Immune Marker Genes Research Articles

Gastric cancer metastasis-related NT5DC2 indicates unfavorable prognosis of patients.

Approximately 80 to 90% of patients with gastric cancer (GC) eventually develop into metastatic GC nowadays,because GC is difficult to be diagnosed at an early stage. GC patients with metastases typically have a poor prognosis. It is necessary to explore a potential prognostic marker in metastatic GC. All GC data were obtained from The Cancer Genome Atlas and Gene Expression Omnibus databases. The metastasis-related candidate gene and its role in GC were analyzed by comprehensive analysis. Totally 1049 metastasis-related genes were identified in GC. Univariate Cox regression analysis screened the top 10 genes (PDHX, SLC43A1, CSAG2, NT5DC2, CSAG1, FMN1, MED1, HIVEP2, FNDC3A, and PPP1R2) that were closely correlated with prognosis of GC patients. Among which, NT5DC2 was screened as the target gene for subsequent study. The NT5DC2 expression were increased in primary GC and metastatic GC samples. Moreover, GC patients with high NT5DC2 expression exhibited shorter overall survival and post progression survival, and the NT5DC2 was metastatic GC patients' independent prognostic factor. Totally 29 pathways were activated in metastatic GC samples with high NT5DC2 expression. Four immune cells' infiltration were significantly different between NT5DC2 high and low expressed metastatic GC patients. NT5DC2 showed significantly negative correlations with 6 types of immune cells' critical marker genes and 5 types of immune cell infiltration. The 10 immune checkpoint expressions were decreased in high NTDC2 expression metastatic GC patients. NT5DC2 plays a prognostic role in metastatic GC. GC patients with high NT5DC2 expression indicates unfavorable prognosis.

Spatially and temporally distinct Ca2+ changes in Lotus japonicus roots orient fungal-triggered signalling pathways towards symbiosis or immunity.

Plants activate an immune or symbiotic response depending on the detection of distinct signals from root-interacting microbes. Both signalling cascades involve Ca2+ as a central mediator of early signal transduction. In this study, we combined aequorin- and cameleon-based methods to dissect the changes in cytosolic and nuclear Ca2+ concentration caused by different chitin-derived fungal elicitors in Lotus japonicus roots. Our quantitative analyses highlighted the dual character of the evoked Ca2+ responses taking advantage of the comparison between different genetic backgrounds: an initial Ca2+ influx, dependent on the LysM receptor CERK6 and independent of the common symbiotic signalling pathway (CSSP), is followed by a second CSSP-dependent and CERK6-independent phase, that corresponds to the well-known perinuclear/nuclear Ca2+ spiking. We show that the expression of immunity marker genes correlates with the amplitude of the first Ca2+ change, depends on elicitor concentration, and is controlled by Ca2+ storage in the vacuole. Our findings provide an insight into the Ca2+-mediated signalling mechanisms discriminating plant immunity- and symbiosis-related pathways in the context of their simultaneous activation by single fungal elicitors.

Identification of Colon Immune Cell Marker Genes Using Machine Learning Methods.

Immune cell infiltration that occurs at the site of colon tumors influences the course of cancer. Different immune cell compositions in the microenvironment lead to different immune responses and different therapeutic effects. This study analyzed single-cell RNA sequencing data in a normal colon with the aim of screening genetic markers of 25 candidate immune cell types and revealing quantitative differences between them. The dataset contains 25 classes of immune cells, 41,650 cells in total, and each cell is expressed by 22,164 genes at the expression level. They were fed into a machine learning-based stream. The five feature ranking algorithms (last absolute shrinkage and selection operator, light gradient boosting machine, Monte Carlo feature selection, minimum redundancy maximum relevance, and random forest) were first used to analyze the importance of gene features, yielding five feature lists. Then, incremental feature selection and two classification algorithms (decision tree and random forest) were combined to filter the most important genetic markers from each list. For different immune cell subtypes, their marker genes, such as KLRB1 in CD4 T cells, RPL30 in B cell IGA plasma cells, and JCHAIN in IgG producing B cells, were identified. They were confirmed to be differentially expressed in different immune cells and involved in immune processes. In addition, quantitative rules were summarized by using the decision tree algorithm to distinguish candidate immune cell types. These results provide a reference for exploring the cell composition of the colon cancer microenvironment and for clinical immunotherapy.

