Immune-related Functions Research Articles

Comprehensive analysis of the lncRNAs, mRNAs, and miRNAs implicated in the immune response of Pinctada fucata martensii to Vibrio parahaemolyticus

Non-coding RNAs (ncRNAs) have been implicated in a variety of biological processes. However, most ncRNAs are of unknown function and are as-yet unannotated. The immune-related functions of ncRNAs in the pearl oyster Pinctada fucata martensii were explored based on transcriptomic differences in the expression levels of long non-coding RNAs (lncRNAs), microRNAs (miRNAs), and messenger RNAs (mRNAs) in the hemocytes of P.f. martensii after challenge by the pathogenic bacterium Vibrio parahaemolyticus. Across the challenged and control pearl oysters, 144 miRNAs and 14,571 lncRNAs were identified. In total, 13,375 ncRNAs were differentially expressed between the challenged and control pearl oysters; in the challenged pearl oysters as compared to the controls, 15 miRNAs and 5147 lncRNAs were upregulated, while 51 miRNAs and 8162 lncRNAs were downregulated. The sequencing results were validated using quantitative real-time polymerase chain reaction (qRT-PCR) analysis. GO and KEGG pathway analysis showed that genes targeted by the differentially expressed ncRNAs were associated with the vascular endothelial growth factor (VEGF) signaling pathway and the nuclear factor kappa-B (NF-κB) signaling pathway. An lncRNA-mRNA-miRNA network that was developed based on the transcriptomic results of this study suggested that lncRNAs may compete with miRNAs for mRNA binding sites. This study may provide a useful framework for the detection of additional novel ncRNAs, as well as new insights into the pathogenic mechanisms underlying the response of P.f. martensii to V. parahaemolyticus.

Extracellular vesicles from Listeria monocytogenes-infected dendritic cells alert the innate immune response.

Communication through cell-cell contacts and extracellular vesicles (EVs) enables immune cells to coordinate their responses against diverse types of pathogens. The function exerted by EVs in this context depends on the proteins and nucleic acids loaded into EVs, which elicit specific responses involved in the resolution of infection. Several mechanisms control protein and nucleic acid loading into EVs; in this regard, acetylation has been described as a mechanism of cellular retention during protein sorting to exosomes. HDAC6 is a deacetylase involved in the control of cytoskeleton trafficking, organelle polarity and cell migration, defense against Listeria monocytogenes (Lm) infection and other immune related functions. Here, we show that the protein content of dendritic cells (DCs) and their secreted EVs (DEVs) vary during Lm infection, is enriched in proteins related to antiviral functions compared to non-infected cells and depends on HDAC6 expression. Analyses of the post-translational modifications revealed an alteration of the acetylation and ubiquitination profiles upon Lm infection both in DC lysates and DEVs. Functionally, EVs derived from infected DCs upregulate anti-pathogenic genes (e.g. inflammatory cytokines) in recipient immature DCs, which translated into protection from subsequent infection with vaccinia virus. Interestingly, absence of Listeriolysin O in Lm prevents DEVs from inducing this anti-viral state. In summary, these data underscore a new mechanism of communication between bacteria-infected DC during infection as they alert neighboring, uninfected DCs to promote antiviral responses.

Construction of a 5-methylcytosine-Related Molecular Signature to Inform the Prognosis and Immunotherapy of Lung Squamous Cell Carcinoma

ABSTRACT Background Methylation of cytosine residues resulting in 5-methylcytosine (5-mC) is an important epigenetic modification associated with tumorigenesis. The present study explored the relationship between methylation, prognosis, and immunotherapy of patients suffering from lung squamous cell carcinoma (LUSC). Methods RNA sequencing data and corresponding clinical information were downloaded, and preprocessed, and unsupervised consistent cluster analysis was used to identify 5-mC-related clusters and gene clusters. 5-mC scores were calculated using principal component analysis, and a Boruta algorithm was used to evaluate the relationship between tumor mutation burden (TMB), immune checkpoint inhibitor response, and prognosis of individual LUSC patients. Results : Two 5-mC clusters and three gene clusters with different prognoses were identified. Patients with higher 5-mC scores showed worse prognoses, which was confirmed in multiple cohorts. Some immune-related biological functions and pathways were enriched in the high-5-mC score subtype. Conclusion The 5-mC score is a potential biomarker independent of TMB, which can be a decisive factor regarding immune treatment responses. Further, patients with low 5-mC scores may respond better to immunotherapy. The 5-mC score can thus be used as a potential biomarker for the prognosis of LUSC patients and their response to immunotherapy.

