Immune Biomarkers Research Articles

Inhibition of TOX exerts anti-tumor effects in acute myeloid leukemia by upregulating IRF7 expression

Thymocyte selection-associated high mobility group box protein (TOX) is regarded as a crucial transcription factor involved in T cell exhaustion in acute myeloid leukemia (AML). Previous studies have identified aberrant TOX expression as a major oncogenic driver in hematologic malignancies, indicating that TOX may potentially be both an immune biomarker and an immunotherapy target. However, due to heterogeneity in the distribution patterns of TOX and its correlation with clinical prognosis, the mechanism underlying TOX-mediated tumor immune responses remains unclear. In this study, we demonstrate that high TOX expression in AML patients is associated with poor prognosis, and TOX overexpression promotes AML cell proliferation and restricts apoptosis. In vitro TOX inhibition promoted the apoptosis of AML cells, suppressed cell viability, and induced cell cycle arrest in the G0/G1 phase. Moreover, TOX knockdown could reduce tumor burden in vivo in immunodeficient mice and prolong their survival. Furthermore, the anti-AML effects of inhibiting TOX may act through activation of the IFN-α signal pathway and upregulating IRF7 expression. In summary, we report for the first time that TOX knockdown exerts powerful anti-tumor effects in AML. These findings will provide a theoretical basis for targeted therapy in AML patients.

Development and validation of biomarkers related to anoikis in liver cirrhosis based on bioinformatics analysis

BACKGROUND According to study, anoikis-related genes (ARGs) have been demonstrated to play a significant impact in cirrhosis, a major disease threatening human health worldwide. AIM To investigate the relationship between ARGs and cirrhosis development to provide insights into the clinical treatment of cirrhosis. METHODS RNA-sequencing data related to cirrhosis were obtained from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) between cirrhotic and normal tissues were intersected with ARGs to derive differentially expressed ARGs (DEARGs). The DEARGs were filtered using the least absolute shrinkage and selection operator, support vector machine recursive feature elimination, and random forest algorithms to identify biomarkers for cirrhosis. These biomarkers were used to create a nomogram for predicting the prognosis of cirrhosis. The proportions of diverse immune cell subsets in cirrhotic vs normal tissues were compared using the CIBERSORT computational method. In addition, the linkage between immune cells and biomarkers was assessed, and a regulatory network of mRNA, miRNA, and transcription factors was constructed relying on the biomarkers. RESULTS The comparison of cirrhotic and normal tissue samples led to the identification of 635 DEGs. Subsequent intersection of the DEGs with ARGs produced a set of 26 DEARGs. Subsequently, three DEARGs, namely, ACTG1 , STAT1 , and CCR7 , were identified as biomarkers using three machine-learning algorithms. The proportions of M1 and M2 macrophages, resting CD4 memory T cells, resting mast cells, and plasma cells significantly differed between cirrhotic and normal tissue samples. The proportions of M1 and M2 macrophages, resting CD4 memory T cells, and resting mast cells were significantly correlated with the expression of the three biomarkers. The mRNA–miRNA–TF network showed that ACTG1 , CCR7 , and STAT1 were regulated by 28, 42, and 35 miRNAs, respectively. Moreover, AR, MAX, EP300, and FOXA1 were found to regulate four miRNAs related to the biomarkers. CONCLUSION This study revealed ACTG1 , STAT1 , and CCR7 as biomarkers of cirrhosis, providing a reference for developing novel diagnostic and therapeutic strategies for cirrhosis.

Blood based immune biomarkers associated with clinical frailty scale in older patients with melanoma receiving checkpoint inhibitor immunotherapy

IntroductionImmunotherapy with checkpoint inhibition (ICI) is increasingly prescribed to older patients with cancer. High age, especially in combination with frailty, has been associated to immune senescence, which is the age-related decline in immune function, thereby possibly hindering ICI effectiveness. This cross-sectional study aimed to assess whether blood cell immune senescence markers are associated with age, frailty and response to anti-PD-1 treatment in older patients with metastatic melanoma.MethodsIn a prospective observational study, sixty patients with stage IIIC or IV melanoma undergoing anti-PD1 treatment were categorized into young (< 65 years; n = 22), old (> 65 years) without frailty (n = 19), and old with frailty (n = 19). In-depth immune cell phenotyping was performed in baseline blood samples (prior to treatment) using multispectral flow cytometry and compared between groups and with immunotherapy treatment response. Antigen-presenting cell capacity was evaluated using mixed lymphocyte reaction and T cell proliferative potential was assessed using PHA proliferation assay.ResultsNo significant differences in treatment response rates were observed across age groups. Older patients, irrespective of frailty, showed lower levels of naïve CD8 + T cells, with the old and frail group also exhibiting reduced tissue-resident effector memory CD8 + T cells and CD8 + mucosal associated invariant T (MAIT) cells. These differences were not associated with treatment outcomes. T cell proliferation and antigen-presenting cell capacities did not differ across groups.ConclusionSeveral ageing and frailty associated changes were detected among circulating immune cells in blood but were not associated with response to immunotherapy in our study. While these findings suggest that the level of frailty and ageing may not necessarily preclude the efficacy of ICI therapy, further investigation is needed to fully understand the impact of frailty and ageing on immunotherapy.

