Immune Cell Composition Research Articles

Integrative HLA typing of tumor and adjacent normal tissue can reveal insights into the tumor immune response

BackgroundThe HLA complex is the most polymorphic region of the human genome, and its improved characterization can help us understand the genetics of human disease as well as the interplay between cancer and the immune system. The main function of HLA genes is to recognize “non-self” antigens and to present them on the cell surface to T cells, which instigate an immune response toward infected or transformed cells. While sequence variation in the antigen-binding groove of HLA may modulate the repertoire of immunogenic antigens presented to T cells, alterations in HLA expression can significantly influence the immune response to pathogens and cancer.MethodsRNA sequencing was used here to accurately genotype the HLA region and quantify and compare the level of allele-specific HLA expression in tumors and patient-matched adjacent normal tissue. The computational approach utilized in the study types classical and non-classical Class I and Class II HLA alleles from RNA-seq while simultaneously quantifying allele-specific or personalized HLA expression. The strategy also uses RNA-seq data to infer immune cell infiltration into tumors and the corresponding immune cell composition of matched normal tissue, to reveal potential insights related to T cell and NK cell interactions with tumor HLA alleles.ResultsThe genotyping method outperforms existing RNA-seq-based HLA typing tools for Class II HLA genotyping. Further, we demonstrate its potential for studying tumor-immune interactions by applying the method to tumor samples from two different subtypes of breast cancer and their matched normal breast tissue controls.ConclusionsThe integrative RNA-seq-based HLA typing approach described in the study, coupled with HLA expression analysis, neoantigen prediction and immune cell infiltration, may help increase our understanding of the interplay between a patient’s tumor and immune system; and provide further insights into the immune mechanisms that determine a positive or negative outcome following treatment with immunotherapy such as checkpoint blockade.

Impact of perinatal administration of probiotics on immune cell composition in neonatal mice.

Newborns and especially preterm infants are much more susceptible to infections than adults. The pathogens causing infections in newborns are often detectable in the intestinal flora of affected children even before disease onset. Therefore, it seems reasonable to prevent dysbiosis in newborns and preterm infants. An approach followed in many neonatal intensive care units (NICUs) is to prevent infections in preterm infants with probiotics however their mechanisms of action of probiotics are incompletely understood. Here, we investigated the effect of perinatal probiotic exposure on immune cells in newborn mice. Pregnant mice were orally treated with a combination of Lactobacillus acidophilus and Bifidobacterium bifidum (Infloran®) from mid-pregnancy until the offspring were harvested. Immune cell composition in organs of the offspring were analyzed by flow cytometry. Perinatal probiotic exposure had profound effects on immune cell composition in the intestine, liver and lungs of newborn mice with reduction of myeloid and B cells and induction of T cells in the probiotic treated animals' organs at weaning. Furthermore, probiotic exposure had an effect on T cell development in the thymus. Our results contribute to a better understanding of the interaction of probiotics with the developing immune system. probiotics have profound effects on immune cell composition in intestines, livers and lungs of newborn mice. probiotics modulate T cell development in thymus of newborn mice. effects of probiotics on neonatal immune cells are particularly relevant in transition phases of the microbiome. our results contribute to a better understanding of the mechanisms of action of probiotics in newborns.

Transcriptomic Analysis of Metastatic Colorectal Tumor with Low Mutational Burden

Objective: To identify potential drug targets for metastasis colorectal cancer (CRC) patients with low mutational burden by examining differences in immune-related gene expression. Methods: For this study, 623 samples were collected from The Cancer Genome Atlas (TCGA) database, comprising tumor mutational burden (TMB), RNA sequencing (RNA-Seq), and clinical data. Differential gene expression analysis, Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of the identified genes were conducted using the R package. Additionally, a comparative analysis of immune infiltrating cell composition in metastatic and non-metastatic groups was performed. Hub genes, exhibiting high levels of interaction, were selected using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database. The Drug Gene Interaction Database (DGIdb) was then utilized to estimate drugs targeting the identified hub genes. Results: The transcriptome data of 326 colorectal cancer patients with low TMB were analyzed, comprising 58 patients with metastasis and 268 patients without metastasis. Among the differential expression in 1,111 genes for patients with metastasis compared to those without metastasis, 733 genes were upregulated, and 378 genes were downregulated. KEGG and GO enrichment analysis indicated significant differences in gene expression in CRC metastatic patients with low TMB compared to non-metastasis patients with low TMB. Enriched pathways included humoral immuneresponse, immunoglobulin production, and regulation of AMPA receptor activity. Two genes related to interleukin-12 were identified through secondary enrichment for immune-related genes. Analysis of tumor-infiltrating immune cell data revealed significant differences in memory-activated T cell CD4 and T cell CD8. Conclusions: This analysis of RNA sequencing data and immune-filtrating cell data revealed significant differences between metastatic colorectal cancer patients with low TMB and their non-metastatic counterparts. These distinctions suggest the possibility of identifying more effective drugs or therapies for metastatic colorectal cancer patients with low TMB.

