Heterogeneity Of Immune Response Research Articles

Translating Lupus: Comparative Transcriptional Profiles of Preclinical Lupus Models and Their Relevance to Human Disease

Systemic lupus erythematosus (SLE) is a chronic, systemic autoimmune disease which can present with mixed organ involvement. Kidney involvement in lupus nephritis (LN) is a severe complication and major cause of mortality in SLE patients, second only to cardiovascular disease. While mouse models have helped uncover some molecular pathways involved in SLE/LN, we need a better understanding of the connection of these pathways and the immune cells involved in disease pathogenesis to develop new and effective therapies. Furthermore, models used for studying SLE/LN in mice have a heterogeneous immune response and may not always represent disease manifestations observed in patients. Identifying models that have shared pathways with human disease would allow for better translation for developing effective SLE/LN therapies. The molecular pathways of five different SLE/LN models (MRL/lpr, poly (I:C)-induced, interferon-α-induced, bm12 GvHD, and spontaneous NZB/W F1) were compared to characterize the immune response in mouse kidneys. These models demonstrated varied magnitudes in immune responses and proportions of innate vs. adaptive cell involvement. These findings were compared to human molecular pathways and cell types from public databases, including the Accelerating Medicine Partnership–Systemic Lupus Erythematosus Program (AMP-SLE), to help corelate mechanisms involved in mouse models to human disease.

Heterogeneity of SARS-CoV-2 immune responses after the nationwide Omicron wave in China.

It remains unclear how previous infections and vaccinations influenced and shaped heterogeneous immune responses against Omicron and its variants in diverse populations in China. After the national wave of Omicron in early 2023, we evaluated serum levels of neutralizing antibodies (nAbs) against Omicron (B.1.1.529) and its variants (BA.5, BF.7, and CH1.1) in 33 COVID-19 convalescents and 40 uninfected vaccinees, using vesicular stomatitis virus-based pseudovirus neutralizing assay. In addition, we followed 34 Delta convalescent patients to compare their immune responses against Omicron before (late 2021) and after the Omicron wave (early 2023). NAbs at the acute phase of the disease were investigated in 50 Omicron inpatients, including 24 vaccinated and 26 unvaccinated patients. Among them, nasal mucosal IgA levels were measured in 42 subjects. Compared to vaccination, breakthrough infections significantly increased the breadth and magnitude of serum nAbs and mucosal IgA levels against Omicron variants. Exposure to Omicron but not Delta elicited stronger pan-Omicron responses. In Omicron inpatients, nAbs continued to rise as vaccination doses increased. However, in both vaccinees and convalescents, a fourth dose vaccination did not elicit higher nAbs against Omicron. Furthermore, nAbs against Omicron variants lasted longer than nAbs against WT SARS-CoV-2. Breakthrough infections of Omicron variants elicited specific immune responses against Omicron compared to vaccination and Delta infection. Although repeated vaccination revealed limited impacts on serum nAbs, populations at high risk of hospitalization may still benefit from continued vaccination.IMPORTANCEThe study described the specific humoral immunity against Omicron and its variants (BA.5, BF.7, and CH1.1) in diverse populations, including Delta-positive convalescent patients, Omicron-infected patients with a previous or current confirmed Delta infection, Omicron-positive patients, and healthy controls. In addition, we followed Delta convalescents for 1 year to evaluate the effect of a booster vaccine, breakthrough infection, and reinfection. Nasal mucosal IgA levels against SARS-CoV-2 were also examined. The findings of this study demonstrated the varied responses of individuals in different states following the outbreak of Omicron, highlighting the potential advantages of ongoing immunization for groups that are more vulnerable and have a greater likelihood of being hospitalized.

Humoral immune response as an indicator for protection against Covid-19 after anti-SARS-COV2-booster vaccination in hematological and oncological patients.