Multi-modal transcriptomics: integrating machine learning and convolutional neural networks to identify immune biomarkers in atherosclerosis

BackgroundAtherosclerosis, a complex chronic vascular disorder with multifactorial etiology, stands as the primary culprit behind consequential cardiovascular events, imposing a substantial societal and economic burden. Nevertheless, our current understanding of its pathogenesis remains imprecise. In this investigation, our objective is to establish computational models elucidating molecular-level markers associated with atherosclerosis. This endeavor involves the integration of advanced machine learning techniques and comprehensive bioinformatics analyses.Materials and methodsOur analysis incorporated data from three publicly available the Gene Expression Omnibus (GEO) datasets: GSE100927 (104 samples, 30,558 genes), which includes atherosclerotic lesions and control arteries from carotid, femoral, and infra-popliteal arteries of deceased organ donors; GSE43292 (64 samples, 23,307 genes), consisting of paired carotid endarterectomy samples from 32 hypertensive patients, comparing atheroma plaques and intact tissues; and GSE159677 (30,498 single cells, 33,538 genes), examining single-cell transcriptomes of calcified atherosclerotic core plaques and adjacent carotid artery tissues from patients undergoing carotid endarterectomy. Utilizing single-cell sequencing, highly variable atherosclerotic monocyte subpopulations were systematically identified. We analyzed cellular communication patterns with temporal dynamics. The bioinformatics approach Weighted Gene Co—expression Network Analysis (WGCNA) identified key modules, constructing a Protein-Protein Interaction (PPI) network from module-associated genes. Three machine-learning models derived marker genes, formulated through logistic regression and validated via convolutional neural network(CNN) modeling. Subtypes were clustered based on Gene Set Variation Analysis (GSVA) scores, validated through immunoassays.ResultsThree pivotal atherosclerosis-associated genes—CD36, S100A10, CSNK1A1—were unveiled, offering valuable clinical insights. Profiling based on these genes delineated two distinct isoforms: C2 demonstrated potent microbicidal activity, while C1 engaged in inflammation regulation, tissue repair, and immune homeostasis. Molecular docking analyses explored therapeutic potential for Estradiol, Zidovudine, Indinavir, and Dronabinol for clinical applications.ConclusionThis study introduces three signature genes for atherosclerosis, shaping a novel paradigm for investigating clinical immunological medications. It distinguishes the high biocidal C2 subtype from the inflammation-modulating C1 subtype, utilizing identified signature gene as crucial targets.

Advances in Immune Biomarkers for Predicting Disease Outcomes and Therapeutic Responses

Advances in Immune Biomarkers for Predicting Disease Outcomes and Therapeutic Responses

Ovarian Stimulation Effects on Ghrelin Secretion and Reproductive Potential

ABSTRACTObjectiveFinely regulated Ghrelin (Ghrl) secretion is essential during early pregnancy, as infra or supraphysiologic levels can be detrimental. Since oestrogens stimulate Ghrl synthesis, ovarian stimulation (OS) might increase ghrelinemia, thus being detrimental for fertility. The aim of this work was to evaluate whether OS increases ghrelinemia and associates with maternal endocrine and immune biomarkers and reproductive success.DesignThe 97 women undergoing assisted reproduction were grouped as follows: OS: undergoing OS and fresh embryo transfer (n = 35); FET: undergoing frozen embryo transfer in a cycle different from that of OS (n = 25) and, OD: undergoing embryo transfer in oocyte donation cycles (n = 37). At embryo transfer day, several endocrine and immune biomarkers were assessed.ResultsOS patients showed significantly higher serum estradiol, progesterone and Ghrl, than those not stimulated. Patients that suffered miscarriage showed significantly lower concentrations of sex‐hormones, with a similar trend for Ghrl, that deserves further investigation. Moreover, OS patients showed decreased frequencies of circulating T cells and reduced ratios of uNK/NK cells, which significantly associated with serum levels of sex‐hormones. Besides, ROC curves identified cut‐off values predictive of clinical pregnancy and/or miscarriage for peripheral counts of uNK cells, T cells, and uNK/NK cells ratio.ConclusionsAs hypothesised, OS significantly increased serum Ghrl in correlation with sex‐hormone levels. These last, significantly associated with maternal immune response and reproductive outcome. Although Ghrl exhibited a similar profile, it did not reach statistical significance, indicating the need for further investigation. Additionally, the identification of maternal immunological cut‐off values holds significant clinical relevance.