P738 Response to etrasimod treatment in ulcerative colitis is associated with a reduction of circulating B and pro-inflammatory T cells: a single-cell-based post-hoc sub-analysis of the ELEVATE UC 52 trial

Abstract Background Etrasimod (ETR) is an oral, once-daily, selective sphingosine 1-phosphate receptor 1,4,5 (S1PR) modulator for the treatment of moderately to severely active ulcerative colitis (UC). The mechanism of action is based on a retention of lymphocytes in lymphatic tissue hindering circulating lymphocytes from entering the gut and causing inflammation. However, the effect of ETR on immune cell function and composition is not well characterized. In addition, it is unknown whether the response of UC patients to ETR treatment is associated with specific immune cell signatures. Methods Single-cell RNA sequencing (scRNAseq), mass cytometry (CyTOF) and clinical data integration were used to characterize the effects of 12 weeks of treatment with ETR on the immune composition and function of peripheral blood mononuclear cells (PBMCs) collected from 15 UC patients at weeks 0 and 12 during the ELEVATE UC Phase 3 clinical trial. As an exploratory cohort, PBMCs from 5 UC patients reaching the primary endpoint of clinical remission at week 12 (modified Mayo score <2), 5 UC patients not responding to ETR treatment (modified Mayo score >2) and 5 placebo-treated UC patients were included. 30 samples were processed for scRNAseq; additionally, 28 blood samples were ex-vivo stimulated with ionomycin/PMA for 4 h and cytokine production was assessed by CyTOF. To determine the effects of ETR in UC patients, immune cell function and composition were compared intra-individually between weeks 0 and 12. Subsequent comparisons between ETR responders, non-responders and placebo-treated UC patients were performed to discriminate responders from non-responders. Results Significant reductions in T and B cell subsets, along with increases in the abundance of dendritic and monocytic cells, were observed in responders by week 12 of -treatment. Importantly, ETR treatment significantly reduced circulating T cells producing pro-inflammatory cytokines, including TNFα and IFNγ, and S1PR modulation led to a mitigation of naïve and effector memory CD4 and CD8 T cells in ETR-treated UC patients achieving clinical remission. In contrast, patients not responding to ETR treatment had significantly higher frequencies of both naïve and TNFα-producing CD4 T cells by week 12. Conclusion In line with the described role of S1PR in lymphocyte trafficking, single-cell analyses of circulating immune cells from ETR-treated UC patients confirmed a significant reduction in B cells and pathogenic T cell subsets after ETR treatment providing an in-depth cellular characterization of S1PR modulation in UC patients thereby contributing to a better understanding of the key mechanism of action of ETR. However, these findings require validation in larger cohorts.

P062 Characterization of UC1 and UC2 patients: towards personalized medicine in Ulcerative Colitis

Abstract Background Ulcerative colitis (UC) is a highly heterogeneous chronic inflammatory bowel disease (IBD) that primarily affects the colon. Although there are some available classifications, mostly based on clinical parameters, the lack of a molecular stratification prevents full comprehension of the diagnostic and prognostic heterogeneity of patients, and thus from correctly predicting their response to available treatments. We have recently developed an unbiased stratification of UC patients (UC1/UC2) based on their transcriptomic profiles (Czarnewski P; et al. Nature Communications, 2019), which holds great potential for the design of personalized medicine in IBD. However, further characterization is necessary to validate it and consolidate its clinical application. Methods To achieve this goal, we used bulk and single-cell RNA sequencing (sc-RNAseq) datasets from a prospective cohort of Swedish IBD patients to understand whether UC1 and UC2 are different diseases or states of the same disease, and to deeply characterize the cellular composition of UC1 and UC2 patients. In addition, we took advantage of murine spatial transcriptomics datasets of colonic tissues at steady state or during mucosal healing, to get insights into the spatiotemporal dynamics of UC1/UC2 transcriptional profiles. Results A longitudinal analysis of UC1/UC2 transcriptomic profiles as well as gene module analysis revealed that UC1 and UC2 profiles are fluctuant during the course of disease, eventually representing different stages of the same disease. scRNAseq analysis allowed us to identify specific cell types characterizing UC2 patients.[FC1] Finally, while genes defining UC2 patients distributed homogenously within the murine mouse colon at steady state and during mucosal healing, UC1 genes primarily mapped within damage/regeneration regions. Conclusion This study details the differences in immune cell composition and molecular pathways in UC1 and UC2 patients, contributing to a more comprehensive understanding of the new molecular stratification system we have developed for ulcerative colitis patients.

Exploration of Positive and Negative Schizophrenia Symptom Heterogeneity and Establishment of Symptom-Related miRNA-mRNA Regulatory Network: Based on Transcriptome Sequencing Data.

