Immunotherapeutic Interventions Research Articles

Orchestrated Copper-Loaded Nanoreactor for Simultaneous Induction of Cuproptosis and Immunotherapeutic Intervention in Colorectal Cancer

Ion interference, including intracellular copper (Cu) overload, disrupts cellular homeostasis, triggers mitochondrial dysfunction, and activates cell-specific death channels, highlighting its significant potential in cancer therapy. Nevertheless, the insufficient intracellular Cu ions transported by existing Cu ionophores, which are small molecules with short blood half-lives, inevitably hamper the effectiveness of cuproptosis. Herein, the ESCu@HM nanoreactor, self-assembled from the integration of H-MnO2 nanoparticles with the Cu ionophore elesclomol (ES) and Cu, was fabricated to facilitate cuproptosis and further induce relevant immune responses. Specifically, the systemic circulation and tumoral accumulation of Cu, causing irreversible cuproptosis, work in conjunction with Mn2+, resulting in the repolarization of tumor-associated macrophages (TAMs) and amplification of the activation of the cGAS-STING pathway by damaged DNA fragments in the nucleus and mitochondria. This further stimulates antitumor immunity and ultimately reprograms the tumor microenvironment (TME) to inhibit tumor growth. Overall, ESCu@HM as a nanoreactor for cuproptosis and immunotherapy, not only improves the dual antitumor mechanism of ES and provides potential optimization for its clinical application, but also paves the way for innovative strategies for cuproptosis-mediated colorectal cancer (CRC) treatment.

Tumor expression of CD83 reduces glioma progression and is associated with reduced immunosuppression.

Malignant glioma, the most lethal form of brain cancer, presents with an immunosuppressive microenvironment that obstructs tumor cell clearance and hampers immunotherapeutic interventions. Despite advancements in characterizing cellular and extracellular profiles in cancer, the immunosuppressive mechanisms specific to glioma remain poorly understood. We conducted single-cell RNA sequencing of glioma samples, which revealed a select subset of human and mouse glioma cells that express CD83, a marker associated with mature antigen-presenting cells (APCs). To investigate the impact of tumor cell CD83 expression of glioma outcomes, we employed an immunocompetent mouse model of glioma, bioinformatics analyses of human samples and in vitro assays. Our findings revealed that CD83+ tumor cells contribute to tumor growth suppression and are associated with enhanced cytotoxic T cell profiles and activated CD8+ T cells. Increased proinflammatory cytokines were identified in CD83-overexpressing tumor conditions, which were also correlated with long-term CD8+ antitumor responses. Importantly, tumor-derived CD83 could mediate communication with T cells, altering the immune microenvironment to potentially enhance immune related tumor clearance. Collectively, our data suggest that tumor cell expression of CD83 supports the endogenous anti-tumor T cell constituency in malignant glioma. Future research endeavors may aim to further investigate whether CD83 expression can enhance immunotherapeutic approaches and improve patient outcomes.

Metabolic dysfunction-associated steatotic liver disease: a key factor in hepatocellular carcinoma therapy response

The conceptual evolution of non-alcoholic fatty liver disease (NAFLD) to what, since 2023, is called metabolic dysfunction-associated steatotic liver disease (MASLD) not only represents a change in the classification and definition of the disease but also reflects a broader understanding of this heterogeneous condition, which still with many aspects to refine. Although the definition of NAFLD can be interchanged to a high percentage with the new MASLD concept in different aspects, MASLD has been proposed as a relevant factor that influences the response to new immunotherapeutic treatments in the management of MASLD-related hepatocellular carcinoma (HCC), compared to HCC of other etiologies. This indicates that the etiology of HCC plays a relevant role in the prognosis, highlighting the urgency of evaluating treatment regimens for this subgroup of patients in upcoming clinical trials. A better understanding of the pathophysiology of MASLD generates strategies that not only aid in its management but also provide strategies to directly intervene in the carcinogenesis of HCC.

