Macrophage-related Genes Research Articles

Construction and validation of a TAMRGs prognostic signature for gliomas by integrated analysis of scRNA and bulk RNA sequencing data

BackgroundThis study aimed to construct and validate a prognostic model based on tumor associated macrophage-related genes (TAMRGs) by integrating single-cell RNA sequencing (scRNA-seq) and bulk RNA sequencing (bulk RNA-seq) data. MethodsThe scRNA-seq data of three inhouse glioma tissues were used to identify the tumor-associated macrophages (TAMs) marker genes, the DEGs from the The Cancer Genome Atlas (TCGA) − Genotype-Tissue Expression (GTEx) dataset were used to further select TAMs marker genes. Subsequently, a TAMRG-score was constructed by Least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox regression analysis in the TCGA dataset and validated in the Chinese Glioma Genome Atlas (CGGA) dataset. ResultsWe identified 186 TAMs marker genes, and a total of 6 optimal prognostic genes including CKS2, LITAF, CTSB, TWISTNB, PPIF and G0S2 were selected to construct a TAMRG-score. The high TAMRG-score was significantly associated with worse prognosis (log-rank test, P<0.001). Moreover, the TAMRG-score outperformed the other three models with AUC of 0.808. Immune cell infiltration, TME scores, immune checkpoints, TMB and drug susceptibility were significantly different between TAMRG-score groups. In addition, a nomogram were constructed by combing the TAMRG-score and clinical information (Age, Grade, IDH mutation and 1p19q codeletion) to predict the survival of glioma patients with AUC of 0.909 for 1-year survival. ConclusionThe high TAMRG-score group was associated with a poor prognosis. A nomogram by incorporating TMARG-score could precisely predict glioma survival, and provide evidence for personalized treatment of glioma.

Comprehensive scRNA-seq analysis to identify new markers of M2 macrophages for predicting the prognosis of prostate cancer

Background Prostate cancer (PCa) has become the highest incidence of malignant tumor among men in the world. Tumor microenvironment (TME) is necessary for tumor growth. M2 macrophages play an important role in many solid tumors. This research aimed at the role of M2 macrophages’ prognosis value in PCa. Methods Single-cell RNA-seq (scRNA-seq) data and mRNA expression data were obtained from the Gene Expression Omnibus database (GEO) and The Cancer Genome Atlas (TCGA). Quality control, normalization, reduction, clustering, and cell annotation of scRNA-seq data were preformed using the Seruat package. The sub-populations of the tumor-associated macrophages (TAMs) were analysis and the marker genes of M2 macrophage were selected. Differentially expressed genes (DEGs) in PCa were identified using limma and the immune infiltration was detected using CIBERSORTx. Then, a weighted correlation network analysis (WGCNA) was constructed to identify the M2 macrophage-related modules and genes. Integration of the marker genes of M2 macrophage from scRNA-seq data analysis and hub genes from WGCNA to select the prognostic gene signature based on Univariate and LASSO regression analysis. The risk score was calculated, and the DEGs, biological function, immune characteristics related to risk score were explored. And a predictive nomogram was constructed. CCK8, Transwell, and wound healing were used to verify cell phenotype changes after co-cultured. Results A total of 2431 marker genes of M2 macrophage and 650 hub M2 macrophage-related genes were selected based on scRNA-seq data and WGCNA. Then, 113 M2 macrophage-related genes were obtained by overlapping the scRNA-seq data and WGCNA results. Nine M2 macrophage-related genes (SMOC2, PLPP1, HES1, STMN1, GPR160, ABCG1, MAZ, MYC, and EPCAM) were screened as prognostic gene signatures. M2 risk score was calculated, the DEGs, Immune score, stromal score, ESTIMATE score, tumor purity, and immune cell infiltration, immune checkpoint expression, and responses of immunotherapy and chemotherapy were identified. And a predictive nomogram was constructed. CCK8, Transwell invasion, and wound healing further verified that M2 macrophages promoted the proliferation, invasion, and migration of PCa (p < 0.05). Conclusions We uncovered that M2 macrophages and relevant genes played key roles in promoting the occurrence, development, and metastases of PCa and played as convincing predictors in PCa.

Interleukin-4-Loaded Heparin Hydrogel Regulates Macrophage Polarization to Promote Osteogenic Differentiation.

