T Helper Research Articles

Retinoic Acid (RA): A Critical Immunoregulatory Molecule in Asthma and Allergies.

Asthma and allergies are chronic inflammatory disorders that are triggered owing to aberrant responses of the immune system against typically innocent environmental substances. Retinoic acid (RA) represents a biologically active metabolite of vitamin A (VA) and high-affinity ligand for RA receptor (RAR) that is implicated in a wide variety of biological processes, including cell proliferation, differentiation, apoptosis, organogenesis, reproduction, and immune responses. In the immune system, RA contributes to the induction of regulatory T (Treg) cells, adhesion molecules required for homing of B and T cells in the gut, and tolerance. Noteworthy, RA has a pivotal role in maintaining the balance of Th17-Treg cells and is also indispensable for appropriate responses of T helper (Th) cells. This mini-review article intends to expose the immune functions of RA, with an emphasis on the enzymatic pathways converting VA into RA and its receptor-dependent actions in asthma and allergies. Recent findings have depicted that RA levels are reduced in asthma and allergies and that treatment with RA alleviates allergy symptoms and airway inflammation. RA also modulates allergic airway disorders by inhibiting Th2/Th17 response and increasing Treg cells. Therefore, RA could be considered a novel and promising therapeutic agent to be studied and used for treating these diseases.

Prognostic Value of Tumour Infiltrating T-Lymphocytes (Tils) with Special Preference to CD8 Positive T-Lymphocyte in Muscle Invasive Urothelial Bladder Cancer

Prognostic Value of Tumour Infiltrating T-Lymphocytes (Tils) with Special Preference to CD8 Positive T-Lymphocyte in Muscle Invasive Urothelial Bladder Cancer

Mass cytometry identifies imbalance of multiple immune-cell subsets associated with biologics treatment in ankylosing spondylitis.

This study aims to comprehensively investigate immune-cell landscapes in ankylosing spondylitis (AS) patients and explore longitudinal immunophenotyping changes induced by biological agents. We employed mass cytometry with 35 cellular markers to analyze blood samples from 34 AS patients and 13 healthy controls (HC). Eleven AS patients were re-evaluated 1 month (4 patients) and 3 months (7 patients) after treatment with biological agents. Flow Self-Organizing Maps (FlowSOM) clustering was performed to identify specific cellular metaclusters. We compared cellular abundances across distinct subgroups and validated subset differences using gating strategies in flow cytometry scatter plots, visualized with FlowJo software. The proportions of differential subsets were then used for intercellular and clinical correlation analysis, as well as for constructing diagnostic models based on the random forest algorithm. In AS patients, we identified and validated nine different immune-cell subsets compared to HC. Three subsets increased: helper T-cell 17 (Th17), mucosa-associated invariant T-cell (MAIT), and classical monocytes (CM). Six subsets decreased: effector memory T-cell (TEM), naïve B cells, transitional B cells, IL10+ memory B cells, non-classical monocytes (NCM), and neutrophils. Treatments with biological agents could rectify cellular abnormalities, particularly the imbalance of CM/NCM. Furthermore, these subsets may serve as biomarkers for assessing disease activity and constructing effective diagnostic models for AS. These findings provide novel insights into the specific patterns of immune cell in AS, facilitating the further development of novel biomarkers and potential therapeutic targets for AS patients.

464 (PB452): Determination of the phase 2 dose of AU-007, an AI-designed human monoclonal antibody that redirects IL-2 to T-effector cells

464 (PB452): Determination of the phase 2 dose of AU-007, an AI-designed human monoclonal antibody that redirects IL-2 to T-effector cells

Phase I/II study of BMS-986156 with ipilimumab or nivolumab with or without stereotactic ablative radiotherapy in patients with advanced solid malignancies

BackgroundBMS-986156 is an agonist of the glucocorticoid-induced tumor necrosis factor receptor (TNFR)-related protein (GITR) and promotes increased effector T-cell activation. Combined anti-GITR, anti-programmed death-1, anti-cytotoxic T-lymphocyte-associated protein 4 antibodies and...

