Comprehensive Landscape of Immune Infiltration and Aberrant Pathway Activation in Ischemic Stroke

Systemic-inflammatory indices and clinical outcomes in patients with anterior circulation acute ischemic stroke undergoing successful endovascular thrombectomy

Background

There is a lack of comprehensive profile assessment on complete blood count (CBC)-derived systemic-inflammatory indices, and their correlations with clinical outcome in patients with anterior circulation acute ischemic stroke (AIS) who achieved successful recanalization by endovascular thrombectomy (EVT).

Methods

Patients with anterior circulation AIS caused by large vessel occlusion (AIS-LVO) were retrospectively screened from December 2018 to December 2022. Systemic-inflammatory indices including ratios of neutrophil-to-lymphocyte (NLR), monocyte-to-lymphocyte (MLR), platelet-to-lymphocyte (PLR), and platelet-to-neutrophil (PNR), systemic immune-inflammation index (SII), systemic inflammation response index (SIRI), and aggregate inflammation systemic index (AISI) on admission and the first day post-EVT were calculated. Their correlations with symptomatic intracranial hemorrhage (sICH) and unfavorable 90-day functional outcome (modified Rankin Scale score of 3-6) were analyzed.

Results

A total of 482 patients [65 (IQR, 56-72) years; 33 % female] were enrolled, of which 231 (47.9 %) had unfavorable 90-day outcome and 50 (10.4 %) developed sICH. Day 1 neutrophil and monocyte counts, NLR, MLR, PLR, SII, SIRI, and AISI were increased, while lymphocyte and PNR were decreased compared to their admission levels. In multivariate analyses, neutrophil count, NLR, SII, and AISI on day 1 were independently associated with 90-day functional outcome. Moreover, day 1 neutrophil count, NLR, MLR, PLR, PNR, SII, and SIRI were independently linked to the occurrence of sICH. No admission variables were identified as independent risk factors for patient outcomes.

Conclusion

CBC-derived systemic-inflammatory indices measured on the first day after successful EVT are predictive of 90-day functional outcome and the sICH occurrence in patients with anterior circulation AIS-LVO.

Bioinformatics Approach to Identify the Pathogenetic Link of Gut Microbiota-Derived Short-Chain Fatty Acids and Ischemic Stroke

Stroke is a life-threatening condition that impairs the arteries and causes neurological impairment. The incidence of stroke is increasing year by year with the arrival of the aging population. Thus, there is an urgent need for early stroke diagnosis. Short-chain fatty acids (SCFAs) can modulate the central nervous system and directly and indirectly impact behavioral and cognitive functions. This study aimed to investigate the connection between SCFA metabolism and stroke development via bioinformatic analysis. Initially, the Gene Set Enrichment Analysis (GSEA) and immune cell infiltration analysis were performed based on RNA data from stroke patients to comprehend the mechanisms governing stroke pathogenesis. The functional analysis, including Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Protein-Protein Interaction (PPI), was performed based on the Differentially Expressed Gene (DEG) selected by the limma package. 1220 SCFA metabolism-related genes screened from Genecards databases were intersected with 242 genes in main modules determined by Weighted Gene Co-Expression Network Analysis (WGCNA), and the final 10 SCFA key genes were obtained. GO analysis revealed that these genes were involved in immune response processes. Through lasso regression analyses, we established a stroke early diagnosis model and selected 6 genes with diagnostic value. The genes were validated by the area under curve (AUC) values and had a relatively good diagnostic performance. Finally, 4 potential therapeutic drugs targeting these genes were predicted using the Drug Signatures Database (DSigDB) via Enrichr. In conclusion, this paper analyzes the involvement of SCFAs in the complex gut-brain axis mechanism, which contributes to developing new targets for treating central nervous system diseases and provides new ideas for early ischemic stroke diagnosis.

Identification of novel biomarkers and immune infiltration characteristics of ischemic stroke based on comprehensive bioinformatic analysis and machine learning

Background

Ischemic stroke (IS) is one of most common causes of disability in adults worldwide. However, there is still a lack of effective and reliable diagnostic markers and therapeutic targets in IS. Furthermore, immune cell dysfunction plays an important role in the pathogenesis of IS. Hence, in-depth research on immune-related targets in progressive IS is urgently needed.

