopathologic features. The radiomics features could reflect the tumor heterogeneity and microenvironment.

Single-cell RNA sequencing explored potential therapeutic targets by revealing the tumor microenvironment of neuroblastoma and its expression in cell death

BACKGROUND

Neuroblastoma (NB) is the most common extracranial solid tumor in childhood and is closely related to the early development and differentiation of neuroendocrine (NE) cells. The disease is mainly represented by high-risk NB, which has the characteristics of high mortality and difficult treatment. The survival rate of high-risk NB patients is not ideal. In this article, we not only conducted a comprehensive study of NB through single-cell RNA sequencing (scRNA-seq) but also further analyzed cuproptosis, a new cell death pathway, in order to find clinical treatment targets from a new perspective.

MATERIALS AND METHODS

The Seurat software was employed to process the scRNA-seq data. This was followed by the utilization of GO enrichment analysis and GSEA to unveil pertinent enriched pathways. The inferCNV software package was harnessed to investigate chromosomal copy number variations. pseudotime analyses involved the use of Monocle 2, CytoTRACE, and Slingshot software. CellChat was employed to analyze the intercellular communication network for NB. Furthermore, PySCENIC was deployed to review the profile of transcription factors.

RESULT

Using scRNA-seq, we studied cells from patients with NB. NE cells exhibited superior specificity in contrast to other cell types. Among NE cells, C1 PCLAF + NE cells showed a close correlation with the genesis and advancement of NB. The key marker genes, cognate receptor pairing, developmental trajectories, metabolic pathways, transcription factors, and enrichment pathways in C1 PCLAF + NE cells, as well as the expression of cuproptosis in C1 PCLAF + NE cells, provided new ideas for exploring new therapeutic targets for NB.

CONCLUSION

The results revealed the specificity of malignant NE cells in NB, especially the key subset of C1 PCLAF + NE cells, which enhanced our understanding of the key role of the tumor microenvironment in the complexity of cancer progression. Of course, cell death played an important role in the progression of NB, which also promoted our research on new targets. The scrutiny of these findings proved advantageous in uncovering innovative therapeutic targets, thereby bolstering clinical interventions.

Generation of cytotoxic aptamers specifically targeting fibroblast-like synoviocytes by CSCT-SELEX for treatment of rheumatoid arthritis

OBJECTIVES

Rheumatoid arthritis (RA) is an autoimmune disease characterised by aggressive fibroblast-like synoviocytes (FLSs). Very few RA patients-derived FLSs (RA-FLSs)-specific surface signatures have been identified, and there is currently no approved targeted therapy for RA-FLSs. This study aimed to screen therapeutic aptamers with cell-targeting and cytotoxic properties against RA-FLSs and to uncover the molecular targets and mechanism of action of the screened aptamers.

METHODS

We developed a cell-specific and cytotoxic systematic evolution of ligands by exponential enrichment (CSCT-SELEX) method to screen the therapeutic aptamers without prior knowledge of the surface signatures of RA-FLSs. The molecular targets and mechanisms of action of the screened aptamers were determined by pull-down assays and RNA sequencing. The therapeutic efficacy of the screened aptamers was examined in arthritic mouse models.

RESULTS

We obtained an aptamer SAPT8 that selectively recognised and killed RA-FLSs. The molecular target of SAPT8 was nucleolin (NCL), a shuttling protein overexpressed on the surface and involved in the tumor-like transformation of RA-FLSs. Mechanistically, SAPT8 interacted with the surface NCL and was internalised to achieve lysosomal degradation of NCL, leading to the upregulation of proapoptotic p53 and downregulation of antiapoptotic B-cell lymphoma 2 (Bcl-2) in RA-FLSs. When administrated systemically to arthritic mice, SAPT8 accumulated in the inflamed FLSs of joints. SAPT8 monotherapy or its combination with tumour necrosis factor (TNF)-targeted biologics was shown to relieve arthritis in mouse models.

CONCLUSIONS

CSCT-SELEX could be a promising strategy for developing cell-targeting and cytotoxic aptamers. SAPT8 aptamer selectively ablates RA-FLSs via modulating NCL-p53/Bcl-2 signalling, representing a potential alternative or complementary therapy for RA.

Construction of circRNA-mediated ceRNA network and immunoassay for investigating pathogenesis of COPD

Background

The chronic respiratory condition known as chronic obstructive pulmonary disease (COPD) was one of the main causes of death and disability worldwide. This study aimed to explore and elucidate new targets and molecular mechanisms of COPD by constructing competitive endogenous RNA (ceRNA) networks.

Methods

GSE38974 and GSE106986 were used to select DEGs in COPD samples and normal samples. Cytoscape software was used to construct and present protein-protein interaction (PPI) network, mRNA-miRNA co-expression network and ceRNA network. The CIBERSORT algorithm and the Lasso model were used to screen the immune infiltrating cells and hub genes associated with COPD, and the correlation between them was analyzed. COPD cell models were constructed in vitro and the expression level of ceRNA network factors mediated by hub gene was detected by reverse transcription-quantitative polymerase chain reaction (RT-qPCR).

Results

In this study, 852 differentially expressed genes were screened in the GSE38974 dataset, including 439 upregulated genes and 413 downregulated genes. Gene clustering analysis of PPI network results was performed using the Minimum Common Tumor Data Element (MCODE) in Cytoscape, and seven hub genes were screened using five algorithms in cytoHubba. CCL20 was verified as an important hub gene based on mRNA-miRNA co-expression network, GSE106986 database validation and the analysis of ROC curve results. Finally, we successfully constructed the circDTL-hsa-miR-330-3p-CCL20 network by Cytoscape. Immune infiltration analysis suggested that CCL20 can co-regulate immune cell migration and infiltration through chemokines CCL7 and CXCL3. In vitro experiments, the expression of circDTL and CCL20 was increased, while the expression of hsa-miR-330-3p was decreased in the COPD cell model.

Conclusion

By constructing the circDTL-hsa-miR-330-3p-CCL20 network, this study contributes to a better understanding of the molecular mechanism of COPD development, which also provides important clues for the development of new therapeutic strategies and drug targets.

DSCI: a database of synthetic biology components for innate immunity and cell engineering decision-making processes

Although significant progress of clinical strategy has been made in gene editing and cell engineering in immunotherapy, it is now apparent that design and modification in terms of complex signaling pathways and motifs on medical synthetic biology are still full of challenges. Innate immunity, the first line of host defense against pathogens, is critical for anti-pathogens immune response as well as regulating durable and protective T cell-mediated anti-tumor responses. Here, we introduce DSCI (Database of Synthetic Biology Components for Innate Immunity, https://dsci.renlab.cn/ ), a web-accessible and integrative database that provides better insights and strategies for innate immune signaling circuit design in biosynthesis. Users can interactively navigate comprehensive and carefully curated components resources that presented as visualized signaling motifs that participate in innate immunity. The current release of DSCI incorporates 1240 independent components and more than 4000 specific entries contextually annotated from public literature with experimental verification. The data integrated into DSCI includes the components of pathways, relationships between regulators, signal motifs based on regulatory cascades, and loop graphs, all of which have been comprehensively annotated to help guide modifications to gene circuits. With the support of DSCI, users can easily obtain guidance of gene circuits construction to make decision of cell engineering based on innate immunity. DSCI not only provides comprehensive and specialized resource on the biological components of innate immune synthesis, but also serves as a useful tool to offer modification or generation strategies for medical synthetic biology.