Degradation of IKZF1 prevents epigenetic progression of Tcell exhaustion in an antigen-specific assay.

In cancer, chronic antigen stimulation drives effector Tcells to exhaustion, limiting the efficacy of Tcell therapies. Recent studies have demonstrated that epigenetic rewiring governs the transition of Tcells from effector to exhausted states and makes a subset of exhausted Tcells non-responsive to PD1 checkpoint blockade. Here, we describe an antigen-specific assay for Tcell exhaustion that generates Tcells phenotypically and transcriptionally similar to those found in human tumors. We perform a screen of human epigenetic regulators, identifying IKZF1 as a driver of Tcell exhaustion. We determine that the IKZF1 degrader iberdomide prevents exhaustion by blocking chromatin remodeling at Tcell effector enhancers and preserving the binding of AP-1, NF-κB, and NFAT. Thus, our study uncovers a role for IKZF1 as a driver of Tcell exhaustion through epigenetic modulation, providing a rationale for the use of iberdomide in solid tumors to prevent Tcell exhaustion.

Benign breast tumors may arise on different immunological backgrounds.

Benign breast tumors are a nonthreatening condition defined as abnormal cell growth within the breast without the ability to invade nearby tissue. However, benign lesions hold valuable biological information that can lead us toward better understanding of tumor biology. In this study, we have used two pathway analysis algorithms, Pathifier and gene set variation analysis (GSVA), to identify biological differences between normal breast tissue, benign tumors and malignant tumors in our clinical dataset. Our results revealed that one-third of all pathways that were significantly different between benign and malignant tumors were immune-related pathways, and 227 of them were validated by both methods and in the METABRIC dataset. Furthermore, five of these pathways (all including genes involved in cytokine and interferon signaling) were related to overall survival in cancer patients in both datasets. The cellular moieties that contribute to immune differences in malignant and benign tumors were analyzed using the deconvolution tool, CIBERSORT. The results showed that levels of some immune cells were specifically higher in benign than in malignant tumors, and this was especially the case for resting dendritic cells and follicular T-helper cells. Understanding the distinct immune profiles of benign and malignant breast tumors may aid in developing noninvasive diagnostic methods to differentiate between them in the future.

Identification of necroptosis genes and characterization of immune infiltration in non-alcoholic steatohepatitis

BackgroundThe most common progressive form of non-alcoholic fatty liver disease (NAFLD) is non-alcoholic steatohepatitis (NASH), which is characterized by the development of cirrhosis, and requires liver transplantation. We screened for the differentially expressed necroptosis-related genes in NASH in this study, and analyzed immune infiltration through microarray and bioinformatics analysis to identify potential biomarkers, and explore the molecular mechanisms involved in NASH.MethodsThe GSE24807 microarray dataset of NASH patients and healthy controls was downloaded, and we identified the differentially expressed genes (DEGs). Necroptosis-related differential genes (NRDEGs) were extracted from these DEGs, and functionally annotated by enrichment analyses. The core genes were obtained by constructing gene co-expression networks using weighted gene co-expression network analysis (WGCNA). Finally, the transcription factor (TF) regulatory network and the mRNA-miRNA network were constructed, and the infiltrating immune cell populations were analyzed with CIBERSORT.ResultsWe identified six necroptosis-related genes (CASP1, GLUL, PYCARD, IL33, SHARPIN, and IRF9), and they are potential diagnostic biomarkers for NASH. In particular, PYCARD is a potential biomarker for NAFLD progression. Analyses of immune infiltration showed that M2 macrophages, γδ T cells, and T follicular helper cells were associated with the immune microenvironment of NASH, which is possibly regulated by CASP1, IL33, and IRF9.ConclusionsWe identified six necroptosis-related genes in NASH, which are also potential diagnostic biomarkers. Our study provides new insights into the molecular mechanisms and immune microenvironment of NASH.