TRB CDR3-cancer testis antigen chemical complementarity scoring for identifying productive immune responses in renal cell carcinoma.

Immunogenomics approaches to the characterization of renal cell carcinoma (RCC) have helped to better our understanding of the features of RCC immune dysfunction. However, much is still unknown with regard to specific immune interactions and their impact in the tumor microenvironment. This study applied chemical complementarity scoring for the TRB complementarity determining region-3 (CDR3) amino acid sequences and cancer testis antigens (CTAs) to determine whether such complementarity correlated with survival and the expression of immune marker genes. TRB recombination reads from RCC tumor samples from RNAseq files obtained from two separate databases, Moffitt Cancer Center and The Cancer Genome Atlas (TCGA), were evaluated. Chemical complementarity scores (CSs) were calculated for TRB CDR3-CTA pairs and survival assessments based on those CSs were performed. Moffitt Cancer Center and TCGA cases representing the upper 50th percentile of chemical CSs for TRB CDR3 amino acid sequences and the CTA POTEA were found to be associated with a better overall survival (OS) Also, greater tumor RNA expression of multiple immune signature genes, including granzyme A, granzyme B, and interferon-gamma were correlated with the higher chemical CSs. These results indicate that TRB CDR3-CTA chemical complementarity scoring may be useful in distinguishing RCC cases with a productive, anti-tumor immune response from cases where basic immune parameter assessments are inconsistent with a productive immune response.

Immunological Role of Megakaryocytes and Platelets during Influenza A Virus Infection

Influenza viruses pose a serious threat to public health, with severe cases often characterized by lung damage and inflammation. However, the underlying mechanisms of these processes remain poorly understood. This study aimed to investigate the essential role of megakaryocytes (MKs) and platelets (PLTs) in influenza A virus (IAV) infections. Conducted at the Department of Rare Respiratory Diseases, Cystic Fibrosis, and Pulmonology, Nord University Hospital, Marseille, France, the study collected seventy blood samples between October 2018 and March 2019. Samples were obtained from healthy individuals and patients diagnosed with IAV. Messenger RNA was extracted from isolated PLTs and subjected to quantitative real-time-polymerase chain reaction using sets of primers targeting immune marker genes. Western blot analysis was also performed for confirmation, focusing on Fas Ligand (FasL). Results showed that PLTs from IAV-infected individuals expressed the FasL, tumor necrosis factor-related apoptosis-inducing ligand, and Granulysin (GNLY) receptors when activated. Furthermore, an in vitro assay revealed the presence of FasL receptors on infected CMK cell lines. In vivo investigations demonstrated that activated MKs and PLTs in mice also expressed FasL. Interestingly, none of the immune receptors under investigation were found in both MKs and PLTs in mouse model studies. In conclusion, MKs and PLTs play a significant role in influencing immune responses that may help prevent viral spread during infection. However, further examination of their mechanisms of action is warranted. Understanding the involvement of these cells in influenza pathogenesis could offer valuable insights for developing potential therapeutic strategies.

Identification of novel gene signature for lung adenocarcinoma by machine learning to predict immunotherapy and prognosis.