In bone tissue engineering, biological scaffolds are designed with structural and functional properties that closely resemble the extracellular environment, aiming to establish a microenvironment conducive to osteogenesis. Macrophages hold significant potential for promoting osteogenesis and modulating the biological behavior of tumor cells. Multiple coculture experiments of macrophages and osteoblasts have demonstrated that macrophage polarization significantly impacts osteogenesis. Therefore, exploring bone biomaterials that can modulate macrophage polarization holds great clinical significance. In this study, heparin was modified with maleimide and was used as a raw material to form a hydrogel with 4-am-PEG-SH. The compound was used to polarize macrophages and promote osteogenesis after combining with interleukin 4 (IL-4) by taking advantage of the electronegativity of heparin. The results revealed overexpressed M2 macrophage-related phenotypic genes and cocultivation with MC3T3-E1 cells demonstrated the osteogenesis-promoting effect of the loaded IL-4 heparin hydrogel. Previous research reported that hydrogel loaded with IL-4 can be used as a biomaterial for osteogenesis promotion. Heparin materials used in this paper are derived from clinically anticoagulant drugs and feature a simple operation. The synthesized hydrogel effectively binds cytokines, regulates macrophages to induce osteogenesis and has many potential clinical applications.

Blocking Gremlin1 inhibits M1 macrophage polarization through Notch1/Hes1 signaling pathway in apical periodontitis

Background Gremlin1 is a multifunctional protein whose expression is demonstrated to be involved in a series of physiology and pathological processes. The association between Gremlin1 and apcial periodontitis (AP) has been established. M1-polarized macrophages are crucial immune cells that exacerbate the progression of apical periodontal inflammatory response, but the function of Gremlin1 during macrophages activation in periapical lesions is still unclear. This study attempts to explore the regulatory effects of Gremlin1 on macrophage polarization on apical periodontitis microenviroment. Methods Clinical specimens were used to determine the expression of Gremlin1 in periapical tissues by immunohistochemical (IHC) staining. Then, the disease models of periapical inflammation in rats were established, and adenovirus- associated virus (AAVs) was used to blockade Gremlin1 expression. Lentivirus carrying sh-Gremlin1 particles were used to transfect THP-1 induced M1-subtype macrophages. To assess the expression of associated molecules, Western blot, immunofluorescence staining were performed. Results Gremlin1 was significantly up-regulated in the periapical tissues of subjects with AP as identified by IHC staining, and positively correlated with levels of M1 macrophage-associated genes. Rats AP model with inhibition of Gremlin1 in periapical lesions exhibited limited infiltration of macrophages and decreased expression of M1 macrophage-related genes in periapical lesions. Furthermore, Gremlin1 blockade substantially decreased the Notch1/Hes1 signaling pathway activation level. The in vitro experiments confirmed the above results. Conclusion Taken together, current study illustrated that the Gremlin1 suppression in periapical lesions inhibited M1 macrophage polarization through Notch1/Hes1 axis. Moreover, Gremlin1 may act as a potential candidate in the treatment of AP.

Machine learning developed a macrophage signature for predicting prognosis, immune infiltration and immunotherapy features in head and neck squamous cell carcinoma

Macrophages played an important role in the progression and treatment of head and neck squamous cell carcinoma (HNSCC). We employed weighted gene co-expression network analysis (WGCNA) to identify macrophage-related genes (MRGs) and classify patients with HNSCC into two distinct subtypes. A macrophage-related risk signature (MRS) model, comprising nine genes: IGF2BP2, PPP1R14C, SLC7A5, KRT9, RAC2, NTN4, CTLA4, APOC1, and CYP27A1, was formulated by integrating 101 machine learning algorithm combinations. We observed lower overall survival (OS) in the high-risk group and the high-risk group showed elevated expression levels in most of the immune checkpoint and human leukocyte antigen (HLA) genes, suggesting a strong immune evasion capacity. Correspondingly, TIDE score positively correlated with risk score, implying that high-risk tumors may resist immunotherapy more effectively. At the single-cell level, we noted macrophages in the tumor microenvironment (TME) predominantly stalled in the G2/M phase, potentially hindering epithelial-mesenchymal transition and playing a crucial role in the inhibition of tumor progression. Finally, the proliferation and migration abilities of HNSCC cells significantly decreased after the expression of IGF2BP2 and SLC7A5 reduced. It also decreased migration ability of macrophages and facilitated their polarization towards the M1 direction. Our study constructed a novel MRS for HNSCC, which could serve as an indicator for predicting the prognosis, immune infiltration and immunotherapy for HNSCC patients.

Comprehensive Analysis of Immune Cell Infiltration and M2-Like Macrophage Biomarker Expression Patterns in Atrial Fibrillation.