Coupled single-cell and bulk RNA-seq analysis reveals the engulfment role of endothelial cells in atherosclerosis

The clearance of apoptotic cell debris, containing professional phagocytosis and non-professional phagocytosis, is essential for maintaining the homeostasis of healthy tissues. Here, we discovered that endothelial cells could engulf apoptotic cell debris in atherosclerotic plaque. Single-cell RNA sequencing (RNA-seq) has revealed a unique endothelial cell subpopulation in atherosclerosis, which was strongly associated with vascular injury-related pathways. Moreover, integrated analysis of three vascular injury-related RNA-seq datasets showed that the expression of scavenger receptor class B type 1 (SR-B1) was up-regulated and specifically enriched in the phagocytosis pathway under vascular injury circumstances. Single-cell RNA-seq and bulk RNA-seq indicate that SR-B1 was highly expressed in a unique endothelial cell subpopulation of mouse aorta and strongly associated with the reorganization of cellular adherent junctions and cytoskeleton which were necessary for phagocytosis. Furthermore, SR-B1 was strongly required for endothelial cells to engulf apoptotic cell debris in atherosclerotic plaque of both mouse and human aorta. Overall, this study demonstrated that apoptotic cell debris could be engulfed by endothelial cells through SR-B1 and associated with the reorganization of cellular adherent junctions and cytoskeleton.

Comparative physiological and transcriptomic analysis of sono-biochemical control over post-acidification of Lactobacillus delbrueckii subsp. bulgaricus

Thermosonication (UT) prestress treatments combining with varied fermentation patterns has been revealed as an effective method to regulate post-acidification as exerted by Lactobacillus delbrueckii subsp. bulgaricus (L. delbrueckii), but sono-biochemical controlling mechanisms remain elusive. This study employed physiological and transcriptomic analysis to explore the response mechanism of L. delbrueckii to UT-induced microstress (600 W, 33 kHz, 10 min). UT stress-induced inhibition of acidification of L. delbrueckii during (post)-fermentation was first confirmed, relying on the UT process parameters such as stress exposure duration and UT power. The significantly enhanced membrane permeability in cells treated by 600 W for 10 min than the microbes stressed by 420 W for 20 min suggested the higher dependence of UT-derived stresses on the treatment durations, relative to the ultrasonic powers. In addition, ultrasonication treatment-induced changes in cell membrane integrity enhanced and/or disrupted permeability of L. delbrueckii, resulting in an imbalance in intracellular conditions associated with corresponding alterations in metabolic behaviors and fermentation efficiencies. UT-prestressed inoculum exhibited a 21.46% decrease in the membrane potential during the lag phase compared to untreated samples, with an intracellular pH of 5.68 ± 0.12, attributed to the lower activities of H+-ATPase and lactate dehydrogenase due to UT stress pretreatments. Comparative transcriptomic analysis revealed that UT prestress influenced the genes related to glycolysis, pyruvate metabolism, fatty acid synthesis, and ABC transport. The genes encoding 3-oxoacyl-[acyl-carrier-protein] reductases I, II, and III, CoA carboxylase, lactate dehydrogenase, pyruvate oxidase, glucose-6-phosphate isomerase, and glycerol-3-phosphate dehydrogenase were downregulated, thus identifying the relevance of the UT microstresses-downregulated absorption and utilization of carbohydrates with the attenuated fatty acid production and energy metabolisms. These findings could contribute to provide a better understanding of the inactivated effects on the post-acidification of L. delbrueckii by ultrasonic pretreatments, thus providing theoretical basis for the targeted optimization of acidification inhibition efficiencies for yogurt products during chilled preservation processes.

Clinical signature and associated immune metabolism of NLRP1 in pan-cancer

Inflammations have been linked to tumours, suggesting a potential association between NLRP1 and cancer. Nevertheless, a systematic assessment of NLRP1's role across various cancer types currently absent. A comprehensive bioinformatic analysis was conducted to determine whether NLRP1 exhibits prognostic relevance linked to immune metabolism across various cancers. The study leveraged data from the TCGA and GTEx databases to explore the clinical significance, metabolic features, and immunological characteristics of NLRP1, employing various tools such as R, GEPIA, STRING and TISIDB. NLRP1 exhibited differential expression patterns across various cancers, with elevated expression correlating with a more favourable prognosis in lung adenocarcinoma (LUAD) and pancreatic adenocarcinoma (PAAD). Downregulation of NLRP1 reduced tumour metabolic activity in LUAD. Moreover, the mutational signature of NLRP1 was linked to a favourable prognosis. Interestingly, high NLRP1 expression inversely correlated with tumour stemness while positively correlating with tumour immune infiltration in various cancers including LUAD and PAAD. Through extensive big data analysis, we delved into the role of NLRP1 across various tumour types, constructing a comprehensive role map of its involvement in pan-cancer scenarios. Our findings highlight the potential of NLRP1 as a promising therapeutic target specifically in LUAD and PAAD.

Identification of the Coexisting Virus-Derived siRNA in Maize and Rice Infected by Rice Black-Streaked Dwarf Virus

Rice black-streaked dwarf virus is transmitted by small brown planthoppers, which causes maize rough dwarf disease and rice black-streaked dwarf disease. This virus leads to slow growth or death of the host plants. During the coevolutionary arms race between viruses and plants, virus-derived small interfering RNAs (vsiRNAs) challenge the plant's defense response and inhibit host immunity through the RNA silencing system. However, it is currently unknown if rice black-streaked dwarf virus can produce the same siRNAs to mediate the RNA silencing in different infected species. In this study, four small RNA libraries and four degradome libraries were constructed by extracting total RNAs from the leaves of the maize (Zea mays) inbred line B73 and japonica rice (Oryza sativa) variety Nipponbare exposed to feeding by viruliferous and nonviruliferous small brown planthoppers. We analyzed the characteristics of small RNAs and explored virus-derived siRNAs in small RNA libraries through high-throughput sequencing. On analyzing the characteristics of small RNA, we noted that the size distributions of small RNAs were mainly 24 nt (19.74 to 62.00%), whereas those of vsiRNAs were mostly 21 nt (41.06 to 41.87%) and 22 nt (39.72 to 42.26%). The 5'-terminal nucleotides of vsiRNAs tended to be adenine or uracil. Exploring the distribution of vsiRNA hot spots on the viral genome segments revealed that the frequency of hotspots in B73 was higher than those in Nipponbare. Meanwhile, hotspots in the S9 and S10 virus genome segments were distributed similarly in both hosts. In addition, the target genes of small RNA were explored by degradome sequencing. Analyses of the regulatory pathway of these target genes unveiled that viral infection affected the ribosome-related target genes in maize and the target genes in the metabolism and biosynthesis pathways in rice. Here, 562 and 703 vsiRNAs were separately obtained in maize and rice and 73 vsiRNAs named as coexisting vsiRNAs (co-vsiRNAs) were detected in both hosts. Stem-loop PCR and real-time quantitative PCR confirmed that co-vsiRNA 3.1 and co-vsiRNA 3.5, derived from genome segment S3, simultaneously play a role in maize and rice and inhibited host gene expression. The study revealed that rice black-streaked dwarf virus can produce the same siRNAs in different species and provides a new direction for developing new antiviral strategies.

Comparison among different preclinical models derived from the same patient with a non-functional pancreatic neuroendocrine tumor

Pancreatic neuroendocrine tumors are the second most common tumors of the pancreas, and approximately half of patients are diagnosed with liver metastases. Currently, the improvement in the efficacy of relevant treatment methods is still limited. Therefore, there is an urgent need for in-depth research on the molecular biological mechanism of pancreatic neuroendocrine tumors. However, due to their relatively inert biology, preclinical models are extremely scarce. Here, the patient-derived organoid, and patient-derived xenograft were successfully constructed. These two models and the previously constructed cell line named SPNE1 all derived from the same patient with a grade 3 non-functional pancreatic neuroendocrine tumor, providing new tumor modeling platforms, and characterized using immunohistochemistry, whole-exome sequencing, and single-cell transcriptome sequencing. Combined with a tumor formation experiment in immunodeficient mice, we selected the model that most closely recapitulated the parental tumor. Overall, the patient-derived xenograft model most closely resembled human tumor tissue.