Cancer patients are at a higher risk to develop severe COVID-19 symptoms after SARS-CoV-2 infection compared to the general population and regularly show an impaired immune response to SARS-CoV-2 vaccination. In our oncological center, 357 patients with hematological and oncological diseases were monitored for neutralizing antibodies from October 2021 over 12 months. All patients had received three anti-SARS-CoV-2 vaccinations with an mRNA-(Comirnaty/BionTech or Spikevax/Moderna) or a vector vaccine (Vakzevria/AstraZeneca or JCOVDEN/Johnson&Johnson). Neutralizing anti-SARS-CoV-2 IgG antibodies in the patients' sera were detected within 3 months before, 3-10 weeks and 5-7 months after the booster vaccination (third vaccination). 112 patients developed a breakthrough SARS-CoV-2 infection during the observation period. High anti-SARS-Cov-2 antibody levels before infection significantly protected against symptomatic Covid-19 disease (p = .003). The median antibody titer in patients with asymptomatic Covid-19 disease was 2080 BAU/ml (binding antibody units per Milliliter) and 765 BAU/ml in symptomatic patients. 98% of the solid tumor patients reached seroconversion after the booster vaccination in comparison to 79% of the hematological patients. High antibody titers of >2080 BAU/ml after the booster vaccination were detected in 61% of the oncological and 34.8% of the hematological patients. 7-10 months after the booster vaccination, the anti-SARS-CoV-2 antibody titer declined to an average of 849 BAU/ml. Considering the heterogenous humoral immune response of cancer patients observed in this study, an individual vaccination strategy based on regular measurement of anti-SARS-CoV-2 antibody levels should be considered in contrast to fixed vaccination intervals.

30 Synergistic systematic analysis with fully human tissue models andin silico modeling of “copycats” reveals mechanisms of T cell suppression in clear cell renal cell carcinoma

Abstract Background Immune checkpoint-inhibitors have become a standard treatment for clear cell renal cell carcinoma (ccRCC). However, responses to checkpoint-inhibition are heterogeneous and many patients are resistant or eventually develop resistance. A better understanding of functional mechanisms governing immune responses in ccRCC is needed to identify biomarkers for therapeutic responses and to unravel novel therapeutic targets to overcome primary or acquired resistance to therapies. Methods We developed a fully human explant model derived from freshly resected ccRCC tissue (Fig. 1A). Our tissue explant model preserves all components of the tumor microenvironment including not only tumor cells, but also the immune cell compartment as well as tumor-stroma and -vasculature in culture (Fig. 1B). Following treatment with combined checkpoint-inhibition (Nivolumab plus Ipilimumab) or an anti-CCR5 inhibitor (Maraviroc), the tissue explants were analyzed by immunohistochemistry staining and multiplex cytokine profiling of 50 cytokines. Spatial and functional insights were incorporated in an agent-based in silico model (PhysiCell, Ghaffarizadeh et al., PLoS Comput. Biol., 2018) for unlimited exploration of functional cellular dynamics in the tumor microenvironment (Fig. 1D). Results Immunohistochemical analyses and cytokine profiling of ccRCC-tissue explants showed heterogeneous immune responses among different patients and indicated an impaired cytotoxic T cell response following checkpoint-inhibition (Fig. 1C). Spatial analyses of immune cell populations revealed clusters of CD8+ T cells and CD163+ macrophages localized closely to CD31+ endothelial cells. Further characterization of the tumor microenvironment revealed high CCR5-expression in the tumor, particularly on the tumor blood vessels (Fig. 1B). Treatment of the tissue explants with the anti-CCR5 inhibitor Maraviroc led to an increase of CD8+ T cells and cytotoxic cytokines (Granzyme B, IFNgamma, TNFalpha, IFNalpha2) in the tumor in comparison to checkpoint-inhibition (Fig. 1C). Spatial and functional information from cultured ccRCC-tissue explants were integrated into an agent-based in silico model of the ccRCC tumor microenvironment, which includes tumor cells, T cells, macrophages and endothelial cells (Fig. 1D). In silico simulation of different immune cell modulating treatment conditions showed an increase of T cells and cytotoxic cytokines upon blockade of the interaction between T cells with endothelial cells or macrophages (Fig. 1E). Conclusions Our combined ex vivo and in silico analyses provide evidence for immunosuppression in the ccRCC tumor microenvironment mediated by macrophages and endothelial cells. CCR5 was shown to be a potential target to overcome immune resistance to checkpoint-inhibition in ccRCC. Further characterization of immune cell compositions and functional mechanisms in the perivascular area is imperative to enhance therapeutic responses to immunotherapies for ccRCC.