Cuproptosis-related lncRNA predict prognosis and immune response of lung adenocarcinoma

BackgroundLung adenocarcinoma (LUAD) accounts for 50% of lung cancers, with high mortality and poor prognosis. Long non-coding RNA (lncRNA) plays a vital role in the progression of tumors. Cuproptosis is a newly discovered form of cell death that is highly investigated. Therefore, in the present study, we aimed to investigate the role of cuproptosis-related lncRNA signature in clinical prognosis prediction and immunotherapy and the relationship with drug sensitivity.Material and methodsGenomic and clinical data were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, and cuproptosis-related genes were obtained from cuproptosis-related studies. The prognostic signature was constructed by co-expression analysis and Cox regression analysis. Patients were divided into high and low risk groups, and then, a further series of model validations were carried out to assess the prognostic value of the signature. Subsequently, lncRNAs were analyzed for gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes Enrichment (KEGG), immune-related functions, and tumor mutation burden (TMB). Finally, we used tumor immune dysfunction and exclusion (TIDE) algorithms on immune escape and immunotherapy of cuproptosis-related lncRNAs, thereby identifying its sensitivity toward potential drugs for LUAD.ResultsA total of 16 cuproptosis-related lncRNAs were obtained, and a prognostic signature was developed. We found that high-risk patients had worse overall survival (OS) and progression-free survival (PFS) and higher mortality. Independent prognostic analyses, ROC, C-index, and nomogram showed that the cuproptosis-related lncRNAs can accurately predict the prognosis of patients. The nomogram and heatmap showed a distinct distribution of the high- and low-risk cuproptosis-related lncRNAs. Enrichment analysis showed that the biological functions of lncRNAs are associated with tumor development. We also found that immune-related functions, such as antiviral activity, were suppressed in high-risk patients who had mutations in oncogenes. OS was poorer in patients with high TMB. TIDE algorithms showed that high-risk patients have a greater potential for immune escape and less effective immunotherapy.ConclusionTo conclude, the 16 cuproptosis-related lncRNAs can accurately predict the prognosis of patients with LUAD and may provide new insights into clinical applications and immunotherapy.

Metformin keeps CD8+ T cells active and moving in NASH-HCC immunotherapy

Metformin keeps CD8+ T cells active and moving in NASH-HCC immunotherapy

Determination of a prediction model for therapeutic response and prognosis based on chemokine signaling-related genes in stage I-III lung squamous cell carcinoma.

Background: The chemokine signaling pathway plays an essential role in the development, progression, and immune surveillance of lung squamous cell carcinoma (LUSC). Our study aimed to systematically analyze chemokine signaling-related genes (CSRGs) in LUSC patients with stage I–III disease and develop a prediction model to predict the prognosis and therapeutic response. Methods: A total of 610 LUSC patients with stage I–III disease from three independent cohorts were included in our study. Least absolute shrinkage and selection operator (LASSO) and stepwise multivariate Cox regression analyses were used to develop a CSRG-related signature. GSVA and GSEA were performed to identify potential biological pathways. The ESTIMATE algorithm, ssGSEA method, and CIBERSORT analyses were applied to explore the correlation between the CSRG signature and the tumor immune microenvironment. The TCIA database and pRRophetic algorithm were utilized to predict responses to immunochemotherapy and targeted therapy. Results: A signature based on three CSRGs (CCL15, CXCL7, and VAV2) was developed in the TCGA training set and validated in the TCGA testing set and GEO external validation sets. A Kaplan–Meier survival analysis revealed that patients in the high-risk group had significantly shorter survival than those in the low-risk group. A nomogram combined with clinical parameters was established for clinical OS prediction. The calibration and DCA curves confirmed that the prognostic nomogram had good discrimination and accuracy. An immune cell landscape analysis demonstrated that immune score and immune-related functions were abundant in the high-risk group. Interestingly, the proportion of CD8 T-cells was higher in the low-risk group than in the high-risk group. Immunotherapy response prediction indicated that patients in the high-risk group had a better response to CTLA-4 inhibitors. We also found that patients in the low-risk group were more sensitive to first-line chemotherapeutic treatment and EGFR tyrosine kinase inhibitors. In addition, the expression of genes in the CSRG signature was validated by qRT‒PCR in clinical tumor specimens. Conclusion: In the present study, we developed a CSRG-related signature that could predict the prognosis and sensitivity to immunochemotherapy and targeted therapy in LUSC patients with stage I–III disease. Our study provides an insight into the multifaceted role of the chemokine signaling pathway in LUSC and may help clinicians implement optimal individualized treatment for patients.