Methylation cytometric pretreatment blood immune profiles with tumor mutation burden as prognostic indicators for survival outcomes in head and neck cancer patients on anti-PD-1 therapy

Tissue biomarkers for immune checkpoint inhibitor (ICI) response are limited by tumor sample heterogeneity and availability. This study identifies clinically actionable pretreatment blood biomarkers that are associated with ICI treatment response and survival in recurrent/metastatic head and neck squamous cell carcinoma. A prospective multi-center study enrolled 100 patients before standard-of-care immunotherapy. Blood immune profiles, measured by methylation cytometry, were assessed alongside tumor mutational burden (TMB) and PD-L1 combined proportion score (CPS). TMB and PD-L1 CPS were available for 56 and 91 patients, respectively. High neutrophils, monocytes, and neutrophil-to-lymphocyte ratio were associated with worse survival, while high CD4T cells, especially naïve CD4T cells, and lymphocyte-to-monocyte ratio were associated with better survival. Significant interactions between TMB and peripheral immune profiles for both progression-free and overall survival were found. Clinically relevant pretreatment peripheral immune biomarkers were identified, demonstrating the potential of DNA-based immune profiling to predict ICI response before treatment.

Identification of Functional Immune Biomarkers in Breast Cancer Patients.

Cancer immunotherapy has emerged as an effective, personalized treatment for certain patients, particularly for those with hematological malignancies. However, its efficacy in breast cancer has been marginal-perhaps due to cold, immune-excluded, or immune-desert tumors. Natural killer T (NKT) cells play a critical role in cancer immune surveillance and are reduced in cancer patients. Thus, we hypothesized that NKT cells could serve as a surrogate marker for immune function. In order to assess which breast cancer patients would likely benefit from immune cell-based therapies, we have developed a quantitative method to rapidly assess NKT function using stimulation with artificial antigen presenting cells followed by quantitative real-time PCR for IFN-γ. We observed a significant reduction in the percentage of circulating NKT cells in breast cancer patients, compared to healthy donors; however, the majority of patients had functional NKT cells. When we compared BC patients with highly functional NKT cells, as indicated by high IFN-γ induction, to those with little to no induction, following stimulation of NKT cells, there was no significant difference in NKT cell number between the groups, suggesting functional loss has more impact than physical loss of this subpopulation of T cells. In addition, we assessed the percentage of tumor-infiltrating lymphocytes and PD-L1 expression within the tumor microenvironment in the low and high responders. Further characterization of immune gene signatures in these groups identified a concomitant decrease in the induction of TNFα, LAG3, and LIGHT in the low responders. We next investigated the mechanisms by which breast cancers suppress NKT-mediated anti-tumor immune responses. We found that breast cancers secrete immunosuppressive lipids, and treatment with commonly prescribed medications that modulate lipid metabolism, can reduce tumor growth and restore NKT cell responses.

Immune checkpoint inhibitor therapy as a neoadjuvant treatment for muscle-invasive bladder carcinoma