Methods

Expression profile data from patients with IS were downloaded from the Gene Expression Omnibus (GEO) database. Then, differential expression analysis and weighted gene coexpression network analysis (WGCNA) were performed to identify the significant modules and differentially expressed genes (DEGs). Key genes were obtained and used in functional enrichment analyses by overlapping module genes and DEGs. Next, hub candidate genes were identified by utilizing three machine learning algorithms: least absolute shrinkage and selection operator (LASSO), random forest, and support vector machine-recursive feature elimination (SVM-RFE). Subsequently, a diagnostic model was constructed based on the hub genes, and receiver operating characteristic (ROC) curves were constructed to validate the performances of the predictive models and candidate genes. Finally, the immune cell infiltration landscape of IS was explored with the CIBERSORT deconvolution algorithm.

Results

A total of 40 key DEGs were identified based on the intersection of the DEGs and module genes, and we found that these genes were mainly enriched in the regulation of lipolysis in adipocytes, neutrophil extracellular trap formation and complement and coagulation cascades. Based on the results from three advanced machine learning algorithms, we obtained 7 hub candidate genes (ABCA1, ARG1, C5AR1, CKAP4, HMFN0839, SDCBP and TLN1) as diagnostic biomarkers of IS and developed a reliable nomogram with high predictive performance (AUC = 0.987). In addition, immune cell infiltration dysregulation was implicated in IS, and compared with those in the normal group, IS patients had increased fractions of gamma delta T cells, monocytes, M0 macrophages, M2 macrophages and neutrophils and clearly lower percentages of naive B cells, CD8 T cells, CD4+ memory T cells, follicular helper T cells, regulatory T cells (Tregs) and resting dendritic cells. Furthermore, correlation analysis indicated a significant correlation between the hub genes and immune cells in progressive IS.

Conclusion

In conclusion, our study identified 7 hub genes as diagnostic biomarkers and established a reliable model to predict the occurrence of IS. Meanwhile, we explored the immune cell infiltration pattern and investigated the relationship between candidate genes and immune cells in the pathogenesis of IS. Hence, our study provides new insights into the diagnosis and treatment of IS.

Analysis and identification of oxidative stress-ferroptosis related biomarkers in ischemic stroke

Studies have shown that a series of molecular events caused by oxidative stress is associated with ferroptosis and oxidation after ischemic stroke (IS). Differential analysis was performed to identify differentially expressed mRNA (DEmRNAs) between IS and control groups. Critical module genes were identified using weighted gene co-expression network analysis (WGCNA). DEmRNAs, critical module genes, oxidative stress-related genes (ORGs), and ferroptosis-related genes (FRGs) were crossed to screen for intersection mRNAs. Candidate mRNAs were screened based on the protein-protein interaction (PPI) network and the MCODE plug-in. Biomarkers were identified based on two types of machine learning algorithms, and the intersection was obtained. Functional items and related pathways of the biomarkers were identified using gene set enrichment analysis (GSEA). Finally, single-sample GSEA (ssGSEA) and Wilcoxon tests were used to identify differential immune cells. An miRNA-mRNA-TF network was created. Quantitative real-time polymerase chain reaction (qRT-PCR) was performed to verify the expression levels of biomarkers in the IS and control groups. There were 8287 DE mRNAs between the IS and control groups. The genes in the turquoise module were selected as critical module genes for IS. Thirty intersecting mRNAs were screened for overlaps. Seventeen candidate mRNAs were also identified. Four biomarkers (CDKN1A, GPX4, PRDX1, and PRDX6) were identified using two types of machine-learning algorithms. GSEA results indicated that the biomarkers were associated with steroid biosynthesis. Nine types of immune cells (activated B cells and neutrophils) were markedly different between the IS and control groups. We identified 3747 miRNA-mRNA-TF regulatory pairs in the miRNA-mRNA-TF regulatory network, including hsa-miR-4469-CDKN1A-BACH2 and hsa-miR-188-3p-GPX4-ATF2. CDKN1A, PRDX1, and PRDX6 were upregulated in IS samples compared with control samples. This study suggests that four biomarkers (CDKN1A, GPX4, PRDX1, and PRDX6) are significantly associated with IS. This study provides a new reference for the diagnosis and treatment of IS.