Single-cell RNA-seq revealed heterogeneous responses and functional differentiation of hemocytes against white spot syndrome virus infection in Litopenaeus vannamei.

Current knowledge of shrimp hemocyte classification mainly comes from morphology, which hinder in-depth characterization of cell lineage development, functional differentiation, and different immune response of hemocyte types during pathogenic infections. Here, single-cell RNA sequencing was used for mapping hemocytes during white spot syndrome virus (WSSV) infection in Litopenaeus vannamei, identifying 16 cell clusters and evaluating their potential antiviral functional characteristics. We have described the dynamic balance between viral infestation and hemocyte immunity. And the functional differentiation of hemocytes under WSSV stimulation was further characterized. Our results provided a comprehensive transcriptional landscape and revealed the heterogeneous immune response in shrimp hemocytes during WSSV infection.

Highly heterogenous humoral immune response in Lyme disease patients revealed by broad machine learning-assisted antibody binding profiling with random peptide arrays.

Lyme disease (LD), a rapidly growing public health problem in the US, represents a formidable challenge due to the lack of detailed understanding about how the human immune system responds to its pathogen, the Borrelia burgdorferi bacterium. Despite significant advances in gaining deeper insight into mechanisms the pathogen uses to evade immune response, substantial gaps remain. As a result, molecular tools for the disease diagnosis are lacking with the currently available tests showing poor performance. High interpersonal variability in immune response combined with the ability of the pathogen to use a number of immune evasive tactics have been implicated as underlying factors for the limited test performance. This study was designed to perform a broad profiling of the entire repertoire of circulating antibodies in human sera at the single-individual level using planar arrays of short linear peptides with random sequences. The peptides sample sparsely, but uniformly the entire combinatorial sequence space of the same length peptides for profiling the humoral immune response to a B.burg. infection and compare them with other diseases with etiology similar to LD and healthy controls. The study revealed substantial variability in antibody binding profiles between individual LD patients even to the same antigen (VlsE protein) and strong similarity between individuals diagnosed with Lyme disease and healthy controls from the areas endemic to LD suggesting a high prevalence of seropositivity in endemic healthy control. This work demonstrates the utility of the approach as a valuable analytical tool for agnostic profiling of humoral immune response to a pathogen.

Comparison of whole blood cytokine immunoassays for rapid, functional immune phenotyping in critically ill patients with sepsis

BackgroundSepsis is characterized by highly heterogeneous immune responses associated with a spectrum of disease severity. Methods that rapidly and sensitively profile these immune responses can potentially personalize immune-adjuvant therapies for sepsis. We hypothesized that the ELLA microfluidic approach to measure cytokine production from the whole blood of septic and critically ill patients would deliver faster, more precise results than the existing optic-driven ELISpot quantification. We tested our hypothesis by measuring ex vivo-stimulated production of TNF and IFNγ in critically ill and septic patients (n = 22), critically ill and non-septic patients (n = 10), and healthy volunteers (n = 10) through both ELLA and ELISpot immunoassays. Blood samples were subjected to one of three stimulants for 4 h or 18 h durations during days 1, 7–10, and 14 of critical illness. Stimulants for lymphocytes included anti-CD3/anti-CD28 and phorbol 12-myristate 13-acetate (PMA), whereas LPS was used for monocytes. Stimulated TNF and IFNγ concentrations were then associated with 30-day mortality.ResultsBoth ELISpot and ELLA immunoassays showed substantial agreement in TNF concentrations post 4 h and 18 h LPS stimulation, with concordance correlation coefficients at 0.62 and 0.60, respectively. ELLA had a broad dynamic measurement range and provided accurate TNF and IFNγ readings at both minimal and elevated cytokine concentrations (with mean coefficients of variation between triplicate readings at 2.1 ± 1.4% and 4.9 ± 7.2%, respectively). However, there was no association between the ELLA-determined cytokine concentrations on the first day of critical illness and 30-day mortality rate. In contrast, using the ELISpot for cytokine quantification revealed that non-survivors had reduced baseline TNF levels at 18 h, decreased LPS-induced TNF levels at 18 h, and diminished TNF levels post 4 h/18 h anti-CD3/28 stimulation.ConclusionsOur study affirms the feasibility of obtaining dependable immune phenotyping data within 6 h of blood collection from critically ill patients, both septic and non-septic, using the ELLA immunoassay. Both ELLA and ELISpot can offer valuable insights into prognosis, therapeutic strategies, and the underlying mechanisms of sepsis development.