High-dimensional profiling of immune responses to kidney transplant reveals heterogeneous T helper 1 and B cell effectors associated with rejection

Rejection is a primary cause of allograft dysfunction after kidney transplantation. The diversity of immune subpopulations involved in the different endotypes of rejection remains to be delineated at single-cell resolution. In a cohort of 76 kidney transplant recipients, we conducted high-dimensional immune phenotyping of blood CD4 T and B cells, single-cell RNA and T/B cell receptor sequencing, and plasma cytokine profiling. Phenotypic, transcriptional, and clonal states of CD4T and B cells could significantly distinguish stable allograft states from rejection. Patients undergoing T cell-mediated rejection displayed accumulation of clonally expanded cytotoxic T helper (Th)1 cells and Th17-like cells, associated with predominant naive B cell responses. In contrast, antibody-mediated rejection was characterized by clonal expansion of Th1-polarized T follicular helper cells and effector T-bet+ memory B cells, both of which strongly expressed interleukin 12 and tumor necrosis factor-signaling pathways. Plasma cytokine analysis confirmed mixed Th1/Th17 and Th1/T follicular helper cell-driven inflammatory profiles distinguishing T cell-mediated rejection and antibody-mediated rejection, respectively. CD4T and B cell subpopulations and signatures were validated using bulk RNA-seq analysis of matched kidney allografts and using an independent single-cell RNA-seq data set. These data improve mechanistic understanding of the immune pathogenesis of rejection and support the development of more specific immunosuppressive therapies to treat allograft rejection.

Progranulin protects against Clostridioides difficile infection by enhancing IL-22 production

ABSTRACT Enhanced mortality, relapse rates, and increased prevalence of Clostridioides difficile infection (CDI) emphasize the need for better therapies and management approaches. Modulating host immune response to ameliorate CDI-associated immunopathology may provide new advantages to currently inadequate antibiotic therapies. Here, we identified progranulin (PGRN) as an important immune target upregulated in response to CDI. PGRN-deficient mice displayed dramatically higher mortality and aggravated epithelial barrier disruption compared with wild type (WT) mice after CDI despite equivalent levels of bacterial burden or toxin in the large intestine. Mechanistically, PGRN protection was mediated by IL-22 production from CD4+ T helper cells, as demonstrated by a decrease in colonic IL-22-producing CD4+ T helper cells in the intestine of PGRN-deficient mice upon CDI and a boost of IL-22-producing CD4+ T helper cells activated by PGRN ex vivo. Clinical evidence suggests that CDI patients had significantly higher serum levels of PGRN compared with healthy controls, which was significantly and positively correlated with IL-22. Our findings thus indicate a critical role for PGRN-promoted CD4+ T cell IL-22 production in shaping gut immunity and reestablishing the intestinal barrier during CDI. As an alternative to pathogen-targeted therapy, this study may provide a new host-directed therapeutic strategy to attenuate severe, refractory CDI.

Nonclinical evaluations of deucravacitinib and Janus kinase inhibitors in homeostatic and inflammatory pathways.

Translational medicine provides insight into novel drugs and predicts unwanted effects. In well-characterized pathways (e.g., cytokine-Janus kinase [JAK]-signal transducers and activators of transcription [STAT]), a variety of in vitro assessments were used to estimate selectivity of effects on different potential targets (i.e., JAK1, JAK2, JAK3, and tyrosine kinase 2 [TYK2]). Several approved drugs were characterized as selective for the JAK family. These assessments are challenged by a lack of compounds that only inhibit one JAK family member. Deucravacitinib is a first-in-class, oral, selective, allosteric inhibitor of TYK2, a kinase required for IL-12, IL-23, and Type I interferon signaling. Unlike deucravacitinib, which selectively binds to the TYK2 regulatory domain, JAK1,2,3 inhibitors target the catalytic domain, contributing to nonselective targeting of JAK1,2,3. Cytokines associated with JAK1,2,3 signaling are required for both immune and nonimmune functions. A similar laboratory abnormality profile was observed in clinical trials using JAK1,2,3 inhibitors that has not been observed with deucravacitinib. In vitro testing of JAK1,2,3 inhibitors has relied upon assays of signal transduction, such as those measuring STAT phosphorylation, for estimates of potency and selectivity. These assay systems can be effective in estimating in vivo efficacy; however, they may not provide insight into downstream outcomes of receptor signaling, which may be more relevant for evaluating safety aspects. Assay systems assessing functional outcomes from cells may yield a more useful translational evaluation. Here, deucravacitinib was assessed for potency and selectivity versus three representatives of the JAK inhibitor class (tofacitinib, baricitinib, and upadacitinib) based on functional assays. JAK inhibitors had suppressive activity against JAK2-dependent hematopoietic colony-forming assays modeling thrombopoiesis, erythropoiesis, and myelopoiesis; however, deucravacitinib did not. Deucravacitinib had limited potency against NK cells, cytotoxic T cells, T-helper cells, and regulatory T cells activated by JAK1/JAK3-dependent common gamma chain cytokines. These data are consistent with the biologic role of JAK1,2,3 and pharmacodynamic changes in clinical laboratory abnormalities. Against TYK2-dependent cytokines, deucravacitinib selectively inhibited Type I interferon stimulation of monocytes and dendritic cells and was a more potent inhibitor than JAK inhibitors. IL-12 and IL-23 functional outputs were similarly potently inhibited by deucravacitinib. Results are consistent with deucravacitinib selectively inhibiting TYK2.

