OncoImmunology

BackgroundChimeric antigen receptor (CAR)-T cell therapies efficacy in solid tumors remains limited, largely due to the profoundly immunosuppressive tumor microenvironment (TME) which drives CAR-T cells to dysfunction and poor persistence. A comprehensive understanding of the dynamic interplay between CAR-T cells and the TME is therefore critical for the rational design of more effective CAR-T strategies for solid cancers. MethodsHere, we performed single-cell RNA sequencing of tumor samples from immunocompetent mice treated with stroma-targeting EDA-CAR-T cells, profiling CAR-T cell states and TME programs at the peak of antitumor response and during subsequent tumor progression. ResultsOur analysis revealed a marked temporal remodeling of EDA-CAR-T cells within the TME, where early antitumor efficacy is associated with concurrent expansion of cytotoxic effector CD8 CAR-T cells and activation of memory CD4 CAR-T subsets. Moreover, EDA-CAR-T cells effectively engaged the myeloid compartment, resulting in strengthened communication networks involving T cell activation. However, by tumor progression, EDA-CAR-T cells suffered a widespread transcriptional reprogramming towards dysfunction, characterized by loss of effector programs alongside induction of exhaustion and immunoregulatory pathways within the TME, including PD-L1/PD-L2 and TGF{beta} signaling, which impairs sustained immune responses. Notably, early CAR-T cell activation led to increased susceptibility to TME-mediated immunosuppression, revealing EDA-CAR-T-specific soluble galectin-mediated cell-to-cell interaction networks. ConclusionsTogether, this works offers a high-resolution view of CAR-T cell dynamics within the solid TME, uncovering cellular and molecular mechanisms of rapid functional decline and identifying regulatory pathways within the TME that can be exploited to improve CAR-T cell therapy efficacy in solid tumors. KEY MESSAGES OF THE ARTICLEO_ST_ABSWhat is already known on this topicC_ST_ABSThe determinants of CAR-T cell therapeutic efficacy in solid tumors remain poorly defined, largely due to the complexity of the immunosuppressive tumor microenvironment. In this effort, it is necessary to perform comprehensive and detailed mechanistic studies that capture CAR-T cell dynamics within the solid tumor microenvironment to understand treatment failure. What this study addsWe performed single-cell profiling of stroma-targeting EDA-CAR-T cells, revealing their dynamic reprogramming toward dysfunction within the solid tumor microenvironment. We dissected CAR-T cell states and their cell-to-cell interactions with the tumor microenvironment across response and tumor progression and identified mechanisms linking CAR-T cell functionality and therapeutic failure. How this study might affect research, practice or policyThis study provides comprehensive mechanistic insights from an immunocompetent model that can be leveraged to identify shared determinants of CAR-T cell functionality in solid tumors and potentially guide the rational development of improved CAR-T cell therapies.

Immune checkpoint therapies have transformed clinical practice; however, reliable biomarkers to predict response remain limited. Tumor mutational burden (TMB) has emerged as an important biomarker because it is thought to reflect neoantigen load, yet its predictive utility has been inconsistent. This limitation may partly arise because TMB primarily captures tumor-intrinsic immunogenicity, which is heterogeneous and does not fully reflect the state of antitumor immunity. To identify transcriptomic surrogates that capture both high mutational burden and antitumor immune activation, we investigated whether mRNA expression of mutagenic APOBEC3 family members could serve as surrogates for high TMB and T cell-rich tumors. Using a pan-cancer computational framework, we evaluated the association of four APOBEC3 genes with mutational burden, neoantigen load, immune infiltration, and immune checkpoint blockade response. Among APOBEC3A, APOBEC3B, APOBEC3G, and APOBEC3H, APOBEC3G emerged as the strongest and most consistent marker of a TMBhighCD8high and NeoantigenhighCD8high tumor phenotypes. Single-cell analyses further demonstrated that APOBEC3G is enriched in both malignant cells and T cells compared with other APOBEC3 family members, with APOBEC3G-positive CD8+ T cells exhibiting elevated activation markers including GZMB and IFNG. Importantly, retrospective analyses of 50 immune checkpoint blockade cohorts showed that APOBEC3G had the most consistent association among APOBEC3 family members with treatment response and clinical outcomes. Together, these findings identify APOBEC3G as a candidate transcriptomic marker of a TMB-associated, T cell-inflamed tumor state linked to immune-checkpoint blockade benefit, warranting further prospective validation.

