Journal of Experimental & Clinical Cancer Research

BackgroundTreatment optimization in HPV-associated oropharyngeal cancer (OPSCC) remains challenging, as recent de-escalation trials have shown limited success. Current patient selection strategies based on smoking history and TNM classification are insufficient, highlighting the need for robust, standardized prognostic biomarkers. We report the first validation of the Immunoscore (IS) for prognostic stratification in HPV-associated OPSCC. Patients and methodsWe analyzed 191 HPV-associated (p16+ and HPV DNA/RNA+) OPSCC patients from an international multicenter cohort (2015-2024), comprising a French monocentric retrospective training cohort (N = 48) and three validation cohorts: French monocentric retrospective (N = 48), French multicenter prospective (N = 50), and US multicenter retrospective (N = 45). IS is a standardized digital pathology assay quantifying CD3lJ and CD8lJ densities in tumor cores and invasive margins, with cut-offs defined in the training cohort and validated across cohorts. Associations with disease-free survival (DFS), time to recurrence (TTR) and overall survival (OS) were assessed, alongside 3RNA-seq and sequential immunofluorescence profiling of immune composition. ResultsMedian age 65; 80% male; 74% smokers; 66% T1-2; 82% N0-1 (AJCC8th). IS-High patients demonstrated superior 3-year DFS in the training and validation cohorts 1-3 (all log-rank P < 0.05). Multivariable analysis identified IS-Low as the strongest independent risk factor for DFS (HR 9.03; 95% CI: 4.02-20.31; P < 0.001). The model combining IS with clinical factors showed higher predictive accuracy for DFS (C-index 0.82) than clinical variables alone (0.7; P < 0.0001). Similar findings were observed for TTR and OS. IS-High tumors showed markedly higher enrichment of lymphoid and myeloid immune cell populations, contrasting with immune-poor signatures in IS-Low tumors. ConclusionsIS is a robust biomarker that outperforms standard clinical variables in both prognostic and predictive accuracy. The enriched cytotoxic immune infiltrate in IS-High tumors explains favorable outcomes and supports their suitability for treatment de-escalation. Prospective validation is warranted.

BackgroundCutaneous melanoma (CM) is an aggressive skin cancer with rising incidence, representing a growing public health concern. Despite the remarkable success of immune-checkpoint inhibitors (ICIs) in the management of advanced disease, mortality remains high due to therapy resistance. Identifying reliable prognostic and predictive biomarkers is therefore essential to improve patient stratification, optimize treatment selection, and minimize unnecessary toxicity. MethodsWe comprehensively profiled the circulating immune landscape of 54 treatment-naive CM patients by integrating flow cytometry immunophenotyping with clinicopathological data, and performed tumor gene expression analysis in a subset of 26 patients. ResultsElevated HLA-DR and CD69 expression on circulating CD4+ T cells, together with reduced circulating CD8+ T cell frequency, emerged as candidate prognostic biomarkers associated with improved survival. Prognostic models combining these immune variables with clinical covariates accurately stratified patients by overall survival (89.5% sensitivity, 72.7% specificity; AUC = 0.872, p < 0.0001) and progression/recurrence risk (75% sensitivity and 71.4% specificity; AUC = 0.763, p = 0.001). In a subset of 43 patients subsequently treated with ICIs, elevated baseline HLA-DR and CD69 expression on circulating CD4+ T cells was also associated with therapeutic benefit. A predictive model integrating these markers with clinical covariates achieved good discriminatory performance (65.2% sensitivity, 88.9% specificity; AUC = 0.775, p = 0.0027). Tumor gene expression profiling supported the role of IFN-{gamma}-related signatures, previously linked to ICI response, as complementary prognostic and predictive tools. ConclusionThese findings highlight systemic CD4+ T cell activation status as a promising, easily measurable biomarker in CM, laying the foundation for future strategies to refine patient stratification and guiding immunotherapy decisions.