Schizophrenia (SCZ) symptoms can be classified as positive and negative ones, each of which has distinct traits and possibly differences in gene expression and regulation. The co-expression networks linked to PANSS (Positive and Negative Syndrome Scale) scores were identified by weighted gene co-expression network analysis (WGCNA) using the expression profiles of miRNA and mRNA in the peripheral blood of first-episode SCZ patients. The heterogeneity between positive and negative symptoms was demonstrated using gene functional enrichment, gene-medication interaction, and immune cell composition analysis. Then, target gene prediction and correlation analysis of miRNA and mRNA constructed a symptom-related miRNA-mRNA regulatory network, screened regulatory pairs, and predicted binding sites. A total of six mRNA co-expression modules, two miRNA co-expression modules, and ten hub genes were screened to be significantly associated with positive symptoms; five mRNA co-expression modules and eight hub genes were correlated with negative symptoms. Positive symptom-related modules were significantly enriched in axon guidance, actin skeleton regulation, and sphingolipid signaling pathway, while negative symptom-related modules were significantly enriched in adaptive immune response, leukocyte migration, dopaminergic synapses, etc. The development of positive symptoms may have been influenced by potential regulatory pairings such as miR-98-5p-EIF3J, miR-98-5p-SOCS4, let-7b-5p-CLUH, miR-454-3p-GTF2H1, and let-7b-5p-SNX17. Additionally, immune cells were substantially connected with several hub genes for symptoms. Positive and negative symptoms in SCZ individuals were heterogeneous to some extent. miRNAs such as let-7b-5p and miR-98-5p might contribute to the incidence of positive symptoms by targeting mRNAs, while the immune system's role in developing negative symptoms may be more nuanced.

P016 Reduction of mucosal (active) eosinophils, B cells and T cells after vedolizumab therapy in patients with ulcerative colitis

Abstract Background Patients with ulcerative colitis (UC) are often treated with biological therapies or small molecules. Knowledge about the impact of these therapies on the intestinal and peripheral blood immune cell composition is scarce. Therefore, we investigated how advanced therapies modulate immune cell distribution in UC patients. Methods We included 30 UC patients (53% male, median age 42 years) who started a biological or small molecule. Before the first drug administration, mucosal colonic biopsies and a peripheral blood sample were obtained. At the end of induction, colonic biopsies and peripheral blood were sampled again. Patients starting adalimumab (n=2), infliximab (n=3), vedolizumab (n=11), ustekinumab (n=6), ozanimod (n=2) and the JAK inhibitors filgotinib (n=3) and tofacitinib (n=3) were included. Endoscopic improvement was defined as a Mayo endoscopic subscore of 0-1 at the end of induction. From the biopsies, a single-cell suspension was made. Intestinal and circulating immune cells were characterized via flow cytometry. Statistical analysis was performed using a paired t-test. Results Independent of the mechanism of action (MOA), patients responding to therapy showed a decrease of colonic granulocytes (neutrophils (p<0.0001) (Figure 1A), basophils (p<0.0001) (Figure 1B) and eosinophils (p=0.008) (Figure 1C)), active eosinophils (p=0.002) (Figure 1D)), B cells (p=0.05) (Figure 1E), regulatory T cells (p<0.0001) (Figure 1F) and T helper (Th) 2 cells (p=0.02) (Figure 1G), balanced with an increase of Th1 cells (p=0.03) (Figure 1H). In peripheral blood, eosinophils increased in patients not responding to therapy (p=0.05) (Figure 1I). Furthermore, we observed that only patients starting vedolizumab (n=11) showed a decrease in colonic eosinophils (p=0.02) (Figure 1J), active eosinophils (p=0.002) (Figure 1K), B cells (p=0.03) (Figure 1L) and T cells (p=0.004) (Figure 1M). Considering only non-vedolizumab patients (n=19), we did not observe this effect. Conclusion UC patients responding to advanced therapies showed a different intestinal immune cell distribution compared to non-responders, regardless of MOA. Vedolizumab therapy furthermore decreased several mucosal immune cell subsets that migrate to the gut through α4β7-MAdCAM-1 binding. While the effect of vedolizumab on B cells and T cells was previously described, we have now potentially identified an additional eosinophil-reducing effect in the colon.