The combined signatures of programmed cell death and immune landscape provide a prognostic and therapeutic biomarker in the hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) ranks as the fourth most common cause of mortality globally among all cancer types. Programmed cell death (PCD) is a crucial biological mechanism governing cancer progression, tumor expansion, and metastatic dissemination. Furthermore, the tumor microenvironment (TME) is critical in influencing overall survival (OS) and immune responses to immunotherapeutic interventions. From a multi-omics perspective, the combination of PCD and TME could help to predict the survival of HCC patient survival and immunotherapy response. Our study analyzed variations in the PCD- and TME-classifier used in the classification of HCC patients into two subgroups: PCD high-TME low and PCD low-TME high. In the following step, we compared the tumor somatic mutation (TMB), immunotherapy response, and functional annotation of both groups of patients. Lastly, Western Blot (WB) were conducted. The immunohistochemistry (IHC) was performed on the Human Protein Atlas (HPA). In the PCD-TME classifier, 23 PCD-related genes and three immune cell types were identified. Patients' prognoses and responses to therapy could be accurately predicted using this model. The findings of this study provide a new instrument for the clinical management of HCC patients, and they contribute to the development of accurate treatment strategies for these patients.

Machine learning model reveals the role of angiogenesis and EMT genes in glioma patient prognosis and immunotherapy

Gliomas represent a highly aggressive class of tumors located in the brain. Despite the availability of multiple treatment modalities, the prognosis for patients diagnosed with glioma remains unfavorable. Therefore, further exploration of new biomarkers is crucial to enhance the prognostic assessment of glioma and to investigate more effective treatment options. In this research, we utilized multiple machine learning techniques to assess the significance of genes related to angiogenesis and epithelial-mesenchymal transition (EMT) in the context of prognosis and treatment for glioma patients. The random forest algorithm highlighted the significance of CALU, and further analysis indicated that the effect of CALU on glioma progression may be regulated by MYC. Different machine learning approaches were employed in our investigation to uncover crucial genes associated with angiogenesis and EMT in glioma. Our findings verify the connection between these genes and the prognosis of patients with glioma, as well as the results of immunotherapeutic interventions. Notably, through experimental verification, we identified CALU as a new prognostic marker for glioma, and inhibiting the expression of CALU can impede the progression of glioma.

EXTH-32. DUAL TARGETING OF CD155/TIGIT AND PD-L1/PD-1 IMMUNE CHECKPOINTS POTENTIATES NATURAL KILLER CELL-MEDIATED CYTOTOXICITY IN MEDULLOBLASTOMA

Abstract Medulloblastoma (MB) is one of the most prevalent pediatric brain malignancies and makes up approximately 20% of all primary brain tumors in children. Current treatment options are not curative for about 30% of patients and leave survivors with an impaired quality of life. Immune checkpoint inhibition can offer a novel targeted therapy but largely remains understudied in MB. The aim of this study was to determine whether immune checkpoint inhibition can be used as a novel targeted therapy in MB. We used MB cell lines, MB patient-derived xenograft (PDX) organoid models, and primary patient-derived MB tissue to study immune checkpoints and their blockade to target MB. We identified the expression of immune checkpoint protein TIGIT on immune cells and its high-affinity ligand CD155 in medulloblastoma patient-derived tissues, cell lines, and PDX MB organoids. In addition, while MB shows weak, if any, PD-L1 protein expression, we found that MB cells can upregulate PD-L1 expression upon stimulation by natural killer (NK) cells via interferon-γ as a putative immune evasive strategy. Subsequent immunotherapeutic interventions with FDA-approved antibodies Tiragolumab (anti-TIGIT), Durvalumab (anti-PD-L1), and their combination potentiated primary NK cell activation and killing of MB cell lines and PDX-derived MB organoids. These data propose a translatable and novel immunotherapeutic strategy for patients diagnosed with MB.