Macrophages play a crucial role in the progression of AF, closely linked to atrial inflammation and myocardial fibrosis. However, the functions and molecular mechanisms of different phenotypic macrophages in AF are not well understood. This study aims to analyze the infiltration characteristics of atrial immune cells in AF patients and further explore the role and molecular expression patterns of M2 macrophage-related genes in AF. This study integrates single-cell and large-scale sequencing data to analyze immune cell infiltration and molecular characterization of the LAA in patients with AF, using SR as a control group. CIBERSORT assesses immune cell types in LAA tissues; WGCNA identifies signature genes; cell clustering analyzes cell types and subpopulations; cell communication explores macrophage interactions; hdWGCNA identifies M2 macrophage gene modules in AF. AF biomarkers are identified using LASSO and Random Forest, validated with ROC curves and RT-qPCR. Potential molecular mechanisms are inferred through TF-miRNA-mRNA networks and single-gene enrichment analyses. Myeloid cell subsets varied considerably between the AF and SR groups, with a significant increase in M2 macrophages in the AF group. Signals of inflammation and matrix remodeling were observed in AF. M2 macrophage-related genes IGF1, PDK4, RAB13, and TMEM176B were identified as AF biomarkers, with RAB13 and TMEM176B being novel markers. A TF-miRNA-mRNA network was constructed using target genes, which are enriched in the PPAR signaling pathway and fatty acid metabolism. Over infiltration of M2 macrophages may be an important factor in the progression of AF. The M2 macrophage-related genes IGF1, RAB13, TMEM176B and PDK4 may regulate the progression of AF through the PPAR signaling pathway and fatty acid metabolism.

Comprehensive transcriptomic analysis unveils macrophage-associated genes for establishing an abdominal aortic aneurysm diagnostic model and molecular therapeutic framework

BackgroundAbdominal aortic aneurysm (AAA) is a highly lethal cardiovascular disease. The aim of this research is to identify new biomarkers and therapeutic targets for the treatment of such deadly diseases.MethodsSingle-sample gene set enrichment analysis (ssGSEA) and CIBERSORT algorithms were used to identify distinct immune cell infiltration types between AAA and normal abdominal aortas. Single-cell RNA sequencing data were used to analyse the hallmark genes of AAA-associated macrophage cell subsets. Six macrophage-related hub genes were identified through weighted gene co-expression network analysis (WGCNA) and validated for expression in clinical samples and AAA mouse models. We screened potential therapeutic drugs for AAA through online Connectivity Map databases (CMap). A network-based approach was used to explore the relationships between the candidate genes and transcription factors (TFs), lncRNAs, and miRNAs. Additionally, we also identified hub genes that can effectively identify AAA and atherosclerosis (AS) through a variety of machine learning algorithms.ResultsWe obtained six macrophage hub genes (IL-1B, CXCL1, SOCS3, SLC2A3, G0S2, and CCL3) that can effectively diagnose abdominal aortic aneurysm. The ROC curves and decision curve analysis (DCA) were combined to further confirm the good diagnostic efficacy of the hub genes. Further analysis revealed that the expression of the six hub genes mentioned above was significantly increased in AAA patients and mice. We also constructed TF regulatory networks and competing endogenous RNA networks (ceRNA) to reveal potential mechanisms of disease occurrence. We also obtained two key genes (ZNF652 and UBR5) through a variety of machine learning algorithms, which can effectively distinguish abdominal aortic aneurysm and atherosclerosis.ConclusionOur findings depict the molecular pharmaceutical network in AAA, providing new ideas for effective diagnosis and treatment of diseases.

FPR1, as a Potential Biomarker of Diagnosis and Infliximab Therapy Responses for Crohn's Disease, is Related to Disease Activity, Inflammation and Macrophage Polarization.

Crohn's disease (CD) represents a multifaceted inflammatory gastrointestinal condition, with a profound significance placed on unraveling its molecular pathways to enhance both diagnostic capabilities and therapeutic interventions. This study focused on identifying a robust macrophage-related signatures (MacroSig) for diagnosing CD, emphasizing the role of FPR1 in macrophage polarization and its implications in CD. Expression profiles from intestinal biopsies and macrophages of 1804 CD patients were retrieved from the Gene Expression Omnibus (GEO). Utilizing CIBERSORTx, differential expression analysis, and weighted correlation network analysis to to identify macrophage-related genes (MRGs). By unsupervised clustering, distinct clusters of CD were identified. Potential biomarkers were identified via using four machine learning algorithms, leading to the establishment of MacroSig which combines insights from 12 machine learning algorithms. Furthermore, the expression of FPR1 was verified in intestinal biopsies of CD patients and two murine experimental colitis models. Finally, we further explored the role of FPR1 in macrophage polarization through single-cell analysis as well as through the study of RAW264.7 cells and peritoneal macrophages. Two distinct clusters with differential levels of macrophage infiltration and inflammation were identified. The MacroSig, which included FPR1 and LILRB2, exhibited high diagnostic accuracy and outperformed existing biomarkers and signatures. Clinical analysis demonstrated a strong correlation of FPR1 with disease activity, endoscopic inflammation status, and response to infliximab treatment. The expression levels of FPR1 were validated in our CD cohort by immunohistochemistry and confirmed in two colitis mouse models. Single-cell analysis indicated that FPR1 is predominantly expressed in macrophages and monocytes. In vitro studies demonstrated that FPR1 was upregulated in M1 macrophages, and its activation promoted M1 polarization. We developed a promising diagnostic signature for CD, and targeting FPR1 to modulate macrophage polarization may represent a novel therapeutic strategy.