Serum differential proteomic profiling of patients with isolated methylmalonic acidemia by iTRAQ.

Isolated methylmalonic acidemia (MMA) is an inherited organic acid metabolic disorder in an autosomal recessive manner, caused by mutations in the methylmalonyl coenzyme A mutase gene, and the isolated MMA patients often suffer from multi-organ damage. The present study aimed to profile the differential proteome of serum between isolated MAA patients and healthy control. The in vivo proteome of isolated MAA patients and healthy subjects was detected by an isobaric tag for relative and absolute quantitation (iTRAQ). A total of 94 differentially expressed proteins (DEPs) were identified between MMA patients and healthy control, including 58 upregulated and 36 downregulated DEPs in MMA patients. Among them, the most significantly upregulated proteins were CRP and immunoglobulins, and the top five most significantly downregulated proteins were all different types of immunoglobulins in MMA patients. GO analysis showed that these DEPs were mainly enriched in immune-related function and membrane protein-related function. KEGG revealed that these DEPs were mainly enriched in lysosome and cholesterol metabolism pathways. Also, these DEPs were predicted to contribute to lipid metabolic diseases. We addressed the proteomes of isolated MMA patients and identified DEPs. Our study expands our current understanding of MMA, and the DEPs could be valuable for designing alternative therapies to alleviate MMA symptoms.

The whole blood transcriptional regulation landscape in 465 COVID-19 infected samples from Japan COVID-19 Task Force

Coronavirus disease 2019 (COVID-19) is a recently-emerged infectious disease that has caused millions of deaths, where comprehensive understanding of disease mechanisms is still unestablished. In particular, studies of gene expression dynamics and regulation landscape in COVID-19 infected individuals are limited. Here, we report on a thorough analysis of whole blood RNA-seq data from 465 genotyped samples from the Japan COVID-19 Task Force, including 359 severe and 106 non-severe COVID-19 cases. We discover 1169 putative causal expression quantitative trait loci (eQTLs) including 34 possible colocalizations with biobank fine-mapping results of hematopoietic traits in a Japanese population, 1549 putative causal splice QTLs (sQTLs; e.g. two independent sQTLs at TOR1AIP1), as well as biologically interpretable trans-eQTL examples (e.g., REST and STING1), all fine-mapped at single variant resolution. We perform differential gene expression analysis to elucidate 198 genes with increased expression in severe COVID-19 cases and enriched for innate immune-related functions. Finally, we evaluate the limited but non-zero effect of COVID-19 phenotype on eQTL discovery, and highlight the presence of COVID-19 severity-interaction eQTLs (ieQTLs; e.g., CLEC4C and MYBL2). Our study provides a comprehensive catalog of whole blood regulatory variants in Japanese, as well as a reference for transcriptional landscapes in response to COVID-19 infection.

Identification of an immune-related gene signature as a prognostic target and the immune microenvironment for adrenocortical carcinoma.

BackgroundAdrenocortical carcinoma (ACC) is a rare endocrine malignancy. Even with complete tumor resection and adjuvant therapies, the prognosis of patients with ACC remains unsatisfactory. In the microtumor environment, the impact of a disordered immune system and abnormal immune responses is enormous. To improve treatment, novel prognostic predictors and treatment targets for ACC need to be identified. Hence, credible prognostic biomarkers of immune‐associated genes (IRGs) should be explored and developed.Material and methodsWe downloaded RNA‐sequencing data and clinical data from The Cancer Genome Atlas (TCGA) data set, Genotype‐Tissue Expression data set, and Gene Expression Omnibus data set. Gene set enrichment analysis (GSEA) was applied to reveal the potential functions of differentially expressed genes.ResultsGSEA indicated an association between ACC and immune‐related functions. We obtained 332 IRGs and constructed a prognostic signature on the strength of 3 IRGs (INHBA, HELLS, and HDAC4) in the training cohort. The high‐risk group had significantly poorer overall survival than the low‐risk group (p < .001). Multivariate Cox regression was performed with the signature as an independent prognostic indicator for ACC. The testing cohort and the entire TCGA ACC cohort were utilized to validate these findings. Moreover, external validation was conducted in the GSE10927 and GSE19750 cohorts. The tumor‐infiltrating immune cells analysis indicated that the quantity of T cells, natural killer cells, macrophage cells, myeloid dendritic cells, and mast cells in the immune microenvironment differed between the low‐risk and high‐risk groups.ConclusionOur three‐IRG prognostic signature and the three IRGs can be used as prognostic indicators and potential immunotherapeutic targets for ACC. Inhibitors of the three novel IRGs might activate immune cells and play a synergistic role in combination therapy with immunotherapy for ACC in the future.