IMMU-63. MESSENGER RNA CHALLENGE PREDICTS CANCER IMMUNOGENICITY AND RESPONSE TO CHECKPOINT INHIBITORS

Abstract BACKGROUND Checkpoint inhibition has emerged as a promising cancer therapeutic approach. Checkpoint inhibitors (CIs) function by overcoming the adaptive T cell exhaustion induced by solid tumor microenvironment including brain tumors, particularly in the neoadjuvant setting. Unfortunately, not every patient who receives CIs will unlock effective antitumor immunity. Objectives: Microsatellite instability and high mutational burden are considered key criteria to predict response to CIs. However, only a minority of patients will fulfill these criteria suggesting the need to develop innovative technologies to identify CI responsive patients. METHODS To determine whether glioma tumors will respond to CIs, we have developed a novel multilamellar mRNA-lipid particle tool to predict response ex vivo. Messenger RNA is complexed into multilamellar lipid particles to form aggregates (RNA-LPAs) to induce pathogen recognition receptor signaling in tumor cells to define an inflammatory profile as an indirect predictor to CI response. RESULTS In naïve mice, we found that multilamellar RNA-LPAs induce activation of Type I IFN system as supported by decreased secretion of IFN-α in MyD88 KO mice compared with wild type mice. We next selected murine glioma cell lines with known response profile to CIs (responders – GL261 and SMA560 vs non-responders – KR158b and CT2A). Prior to evaluation of cytokine profiling, successful uptake of RNA-LPAs was achieved in all cell lines. In 2D cell lines cultures and their corresponding 3D tumor spheroids, we demonstrated that treatment of CI responsive murine glioma models showed a differential cytokine signature (increased secretion of IFN-β/IL-6/CCL4 versus non-responsive models). CONCLUSION We identified a unique inflammatory signature after ex vivo RNA-LPAs challenge that correlates with checkpoint blockade activity. These findings allow for creation of a diagnostic assay to quickly assess tumor immunogenicity, allowing for informed immunotherapeutic treatment.

IMMU-72. TYPE I INTERFERON SIGNALING WITHIN GLIOBLASTOMA CELLS PROMOTES T-CELL EXHAUSTION AND RESISTANCE TO CHECKPOINT INHIBITORS

Abstract Glioblastoma (GBM) remains among the most fatal cancers with few treatment modalities and resistance to modern immunotherapeutic treatment paradigms including immune checkpoint inhibitors (ICI). ICIs neutralize the regulatory signals that disable T cells and have demonstrated remarkable efficacy against a variety of cancers, though not in GBM. The impotence of ICI in GBM has been linked to the tumor’s remarkable capacity to elicit T cell exhaustion, though the mechanism remains poorly understood. Chronic interferon (IFN) cytokine signaling is known to promote immunosuppression and Tex in several cancer types as well as resistance to ICI. However, the role of IFN in GBM has not been investigated despite evidence that IFN signatures exist within clinical samples of GBM. Syngeneic murine GBM cell lines CT2A and SB28 were utilized for in vivo and in vitro studies. Anti-mouse PD-1 and CD8 antibodies or PBS control were injected intraperitoneally. CRISPR editing was used to create validated knockouts (KO) of the type I IFN receptor (IFNAR1) in CT2A. Mice bearing IFNAR1 KO intracranial tumors have improved median survival (p < 0.05) and are exquisitely sensitive to checkpoint anti-PD-1 blockade (p < 0.05) with the majority of mice surviving. Furthermore, surviving mice reject the subsequent intracranial re-challenge with parental CT2A tumors compared to controls (p <0.05) suggesting central memory responses mediating rejection. We conclude that abrogation of Type I IFN signaling is sufficient to extend survival which is further enhanced by ICI. Work is ongoing to further elucidate the precise mechanism that mediates this response and to identify a therapeutic intervention that enables tumor-specific inhibition of the IFN pathway with preliminary work suggesting a CD8 T cell mediated response and reversal of the T cell exhaustion phenotype.