Identification of a Macrophage marker gene signature to evaluate immune infiltration and therapeutic response in hepatocellular carcinoma

BackgroundOnly a minority of hepatocellular carcinoma (HCC) patients can benefit from systemic regimens. Macrophages, which abundantly infiltrate in HCC, could mediate tumour microenvironment remodelling and immune escape, proving to be powerful weapons in combating HCC. Thus, a deeper understanding of macrophages is necessary for improving existing antitumour treatments. MethodsWith a series of bioinformatic approaches, we comprehensively explored the role of macrophage-related genes in human HCCs from multiple single-cell and bulk RNA sequencing datasets. Unsupervised clustering was performed to cluster the macrophage marker genes (MMGs). GSVA and functional enrichment analysis were used to elucidate the functional differences among the MMG-associated clusters. Subsequently, a component analysis algorithm was used to construct a Macrosig score, and the prognosis, biological characteristics, mutation profile, TME cell infiltration status and drug response of patients with different Macrosig scores were further analysed. ResultsWe identified 13 MMGs in 574 HCC samples, based on which three MMG-associated clusters were defined. Overall survival time, clinicopathological features and immune infiltration scores differed among the different clusters. On this basis, 12 hub genes were identified among these clusters; subsequently, a scoring system was constructed to determine the Macrosig score. Importantly, patients with low-Macrosig scores, characterized by increased immune infiltration, increased mutation frequency and increased immune checkpoint expression, including CTLA-4, LAG3, PDCD1 and TIGIT, exhibited enhanced efficacy of immunotherapy when validated in an external database. Moreover, a low-Macrosig score indicates increased sensitivity to AZD.2281, A.443654, ABT.263, ABT.888, AG.014699 and ATRA, while a high Macrosig score indicates increased sensitivity to AZD6482, AKT inhibitor VIII, AS601245, AZ628, AZD.0530 and AZD6244. ConclusionsA novel scoring system was constructed to guide more effective prognostic evaluation and tailoring therapeutic regimens for HCC patients.

Paeoniae Radix Alba effectively attenuates Polygonum multiflorum Thunb. -induced idiosyncratic liver injury by modulating M2 macrophage polarization

Objective: Polygonum multiflorum Thunb. (PM) is a commonly used tonic herb known to cause idiosyncratic drug-induced liver injury (IDILI). This study explored the detoxification effects and potential mechanisms of action of Paeoniae Radix Alba (PRA) on PM-induced IDILI. Methods: Network pharmacology analysis was utilized to predict the related targets of "PRA-PM-innate immunity.” A non-hepatotoxic lipopolysaccharide (LPS) and PM-induced IDILI model was used to evaluate the detoxification effects of PRA by measuring liver function indicators, pathological examinations, and macrophage-related factors. Bone marrow-derived macrophages (BMDMs) were stimulated with IL-4 to differentiate into M2 macrophages, and the effects of PM and PRA on M2 macrophage polarization were explored. Results: Target screening of "PRA-PM-innate immunity" identified 21 intersecting targets, most of which were closely associated with macrophage polarization. In rat models of IDILI induced by PM, the combined use of PRA significantly reduced the extent of liver damage and the levels of inflammatory factors, while promoting the expression of M2 macrophage-related factors such as IL-4, IL-10, Arg1, and CD206. In vitro, PM dose-dependently inhibited the expression of the Arg1 protein and M2 macrophage-related genes, whereas PRA exhibited the opposite effect. When used in combination, PRA ameliorated the inhibitory effect of PM on M2 macrophage polarization. Conclusions: Our results demonstrate that PRA has a therapeutic effect on PM-induced IDILI; its mechanism may involve alleviating liver injury by promoting M2 macrophage polarization, thus reducing the expression of inflammatory factors.

Mechanistic study of pre-eclampsia and macrophage-associated molecular networks: bioinformatics insights from multiple datasets