Interleukin 9 mediates T follicular helper cell activation to promote antibody responses.

Antigen-specific humoral responses are orchestrated through complex interactions among immune cells in lymphoid tissues, including the collaboration between B cells and T follicular helper (Tfh) cells. Accumulating evidence indicates a crucial role for interleukin-9 (IL-9) in the formation of germinal centers (GCs), enhancing the generation of class-switched high-affinity antibodies. However, the exact function of IL-9 in Tfh cell regulation remains unclear. In this study, we examined the humoral immune responses of CD4Cre/+Il9rafl/fl mice, which lack an IL-9-specific receptor in Tfh cells. Upon intraperitoneal immunization with sheep red blood cells (SRBCs), CD4Cre/+Il9rafl/fl mice displayed diminished levels of SRBC-specific IgG antibodies in their sera, along with reduced levels of GC B cells and plasma cells. Notably, Il9ra-deficient Tfh cells in the spleen exhibited decreased expression of their signature molecules such as B-cell lymphoma 6, C-X-C chemokine receptor 5, IL-4, and IL-21 compared to control mice. In models of allergic asthma induced by house dust mite (HDM) inhalation, CD4Cre/+Il9rafl/fl mice failed to elevate serum levels of HDM-specific IgE and IgG. This was accompanied by reductions in Tfh cells, GC B cells, and plasma cells in mediastinal lymph nodes. Furthermore, group 2 innate lymphoid cells (ILC2s) were identified as producers of IL-9 under immunizing conditions, possibly induced by leukotrienes released by activated IgD+ B cells around the T-B border. These observations may indicate the critical role of IL-9 receptor signaling in the activation of Tfh cells, with ILC2s potentially capable of supplying IL-9 in organized lymphoid tissues.

Tucaresol: A Clinical Stage Oral Candidate Drug with Two Distinct Antiviral Mechanisms

Globally, approximately 39 million people are living with Human Immunodeficiency Virus, HIV, arising from approximately 86 million infections since this epidemic began in 1981. However, the number of HIV infections is unevenly distributed with two thirds of global infections confined to Sub-Saharan Africa. Due to viral drug resistance, the most effective treatment requires a triple drug combination thereby adding to the complexity and cost of therapy. As such, many people living with HIV or at risk of infection do not have access to prevention or treatment of this potentially fatal disease. There is no cure for HIV [1]. Tucaresol is an orally active clinical stage drug which functions as a host targeted antiviral agent by protection or reconstitution of CD4+ T helper immune cells. We report herein that Tucaresol also displays in-vitro activity against HIV in infected human peripheral blood mononuclear cells. Although this in-vitro antiviral activity is not potent, the excellent safety profile and bioavailability of Tucaresol, along with its low Molecular Weight, support attainment of relevant drug concentrations in man to achieve significant in-vivo activity. This is demonstrated by previously reported stabilization of viremia in a prior proof of concept phase 1b/2a HIV clinical trial [2]. It is possible that the significant in-vivo activity of Tucaresol arises from synergy between co-stimulation of CD4+ T helper cells and the direct activity against virally infected cells. A pan in-vitro viral screen of Tucaresol further revealed a weak, direct antiviral activity against human herpes virus 6B, human papillomavirus 11, measles virus and hepatitis B virus.