IMMU-24. GLIOBLASTOMA ENRICHED GLYCOSPHINGOLIPIDS MODULATE THE FUNCTION OF HUMAN INKT CELLS

Abstract Glioblastoma is an aggressive primary brain tumor highly resistant to currently available immunotherapies. A deeper understanding of its underlying immunoregulatory mechanisms is paramount to developing future immunotherapeutic treatments. Invariant natural killer T (iNKT) cells are unconventional T cells that recognize lipid antigens presented by an MHC-like molecule called CD1d. Although iNKT cells have been shown to regulate tumor immunity in other cancer types, their role in glioblastoma is not well characterized. Given the lipid-rich nature of the brain and the unique metabolic activity of glioblastoma cells, we hypothesized that interactions between glioblastoma and iNKT cells through glioblastoma-produced lipids could contribute to the immunosuppressive nature of the disease. We report multiple lipid species enriched in aggressive human glioblastoma stem-like cell (GSC) lines that activate human iNKT cells and modulate their functions. Lipidomic LC-MS analysis of GSCs, low-grade glioma stem-like cell lines, and normal human astrocytes revealed various glycosphingolipid species, including sulfatides, highly enriched in the GSCs. Multiple enriched sulfatide species, when presented by CD1d, were recognized by and activated iNKT cells in a dose-dependent manner. Additionally, cytokine analysis of stimulated human PBMC-derived iNKT cells demonstrated that the enriched sulfatides did not induce Th1 cytokine production, but rather many non-Th1 cytokines that potentially counteract Th1-type immune responses. This modulation of iNKT cell function by glioblastoma-enriched glycosphingolipids may contribute to the immunosuppression of glioblastoma and could highlight sulfatide production as a potential therapeutic target for glioblastoma treatment.

Hybrid discrete‐continuum modeling of tumor‐immune interactions: Fractional time and space analysis with immunotherapy

In this paper, we introduce an innovative hybrid discrete‐continuum model that provides a comprehensive framework for understanding the intricate interactions between tumor cells, immune cells, and the effects of immunotherapy. This study distinguishes itself by addressing the limitations of traditional diffusion models, which often fail to capture the irregular and nonlocal movements of cells within the complex tumor microenvironment. To overcome these challenges, we employ fractional time derivatives and the fractional Laplacian operator, offering a more accurate representation of anomalous diffusion processes that are critical in cancer dynamics. Our research begins with a rigorous mathematical analysis, where we establish the global existence of a unique mild solution, laying a solid theoretical foundation for the model. A key innovation of our study is the introduction of the “invasion threshold,” a critical parameter inspired by the next‐generation operator used in epidemiological modeling. This threshold provides a powerful tool for determining the existence and stability of equilibrium points, offering deep insights into the conditions that either promote or inhibit tumor growth under immunotherapeutic interventions. By integrating a hybrid discrete‐continuum approach, we capture the individual behavior of each cell, allowing for a more detailed exploration of the dynamic interplay within the tumor microenvironment. This model not only advances our understanding of tumor‐immune interactions but also holds potential for informing more effective therapeutic strategies, making a significant contribution to the field of mathematical oncology.

Application of spatial-omics to the classification of kidney biopsy samples in transplantation.

Improvement of long-term outcomes through targeted treatment is a primary concern in kidney transplant medicine. Currently, the validation of a rejection diagnosis and subsequent treatment depends on the histological assessment of allograft biopsy samples, according to the Banff classification system. However, the lack of (early) disease-specific tissue markers hinders accurate diagnosis and thus timely intervention. This challenge mainly results from an incomplete understanding of the pathophysiological processes underlying late allograft failure. Integration of large-scale multimodal approaches for investigating allograft biopsy samples might offer new insights into this pathophysiology, which are necessary for the identification of novel therapeutic targets and the development of tailored immunotherapeutic interventions. Several omics technologies - including transcriptomic, proteomic, lipidomic and metabolomic tools (and multimodal data analysis strategies) - can be applied to allograft biopsy investigation. However, despite their successful application in research settings and their potential clinical value, several barriers limit the broad implementation of many of these tools into clinical practice. Among spatial-omics technologies, mass spectrometry imaging, which is under-represented in the transplant field, has the potential to enable multi-omics investigations that might expand the insights gained with current clinical analysis technologies.

Mycobacterium w - a promising immunotherapeutic intervention for diseases.