BackgroundPre-eclampsia is a pregnancy-related disorder characterized by hypertension and proteinuria, severely affecting the health and quality of life of patients. However, the molecular mechanism of macrophages in pre-eclampsia is not well understood.MethodsIn this study, the key biomarkers during the development of pre-eclampsia were identified using bioinformatics analysis. The GSE75010 and GSE74341 datasets from the GEO database were obtained and merged for differential analysis. A weighted gene co-expression network analysis (WGCNA) was constructed based on macrophage content, and machine learning methods were employed to identify key genes. Immunoinfiltration analysis completed by the CIBERSORT method, R package “ClusterProfiler” to explore functional enrichment of these intersection genes, and potential drug predictions were conducted using the CMap database. Lastly, independent analysis of protein levels, localization, and quantitative analysis was performed on placental tissues collected from both preeclampsia patients and healthy control groups.ResultsWe identified 70 differentially expressed NETs genes and found 367 macrophage-related genes through WGCNA analysis. Machine learning identified three key genes: FNBP1L, NMUR1, and PP14571. These three key genes were significantly associated with immune cell content and enriched in multiple signaling pathways. Specifically, these genes were upregulated in PE patients. These findings establish the expression patterns of three key genes associated with M2 macrophage infiltration, providing potential targets for understanding the pathogenesis and treatment of PE. Additionally, CMap results suggested four potential drugs, including Ttnpb, Doxorubicin, Tyrphostin AG 825, and Tanespimycin, which may have the potential to reverse pre-eclampsia.ConclusionStudying the expression levels of three key genes in pre-eclampsia provides valuable insights into the prevention and treatment of this condition. We propose that these genes play a crucial role in regulating the maternal-fetal immune microenvironment in PE patients, and the pathways associated with these genes offer potential avenues for exploring the molecular mechanisms underlying preeclampsia and identifying therapeutic targets. Additionally, by utilizing the Connectivity Map database, we identified drug targets like Ttnpb, Doxorubicin, Tyrphostin AG 825, and Tanespimycin as potential clinical treatments for preeclampsia.

A risk scoring model based on M2 macrophage-related genes for predicting prognosis of HBV-related hepatocellular carcinoma

To investigate the prognostic value of M2 macrophage-related genes (MRG) in hepatitis B virus (HBV)- related hepatocellular carcinoma (HCC). The transcriptome data of 73 patients with HBV-related HCC were obtained from TCGA database, and the MRG modules were identified by WGCNA. The MRG-based risk scoring model was constructed by LASSO regression analysis and validated using an external dataset. The correlation of the risk score with immune cell infiltration and drug sensitivity of HCC were analyzed with CIBERSORT and R. pRRophetic. The signaling pathways of the differential genes between the high- and low-risk groups were investigated using GSVA and GSEA enrichment analyses, and MRG expressions at the single cell level were validated using R.Seurat. The cell interaction intensity was analyzed by R.Cellchat to identify important cell types related to HCC progression. MRG expression levels were detected by RT-qPCR in THP-1 cells with HCC-conditioned medium-induced M2 polarization and in HBV-positive HCC cells. A high M2 macrophage infiltration level was significantly correlated with a poor prognosis of HCC, and 5 hub MRG (VTN, GCLC, PARVB, TRIM27, and GMPR) were identified. The overall survival of HCC patients was significantly lower in the high-risk than in the low-risk group. The high- and the low-risk groups showed significant enrichment of M2 macrophages and na?ve B cells, respectively, and were sensitive to BI. 2536 and to AG. 014699, AKT. inhibitor. Ⅷ, AZD. 0530, AZD7762, and BMS. 708163, respectively. The proliferation-related and metabolism-related pathways were enriched in the high-risk group, where monocytes showed the most active cell interactions during HCC progression. VTN was significantly upregulated in HCC cell lines, while GCLC, PARVB, TRIM27, and GMPR were upregulated in M2 THP-1 cells. The MRG-based risk scoring model can accurately predict the prognosis of HBV-related HCC and reveal the differences in tumor microenvironment to guide precision treatment of the patients.

Upregulation of HMOX1 associated with M2 macrophage infiltration and ferroptosis in proliferative diabetic retinopathy

The roles of immune cell infiltration and ferroptosis in the progression of proliferative diabetic retinopathy (PDR) remain unclear. To identify upregulated molecules associated with immune infiltration and ferroptosis in PDR, GSE60436 and GSE102485 datasets were downloaded from the Gene Expression Omnibus (GEO). Genes associated with immune cell infiltration were examined through Weighted Gene Co-expression Network Analysis (WGCNA) and CIBERSORT algorithm. Common differentially expressed genes (DEGs) were intersected with ferroptosis-associated and immune cell infiltration-related genes. Localization of cellular expression was confirmed by single-cell analysis of GSE165784 dataset. Findings were validated by qRT-PCR, ELISA, Western blotting, and immunofluorescence staining. As a result, the infiltration of M2 macrophages was significantly elevated in fibrovascular membrane samples from PDR patients than the retinas of control subjects. Analysis of DEGs, M2 macrophage-related genes and ferroptosis-related genes identified three hub intersecting genes, TP53, HMOX1 and PPARA. qRT-PCR showed that HMOX1 was significantly higher in the oxygen-induced retinopathy (OIR) mouse model retinas than in controls. Single-cell analysis confirmed that HMOX1 was located in M2 macrophages. ELISA and western blotting revealed elevated levels of HMOX1 in the vitreous humor of PDR patients and OIR retinas, and immunofluorescence staining showed that HMOX1 co-localized with M2 macrophages in the retinas of OIR mice. This study offers novel insights into the mechanisms associated with immune cell infiltration and ferroptosis in PDR. HMOX1 expression correlated with M2 macrophage infiltration and ferroptosis, which may play a crucial role in PDR pathogenesis.