In-silico identification and functional characterization of common genes associated with type 2 diabetes and hypertension

Type 2 diabetes (T2D) and hypertension are global public health concerns and major metabolic disorders in humans. Experimental evidence indicates considerable hereditary influences on the etiology of T2D and hypertension, but the molecular basis of these diseases is still limited. Thus, the current study analyzed 185 (132 T2D and 53 hypertension) GWAS catalog datasets and identified 83 common genes linked to T2D and hypertension pathogenesis. These genes were further examined using various bioinformatics approaches to elucidate their molecular mechanisms underlying the pathophysiology of T2D and hypertension. Gene ontology (GO) analysis revealed the biological, cellular, and molecular functions of these genes, which were also linked to different T2D and hypertension pathways. Specifically, seven genes were found to be crucial for T2D, and nine were directly associated with hypertension. Protein-protein interaction (PPI) analysis identified 28 candidate genes and seven hub genes through 11 topological methods. Among 231 miRNAs, seven were significant in interacting with the hub genes, and nine transcription factors (TFs) out of 36 were linked to these hub genes. Additionally, two of the seven hub genes were downregulated by 43 FDA-approved drugs. These findings elucidate the molecular processes underlying T2D and hypertension, suggesting that targeting these genes could lead to future drug development and therapeutic strategies to treat T2D and hypertension.

Comparative genomic landscape of lower-grade glioma and glioblastoma

Biomarkers for classifying and grading gliomas have been extensively explored, whereas populations in public databases were mostly Western/European. Based on public databases cannot accurately represent Chinese population. To identify molecular characteristics associated with clinical outcomes of lower-grade glioma (LGG) and glioblastoma (GBM) in the Chinese population, we performed whole-exome sequencing (WES) in 16 LGG and 35 GBM tumor tissues. TP53 (36/51), TERT (31/51), ATRX (16/51), EFGLAM (14/51), and IDH1 (13/51) were the most common genes harboring mutations. IDH1 mutation (c.G395A; p.R132H) was significantly enriched in LGG, whereas PCDHGA10 mutation (c.A265G; p.I89V) in GBM. IDH1-wildtype and PCDHGA10 mutation were significantly related to poor prognosis. IDH1 is an important biomarker in gliomas, whereas PCDHGA10 mutation has not been reported to correlate with gliomas. Different copy number variations (CNVs) and oncogenic signaling pathways were identified between LGG and GBM. Differential genomic landscapes between LGG and GBM were revealed in the Chinese population, and PCDHGA10, for the first time, was identified as the prognostic factor of gliomas. Our results might provide a basis for molecular classification and identification of diagnostic biomarkers and even potential therapeutic targets for gliomas.

Identifying prognostic biomarkers in oral squamous cell carcinoma: an integrated single-cell and bulk RNA sequencing study on mitophagy-related genes

Oral squamous cell carcinoma (OSCC) has an extremely poor prognosis. Recent studies have suggested that mitophagy-related genes (MRGs) are closely correlated with the development and occurrence of cancer, but the role they play in oral cancer has not yet been explained.We conducted a comprehensive analysis of integrated single-cell and bulk RNA sequencing (RNA-seq) data retrieved from Gene Expression Omnibus (GEO) datasets and The Cancer Genome Atlas (TCGA) database. Multiple methods were combined to provide a comprehensive understanding of the genetic expression patterns and biology of OSCC, such as analysis of pseudotime series, CellChat cell communication, immune infiltration, Gene Ontology (GO), LASSO Cox regression, gene set variation analysis (GSVA), Kyoto Encyclopedia of Genes and Genomes (KEGG), gene set enrichment analysis (GSEA), Tumor Mutation Burden (TMB) and drug sensitivity assessments. The findings of this study demonstrated significantly greater activity of MRGs in NK cells than in other cells in OSCC. A reliable prognostic model was developed using 12 candidate genes strongly associated with mitochondrial autophagy. T stage, N stage and risk score were revealed as independent prognostic factors. Distinctively enriched pathways and immune cells were observed in different risk groups. Notably, low-risk patients were more responsive to chemotherapy. In addition, a nomogram model with excellent predictive ability was established by combining the risk scores and clinical features. The activity of MRGs suggest the potential for the development of new targeted therapies. The construction of a robust prognostic model also provides reference value for individualized prediction and clinical decision-making in patients with OSCC.

Identification of key genes and immune infiltration in peripheral blood biomarker analysis of delayed cerebral ischemia: Valproic acid as a potential therapeutic drug

BACKGROUND

Delayed cerebral ischemia (DCI) is a common and serious complication of subarachnoid hemorrhage (SAH). Its pathogenesis is not fully understood. Here, we developed a predictive model based on peripheral blood biomarkers and validated the model using several bioinformatic multi-analysis methods.

METHODS

Six datasets were obtained from the GEO database. Characteristic genes were screened using weighted correlation network analysis (WGCNA) and differentially expressed genes. Three machine learning algorithms, elastic networks-LASSO, support vector machines (SVM-RFE) and random forests (RF), were also used to construct diagnostic prediction models for key genes. To further evaluate the performance and predictive value of the diagnostic models, nomogram model were constructed, and the clinical value of the models was assessed using Decision Curve Analysis (DCA), Area Under the Check Curve (AUC), Clinical Impact Curve (CIC), and validated in the mouse single-cell RNA-seq dataset. Mendelian randomization(MR) analysis explored the causal relationship between SAH and stroke, and the intermediate influencing factors. We validated this by retrospectively analyzing the qPCR levels of the most relevant genes in SAH and SAH-DCI patients. This experiment demonstrated a statistically significant difference between SAH and SAH-DCI and normal group controls. Finally, potential small molecule compounds interacting with the selected features were screened from the Comparative Toxicogenomics Database (CTD).

RESULTS

The fGSEA results showed that activation of Toll-like receptor signaling and leukocyte transendothelial cell migration pathways were positively correlated with the DCI phenotype, whereas cytokine signaling pathways and natural killer cell-mediated cytotoxicity were negatively correlated. Consensus feature selection of DEG genes using WGCNA and three machine learning algorithms resulted in the identification of six genes (SPOCK2, TRRAP, CIB1, BCL11B, PDZD8 and LAT), which were used to predict DCI diagnosis with high accuracy. Three external datasets and the mouse single-cell dataset showed high accuracy of the diagnostic model, in addition to high performance and predictive value of the diagnostic model in DCA and CIC. MR analysis looked at stroke after SAH independent of SAH, but associated with multiple intermediate factors including Hypertensive diseases, Total triglycerides levels in medium HDL and Platelet count. qPCR confirmed that significant differences in DCI signature genes were observed between the SAH and SAH-DCI groups. Finally, valproic acid became a potential therapeutic agent for DCI based on the results of target prediction and molecular docking of the characterized genes.

CONCLUSION

This diagnostic model can identify SAH patients at high risk for DCI and may provide potential mechanisms and therapeutic targets for DCI. Valproic acid may be an important future drug for the treatment of DCI.

Chronic disease management via modulation of cellular signaling by phytoestrogen Bavachin

The emergence of chronic diseases, particularly cancers, cardiovascular, and bone disorders, presents a formidable challenge, as currently available synthetic drugs often result in significant side effects and incur higher costs. Phytoestrogen Bavachin, present in the Psoralea corylifolia L. plant, represents structural and functional similarity to mammalian estrogen and has recently attracted researchers for its medicinal properties. This review spotlighted the extraction methods, bioavailability and therapeutic interventions of Bavachin against diseases. Bavachin exerted estrogenic properties, demonstrating the ability to bind to estrogen receptors (ERs), mimicking the actions of human estrogen and initiating estrogen-responsive pathways. Bavachin delivered potent therapeutic ventures in abrogating chronic diseases, including cancer, neuronal, bone, cardiovascular, skin, lung, and liver disorders via targeting signaling transductions, managing calcium signaling, immune regulation, inflammation, apoptosis, and oxidative stress. In-silico analysis, including Gene ontology and pathway enrichment analysis, retrieved molecular targets of Bavachin, majorly cytochrome c oxidase (COX), nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB), Nucleotide-binding domain, leucine-rich-containing family, pyrin domain-containing-3 (NLRP3), and ER, hypothesizing Bavachin's cellular mechanism in preventing crucial health ailments. Limitations of Bavachin were also summarized, evidenced by hepatotoxicity at specific dosage levels. In conclusion, Bavachin showed promising therapeutic efficacy in suppressing chronic diseases and can be considered as an adequate replacement for hormone replacement therapy, necessitating further investigations on its effectiveness, safety, and clinical outcomes.