Abstract A061: A novel genetically engineered mouse model of Myc-driven pancreatic cancer recapitulates phenotypic heterogeneity, metastasis, and therapy resistance seen in clinical populations

Abstract One of the most aggressive cancers in the US is pancreatic ductal adenocarcinoma (PDAc), whose incidence is expected to rise in the coming years. The standard-of-care treatments have improved over the past few decades, but they still primarily involve harsh chemotherapy cocktails and have only marginally increased overall survival, to a 5-year survival rate of 12 percent. c-MYC (MYC), a potent transcription factor, is frequently dysregulated in PDAc. In PDAc and other cancers, MYC plays a significant role in tumor progression, and its dysregulation has been linked to tumor aggressiveness and therapeutic resistance. In various mouse models of cancer, it has been demonstrated that oncogenic MYC expression controls components of the tumor microenvironment (TME). MYC expression in PDAc has been associated with a desmoplastic immune suppressive TME, though the precise mechanism is still unknown. In this study, we introduce a novel genetically modified mouse model (GEMM) of PDAc that can be used to simulate the disease's heterogeneity and investigate how MYC controls the tumor’s immune and stromal microenvironments. In the pancreas of our KMCERT2 model, both mutant Kras and lowly deregulated Myc are expressed through inducible Cre-driven mechanisms. Our research demonstrates how deregulated MYC cooperates with oncogenic KRASG12D in the adult pancreas to promote PDAc, faithfully reproducing the inter- and intra-tumoral heterogeneity observed in clinical PDAc populations. Currently, an embryonic KrasG12D- and p53 loss/mutant-driven PDAc model (KPC) is used for the majority of murine studies of PDAc. To learn more about the mechanisms underlying observed phenotypes in our KMCERT2 model, RNA- and DNA sequencing were performed on microdissected autochthonous tumor specimens as well as KMCERT2 tumor-derived cell lines. In contrast to the KPC model, our inducible KMCERT2 model of PDAc exhibits genetic alterations, such as CDKN2A loss, comparable to human disease. A distinct loss of nuclear p53 expression is also observed. Intriguingly, multiplexed immunohistochemistry analysis of immune cell composition showed that MYC-driven tumors have a higher density of antigen-presenting cells (APCs) when compared to spontaneous KPC tumors. Standard-of-care medications like gemcitabine and FOLFIRINOX are frequently ineffective against human PDAc. Orthotopic therapeutic studies using our KMCERT2 tumor-derived cell lines show a variety of responses to these therapies, with both resistant and sensitive tumor models, allowing us to use this model to better understand the mechanisms causing therapeutic resistance and to test new therapies. Additionally, we observe consistent liver metastasis in both spontaneous and orthotopic transplant settings. Together, these studies investigate the function of dysregulated MYC expression in murine PDAc metastatic behavior, immune phenotypes, and therapeutic response. It also offers mouse models of PDAc that are both spontaneous and orthotopic, recapitulating the complex and highly metastatic nature of the human disease. Citation Format: Isabel A. English, Patrick J. Worth, Kevin A. MacPherson, Michael B. Heskett, Vidhi Shah, Jackie L. Phipps, Courtney Betts, Shamilene Sivagnanam, Carl Pelz, Amy S. Farrell, Brittany L. Allen-Petersen, Meghan M. Joly, Motoyuki Tsuda, Colin J. Daniel, Jenny Eng, Xiaoyan Wang, Ashley L. Kiemen, Laura D. Wood, Terry K. Morgan, Mary C. Thoma, Jennifer M. Chu, Paul T. Spellman, Lisa M. Coussens, Ellen M. Langer, Rosalie C. Sears. A novel genetically engineered mouse model of Myc-driven pancreatic cancer recapitulates phenotypic heterogeneity, metastasis, and therapy resistance seen in clinical populations [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Pancreatic Cancer; 2023 Sep 27-30; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(2 Suppl):Abstract nr A061.

Abstract A028: Multiomic modelling of pancreatic IPMN stroma reveals distinct tertiary lymphoid structure distribution: Mapping the transcriptomic landscape via regional bulk, single-cell and subcellular approaches