A ubiquitin-related gene signature for predicting prognosis and constructing molecular subtypes in osteosarcoma.

Background: Ubiquitination is medicated by three classes of enzymes and has been proven to involve in multiple cancer biological processes. Moreover, dysregulation of ubiquitination has received a growing body of attention in osteosarcoma (OS) tumorigenesis and treatment. Therefore, our study aimed to identify a ubiquitin-related gene signature for predicting prognosis and immune landscape and constructing OS molecular subtypes. Methods: Therapeutically Applicable Research to Generate Effective Treatments (TARGET) was regarded as the training set through univariate Cox regression, Lasso Cox regression, and multivariate Cox regression. The GSE21257 and GSE39055 served as the validation set to verify the predictive value of the signature. CIBERSORT was performed to show immune infiltration and the immune microenvironment. The NMF algorithm was used to construct OS molecular subtypes. Results: In this study, we developed a ubiquitin-related gene signature including seven genes (UBE2L3, CORO6, DCAF8, DNAI1, FBXL5, UHRF2, and WDR53), and the gene signature had a good performance in predicting prognosis for OS patients (AUC values at 1/3/5 years were 0.957, 0.890, and 0.919). Multivariate Cox regression indicated that the risk score model and prognosis stage were also independent prognostic prediction factors. Moreover, analyses of immune cells and immune-related functions showed a significant difference in different risk score groups and the three clusters. The drug sensitivity suggested that IC50 of proteasome inhibitor (MG-132) showed a notable significance between the risk score groups (p < 0.05). Through the NMF algorithm, we obtained the three clusters, and cluster 3 showed better survival outcomes. The expression of ubiquitin-related genes (CORO6, UBE2L3, FBXL5, DNAI1, and DCAF8) showed an obvious significance in normal and osteosarcoma tissues. Conclusion: We developed a novel ubiquitin-related gene signature which showed better predictive prognostic ability for OS and provided additional information on chemotherapy and immunotherapy. The OS molecular subtypes would also give a useful guide for individualized therapy.

SIRGs score may be a predictor of prognosis and immunotherapy response for esophagogastric junction adenocarcinoma.

BackgroundEsophagogastric junction adenocarcinoma (EGJA) is a special malignant tumor with unknown biological behavior. PD-1 checkpoint inhibitors have been recommended as first-line treatment for advanced EGJA patients. However, the biomarkers for predicting immunotherapy response remain controversial.MethodsWe identified stromal immune-related genes (SIRGs) by ESTIMATE from the TCGA-EGJA dataset and constructed a signature score. In addition, survival analysis was performed in both the TCGA cohort and GEO cohort. Subsequently, we explored the differences in tumor-infiltrating immune cells, immune subtypes, immune-related functions, tumor mutation burden (TMB), immune checkpoint gene expression, immunophenoscore (IPS) between the high SIRGs score and low SIRGs score groups. Finally, two validation cohorts of patients who had accepted immunotherapy was used to verify the value of SIRGs score in predicting immunotherapy response.ResultsEight of the SIRGs were selected by LASSO regression to construct a signature score (SIRGs score). Univariate and multivariate analyses in the TCGA and GEO cohort suggested that SIRGs score was an independent risk factor for the overall survival (OS) and it could increase the accuracy of clinical prediction models for survival. However, in the high SIRGs score group, patients had more immune cell infiltration, more active immune-related functions, higher immune checkpoint gene expression and higher IPS-PD1 and IPS-PD1-CTLA4 scores, which indicate a better response to immunotherapy. The external validation illustrated that high SIRGs score was significantly associated with immunotherapy response and immune checkpoint inhibitors (ICIs) can improve OS in patients with high SIRGs score.ConclusionThe SIRGs score may be a predictor of the prognosis and immune-therapy response for esophagogastric junction adenocarcinoma.

A novel prognostic 7-methylguanosine signature reflects immune microenvironment and alternative splicing in glioma based on multi-omics analysis.