Lung adenocarcinoma (LUAD) as a frequent type of lung cancer has a 5-year overall survival rate of lower than 20% among patients with advanced lung cancer. This study aims to construct a risk model to guide immunotherapy in LUAD patients effectively. LUAD Bulk RNA-seq data for the construction of a model, single-cell RNA sequencing (scRNA-seq) data (GSE203360) for cell cluster analysis, and microarray data (GSE31210) for validation were collected from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. We used the Seurat R package to filter and process scRNA-seq data. Sample clustering was performed in the ConsensusClusterPlus R package. Differentially expressed genes (DEGs) between two groups were mined by the Limma R package. MCP-counter, CIBERSORT, ssGSEA, and ESTIMATE were employed to evaluate immune characteristics. Stepwise multivariate analysis, Univariate Cox analysis, and Lasso regression analysis were conducted to identify key prognostic genes and were used to construct the risk model. Key prognostic gene expressions were explored by RT-qPCR and Western blot assay. A total of 27 immune cell marker genes associated with prognosis were identified for subtyping LUAD samples into clusters C3, C2, and C1. C1 had the longest overall survival and highest immune infiltration among them, followed by C2 and C3. Oncogenic pathways such as VEGF, EFGR, and MAPK were more activated in C3 compared to the other two clusters. Based on the DEGs among clusters, we confirmed seven key prognostic genes including CPA3, S100P, PTTG1, LOXL2, MELTF, PKP2, and TMPRSS11E. Two risk groups defined by the seven-gene risk model presented distinct responses to immunotherapy and chemotherapy, immune infiltration, and prognosis. The mRNA and protein level of CPA3 was decreased, while the remaining six gene levels were increased in clinical tumor tissues. Immune cell markers are effective in clustering LUAD samples into different subtypes, and they play important roles in regulating the immune microenvironment and cancer development. In addition, the seven-gene risk model may serve as a guide for assisting in personalized treatment in LUAD patients.

The landscape of PBMC methylome in canine mammary tumors reveals the epigenetic regulation of immune marker genes and its potential application in predicting tumor malignancy

BackgroundGenome-wide dysregulation of CpG methylation accompanies tumor progression and characteristic states of cancer cells, prompting a rationale for biomarker development. Understanding how the archetypic epigenetic modification determines systemic contributions of immune cell types is the key to further clinical benefits.ResultsIn this study, we characterized the differential DNA methylome landscapes of peripheral blood mononuclear cells (PBMCs) from 76 canines using methylated CpG-binding domain sequencing (MBD-seq). Through gene set enrichment analysis, we discovered that genes involved in the growth and differentiation of T- and B-cells are highly methylated in tumor PBMCs. We also revealed the increased methylation at single CpG resolution and reversed expression in representative marker genes regulating immune cell proliferation (BACH2, SH2D1A, TXK, UHRF1). Furthermore, we utilized the PBMC methylome to effectively differentiate between benign and malignant tumors and the presence of mammary gland tumors through a machine-learning approach.ConclusionsThis research contributes to a better knowledge of the comprehensive epigenetic regulation of circulating immune cells responding to tumors and suggests a new framework for identifying benign and malignant cancers using genome-wide methylome.

A novel eight-gene Immune Cell-Associated Predictive Gene model to predict recurrence in triple-negative breast cancer.

Tumour tissue contains not only tumour cells but also some stromal cells and immune cells. This is one composition of the immune microenvironment of the tumour and causes a significant effect on the prognostic factors and recurrence of malignant tumor. In this research, single-cell RNA data from triple-negative breast cancers (TNBCs) were comprehensively analyzed and 1,527 marker genes expressed in immune cells were identified. Subsequently, RNA sequencing and clinical data from 360 patients in the Triple Negative Breast Cancer database at the Fudan University Shanghai Cancer Center (FUSCC) were divided into two groups in a 1:1 ratio, the training group and the validation group. An eight-gene Immune Cell-Associated Predictive Gene (ICAPG) model for predicting breast cancer (BC) recurrence was developed using mRNA data from the training group combined with immune cell marker genes. Based on this model, subjects were divided into two different risk level groups. The predictive power of the model was fully validated using the validation group and The Cancer Genome Atlas (TCGA) database. The localization and expression of these eight genes were then confirmed in a single-cell database. ssGSEA and CIBERSORT algorithms were used to characterize the differences in immune cell infiltration between the two different risk groups. The eight-gene ICAPG model was proven to be effective in the validation group. The low-risk group patients presented higher criterion of infiltration of CD8+ T cells and higher levels of tumour-infiltrating lymphocytes (TILs). In addition, the relationship between predictive models and homologous recombination deficiency (HRD) was explored and it was revealed that subjects from the high-risk group tended to have higher HRD values. This research established a new predictive model on the basis of immune cell marker genes that might effectively predict relapse in TNBC patients.