Abstract Background and objectives Immunotherapy has become a standard treatment for patients with advanced urothelial carcinoma, and neoadjuvant immunotherapy is being extensively explored. This review highlights the initial findings and key clinical therapeutic insights on immune checkpoint inhibitors in the early treatment of muscle-invasive bladder cancer across diverse patient populations. Materials and methods Relevant trials were retrieved from PubMed/MEDLINE and clinical trials databases. In addition, abstracts of major international oncology meetings (American Society of Clinical Oncology, American Association for Cancer Research, European Society of Medical Oncology, and European Council of Clinical Oncology) were reviewed until the European Society of Medical Oncology 2023 congress. The review also incorporated results from several exploratory investigations disclosed in recent years. Results This review focused on neoadjuvant immune checkpoint inhibitor monotherapy, combination therapy, and clinical biomarkers in relation to cisplatin-based chemotherapy tolerance. Most available literature consists of clinical investigations involving small sample, single-arm Phase II trials, with the primary endpoint being the pathologic complete response rate. The preliminary results from these studies are promising, demonstrating stage reduction rates comparable to or even exceeding those of standard chemotherapy, without compromising subsequent radical cystectomy. Conclusions Early results of immune checkpoint inhibitors in the neoadjuvant treatment of bladder cancer have demonstrated promising efficacy. However, these findings require confirmation in large Phase III clinical trials, with particular emphasis on long-term survival benefits and identifying patients who respond to treatment.

Abstract PR013: Highly accurate detection of early-stage colorectal cancer using tumor and immune extracellular vesicles biomarkers

Abstract Introduction: Colorectal cancer (CRC) is one of the most common cancers worldwide, and early detection is critical for successful treatment and improved survival rates. However, precancerous and early-stage CRC present significant diagnostic challenges due to the small size of lesions and the very low expression of tumor-specific biomarkers in the bloodstream. Current genomics-based diagnostic methods struggle to detect these lesions, making it imperative to develop more sensitive and specific approaches. Circulating extracellular vesicles (EVs) are emerging as a promising solution for early-stage CRC detection, since EVs are produced by tumor cells as well as the tumor microenviroment and host immune cells. Thus, EVs may offer the means to detect and monitor small early-stage tumors through both direct detection of tumor- associated biomarkers as well through tumor specific host response and tumor microenvironment biomarkers. Methods: To identify novel early-stage CRC specific biomarkers, we performed proteomics analysis on EVs purified from patient plasma using size exclusion chromatography and a proprietary buffer system that enhances EV and corona protein recovery. TrueDiscovery™ Data-independent acquisition (DIA) mass spectrometry (MS) analysis was conducted on 24 pre- cancer/stage 0 and 25 stage 1 CRC patients and 75 normal patient plasma samples. An in-house developed machine learning pipeline was used to identify differentially expressed proteins and model candidate multiplexes to identify those with extremely high diagnostic accuracy (&amp;gt; 0.99). Results: An average of ∼2,500 proteins were identified per sample and included in bioinformatics analysis. Comparative analysis between control patient EVs and either pre- cancerous/Stage 0, or Stage 1 colon cancer EVs using an in-house Machine Learning pipeline identified 336 and 493 differentially expressed proteins for each group (FDR adjusted p-value &amp;lt; 0.001). Of these, the best 17 pre/stage 0 proteins and 53 stage 1 proteins were trained and tested using Support Vector Machine to assess all potential 3-plexes in order to identify those with mean diagnostic accuracy &amp;gt; 99%. This yielded 5 3-plexes in precancer/stage 0 and 34 3-plexes in stage 1 with near perfect diagnostic accuracy. These plexes are currently being assessed in single analyte and multiplex immunoassays with the goal of translating candidate 3-plexes to the clinical. Conclusions: Key biomarkers from CRC patient EVs indicate the potential to detect and diagnose early-stage and low tumor burden cancers using our methods. Interestingly, the most accurate 3-plexes consist of proteins from immune, inflammatory and metabolic processes, suggesting that for the detection of early stage cancer it may be critical to include both tumor and host specific biomarkers. Citation Format: Poorva Mudgal, Cheryl Bandoski, Zachary Opheim, Martin Mehnert, Valesca Anschau, Issa Isaac, Alan Ezrin, Todd Hembrough. Highly accurate detection of early-stage colorectal cancer using tumor and immune extracellular vesicles biomarkers [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr PR013.

Abstract A063: Highly accurate detection of early-stage colorectal cancer using tumor and immune extracellular vesicles biomarkers

Abstract This abstract is being presented as a short talk in the scientific program. A full abstract is printed in the Proffered Abstracts section (PR013) of the Conference Program/Proceedings. Citation Format: Poorva Mudgal, Cheryl Bandoski, Zachary Opheim, Martin Mehnert, Valesca Anschau, Issa Isaac, Alan Ezrin, Todd Hembrough. Highly accurate detection of early-stage colorectal cancer using tumor and immune extracellular vesicles biomarkers [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr A063.

