Cuproptosis and Immune-Related Gene Signature Predicts Immunotherapy Response and Prognosis in Lung Adenocarcinoma

Cuproptosis and associated immune-related genes (IRG) have been implicated in tumorigenesis and tumor progression. However, their effects on lung adenocarcinoma (LUAD) have not been elucidated. Therefore, we investigated the impact of cuproptosis-associated IRGs on the immunotherapy response and prognosis of LUAD using a bioinformatical approach and in vitro experiments analyzing clinical samples. Using the cuproptosis-associated IRG signature, we classified LUAD into two subtypes, cluster 1 and cluster 2, and identified three key cuproptosis-associated IRGs, NRAS, TRAV38-2DV8, and SORT1. These three genes were employed to establish a risk model and nomogram, and to classify the LUAD cohort into low- and high-risk subgroups. Biofunctional annotation revealed that cluster 2, remarkably downregulating epigenetic, stemness, and proliferation pathways activity, had a higher overall survival (OS) and immunoinfiltration abundance compared to cluster 1. Real-time quantitative PCR (RT-qPCR) validated the differential expression of these three genes in both subgroups. scRNA-seq demonstrated elevated expression of NRAS and SORT1 in macrophages. Immunity and oncogenic and stromal activation pathways were dramatically enriched in the low-risk subgroup, and patients in this subgroup responded better to immunotherapy. Our data suggest that the cuproptosis-associated IRG signature can be used to effectively predict the immunotherapy response and prognosis in LUAD. Our work provides enlightenment for immunotherapy response assessment, prognosis prediction, and the development of potential prognostic biomarkers for LUAD patients.

Subviral Dense Bodies of Human Cytomegalovirus Enhance Interferon-Beta Responses in Infected Cells and Impair Progeny Production

(1) Background: Infection with human cytomegalovirus (HCMV) leads to the production and release of subviral particles, termed Dense Bodies (DB). They are enclosed by a membrane resembling the viral envelope. This membrane mediates the entrance of DBs into cells in a way that is comparable to virus infection. HCMV attachment and entry trigger the induction of interferon synthesis and secretion, and the subsequent expression of interferon-regulated genes (IRGs) that might inhibit replication of the virus. Recently, we demonstrated that DBs induce a robust interferon response in the absence of infection. Little is known thus far, including how DBs influence HCMV infection and virus-host interaction. (2) Methods: Purified DBs were used to study the impact on virus replication and on the innate defense mechanisms of the cell. (3) Results: The incubation of cells with DBs at the time of infection had little effect on viral genome replication. Preincubation of DBs, however, led to a marked reduction in viral release from infected cells. These cells showed an enhancement of the cytopathic effect, associated with a moderate increase in early apoptosis. Despite virus-induced mechanisms to limit the interferon response, the induction of interferon-regulated genes (IRGs) was upregulated by DB treatment. (4) Conclusions: DBs sensitize cells against viral infection, comparable to the effects of interferons. The activities of these particles need to be considered when studying viral-host interaction.

An inflammatory-related genes signature based model for prognosis prediction in breast cancer

Background

Breast cancer has become the most common malignant tumor in the world. It is vital to discover novel prognostic biomarkers despite the fact that the majority of breast cancer patients have a good prognosis because of the high heterogeneity of breast cancer, which causes the disparity in prognosis. Recently, inflammatory-related genes have been proven to play an important role in the development and progression of breast cancer, so we set out to investigate the predictive usefulness of inflammatory-related genes in breast malignancies.

Methods

We assessed the connection between Inflammatory-Related Genes (IRGs) and breast cancer by studying the TCGA database. Following differential and univariate Cox regression analysis, prognosis-related differentially expressed inflammatory genes were estimated. The prognostic model was constructed through the Least Absolute Shrinkage and Selector Operation (LASSO) regression based on the IRGs. The accuracy of the prognostic model was then evaluated using the Kaplan-Meier and Receiver Operating Characteristic (ROC) curves. The nomogram model was established to predict the survival rate of breast cancer patients clinically. Based on the prognostic expression, we also looked at immune cell infiltration and the function of immune-related pathways. The CellMiner database was used to research drug sensitivity.