ZYG11B participates in the modulation of colorectal cancer cell proliferation and immune infiltration and is a prognostic biomarker.

The biological function of ZYG11B is still unclear, and few studies on ZYG11B in colorectal cancer were reported. The purpose of our research is to detect the biological functions of ZYG11B in colorectal cancer through The Cancer Genome Atlas (TCGA) database online and the vitro cell experiments. The information of ZYG11B in colorectal cancer were downloaded from TCGA database. The bioinformatics analysis has been utilized to examine the expression, functional enrichment, association of immune, clinicopathological characteristics and diagnostic prognostic value. CCK-8 and apoptosis assays have been utilized to identify the abilities of progression and apoptosis. The abilities of invasion and migration were detected by transwell assay. In contrast to adjacent normal tissues, colorectal cancer tissues exhibited a notably diminished expression of ZYG11B (p < 0.001). Further examination through functional enrichment analysis unveiled the enrichment of various pathways associated with tumor proliferation and apoptosis. The implementation of CCK-8 and apoptosis assays validated the suppressive impact of ZYG11B on the progression of colorectal cancer cells (p < 0.001). A significant positive correlation was found between ZYG11B and Tcm and T helper cells (R ≥ 0.3, p < 0.001). Moreover, the expression of ZYG11B demonstrated a prominent presence among subjects without previous experience of colon polyps (p < 0.05), devoid of lymphatic infiltration (p < 0.01), and age ≤ 65 years (p < 0.01). Additionally, ZYG11B exhibited higher expression levels among patients diagnosed with colorectal adenocarcinoma (p < 0.05). Following the analysis of survival prognosis, it became evident that increased ZYG11B expression correlated with enhanced survival rates (p < 0.01) and the ability to accurately forecast the prognosis and survival of COAD/READ patients. ZYG11B plays a tumor suppressive role in the proliferation process of colorectal cancer and may have a broad application prospect in the diagnosis and prognosis evaluation of colorectal cancer with more study.

Differential Diagnosis of Tuberculosis and Sarcoidosis by Immunological Features Using Machine Learning.

Despite the achievements of modern medicine, tuberculosis remains one of the leading causes of mortality globally. The difficulties in differential diagnosis have particular relevance in the case of suspicion of tuberculosis with other granulomatous diseases. The most similar clinical and radiologic changes are sarcoidosis. The aim of this study is to apply mathematical modeling to determine diagnostically significant immunological parameters and an algorithm for the differential diagnosis of tuberculosis and sarcoidosis. Materials and methods: The serum samples of patients with sarcoidosis (SD) (n = 29), patients with pulmonary tuberculosis (TB) (n = 32) and the control group (n = 31) (healthy subjects) collected from 2017 to 2022 (the average age 43.4 ± 5.3 years) were examined. Circulating 'polarized' T-helper cell subsets were analyzed by multicolor flow cytometry. A symbolic regression method was used to find general mathematical relations between cell concentrations and diagnosis. The parameters of the selected model were finally fitted through multi-objective optimization applied to two conflicting indices: sensitivity to sarcoidosis and sensitivity to tuberculosis. Results: The difference in Bm2 and CD5-CD27- concentrations was found to be more significant for the differential diagnosis of sarcoidosis and tuberculosis than any individual concentrations: the combined feature Bm2 - [CD5-CD27-] differentiates sarcoidosis and tuberculosis with p < 0.00001 and AUC = 0.823. An algorithm for differential diagnosis was developed. It is based on the linear model with two variables: the first variable is the difference Bm2 - [CD5-CD27-] mentioned above, and the second is the naïve-Tregs concentration. The algorithm uses the model twice and returns "dubious" in 26.7% of cases for patients with sarcoidosis and in 16.1% of cases for patients with tuberculosis. For the remaining patients with one of these two diagnoses, its sensitivity to sarcoidosis is 90.5%, and its sensitivity to tuberculosis is 88.5%. Conclusions: A simple algorithm was developed that can distinguish, by certain immunological features, the cases in which sarcoidosis is likely to be present instead of tuberculosis. Such cases may be further investigated to rule out tuberculosis conclusively. The mathematical model underlying the algorithm is based on the analysis of "naive" T-regulatory cells and "naive" B-cells. This may be a promising approach for differential diagnosis between pulmonary sarcoidosis and pulmonary tuberculosis. The findings may be useful in the absence of clear differential diagnostic criteria between pulmonary tuberculosis and sarcoidosis.