Background The clinical significance of clonal hematopoiesis of indeterminate potential (CHIP) in melanoma remains incompletely defined, particularly with respect to CHIP genotype, clone size, and somatic mutations (e.g BRAF mutations). We integrated human cohort data and a syngeneic melanoma mouse model to evaluate whether CHIP is associated with melanoma risk, tumor growth, and differential clinical outcomes. Methods We analyzed CHIP prevalence and survival in a large treatment-unselected melanoma cohort (n=2,480), evaluated tumor growth in a syngeneic BRAF-mutant (BRAFmut) melanoma murine model of TET2-CHIP and DNMT3A-CHIP, and assessed survival outcomes in an immune checkpoint inhibitor (ICI)-treated advanced melanoma cohort (n=361). Associations with progression-free survival (PFS) and overall survival (OS) were evaluated using Kaplan-Meier analyses and multivariable Cox proportional hazards models. Results CHIP was enriched among patients with treatment-unselected melanoma compared with age/sex-matched healthy controls, and larger CHIP clone size showed an age-adjusted association with inferior OS. In a syngeneic BRAFmut melanoma murine model, TET2-CHIP, but not DNMT3A-CHIP, was associated with significantly increased primary melanoma tumor growth. Among patients with ICI-treated advanced melanoma, CHIP was associated with worse OS compared with patients without CHIP. TET2-CHIP had the strongest adverse association with survival, whereas DNMT3A-CHIP was not significantly associated with PFS or OS. Conclusions CHIP is enriched in melanoma and exploratory analyses demonstrate genotype-specific differences in melanoma tumor growth and clinical outcomes. These findings support further investigation of genotype-specific CHIP profiling as a potential biomarker for melanoma risk stratification and immunotherapy outcomes.

BackgroundTumor-associated neutrophils (TANs) are emerging as functionally heterogeneous and plastic cells in the tumor microenvironment. In immunologically cold tumors, elevated neutrophil abundance correlates with poor prognosis and resistance to immune checkpoint inhibition (ICI). Whether distinct anti-tumoral neutrophil states can be induced by different immunotherapies and how they relate to treatment efficacy remains unclear. MethodsUsing the syngeneic MOC2-huEGFR (M2h) mouse model of head and neck squamous cell cancer (HNSCC), we treated tumor-bearing mice with agonistic anti-CD40 monoclonal antibody (mAb) (aCD40), TNF, Cetuximab, or a combination of all three, designated Neutrophil Activating Therapy (NAT). In addition to evaluating anti-tumor efficacy, we performed single-cell multiomics RNA and protein sequencing, followed by bioinformatics analyses and flow cytometry validation. NAT-induced anti-tumor efficacy and related neutrophil states were also assessed in another cold tumor model, 9464D-GD2 neuroblastoma. Murine treatment-induced neutrophil gene signatures were then evaluated using clinical, proteomic, and transcriptomic data from HNSCC patients. ResultsFive transcriptionally distinct neutrophil states (N0-N4), including precursor state CD49d+ N4, were identified using the M2h model. N0 neutrophils (immunosuppressive/quiescent) dominated untreated tumors, but not in successful treatments. ISG+ N1 neutrophils and CCR3+ N3 neutrophils expanded by aCD40, TNF, and NAT treatment with anti-tumoral gene signatures and found more interacting with CD8+ T cells from bioinformatics analysis. N2 neutrophils reflected a recently established hypoxia-adapted state found in all treatments. ICAM1 (CD54) emerged as a marker of treatment-induced neutrophil activation, discriminating N1, N2, and N3 neutrophils from N0 neutrophils, validated by flow cytometry. In the 9464D-GD2 neuroblastoma model, NAT treatment also reduced the N0 dominance seen in untreated tumors in the HNSCC model but failed to induce anti-tumoral neutrophil states. In 23 HNSCC patients who received ICI therapy, ICAM1 protein expression in neutrophils trended toward association with responder status (TMA-level p=0.029), and ICAM1 neutrophil gene expression also trended toward association with improved overall survival in TCGA data (HR=0.75, p=0.059). ConclusionsDistinct immunotherapy-induced neutrophil states are defined by transcriptional profiles enriched in different functional pathways, associated with both anti-tumor and pro-tumor signatures. ICAM1 identifies activated neutrophils and potentially serves as a biomarker of ICI response in HNSCC, warranting further clinical validation. WHAT IS ALREADY KNOWN ON THIS TOPICNeutrophil heterogeneity has received increasing attention, with studies identifying antitumoral neutrophil populations, either at baseline or induced by treatment. Several effective treatment regimens involve an anti-CD40 agonist (aCD40) antibody, among them Neutrophil Activating Therapy (NAT), which combines aCD40, TNF, and a tumor antigen binding antibody designed to reprogram neutrophils. NAT could thus be particularly effective in cold, myeloid-rich tumors that are largely unresponsive to conventional immunotherapies such as checkpoint blockade, enacting these anti-tumoral effects through similar and different mechanisms; however, this has not been tested. WHAT THIS STUDY ADDSThis study adds a single-cell multi-omics framework for defining treatment-induced neutrophil heterogeneity in MOC2-huEGFR and 9464D-GD2 tumors, two immunologically cold models. It highlights ICAM1/CD54 and interferon-stimulated genes as markers of a dominant antitumor neutrophil state, while showing that neutrophil state composition variy across tumor models. HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE, OR POLICYThese results support the efficacy of a myeloid-modulating therapy built around aCD40 and TNF in a cold murine head and neck cancer model, and to a lesser extent in a cold murine neuroblastoma model. ICAM1/CD54 expression in neutrophils was also identified as a promising marker of antitumor activity and treatment response. More broadly, this work suggests that incorporating aCD40 and/or TNF into existing treatment regimens could improve outcomes, while ICAM1/CD54-high neutrophils may serve as a useful therapeutic readout.