Abstract 4136930: Plasminogen Activator Urokinase Receptor (PLAUR) Levels are a Predictor of Adverse Cardiovascular Outcomes in the General Population, Independent of High-Sensitive CRP (hs-CRP)

Background: The gene Plasminogen Activator Urokinase Receptor (PLAUR) encodes the urokinase plasminogen activator surface receptor (uPAR), which upon cleavage releases Soluble Urokinase Plasminogen Activator Receptor (suPAR). SuPAR has emerged as a novel biomarker of inflammation and immunity and is associated with adverse cardiovascular events, particularly coronary artery disease (CAD), regardless of hs-CRP levels, a well-established inflammatory biomarker. However, whether the PLAUR gene predicts adverse cardiovascular events remains uncertain. Methods: We investigated the relationship between PLAUR levels, measured via Olink Immunoassay, in 40,790 individuals from the UK Biobank, and the occurrence of adverse cardiovascular events such as myocardial infarction (MI), as well as all-cause and cardiovascular mortality. Our analysis involved the use of Cox and Fine and Gray proportional hazards models, adjusting for age, sex, race, HDL, LDL, triglyceride levels, BMI, prevalence of hypertension (HTN), prevalence of type 2 diabetes (T2D), smoking history, and use of blood pressure and cholesterol medications. Main Outcomes: The primary outcome was a composite outcome of cardiovascular mortality and MI and the secondary outcome was all-cause mortality. Results: The mean (SD) age was 58 (8) years, 45% men and 94% white. During a median follow-up of 14 (interquartile range 12.3 – 15) years, 7.9% of the population had an MI, 2.7% suffered cardiovascular death, 9.5% all-cause mortality. After adjusting for aforementioned demographic and clinical factors, as well as medication usage, each standard deviation increase in PLAUR levels was associated with a heightened risk of incident non-fatal MI and cardiovascular (CV) death, with a hazard ratio (HR) of 2.31 (95% CI 2.00-2.45), and all-cause mortality, with an HR of 3.81 (95% CI 3.48-4.18). Even after further adjustment for hs-CRP levels, PLAUR levels remained predictive of non-fatal MI and CV death (HR 2.03, 95% CI 1.83-2.26) and all-cause mortality (HR 3.43, 95% CI 3.12-3.77). Furthermore, in a fully adjusted Cox regression model, a significant interaction between PLAUR levels and sex (p = 0.0003) was observed in predicting the primary outcome. The interaction was found to have a stronger predictive value in females compared to males. Conclusion: PLAUR levels are a strong predictor of adverse cardiovascular outcomes in the general population, independent of traditional risk factors and inflammation.

Koala ocular disease grades are defined by chlamydial load changes and increases in Th2 immune responses.

This study employs bulk RNA sequencing, PCR, and ELISA assays to analyze the pathological factors affecting the outcomes of C. pecorum ocular infections in koalas. It investigates the immune responses and gene expression profiles associated with various stages of koala ocular chlamydiosis. A cohort of 114 koalas from Queensland, Australia were assessed, with 47% displaying clinical signs of ocular disease. Animals were classified into three cohorts: acute active disease (G1), chronic active disease (G2), and chronic inactive disease (G3), along with subclinical Chlamydia pecorum positive (H2) and healthy (H1) cohorts. Analysis of clinical, microbiological, humoral immune and cellular immune biomarkers revealed varying chlamydial loads and anti-chlamydial IgG levels across disease grades, with a negative correlation observed between ocular chlamydial load and anti-chlamydial IgG. Koala ocular mucosa gene expression analysis from 27 koalas identified shared expression pathways across disease cohorts, with a significant upregulation of IFNγ expression and tryptophan metabolism in all disease stages. These findings help elucidate immune response dynamics and molecular pathways underlying koala ocular chlamydiosis, providing insights crucial for disease management strategies.

Alcohol and cannabis use associated with cardiometabolic biomarkers among "All of Us" cancer survivors.