Abstract PO4-25-01: Selective elimination of CD169+ macrophages in lymph nodes invaded by breast cancers

Abstract Lymph node metastasis is a prognostically significant factor in breast cancer, though the colonization mechanism of cancer cells in this immune cell-rich organ remains elusive. This study aimed to elucidate the impact of breast cancer on the lymph node immune cell landscape. Multiscale transcriptomic analyses were performed on both metastatic and non-metastatic lymph node samples from breast cancer patients with lymph node metastasis. Twenty laser-micro-dissected sections were obtained from 17 lymph nodes across six breast cancer patients at stages II–III, with each patient contributing both types of lymph nodes for direct comparison. Comparing the transcriptomes of paired lymph nodes with and without metastasis from the same patients revealed selective downregulation of CD169+ macrophage-related genes in metastatic lymph nodes. The spatial transcriptome indicated a potential depletion of CD169+ macrophages, initiators of anticancer immunity, from their residence (sinuses) in metastatic lymph nodes, while other principal immune cell types were unaltered. Mass spectrometry imaging revealed that the numbers of CD169+ macrophages were smaller in the metastatic lymph nodes than in the non-metastatic lymph nodes, suggesting that cancer cells uprooted CD169+ macrophages from the lymph nodes. Conversely, the count of B, T, Treg, and CD11c+ cells remained comparable in both lymph node types, albeit an enrichment of Treg cells around metastasized cancer tissues was observed. Additional immunohistochemistry analysis of 315 non-metastatic lymph nodes and 159 metastatic lymph nodes from 58 patients with breast cancer showed that a reduced CD169+ macrophage population was prevalent in various breast cancer subtypes. A subset of metastatic lymph nodes (37 out of 159) displayed a complete absence of detectable CD169+ macrophages. The data also depicted a gradual decline in CD169+ macrophages correlating with the pN classification, while no correlation was identified with pathological tumor size classification (pT) or metastasized cancer volume. The data suggest precedence of CD169+ macrophage elimination over other reported immune cell abnormalities, such as cell number and metabolic irregularities. CD169+ macrophages are a unique type of resident macrophages in the lymphoid organs that present cancer-derived antigens to CD8+ cells. The antigen-presenting role of CD169+ macrophages to T cells, a pivotal step in adaptive immunity, signifies the catastrophic implications of their suppression. This study underscores CD169+ macrophage suppression as a pronounced pathological phenotype in lymph nodes with breast cancer metastasis, thereby establishing it as a critical future therapeutic target. Citation Format: Yurina Maeshima, Tatsuki R. Kataoka, Alexis Vandenbon, Masahiro Hirata, Yasuhide Takeuchi, Yutaka Suzuki, Yukiko Fukui, Yumiko Ibi, Hironori Haga, Satoshi Morita, Masakazu Toi, Shinpei Kawaoka, Kosuke Kawaguchi. Selective elimination of CD169+ macrophages in lymph nodes invaded by breast cancers [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO4-25-01.

Machine learning and deep learning to identifying subarachnoid haemorrhage macrophage-associated biomarkers by bulk and single-cell sequencing.

We investigated subarachnoid haemorrhage (SAH) macrophage subpopulations and identified relevant key genes for improving diagnostic and therapeutic strategies. SAH rat models were established, and brain tissue samples underwent single-cell transcriptome sequencing and bulk RNA-seq. Using single-cell data, distinct macrophage subpopulations, including a unique SAH subset, were identified. The hdWGCNA method revealed 160 key macrophage-related genes. Univariate analysis and lasso regression selected 10 genes for constructing a diagnostic model. Machine learning algorithms facilitated model development. Cellular infiltration was assessed using the MCPcounter algorithm, and a heatmap integrated cell abundance and gene expression. A 3 × 3 convolutional neural network created an additional diagnostic model, while molecular docking identified potential drugs. The diagnostic model based on the 10 selected genes achieved excellent performance, with an AUC of 1 in both training and validation datasets. The heatmap, combining cell abundance and gene expression, provided insights into SAH cellular composition. The convolutional neural network model exhibited a sensitivity and specificity of 1 in both datasets. Additionally, CD14, GPNMB, SPP1 and PRDX5 were specifically expressed in SAH-associated macrophages, highlighting its potential as a therapeutic target. Network pharmacology analysis identified some targeting drugs for SAH treatment. Our study characterised SAH macrophage subpopulations and identified key associated genes. We developed a robust diagnostic model and recognised CD14, GPNMB, SPP1 and PRDX5 as potential therapeutic targets. Further experiments and clinical investigations are needed to validate these findings and explore the clinical implications of targets in SAH treatment.

Comprehensive analysis of macrophage-related genes in prostate cancer by integrated analysis of single-cell and bulk RNA sequencing.