Patterns of inflammatory immune responses in patients with septic shock receiving vitamin C, hydrocortisone, and thiamine: clustering analysis in Korea.

Sepsis is characterized by heterogeneous immune responses that may evolve during the course of illness. This study identified inflammatory immune responses in septic patients receiving vitamin C, hydrocortisone, and thiamine. This was a single-center, post-hoc analysis of 95 patients with septic shock who received the vitamin C protocol. Blood samples were drawn on days 1-2, 3-4, and 6-8 after shock onset. Group-based multi-trajectory modeling was used to identify immune trajectory groups. The median age was 78 years (interquartile range, 70-84 years), and 56% were male. Clustering analysis identified group 1 (n=41), which was characterized by lower interleukin (IL)-6, tumor necrosis factor (TNF)-α, and IL-10 levels, and these levels remained stationary or mildly increased until day 7. Conversely, group 2 (n=54) expressed initially higher IL-6, TNF-α, and IL-10 levels that decreased rapidly by day 4. There was a nonsignificant increase in lymphocyte count and a decrease in C-reactive protein level until day 7 in group 2. The intensive care unit mortality rate was significantly lower in group 2 (39.0% vs. 18.5%, P=0.03). Group 2 also had a significantly higher decrease in the mean (standard deviation) vasopressor dose (norepinephrine equivalent: -0.09±0.16 μg/kg/min vs. -0.23±0.31 μg/kg/min, P<0.001) and Sequential Organ Failure Assessment score (0±5 vs. -4±3, P=0.002) between days 1 and 4. There may be different subphenotypes in septic patients receiving the vitamin C protocol.

Depicting the landscape of gut microbial-metabolic interaction and microbial-host immune heterogeneity in deficient and proficient DNA mismatch repair colorectal cancers

BackgroundAccumulating evidence has indicated the role of gut microbiota in remodeling host immune signatures, but various interplays underlying colorectal cancers (CRC) with deficient DNA mismatch repair (dMMR) and proficient DNA...

A precise molecular subtyping of ulcerative colitis reveals the immune heterogeneity and predicts clinical drug responses

Background and AimsWe sought to identify novel molecular subtypes of ulcerative colitis (UC) based on large-scale cohorts and establish a clinically applicable subtyping system for the precision treatment of the disease.MethodsEight microarray profiles containing colon samples from 357 patients were utilized. Expression heterogeneity was screened out and stable subtypes were identified among UC patients. Immune infiltration pattern and biological agent response were compared among subtypes to assess the value in guiding treatment. The relationship between PRLR and TNFSF13B genes with the highest predictive value was further validated by functional experiments.ResultsThree stable molecular subtypes were successfully identified. Immune cell infiltration analysis defined three subtypes as innate immune activated UC (IIA), whole immune activated UC (WIA), and immune homeostasis like UC (IHL). Notably, the response rate towards biological agents (infliximab/vedolizumab) in WIA patients was the lowest (less than 10%), while the response rate in IHL patients was the highest, ranging from 42 to 60%. Among the featured genes of subtypes, the ratio of PRLR to TNFSF13B could effectively screen for IHL UC subtype suitable for biological agent therapies (Area under curve: 0.961–0.986). Furthermore, we demonstrated that PRLR expressed in epithelial cells could inhibit the expression of TNFSF13B in monocyte-derived macrophages through the CXCL1-NF-κB pathway.ConclusionsWe identified three stable UC subtypes with a heterogeneous immune pattern and different response rates towards biological agents for the first time. We also established a precise molecular subtyping system and classifier to predict clinical drug response and provide individualized treatment strategies for UC patients.