Integrating network toxicology and molecular docking to explore the toxicity of the environmental pollutant butyl hydroxyanisole: An example of induction of chronic urticaria

The study aimed to comprehensively investigate environmental pollutants' potential toxicity and underlying molecular mechanisms, focusing on chronic urticaria (CU) induced by butylated hydroxyanisole (BHA) exposure, further drawing public awareness regarding the potential risks of environmental pollutants, applying ChEMBL, STITCH, and SwissTargetPrediction databases to predict the targets of BHA, CTD, GeneCards, and OMIM databases to collect the relevant targets of CU. Ultimately, we identified 81 potential targets of BHA-induced CU and extracted 31 core targets, including TNF, SRC, CASP3, BCL2, IL2, and MMP9. GO and KEGG enrichment analyses revealed that these core targets were predominantly involved in cancer signaling, estrogen and endocrine resistance pathways. Furthermore, molecular docking confirmed the ability of BHA to bind with core targets. The onset and development of CU may result from BHA by affecting multiple immune signaling pathways. Our study elucidated the molecular mechanisms of BHA toxicity and its role in CU induction, providing the basis for preventing and treating chronic urticaria associated with environmental BHA exposure.

Identification and Validation of Aging- and Endoplasmic Reticulum Stress-Related Genes in Periodontitis Using a Competing Endogenous RNA Network

Periodontitis is a multifactorial chronic inflammatory disease that destroy periodontium. Apart from microbial infection and host immune responses, emerging evidence shows aging and endoplasmic reticulum stress (ER stress) play a key role in periodontitis pathogenesis. The aim of this study is to identify aging-related genes (ARGs) and endoplasmic reticulum stress-related genes (ERGs) in periodontitis. Data were obtained from the Gene Expression Omnibus (GEO), Human Ageing Genomic Resources (HAGR) and GeneCards databases to identify differentially expressed mRNAs/miRNAs/lncRNAs (DEmRNAs/DEmiRNAs/DElncRNAs), ARGs and ERGs, respectively. We used the MultiMiR database for the reverse prediction of miRNAs and predicted miRNA-lncRNA interactions using the STARBase database. Afterwards, we constructed a mRNA-miRNA-lncRNA ceRNA network. A total of 10 hub genes, namely LCK, LYN, CXCL8, IL6, HCK, IL1B, BTK, CXCL12, GNAI1 and FCER1G, and 5 DEmRNAs-ARGs-ERGs were then discovered. Further, weighted gene co-expression network analysis (WGCNA) and single sample gene set enrichment analysis (ssGSEA) were performed to explore co-expression modules and immune infiltration respectively. Finally, we used transmission electron microscope (TEM), inverted fluorescence microscopy, quantitative real-time polymerase chain reaction (qRT-PCR) and Western Blot to verify the bioinformatic results in periodontal ligament stem cells (PDLSCs) infected with Porphyromonas gingivalis (P. gingivalis). The experimental results broadly confirmed the accuracy of bioinformatic analysis. The present study established an aging- and ER stress-related ceRNA network in periodontitis, contributing to a deeper understanding of the pathogenesis of periodontitis.

Endoplasmic Reticulum Membrane Protein Complex Regulates Cancer Stem Cells and is Associated with Sorafenib Resistance in Hepatocellular Carcinoma

Background

Hepatocellular carcinoma (HCC) remains a leading cause of cancer-related mortality, underscoring the need for novel therapeutic targets. This study aimed to elucidate the role of endoplasmic reticulum membrane protein complex subunit 1 (EMC1) in HCC progression and its therapeutic potential.

Methods

Publicly available sequencing data and biopsy specimens were analyzed to assess EMC's clinical value and functions in HCC. In vitro experiments validated EMC functions, and multiplex immunofluorescence analysis examined EMC-associated sorafenib resistance mechanisms. EMC1 expression was knocked down in HCC cell lines, followed by cell viability, wound healing, and transwell migration assays. Tumor growth and response to sorafenib treatment were evaluated in mouse models. Metabolomic analysis assessed changes in the TCA cycle.

Results

EMC genes were aberrantly expressed in HCC, and high EMC1 expression correlated with poorer survival rates. EMC1 disruption enhanced HCC cells' sensitivity to sorafenib, reducing cell viability, increasing apoptosis, and decreasing tumor size and weight. EMC1 maintained cancer cell stemness and promoted M2 macrophage infiltration. Metabolomic analysis revealed significant changes in the TCA cycle, indicating EMC1's role in HCC metabolic reprogramming. Importantly, EMC1 is highly associated with sorafenib resistance, potentially linked to CTNNB1 mutation or activation.

Conclusion

EMC1 plays a critical role in regulating the sorafenib resistance in HCC. Targeting EMC1 may improve HCC treatment efficacy.

Exploring a specialized programmed-cell death patterns to predict the prognosis and sensitivity of immunotherapy in cutaneous melanoma via machine learning

The mortality and therapeutic failure in cutaneous melanoma (CM) are mainly caused by wide metastasis and chemotherapy resistance. Meanwhile, immunotherapy is considered a crucial therapy strategy for CM patients. However, the efficiency of currently available methods and biomarkers in predicting the response of immunotherapy and prognosis of CM is limited. Programmed cell death (PCD) plays a significant role in the occurrence, development, and therapy of various malignant tumors. In this research, we integrated fourteen types of PCD, multi-omics data from TCGA-SKCM and other cohorts in GEO, and clinical CM patients to develop our analysis. Based on significant PCD patterns, two PCD-related CM clusters with different prognosis, tumor microenvironment (TME), and response to immunotherapy were identified. Subsequently, seven PCD-related features, especially CD28, CYP1B1, JAK3, LAMP3, SFN, STAT4, and TRAF1, were utilized to establish the prognostic signature, namely cell death index (CDI). CDI accurately predicted the response to immunotherapy in both CM and other cancers. A nomogram with potential superior predictive ability was constructed, and potential drugs targeting CM patients with specific CDI have also been identified. Given all the above, a novel CDI gene signature was indicated to predict the prognosis and exploit precision therapeutic strategies of CM patients, providing unique opportunities for clinical intelligence and new management methods for the therapy of CM.

Heavy metals and elderly kidney health: A multidimensional study through Enviro-target Mendelian Randomization

Chronic Kidney Disease (CKD), closely linked to environmental factors, poses a significant public health challenge. This study, based on 529 triple-repeated measures from key national environmental pollution area and multiple gene-related public databases, employs various epidemiological and bioinformatics models to assess the impact of combined heavy metal exposure (Chromium [Cr], Cadmium [Cd], and Lead [Pb]) on early renal injury and CKD in the elderly. Introducing the novel Enviro-Target Mendelian Randomization method, our research explores the causal relationship between metals and CKD. The findings indicate a positive correlation between increased levels of metal and renal injury, with combined exposure caused renal damage more significantly than individual exposure. The study reveals that metals primarily influence CKD development through oxidative stress and metal ion resistance pathways, focusing on three related genes (SOD2, MPO, NQO1) and a transcription factor (NFE2L2). Metals were found to regulate oxidative stress levels in the body by increasing the expression of SOD2, MPO, NQO1, and decreasing NFE2L2, leading to CKD onset. Our research establishes a new causal inference framework linking environmental pollutants-pathways-genes-CKD, assessing the impact and mechanisms of metal exposure on CKD. Future studies with more extensive in vitro evidence and larger population are needed to validate.