Results

In this study, 7 IRGs were selected to construct a prognostic risk model. Further research revealed a negative relationship between the risk score and the prognosis of breast cancer patients. The ROC curve proved the accuracy of the prognostic model, and the nomogram accurately predicted survival rate. The scores of tumor-infiltrating immune cells and immune-related pathways were utilized to calculate the differences between the low- and high-risk groups, and then explored the relationship between drug susceptibility and the genes that were included in the model.

Conclusion

These findings contributed to a better understanding of the function of inflammatory-related genes in breast cancer, and the prognostic risk model provides a potentially promising prognostic strategy for breast cancer.

Identification of immune-related molecular clusters and diagnostic markers in chronic kidney disease based on cluster analysis

Background: Chronic kidney disease (CKD) is a heterogeneous disease with multiple etiologies, risk factors, clinical manifestations, and prognosis. The aim of this study was to identify different immune-related molecular clusters in CKD, their functional immunological properties, and to screen for promising diagnostic markers. Methods: Datasets of 440 CKD patients were obtained from the comprehensive gene expression database. The core immune-related genes (IRGs) were identified by weighted gene co-expression network analysis. We used unsupervised clustering to divide CKD samples into two immune-related subclusters. Then, functional enrichment analysis was performed for differentially expressed genes (DEGs) between clusters. Three machine learning methods (LASSO, RF, and SVM-RFE) and Venn diagrams were applied to filter out 5 significant IRGs with distinguished subtypes. A nomogram diagnostic model was developed, and the prediction effect was verified using calibration curve, decision curve analysis. CIBERSORT was applied to assess the variation in immune cell infiltration among clusters. The expression levels, immune characteristics and immune cell correlation of core diagnostic markers were investigated. Finally, the Nephroseq V5 was used to assess the correlation among core diagnostic markers and renal function. Results: The 15 core IRGs screened were differentially expressed in normal and CKD samples. CKD was classified into two immune-related molecular clusters. Cluster 2 is significantly enriched in biological functions such as leukocyte adhesion and regulation as well as immune activation, and has a severe immune prognosis compared to cluster 1. A nomogram diagnostic model with reliable prediction of immune-related clusters was developed based on five signature genes. The core diagnostic markers LYZ, CTSS, and ISG20 were identified as playing an important role in the immune microenvironment and were shown to correlate meaningfully with immune cell infiltration and renal function. Conclusion: Our study identifies two subtypes of CKD with distinct immune gene expression patterns and provides promising predictive models. Along with the exploration of the role of three promising diagnostic markers in the immune microenvironment of CKD, it is anticipated to provide novel breakthroughs in potential targets for disease treatment.

Subviral Dense Bodies of Human Cytomegalovirus Induce an Antiviral Type I Interferon Response

(1) Background: Cells infected with the human cytomegalovirus (HCMV) produce subviral particles, termed dense bodies (DBs), both in-vitro and in-vivo. They are released from cells, comparable to infectious virions, and are enclosed by a membrane that resembles the viral envelope and mediates the entry into cells. To date, little is known about how the DB uptake influences the gene expression in target cells. The purpose of this study was to investigate the impact of DBs on cells, in the absence of a viral infection. (2) Methods: Mass spectrometry, immunoblot analyses, siRNA knockdown, and a CRISPR-CAS9 knockout, were used to investigate the changes in cellular gene expression following a DB exposure; (3) Results: A number of interferon-regulated genes (IRGs) were upregulated after the fibroblasts and endothelial cells were exposed to DBs. This upregulation was dependent on the DB entry and mediated by the type I interferon signaling through the JAK-STAT pathway. The induction of IRGs was mediated by the sensing of the DB-introduced DNA by the pattern recognition receptor cGAS. (4) Conclusions: The induction of a strong type I IFN response by DBs is a unique feature of the HCMV infection. The release of DBs may serve as a danger signal and concomitantly contribute to the induction of a strong, antiviral immune response.