A comprehensively prognostic and immunological analysis of chloride intracellular channel protein 5 (CLIC5) in pan-cancer and identification in ovarian cancer.

CLIC5 encoded protein associates with actin-based cytoskeletal and is increasingly thought to play significant roles in human cancers. We use TCGA and GEO to explore CLIC5 expression differences, mutation and DNA methylation, TMB, MSI, and immune cell infiltration. We verified the mRNA expression of CLIC5 in human ovarian cancer cells by real-time PCR and detected the expression of CLIC5 as well as immune marker genes in ovarian cancer by immunohistochemistry. The pan-cancer analysis showed that CLIC5 is highly expressed in several malignant tumors. In some cancers, CLIC5 expression in tumor samples is associated with poorer overall survival. For example, patients with ovarian cancer with high expression of CLIC5 have a poor prognosis. CLIC5 mutation frequency increased in all tumor types. The CLIC5 promoter is hypomethylated in most tumors. CLIC5 was associated with tumor immunity and different immune cells of different tumor types, such as CD8 + T cells, tumor-associated fibroblasts, macrophages, etc. CLIC5 was positively correlated with various immune checkpoints, and TMB and MSI were correlated with dysregulation of CLIC5 in tumors. The expression of CLIC5 in ovarian cancer was detected by qPCR and IHC, and the results were consistent with the bioinformatics results. There were a strong positive correlation between CLIC5 expression and M2 macrophage (CD163) infiltration and a negative correlation with CD8 + T-cell infiltration. In conclusions, our first pan-cancer analysis offered a detailed grasp of the cancerogenic functions of CLIC5 in a variety of malignancies. CLIC5 participated in immunomodulation and performed a crucial function in the tumor microenvironment.

Comprehensive analysis to construct a novel immune-related prognostic panel in aging-related gastric cancer based on the lncRNA‒miRNA-mRNA ceRNA network.

Introduction: Gastric cancer (GC) is the fifth frequent malignancy and is responsible for the third leading cause of cancer-related deaths. Gastric cancer is an aging-related disease, with incidence and mortality rates increasing with aging. The development of GC is affected by lncRNAs, miRNAs, and mRNAs at the transcriptional and posttranscriptional levels. This study aimed to establish a prognostic panel for GC based on competing endogenous RNA (ceRNA) networks. Methods: RNA sequences were obtained from the TCGA database. Different expressions of RNAs were scrutinized with the EdgeR package. The ceRNA network was built using the starBase database and the Cytoscape. The prognostic panel was constituted with the LASSO algorithm. We developed a nomogram comprising clinical characteristic and risk score. The receiver operating characteristic (ROC) was used to evaluate the accuracy of the nomogram prediction. Hub RNAs expressions were detected by qPCR, immunohistochemistry and western blot respectively. Clinical relevance and survival analyses were analyzed. The relationship between RNAs and immune infiltrations, as well as immune checkpoints, was analyzed and evaluated using the CIBERSORT, TIMER and TISIDB databases. Results: Four DElncRNAs, 21 DEmiRNAs and 45 DEmRNAs were included in the ceRNA network. A 3-element panel (comprising lncRNA PVT1, hsa-miR-130a-3p and RECK) with poor overall survival (OS) was established and qPCR was applied to validate the expressions of hub RNAs. Hub RNAs were firmly associated with T, M, and N stage. The CIBERSORT database showed that the high lassoScore group exhibited a significantly high ratio of resting memory CD4+ T cells, M2 macrophages and a significantly low ratio of activated memory CD4+ T cells and M1 macrophages. According to the TIMER database, this panel was linked to immune infiltrations and immune cell gene markers. TISIDB database indicated that RECK was positively correlated with immune checkpoints (including CD160, CD244, PDCD1, and TGFBR1). Discussion: A novel triple prognostic panel of GC constructed based on the ceRNA network was associated with clinical prognostic, clinicopathological features, immune infiltrations, immune checkpoints and immune gene markers. This panel might provide potential therapeutic targets for GC and more experimental verification research is needed.

Prediction of liver cancer prognosis based on immune cell marker genes.