Background: Prostate cancer (PCa) presents a formidable clinical paradox. It is immunologically cold and resistant to immune checkpoint blockade (ICB), yet bulk genomic analyses consistently reveal low and non-prognostic expression of CD274 (PD-L1), the primary molecular target of such therapies. We hypothesised that this paradox arises from a failure of current methodologies to account for two critical, interacting dimensions: the granular heterogeneity of basal gene expression (the static engine) and the spatiotemporal dynamics of adaptive resistance mediated by interferon-gamma (the adaptive engine). Methods: We developed a rigorous, multi-phase computational framework integrating clinical genomics with hybrid agent-based modelling. In Phase I, we extracted and normalized CD274 mRNA expression from the TCGA-PRAD cohort (n = 554) to define the empirical landscape of basal resistance. In Phase II, we developed a spatial Agent-Based Model (ABM) parameterized by this distribution to simulate clonal selection. In Phase III, we extended this into a Hybrid Discrete-Continuum model, coupling discrete agents with a reaction-diffusion Partial Differential Equation (PDE) representing the IFN-{gamma} field. We simulated 50 stochastic replicates per arm across four experimental arms, including Diffusion and Induction knockouts. Results: Bulk TCGA analysis confirmed low average PD-L1 expression (Median Transcripts Per Million (TPM) = 1.48; Interquartile Range (IQR): 0.91-2.14) with no prognostic value (Hazard Ratio (HR) = 1.15; 95% Confidence Interval (CI): 0.67-1.97; log-rank p = 0.605). However, the static ABM revealed that rare, high-expressing genomic outliers (>9.0 TPM) drive persistence through Darwinian immunoediting, enriching the surviving population's resistance by 3.86-fold. The hybrid adaptive model demonstrated a far superior survival strategy: the IFN-{gamma}/PD-L1 feedback loop facilitated the emergence of "protective sanctuaries"-localised regions of high resistance at the tumour-immune interface. This mechanism increased final tumour burden by ~4.5-fold compared to static selection alone (p<0.001). Spatiotemporal analysis confirmed that resistance is not a fixed trait but a dynamic state induced by immune pressure. Diffusion knockout (D = 0) abolished sanctuary formation, reducing final burden by 65% (p<0.001), while induction knockout (Pmax = 0) reverted to static outcomes. Conclusions: This study resolves the cold tumour paradox by demonstrating that PCa resistance is driven by a twin engine of rare genomic outliers and adaptive spatial dynamics. The failure of biomarkers in PCa is due to their inability to capture the dynamic mirage of adaptive sanctuaries. Our validated framework offers a platform for testing synchronised therapeutic disruptions targeting both the static genomic landscape and the dynamic cytokine signalling axis.

Cancer remains a major therapeutic challenge despite substantial advances in diagnosis and treatment, including immune checkpoint blockade. Among emerging immunotherapeutic approaches, adoptive cell transfer (ACT) has attracted growing interest. Human peripheral V{gamma}9V{delta}2 T cells are promising candidates for ACT because they combine rapid and potent antitumor functions with major histocompatibility complex (MHC)-independent tumor recognition, enabling allogeneic use with limited risk of graft-versus-host disease. This raises the possibility of generating standardized V{gamma}9V{delta}2 T-cell banks from healthy donors for off-the-shelf immunotherapy. Here, we provide preclinical evidence supporting the suitability of allogeneic human V{gamma}9V{delta}2 T cells for ACT. We characterized peripheral blood V{gamma}9V{delta}2 T cells from healthy donors after successive antigen-specific and non-specific amplification steps, assessing their phenotype, effector functions, and metabolic state. Amplified cells maintained a strong pro-inflammatory Th1-like profile, preserved cytotoxic activity, and did not produce immunoregulatory cytokines. They also displayed high purity, a predominant effector memory phenotype, reduced expression of several inhibitory immune checkpoints, and sustained antitumor reactivity. Altogether, these findings support the development of allogeneic V{gamma}9V{delta}2 T-cell products as a scalable platform for next-generation cancer immunotherapies.

Malignant peripheral nerve sheath tumours (MPNSTs) are high grade soft-tissue sarcomas with an unmet need for novel therapies. Tumour antigen-based approaches, including neoantigen and tumour-associated antigen (TAA) directed therapies, offer potential opportunities for immunotherapy. Here, we integrated public domain tumour DNA and RNA sequencing data with in-silico prediction to systematically characterise the (neo)antigenic landscape of MPNST. We stratified the predictions across the two known sub-groups of MPNST, those associated without and with Polycomb Repressor Complex 2 (PRC2) loss of function variants (PRC2-Loss). Using computational pipelines including pVACtools, we identified high-confidence neoantigens based on pMHC affinity derived from somatic mutations and gene fusions, as well as recurrently overexpressed cell-surface TAAs. All predicted neoantigens were private to individual MPNST cases, with different neoantigens across both tumour subtypes. PRC2-Loss tumours showed reduced immune infiltration with downregulation of antigen processing and presentation pathways compared to PRC2-WT, confirming intrinsic constraints to effective neoantigen-directed immune priming. Moreover, PRC2-Loss MPNSTs demonstrated recurrent copy number driven overexpression of cell surface TAAs (chromosome 8), providing alternative immunotherapeutic targets that are pMHC independent. These findings confirm a PRC2-independent private immuno-antigenic peptide repertoire with an immune resistant MPNST microenvironment in PRC-Loss. These data provide further impetus for rational development of complementary immune based treatment strategies, including personalised neoantigen vaccines and cell surface protein TAA-directed therapies dependent on PRC2 status.