Dipeptidyl peptidase-4 marks distinct subtypes of human adipose stromal/stem cells with different hepatocyte differentiation and immunoregulatory properties

BackgroundHuman adipose-derived stromal/stem cells (hASCs) play important roles in regenerative medicine and numerous inflammatory diseases. However, their cellular heterogeneity limits the effectiveness of treatment. Understanding the distinct subtypes of hASCs and their phenotypic implications will enable the selection of appropriate subpopulations for targeted approaches in regenerative medicine or inflammatory diseases.MethodshASC subtypes expressing dipeptidyl peptidase-4 (DPP4) were identified via fluorescence-activated cell sorting (FACS) analysis. DPP4 expression was knocked down in DPP4+ hASCs via DPP4 siRNA. The capacity for proliferation, hepatocyte differentiation, inflammatory factor secretion and T-cell functionality regulation of hASCs from DPP4−, DPP4+, and control siRNA-treated DPP4+ hASCs and DPP4 siRNA-treated DPP4+ hASCs were assessed.ResultsDPP4+ hASCs and control siRNA-treated DPP4+ hASCs presented a lower proliferative capacity but greater hepatocyte differentiation capacity than DPP4− hASCs and DPP4 siRNA-treated DPP4+ hASCs. Both DPP4+ hASCs and DPP4− hASCs secreted high levels of vascular endothelial growth factor-A (VEGF-A), monocyte chemoattractant protein-1 (MCP-1), and interleukin 6 (IL-6), whereas the levels of other factors, including matrix metalloproteinase (MMP)-1, eotaxin-3, fractalkine (FKN, CX3CL1), growth-related oncogene-alpha (GRO-alpha, CXCL1), monokine induced by interferon-gamma (MIG), macrophage inflammatory protein (MIP)-1beta, and macrophage colony-stimulating factor (M-CSF), were significantly greater in the supernatants of DPP4+ hASCs than in those of DPP4− hASCs. Exposure to hASC subtypes and their conditioned media triggered changes in the secreted cytokine profiles of T cells from healthy donors. The percentage of functional T cells that secreted factors such as MIP-1beta and IL-8 increased when these cells were cocultured with DPP4+ hASCs. The percentage of polyfunctional CD8+ T cells that secreted multiple factors, such as IL-17A, tumour necrosis factor alpha (TNF-α) and TNF-β, decreased when these cells were cocultured with supernatants derived from DPP4+ hASCs.ConclusionsDPP4 may regulate proliferation, hepatocyte differentiation, inflammatory cytokine secretion and T-cell functionality of hASCs. These data provide a key foundation for understanding the important role of hASC subpopulations in the regulation of T cells, which may be helpful for future immune activation studies and allow them to be customized for clinical application.

Dissecting the immune infiltrate of primary luminal B-like breast carcinomas in relation to age.