Background: Immune checkpoint inhibitors have transformed cancer treatment, yet a large number of patients fail to respond. Identifying molecular characteristics that predict response before treatment initiation remains an unmet need. Towards that end, this study presents a large-scale integrative analysis of existing single-cell and bulk tissue datasets, aimed at identifying predictive features while providing insights into their cellular origin and potential function within the tumor microenvironment. Methods: A stepwise analysis was performed using single-cell RNA-sequencing data from 60 melanoma patients at baseline, separated into discovery (n=41) and validation (n=19) sets. An integrated bulk transcriptomics dataset (n=128) from melanoma patients and a bladder cancer dataset (n=298) were used for further validation. Results: Integrative analysis of melanoma single-cell datasets revealed that responders exhibit distinct molecular profiles across multiple cell types compared to non-responders. Notably, these included downregulation of the TNFR superfamily and other immunosuppressive genes (TNFRSF18, TNFRSF9, TNFRSF4, LGALS1, BATF, IL12RB2, LINGO1, DUSP4, SDC4, VCAM1) in T-cells. By investigating the findings from the immune cell populations in the bulk tumor context, 13 transcripts were found to be consistently associated with response across all cohorts. These were differentially expressed in T-cells (SELL, EPB41, CD96, UHFR2, LINGO1, LGALS1), B-cells (ALDH5A1), NK cells (PLEC, PDGFRB) and Monocytes (TLR10, ST6GAL1, IKZF1, MPRIP). A predictive model based on these features effectively discriminated responders from non-responders in melanoma (AUC=0.73). The model maintained significant predictive power in an independent bladder cancer dataset (IMvigor210; AUC=0.64). Of high clinical relevance, it demonstrated enhanced performance in identifying responders among patients with low tumor mutational burden (AUC=0.75). Conclusion: Our study reveals pre-treatment molecular features related to immune-cancer crosstalk that are associated with response to immunotherapy. A 13-gene model demonstrates potential added clinical value in stratifying responders, particularly in patients with low tumor mutational burden, meriting further validation.

Antigen density critically influences CAR T-cell efficacy. We show that ibrutinib induces CD19 upregulation in B-cell lymphoma models, enhancing CAR T-cell cytotoxicity. Pharmacologic modulation of target antigen expression represents a promising strategy to overcome resistance.

Tumor-draining lymph nodes (tdLNs) are critical hubs of anti-tumor immunity but are also vulnerable to tumor-mediated immunosuppression. We analyzed T cell and B cell receptor (TCR/BCR) repertoires and transcriptomes from sentinel and non-sentinel lymph nodes of patients with melanoma from a historical pre-immune checkpoint inhibitor cohort (1994-2002) and an independent contemporary validation cohort (2022-2024). Melanoma-positive lymph nodes exhibited increased immune receptor clonality compared with tumor-free nodes. While average clonality showed no consistent association with outcome, the presence of extreme high-clonality outliers in individual lymph nodes was strongly associated with poor melanoma-specific survival. These outliers were characterized by a loss of lymphocyte-related genes and activation markers, an enrichment of melanocytic transcripts, and the suppression of immune signaling pathways, consistent with local immune dysfunction. Increased clonality was confined to lymph nodes and not observed in the peripheral blood. T cell responses to melanocyte differentiation antigens were infre-quently shared between lymph nodes and peripheral blood, highlighting immune compartmentalization.