Analysis and Regulatory Mechanisms of Platelet-Related Genes in Patients with Ischemic Stroke

It was found that ischemic stroke (IS) was associated with abnormal platelet activity and thrombosis. However, the potential significance of platelet-related genes (PRGs) in IS still needs to be more thorough. This study extracted IS-related transcriptome datasets from the Gene Expression Omnibus (GEO) database. The target genes were obtained by intersecting the differentially expressed genes (DEGs), the module genes related to IS, and PRGs, where the key genes of IS were screened by two machine learning algorithms. The key genes-based diagnostic model was constructed. Gene set enrichment analysis (GSEA) and the immune microenvironment analyses were analyzed targeting key genes in IS. The co-expression, TF-mRNA, and competitive endogenous RNAs (ceRNA) regulatory networks were constructed to reveal the potential regulation of key genes. Potential drugs targeting key genes were predicted as well. Totals of eight target genes were obtained and were associated with immune-related functions. Four platelet-related key genes were acquired, which were related to immunity and energy metabolism. The abnormal expressions of DOCK8, GIMAP5, ICOS were determined by the quantitative real-time polymerase chain reaction (qRT-PCR), and the significant correlations among these key genes were identified. Notably, hsa-miR-17-3p, hsa-miR-3158-3p, hsa-miR-423-3p, and hsa-miR-193a-8p could regulate all key genes at the same time. In addition, Caffeine, Carboplatin, and Vopratelimab were the targeted drugs of these key genes. This study identified four platelet-related key genes of IS, which might help to deepen the understanding of the role of platelet-related genes in the molecular mechanism of IS.

CD24hiCD27+ Bregs within Metastatic Lymph Nodes Promote Multidrug Resistance in Breast Cancer

PURPOSE

Axillary lymph nodes (LN) are the primary and dominant metastatic sites in breast cancer. However, the interaction between tumor cells and immune cells within metastatic LNs (mLN) remains poorly understood. In our study, we explored the effect of CD24hiCD27+ regulatory B cells (Breg) within mLNs on orchestrating drug resistance of breast cancer cells.

EXPERIMENTAL DESIGN

We collected mLN samples from patients with breast cancer who had received standard neoadjuvant therapy (NAT) and analyzed the spatial features of CD24hiCD27+ Bregs through multicolor immunofluorescence staining. The effect of CD24hiCD27+ Bregs on drug resistance of breast cancer cells was evaluated via in vitro experiments. A mouse model with mLNs was used to evaluate the strategies with blocking the interactions between Bregs and breast cancer for improving tumor regression within mLNs.

RESULTS

In patients with breast cancer who had received NAT, there is a close spatial correlation between activated CD24hiCD27+ Bregs and residual tumor cells within mLNs. Mechanistically, CD24hiCD27+ Bregs greatly enhance the acquisition of multidrug resistance and stem-like features of breast cancer cells by secreting IL6 and TNFα. More importantly, breast cancer cells further promote the activation of CD24hiCD27+ Bregs via CD40L-dependent and PD-L1-dependent proximal signals, forming a positive feedback pattern. PD-L1 blockade significantly attenuates the drug resistance of breast cancer cells induced by CD24hiCD27+ Bregs, and addition of anti-PD-L1 antibody to chemotherapy improves tumor cell remission in mLNs.

CONCLUSIONS

Our study reveals the pivotal role of CD24hiCD27+ Bregs in promoting drug resistance by interacting with breast cancer cells in mLNs, providing novel evidence for an improved strategy of chemoimmunotherapy combination for patients with breast cancer with mLNs.

Investigating the ID3/SLC22A4 as immune-related signatures in ischemic stroke

BACKGROUND

Ischemic stroke (IS) is a fearful disease that can cause a variety of immune events. Nevertheless, precise immune-related mechanisms have yet to be systematically elucidated. This study aimed to identify immune-related signatures using machine learning and to validate them with animal experiments and single cell analysis.