Macrophages, as essential components of the tumor immune microenvironment (TIME), could promote growth and invasion in many cancers. However, the role of macrophages in tumor microenvironment (TME) and immunotherapy in PCa is largely unexplored at present. Here, we investigated the roles of macrophage-related genes in molecular stratification, prognosis, TME, and immunotherapeutic response in PCa. Public databases provided single-cell RNA sequencing (scRNA-seq) and bulk RNAseq data. Using the Seurat R package, scRNA-seq data was processed and macrophage clusters were identified automatically and manually. Using the CellChat R package, intercellular communication analysis revealed that tumor-associated macrophages (TAMs) interact with other cells in the PCa TME primarily through MIF - (CD74+CXCR4) and MIF - (CD74+CD44) ligand-receptor pairs. We constructed coexpression networks of macrophages using the WGCNA to identify macrophage-related genes. Using the R package ConsensusClusterPlus, unsupervised hierarchical clustering analysis identified two distinct macrophage-associated subtypes, which have significantly different pathway activation status, TIME, and immunotherapeutic efficacy. Next, an 8-gene macrophage-related risk signature (MRS) was established through the LASSO Cox regression analysis with 10-fold cross-validation, and the performance of the MRS was validated in eight external PCa cohorts. The high-risk group had more active immune-related functions, more infiltrating immune cells, higher HLA and immune checkpoint gene expression, higher immune scores, and lower TIDE scores. Finally, the NCF4 gene has been identified as the hub gene in MRS using the "mgeneSim" function.

Vitamin A enhanced periosteal osteoclastogenesis is associated with increased number of tissue-derived macrophages/osteoclast progenitors

A deleterious effect of elevated levels of vitamin A on bone health has been reported in numerous clinical studies. Mechanistic studies in rodents have shown that numbers of periosteal osteoclasts are increased, while endocortical osteoclasts are simultaneously decreased by vitamin A treatment. These observations indicate that osteoclastogenesis on the endocortical and periosteal surfaces of bone is differentially controlled by vitamin A. The present study investigated the in vitro and in vivo effect of all-trans retinoic acid (ATRA), the active metabolite of vitamin A, on periosteal osteoclast progenitors. Mouse calvarial bone cells were cultured in media containing ATRA, with or without the osteoclastogenic cytokine RANKL, on plastic dishes or bone discs. Whereas ATRA did not stimulate osteoclast formation alone, the compound robustly potentiated the formation of RANKL-induced bone resorbing osteoclasts. This effect was due to stimulation by ATRA (EC50 ∼3nM) on the numbers of macrophages/osteoclast progenitors in the bone cell cultures, as assessed by mRNA and protein expression of several macrophage and osteoclast progenitor cell markers, such as M-CSF receptor, RANK, F4/80 and CD11b, as well as by FACS-analysis of CD11b+/F480+/Gr1- cells. The stimulation of macrophage numbers in the periosteal cell cultures was not mediated by increased M-CSF or IL-34. In contrast, ATRA did not enhance macrophages in bone marrow cell cultures. Importantly, ATRA treatment upregulated the mRNA expression of several macrophage-related genes also in the periosteum of tibia in adult mice. These observations demonstrate a novel mechanism by which vitamin A enhances osteoclast formation specifically on periosteal surfaces.

A prognostic model of idiopathic pulmonary fibrosis constructed based on macrophage and mitochondria-related genes

BackgroundStudies have shown that mitochondrial function and macrophages may play a role in the development of idiopathic pulmonary fibrosis (IPF). However, the understanding of the interactions and specific mechanisms between mitochondrial function and macrophages in pulmonary fibrosis is still very limited.MethodsTo construct a prognostic model for IPF based on Macrophage- related genes (MaRGs) and Mitochondria-related genes (MitoRGs), differential analysis was performed to achieve differentially expressed genes (DEGs) between IPF and Control groups in the GSE28042 dataset. Then, MitoRGs, MaRGs and DEGs were overlapped to screen out the signature genes. The univariate Cox analysis and the least absolute shrinkage and selection operator (LASSO) algorithm were implemented to achieve key genes. Furthermore, the independent prognostic analysis was employed. The ingenuity pathway analysis (IPA) was employed to further understand the molecular mechanisms of key genes.Next, the immune infiltration analysis was implemented to identify differential immune cells between two risk subgroups.ResultsThere were 4791 DEGs between IPF and Control groups. Furthermore, 26 signature genes were achieved by the intersection processing. Three key genes including ALDH2, MCL1, and BCL2A1 were achieved, and the risk model based on the key genes was created. In addition, a nomogram for survival forecasting of IPF patients was created based on riskScore, Age, and Gender, and we found that key genes were associated with classical pathways including ‘Apoptosis Signaling’, ‘PI3K/AKT Signaling’, and so on. Next, two differential immune cells including Monocytes and CD8 T cells were identified between two risk subgroups. Moreover, we found that MIR29B2CHG and hsa-mir-1-3p could regulate the expression of ALDH2.ConclusionWe achieved 3 key genes including ALDH2, MCL1,, and BCL2A1 associated with IPF, providing a new theoretical basis for clinical treatment of IPF.