Abstract Background Intraductal Papillary Mucinous Neoplasms (IPMN) remain the largest subtype of cystic pancreatic cancer precursors. Cancer risk has been observed to vary between histological grades and histological subtypes. Spatial characterisation has revealed variation in immune cell distribution disease subtypes. Methods A cohort of 14 surgically resected IPMN tumors across a range of histological grades (Low-grade LG, high-grade HG and invasive IPMN cancers IPMN-PDAC) and subtypes (gastric, intestinal, pancreaticobiliary) underwent multimodal spatial interrogation. After expert histopathological annotation; tissue sections underwent regional whole transcriptome analysis with TempO-seq and 10x Visium. Extensive region analysis with NanoString GeoMx employing segmentation using staining for epithelium (PanCK) fibroblast stroma (aSMA) was performed. A tissue microarray was then constructed, and representative cores underwent single-cell and subcellular spatial transcriptomic analysis with NanoString CosMx. Raw count data and digital images were exported and analysed using Seurat, Giotto, SPATA2 and custom R pipelines. Region deconvolution, Harmony integration, Leiden Clustering, Gene Set Enrichment Analysis, Trajectory Mapping, and Moran’s I Analysis were performed. Results TempO-seq revealed up-regulation of canonical oncogene expression in all IPMN-PDAC cases as compared to LG and HG IPMN. There were no statistically significant differences in expression comparing LG and HG IPMN lesions. Visium differential gene expression and clustering models identified cancer epithelium, stroma and lymphatic components that correlated with histopathological annotations. Immune cell rich spots were identified via gene ontology of top 50 marker genes. The spatial trajectory of B-cell expression signatures in IPMN-PDAC showed greater concentration and less variability than HG tumors, Moran’s I -0.34 vs 0.12 (P = 0.021). B-cells in HG IPMN were showed greater concentration and less variability than LG IPMN, Moran’s I -0.15 vs 0.02 (P=0.05). Much of this concentration was in identified lymphoid aggregates or tertiary lymphoid structures. The spatial trajectory of T-cell expression. The spatial trajectory of macrophage expression showed greater concentration and less variability than in LG and HG tumors. GeoMx analysis of stromal regions identified up regulation of B cell signatures in IPMN PDAC and HG IPMN when compared to LG IPMN. Markers associated with TLS formation were found to be significantly upregulated including CXCL13, CXCR5 and LAMP3. Pancreaticobiliary subtypes were found to have the least concentrated B-cell distribution across subtypes. Conclusions Immune cell composition was found to vary across histological grades and subtypes of IPMN. A paradoxical relationship was observed between T-cell infiltrates and B-cell and macrophage populations. The greater proportion of tertiary lymphoid structures, and high levels of TLS specific gene expression, may indicate a propensity for b-cell activation in IPMN tumors which progress to malignancy. Citation Format: Andrew J. Cameron, Assya Legrini, Colin S. Wood, Craig Nourse, Yoana Doncheva, Claire Kennedy Dietrich, Colin Nixon, Jennifer Hay, Fraser Duthie, Pawel Herzyk, Jennifer Morton, Nigel B. Jamieson. Multiomic modelling of pancreatic IPMN stroma reveals distinct tertiary lymphoid structure distribution: Mapping the transcriptomic landscape via regional bulk, single-cell and subcellular approaches [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Pancreatic Cancer; 2023 Sep 27-30; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(2 Suppl):Abstract nr A028.

Glioblastoma with high O6-methyl-guanine DNA methyltransferase expression are more immunologically active than tumors with low MGMT expression.

Glioblastoma (GBM) is a highly lethal brain tumor. The effectiveness of temozolomide (TMZ) treatment in GBM is linked to the methylation status of O6-methyl-guanine DNA methyltransferase (MGMT) promoter. Patients with unmethylated MGMT promoter have limited treatment options available. Consequently, there is a pressing need for alternative therapeutic strategies for such patients. Data, including transcriptomic and clinical information, as well as information on MGMT promoter methylation status in primary GBM, were obtained from The Cancer Genome Atlas (TCGA) (n=121) and Chinese Glioma Genome Atlas (CGGA) (n=83) datasets. Samples were categorized into high and low MGMT expression groups, MGMT-high (MGMT-H) and MGMT-low (MGMT-L) tumors. A comprehensive transcriptome analysis was conducted to explore the tumor-immune microenvironment. Furthermore, we integrated transcriptome data from 13 GBM patients operated at our institution with findings from tumor-infiltrating lymphocyte (TIL) cultures, specifically investigating their response to autologous tumors. Gene signatures associated with various immune cells, including CD8 T cells, helper T cells, B cells, and macrophages, were noted in MGMT-H tumors. Pathway analysis confirmed the enrichment of immune cell-related pathways. Additionally, biological processes involved in the activation of monocytes and lymphocytes were observed in MGMT-H tumors. Furthermore, TIL culture experiments showed a greater presence of tumor-reactive T cells in MGMT-H tumors compared to MGMT-L tumors. These findings suggest that MGMT-H tumors has a potential for enhanced immune response against tumors mediated by CD8 T cells. Our study provides novel insights into the immune cell composition of MGMT-H tumors, which is characterized by the infiltration of type 1 helper T cells and activated B cells, and also the presence of tumor-reactive T cells evidenced by TIL culture. These findings contribute to a better understanding of the immune response in MGMT-H tumors, emphasizing their potential for immunotherapy. Further studies are warranted to investigate on the mechanisms of MGMT expression and antitumor immunity.

Elucidating key immunological biomarkers and immune microenvironment dynamics in aging-related intracranial aneurysm through integrated multi-omics analysis.