METHODS

In this study, we screened 24 differentially expressed genes (DEGs) while identifying immune-related signatures that may play a key role in IS development through a comprehensive strategy between least absolute shrinkage and selection operation (LASSO) regression, support vector machine (SVM) and immune-related genes. In addition, we explored immune infiltration using the CIBERSORT algorithm. Finally, we performed validation in mouse brain tissue and single cell analysis.

RESULTS

We identified 24 DEGs for follow-up analysis. ID3 and SLC22A4 were finally identified as the better immune-related signatures through a comprehensive strategy among DEGs, LASSO, SVM and immune-related genes. RT-qPCR, western blot, and immunofluorescence revealed a significant decrease in ID3 and a significant increase in SLC22A4 in the middle cerebral artery occlusion group. Single cell analysis revealed that ID3 was mainly concentrated in endothelial_2 cells and SLC22A4 in astrocytes in the MCAO group. A CIBERSORT finds significantly altered levels of immune infiltration in IS patients.

CONCLUSIONS

This study focused on immune-related signatures after stroke and ID3 and SLC22A4 may be new therapeutic targets to promote functional recovery after stroke. Furthermore, the association of ID3 and SLC22A4 with immune cells may be a new direction for post-stroke immunotherapy.

Uncovering Candidate mRNAs, Signaling Pathways and Immune Cells in Atherosclerotic Plaque and Ischemic Stroke

Background

The specific molecular mechanistic link between atherosclerotic plaques and ischemic stroke (IS) is not clear. The aim of this study is to explore the potential molecular relationship between atherosclerotic plaques and IS.

Methods

All data were downloaded from the Gene Expression Omnibus (GEO) database. Key hub differentially expressed mRNAs (DEmRNAs) related to atherosclerotic plaques and IS were identified by differential expression analysis and least absolute shrinkage and selection operator (LASSO) analysis. Subsequently, a diagnostic model was established based on the expression of key hub DEmRNAs and logistic regression. In order to understand the molecular mechanism of key hub DEmRNAs, the transcription factor (TF) regulatory network and mRNA-miRNA-lncRNA regulatory network were also constructed. In addition, functional enrichment analysis and single-sample Gene Set Enrichment Analysis (ssGSEA) analysis were also performed.

Results

Four key hub DEmRNAs (ADCY3, CLDN7, PPM1B and RRAS2) were identified by differential expression analysis and LASSO analysis. Moreover, the diagnostic model based on four key hub DEmRNAs has excellent diagnostic accuracy. We also found that Type 1 T helper cell may be associated with IS caused by atherosclerosis based on ssGSEA analysis. In the mRNA-miRNA-lncRNA regulatory network, we found that multiple signaling axes such as RRAS2-hsa-miR-3150b-3p-ILF3-AS1, PPM1B-hsa-miR-541-5p-LINC00294, CLDN7-hsa-miR-184-LINC00467 and ADCY3-hsa-miR-488-3p-URB1-AS1 may play an important role in the progression of IS. In addition, some signaling pathways, including chemokine signaling pathway, MAPK signaling pathway and cAMP signaling pathway, may be involved in regulating IS.

Conclusion

The identified key molecules, signaling pathways and immune cells may help to provide a theoretical basis for exploring the relationship between atherosclerotic plaque and the progression of IS.

The critical role of apoptosis in mesenchymal stromal cell therapeutics and implications in homeostasis and normal tissue repair

Mesenchymal stromal cells (MSCs) have been extensively tested for the treatment of numerous clinical conditions and have demonstrated good safety but mixed efficacy. Although this outcome can be attributed in part to the heterogeneity of cell preparations, the lack of mechanistic understanding and tools to establish cell pharmacokinetics and pharmacodynamics, as well as the poorly defined criteria for patient stratification, have hampered the design of informative clinical trials. We and others have demonstrated that MSCs can rapidly undergo apoptosis after their infusion. Apoptotic MSCs are phagocytosed by monocytes/macrophages that are then reprogrammed to become anti-inflammatory cells. MSC apoptosis occurs when the cells are injected into patients who harbor activated cytotoxic T or NK cells. Therefore, the activation state of cytotoxic T or NK cells can be used as a biomarker to predict clinical responses to MSC treatment. Building on a large body of preexisting data, an alternative view on the mechanism of MSCs is that an inflammation-dependent MSC secretome is largely responsible for their immunomodulatory activity. We will discuss how these different mechanisms can coexist and are instructed by two different types of MSC "licensing": one that is cell-contact dependent and the second that is mediated by inflammatory cytokines. The varied and complex mechanisms by which MSCs can orchestrate inflammatory responses and how this function is specifically driven by inflammation support a physiological role for tissue stroma in tissue homeostasis, and it acts as a sensor of damage and initiator of tissue repair by reprogramming the inflammatory environment.