The impact of aging on the immune landscape of luminal breast cancer (Lum-BC) is poorly characterized. Understanding the age-related dynamics of immune editing in Lum-BC is anticipated to improve the therapeutic benefit of immunotherapy in older patients. To this end, here we applied the 'multiple iterative labeling by antibody neo-deposition' (MILAN) technique, a spatially resolved single-cell multiplex immunohistochemistry method. We created tissue microarrays by sampling both the tumor center and invasive front of luminal breast tumors collected from a cohort of treatment-naïve patients enrolled in the prospective monocentric IMAGE (IMmune system and AGEing) study. Patients were subdivided into three nonoverlapping age categories (35-45 = 'young', n = 12; 55-65 = 'middle', n = 15; ≥70 = 'old', n = 26). Additionally, depending on localization and amount of cytotoxic T lymphocytes, the tumor immune types 'desert' (n = 22), 'excluded' (n = 19), and 'inflamed' (n = 12) were identified. For the MILAN technique we used 58 markers comprising phenotypic and functional markers allowing in-depth characterization of T and B lymphocytes (T&B-lym). These were compared between age groups and tumor immune types using Wilcoxon's test and Pearson's correlation. Cytometric analysis revealed a decline of the immune cell compartment with aging. T&B-lym were numerically less abundant in tumors from middle-aged and old compared to young patients, regardless of the geographical tumor zone. Likewise, desert-type tumors showed the smallest immune-cell compartment and were not represented in the group of young patients. Analysis of immune checkpoint molecules revealed a heterogeneous geographical pattern of expression, indicating higher numbers of PD-L1 and OX40-positive T&B-lym in young compared to old patients. Despite the numerical decline of immune infiltration, old patients retained higher expression levels of OX40 in T helper cells located near cancer cells, compared to middle-aged and young patients. Aging is associated with important numerical and functional changes of the immune landscape in Lum-BC. © 2024 The Author(s). The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Exploring the prognostic value of T follicular helper cell levels in chronic lymphocytic leukemia

Chronic lymphocytic leukemia (CLL) presents with heterogeneous clinical outcomes, suggesting varied underlying pathogenic mechanisms. This study aims to elucidate the impact of T follicular helper (Tfh) cells on CLL progression and prognosis. Gene expression profile data for CLL were collected from GSE22762 and GSE39671 datasets. Patients were divided into high and low groups using Tfh levels using the optimal cutoff value based on overall survival (OS) and time-to-first treatment (TTFT). Differential expression analysis was performed between these groups, followed by co-expression network analysis and single-sample Gene Set Enrichment Analysis (ssGSEA). Marker genes of Tfh cells were used to construct prognostic models. Additionally, 40 CLL patients were recruited and categorized based on median Tfh levels. Marker gene expression was assessed using RT-qPCR and Western Blot, and immune cell levels were determined through flow cytometry. The high group showed better prognosis compared to the low group. Among the 1121 differentially expressed genes identified, five co-expression networks were constructed, with the turquoise module showing the highest correlation with Tfh cells. Genes within this module significantly participate in cytokine-cytokine receptor interaction, PI3K-Akt signaling pathway, and natural killer cell mediated cytotoxicity. Tfh cells were significantly negatively correlated with activated B cells and positively correlated with Tregs. The Random Survival Forest (RSF) model identified 10 marker genes, and further analysis using Lasso regression and nomogram selected CLEC4A, RAE1, CD84, and PRDX1 as prognostic markers. In the high group, levels of CLEC4A and RAE1 were higher than in the low group, whereas CD84 and PRDX1 were lower. Flow cytometry revealed that the level of activated B cells in the high Tfh group was significantly lower than in the low Tfh group, while the level of Tregs is significantly higher in the high Tfh group. This study seeks to contribute to a more detailed understanding of the pathogenesis of CLL, delving into the prognostic significance of Tfh.

Integrated bioinformatics analysis identifies PCSK9 as a prognosticator correlated with lipid metabolism in pancreatic adenocarcinoma