The exact cause of intracranial aneurysms (IA) is still unclear. However, pro-inflammatory factors are known to contribute to IA progression. The specific changes in the immune microenvironment of IAs remain largely unexplored. This study analyzed single-cell sequencing data from a male mouse model of brain aneurysm, focusing on samples before and after elastase-induced Willis aneurysms. The data helped identify eight distinct cell subpopulations: fibroblasts, macrophages, NK cells, endothelial cells, B cells, granulocytes, and monocytes. The study also involved bulk RNA sequencing of 97 IA samples, utilizing ssGSEA and CIBERSORT algorithms for analysis. Intercellular communication among these cells was inferred to understand the immune dynamics in IA. The study found that fibroblasts and macrophages are predominant in various disease states of IA. Notably, the onset of IA was marked by a significant increase in fibroblasts and a decrease in macrophages. There was a marked increase in cellular interactions, especially involving macrophages, at the onset of the disease. Through enrichment analysis, 12 potential immunogenic biomarkers were identified. Of these, Rgs1 emerged as a critical molecule in IA formation, confirmed through secondary validation in a single-cell sequencing dataset. This comprehensive analysis of immune cell composition and intercellular communication in IA tissues highlights the significant roles of macrophages and the molecule Rgs1. These findings shed light on the physiological and pathological conditions of IA, offering new insights into its immune microenvironment.

Utilizing multimodal mass spectrometry imaging for profiling immune cell composition and N-glycosylation across colorectal carcinoma disease progression.

Colorectal cancer (CRC) stands as a leading cause of death worldwide, often arising from specific genetic mutations, progressing from pre-cancerous adenomas to adenocarcinomas. Early detection through regular screening can result in a 90% 5-year survival rate for patients. However, unfortunately, only a fraction of CRC cases are identified at pre-invasive stages, allowing progression to occur silently over 10-15years. The intricate interplay between the immune system and tumor cells within the tumor microenvironment plays a pivotal role in the progression of CRC. Immune cell clusters can either inhibit or facilitate tumor initiation, growth, and metastasis. To gain a better understanding of this relationship, we conducted N-glycomic profiling using matrix-assisted laser desorption-ionization mass spectrometry imaging (MALDI-MSI). We detected nearly 100 N-glycan species across all samples, revealing a shift in N-glycome profiles from normal to cancerous tissues, marked by a decrease in high mannose N-glycans. Further analysis of precancerous to invasive carcinomas showed an increase in pauci-mannose biantennary, and tetraantennary N-glycans with disease progression. Moreover, a distinct stratification in the N-glycome profile was observed between non-mucinous and mucinous CRC tissues, driven by pauci-mannose, high mannose, and bisecting N-glycans. Notably, we identified immune clusters of CD20+ B cells and CD3/CD44+ T cells distinctive and predictive with signature profiles of bisecting and branched N-glycans. These spatial N-glycan profiles offer potential biomarkers and therapeutic targets throughout the progression of CRC.

Spatial analysis of tissue immunity and vascularity by light sheet fluorescence microscopy.

The pathogenesis of cancer and cardiovascular diseases is subjected to spatiotemporal regulation by the tissue microenvironment. Multiplex visualization of the microenvironmental components, including immune cells, vasculature and tissue hypoxia, provides critical information underlying the disease progression and therapy resistance, which is often limited by imaging depth and resolution in large-volume tissues. To this end, light sheet fluorescence microscopy, following tissue clarification and immunostaining, may generate three-dimensional high-resolution images at a whole-organ level. Here we provide a detailed description of light sheet fluorescence microscopy imaging analysis of immune cell composition, vascularization, tissue perfusion and hypoxia in mouse normal brains and hearts, as well as brain tumors. We describe a procedure for visualizing tissue vascularization, perfusion and hypoxia with a transgenic vascular labeling system. We provide the procedures for tissue collection, tissue semi-clearing and immunostaining. We further describe standard methods for analyzing tissue immunity and vascularity. We anticipate that this method will facilitate the spatial illustration of structure and function of the tissue microenvironmental components in cancer and cardiovascular diseases. The procedure requires 1-2 weeks and can be performed by users with expertise in general molecular biology.

Obesity modulates the cellular and molecular microenvironment in the peritoneal cavity: implication for ovarian cancer risk.

Abdominal obesity increases the risk of developing ovarian cancer but the molecular mechanisms of how obesity supports ovarian cancer development remain unknown. Here we investigated the impact of obesity on the immune cell and gene expression profiles of distinct abdominal tissues, focusing on the peritoneal serous fluid (PSF) and the omental fat band (OFB) as critical determinants for the dissemination of ovarian metastases and early metastatic events within the peritoneal cavity. Female C57BL/6 mice were fed a low-fat (LFD) or a high-fat diet (HFD) for 12 weeks until the body weights in the HFD group were significantly higher and the mice displayed an impaired glucose tolerance. Then the mice were injected with the murine ovarian cancer cells (MOSE-LTICv) while remaining on their diets. After 21 days, the mice were sacrificed, tumor burden was evaluated and tissues were harvested. The immune cell composition of abdominal tissues and changes in gene expression in the PSF and OFB were evaluated by flow cytometry and qPCR RT2-profiler PCR arrays and confirmed by qRT-PCR, respectively. Other peritoneal adipose tissues including parametrial and retroperitoneal white adipose tissues as well as blood were also investigated. While limited effects were observed in the other peritoneal adipose tissues, feeding mice the HFD led to distinct changes in the immune cell composition in the PSF and the OFB: a depletion of B cells but an increase in myeloid-derived suppressor cells (MDSC) and mono/granulocytes, generating pro-inflammatory environments with increased expression of cyto- and chemokines, and genes supporting adhesion, survival, and growth, as well as suppression of apoptosis. This was associated with a higher peritoneal tumor burden compared to mice fed a LFD. Changes in cellular and genetic profiles were often exacerbated by the HFD. There was a large overlap in genes that were modulated by both the HFD and the cancer cells, suggesting that this 'genetic fingerprint' is important for ovarian metastases to the OFB. In accordance with the 'seed and soil' theory, our studies show that obesity contributes to the generation of a pro-inflammatory peritoneal environment that supports the survival of disseminating ovarian cancer cells in the PSF and the OFB and enhances the early metastatic adhesion events in the OFB through an increase in extracellular matrix proteins and modulators such as fibronectin 1 and collagen I expression as well as in genes supporting growth and invasion such as Tenacin C. The identified genes could potentially be used as targets for prevention strategies to lower the ovarian cancer risk in women with obesity.