Integrated bioinformatics and machine-learning screening for immune-related genes in diagnosing non-alcoholic fatty liver disease with ischemic stroke and RRS1 pan-cancer analysis

Background

The occurrence of ischemic stroke (IS) is associated with nonalcoholic fatty liver disease (NAFLD). The cancer burden of NAFLD complicated by IS also warrants attention. This study aimed to identify candidate immune biomarkers linked to NAFLD and IS and analyze their association with cancer.

Methods

Two of each of the NAFLD and IS datasets were downloaded, differentially expressed genes (DEGs) were identified, and module genes were screened via weighted gene coexpression network analysis (WGCNA). Subsequently, utilizing machine learning (least absolute shrinkage and selection operator regression, random forest and support vector machine-recursive feature elimination) and immune cell infiltration analysis, immune-related candidate biomarkers for NAFLD with IS were determined. Simultaneously, a nomogram was established, the diagnostic efficacy was assessed, and the role of candidate biomarkers in cancer was ascertained through pan-cancer analyses.

Results

In this study, 117 and 98 DEGs were identified from the combined NAFLD and IS datasets, respectively, and 279 genes were obtained from the most significant modules of NAFLD. NAFLD module genes and IS DEGs were intersected to obtain nine genes, which were enriched in the inflammatory response and immune regulation. After overlapping the results of the three machine learning algorithms, six candidate genes were obtained, based on which a nomogram was constructed. The calibration curve demonstrated good accuracy, and the candidate genes had high diagnostic values. The genes were found to be related to the immune dysregulation of stroke, and RRS1 was strongly associated with the prognosis, immune cell infiltration, microsatellite instability (MSI), and tumor mutation burden (TMB).

Conclusion

Six common candidate immune-related genes (PTGS2, FCGR1A, MMP9, VNN3, S100A12, and RRS1) of NAFLD and IS were identified, and a nomogram for diagnosing NAFLD with IS was established. RRS1 may serve as a candidate gene for predicting the prognosis of patients with cancer who have NAFLD complicated by IS, which could aid in their diagnosis and treatment.

Identification of immunogenic cell death-related gene classification patterns and immune infiltration characterization in ischemic stroke based on machine learning

Ischemic stroke (IS) accounts for more than 80% of strokes and is one of the leading causes of death and disability in the world. Due to the narrow time window for treatment and the frequent occurrence of severe bleeding, patients benefit less from early intravenous thrombolytic drug therapy. Therefore, there is an urgent need to explore the molecular mechanisms poststroke to drive the development of new therapeutic approaches. Immunogenic cell death (ICD) is a type of regulatory cell death (RCD) that is sufficient to activate the adaptive immune response of immunocompetent hosts. Although there is growing evidence that ICD regulation of immune responses and immune responses plays an important role in the development of IS, the role of ICD in the pathogenesis of IS has rarely been explored. In this study, we systematically evaluated ICD-related genes in IS. The expression profiles of ICD-related genes in IS and normal control samples were systematically explored. We conducted consensus clustering, immune infiltration analysis, and functional enrichment analysis of IS samples using ICD differentially expressed genes. The results showed that IS patients could be classified into two clusters and that the immune infiltration profile was altered in different clusters. In addition, we performed machine learning to screen nine signature genes that can be used to predict the occurrence of disease. We also constructed nomogram models based on the nine risk genes (CASP1, CASP8, ENTPD1, FOXP3, HSP90AA1, IFNA1, IL1R1, MYD88, and NT5E) and explored the immune infiltration correlation, gene-miRNA, and gene-TF regulatory network of the nine risk genes. Our study may provide a valuable reference for further elucidation of the pathogenesis of IS and provide directions for drug screening, personalized therapy, and immunotherapy for IS.