Construction and Identification of an NLR-Associated Prognostic Signature Revealing the Heterogeneous Immune Response in Skin Cutaneous Melanoma.

Skin cutaneous melanoma (SKCM) is the deadliest dermatology tumor. Ongoing researches have confirmed that the NOD-like receptors (NLRs) family are crucial in driving carcinogenesis. However, the function of NLRs signaling pathway-related genes in SKCM remains unclear. To establish and identify an NLRs-related prognostic signature and to explore its predictive power for heterogeneous immune response in SKCM patients. Establishment of the predictive signature using the NLRs-related genes by least absolute shrinkage and selection operator-Cox regression analysis (LASSO-COX algorithm). Through univariate and multivariate COX analyses, NLRs signature's independent predictive effectiveness was proven. CIBERSORT examined the comparative infiltration ratios of 22 distinct types of immune cells. RT-qPCR and immunohistochemistry implemented expression validation for critical NLRs-related prognostic genes in clinical samples. The prognostic signature, including 7 genes, was obtained by the LASSO-Cox algorithm. In TCGA and validation cohorts, SKCM patients with higher risk scores had remarkably poorer overall survival. The independent predictive role of this signature was confirmed by multivariate Cox analysis. Additionally, a graphic nomogram demonstrated that the risk score of the NLRs signature has high predictive accuracy. SKCM patients in the low-risk group revealed a distinct immune microenvironment characterized by the significantly activated inflammatory response, interferon-α/γ response, and complement pathways. Indeed, several anti-tumor immune cell types were significantly accumulated in the low-risk group, including M1 macrophage, CD8 T cell, and activated NK cell. It is worth noting that our NLRs prognostic signature could serve as one of the promising biomarkers for predicting response rates to immune checkpoint blockade (ICB) therapy. Furthermore, the results of expression validation (RT-qPCR and IHC) were consistent with the previous analysis. A promising NLRs signature with excellent predictive efficacy for SKCM was developed.

The joint role of methylation and immune-related lncRNAs in ovarian cancer: Defining molecular subtypes and developing prognostic signature

IntroductionComplex outcome of ovarian cancer (OC) stems from the tumor immune microenvironment (TIME) influenced by genetic and epigenetic factors. This study aimed to comprehensively explored the subclasses of OC through lncRNAs related to both N6-methyladenosine (m6A)/N1-methyladenosine (m1A)/N7-methylguanosine (m7G)/5-methylcytosine (m5C) in terms of epigenetic variability and immune molecules and develop a new set of risk predictive systems. Material and methodsThe lncRNA data of OC were collected from TCGA. Spearman correlation analysis on lncRNA data of OC with immune-related gene expression and with m6A/m5C/m1A/m7G were respectively conducted. The m6A/m5C/m1A/m7G-related m6A/m5C/m1A/m7G related immune lncRNA subtypes were identified on the basis of the prognostic lncRNAs. Heterogeneity among subtypes was evaluated by tumor mutation analysis, tumor microenvironment (TME) component analysis, response to immune checkpoint blocked (ICB) and chemotherapeutic drugs. A risk predictive system was developed based on the results of Cox regression analysis and random survival forest analysis of the differences between each specific cluster and other clusters. ResultsThree m6A/m5C/m1A/m7G-related immune lncRNA subtypes of OC showing distinct differences in prognosis, mutation pattern, TIME components, immunotherapy and chemotherapy response were identified. A set of risk predictive system consisting of 10 lncRNA for OC was developed, according to which the risk score of samples in each OC dataset was calculated and risk type was defined. ConclusionsThis study classified three m6A/m5C/m1A/m7G-related immune lncRNA subtypes with distinct heterogeneous mutation patterns, TME components, ICB therapy and immune response, and provided a set of risk predictive system consisted of 10 lncRNA for OC.