Identification of SV2C and DENR as Key Biomarkers for Parkinson's Disease Based on Bioinformatics, Machine Learning, and Experimental Verification.

The objective of this study is to investigate the potential biomarkers and therapeutic target genes for Parkinson's disease (PD). We analyzed four datasets (GSE8397, GSE20292, GSE20163, GSE20164) from the Gene Expression Omnibus database. We employed weighted gene co-expression network analysis and differential expression analysis to select genes and perform functional analysis. We applied three algorithms, namely, random forest, support vector machine recursive feature elimination, and least absolute shrinkage and selection operator, to identify hub genes, perform functional analysis, and assess their clinical diagnostic potential using receiver operating characteristic (ROC) curve analysis. We employed the xCell website to evaluate differences in the composition patterns of immune cells in the GEO datasets. We also collected serum samples from PD patients and established PD cell model to validate the expression of hub genes using enzyme-linked immunosorbent assay and quantitative real-time polymerase chain reaction. Our findings identified SV2C and DENR as two hub genes for PD and decreased in PD brain tissue compared with controls. ROC analysis showed effectively value of SV2C and DENR to diagnose PD, and they were downregulated in the serum of PD patients and cell model. Functional analysis revealed that dopamine vesicle transport and synaptic vesicle recycling are crucial pathways in PD. Besides, the differences in the composition of immune cells, especially basophils and T cells, were discovered between PD and controls. In summary, our study identifies SV2C and DENR as potential biomarkers for diagnosing PD and provides a new perspective for exploring the molecular mechanisms of PD.

Immune and stromal transcriptional patterns that influence the outcome of classic Hodgkin lymphoma

Classic Hodgkin lymphoma (cHL) is characterized by a rich immune microenvironment as the main tumor component. It involves a broad range of cell populations, which are largely unexplored, even though they are known to be essential for growth and survival of Hodgkin and Reed–Sternberg cells. We profiled the gene expression of 25 FFPE cHL samples using NanoString technology and resolved their microenvironment compositions using cell-deconvolution tools, thereby generating patient-specific signatures. The results confirm individual immune fingerprints and recognize multiple clusters enriched in refractory patients, highlighting the relevance of: (1) the composition of immune cells and their functional status, including myeloid cell populations (M1-like, M2-like, plasmacytoid dendritic cells, myeloid-derived suppressor cells, etc.), CD4-positive T cells (exhausted, regulatory, Th17, etc.), cytotoxic CD8 T and natural killer cells; (2) the balance between inflammatory signatures (such as IL6, TNF, IFN-γ/TGF-β) and MHC-I/MHC-II molecules; and (3) several cells, pathways and genes related to the stroma and extracellular matrix remodeling. A validation model combining relevant immune and stromal signatures identifies patients with unfavorable outcomes, producing the same results in an independent cHL series. Our results reveal the heterogeneity of immune responses among patients, confirm previous findings, and identify new functional phenotypes of prognostic and predictive utility.

Making mouse transcriptomics deconvolution accessible with immunedeconv.

Transcriptome deconvolution has emerged as a reliable technique to estimate cell-type abundances from bulk RNA sequencing data. Unlike their human equivalents, methods to quantify the cellular composition of complex tissues from murine transcriptomics are sparse and sometimes not easy to use. We extended the immunedeconv R package to facilitate the deconvolution of mouse transcriptomics, enabling the quantification of murine immune-cell types using 13 different methods. Through immunedeconv, we further offer the possibility of tweaking cell signatures used by deconvolution methods, providing custom annotations tailored for specific cell types and tissues. These developments strongly facilitate the study of the immune-cell composition of mouse models and further open new avenues in the investigation of the cellular composition of other tissues and organisms. The R package and the documentation are available at https://github.com/omnideconv/immunedeconv.