A New Therapeutic Trend: Natural Medicine for Ameliorating Ischemic Stroke via PI3K/Akt Signaling Pathway

Ischemic stroke (IS) is an acute cerebrovascular disease caused by sudden arterial occlusion, which is characterized by a high morbidity, mortality, and disability rate. It is one of the most important causes of nervous system morbidity and mortality in the world. In recent years, the search for new medicine for the treatment of IS has become an attractive research focus. Due to the extremely limited time window of traditional medicine treatment, some side effects may occur, and accompanied by the occurrence of adverse reactions, the frequency of exploration with natural medicine is significantly increased. Phosphatidylinositol-3-kinase/Protein kinase B (PI3K/Akt) signaling pathway is a classical pathway for cell metabolism, growth, apoptosis, and other physiological activities. There is considerable research on medicine that treats various diseases through this pathway. This review focuses on how natural medicines (including herbs and insects) regulate important pathophysiological processes such as inflammation, oxidative stress, apoptosis, and autophagy through the PI3K/Akt signaling pathway, and the role it plays in improving IS. We found that many kinds of herbal medicine and insect medicine can alleviate the damage caused by IS through the PI3K/Akt signaling pathway. Moreover, the prescription after their combination can also achieve certain results. Therefore, this review provides a new candidate category for medicine development in the treatment of IS.

Expression pattern and clinical value of Key RNA methylation modification regulators in ischemic stroke

Ischemic stroke (IS) is one of the major causes of death and disability worldwide, and effective diagnosis and treatment methods are lacking. RNA methylation, a common epigenetic modification, plays an important role in disease progression. However, little is known about the role of RNA methylation modification in the regulation of IS. The aim of this study was to investigate RNA methylation modification patterns and immune infiltration characteristics in IS through bioinformatics analysis. We downloaded gene expression profiles of control and IS model rat brain tissues from the Gene Expression Omnibus database. IS profiles were divided into two subtypes based on RNA methylation regulators, and functional enrichment analyses were conducted to determine the differentially expressed genes (DEGs) between the subtypes. Weighted gene co-expression network analysis was used to explore co-expression modules and genes based on DEGs. The IS clinical diagnosis model was successfully constructed and four IS characteristic genes (GFAP, GPNMB, FKBP9, and CHMP5) were identified, which were significantly upregulated in IS samples. Characteristic genes were verified by receiver operating characteristic curve and real-time quantitative PCR analyses. The correlation between characteristic genes and infiltrating immune cells was determined by correlation analysis. Furthermore, GPNMB was screened using the protein-protein interaction network, and its regulatory network and the potential therapeutic drug chloroquine were predicted. Our finding describes the expression pattern and clinical value of key RNA methylation modification regulators in IS and novel diagnostic and therapeutic targets of IS from a new perspective.

The mechanism of microglia-mediated immune inflammation in ischemic stroke and the role of natural botanical components in regulating microglia: A review

Ischemic stroke (IS) is one of the most fatal diseases. Neuroimmunity, inflammation, and oxidative stress play important roles in various complex mechanisms of IS. In particular, the early proinflammatory response resulting from the overactivation of resident microglia and the infiltration of circulating monocytes and macrophages in the brain after cerebral ischemia leads to secondary brain injury. Microglia are innate immune cells in the brain that constantly monitor the brain microenvironment under normal conditions. Once ischemia occurs, microglia are activated to produce dual effects of neurotoxicity and neuroprotection, and the balance of the two effects determines the fate of damaged neurons. The activation of microglia is defined as the classical activation (M1 type) or alternative activation (M2 type). M1 type microglia secrete pro-inflammatory cytokines and neurotoxic mediators to exacerbate neuronal damage, while M2 type microglia promote a repairing anti-inflammatory response. Fine regulation of M1/M2 microglial activation to minimize damage and maximize protection has important therapeutic value. This review focuses on the interaction between M1/M2 microglia and other immune cells involved in the regulation of IS phenotypic characteristics, and the mechanism of natural plant components regulating microglia after IS, providing novel candidate drugs for regulating microglial balance and IS drug development.