Calibrating T cell help by antigen cross-linking as a universal vaccine platform against rapidly evolving pathogenic viruses

Abstract The effectiveness of influenza vaccine is limited by the heterogeneous immune response it elicits. Factors such as age, sex, and pre-existing antibody titers only partially explain this heterogeneity. Using a novel deconvolution analysis we find subtype-specific bias as a major source of this inter-individual variation. Since the 1940’s it has been proposed that this phenomenon is due to prior strain exposure, referred to as “Original Antigenic Sin”. But our analysis of flu vaccine responses in a monozygotic twin cohort showed that antigenic imprinting from past exposures can only partially explain strain preference (r 2=0.25, p=4.7×10 −5). Thus, we hypothesized that host genetics may play a major role in subtype-bias. Consistent with this is our finding that strain-preferences are evident after vaccination in an influenza naïve infant cohort indicating that prior exposure is not essential. We determined the source of this genetic component to the wide variation in influenza hemagglutinin peptide presentation by different HLA class-II alleles resulting in an imbalanced, subtype-specific CD4 +T follicular help after vaccination. To address this, we developed a tunable, plug-and-play vaccine platform to better calibrate T cell help. In a human tonsil organoid system, we demonstrated that engineered, cross-linked HA induces a significantly higher response against multiple influenza subtypes in comparison to the inactivated influenza vaccine. In summary, we have developed an effective strategy to overcome response bias in a population with diverse genetic backgrounds and pre-existing immunity. Furthermore, we successfully adapted this platform to generate a pan-coronavirus vaccine. Supported by grants from NIH to MMD (5U19AI090019, 5U19AI057229). Additional support was provided by ITI-YIA to VM.

Abstract 6328: An off-the-shelf Twin BiTE combination therapy controls heterogenous glioblastoma and shapes immune response

Abstract Glioblastoma (GBM) is the most common primary brain tumor in adults, characterized by a median survival of 12-14 months with less than 10% of patients surviving at least 2 years from diagnosis. The discovery of tumor-associated antigens (TAAs) has permitted development of a new array of therapeutic strategies that selectively target GBM and spare normal cells of the CNS. In this study we used an alternative off-the-shelf approach to activate the immune system and direct it against the tumor, taking into account antigen heterogeneity and TME immune suppression without the need of engineering the patient’s immune cells. We generated TAA-targeting Bispecific T-cell Engagers (BiTEs) and engineered adult stem cells to secrete twin BiTEs (T-BiTE-SC). The approach was tested in combination with in naïve T cells on established and primary patient-derived cell lines expressing various levels of the target antigens. Moreover, to further support the therapeutic action of T cells, and combat immune-suppressive microenvironment and exhaustion, we combined our T-BiTE SC with an immune-stimulating cytokine. We show the efficacy of the individual BiTEs against different primary and established tumor cell lines. Moreover, the T-BiTE-SC, significantly controlled the growth of a tumor expressing heterogeneous levels of the targeted antigens. The immune stimulation reduced T cell exhaustion and consolidated a Th1 phenotype. Altogether our study demonstrated the feasibility and efficacy of an off-the-shelf immunotherapy, based on BiTEs simultaneously targeting tumor heterogeneity without the need for direct engineering of the immune cells. Citation Format: Filippo Rossignoli, Paulo Borges, Rebecca Lumia, Khalid Shah. An off-the-shelf Twin BiTE combination therapy controls heterogenous glioblastoma and shapes immune response [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6328.

Self-driven immune checkpoint blockade and spatiotemporal-sensitive immune response monitoring in acute myeloid leukemia using an all-in-one turn-on bionanoprobe.