Monitoring the response after treatment of liver cancer and timely adjusting the treatment strategy are crucial to improve the survival rate of liver cancer. At present, the clinical monitoring of liver cancer after treatment is mainly based on serum markers and imaging. Morphological evaluation has limitations, such as the inability to measure small tumors and the poor repeatability of measurement, which is not applicable to cancer evaluation after immunotherapy or targeted treatment. The determination of serum markers is greatly affected by the environment and cannot accurately evaluate the prognosis. With the development of single cell sequencing technology, a large number of immune cell-specific genes have been identified. Immune cells and microenvironment play an important role in the process of prognosis. We speculate that the expression changes of immune cell-specific genes can indicate the process of prognosis. Therefore, this paper first screened out the immune cell-specific genes related to liver cancer, and then built a deep learning model based on the expression of these genes to predict metastasis and the survival time of liver cancer patients. We verified and compared the model on the data set of 372 patients with liver cancer. The experiments found that our model is significantly superior to other methods, and can accurately identify whether liver cancer patients have metastasis and predict the survival time of liver cancer patients according to the expression of immune cell-specific genes. We found these immune cell-specific genes participant multiple cancer-related pathways. We fully explored the function of these genes, which would support the development of immunotherapy for liver cancer.

Information about immune cell proportions and tumor stage improves the prediction of recurrence in patients with colorectal cancer

Predicting cancer recurrence is essential to improving the clinical outcomes of patients with colorectal cancer (CRC). Although tumor stage information has been used as a guideline to predict CRC recurrence, patients with the same stage show different clinical outcomes. Therefore, there is a need to develop a method to identify additional features for CRC recurrence prediction. Here, we developed a network-integrated multiomics (NIMO) approach to select appropriate transcriptome signatures for better CRC recurrence prediction by comparing the methylation signatures of immune cells. We validated the performance of the CRC recurrence prediction based on two independent retrospective cohorts of 114 and 110 patients. Moreover, to confirm that the prediction was improved, we used both NIMO-based immune cell proportions and TNM (tumor, node, metastasis) stage data. This work demonstrates the importance of (1) using both immune cell composition and TNM stage data and (2) identifying robust immune cell marker genes to improve CRC recurrence prediction.

CILP2: A prognostic biomarker associated with immune infiltration in colorectal cancer

PurposeThe function played by cartilage intermediate layer protein 2 (CILP2) between colorectal cancer (CRC) progression and immune response remains unclear, especially with respect to immune cell infiltration and checkpoints. Materials and Methods: We examined CILP2 expression in The Cancer Genome Atlas (TCGA) COAD-READ cohort and analyzed its relationship with clinicopathological features, mutations, survival, and immunity. Gene ontology, Kyoto Encyclopedia of Genes and Genomes pathway analysis, and gene set enrichment analyses (GSEA) were performed to determine CILP2 related pathways. To further investigate the results of TCGA analysis, validation was performed using CRC cell lines, fresh pathological tissues, and a CRC tissue microarray (TMA). Results: In both TCGA and TMA cohorts, CILP2 expression was increased in CRC tissues and was associated with patient T stage (T3 and T4), N stage (N1), pathological stage (III and IV), and overall survival. Immune cell infiltration and checkpoint analysis revealed that CILP2 expression is highly correlated with multiple immune marker genes, including PD-1. In addition, results of enrichment analysis indicated that CILP2 related genes was mainly enriched in extracellular matrix related functions. Conclusion: Elevated CILP2 expression is associated with adverse CRC clinical features and immune cells, it has potential as a biomarker detrimental to CRC survival.

Electrostatic Complementarities of Glioblastoma-Resident T-Cell Receptors and Cancer Testis Antigens Linked to Poor Outcomes and High Levels of Sphingosine Kinase-2 Expression.