Toxoplasma gondii CDPK3 Controls the Intracellular Proliferation of Parasites in Macrophages

Interferon-γ (IFN-γ)-activated macrophages restrain the replication of intracellular parasites and disrupt the integrity of vacuolar pathogens. The growth of the less virulent type II strain of Toxoplasma gondii (such as ME49) was strongly inhibited by IFN-γ-activated murine macrophages. However, the mechanism of resistance is poorly understood. Immunity-related GTPases (IRGs) as well as guanylate-binding proteins (GBPs) contributed to this antiparasitic effect. Previous studies showed the cassette of autophagy-related proteins including Atg7, Atg3, and Atg12-Atg5-Atg16L1 complex, plays crucial roles in the proper targeting of IFN-γ effectors onto the parasitophorous vacuole (PV) membrane of Toxoplasma gondii and subsequent control of parasites. TgCDPK3 is a calcium dependent protein kinase, located on the parasite periphery, plays a crucial role in parasite egress. Herein, we show that the less virulent strain CDPK3 (ME49, type II) can enhance autophagy activation and interacts with host autophagy proteins Atg3 and Atg5. Infection with CDPK3-deficient ME49 strain resulted in decreased localization of IRGs and GBPs around PV membrane. In vitro proliferation and plaque assays showed that CDPK3-deficient ME49 strain replicated significantly more quickly than wild-type parasites. These data suggested that TgCDPK3 interacts with the host Atg3 and Atg5 to promote the localization of IRGs and GBPs around PV membrane and inhibits the intracellular proliferation of parasites, which is beneficial to the less virulent strain of Toxoplasma gondii long-term latency in host cells.

Identification of the Key Immune-Related Genes in Chronic Obstructive Pulmonary Disease Based on Immune Infiltration Analysis

Purpose

Chronic obstructive pulmonary disease (COPD) is a major cause of death and morbidity worldwide. A better understanding of new biomarkers for COPD patients and their complex mechanisms in the progression of COPD are needed.

Methods

An algorithm was conducted to reveal the proportions of 22 subsets of immune cells in COPD samples. Differentially expressed immune-related genes (DE-IRGs) were obtained based on the differentially expressed genes (DEGs) of the GSE57148 dataset, and 1509 immune-related genes (IRGs) were downloaded from the ImmPort database. Functional enrichment analyses of DE-IRGs were conducted by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses and Ingenuity Pathway Analysis (IPA). We defined the DE-IRGs that had correlations with immune cells as hub genes. The potential interactions among the hub genes were explored by a protein-protein interaction (PPI) network.

Results

The CIBERSORT results showed that lung tissue of COPD patients contained a greater number of resting NK cells, activated dendritic cells, and neutrophils than normal samples. However, the fractions of follicular helper T cells and resting dendritic cells were relatively lower. Thirty-eight DE-IRGs were obtained for further analysis. Functional enrichment analysis revealed that these DE-IRGs were significantly enriched in several immune-related biological processes and pathways. Notably, we also observed that DE-IRGs were associated with the coronavirus disease COVID-19 in the progression of COPD. After correlation analysis, six DE-IRGs associated with immune cells were considered hub genes, including AHNAK, SLIT2 TNFRRSF10C, CXCR1, CXCR2, and FCGR3B.

Conclusion

In the present study, we investigated immune-related genes as novel diagnostic biomarkers and explored the potential mechanism for COPD based on CIBERSORT analysis, providing a new understanding for COPD treatment.

A novel risk score predicts prognosis in melanoma: The combination of three tumor-infiltrating immune cells and four immune-related genes

Tumor-infiltrating immune cells (TIICs) and immune-related genes (IRGs) of melanoma are associated with prognosis. However, whether the combination of TIICs and IRGs can be used as prognostic clinical biomarkers are still unknown. Here, we downloaded transcription profile of melanoma from TCGA. Then, three TIICs and four IRGs that associated with the overall survival were used to constructed the Immune Cell Score (ICS) and Immune Gene Score (IGS) respectively. Next, to improve the accuracy of ICS and IGS for melanoma prognostic, we combined the ICS and IGS constructed the Immune Cell and Gene Score (ICGS) model. ICGS had higher accuracy and predictive ability than ICS or IGS. Meanwhile, ICGS model reliability was validated by two independent datasets of melanoma. Functional enrichment and protein-protein interaction network analysis based on ICGS were performed to identify T cell mediated immune and inflammatory response are highly associated with melanoma.