BackgroundGliomas are heterogeneous tumors with poor outcomes following current therapies, including immunotherapy. The tumor microenvironment (TME) is a critical determinant of therapeutic response in gliomas. We have classified the immune TME of gliomas by multiplex immunofluorescence (mIF). MethodsTissue taken at initial resection from 354 patients with newly-diagnosed glioma grades 2-4 were analyzed using three mIF panels of markers for T, B, and myeloid cells. Tumor cores were characterized by the relative abundances of: (i) 15 primary immune phenotypes, (ii) 96 secondary immune phenotypes, and, (iii) 29 biologically meaningful multi-marker immune phenotypes. ResultsUsing unsupervised cluster analysis of WHO grade 4 gliomas we identified four subtypes , {beta}, {gamma}, and {delta} that were internally reproducible. Immune subtype was characterized by high abundance of antigen-presenting cells (APCs) and low levels of MHC II- monocytes. Subtype {beta} was high in regulatory T cells and myeloid cells, but low in lymphocytes with effector functions. Subtype {gamma} displayed high abundance of immune cell phenotypes, particularly lymphocytes with effector or helper functions. Subtype {delta} was low in lymphoid and myeloid immune phenotypes and APCs, with poorer outcomes. Grade 3 tumors could also be classified into , {beta}, {gamma}, and {delta} subtypes, indicating generalizability of these immune TME subtypes across high grade gliomas. ConclusionsWe have identified internally reproducible criteria for classifying gliomas according to the immune microenvironment, findings that could aid our understanding of the natural progression of low- and high-grade gliomas and inform the rational application of immune-oncologic therapeutic interventions.

Background: Multiple myeloma (MM) progression is accompanied by remodeling of the bone marrow immune microenvironment. Local interactions among malignant plasma cells, stromal cells, myeloid cells, and immune cells not only support tumor cell survival, expansion, and immune escape, but are also closely associated with disease progression, therapeutic response, and clinical prognosis. Moreover, T cell exhaustion is a common T cells dysfunction in MM and limited efficacy of T cell-targeting therapies. However, the in situ organization and clinical significance of exhausted T cells in MM patients bone marrow remain insufficiently understood. Methods: In this study, we analyzed bone marrow Xenium 5K spatial transcriptomics data from control (Ctrl), monoclonal gammopathy of undetermined significance (MGUS), smoldering myeloma (SM), and MM samples. After canonical multi-sample integration and celltype annotation, we used Gaussian mixture model (GMM)-based spatial partitioning, and multilayer perceptron (MLP) machine learning for systematic characterization the T cell microenvironment in MM bone marrow. Results: Our results showed that exhaustion-like T cells increased during MM progression and formed spatially discrete T cell-enriched regions in the bone marrow, which we defined as exhaustion-like bone marrow T cell islands (eBM-TIs). These niches were mainly characterized by enhanced T cell-plasma cell communication associated with upregulated Galectin signaling. Pseudobulk analysis further showed enhanced IFN-related signaling in eBM-TIs, accompanied by upregulation of CXCR3 ligands such as CXCL9 and CXCL10, suggesting that the IFN-CXCL9/10 axis may contribute to T cell chemotaxis, maintenance of chronic inflammation, and formation of exhaustion-like states. By transferring spatial niche labels to scRNA-seq cohorts with available clinical staging information using MLP, we further found that the proportion of eBM-TI-like T cells was associated with higher disease risk and unfavorable prognostic outcomes. Conclusions: In summary, this study identifies eBM-TIs as a spatial niche in the MM bone marrow. These niches represent an important immune unit linking chronic inflammation, T cell exhaustion, and clinical risk, and may serve as a potential biomarker of MM disease progression.

Brain metastases (BrM) are associated with poor prognosis. A better understanding of anti-tumor immune responses in the context of immune specialized microenvironment of the brain is required to develop improved therapeutic strategies for this disease. We demonstrate that the conventional dendritic cells type 1 (cDC1) gene signature positively correlates with a prolonged BrM-dependent survival in melanoma and breast cancer patients. Furthermore, intracranial anti-tumor immune responses in preclinical BrM models consistently rely on cDC1s for tumor growth control, BrM-dependent survival and maintenance of the intra-tumoral CD8+ T cell pool, in contrast to variable, cancer type-dependent cDC1 roles in extracranial tumors. This is underpinned by tumor site-specific cDC1 molecular profiles with distinct Toll like receptor repertoires, upregulation of co-stimulatory molecules and IL-12, and enhanced type-I-IFN signaling in intracranial cDC1s, with the latter driving increased cDC1 activation. cDC1s also promote the conversion of progenitor exhausted CD8+ T cells to transient effectors, which is further enhanced by immune checkpoint blockade therapy. These findings pinpoint cDC1s as a major cell population of interest in the development of future immunotherapies for BrM.