Abstract 106: Selective elimination of CD169+ macrophages in lymph nodes invaded by breast cancers

Abstract Background: Lymph node metastasis is known as one of the strongest prognostic factors in breast cancer. The invasion mechanism of metastasized cancer cells in such immune cell-rich organs remains clear. Here, we aimed to elucidate the impact of metastasized cancer cells on the lymph node immune cell landscape. Methods: Multiscale transcriptomic analyses were performed on both metastatic and nonmetastatic lymph node samples from breast cancer patients with lymph node metastasis. As cancer cells interact with lymphocytes in lymph nodes in direct, proximal, and distant manners, we tried to capture the direct and proximal impact on immune cells in invaded lymph nodes by comparing paired metastatic and non-metastatic lymph node samples. Laser-micro-dissected sections were obtained from 17 lymph nodes across six breast cancer patients at stages II‒III, with each patient contributing both types of lymph nodes for direct comparison. We performed bulk transcriptome, spatial transcriptome, and imaging mass cytometry to analyze the obtained lymph nodes. Furthermore, we conducted immunohistochemistry analyses against a larger patient cohort (574 lymph nodes from 58 patients). Results: Comparing the transcriptomes of paired lymph nodes with and without metastasis from the same patients revealed selective downregulation of CD169+ macrophage-related genes in metastatic lymph nodes. The spatial transcriptome indicated a potential depletion of CD169+macrophages, initiators of anticancer immunity, from their residence in metastatic lymph nodes, while other principal immune cell types were unaltered. Mass cytometry imaging revealed that the numbers of CD169+ macrophages were smaller in the metastatic lymph nodes than in the nonmetastatic lymph nodes. Conversely, the number of B cells, CD4+ T cells, CD8+T cells, Treg cells, and CD11c+ cells remained comparable in both lymph node types. Additional immunohistochemistry analysis of 315 nonmetastatic lymph nodes and 159 metastatic lymph nodes from 58 patients with breast cancer showed that a reduced CD169+ macrophage population was prevalent in all breast cancer subtypes. CD169+ macrophages gradually decreased in correlation with pathological lymph node metastasis status, while no correlation was identified with pathological tumor size classification or metastasized cancer volume in invaded lymph nodes. Discussion: CD169+ macrophages are a unique type of resident macrophages in the lymphoid organs that present cancer-derived antigens to CD8+ T cells. The antigen-presenting role of CD169+ macrophages to T cells is a pivotal step in adaptive immunity. The elimination of CD169+ macrophage implies the disruption of the first step of the initial immune response. This study uncovered CD169+ macrophage suppression as a pronounced pathological phenotype in lymph nodes with breast cancer metastasis, thereby establishing it as a critical future therapeutic target. Citation Format: Yurina Maeshima, Tatsuki R. Kataoka, Alexis Vandenbon, Masahiro Hirata, Yasuhide Takeuchi, Yutaka Suzuki, Yukiko Fukui, Yumiko Ibi, Hironori Haga, Satoshi Morita, Masakazu Toi, Shinpei Kawaoka, Kosuke Kawaguchi. Selective elimination of CD169+ macrophages in lymph nodes invaded by breast cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 106.

Identification of macrophage-related molecular subgroups and risk signature in colorectal cancer based on a bioinformatics analysis

Macrophages play a crucial role in tumor initiation and progression, while macrophage-associated gene signature in colorectal cancer (CRC) patients has not been investigated. Our study aimed to identify macrophage-related molecular subgroups and develop a macrophage-related risk model to predict CRC prognosis. The mRNA expression profile and clinical information of CRC patients were obtained from TCGA and GEO databases. CRC patients from TCGA were divided into high and low macrophage subgroups based on the median macrophage score. The ESTIMATE and CIBERSORT algorithms were used to assess immune cell infiltration between subgroups. GSVA and GSEA analyses were performed to investigate differences in enriched pathways between subgroups. Univariate and LASSO Cox regression were used to build a prognostic risk model, which was further validated in the GSE39582 dataset. A high macrophage score subgroup was associated with poor prognosis, highly activated immune-related pathways and an immune-active microenvironment. A total of 547 differentially expressed macrophage-related genes (DEMRGs) were identified, among which seven genes (including RIMKLB, UST, PCOLCE2, ZNF829, TMEM59L, CILP2, DTNA) were identified by COX regression analyses and used to build a risk score model. The risk model shows good predictive and diagnostic values for CRC patients in both TCGA and GSE39852 datasets. Furthermore, multivariate Cox regression analysis showed that the risk score was an independent risk factor for overall survival in CRC patients. Our findings provided a novel insight into macrophage heterogeneity and its immunological role in CRC. This risk score model may serve as an effective prognostic tool and contribute to personalised clinical management of CRC patients.