Glioma is the most common type of central nervous system tumor with increasing incidence. 7-methylguanosine (m7G) is one of the diverse RNA modifications that is known to regulate RNA metabolism and its dysregulation was associated with various cancers. However, the expression pattern of m7G regulators and their roles in regulating tumor immune microenvironments (TIMEs) as well as alternative splicing events (ASEs) in glioma has not been reported. In this study, we showed that m7G regulators displayed a close correlation with each other and most of them were differentially expressed between normal and glioma tissues. Two m7G signatures were then constructed to predict the overall survival of both GBM and LGG patients with moderate predictive performance. The risk score calculated from the regression coefficient and expression level of signature genes was proved to be an independent prognostic factor for patients with LGG, thus, a nomogram was established on the risk score and other independent clinical parameters to predict the survival probability of LGG patients. We also investigated the correlation of m7G signatures with TIMEs in terms of immune scores, expression levels of HLA and immune checkpoint genes, immune cell composition, and immune-related functions. While exploring the correlation between signature genes and the ASEs in glioma, we found that EIF4E1B was a key regulator and might play dual roles depending on glioma grade. By incorporating spatial transcriptomic data, we found a cluster of cells featured by high expression of PTN exhibited the highest m7G score and may communicate with adjacent cancer cells via SPP1 and PTN signaling pathways. In conclusion, our work brought novel insights into the roles of m7G modification in TIMEs and ASEs in glioma, suggesting that evaluation of m7G in glioma could predict prognosis. Moreover, our data suggested that blocking SPP1 and PTN pathways might be a strategy for combating glioma.

Development and Validation of an ADME-Related Gene Signature for Survival, Treatment Outcome and Immune Cell Infiltration in Head and Neck Squamous Cell Carcinoma.

ADME genes are a set of genes which are involved in drug absorption, distribution, metabolism, and excretion (ADME). However, prognostic value and function of ADME genes in head and neck squamous cell carcinoma (HNSCC) remain largely unclear. In this study, we established an ADME-related prognostic model through the least absolute shrinkage and selection operator (LASSO) analysis in the Cancer Genome Atla (TCGA) training cohort and its robustness was validated by TCGA internal validation cohort and a Gene Expression Omnibus (GEO) external cohort. The 14-gene signature stratified patients into high- or low-risk groups. Patients with high-risk scores exhibited significantly poorer overall survival (OS) and disease-free survival (DFS) than those with low-risk scores. Receiver operating characteristic (ROC) curve analysis was used to confirm the signature’s predictive efficacy for OS and DFS. Furthermore, gene ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway analyses showed that immune-related functions and pathways were enriched, such as lymphocyte activation, leukocyte cell-cell adhesion and T-helper cell differentiation. The Cell-type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT) and other analyses revealed that immune cell (especially B cell and T cell) infiltration levels were significantly higher in the low-risk group. Moreover, patients with low-risk scores were significantly associated with immunotherapy and chemotherapy treatment benefit. In conclusion, we constructed a novel ADME-related prognostic and therapeutic biomarker associated with immune cell infiltration of HNSCC patients.

A New Crustin Gene Homolog SpCrus8 Identified in Scylla paramamosain Exerting In Vivo Protection Through Opsonization and Immunomodulation.

Crustins are the most abundant class of antimicrobial peptides in crustaceans and are essential for protecting animals from infection. Among them, type II crustins usually exhibit potent antimicrobial activity. Interestingly, in this study, a newly identified type II crustin gene homolog (named SpCrus8) from mud crab Scylla paramamosain, the recombinant proteins of which (rSpCrus8 and rTrx-SpCrus8) showed no obvious antibacterial effects, but could significantly reduce the bacterial load in crab hemolymph and improve the survival rate of crabs infected with Vibrio alginolyticus. The immune-related function of SpCrus8 and the underlying mechanism deserve further investigation. It was found that the SpCrus8 gene was widely distributed in various tissues of adult crabs. In the hepatopancreas of crabs infected with V. alginolyticus or Staphylococcus aureus, transcripts of the SpCrus8 gene were remarkably induced, indicating that the SpCrus8 gene was involved in the immune response to bacterial infection in vivo. In addition, rSpCrus8 and rTrx-SpCrus8 had strong binding activity not only to microbial surface components (lipopolysaccharide, lipoteichoic acid, peptidoglycan, and glucan), but also to the tested bacteria (S. aureus, Pseudomonas aeruginosa and V. alginolyticus). Notably, rSpCrus8 and rTrx-SpCrus8 could significantly promote hemocyte phagocytosis. After rSpCrus8 and rTrx-SpCrus8 treatment, a large number of fluorescent microspheres were observed to aggregate into clusters and be phagocytosed by multiple hemocytes, while hemocytes in the control group phagocytosed only individual microspheres, indicating that SpCrus8 played an important role in opsonization. When the SpCrus8 gene was knocked down, the expression levels of the key phagocytosis-related genes SpRab5 and SpRab7 were significantly downregulated, as well as the IMD signaling pathway genes SpIKKβ and SpRelish, and another crustin gene SpCrus5. Correspondingly, all the SpIKKβ, SpRelish and SpCrus5 genes were significantly upregulated after rSpCrus8 treatment, suggesting that SpCrus8 might be involved in the immunomodulation of S. paramamosain. Taken together, this study revealed the immune-related functions of the SpCrus8 gene in opsonization and regulation, which will help us further understand the role of the crustin gene family in the immune system of mud crabs and provide new insights into the function of type II crutins.