Glioblastoma (GBM) is the most aggressive primary brain tumor in adults. Despite a growing understanding of glioblastoma pathology, the prognosis remains poor. In this study, we used a previously extensively benchmarked algorithm to retrieve immune receptor (IR) recombination reads from GBM exome files available from the cancer genome atlas. The T-cell receptor complementarity determining region-3 (CDR3) amino acid sequences that represent the IR recombination reads were assessed and used for the generation of chemical complementarity scores (CSs) that represent potential binding interactions with cancer testis antigens (CTAs), which is an approach particularly suited to a big data setting. The electrostatic CSs representing the TRA and TRB CDR3s and the CTAs, SPAG9, GAGE12E, and GAGE12F, indicated that an increased electrostatic CS was associated with worse disease-free survival (DFS). We also assessed the RNA expression of immune marker genes, which indicated that a high-level expression of SPHK2 and CIITA genes also correlated with high CSs and worse DFS. Furthermore, apoptosis-related gene expression was revealed to be lower when the TCR CDR3-CTA electrostatic CSs were high. Adaptive IR recombination reads from exome files have the potential to aid in GBM prognoses and may provide opportunities to detect unproductive immune responses.

Abstract 3467: GRWD5769: A first-in-class inhibitor of ERAP1, generating novel cancer antigens to drive de novo anti-tumor T cell responses

Abstract Immune checkpoint inhibitors (ICI) have changed the cancer treatment paradigm, yet significant unmet need remains. Clinical data shows that increasing antigen presentation diversity, genomic instability, tumor mutational burden and HLA diversity, as well as preventing permanent exhaustion of pre-existing cytotoxic T cells, caused by chronic cancer antigen stimulation, are all factors that improve clinical response to ICI. Additionally, increasing presentation of cancer-specific target peptides on cancer cells will enhance T cell receptor (TCR)-mediated therapeutics such as ImmTACs or TCR-Engineered T cells. Endoplasmic reticulum aminopeptidase 1 (ERAP1) trims peptides loaded into classical and non-classical MHC Class I. In cancer, knockout or inhibition of ERAP1 changes a proportion of the antigen repertoire, generating and upregulating cancer antigens. This leads to the activation of de novo anti-tumor T cell responses, causing tumor growth inhibition and bypassing T cell exhaustion. We report the preclinical development, characterization and mechanistic analysis of the first-in-class ERAP1 inhibitor, GRWD5769. Extensive analysis of the immunopeptidomes of diverse cancer cell lines robustly showed that GRWD5769 modulates the cancer-related antigen repertoire across genotypes and cancer-type backgrounds. Novel or upregulated neoantigens generated by ERAP1 inhibition are conserved across cancer cell types and genetic backgrounds. ERAP1 inhibition in combination with an ICI (anti-PD1 mAb) diversified the TCR repertoire, upregulated prognostic immune gene markers in the tumor, including markers for recently activated (thus non-exhausted) T cells, and drove infiltration of T cells into syngeneic mouse model tumors. This combination is efficacious across syngeneic models, including different mouse strains and the effects of ERAP1 inhibition on the T cell response correlate with efficacy. Further, ex vivo human T cell co-cultures with cancer cell lines demonstrate that novel and upregulated neoantigens generated by ERAP1 inhibition drive tumor cell killing. In addition, these studies showed enhanced tumor cell killing when an ImmTAC was used in combination with ERAP1 inhibition to enhance presentation of the cancer-specific target peptide. In conclusion, the first-in-class, ERAP1 inhibitor clinical candidate, GRWD5769, drives novel anti-tumor T cell responses through neoantigen creation and circumventing T cell exhaustion. GRWD5769 has demonstrated a good safety profile in GLP toxicology studies and robust proof of mechanism and proof of principle biomarkers have been developed to provide a clear path to establish the activity and efficacy of GRWD5769 in patients in 2023. Citation Format: Andrew Leishman, Wayne Paes, Emma Sparrow, Ana Ribeiro, Michael Cundell, Milos Aleksic, Michael P. Pinggera, Jessica Sette, Kate Anderton, Nicola Ternette, Juliet Morgan, Jason J. Shiers, Martin Quibell, Peter I. Joyce. GRWD5769: A first-in-class inhibitor of ERAP1, generating novel cancer antigens to drive de novo anti-tumor T cell responses [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3467.