Analysis of brain and blood single-cell transcriptomics in acute and subacute phases after experimental stroke.

Cerebral ischemia triggers a powerful inflammatory reaction involving peripheral leukocytes and brain resident cells that contribute to both tissue injury and repair. However, their dynamics and diversity remain poorly understood. To address these limitations, we performed a single-cell transcriptomic study of brain and blood cells 2 or 14 days after ischemic stroke in mice. We observed a strong divergence of post-ischemic microglia, monocyte-derived macrophages and neutrophils over time, while endothelial cells and brain-associated macrophages showed altered transcriptomic signatures at 2 days poststroke. Trajectory inference predicted the in situ trans-differentiation of macrophages from blood monocytes into day 2 and day 14 phenotypes, while neutrophils were projected to be continuously de novo recruited from the blood. Brain single-cell transcriptomes from both female and male aged mice were similar to that of young male mice, but aged and young brains differed in their immune cell composition. Although blood leukocyte analysis also revealed altered transcriptomes after stroke, brain-infiltrating leukocytes displayed higher transcriptomic divergence than their circulating counterparts, indicating that phenotypic diversification occurs within the brain in the early and recovery phases of ischemic stroke. A portal ( https://anratherlab.shinyapps.io/strokevis/ ) is provided to allow user-friendly access to our data.

Identification and validation of genes associated with aging-related cardiovascular disease.

Aging is acknowledged as the most significant risk factor for cardiovascular disease (CVD). This study sought to identify and validate potential aging-related genes associated with CVD by using bioinformatics. The confluence of the limma test, weighted correlation network analysis (WGCNA), and 2129 aging and senescence-associated genes led to the identification of aging-related differential expression genes (ARDEGs). By using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG), potential biological roles and pathways of ARDEGs were identified. To find the significantly different functions between CVD and non-cardiovascular disease (nCVD) and to reckon the processes score, enrichment analysis of all genes was carried out using gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA). By using GO and KEGG, potential biological roles and pathways of ARDEGs were identified. To evaluate the immune cell composition of the immune microenvironment, we performed an immune infiltration analysis on the dataset from the training group. We were able to acquire four ARDEGs (PTGS2, MMP9, HBEGF, and FN1). Aging, cellular senescence, and nitric oxide signal transduction were selected for biological function analysis. The diagnostic value of the four ARDEGs in distinguishing CVD from nCVD samples was deemed to be favorable. This research identified four ARDEGs that are associated with CVD. This study provides insight into prospective novel biomarkers for aging-related CVD diagnosis and progression monitoring.

Immune Cell Alterations and PI3K-PKB Pathway Suppression in Patients with Allergic Rhinitis Undergoing Sublingual Immunotherapy.

Our prior clinical study assessed the efficacy and safety of sublingual immunotherapy (SLIT) with standardized Dermatophagoides farina drops on patients with allergic rhinitis (AR) while analyzing the characteristics of adverse reactions. This study was conducted to evaluate the immune cell composition alterations in AR patients before and after SLIT, and to comprehensively investigate the role and changes of antigen-specific immune cells associated with treatment efficacy. A total of 68 AR patients who completed 12months of SLIT were included in the study. Before the trial's initiation and after 1year of SLIT, 10ml of venous blood was collected. Peripheral blood mononuclear cells were isolated using the Ficoll gradient method. The mRNA transcriptome was analyzed using an Affymetrix microarray. The proportions of 22 immune cell types were calculated via the CIBERSORTx platform. Correlations between each immune cell type and SLIT were analyzed. PI3K-PKB pathway dysregulation were analyzed using quantitative PCR and Western blot. Flow cytometry was utilized to assess the percentages of Th1 and Th2 cells. Mono-sensitized AR patients exhibited marked increases in plasma cells, activated memory T cells, regulatory T cells, and activated dendritic cells, while experiencing decreased neutrophils and resting dendritic cells. In poly-sensitized AR patients, the most notable change was an increase in regulatory T cells, coupled with decreased T follicular helper cells, resting dendritic cells, and activated mast cells. These findings indicated that SLIT reshaped immune cell profiles in AR patients, and, notably, the specific changes differed between mono-sensitized and poly-sensitized individuals. Furthermore, SLIT appeared to shift the immune response towards a Th2 decrease profile in both groups. Importantly, suppression of the PI3K-PKB pathway was evidenced as inhibition of PKB phosphorylation and the decrease of glycogen synthase kinase 3 β (GSKβ) and mammalian target of rapamycin (mTOR) expression after SLIT. Our study has demonstrated that SLIT treatment led to distinct changes in immune cell profiles between mono-sensitized and poly-sensitized AR patients. Furthermore, SLIT appeared to reduce a Th2 immune response, highlighting its efficacy in AR treatment. Importantly, the study revealed the suppression of the PI3K-PKB pathway, shedding light on the immunological mechanisms underlying SLIT's effectiveness.