Dendritic cells (DCs) are central orchestrators of antitumor immunity. Several DC subsets--including conventional type 1 (cDC1), conventional type 2 (cDC2), plasmacytoid DCs (pDCs), and mature DC populations--play distinct roles in immune surveillance, tumor control, immunotherapy response and prognosis. Recent findings suggest that cDC1 are spatially closed to CD8 T-cell and contribute to tertiary lymphoid structure formation in lung cancer. However, how other DC subsets interact with cDC1 to shape the tumor microenvironment (TME) remains largely unknown. Here, we analyzed the spatial distribution of major DC subsets, including cDC1, cDC2, mature DC and pDC, together with CD8 T cells in a cohort of anti-PD1-treated NSCLC patients and we deciphered the corresponding immune microenvironment behavior by paired transcriptomic analysis. We found that, while other DC subsets populated the stroma, cDC2 were localized both in the stroma and in tumor nests. Moreover, unlike other DC subsets, cDC2 abundancy did not affect ICB response both at transcriptomic and in situ analysis. We described spatial organization of DCs in megaclusters characterized by distinct proportions of DC subsets. Patients enriched in megaclusters involving variable proportion of pDC, cDC1 and mature DC, exhibited pro-inflammatory transcriptomic programs while those enriched in cDC2-based megaclusters showed limited immune activation features. Globally, DC in lung cancer were structured around three distinct DC spatial patterns, namely cDC1-driven, cDC2-driven and DC-Scattered, each defined by unique compositions of DC megaclusters, immune features and pathways activation profiles. Among them, the cDC1-driven pattern was associated to prolonged anti-PD1 response in two independent cohorts.

CD47 is a "dont eat me" signal that suppresses macrophage-mediated phagocytosis. Its upregulation in lung and other cancers facilitates tumour immune escape, making CD47 a promising immunotherapeutic target. Studies have demonstrated anti-tumour efficacy of CD47 blockade in preclinical lung cancer models, but monoclonal antibodies targeting CD47 have had limited efficacy as monotherapy in solid tumour patients to date. This discrepancy may in part reflect the use of human tumour xenografts in mice that do not have fully-functioning immune systems in preclinical efficacy studies. Thus, understanding tumour responses to CD47 inhibition using immune competent lung cancer models is needed to inform strategies to harness its therapeutic potential. Here, we characterized the effects of CD47 knockout (KO) on tumour growth and immune responses in two syngeneic, orthotopic murine lung cancer models, LLC-Luc (LLC) and CMT167 (CMT). As expected, CD47 KO impaired the fitness of LLC and CMT cells in vivo. Mice with CD47-deficient tumours exhibited prolonged survival and increased infiltration of anti-tumour leukocytes. However, although CD47 KO impaired lung tumour growth in syngeneic mice, KO tumours were ultimately lethal. Immunophenotyping revealed an increased prevalence of PD-L1+ cells in CD47-deficient tumours, nominating PD-L1-mediated suppression of tumour immunity as an acquired mechanism of resistance to CD47 blockade. Concordantly, dual inhibition of CD47 and PD-L1 extended the survival of CMT tumour-bearing mice compared to inhibition of either alone. These findings suggest that PD-L1 blockade could be leveraged to overcome resistance and potentiate the efficacy of CD47-targeted immunotherapy in lung cancer.

Macrophage-melanoma interactions critically shape the tumor microenvironment, yet the cytokine networks driving this process remain incompletely understood. Among these, colony-stimulating factors--particularly granulocyte-macrophage colony-stimulating factor (GM-CSF) and granulocyte colony-stimulating factor (G-CSF or CSF3)--regulate myeloid cell behavior during cancer progression, although their specific roles in melanoma remain unclear. Using co-culture systems of melanoma and monocyte-derived macrophages, we found that GM-CSF-primed macrophages induced robust G-CSF secretion and concurrent CSF3 upregulation in both cell compartments. Moreover, transcriptomic profiling of patient-derived tumor-associated macrophages (TAMs) confirmed elevated CSF3 and CSF3R expression in metastatic melanoma. Multiplex immunofluorescence analysis of a stage II-IV primary melanoma cohort (n=84) revealed increased G-CSF and CD114 expression in TAMs and tumor cells from patients who subsequently developed metastasis. High G-CSF levels in either TAMs or melanoma cells emerged as an independent prognostic factor for shorter disease-free and overall survival (p < 0.001). Mechanistically, G-CSF activated STAT1/STAT3 signaling in melanoma cells and promoted proliferation and invasion in a CD114-dependent manner. Of note, G-CSF drove monocyte differentiation toward a distinct inflammatory macrophage state characterized by STAT1/STAT3 activation and a pro-invasive secretory profile. Furthermore, melanoma cells conditioned by G-CSF-differentiated macrophages displayed increased in vivo lung colonization and enriched transcriptional programs linked to invasion and proliferation. Collectively, these findings establish the G-CSF/CD114 axis as a potential clinically relevant driver of melanoma metastasis and identify G-CSF as a novel independent prognostic biomarker. HIGHLIGHTSO_LIDespite its extended clinical use, G-CSF role in human melanoma remains undefined. C_LIO_LIHigh G-CSF expression in primary melanomas correlates with poor patient survival. C_LIO_LIG-CSF promotes melanoma cell invasion and proliferation through CD114 signaling. C_LIO_LIG-CSF drives macrophage differentiation toward a pro-tumoral phenotype. C_LIO_LIMelanoma cells conditioned by G-CSF-primed macrophages are more metastatic. C_LI