Immune checkpoint (ICP) blockade (ICB) is one of the most promising immunotherapies for acute myeloid leukemia (AML). However, owing to their heterogeneity, AML cells may cause uncoordinated metabolic fluxes and heterogeneous immune responses, inducing the release of a spatiotemporally sensitive immune response marker. Timely and in situ detection of immune responses in ICB therapy is important for therapeutic strategy adjustment. Herein, we constructed an all-in-one nanoprobe for self-driving ICB and simultaneously detecting an immune response in the same AML cell in vivo, thus enabling accurate evaluation of heterogenetic immune responses in living AML mice without additional drug treatment or probe processes. The nature-inspire polydopamine (PDA) nanoparticles loaded with an ICP blocker were targeted to the leukocyte immunoglobulin like receptor B4 (a new ICP) of AML cells to induce the release of immune response marker granzyme B (GrB). The PDA nanoparticles were additionally paired with carbon-derived graphene quantum dots (GQDs) to construct a full-organic 'turn-on' bionanoprobe that can transfer fluorescence resonance energy for GrB detection. This multifunctional nanoprobe was validated for triggering ICB therapy and monitoring the changes of GrB levels in real-time both in vitro and in vivo. The organic nanoprobe showed excellent permeability and retention in tumor cells and high biocompatibility in vivo. This bionanoprobe orderly interacted with the upstream ICP molecules and downstream signal molecule GrB, thereby achieving in situ immune response signals within the therapeutic efficacy evaluation window.

Point‐of‐care multiplexed single‐cell protein secretion analysis based on tyramide signal amplification

AbstractSecreted proteins are critical mediators in various biological systems, including the immune system, nervous system, and tumor microenvironment. Understanding profound cellular functional heterogeneity in secretion requires multiplexed secreted protein analysis at the single‐cell level. However, most single‐cell protein secretion analysis technologies rely on bulky, expensive instruments, preventing widespread use. Herein, we proposed using a portable and low‐cost desktop scanner to detect multiplexed proteins secreted from single cells. Gold nanoparticle‐enhanced silver staining and tyramide signal amplification are combined to construct a two‐step amplification for single‐cell secretion assay detection. We used this approach to investigate the heterogeneous immune response of macrophages at the single‐cell level, which revealed that only a minority of cells could secrete 10‐fold more MCP‐1 and TNF‐α than the averaged secretion. The reported platform eliminates bulky equipment for single‐cell secretion analysis, making it affordable for basic and clinical research.

Machine-learning Modeling for Personalized Immunotherapy- An Evaluation Module.

Immune-cell therapy and targeting therapy are in rapid development to treat tumor diseases. However, current immune-cell therapy and targeting immunotherapy often face three challenges (three Ss): safety challenges such as cytokine releasing syndrome (C.R.S.); specificity targeting problems such as low efficacy caused by off-targeting tumor cells; unsatisfying payment are confounded to clinical patients and physicians. We have been studying immunotherapy for more than thirty years, and recently, personalized immunotherapy to treat tumor disease has been proposed. After we discovered quiescent genes from immune cells within the tumor microenvironment, we set up single-cell genomics analysis, studying heterogeneous immune responses from multiple tumor antigens (neo-antigen); here, we further introduce a new generation of immunotherapy module by using a machine-learning model to assess optimal immunotherapy. The machine-learning model combined with single-cell genomic analysis can predict optimal immune-cell (such as T-cells) and other optimal targeting drugs such as PD1 and CTLA4 inhibitors for the patient to use.

Spatial maps of Tcell receptors and transcriptomes reveal distinct immune niches and interactions in the adaptive immune response.

T cells mediate antigen-specific immune responses to disease through the specificity and diversity of their clonotypic Tcell receptors (TCRs). Determining the spatial distributions of Tcell clonotypes in tissues is essential to understanding Tcell behavior, but spatial sequencing methods remain unable to profile the TCR repertoire. Here, we developed Slide-TCR-seq, a 10-μm-resolution method, to sequence whole transcriptomes and TCRs within intact tissues. We confirmed the ability of Slide-TCR-seq to map the characteristic locations of Tcells and their receptors in mouse spleen. In human lymphoid germinal centers, we identified spatially distinct TCR repertoires. Profiling Tcells in renal cell carcinoma and melanoma specimens revealed heterogeneous immune responses: Tcell states and infiltration differed intra- and inter-clonally, and adjacent tumor and immune cells exhibited distinct gene expression. Altogether, our method yields insights into the spatial relationships between clonality, neighboring cell types, and gene expression that drive Tcell responses.