Immunomodulating agents interact with the immune system and alter the outcome of specific immune processes. As our understanding of the immune system continues to evolve, there is a growing effort to identify agents with immunomodulating applications to use therapeutically to treat various diseases. Mycobacterium w (Mw), a heat-killed mycobacterium, is an atypical mycobacterial species that possesses strong immunomodulatory properties. Mw was initially evaluated as an immune-therapeutic against leprosy, but since then Mw has generated a lot of interest and been studied for therapeutic applications across a host of diseases, such as pulmonary tuberculosis, tuberculous pericarditis, sepsis, lung cancer, and more. This article summarizes a large body of work published in the past five decades, describing various aspects of Mw and its potential for further therapeutic development.

Single-cell and bulk transcriptomic datasets enable the development of prognostic models based on dynamic changes in the tumor immune microenvironment in patients with hepatocellular carcinoma and portal vein tumor thrombus.

Hepatocellular carcinoma (HCC) patients exhibiting portal vein tumor thrombosis (PVTT) face a high risk of rapid malignant progression and poor outcomes, with this issue being compounded by a lack of effective treatment options. The integration of bulk RNA-sequencing (RNA-seq) and single-cell RNA-seq (scRNA-seq) datasets focused on samples from HCC patients with PVTT has the potential to yield unprecedented insight into the dynamic changes in the tumor microenvironment (TME) and associated immunological characteristics in these patients, providing an invaluable tool for the reliable prediction of disease progression and treatment responses. scRNA-seq data from both primary tumor (PT) and PVTT cells were downloaded from the Gene Expression Omnibus (GEO) database, while the International Cancer Genome Consortium (ICGC) and Cancer Genome Atlas (TCGA) databases were used to access bulk RNA-seq datasets. scRNA-seq, clustering, GSVA enrichment, mutational profiling, and predictive immunotherapeutic treatment analyses were conducted using these data with the goal of systematically assessing the heterogeneity of PT and PVTT cells and establishing a model capable of predicting immunotherapeutic and prognostic outcomes in patients with HCC. These analyses revealed that PVTT cells exhibited patterns of tumor proliferation, stromal activation, and low levels of immune cell infiltration, presenting with immune desert and immune rejection-like phenotypes. PT cells, in contrast, were found to exhibit a pattern of immunoinflammatory activity. Core PVTT-associated genes were clustered into three patterns consistent with the tumor immune rejection and immune desert phenotypes. An established clustering model was capable of predicting tumor inflammatory stage, subtype, TME stromal activity, and patient outcomes. PVTT signature genes were further used to establish a risk model, with the risk scores derived from this model providing a tool to evaluate patient clinicopathological features including clinical stage, tumor differentiation, histological subtype, microsatellite instability status, and tumor mutational burden. These risk scores were also able to serve as an independent predictor of patient survival outcomes, responses to adjuvant chemotherapy, and responses to immunotherapy. In vitro experiments were used to partially validate the biological prediction results. These results offer new insight into the biological and immunological landscape of PVTT in HCC patients, By utilizing individual patient risk scores, providing an opportunity to guide more effective immunotherapeutic interventional efforts.

Emerging Cationic Nanovaccines.

Cationic vaccines of nanometric sizes can directly perform the delivery of antigen(s) and immunomodulator(s) to dendritic cells in the lymph nodes. The positively charged nanovaccines are taken up by antigen-presenting cells (APCs) of the lymphatic system often originating the cellular immunological defense required to fight intracellular microbial infections and the proliferation of cancers. Cationic molecules imparting the positive charges to nanovaccines exhibit a dose-dependent toxicity which needs to be systematically addressed. Against the coronavirus, mRNA cationic nanovaccines evolved rapidly. Nowadays cationic nanovaccines have been formulated against several infections with the advantage of cationic compounds granting protection of nucleic acids in vivo against biodegradation by nucleases. Up to the threshold concentration of cationic molecules for nanovaccine delivery, cationic nanovaccines perform well eliciting the desired Th 1 improved immune response in the absence of cytotoxicity. A second strategy in the literature involves dilution of cationic components in biocompatible polymeric matrixes. Polymeric nanoparticles incorporating cationic molecules at reduced concentrations for the cationic component often result in an absence of toxic effects. The progress in vaccinology against cancer involves in situ designs for cationic nanovaccines. The lysis of transformed cancer cells releases several tumoral antigens, which in the presence of cationic nanoadjuvants can be systemically presented for the prevention of metastatic cancer. In addition, these local cationic nanovaccines allow immunotherapeutic tumor treatment.