Background: CD8+ tumor-infiltrating lymphocytes (TILs) are established prognostic markers in colorectal cancer, yet the clinical significance of CD103+CD8+ tissue-resident memory-like (TRM-like) T cells in locally advanced rectal cancer (LARC) after neoadjuvant chemoradiotherapy (NACRT) remains unknown. Methods: We quantified CD8+ and CD103+CD8+ T-cell densities in stromal and intratumoral compartments of post-NACRT resection specimens from 40 LARC patients using Cu-Cyto, a deep learning-based imaging cytometry platform. Associations with survival, pathological response, and adjuvant chemotherapy (AC) were examined. Treatment-induced T-cell dynamics were assessed in paired pretreatment biopsies and post-NACRT resections (n = 9). Results: High stromal CD103+CD8+ density independently predicted better 5-year RFS (67.4% vs. 12.1%, p < 0.001) and OS (80.0% vs. 26.6%, p = 0.016); intratumoral density showed no prognostic significance. Pathological response correlated with stromal CD8+ but not CD103+CD8+ density. Paired analysis revealed a selective non-expansion of the CD103+ subset: stromal CD8+ T cells increased significantly after NACRT while CD103+CD8+ density remained unchanged. AC may preferentially benefit patients with low stromal CD103+CD8+ density. Conclusions: Stromal CD103+CD8+ T-cell density is a robust independent prognostic biomarker in rectal cancer after NACRT that appears to reflect pre-existing rather than treatment-induced immunity. Given its stability across NACRT, pretreatment biopsy assessment may provide equivalent prognostic information, with potential implications for patient stratification before treatment initiation.

Background: Non-invasive diagnosis, reliable recurrence surveillance remain critical unmet needs in gliomas. Glioma induces profound systemic immune alterations despite its anatomical confinement to the central nervous system. Circulating immune cells, particularly monocytes, are key mediators of tumor-host crosstalk and may retain tumor-induced transcriptional imprints. However, their potential clinical utility as blood-based biomarkers for detection and monitoring, remain largely unexplored. Methods and findings: In this study, we performed integrated single-cell RNA sequencing of blood immune cells and demonstrated that circulating CD14+ monocytes are significantly expanded in glioma patients, exhibiting features of differentiation arrest and increased transcriptional plasticity. These cells harbor glioma-specific molecular signatures distinct from those observed in healthy controls and patients with other tumors. Leveraging these findings, we developed an ensemble machine learning diagnostic model based on transcriptomic profiles of circulating CD14+ monocytes (training cohort, n=107), which achieved a mean area under the receiver operating characteristic curve (AUC) of 0.971 during cross-validation. In an independent cohort of 567 participants, the model maintained high diagnostic accuracy, yielding an AUC of 0.877 for distinguishing glioma from controls and other tumors. And it achieved a recurrence detection AUC of 0.969 in 51 postoperative samples. Moreover, in a prospective follow-up study involving 30 glioma patients, lower model-derived scores of postoperation were significantly associated with prolonged progression-free survival (log-rank test, P=0.043), supporting its prognostic utility. Conclusion: We demonstrate circulating CD14+ monocytes undergo glioma-specific transcriptional reprogramming, generating systemic tumor-associated signal captured via transcriptomic profiling. This blood-based diagnostic model provides non-invasive, scalable approach for glioma detection, recurrence surveillance, outcome prediction.