Cancer survivors are at increased risk for cardiometabolic comorbidities following cancer treatment which may be further exacerbated by cannabis and alcohol use. We aimed to examine the direct relationships of cannabis, alcohol, and the co-use of both substances with cardiometabolic risk factors and to explore disparities by race/ethnicity and sex. Cross-sectional data were extracted from adult cancer survivors in the "All of Us" from 2018-2022. Cannabis use was defined as occasional or frequent/regular cannabis use (vs never) in the past three months and hazardous alcohol intake (AUDIT-C >3 for females, AUDIT-C >4 for males) vs non-hazardous in the past year, respectively. Co-use was defined as participants who engaged in regular cannabis and hazardous alcohol intake. We identified binary cardiovascular, immune, and metabolic systems biomarkers, with high values defined by clinically established cutoffs or >75th percentile. We used multivariable logistic regression adjusting for socio-demographic and clinical factors. In our sample (N=7,054), 7.6% were Hispanic, 6.2% were Black, and 86.2% were White cancer survivors. Less than 5% of Hispanic and White survivors reported substance co-use compared to 7% of Black survivors. Compared to never users, co-users were 1.58(95% CI=1.14-2.19) more likely to have high blood pressure. No significant associations were found between co-use and immune biomarkers or sex differences. Co-use of cannabis and hazardous alcohol may worsen high blood pressure in survivors, who are at higher risk for cardiometabolic comorbidities. The study investigates substance use and cardiometabolic biomarkers, urging more research on their effects on cancer survivors.

CTIM-14. EARLY SAFETY DATA FROM A RANDOMIZED, MULTICENTER, DOUBLE-BLIND, PHASE 2B STUDY OF IGV-001, AN AUTOLOGOUS CELL IMMUNOTHERAPY, VERSUS PLACEBO, IN NEWLY DIAGNOSED GLIOBLASTOMA (NDGBM)

Abstract Standard of care (SOC) for ndGBM begins with maximal safe resection followed by adjuvant radiotherapy and temozolomide, and maintenance temozolomide. IGV-001 is an autologous biologic-device combination immunotherapy for the treatment of ndGBM that consists of autologous GBM tumor cells and an antisense oligonucleotide against IGF-1R mRNA, irradiated and administered via biodiffusion chambers implanted in the abdomen. In a phase 1b study, IGV-001 was well tolerated without unexpected adverse events in subjects with ndGBM. Multiple efficacy signals were observed, including significant improvements in progression-free survival (PFS), overall survival (OS), radiographic evidence of tumor response, and changes in immune response biomarkers. Here, we present early safety data from the phase 2b randomized, multicenter, double-blind, placebo-controlled study (NCT04485949) designed to assess efficacy and safety of IGV-001 in subjects with ndGBM across 20 sites in the United States. After surgical resection, subjects were randomized 2:1 and treated with IGV-001 or placebo followed by SOC. The primary outcome is PFS, defined as the time from randomization to first progression, as determined by blinded central radiology review, or death. Secondary outcomes include OS, defined as the time from randomization to death due to any cause, and safety. As of May 22, 2024, 99 subjects were randomized and 95 implanted with IGV-001 or placebo plus SOC. A total of 39/45 (86.7%) subjects had sufficient follow-up time after initiated treatment with concurrent radiation and temozolomide. Nine of 72 randomized (12.5%) discontinued treatment, including 7 who stopped during the SOC treatment period. None ceased treatment for adverse events, protocol deviations, or death. A total of 11/72 (15.3%) randomized subjects discontinued the study after randomization. A review of blinded safety data did not show any emerging risk and supports no change to the benefit-risk profile of IGV-001 versus placebo. Updated data will be presented.

CTIM-11. LONG-TERM SURVIVORS FROM A PHASE 1B STUDY OF IGV-001 IN PATIENTS WITH NEWLY DIAGNOSED GLIOBLASTOMA

Abstract Imvax has developed the Goldspire™ platform to create IGV-001, an autologous biologic-device combination product for the treatment of newly diagnosed glioblastoma (ndGBM). IGV-001 consists of autologous GBM tumor cells and an antisense oligonucleotide against IGF-1R mRNA (IMV-001), irradiated and administered via biodiffusion chambers (BDCs) implanted in the abdomen. Together, these components stimulate immunogenic cell death and antigen release. IGV-001 was well tolerated and multiple efficacy signals were observed in a Phase 1b study in patients with ndGBM (Andrews et al., 2021), including significant improvements in progression-free survival (PFS), radiographic evidence of tumor response, and changes in immune response biomarkers. The Phase 1b study enrolled 33 patients in four different cohorts implanted with 10 or 20 BDCs for 24 or 48 hours. Here we report on 6 subjects with survival beyond 4 years, including 5 subjects who survived 5 years or more (15.2%). There were 4 male and 2 female subjects, with a median age of 52 years (range 32-75). At diagnosis the MGMT promoter was methylated in 4 of 5 subjects that survived 5 years or more. We also report on T cell receptor Vβ CDR3 region sequencing of peripheral blood mononuclear cells and tissue infiltrated lymphocytes that was performed in a subset of 9 patients, including 3 subjects who survived beyond 4 years. Immune correlates of IGV-001 suggest an association between peripheral T cell clonal expansion and PFS/OS outcomes. A Phase 2b randomized, multicenter, double-blind, placebo-controlled study to assess the safety and efficacy of IGV-001 in patients with ndGBM (NCT04485949) has completed enrollment and results are expected to be available in 2025.