BackgroundPancreatic adenocarcinoma (PAAD) is the most frequent kind of pancreatic cancer (PC). Recent studies suggest that lipid metabolism facilitates tumorigenesis, disease progression, and resistance to therapy by promoting lipid synthesis, accumulation, and breakdown. Thus, exploring the lipid metabolism network could unveil novel therapeutic avenues for early detection, precision medicine, and prognostication in PAAD. This project intends to develop new lipid metabolism-related biomarkers for PAAD diagnosis and investigate the link between important genes and immune cell infiltration (ICI).MethodsTissue samples from 20 PAAD patients and 20 healthy controls were obtained. Analysis were focused on the datasets GSE71729 and GSE16515, which include samples of PAAD (n = 161) and those from healthy human tissue (n = 61), derived from the GEO database. Knockdown of PCSK9 on PC cells were conducted by si-RNA and sh-RNA. Migration and cell functional experiments were performed to assess the role of PCSK9 in cell multiplication. Furthermore, a xenograft mouse model was employed to confirm PCSK9's function in vivo.ResultsThe expression level of Proprotein convertase subtilisin/kexin type 9 (PCSK9) is significantly elevated in tissues affected by PAAD when compared to normal tissues. Survival analyses indicated that increased PCSK9 levels are inversely related to overall and disease-free survival (DFS). PCSK9’s functional annotation associated it with the cell cycle and metabolism, especially energy metabolism. Examination of ICI data determined that PCSK9 expression demonstrated an unambiguous association with the M0 macrophages, T follicular helper cells (Tfh), gamma delta T cells and activated DC, and an inverse relationship with Monocytes, CD8+ T cells, memory B cells, resting CD4+ memory T cells, activated NK cells and resting DC abundance. PCSK9 expression knockdown has the ability to impede PC cells’ migration and proliferation.ConclusionOur study identified PCSK9 as a critical gene in PAAD. Expression levels of PCSK9 varied between PAAD and normal samples. ROC analysis verified PCSK9's strong capacity to differentiate PC from normal samples. Importantly, PCSK9 expression was considerably elevated in PC cell lines and tissues. Furthermore, PCSK9 stimulates the migration and proliferation of tumor cells in vivo and vitro.

Identification of key hub genes in knee osteoarthritis through integrated bioinformatics analysis.

Knee osteoarthritis (KOA) is a common chronic joint disease globally. Synovial inflammation plays a pivotal role in its pathogenesis, preceding cartilage damage. Identifying biomarkers in osteoarthritic synovial tissues holds promise for early diagnosis and targeted interventions. Gene expression profiles were obtained from the Gene Expression Omnibus database. Subsequent analyses included differential expression gene (DEG) analysis and weighted gene co-expression network analysis (WGCNA) on the combined datasets. We performed functional enrichment analysis on the overlapping genes between DEGs and module genes and constructed a protein-protein interaction network. Using Cytoscape software, we identified hub genes related to the disease and conducted gene set enrichment analysis on these hub genes. The CIBERSORT algorithm was employed to evaluate the correlation between hub genes and the abundance of immune cells within tissues. Finally, Mendelian randomization analysis was utilized to assess the potential of these hub genes as biomarkers. We identified 46 differentially expressed genes (DEGs), comprising 20 upregulated and 26 downregulated genes. Using WGCNA, we constructed a gene co-expression network and selected the most relevant modules, resulting in 24 intersecting genes with the DEGs. KEGG enrichment analysis of the intersecting genes identified the IL-17 signaling pathway, associated with inflammation, as the most significant pathway. Cytoscape software was utilized to rank the candidate genes, with JUN, ATF3, FOSB, NR4A2, and IL6 emerging as the top five based on the Degree algorithm. A nomogram model incorporating these five genes, supported by ROC curve analysis, validated their diagnostic efficacy. Immune infiltration and correlation analysis revealed that macrophages were significantly associated with JUN (p < 0.01), FOSB (p < 0.01), and NR4A2 (p < 0.05). Additionally, T follicular helper cells showed significant associations with ATF3 (p < 0.05), FOSB (p < 0.05), and JUN (p < 0.05). Mendelian randomization analysis provided strong evidence linking JUN (IVW: OR = 0.910, p = 0.005) and IL6 (IVW: OR = 1.024, p = 0.026) with KOA. Through the utilization of various bioinformatics analysis methods, we have pinpointed key hub genes relevant to knee osteoarthritis. These findings hold promise for advancing pre-symptomatic diagnostic strategies and enhancing our understanding of the biological underpinnings behind knee osteoarthritis susceptibility genes.