Identification of Survival Risk and Immune-Related Characteristics of Kidney Renal Clear Cell Carcinoma

Background Immunity exerts momentous functions in the progression and treatment of kidney renal clear cell carcinoma (KIRC). A better understanding of the relationship between KIRC and immunity may make a great contribution to evaluating the prognosis and immune-related therapeutic response of KIRC. Methods A series of information such as RNA sequence, clinical data, and tumor mutation burden (TMB) of KIRC patients were downloaded through The Cancer Genome Atlas (TCGA). Next, combining the survival information and gene expression data of TCGA and Gene Expression Omnibus (GEO), we established an immune gene-related prognosis model (IGRPM) and analyzed it. Then we constructed a nomogram which was convenient for clinicians to judge the prognosis of KIRC. Last but not the least, the expressions of some genes used to construct IGRPM in early KIRC, and adjacent normal tissues were verified through real-time fluorescence quantitative polymerase chain reaction (RT-qPCR). Perl (strawberry-perl-5.30.0.1-64bit), R software (4.0.3), and GraphPad Prism 7 were used to process the relevant data. Results The single-sample gene set enrichment analysis (ssGSEA) showed that there were significant differences in StromalScore, ImmuneScore, ESTIMATEScore, TumorPurity, 22 kinds of human immune cells infiltration, and HLA genes expression between high immunity group (Immunity_H) and low immunity group (Immunity_L). The Immunity_H expressed more immune-related genes and enriched more immune-related functions than the Immunity_L. In addition, compared with the low-risk group, the high-risk group had worse survival outcome and higher TMB. Combining IGRPM-based risk characteristic and TMB, we found that low-TMB + low-risk was the most beneficial to the survival outcome of KIRC patients. The risk characteristic based on IGRPM could be used as an independent prognostic factor for KIRC, and the nomogram constructed for evaluating the prognosis of KIRC showed excellent predictive potential. The RT-qPCR results suggested that not all the genes used to construct IGRPM showed differential expression in early KIRC compared with adjacent normal tissues, but all these genes had significant influence on the prognosis of KIRC. Conclusion These comprehensive immune assessments and survival predictions, integrating multiple aspects of data and clinical information, can provide additional value to the current Tumor Node Metastasis staging system for risk stratification of KIRC and may facilitate the development of KIRC immunotherapy.

Characteristics of Fatty Acid Metabolism in Lung Adenocarcinoma to Guide Clinical Treatment.

BackgroundLung adenocarcinoma (LUAD) has a very high morbidity and mortality rate, and its pathogenesis and treatment are still in the exploratory stage. Fatty acid metabolism plays a significant role in tumorigenesis, progression, and immune regulation. However, the gene expression of fatty acid metabolism in patients with LUAD and its relationship with prognosis remain unclear.MethodsWe collected 309 fatty acid metabolism-related genes, established a LUAD risk model based on The Cancer Genome Atlas (TCGA) using Least Absolute Shrinkage Selection Operator (LASSO) regression analysis, and divided LUAD patients into high-risk and low-risk groups, which were further validated using the Gene Expression Omnibus (GEO) database. The nomogram, principal component analysis (PCA), and receiver operating characteristic (ROC) curves showed that the model had the best predictive performance. The ROC curves and calibration plots confirmed that the nomogram had good predictive power. We further analyzed the differences in clinical characteristics, immune cell infiltration, immune-related functions, chemotherapy drug sensitivity, and immunotherapy efficacy between the high-risk and low-risk groups. We also analyzed the enrichment pathways and protein–protein interaction (PPI) networks of different genes in the high-risk and low-risk groups to screen for target genes and further explored the correlation between target genes and differences in survival prognosis, clinical characteristics, gene mutations, and immune cells.ResultsRisk score and staging are independent prognostic factors for patients with LUAD. The high-risk group had lower immune cell infiltration, was more sensitive to chemotherapeutic agents, and had a poorer survival prognosis. We also obtained three pivotal genes with poor survival prognosis in the high expression group, which were strongly associated with clinical symptoms and immune cells.ConclusionRisk score and staging are independent prognostic factors for patients with LUAD. The high-risk group had lower immune cell infiltration, was more sensitive to chemotherapeutic agents, and had a poorer survival prognosis. We also obtained three survival prognosis-associated target genes that are closely associated with clinical symptoms and immune cells and may be potential targets for immune-targeted therapy in LUAD.