A novel mitochondria-related gene signature in esophageal carcinoma: prognostic, immune, and therapeutic features

Esophageal carcinoma (ESCA) is a common and lethal malignant tumor worldwide. The mitochondrial biomarkers were useful in finding significant prognostic gene modules associated with ESCA owing to the role of mitochondria in tumorigenesis and progression. In the present work, we obtained the transcriptome expression profiles and corresponding clinical information of ESCA from The Cancer Genome Atlas (TCGA) database. Differential expressed genes (DEGs) were overlapped with 2030 mitochondria-related genes to get mitochondria-related DEGs. The univariate cox regression, Least Absolute Shrinkage and Selection Operator (LASSO) regression, and multivariate cox regression were sequentially used to define the risk scoring model for mitochondria-related DEGs, and its prognostic value was verified in the external datasets GSE53624. Based on the risk score, ESCA patients were divided into high- and low-risk groups. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA) were performed to further investigate the difference between low- and high-risk groups at the gene pathway level. CIBERSORT was used to evaluate immune cell infiltration. The mutation difference between high- and low-risk groups was compared by using the R package "Maftools". Cellminer was used to assess the association between the risk scoring model and drug sensitivity. As the most important outcome of the study, a 6-gene risk scoring model (APOOL, HIGD1A, MAOB, BCAP31, SLC44A2, and CHPT1) was constructed from 306 mitochondria-related DEGs. Pathways including the "hippo signaling pathway" and "cell-cell junction" were enriched in the DEGs between high and low groups. According to CIBERSORT, samples with high-risk scores demonstrated a higher abundance of CD4+ T cells, NK cells, M0 and M2 macrophages, and a lower abundance of M1 macrophages. The immune cell marker genes were correlated with the risk score. In mutation analysis, the mutation rate of TP53 was significantly different between the high- and low-risk groups. Drugs with a strong correlation with the risk model were selected. In conclusion, we focused on the role of mitochondria-related genes in cancer development and proposed a prognostic signature for individualized integrative assessment.

Single-Cell and Transcriptome-Based Immune Cell-Related Prognostic Model in Clear Cell Renal Cell Carcinoma.

Traditional studies mostly focus on the role of single gene in regulating clear cell renal cell carcinoma (ccRCC), while it ignores the impact of tumour heterogeneity on disease progression. The purpose of this study is to construct a prognostic risk model for ccRCC by analysing the differential marker genes related to immune cells in the single-cell database to provide help in clinical diagnosis and targeted therapy. Single-cell data and ligand-receptor relationship pair data were downloaded from related publications, and ccRCC phenotype and expression profile data were downloaded from TCGA and CPTAC. Based on the DEGs of each cluster acquired from single-cell data, immune cell marker genes, and ligand-receptor gene data, we constructed a multilayer network. Then, the genes in the network and the genes in TCGA were used to construct the WGCNA network, which screened out prognosis-associated genes for subsequent analysis. Finally, a prognostic risk scoring model was obtained, and CPTAC data showed that the effectiveness of this model was good. A nomogram based on the predictive model for predicting the overall survival was established, and internal validation was performed well. Our findings suggest that the predictive model built and based on the immune cell scRNA-seq will enable us to judge the prognosis of patients with ccRCC and provide more accurate directions for basic relevant research and clinical practice.

A novel oral formulation of the melanocortin-1 receptor agonist PL8177 resolves inflammation in preclinical studies of inflammatory bowel disease and is gut restricted in rats, dogs, and humans.