CTIM-33. IMMUNE BIOMARKERS OF TREATMENT RELATED IMAGING CHANGES IN GLIOBLASTOMA PATIENTS TREATED WITH STANDARD OF CARE PLUS PEMBROLIZUMAB

Abstract Pseudoprogression is a post-treatment imaging phenomenon in glioblastoma (GBM) that mimics true progression. Immune checkpoint inhibition with pembrolizumab has shown clinical benefits in multiple cancers and is a burgeoning treatment in GBM. Discerning pseudoprogression, or treatment-related imaging changes, from true progression is essential for appropriate treatment recommendations. However, there are no reliable biomarkers that can differentiate between pseudoprogression and true progression. Our prospective single-arm study (NCT 03347617) evaluated immune cell sub-populations (B-cells, T-cells, NK cells, monocytes, and myeloid cells) in newly diagnosed GBM patients who received standard-of-care chemoradiation plus concurrent pembrolizumab after maximal safe resection. Flow cytometry was performed on blood collected at predetermined timepoints (pre-treatment, post-radiation, suspected progression, and confirmed progression) and immune cell sub-populations were evaluated as covariates in univariable and multivariable logistic regression analysis. Of the 56 patients enrolled in this trial, 51 completed blood collection. Median survival was 13.84 months. Fifteen (29%) patients had pseudoprogression by modified RANO criteria and 36 (70.5%) had suspected or confirmed progression. Univariable analysis identified the following serum derived immune populations as being significantly associated with pseudoprogression: cytotoxic T-cell percentage (CD3+CD8+; HR: 1.10; p=0.045); total NK Cells percentage (CD3+CD56+; HR:0.912; p=0.0.053); IGD+CD27-naïve B-cells of B-cell percentage (HR: 0.976; p=0.014); IGD+CD27+non-switched B of B-cell percentage (HR:1.07; p=0.036). Backward selection multivariable logistic regression analysis confirmed the significant association of cytotoxic T-cell percentage (CD3+CD8+; HR:1.02; p=0.049) with pseudoprogression while controlling for IGD+CD27+non-switched B of B-cell percentage (HR:1.01, p=0.116). Increasing levels of serum cytotoxic T-cells in GBM patients treated with standard-of-care plus pembrolizumab is associated with pseudoprogression and may be used to differentiate between true progression. Validation of results is needed in a control population treated with standard-of-care prior to clinical implementation. Future studies will utilize serum immune biomarkers coupled with radiomic features to better characterize the pseudoprogression signature in GBM.

Targeting LLT1 as a potential immunotherapy option for cancer patients non-responsive to existing checkpoint therapies in multiple solid tumors

BackgroundHigh levels of LLT1 expression have been found in several cancers, where it interacts with CD161 on NK cells to facilitate tumor immune escape. Targeting LLT1 could potentially relieve this inhibitory signal and enhance anti-tumor responses mediated through NK cells. Using the ‘The Cancer Genome Atlas’ (TCGA) database, we investigated the role of LLT1 in the tumor microenvironment (TME) across various cancers. Identifying such biomarkers could create new therapeutic options for patients in addition to complementing existing immunotherapies.MethodsLLT1 expression was evaluated in 33 cancers using TCGA transcriptome data. Univariate Cox regression analysis was employed to assess the correlation of LLT1 expression with patient survival. The relationship between LLT1 expression with immune infiltrates, immune gene signatures, and cancer genomic biomarkers (TMB, MSI, and MMR) was also investigated. Immunofluorescence studies were conducted to validate LLT1 expression in tumors. Furthermore, using the CRI iAtlas data, we evaluated LLT1 distribution and its correlation with other immune checkpoint genes in patients non-responsive to existing immune checkpoint therapies across multiple solid cancers.ResultsHigh expression of LLT1 was observed in 12 cancers, including BRCA, CHOL, ESCA, GBM, HNSC, KIRC, KIRP, LIHC, LUAD, STAD, SARC, and PCPG. In certain cancers like COAD, KICH, and KIRC, high LLT1 expression was associated with poor prognosis. Further analysis revealed that upregulated LLT1 was associated with an abundance of NK and T cell infiltrates in the TME, as well as exhaustive immune biomarkers, and inversely associated with pro-inflammatory and tumor suppressor signatures. High LLT1 expression is also positively correlated with genomic biomarkers in certain cancers. Immunofluorescence studies confirmed moderate to high LLT1 expression in immune-resistant prostate cancer, glioma, ovarian cancer, and immune-sensitive liver cancer cell lines. An independent assessment of clinical cohorts from CRI iAtlas showed a correlation of upregulated LLT1 with multiple immunosuppressive genes in patients non-responsive to current ICIs.ConclusionsThe biomarker analysis revealed a clear association between elevated LLT1 expression and an immunosuppressive TME in patient cohorts from TCGA and clinical databases. Therefore, this study provides a foundation for utilizing LLT1 as a potential target to improve clinical responses in ICI non-responsive patients with upregulated LLT1.