BackgroundMesothelioma (Me) is an aggressive cancer with limited response to conventional therapies. The tumors harsh microenvironment contributes to immune escape and therapy resistance and the effects of ICIs on Me are still unclear. Adenosine, an immunosuppressive molecule produced from AMP by the enzyme CD73, accumulates in hypoxic tumor areas. Elevated CD73 and adenosine receptor A2B (A2Br) levels on Me cells are linked to worse patient outcomes, indicating their important role in disease progression and potential as targets for treatment. AimThis study characterizes the Me-ME (micro environment) and evaluates the efficacy of TT-4 (A2B inibitor) and AB680 (CD73 inibitor), alone or with aPD-1, using 3D models in vitro and in vivo. MethodsCD73 and A2B receptor levels were quantified in tumor and normal samples using qRT-PCR and IHC. Cells lines were treated with CoCl2 to mimic hypoxia, then CD73, A2Br and related markers were analyzed. MSTO-211H and REN cells were silenced for CD73, grown as spheroids and adenosine release was measured. Co-culture spheroids of MSTO-211H and Jurkat cells were treated with AMP and CD73 inhibitor, then analyzed for viability and immune markers. An orthotopic Me model was established by injecting AB1-B/c-LUC cells and monitored by in vivo imaging. Proteomic analysis of spheroids was conducted to identify proteins and pathways involved. ResultsHypoxia boosts CD73 and A2Br expression in Me cells, leading to adenosine production via CD73. In 3D co-cultures, AB680 lowered Me cell viability and enhanced activation of Jurkat T cells. In mice, combining aPD-1 therapy with A2Br or CD73 inhibitors strongly reduced tumor growth. Proteomics identified 93 proteins influenced by adenosine signaling through A2B. ConclusionTargeting the adenosine pathway alongside PD-1 blockade offers a promising new immunotherapy strategy for Me.

Background: Immune-oncology has revolutionized cancer treatment, but some patients fail to benefit due to primary resistance and tumour-immune evasion. Extracellular vesicles (EVs) are secreted by both tumour and immune cells and mediate communication between cancer cells and the immune system. Our study used proteomic profiling of circulating EVs collected from NSCLC patients treated with immune checkpoint inhibitors (ICI) to identify predictive biomarkers of response as well as immune evasion mechanisms related to treatment resistance. Methods: EVs were isolated from plasma collected prior to ICI treatment using peptide-affinity purification and high-throughput proteomics was performed using Proximal Extension Assay. Differentially expressed EV proteins between durable (DR) and non-durable responders (NDR) were identified and evaluated using Cox proportional hazards regression, survival analysis, sex-stratified analysis, as well as pathway and network analysis. Results: Proteomics analysis identified 116 differentially expressed EV proteins between DR and NDR. NDR was characterized by enrichment of inflammatory, angiogenic, and immune-suppressive EV proteins, such as IL1RL1, TFRC, IL6ST, galectins, TNF superfamily death receptors, chemokines, and PCSK9. Pathway analysis revealed enrichment of angiogenesis, chemotaxis, ECM remodeling, and neutrophil degranulation associated with poor progression-free survival (PFS). In contrast, DR to ICI treatment was associated with EV proteins related to T- and B-cell activation and adaptive immunity. Sex-related differences in abundance and association with PFS was observed for certain EV proteins, including IL1RL1 and TFRC. A six protein EV model (IL1RL1, TFRC, ERI1, CCN5, IGFBPL1, and TNFRSF13C) demonstrated good prognostic performance for identifying NDR (AUC = 0.907) and stratified patients into three discrete risk groups. Conclusions: High-plex EV proteomics revealed biologically coherent tumour-immune signaling programs that are associated with ICI treatment resistance. Profiling circulating EVs may improve our understanding of EV-mediated immune evasion mechanisms and identify protein signatures that reflect the tumour immune microenvironment and predict response to immune checkpoint blockade.

Abstract Introduction: IL-15 is one of the most promising candidate cytokines in cancer immunotherapy due to its ability to promote the activity of different cytotoxic innate immune cell subsets such as NK, ILC1 and gammadelta T cells. During biosynthesis, IL-15 associates with IL-15alpha and is transported to the cell surface where IL-15Ralpha trans-presents IL-15 to target neighboring cells expressing the beta chain (IL-2Rbeta) and the common gamma chain. Our group previously showed that in autoimmune type 1 diabetes and early innate immune responses to infections trans-presentation by IL-15Ralpha is dispensable. Here we addressed the relative roles of IL-15 and trans-presented IL-15 in the control of established tumors and spontaneous tumor development. Methodology: Growth kinetics of tumor cell lines were monitored in WT, Il15-/- and Il15ra-/- mice. Spontaneous fibrosarcoma was induced with Methylcholanthrene (MCA) in WT, Il15-/- and Il15ra-/- mice. Cell lines were established from MCA-induced tumors to characterize their immunogenicity. Results: Growth of established tumor cell lines were comparable in the three genotypes. MCA-induced tumor incidence was reduced in Il15ra-/- mice when compared to WT and Il15-/- mice. In vitro, MCA tumor-derived cell lines expressed MHC-I and PD-L1 and had comparable proliferation rates. In vivo, MCA tumor-derived cell lines established from the 3 genotypes showed comparative growth in WT mice suggesting that IL-15 does not impact immunoediting. Nonetheless, NLRC5 expressing B16-F10 tumors were contained in WT and Il15ra-/- mice but not in Il15-/- mice. Conclusions: Taken together, these results show that in the absence of trans-presentation by IL-15Ralpha, IL-15 can better control spontaneous tumor development and that IL-15 signaling plays a minor role in immunosurveillance in this model. IL-15 signaling, independent of IL-15Ralpha has a significant role in the control of solid tumors.