Identification of an Immune-Related Prognostic Signature Associated With Immune Infiltration in Melanoma

Melanoma is the leading cause of cancer-related death among skin tumors, with an increasing incidence worldwide. Few studies have effectively investigated the significance of an immune-related gene (IRG) signature for melanoma prognosis. Here, we constructed an IRGs prognostic signature using bioinformatics methods and evaluated and validated its predictive capability. Then, immune cell infiltration and tumor mutation burden (TMB) landscapes associated with this signature in melanoma were analyzed comprehensively. With the 10-IRG prognostic signature, melanoma patients in the low-risk group showed better survival with distinct features of high immune cell infiltration and TMB. Importantly, melanoma patients in this subgroup were significantly responsive to MAGE-A3 in the validation cohort. This immune-related prognostic signature is thus a reliable tool to predict melanoma prognosis; as the underlying mechanism of this signature is associated with immune infiltration and mutation burden, it might reflect the benefit of immunotherapy to patients.

An immune-related prognostic signature for predicting breast cancer recurrence

Breast cancer (BC) is the most common cancer among women worldwide and is the second leading cause of cancer‐related deaths in women. Increasing evidence has validated the vital role of the immune system in BC development and recurrence. In this study, we identified an immune‐related prognostic signature of BRCA that could help delineate risk scores of poor outcome for each patient. This prognostic signature comprised information on five danger genes—TSLP, BIRC5, S100B, MDK, and S100P—and three protect genes RARRES3, BLNK, and ACO1. Kaplan‐Meier survival curve showed that patients classified as low‐risk according to optimum cut‐off risk score had better prognosis than those identified within the high‐risk group. ROC analysis indicated that the identified prognostic signature had excellent diagnostic efficiency for predicting 3‐ and 5‐years relapse‐free survival (RFS). Multivariate Cox regression analysis proved that the prognostic signature is independent of other clinical parameters. Stratification analysis demonstrated that the prognostic signature can be used to predict the RFS of BC patients within the same clinical subgroup. We also developed a nomogram to predict the RFS of patients. The calibration plots exhibited outstanding performance. The validation sets (GSE21653, GSE20711, and GSE88770) were used to external validation. More convincingly, the real time RT‐PCR results of clinical samples demonstrated that danger genes were significantly upregulated in BC samples, whereas protect genes were downregulated. In conclusion, we developed and validated an immune‐related prognostic signature, which exhibited excellent diagnostic efficiency in predicting the recurrence of BC, and will help to make personalized treatment decisions for patients at different risk score.

Loss of the interferon-γ-inducible regulatory immunity-related GTPase (IRG), Irgm1, causes activation of effector IRG proteins on lysosomes, damaging lysosomal function and predicting the dramatic susceptibility of Irgm1-deficient mice to infection

Background

The interferon-γ (IFN-γ)-inducible immunity-related GTPase (IRG), Irgm1, plays an essential role in restraining activation of the IRG pathogen resistance system. However, the loss of Irgm1 in mice also causes a dramatic but unexplained susceptibility phenotype upon infection with a variety of pathogens, including many not normally controlled by the IRG system. This phenotype is associated with lymphopenia, hemopoietic collapse, and death of the mouse.

Results

We show that the three regulatory IRG proteins (GMS sub-family), including Irgm1, each of which localizes to distinct sets of endocellular membranes, play an important role during the cellular response to IFN-γ, each protecting specific membranes from off-target activation of effector IRG proteins (GKS sub-family). In the absence of Irgm1, which is localized mainly at lysosomal and Golgi membranes, activated GKS proteins load onto lysosomes, and are associated with reduced lysosomal acidity and failure to process autophagosomes. Another GMS protein, Irgm3, is localized to endoplasmic reticulum (ER) membranes; in the Irgm3-deficient mouse, activated GKS proteins are found at the ER. The Irgm3-deficient mouse does not show the drastic phenotype of the Irgm1 mouse. In the Irgm1/Irgm3 double knock-out mouse, activated GKS proteins associate with lipid droplets, but not with lysosomes, and the Irgm1/Irgm3^−/− does not have the generalized immunodeficiency phenotype expected from its Irgm1 deficiency.