TOWARDS A NETWORK APPROACH IN THE CHARACTERIZATION OF THE IMMUNE RESPONSE IN COLORECTAL CANCER

Objectives: Colorectal cancer (CRC) is one of the tumors with a dominant inflammatory component. An impressive volume of research has focused on the potential diagnostic or therapeutic application of the molecules (cytokines, adhesion molecules, others) that alter their expression during inflammation in tumors. However, recently these molecules have been shown to establish complicated relations (cytokine networks) in tumor biology. The present study aims to characterize the cytokine network in colorectal cancer, to highlight the quantitative development of immune modules, the ways in which they are organized and to determine whether there is a superior level coordination in the immune response in colorectal cancer. Methods: The serum levels of nine interleukins (IL-1β, IL-6, IL-8, IL-33, IL-17A, IL-22, IFN (interferon)-γ, IL-4 and IL-10) two cell adhesion molecules-ICAM-1 and P-sel (P-selectin)- and a matrix-metalloproteinase (MMP-7) were measured by ELISA (Enzyme-linked immunosorbent assay) in thirty-three CRC patients and thirty-five healthy controls. Cytokines were selected to represent the main immune networks in CRC. Data were processed in order to find molecules with correlated or group behavior. Results: Three groups or ensembles and a number of independent modules were determined by the present study. Conclusions: The study highlights a heterogenous immune response, with an overall reduced level, with both pro-and antitumoral elements, which tend to be organized into functional groups. This may serve as starting point for strategic approaches in therapy. Keywords: Colorectal, cancer, cytokine, adhesion, network

The Frequency and Patterns of Post-COVID-19 Vaccination Syndrome Reveal Initially Mild and Potentially Immunocytopenic Signs in Primarily Young Saudi Women.

Vaccination is the most promising approach for ending or containing the SARS-CoV-2 pandemic. However, serious post-COVID-19 vaccine reactions, including immunocytopenia (ITP) syndrome, have been increasingly reported. Several factors cause increased risks including multiple doses, age-dependent heterogeneity in immune-responses, platelet cross-reactions with microbial components, and Long-COVID syndrome. Thus, in the absence of widely available specific therapeutics, vigilance is important while more studies are needed. Using a structured questionnaire sent to different regions in Saudi Arabia, we conducted a comprehensive investigation on the frequency, rates, disease patterns, and patient demographics of post-COVID-19 vaccine side effects on febrile patients after administration three major vaccines. Results indicated that the majority of respondents administered Pfizer BioNtech vaccine (81%, n = 809); followed by AstraZeneca (16%, n = 155); and Moderna (3%, n = 34). Overall 998 participants, 74% (n = 737) showed no serious symptoms; however, 26.2% (n = 261) revealed typical syndromes. In a focused group of 722 participants, the following rates were identified: shortness of breath (20%), bruises or bleeding (18%), inattention (18%), GIT symptoms (17.6%), skin irritation (8.6%), and anosmia and ageusia (8%) were the most prominent among those who showed typical symptoms. The onset time was mostly between 1–3 days in 49% (n = 128), followed by 4–7 days in 21.8% (n = 57), 8–14 days in 16.5% (n = 43), and more than a month in 12.6% (n = 33). The onsets occurred mostly after the first, second, or both doses, 9%, 10%, and 7% of participants, respectively. The frequency of symptoms was significantly higher after Moderna® vaccine (p-value = 0.00006) and it was significantly lower in participants who received Pfizer (p-value = 0.00231). We did not find significant difference in symptoms related to differences in regions. Similarly, the region, age, sex, education, and nationality had no influence on the dose and onset timings. The findings of this study have significant clinical implications in disease management strategies, preventive measures, and vaccine development. Future vertical studies would reveal more insights into the mechanisms of post-COVID-19 vaccine syndrome.