The Y-ome Conundrum: Insights into Uncharacterized Genes and Approaches for Functional Annotation

The ever-increasing availability of genome sequencing data has revealed a substantial number of uncharacterized genes without known functions across various organisms. The first comprehensive genome sequencing of E. coli K12 revealed that more than 50% of its open reading frames corresponded to transcripts with no known functions. The group of protein-coding genes without a functional description and/or a recognized pathway, beginning with the letter "Y", is classified as the "y-ome". Several efforts have been made to elucidate the functions of these genes and to recognize their role in biological processes. This review provides a brief update on various strategies employed when studying the y-ome, such as high-throughput experimental approaches, comparative omics, metabolic engineering, gene expression analysis, and data integration techniques. Additionally, we highlight recent advancements in functional annotation methods, including the use of machine learning, network analysis, and functional genomics approaches. Novel approaches are required to produce more precise functional annotations across the genome to reduce the number of genes with unknown functions.

Complete genome sequence analysis of a biosurfactant-producing bacterium Bacillus velezensis L2D39

Biosurfactants are amphipathic molecules with high industrial values owing to their chemical properties and stability under several environmental conditions. They have become attractive microbial products in the emerging biotechnology industry, offering a potential environmentally-friendly alternative to synthetic surfactants. Nowadays, several types of biosurfactants are commercially available for a wide range of applications in healthcare, agriculture, oil extraction and environmental remediation. In this study, a marine bacterium Bacillus velezensis L2D39 with the capability of producing biosurfactants was successfully isolated and characterized. The complete genome sequence of the bacterium B. velezensis L2D39 was obtained using PacBio Sequel HGAP.4, resulting in a sequence consisting of 4,140,042 base pairs with a 46.2 mol% G + C content and containing 4071 protein-coding genes. The presence of gene clusters associated with biosurfactants was confirmed through antiSMASH detection. The analysis of complete genome sequence will provide insight into the potential applications of this bacterium in biotechnological and natural product biosynthesis.

Effect of conditioned media on the angiogenic activity of mesenchymal stem cells

Mesenchymal stem cells (MSCs) are promising candidates for use in novel cell therapies, although such live cell products are highly complex compared with traditional drugs. For example, difficulties such as the control of manufacturing conditions hinder the manufacture of stable cell populations that maintain their therapeutic potency. Here, assuming that medium selection significantly affects cell potency, we focused on the culture media as a critical manufacturing factor influencing the therapeutic efficacy of MSCs. We therefore performed a tube formation assay to quantify the angiogenic activities of conditioned media used to culture human umbilical vein endothelial cells compared with unconditioned media. Comprehensive molecular genetic analysis using microarrays was applied to determine the effects of these media on signal transduction pathways. We found that activation of the vascular endothelial growth factor (VEGF) signaling pathway differed, and that VEGF concentration was dependent on the composition of the conditioned media. These results indicate that the activation level of cell signaling pathways which contribute to therapeutic efficacy may vary depending on the media components affecting MSCs during their cultivation. Moreover, they indicate that therapeutic efficacy will likely depend on how cells are handled during manufacture. These findings will enhance our understanding of the quality control measures required to ensure the efficacy and safety of cell therapy products.

BBSdb, an open resource for bacterial biofilm-associated proteins

Bacterial biofilms are organized heterogeneous assemblages of microbial cells encased within a self-produced matrix of exopolysaccharides, extracellular DNA and proteins. Over the last decade, more and more biofilm-associated proteins have been discovered and investigated. Furthermore, omics techniques such as transcriptomes, proteomes also play important roles in identifying new biofilm-associated genes or proteins. However, those important data have been uploaded separately to various databases, which creates obstacles for biofilm researchers to have a comprehensive access to these data. In this work, we constructed BBSdb, a state-of-the-art open resource of bacterial biofilm-associated protein. It includes 48 different bacteria species, 105 transcriptome datasets, 21 proteome datasets, 1205 experimental samples, 57,823 differentially expressed genes (DEGs), 13,605 differentially expressed proteins (DEPs), 1,930 'Top 5% differentially expressed genes', 444 'Threshold-based DEGs' and a predictor for prediction of biofilm-associated protein. In addition, 1,781 biofilm-associated proteins, including annotation and sequences, were extracted from 942 articles and public databases via text-mining analysis. We used E. coli as an example to represent how to explore potential biofilm-associated proteins in bacteria. We believe that this study will be of broad interest to researchers in field of bacteria, especially biofilms, which are involved in bacterial growth, pathogenicity, and drug resistance. Availability and implementation: The BBSdb is freely available at http://124.222.145.44/#!/.

Transcription factor CmHSFA4-CmMYBS3 complex enhances salt tolerance in chrysanthemum by repressing CmMYB121 expression

Excessive soil salinity not only hampers plant growth and development but can also lead to plant death. Previously, we found that heat-shock factor A4 (CmHSFA4) enhances the tolerance of chrysanthemum (Chrysanthemum morifolium) to salt. However, the underlying molecular mechanism remains unclear. In this study, we identified a candidate MYB transcription factor, CmMYB121, which responded to salt stress. We observed that the CmMYB121 transcription is suppressed by CmHSFA4. Moreover, overexpression of CmMYB121 exacerbated chrysanthemum sensitivity to salt stress. CmHSFA4 directly bound to the promoter of CmMYB121 at the heat-shock element. Protein-protein interaction assays identified an interaction between CmHSFA4 and CmMYBS3, a transcriptional repressor, and recruited the corepressor TOPLESS (CmTPL) to inhibit CmMYB121 transcription by impairing the H3 and H4 histone acetylation levels of CmMYB121. Our study demonstrated that a CmHSFA4-CmMYBS3-CmTPL complex modulates CmMYB121 expression, consequently regulating the tolerance of chrysanthemum to salt. The findings shed light on the responses of plants to salt stress.

DNA methylation and whole-genome transcription analysis in CD4+ T cells from systemic lupus erythematosus patients with or without renal damage

BACKGROUND

Lupus nephritis (LN) is the most common cause of kidney injury in systemic lupus erythematosus (SLE) patients and is associated with increased mortality. DNA methylation, one of the most important epigenetic modifications, has been reported as a key player in the pathogenesis of SLE. Hence, our article aimed to explore DNA methylation in CD4+ T cells from LNs to identify additional potential biomarkers and pathogenic genes involved in the progression of LN.

METHODS

Our study enrolled 46 SLE patients with or without kidney injury and 23 healthy controls from 2019 to 2022. CD4+ T cells were sorted for DNA methylation genotyping and RNA-seq. Through bioinformatics analysis, we identified the significant differentially methylated CpG positions (DMPs) only in the LN group and validated them by Bisulfite PCR. Integration analysis was used to screen for differentially methylated and expressed genes that might be involved in the progression of LN, and the results were analyzed via cell experiments and flow cytometry.

RESULTS

We identified 243 hypomethylated sites and 778 hypermethylated sites only in the LN cohort. Three of these DMPs, cg08332381, cg03297029, and cg16797344, were validated by Bisulfite PCR and could be potential biomarkers for LN. Integrated analysis revealed that the expression of BCL2L14 and IFI27 was regulated by DNA methylation, which was validated by azacytidine (5-aza) treatment. The overexpression of BCL2L14 in CD4+ T cells might induce renal fibrosis and inflammation by regulating the differentiation and function of Tfh cells.

CONCLUSION

Our study identified novel aberrant DMPs in CD4+ T cells only in LN patients and DNA methylation-regulated genes that could be potential LN biomarkers. BCL2L14 is likely involved in the progression of LN and might be a treatment target.

Pathogen stimulations and immune cells synergistically affect the gene expression profile characteristics of porcine peripheral blood mononuclear cells

BACKGROUND

Pigs serve as a crucial source of protein in the human diet and play a fundamental role in ensuring food security. However, infectious diseases caused by bacteria or viruses are a major threat to effective global pig farming, jeopardizing human health. Peripheral blood mononuclear cells (PBMCs) are a mixture of immune cells that play crucial roles in immunity and disease resistance in pigs. Previous studies on the gene expression regulation patterns of PBMCs have concentrated on a single immune stimulus or immune cell subpopulation, which has limited our comprehensive understanding of the mechanisms of the pig immune response.