Conclusions

The membrane targeting properties of the three GMS proteins to specific endocellular membranes prevent accumulation of activated GKS protein effectors on the corresponding membranes and thus enable GKS proteins to distinguish organellar cellular membranes from the membranes of pathogen vacuoles. Our data suggest that the generalized lymphomyeloid collapse that occurs in Irgm1^−/− mice upon infection with a variety of pathogens may be due to lysosomal damage caused by off-target activation of GKS proteins on lysosomal membranes and consequent failure of autophagosomal processing.

Electronic supplementary material

The online version of this article (doi:10.1186/s12915-016-0255-4) contains supplementary material, which is available to authorized users.

Genetic diversity and population structure in Physalis peruviana and related taxa based on InDels and SNPs derived from COSII and IRG markers

The genus Physalis is common in the Americas and includes several economically important species, among them Physalis peruviana that produces appetizing edible fruits. We studied the genetic diversity and population structure of P. peruviana and characterized 47 accessions of this species along with 13 accessions of related taxa consisting of 222 individuals from the Colombian Corporation of Agricultural Research (CORPOICA) germplasm collection, using Conserved Orthologous Sequences (COSII) and Immunity Related Genes (IRGs). In addition, 642 Single Nucleotide Polymorphism (SNPs) markers were identified and used for the genetic diversity analysis. A total of 121 alleles were detected in 24 InDels loci ranging from 2 to 9 alleles per locus, with an average of 5.04 alleles per locus. The average number of alleles in the SNP markers was two. The observed heterozygosity for P. peruviana with InDel and SNP markers was higher (0.48 and 0.59) than the expected heterozygosity (0.30 and 0.41). Interestingly, the observed heterozygosity in related taxa (0.4 and 0.12) was lower than the expected heterozygosity (0.59 and 0.25). The coefficient of population differentiation F_ST was 0.143 (InDels) and 0.038 (SNPs), showing a relatively low level of genetic differentiation among P. peruviana and related taxa. Higher levels of genetic variation were instead observed within populations based on the AMOVA analysis. Population structure analysis supported the presence of two main groups and PCA analysis based on SNP markers revealed two distinct clusters in the P. peruviana accessions corresponding to their state of cultivation. In this study, we identified molecular markers useful to detect genetic variation in Physalis germplasm for assisting conservation and crossbreeding strategies.

Early inflammatory response to the saponin adjuvant Matrix-M in the pig

The early inflammatory response to Matrix-M was evaluated in pigs. Adverse reactions measured as body temperature, appetite, activity level and reaction at the site of injection were not observed after s.c. injection with three doses of the adjuvant (75, 100 or 150μg) into one week old piglets. Analyses of the immediate cytokine response of PBMC after in vitro exposure to Matrix-M (AbISCO-100(®)) revealed only a low expression of mRNA for tumour necrosis factor-α (p<0.05) after 6h incubation. Histological examination revealed an infiltration of leukocytes, haemorrhage and necrosis in muscle 24h after i.m. injection of 150μg Matrix-M in pigs aged eleven weeks. At this time, different grades of reactive lymphoid hyperplasia were recorded in the draining lymph node that was enlarged in three of these six pigs injected with Matrix-M. The global transcriptional response at the site of injection and in the draining lymph node was analyzed using Affymetrix GeneChip Porcine Genome Array. A significant enrichment of gene signatures for the cell types described as "myeloid cells" and "plasmacytoid dendritic cells" was observed at the site of injection in Matrix-M injected pigs compared with pigs injected with saline. A number of genes encoding cytokines/chemokines or their receptors were upregulated at the injection site as well as in the draining lymph node. In the draining lymph node, a majority of the upregulated genes were interferon-regulated genes (IRGs). The expression of IFN-β, but not IFN-α, was increased in the draining lymph nodes of a majority of the pigs exposed to Matrix-M. These IFN-β expressing pigs also expressed increased levels of osteopontin (OPN) or stimulator of interferon genes (STING), two factors known to facilitate the expression of type I IFNs in response to viral infection. Thus, Matrix-M does not appear to induce any harmful inflammatory response in piglets whilst contributing to the innate immunity by activating the type I IFN system, possibly through several alternative signalling pathways.