Platelet Toll-Like-Receptor-2 and -4 Mediate Different Immune-Related Responses to Bacterial Ligands.

Background Like immune cells, platelets express toll-like receptors (TLRs) on their surface membrane. TLR2 and TLR4 are able to recognize bacterial antigens and have the potential to influence hemostatic functions and classical intracellular signaling pathways. This study investigated the role of TLR2 and TLR4 for immune-related functions in human platelets. Materials and Methods Washed platelets and neutrophils were prepared from fresh human peripheral blood. Basal-, Pam3CSK4- (as TLR2 agonist) and Lipopolysaccharides (LPS; as TLR4 agonist) -induced CD62P expression, fibrinogen binding and TLR2 or TLR4 expression, intracellular reactive oxygen species (ROS) production in H 2 DCFDA-loaded platelets and uptake of fluorescence-labeled TLR ligands, and fluorophore-conjugated fibrinogen were evaluated by flow cytometry. Analysis of platelet–neutrophil complexes was performed after coincubation of washed platelets and neutrophils in the presence and absence of TLR2 or TLR4 agonists on poly-L-lysine coated surfaces, followed by immunostaining and immunofluorescence imaging. Results Pam3CSK4 rapidly and transiently increased TLR2 and TLR4 expression. Over the course of 30 minutes after activation with Pam3CSK4 and LPS, the expression of both receptors decreased. Pam3CSK4-stimulated intracellular ROS production and the uptake of TLR ligands or fibrinogen much stronger than LPS. Besides, TLR4 activation led to a significant increase of platelet–neutrophil contacts. Conclusion Stimulation leads to rapid mobilization of TLR2 or TLR4 to the platelet surface, presumably followed by receptor internalization along with bound TLR ligands. After activation, platelet TLR2 and TLR4 mediate different immune-related reactions. In particular, TLR2 induces intracellular responses in platelets, whereas TLR4 initiates interactions with other immune cells such as neutrophils.

A potential EBV-related classifier is associated with the efficacy of immunotherapy in gastric cancer.

BackgroundGastric cancer (GC) is a global health problem. As a complicated heterogeneous disease, The Cancer Genome Atlas (TCGA) Research Network recognized four subtypes of GC, including Epstein-Barr virus (EBV)-positive GC (EBVaGC), which accounts for approximately 9% of all GC cases. The response to immunotherapy in GC is limited, and whether EBV status is a predictor of immunotherapy remains controversial.MethodsThe differential gene expression analysis was utilized to compare the gene expression between the EBV-positive group and the EBV-negative group in the TCGA-Stomach Adenocarcinoma (TCGA-STAD) cohort. Weighted gene co-expression network analysis (WGCNA), protein-protein interaction (PPI) network analysis, and gene functional enrichment analysis were used to investigate the most pivotal hub genes and their roles. The “Estimation of Stromal and Immune cells in Malignant Tumours using Expression data” (ESTIMATE) and CIBERSORT algorithms were performed to infer the immune compositions of tissue samples. Furthermore, quantitative real-time polymerase chain reaction (RT-qPCR) and survival analysis were used to validate the expression and prognosis of these hub genes in Sun Yat-sen University Cancer Center (SYSUCC) cohort. A GC cohort that received anti-programmed cell death 1 (PD-1) therapy was used to analyze the predicted efficacy based on the expression of hub genes.ResultsThere is a total of 1,686 differentially expressed genes (DEGs) between the EBV-positive group and EBV-negative group, and WGCNA identified a yellow-colored module that was most related to EBV features. Functional enrichment analysis of 144 genes in this yellow module demonstrated that these genes primarily performed immune-related functions, and PPI network analysis through the CytoHubba plug-in identified 11 hub genes in the network. The RT-qPCR results in the SYSUCC cohort further validated that the hub genes were all increased in the EBV-positive group. Finally, we found that a potential classifier was associated with the efficacy of immunotherapy based on the expression of these 11 hub genes.ConclusionsOur study identified several hub genes associated with EBV status that are closely related to the immune microenvironmental features of EBVaGC and may be used as molecular markers for predicting the immune response in GC.