Diffuse Large B-cell lymphoma (DLBCL) is the most common aggressive lymphoma in the Western world. First-line immunochemotherapy fails in approximately 30-40% of patients, with refractory and relapse patients presenting a dismal prognosis. Currently, these high-risk patients cannot be accurately identified at diagnosis. Using statistical modeling and machine learning approaches applied to large public DLBCL datasets, we identified a novel predictive signature based on the reactivation of eight normally silent tissue-dependent genes associated with survival. We then developed a multiplex RT-MLPseq based assay, compatible with formalin-fixed paraffin-embedded (FFPE) samples and transferable into routine clinical practice, enabling analysis of expression of these eight genes and validated their prognosis impact in an independent real-life cohort. This signature could be integrated with current prognostic indices and molecular classifications to improve patient stratification and guide treatment selection toward a personalized theragnostic approach, thereby enhancing management of non-responder patients. Data Sharing StatementFor access to original data, please contact: anouk.emadali@univ-grenoble-alpes.fr Key points- Ectopic activation of 8 tissue-specific genes defines a robust prognostic signature for survival stratification in DLBCL patients - A FFPE-compatible RT-MLPseq assay enables clinical use and improves risk stratification beyond IPI and COO, especially in high-risk patients

BackgroundGlioblastoma is an aggressive and incurable brain tumor. Clinical trials of immune checkpoint inhibitors showed no clinical benefit in glioblastoma when given after surgery. However, a clinical trial in which PD1 inhibition was given prior to second surgery did show pharmacodynamic evidence for activity. This suggests the possibility that immune checkpoint inhibitors may be more effective in a setting where large tumors are present. Here we have studied immune responses to large tumors in an autochthonous mouse model of glioblastoma. MethodsGlioblastoma was induced by transfection with oncogenic plasmids injected directly into the lateral ventricle of neonatal mice. Immune responses were assessed using a combination of spectral flow cytometry and immunohistochemistry. ResultsThere was a marked immune response to large tumors, with significant increases in CD4 T cells and dendritic cells. T cell changes occurred primarily at leptomeningeal/perivascular border sites. A large proportion of CD4 T cells expressed PD1 and half of these were regulatory T cells. NK cells were also increased in mice with large tumors, but were predominantly in immature states. The mouse model accurately recapitulates the formation of palisading necroses. These contain apoptotic cells and avidly recruit myeloid cells that are induced to express large amounts of TGF{beta}. ConclusionsLarge glioblastoma tumors generate a border site population of PD1 positive T cells that may explain the pharmacodynamic response in neoadjuvant trials, and a palisading necrosis-driven immunosuppressive mechanism that may explain why responses are insufficient to provide a significant clinical benefit. KEY POINTSThe SB mouse model accurately recapitulates immune features of human glioblastoma Large tumors induce a significant border site immune response Palisading necroses in large tumors counter this with a strong immunosuppressive response IMPORTANCE OF STUDYImmune checkpoint inhibitors have not shown efficacy in glioblastoma when used post-surgery, but do show pharmacodynamic activity when used in patients prior to second surgery (i.e. neoadjuvant). This suggest the possibility that immune checkpoint inhibition is more effective when large tumors are present. Using a clinically-relevant autochthonous mouse model, we show here that large tumors induce an immune response that is evident in leptomeningeal border sites. Large tumors in this mouse model also generate palisading necroses, a well-known diagnostic feature in glioblastoma tumors. These palisading necroses generate large amounts of TGF{beta}, providing a mechanism by which large tumors can suppress border site immune responses. This further supports the concept that palisading necroses are drivers of glioblastoma malignancy and suggests novel strategies to enhance responses to immune checkpoint inhibition in this cancer.