RESULTS

Here, we integrated and re-analyzed RNA-seq data published online for porcine PBMC stimulated by lipopolysaccharide (LPS), polyinosinic acid (PolyI:C), and various unknown microorganisms (EM). The results revealed that gene expression and its functional characterization are highly specific to the pathogen, identifying 603, 254, and 882 pathogen-specific genes and 38 shared genes, respectively. Notably, LPS and PolyI:C stimulation directly triggered inflammatory and immune-response pathways, while exposure to mixed microbes (EM) enhanced metabolic processes. These pathogen-specific genes were enriched in immune trait-associated quantitative trait loci (QTL) and eGenes in porcine immune tissues and were implicated in specific cell types. Furthermore, we discussed the roles of eQTLs rs3473322705 and rs1109431654 in regulating pathogen- and cell-specific genes CD300A and CD93, using cellular experiments. Additionally, by integrating genome-wide association studies datasets from 33 complex traits and diseases in humans, we found that pathogen-specific genes were significantly enriched for immune traits and metabolic diseases.

CONCLUSIONS

We systematically analyzed the gene expression profiles of the three stimulations and demonstrated pathogen-specific and cell-specific gene regulation across different stimulations in porcine PBMCs. These findings enhance our understanding of shared and distinct regulatory mechanisms of genetic variants in pig immune traits.

Key extracellular proteins and TF-miRNA co-regulatory network in diabetic foot ulcer: Bioinformatics and experimental insights

BACKGROUND

Diabetic foot ulcers (DFUs), a serious complication of diabetes, are associated with abnormal extracellular protein (EP) metabolism. The identification of key EPs and their regulatory networks is crucial for the understanding of DFU formation and development of effective treatments. In this study, a large-scale bioinformatics analysis was conducted to identify potential therapeutic targets and experimental validation was performed to ensure the reliability and biological relevance of the findings.

METHODS

Due to the comprehensive profiling of DFU samples provided by the GSE80178 dataset, we initially selected it to derive differentially expressed genes (DEGs) associated with DFU. Subsequently, utilizing the UniProt database and annotated EP list from the Human Protein Atlas annotation database, we screened for extracellular protein-related differentially expressed genes (EP-DEGs) due to their crucial role in the pathogenesis and healing of DFU. We examined EP-DEG pathway enrichment and protein-protein interaction networks, analyzed paired full-thickness skin tissue samples from 24 patients with DFUs and healthy controls, and performed polymerase chain reaction (PCR) experiments to validate candidate genes. Ultimately, we constructed a transcription factor (TF)-microRNA (miRNA)-hub gene co-regulatory network to explore upstream and downstream regulatory connections based on validated DEGs.

RESULTS

Four crucial candidate genes (FMOD, LUM, VCAN, and S100A12) were identified and verified via PCR analysis. The TF-miRNA-hub EP-DEG regulatory network contained the pivotal TFs TRIM28 and STAT3 and the miRNAs hsa-mir-20a-5p, hsa-miR-21, and hsa-miR-203.

CONCLUSION

The findings of this study advance our understanding of the pathology of DFU by defining key roles of specific EPs and elucidating a comprehensive regulatory network. These insights pave the way for novel approaches to improve DFU treatment outcomes.

The Integrated Bioinformatic Approach Reveals the Prognostic Significance of LRP1 Expression in Ovarian Cancer

A hyperactive tumour microenvironment (TME) drives unrestricted cancer cell survival, drug resistance, and metastasis in ovarian carcinoma (OC). However, therapeutic targets within the TME for OC remain elusive, and efficient methods to quantify TME activity are still limited. Herein, we employed an integrated bioinformatics approach to determine which immune-related genes (IRGs) modulate the TME and further assess their potential theragnostic (therapeutic + diagnostic) significance in OC progression. Using a robust approach, we developed a predictive risk model to retrospectively examine the clinicopathological parameters of OC patients from The Cancer Genome Atlas (TCGA) database. The validity of the prognostic model was confirmed with data from the International Cancer Genome Consortium (ICGC) cohort. Our approach identified nine IRGs, AKT2, FGF7, FOS, IL27RA, LRP1, OBP2A, PAEP, PDGFRA, and PI3, that form a prognostic model in OC progression, distinguishing patients with significantly better clinical outcomes in the low-risk group. We validated this model as an independent prognostic indicator and demonstrated enhanced prognostic significance when used alongside clinical nomograms for accurate prediction. Elevated LRP1 expression, which indicates poor prognosis in bladder cancer (BLCA), OC, low-grade gliomas (LGG), and glioblastoma (GBM), was also associated with immune infiltration in several other cancers. Significant correlations with immune checkpoint genes (ICGs) highlight the potential importance of LRP1 as a biomarker and therapeutic target. Furthermore, gene set enrichment analysis highlighted LRP1's involvement in metabolism-related pathways, supporting its prognostic and therapeutic relevance also in BLCA, OC, low-grade gliomas (LGG), GBM, kidney cancer, OC, BLCA, kidney renal clear cell carcinoma (KIRC), stomach adenocarcinoma (STAD), and stomach and oesophageal carcinoma (STES). Our study has generated a novel signature of nine IRGs within the TME across cancers, that could serve as potential prognostic predictors and provide a valuable resource to improve the prognosis of OC.

Identification of a pro-protein synthesis osteosarcoma subtype for predicting prognosis and treatment

Osteosarcoma (OS) is a heterogeneous malignant spindle cell tumor that is aggressive and has a poor prognosis. Although combining surgery and chemotherapy has significantly improved patient outcomes, the prognosis for OS patients with metastatic or recurrent OS has remained unsatisfactory. Therefore, it is imperative to gain a fresh perspective on OS development mechanisms and treatment strategies. After studying single-cell RNA sequencing (scRNA-seq) data in public databases, we identified seven OS subclonal types based on intra-tumor heterogeneity. Subsequently, we constructed a prognostic model based on pro-protein synthesis osteosarcoma (PPS-OS)-associated genes. Correlation analysis showed that the prognostic model performs extremely well in predicting OS patient prognosis. We also demonstrated that the independent risk factors for the prognosis of OS patients were tumor primary site, metastatic status, and risk score. Based on these factors, nomograms were constructed for predicting the 3- and 5-year survival rates. Afterward, the investigation of the tumor immune microenvironment (TIME) revealed the vital roles of γδ T-cell and B-cell activation. Drug sensitivity analysis and immune checkpoint analysis identified drugs that have potential application value in OS. Finally, the jumping translocation breakpoint (JTB) gene was selected for experimental validation. JTB silencing suppressed the proliferation, migration, and invasion of OS cells. Therefore, our research suggests that PPS-OS-related genes facilitate the malignant progression of OS and may be employed as prognostic indicators and therapeutic targets in OS.

Zebrafish myo7aa affects congenital hearing by regulating Rho-GTPase signaling

Introduction

myo7aa, the homolog of the human Usher 1B syndrome pathogenic gene, myo7A, plays an important role in stereociliary development and maintenance, therefore, is critical for hearing and balance. However, the molecular mechanisms that myo7aa regulate hearing and balance still need to be studied.

Methods

In this study, we generated two independent zebrafish myo7aa knockout lines using CRISPR/Cas9 technology. To investigate the effects of myo7aa on hearing, YO-PRO-1 staining and startle response assay were used. To gain insight into the specific molecular mechanisms by which myo7aa affects hearing, transcriptome sequencing and bioinformatics analysis were employed.

Results

Our study showed that hair cells of myo7aa-/- zebrafish can not take up YO-PRO-1 fluorescent dye and are insensitive to acoustic stimulation in myo7aa-/- zebrafish compared to wild type. Genes related to the Rho GTPase signaling pathway, such as arhgap33, dab2ip, and arghef40, are significantly down-regulated in myo7aa-/- zebrafish embryos at 3 dpf. GTP and ATP compensation can partially rescue the hair cell defects in myo7aa knockout zebrafish.