Establishment and Validation of a Ferroptosis-Related lncRNA Signature for Prognosis Prediction in Lower-Grade Glioma.

BackgroundThe prognosis of lower-grade glioma (LGG) is highly variable, and more accurate predictors are still needed. The aim of our study was to explore the prognostic value of ferroptosis-related long non-coding RNAs (lncRNAs) in LGG and to develop a novel risk signature for predicting survival with LGG.MethodsWe first integrated multiple datasets to screen for prognostic ferroptosis-related lncRNAs in LGG. A least absolute shrinkage and selection operator (LASSO) analysis was then utilized to develop a risk signature for prognostic prediction. Based on the results of multivariate Cox analysis, a prognostic nomogram model for LGG was constructed. Finally, functional enrichment analysis, single-sample gene set enrichment analysis (ssGSEA), immunity, and m6A correlation analyses were conducted to explore the possible mechanisms by which these ferroptosis-related lncRNAs affect survival with LGG.ResultsA total of 11 ferroptosis-related lncRNAs related to the prognosis of LGG were identified. Based on prognostic lncRNAs, a risk signature consisting of 8 lncRNAs was constructed and demonstrated good predictive performance in both the training and validation cohorts. Correlation analysis suggested that the risk signature was closely linked to clinical features. The nomogram model we constructed by combining the risk signature and clinical parameters proved to be more accurate in predicting the prognosis of LGG. In addition, there were differences in the levels of immune cell infiltration, immune-related functions, immune checkpoints, and m6A-related gene expression between the high- and low-risk groups.ConclusionIn summary, our ferroptosis-related lncRNA signature exhibits good performance in predicting the prognosis of LGG. This study may provide useful insight into the treatment of LGG.

Comprehensive Analysis of LINC01615 in Head and Neck Squamous Cell Carcinoma: A Hub Biomarker Identified by Machine Learning and Experimental Validation.

Background Head and neck squamous cell carcinoma (HNSCC) is one of the most common cancers, but in clinical practice, the lack of precise biomarkers often results in an advanced diagnosis. Hence, it is crucial to explore novel biomarkers to improve the clinical outcome of HNSCC patients. Methods We downloaded RNA-seq data consisting of 502 HNSCC tissues and 44 normal tissues from the TCGA database, and lncRNA genomic sequence information was downloaded from the GENECODE database for annotating lncRNA expression profiles. We used Cox regression analysis to screen prognostic lncRNAs, the threshold as HR >1 and p value <0.05. Subsequently, three survival outcomes (overall survival, progress-free interval, and disease-specific survival)-related lncRNAs overlapped to get the common lncRNAs. The hub biomarker was identified using LASSO and random forest models. Subsequently, we used a variety of statistical methods to validate the prognostic ability of the hub marker. In addition, Spearman correlation analysis between the hub marker expression and genomic heterogeneity was conducted, such as instability (MSI), homologous recombination deficiency (HRD), and tumor mutational burden (TMB). Finally, we used enrichment analysis, ssGSEA, and ESTIMATE algorithms to explore the changes in the underlying immune-related pathway and function. Finally, the MTT assay and transwell assay were performed to determine the effect of LINC01615 silencing on tumor cell proliferation, invasion, and migration. Results Cox regression analysis revealed 133 lncRNAs with multiple prognostic significance. The machine learning algorithm screened out the hub lncRNA with the highest importance in the RF model: LINC01615. Clinical correlation analysis revealed that the LINC01615 increased with increasing the T stage, N stage, pathology grade, and clinical stage. LINC01615 could be used as a predictor of HNSCC prognosis validating by a variety of statistical methods. Subsequently, when clinical indicators were combined with the LINC01615 expression, the visualization model (nomogram) was more applicable to clinical practice. Finally, immune algorithms indicated that LINC01615 may be involved in the regulation of lymphocyte recruitment and immunological infiltration in HNSCC, and the LINC01615 expression represented genomic heterogeneity in pan-cancer. Functionally, silencing of LINC01615 suppresses cell proliferation, invasion, and migration in HEP-2 and TU212 cells. Conclusion LINC01615 may play an important role in the prostromal cell enrichment and immunosuppressive state and serve as a prognostic biomarker in HNSCC.