PL8177 is a potent and selective agonist of the melanocortin 1 receptor (MC1R). PL8177 has shown efficacy in reversing intestinal inflammation in a cannulated rat ulcerative colitis model. To facilitate oral delivery, a novel, polymer-encapsulated formulation of PL8177 was developed. This formulation was tested in 2 rat ulcerative colitis models and evaluated for distribution, in vivo, in rats, dogs, and humans. The rat models of colitis were induced by treatment with 2,4-dinitrobenzenesulfonic acid or dextran sulfate sodium. Single nuclei RNA sequencing of colon tissues was performed to characterize the mechanism of action. The distribution and concentration of PL8177 and the main metabolite within the GI tract after a single oral dose of PL8177 was investigated in rats and dogs. A phase 0 clinical study using a single microdose (70 µg) of [14C]-labeled PL8177 investigated the release of PL8177 in the colon of healthy men after oral administration. Rats treated with 50 µg oral PL8177 demonstrated significantly lower macroscopic colon damage scores and improvement in colon weight, stool consistency, and fecal occult blood vs the vehicle without active drug. Histopathology analysis resulted in the maintenance of intact colon structure and barrier, reduced immune cell infiltration, and increased enterocytes with PL8177 treatment. Transcriptome data show that oral PL8177 50 µg treatment causes relative cell populations and key gene expressions levels to move closer to healthy controls. Compared with vehicle, treated colon samples show negative enrichment of immune marker genes and diverse immune-related pathways. In rats and dogs, orally administered PL8177 was detected at higher amounts in the colon vs upper GI tract. [14C]-PL8177 and the main metabolite were detected in the feces but not in the plasma and urine in humans. This suggests that the parent drug [14C]-PL8177 was released from the polymer formulation and metabolized within the GI tract, where it would be expected to exert its effect. Collectively, these findings support further research into the oral formulation of PL8177 as a possible therapeutic for GI inflammatory diseases in humans.

Rickettsia parkeri hijacks tick hemocytes to manipulate cellular and humoral transcriptional responses.

Blood-feeding arthropods rely on robust cellular and humoral immunity to control pathogen invasion and replication. Tick hemocytes produce factors that can facilitate or suppress microbial infection and pathogenesis. Despite the importance of hemocytes in regulating microbial infection, understanding of their basic biology and molecular mechanisms remains limited. Here we combined histomorphology and functional analysis to identify five distinct phagocytic and non-phagocytic hemocyte populations circulating within the Gulf Coast tick Amblyomma maculatum. Depletion of phagocytic hemocytes using clodronate liposomes revealed their function in eliminating bacterial infection. We provide the first direct evidence that an intracellular tick-borne pathogen, Rickettsia parkeri, infects phagocytic hemocytes in Am. maculatum to modify tick cellular immune responses. A hemocyte-specific RNA-seq dataset generated from hemocytes isolated from uninfected and R. parkeri-infected partially blood-fed ticks generated ~40,000 differentially regulated transcripts, >11,000 of which were immune genes. Silencing two differentially regulated phagocytic immune marker genes (nimrod B2 and eater-two Drosophila homologs), significantly reduced hemocyte phagocytosis. Together, these findings represent a significant step forward in understanding how hemocytes regulate microbial homeostasis and vector competence.

Research Note: Analysis of immune responses in broilers after vaccination against Campylobacter jejuni

Campylobacter infections traced mainly to poultry products are major bacterial foodborne zoonoses. Among the many control strategies evaluated at primary poultry level to reduce these infections, vaccination could be a solution, but no effective vaccines are available to date. A better understanding of the immune mechanisms involved in protection against Campylobacter would be helpful for designing novel vaccine strategies. The present study was designed to analyze in more depth the immune responses developed in broilers in order to potentially identify which immune parameters may be important for establishing protection against Campylobacter by comparing the immune responses obtained here with those obtained in a previous study performed on vaccinated specific-pathogen-free Leghorn chickens that presented a partial reduction of Campylobacter after experimental challenge. The protection against Campylobacter colonization was evaluated at different time points over 40 d of rearing, by measuring specific IgY levels in serum and IgA antibodies in bile reflecting the systemic and mucosal humoral responses respectively and the relative expressions of 9 cecal immune marker genes (cytokines and antimicrobial peptides), which reflect the innate and cellular immune responses. Despite no reduction of Campylobacter in the cecum, a systemic immune response over time characterized by the production of specific anti-flagellin IgY was observed, in addition to upregulation of the antimicrobial peptide avian β-defensin (AvBD) 12 gene expression in the cecum of vaccinated broilers compared with the placebo group. However, the levels of specific anti-flagellin mucosal IgA antibodies in the bile as well as the relative expression of other cecal cytokines studied was underexpressed in the vaccinated group or similar in both groups.