Discussion

Our findings suggest that zebrafish myo7aa affects congenital hearing by regulating Rho GTPase signaling, and loss of myo7aa leads to abnormal Rho GTPase signaling and impairs hair cell function. myo7aa, myo7A, arhgap33, dab2ip, arghef40 and myo7aa-/- fonts in the abstract are italicized. -/- is a superscript format.

Ferroptosis-Associated Extracellular Matrix Remodeling in Radiation-Induced Lung Fibrosis Progression

Background: Radiation-induced lung fibrosis (RILF) is a life-threatening complication of thoracic radiotherapy. Ferroptosis, a recently discovered type of cell death, is believed to contribute to RILF, though the associated mechanisms are unknown. This study aimed to investigate the potential mechanism of ferroptosis in RILF and examine the contribution of different cell types to ferroptosis during RILF progression. Methods: Histopathological changes in RILF lung tissue were assessed through H&E and Masson staining. IHC staining investigated ferroptosis markers (GPX4, ACSL4, NCOA4). Ferroptosis-related genes (FRG) and pathway scores were derived from RILF transcriptome microarray data. The sc-RNAseq analysis detected FRG score dynamics across cell types, validated by IF staining for PDGFR-α and ACSL4. Results: ACSL4 and NCOA4 protein levels were significantly higher and GPX4 lower in IR than control. FRG scores were positively correlated with fibrosis-related pathway scores in the RILF transcriptome data. FRG and ECM scores were concurrently upregulated in myofibroblasts. Enhanced co-staining of PDGFR-α and ACSL4 were observed in the fibrotic areas of RILF lungs. Conclusions: Our research indicated that in RILF, fibroblasts undergoing ferroptosis may release increased levels of ECM, potentially accelerating the progression of lung fibrosis. This finding presents ferroptosis as a potential therapeutic target in RILF.

Crosstalk among proximal tubular cells, macrophages, and fibroblasts in acute kidney injury: single-cell profiling from the perspective of ferroptosis

The link between ferroptosis, a form of cell death mediated by iron and acute kidney injury (AKI) is recently gaining widespread attention. However, the mechanism of the crosstalk between cells in the pathogenesis and progression of acute kidney injury remains unexplored. In our research, we performed a non-negative matrix decomposition (NMF) algorithm on acute kidney injury single-cell RNA sequencing data based specifically focusing in ferroptosis-associated genes. Through a combination with pseudo-time analysis, cell-cell interaction analysis and SCENIC analysis, we discovered that proximal tubular cells, macrophages, and fibroblasts all showed associations with ferroptosis in different pathways and at various time. This involvement influenced cellular functions, enhancing cellular communication and activating multiple transcription factors. In addition, analyzing bulk expression profiles and marker genes of newly defined ferroptosis subtypes of cells, we have identified crucial cell subtypes, including Egr1 + PTC-C1, Jun + PTC-C3, Cxcl2 + Mac-C1 and Egr1 + Fib-C1. All these subtypes which were found in AKI mice kidneys and played significantly distinct roles from those of normal mice. Moreover, we verified the differential expression of Egr1, Jun, and Cxcl2 in the IRI mouse model and acute kidney injury human samples. Finally, our research presented a novel analysis of the crosstalk of proximal tubular cells, macrophages and fibroblasts in acute kidney injury targeting ferroptosis, therefore, contributing to better understanding the acute kidney injury pathogenesis, self-repairment and acute kidney injury-chronic kidney disease (AKI-CKD) progression.

Transcriptomic Analysis of Metastatic Uveal Melanoma and Differences in Male and Female Patients

BACKGROUND/AIM

Uveal melanoma is an ocular malignancy whose prognosis severely worsens following metastasis. In order to improve the understanding of molecular physiology of metastatic uveal melanoma, we identified genes and pathways implicated in metastatic vs non-metastatic uveal melanoma.

PATIENTS AND METHODS

A previously published dataset from Gene Expression Omnibus (GEO) was used to identify differentially expressed genes between metastatic and non-metastatic samples as well as to conduct pathway and perturbagen analyses using Gene Set Enrichment Analysis (GSEA), EnrichR, and iLINCS.

RESULTS

In male metastatic uveal melanoma samples, the gene LOC401052 is significantly down-regulated and FHDC1 is significantly up-regulated compared to non-metastatic male samples. In female samples, no significant differently expressed genes were found. Additionally, we identified many significant up-regulated immune response pathways in male metastatic uveal melanoma, including "T cell activation in immune response". In contrast, many top up-regulated female pathways involve iron metabolism, including "heme biosynthetic process". iLINCS perturbagen analysis identified that both male and female samples have similar discordant activity with growth factor receptors, but only female samples have discordant activity with progesterone receptor agonists.

CONCLUSION

Our results from analyzing genes, pathways, and perturbagens demonstrate differences in metastatic processes between sexes.

CircABHD2 Inhibits Malignant Progression of Endometrial Cancer by Regulating NAD+/NAMPT Metabolism Axis

Circular RNAs (circRNAs) perform important functions in the regulation of diverse physiological and pathological processes. CircABHD2 exhibits down-regulation in both endometrial cancer (EC) cells and tissues, but the biological roles and mechanisms of action in EC are still unclear. This study aims to provide a theoretical basis for the role of circABHD2 in EC and potential targets for individualized precision therapy. Dysregulated circRNAs were identified using RNA sequencing (RNA-Seq) from EC tissues and validated using RT-qPCR. CCK-8, colony formation assay, wound healing assay, transwell assay, cell cycle, and apoptosis assay were used to evaluate the effects of circABHD2 on EC cells. Metabolomics assay and western blot analyses were used to investigate the potential mechanisms of circABHD2. From sequencing of RNA (RNA-Seq) analysis of EC tissues, we obtained 19 dysregulated circRNAs, including 8 upregulated ones and 11 downregulated ones. Using RT-qPCR on 32 EC tissues and 19 normal endometrial tissues, we confirmed that circABHD2 was downregulated in EC tissues. The expression levels of circABHD2 were closely relevant to the International Federation of Gynecology and Obstetrics (FIGO) stage and differentiation degree of EC. Functional experiments demonstrated that overexpression of circABHD2 decreased proliferation, migration, invasion, and promoted cell apoptosis. Un-targeted metabolomic assay revealed 31 differential metabolites in EC cells overexpressing circABHD2. KEGG analysis of differential metabolites indicated that NAD+ is the core metabolite regulated by circABHD2. NAMPT is one key enzyme involved in the synthetic pathway responsible for NAD+. Subsequent experiments confirmed that by inhibiting NAMPT protein expression in EC cells, cirABHD2 can inhibit NAD+ level, suggesting that circABHD2 may inhibit EC by regulating the metabolic axis of NAD+/NAMPT. CircABHD2, a downregulated circRNA in EC cells and tissues, inhibits the malignant progression of EC via the NAD+/NAMPT metabolic axis. This discovery presents a promising diagnostic biomarker and potential therapeutic target for EC.

Giardia intestinalis extracellular vesicles induce changes in gene expression in human intestinal epithelial cells in vitro

Giardiasis is a common waterborne zoonotic disease caused by Giardia intestinalis. Upon infection, Giardia releases excretory and secretory products (ESPs) including secreted proteins (SPs) and extracellular vesicles (EVs). Although the interplay between ESPs and intestinal epithelial cells (IECs) has been previously described, the functions of EVs in these interactions and their differences from those of SPs require further exploration. In the present study, EVs and EV-depleted SPs were isolated from Giardia ESPs. Proteomic analyses of isolated SPs and EVs showed 146 and 91 proteins, respectively. Certain unique and enriched proteins have been identified in SPs and EVs. Transcriptome analysis of Caco-2 cells exposed to EVs showed 96 differentially expressed genes (DEGs), with 56 upregulated and 40 downregulated genes. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA) indicated that Caco-2 genes related to metabolic processes, the HIF-1 signaling pathway, and the cAMP signaling pathway were affected. This study provides new insights into host-parasite interactions, highlighting the potential significance of EVs on IECs during infections.