Identification of three subtypes of ovarian cancer and construction of prognostic models based on immune-related genes

BackgroundImmunotherapy has revolutionized the treatment of ovarian cancer (OC), but different immune microenvironments often constrain the efficacy of immunotherapeutic interventions. Therefore, there is an imperative to delineate novel immune subtypes for development of efficacious immunotherapeutic strategies.MethodsThe immune subtypes of OC were identified by consensus cluster analysis. The differences in clinical features, genetic mutations, mRNA stemness (mRNAsi) and immune microenvironments were analyzed among subtypes. Subsequently, prognostic risk models were constructed based on differentially expressed genes (DEGs) of the immune subtypes using weighted correlation network analysis.ResultsOC patients were classified into three immune subtypes with distinct survival rates and clinical features. Different subtypes exhibited varying tumor mutation burdens, homologous recombination deficiencies, and mRNAsi levels. Significant differences were observed among immune subtypes in terms of immune checkpoint expression and immunogenic cell death. Prognostic risk models were validated as independent prognostic factors demonstrated great predictive performance for survival of OC patients.ConclusionIn this study, three distinct immune subtypes were identified based on gene sets related to vaccine response, with the C2 subtype exhibiting significantly worse prognosis. While no statistically significant differences in tumor mutation burden (TMB) were observed across the three subtypes, the homologous recombination deficiency (HRD) score and mRNA stemness index (mRNAsi) were notably elevated in the C2 group compared to the others. Immune infiltration analysis indicated that the C2 subtype may have an increased presence of regulatory T (Treg) cells, potentially contributing to a more favorable response to combination therapies involving PARP inhibitors and immunotherapy. These findings offer a precision medicine approach for tailoring immunotherapy in ovarian cancer patients. Moreover, the C3 subtype demonstrated significantly lower expression levels of immune checkpoint genes, a pattern validated by independent datasets, and associated with a better prognosis. Further investigation revealed that the immune-related gene FCRL5 correlates with ovarian cancer prognosis, with in vitro experiments showing that it influences the proliferation and migration of the ovarian cancer cell line SKOV3.

Anti-dopamine receptor 2 antibody encephalitis in adults: a case report

BackgroundAnti-dopamine receptor 2 (D2R) antibody encephalitis (D2R encephalitis) is a subtype of autoimmune encephalitis (AE). Lesions in affected patients primarily involve the basal ganglia, resulting in a range of psychiatric and movement disorders. A majority of cases reported to date have impacted children or adolescents, whereas we here describe a case of adult-onset D2R encephalitis.Case presentationA 30-year-old female patient affected by insomnia, recent memory impairment, bradykinesia, decreased responsivity, increased muscular tone of the extremities, and involuntary shaking of the right limb. Magnetic resonance imaging (MRI) of the basal ganglia did not reveal any notable findings, and both serum and cerebrospinal fluid were positive for antibodies specific for D2R. D2R encephalitis was diagnosed following the exclusion of other diseases. The patient’s symptoms improved significantly with immunotherapeutic treatment, and she recovered fully over a 6-month follow-up period.ConclusionsD2R is a new form of AE that can develop in adults and can be effectively treated via immunotherapy.

Clinicopathologic features and tumor immune microenvironment of lymphocyte-rich hepatocellular carcinoma