Assessing sepsis-induced immunosuppression to predict positive blood cultures.

Bacteremia is a life-threatening condition that can progress to sepsis and septic shock, leading to significant mortality in the emergency department (ED). The standard diagnostic method, blood culture, is time-consuming and prone to false positives and false negatives. Although not widely accepted, several clinical and artificial intelligence-based algorithms have been recently developed to predict bacteremia. However, these strategies require further identification of new variables to improve their diagnostic accuracy. This study proposes a novel strategy to predict positive blood cultures by assessing sepsis-induced immunosuppression status through endotoxin tolerance assessment. Optimal assay conditions have been explored and tested in sepsis-suspected patients meeting the Sepsis-3 criteria. Blood samples were collected at ED admission, and endotoxin (lipopolysaccharide, LPS) challenge was performed to evaluate the innate immune response through cytokine profiling. Clinical variables, immune cell population biomarkers, and cytokine levels (tumor necrosis factor [TNFα], IL-1β, IL-6, IL-8, and IL-10) were measured. Patients with positive blood cultures exhibited significantly lower TNFα production after LPS challenge than did those with negative blood cultures. The study also included a validation cohort to confirm that the response was consistent. The results of this study highlight the innate immune system immunosuppression state as a critical parameter for sepsis diagnosis. Notably, the present study identified a reduction in monocyte populations and specific cytokine profiles as potential predictive markers. This study showed that the LPS challenge can be used to effectively distinguish between patients with bloodstream infection leading to sepsis and those whose blood cultures are negative, providinga rapid and reliable diagnostic tool to predict positive blood cultures. The potential applicability of these findings could enhance clinical practice in terms of the accuracy and promptness of sepsis diagnosis in the ED, improving patient outcomes through timely and appropriate treatment.

A Prospective Cohort Study on the Effects of Repeated Acute Stress on Cortisol Awakening Response and Immune Function in Military Medical Students.

Background: The cortisol awakening response (CAR) is a pivotal component of the body's stress response, yet its dynamics under repeated acute stress and its interplay with immune biomarkers remain inadequately understood. Methods: This study examined 80 second-year military medical students undergoing a 5-day intensive surgical simulation designed to elicit stress responses. Salivary samples were collected daily upon waking and 30 min thereafter to measure cortisol and a panel of cytokines using bead-based multiplex ELISA. Results: Analysis revealed a significant blunting of the CAR on the third day of training (p = 0.00006), followed by a recovery on the fourth day (p = 0.0005). Concurrently, specific cytokines such as CXCL1 (r = 0.2, p = 0.0005), IL-6 (r = 0.13, p = 0.02), IL-10 (r = 0.14, p = 0.02), and VEGF-A (r = 0.17, p = 0.003) displayed patterns correlating with the CAR, with increased strength of associations observed when assessing cytokine levels against the CAR of the preceding day (CXCL1 r = 0.41, p = 0.0002. IL-6 r = 0.38, p = 0.0006. IL-10 r = 0.3, p = 0.008. VEGF-A r = 0.41, p = 0.0002). Conclusions: These results suggest a temporal relationship between stress-induced cortisol dynamics and immune regulation. The CAR pattern demonstrated in this study may represent induction of and recovery from psychological burnout. Moreover, the observed cytokine associations provide insight into the mechanisms by which stress can influence immune function. The results may have broader implications for managing stress in high-performance environments, such as military and medical professions, and for identifying individuals at risk of stress-related immune suppression.