Species-specific duplicated FMRFaR-like gene A62 regulates spontaneous locomotion in Apolygus lucorum

BACKGROUND

Apolygus lucorum, a major cotton pest, has undergone a significant expansion of the FMRFaR gene within the GPCR superfamily, resulting in two classes of GPCR, namely FMRFaR (A54-55) and newly duplicated FMRFaR-like (A56-62). Notably, FMRFaR-like genes, particularly A62, show enhanced expression in the legs and wings of adults, indicating their potential role in locomotion. Employing A62 as a representative of FMRFaR-like, our study investigates the influence of FMRFa, FMRFaR, and FMRFaR-like on locomotion and development of A. lucorum.

RESULTS

FMRFaR and FMRFa exhibit comparable temporal and tissue expression patterns, whereas the FMRFaR-like genes within A. lucorum exhibit completely distinct evolutionary and expression patterns compared to classical FMRFaR. RNA interference (RNAi) experiments revealed that suppressing FMRFa expression results in complete lethality in A. lucorum, but neither FMRFaR nor A62 exhibit the same effect after RNAi. Suppressing the expression of FMRFa only decreases the expression of the A54 gene simultaneously, suggesting that A54 may function as a classical FMRFaR activated by FMRFa. RNAi of A62 leads to wing malformation and a significant reduction in spontaneous movement behavior in A. lucorum. Further transcriptomic analysis revealed that A62 affects the A. lucorum's movement behavior through energy metabolism pathways and motor protein pathways.

CONCLUSION

Our study unveils the unique and complex roles of FMRFa and its receptor in A. lucorum. These findings provide valuable insights into potential targets for pest control strategies aimed at managing A. lucorum populations in cotton fields. © 2024 Society of Chemical Industry.

Pterostilbene exerts anti-lung squamous cell carcinoma function by suppressing the level of KANK3

Early detection of lung squamous cell carcinoma (LUSC) has a significant impact on clinical outcomes, and pterostilbene (PT) is a natural compound with promising anti-oncogenic activities. This study aimed to identify potential LUSC biomarkers through a series of bioinformatic analyses and clinical verification and explored the interaction between PT and selected biomarkers during the treatment of LUSC. The analysis of the expression profile of the clinical samples of LUSC was performed to identify dysexpressed genes (DEGs) and validated by IHC. The role of KANK3 in the anti-LUSC effects of PT was assessed with a series of in vitro and in vivo assays. 4335 DEGs were identified, including 1851 upregulated genes and 2484 downregulated genes. Survival analysis showed that KANK3 was significantly higher in patients with LUSC with an advanced tumor stage. In in vitro assays, PT suppressed cell viability, induced apoptosis, and inhibited migration and invasion in LUSC cell lines, which was associated with downregulation of KANK3. After the reinduction of the KANK3 level in LUSC cells, the anti-LUSC function of PT was impaired. In mice model, reinduction of KANK3 increased tumor growth and metastasis even under the treatment of PT. The findings outlined in the current study indicated that PT exerted anti-LUSC function in a KANK3 inhibition-dependent manner.

The prognostic and clinical value of genes associate with immunity and amino acid Metabolism in Lung Adenocarcinoma

Background

Lung adenocarcinoma (LUAD) is the commonest subtype of primary lung cancer. A comprehensive analysis of the association of immunity with amino acid metabolism in LUAD is critical for understanding the disease.

Methods

The present study examined LUAD and noncancerous cases from the TCGA database. Differentially expressed genes (DEGs) between LUAD and noncancerous tissues were detected by analyzing processed expression profiles. We cross-referenced the up-regulated DEGs with Immune and Amino Acid Metabolism-related genes (I&AAMGs), resulting in Immune and Amino Acid Metabolism related differentially expressed genes (IAAAMRDEGs). The STRING database was employed to analyze PPI on IAAAMRDEGs, obtaining excavated hub genes, whose biological processes, molecular functions and cellular components were examined with GO/KEGG. Potential mechanisms related to LUAD were investigated by GSEA and GSVA. A prognostic model was built by LASSO-COX analysis, taking into consideration risk scores and prognostic factors to determine biomarkers affecting LUAD occurrence and prognosis.

Results

Totally 377 genes were detected at the intersection of upregulated DEGs and I&AAMGs. Analysis of PPI on these 377 IAAAMRDEGs yielded 17 hub genes. A LASSO regression analysis was utilized to assess the prognostic values of the 17 hub genes. Validation using the combined dataset confirmed 4 genes, e.g., polo-like kinase (PLK1), Ribonucleotide Reductase Subunit M2 (RRM2), Thyroid Hormone Receptor Interactor 13 (TRIP13), and Hyaluronan-Mediated Motility Receptor (HHMR). The model's accuracy was further assessed by ROC curve analysis and the COX model. In addition, immunohistochemical staining obtained from the HPA database, revealed enhanced PLK1 expression in LUAD samples.

Conclusion

LUAD pathogenesis is highly associated with immunity and amino acid metabolism. The PLK1, RRM2, TRIP13, and HMMR genes have prognostic values for LUAD. PLK1 upregulation in LUAD might be involved in tumorigenesis by modulating the cell cycle and represents a potential prognostic factor in clinic.

Comprehensive Analysis of angiogenesis associated genes and tumor microenvironment infiltration characterization in cervical cancer

Background

Cervical cancer is among the most prevalent malignancies worldwide. This study explores the relationships between angiogenesis-related genes (ARGs) and immune infiltration, and assesses their implications for the prognosis and treatment of cervical cancer. Additionally, it develops a diagnostic model based on angiogenesis-related differentially expressed genes (ARDEGs).

Methods

We systematically evaluated 15 ARDEGs using Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Set Enrichment Analysis (GSEA), and Gene Set Variation Analysis (GSVA). Immune cell infiltration was assessed using a single-sample gene-set enrichment analysis (ssGSEA) algorithm. We then constructed a diagnostic model for ARDEGs using Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis and evaluated the diagnostic value of this model and the hub genes in predicting clinical outcomes and immunotherapy responses in cervical cancer.

Results

A set of ARDEGs was identified from the Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and UCSC Xena database. We performed KEGG, GO, and GSEA analyses on these genes, revealing significant involvement in cell proliferation, differentiation, and apoptosis. The ARDEGs diagnostic model, constructed using LASSO regression analysis, showed high predictive accuracy in cervical cancer patients. We developed a reliable nomogram and decision curve analysis to evaluate the clinical utility of the ARDEG diagnostic model. The 15 ARDEGs in the model were associated with clinicopathological features, prognosis, and immune cell infiltration. Notably, ITGA5 expression and the abundance of immune cell infiltration (specifically mast cell activation) were highly correlated.

Conclusion

This study identifies the prognostic characteristics of ARGs in cervical cancer patients, elucidating aspects of the tumor microenvironment. It enhances the predictive accuracy of immunotherapy outcomes and establishes new strategies for immunotherapeutic interventions.

Coordinated inflammation and immune response transcriptional regulation in breast cancer molecular subtypes

Breast cancer, characterized by its complexity and diversity, presents significant challenges in understanding its underlying biology. In this study, we employed gene co-expression network analysis to investigate the gene composition and functional patterns in breast cancer subtypes and normal breast tissue. Our objective was to elucidate the detailed immunological features distinguishing these tumors at the transcriptional level and to explore their implications for diagnosis and treatment. The analysis identified nine distinct gene module clusters, each representing unique transcriptional signatures within breast cancer subtypes and normal tissue. Interestingly, while some clusters exhibited high similarity in gene composition between normal tissue and certain subtypes, others showed lower similarity and shared traits. These clusters provided insights into the immune responses within breast cancer subtypes, revealing diverse immunological functions, including innate and adaptive immune responses. Our findings contribute to a deeper understanding of the molecular mechanisms underlying breast cancer subtypes and highlight their unique characteristics. The immunological signatures identified in this study hold potential implications for diagnostic and therapeutic strategies. Additionally, the network-based approach introduced herein presents a valuable framework for understanding the complexities of other diseases and elucidating their underlying biology.