Lymphocyte-rich hepatocellular carcinoma (LR-HCC) is a rare variant of HCC characterized by pronounced lymphoid infiltration, providing an opportunity to explore the tumor immune microenvironment (TIME) and its potential impact on disease progression and therapy. This study aimed to describe the clinicopathological features and TIME components of LR-HCC to inform more effective treatment strategies. In this study, we present five novel cases of LR-HCC alongside a comprehensive retrospective analysis of 136 previously documented cases. Immunohistochemical evaluation was utilized to systematically assess TIME components and immune checkpoint inhibitor (ICI) targets. Our findings demonstrated a significant predominance of CD3+ T cells over CD20+ B cells (1.5:1, P < 0.001) and a higher frequency of CD8+ cytotoxic T cells compared to Foxp3+ regulatory T cells (2.4:1, P < 0.001), indicating an immune landscape potentially favorable for immunotherapeutic interventions. Programmed cell death ligand 1 (PD-L1) expression was detected in three out of five cases using the VENTANA SP263 assay, suggesting potential responsiveness to ICIs. A pooled analysis of 38 cases showed a 5-year overall survival rate of 73.6 %, which is notably lower than previously reported rates (>90 %), with 29.4 % of patients experiencing postoperative recurrence or lymph node metastasis. Multivariate analysis identified tumor size as an independent predictor of overall survival. These findings emphasize the relevance of TIME characteristics in understanding LR-HCC and point to promising avenues for targeted and immune-based therapies, contributing to the optimization of clinical management for this distinct cancer subtype.

Multi-Enzyme Nanoparticles as Efficient Pyroptosis and Immunogenic Cell Death Inducers for Cancer Immunotherapy.

Immunotherapy represents a widely employed modality in clinical oncology, leveraging the activation of the human immune system to target and eradicate cancer cells and tumor tissues via endogenous immune mechanisms. However, its efficacy remains constrained by inadequate immune responses within "cold" tumor microenvironment (TME). In this study, a multifunctional nanoscale pyroptosis inducer with cascade enzymatic activity (IMZF), comprising superoxide dismutase (SOD), catalase (CAT), peroxidase (POD), and glutathione oxidase (GSHOx), is dissociated within the acidic and glutathione-rich TME. The vigorous enzymatic activity not only generates oxygen (O2) to alleviate hypoxia and promote M2 to M1 macrophage polarization but also yields reactive oxygen species (ROS) and depletes glutathione (GSH) within the TME. Functioning as an immunogenic cell death (ICD) activator and pyroptosis inducer, IMZF synergistically triggers dendritic cell maturation and inflammatory lymphocyte infiltration via ICD-associated pyroptosis, thereby reversing immune suppression within the TMEs. Consequently, it exerts inhibitory effects on both primary and distal tumors. This cascade enzymatic platform-based pyroptosis inducer offers an intelligent strategy for effectively overcoming immune suppression within "cold" tumors, thereby providing a promising avenue for advanced immunotherapeutic interventions.

Development of a prognostic model related to homologous recombination deficiency in glioma based on multiple machine learning.

Despite advances in neuro-oncology, treatments of glioma and tools for predicting the outcome of patients remain limited. The objective of this research is to construct a prognostic model for glioma using the Homologous Recombination Deficiency (HRD) score and validate its predictive capability for glioma. We consolidated glioma datasets from TCGA, various cancer types for pan-cancer HRD analysis, and two additional glioma RNAseq datasets from GEO and CGGA databases. HRD scores, mutation data, and other genomic indices were calculated. Using machine learning algorithms, we identified signature genes and constructed an HRD-related prognostic risk model. The model's performance was validated across multiple cohorts. We also assessed immune infiltration and conducted molecular docking to identify potential therapeutic agents. Our analysis established a correlation between higher HRD scores and genomic instability in gliomas. The model, based on machine learning algorithms, identified seven key genes, significantly predicting patient prognosis. Moreover, the HRD score prognostic model surpassed other models in terms of prediction efficacy across different cancers. Differential immune cell infiltration patterns were observed between HRD risk groups, with potential implications for immunotherapy. Molecular docking highlighted several compounds, notably Panobinostat, as promising for high-risk patients. The prognostic model based on the HRD score threshold and associated genes in glioma offers new insights into the genomic and immunological landscapes, potentially guiding therapeutic strategies. The differential immune profiles associated with HRD-risk groups could inform immunotherapeutic interventions, with our findings paving the way for personalized medicine in glioma treatment.

Vaccination generates functional progenitor tumor-specific CD8 T cells and long-term tumor control

BackgroundImmune checkpoint blockade (ICB) therapies are an important treatment for patients with advanced cancers; however, only a subset of patients with certain types of cancer achieve durable remission. Cancer vaccines...