BackgroundThe tumour microenvironment (TME) influences breast cancer progression and treatment response. We investigated whether TME composition predicts tamoxifen benefit in postmenopausal women with oestrogen receptor-positive, HER2-negative (ER+HER2-) breast cancer. MethodsThis study included 513 patients from the Stockholm Tamoxifen (STO-3) trial, which randomised postmenopausal, lymph node-negative women to tamoxifen or no endocrine therapy. Bulk tumour transcriptomes were deconvoluted with the ConsensusTME algorithm to estimate the relative abundance of 18 immune and stromal cell types. A summary score of combined immune cells was created on a per patient basis and evaluated alongside fibroblast and endothelial stromal compartments. Patients were categorised into immune and stromal tertiles on the basis of these scores. Associations between TME composition and tumour characteristics were evaluated using Spearman correlations and Fishers exact test. Tamoxifen benefit was analysed by univariable Kaplan-Meier (log-rank) and multivariable Cox proportional hazards adjusting for age, tumour size, grade, progesterone receptor, Ki-67, and radiotherapy. Differential expression was assessed with limma and pathway enrichment with fgsea using Hallmark gene sets from MSigDB. ResultsLow immune abundance was significantly associated with higher ER expression (Fishers exact test p < 0.001). Among tamoxifen-treated patients, those with low immune scores showed improved distant recurrence-free interval (DRFI) relative to untreated patients (log-rank p < 0.001). Similarly, intermediate endothelial (p < 0.001) and low/intermediate fibroblast abundances (p = 0.042, p = 0.009) were associated with favourable DRFI. In multivariable models, low immune (aHR = 0.17, 95% CI 0.08-0.40), intermediate endothelial (aHR = 0.21, 95% CI 0.09-0.51), and low/intermediate fibroblast tertiles (aHR = 0.50, 95% CI 0.27-0.93; aHR = 0.36, 95% CI 0.17-0.77) retained significance. Transcriptomic analysis revealed enrichment of oestrogen-response, MYC-target, and oxidative-phosphorylation pathways in low-immune and low-fibroblast tumours, while interferon-{gamma} response and allograft rejection pathways were downregulated. ConclusionsTME composition modulates tamoxifen benefit in postmenopausal ER+HER2-breast cancer. Low immune, intermediate endothelial, and low/intermediate fibroblast abundances are associated with improved benefit from tamoxifen, suggesting that both immune and stromal compartments influence endocrine treatment efficacy.

BackgroundInterferon-gamma (IFN-{gamma}) is the primary effector cytokine of adaptive anti-tumor immunity, yet it paradoxically induces a potent immunosuppressive tumor microenvironment (TME). The full mechanistic scope of this paradox in head and neck squamous cell carcinoma (HNSC) has not been characterized at the transcriptomic scale. MethodsUsing TCGA HNSC RNA-seq data (n = 522), we applied an integrated computational pipeline: Spearman correlation analysis, principal component analysis (PCA), UMAP, K-means clustering (k = 4), Random Forest regression, deep neural networks, permutation importance, JAK-STAT cascade mapping, and DNN-based transcriptome-wide mediation analysis across 57 IFN-{gamma} pathway and 78 immunosuppressive genes. ResultsIFN-{gamma} pathway activity was universally and positively correlated with six immunosuppressive axes, including checkpoints (CD274; LAG3; IDO1), Tregs, myeloid suppression, and tryptophan catabolism. K-means clustering identified four immunologically distinct tumor subgroups. DNN models predicted suppressive TME. Permutation importance identified IRF8 as the dominant mediator linking IFN-{gamma} signaling to immunosuppression. DNN mediation analysis identified PDCD1LG2 (PD-L2) as the strongest intermediary between IFNG and PD-L1 regulation, followed by JAK2 and GBP5. ConclusionsIFN-{gamma} orchestrates coordinated immunosuppression in HNSC through JAK-STAT-IRF8 signaling. PDCD1LG2 and JAK2 are actionable mediators of this paradox, supporting combination strategies co-targeting IFN-{gamma}-induced checkpoint induction and direct checkpoint blockade in HNSC immunotherapy. GRAPHICAL ABSTRACT

The RUNX1 transcription factor is a critical regulator of hematopoiesis and frequently mutated in myeloid malignancies. In the myeloproliferative neoplasm, chronic myeloid leukemia (CML), secondary somatic RUNX1 mutations and RUNX1::MECOM/EVI1, are associated with tyrosine kinase inhibitor (TKI) resistance and progression to the blast-phase (BP-CML). Research has predominantly focussed on transcriptional dysregulation mediated by RUNX1 mutations in myeloid malignancies, whilst post-transcriptional dysregulation remains comparatively unexplored. To address this, we used orthogonal organic phase separation (OOPS), to characterise the RNA-binding proteome of RUNX1 deficient BP-CML cells. RUNX1 depleted BP-CML cells exhibited significant alterations to RBP abundance involved in stress response pathways and translation/ribosome-biogenesis (RiBi). Furthermore, RUNX1 depletion or expression of RUNX1::EVI1 in BP-CML cells induced expression and RNA binding activity of SPATS2L, a component of stress granules (SG); membraneless cytoplasmic condensates protecting mRNAs from degradation, promoting survival under stress. Whilst RUNX1 depletion increased SG-assembly, SPATS2L depletion reduced SG-assembly in BP-CML cells and inhibited the growth and survival of multiple BP-CML cell lines. The translation inhibitor homoharringtonine (HHT), used historically in TKI-resistant CML, ablated SG-assembly in BP-CML cells with RUNX1 depletion, and, primary BP-CML cells with LOF/hypomorphic RUNX1 mutations (characterised by defective DNA-binding/CBF{beta}-interaction) were preferentially sensitised to HHT. Finally, suppressing SPATS2L expression induced by RUNX1 depletion, increased the HHT-sensitivity of RUNX1 depleted BP-CML cells, suggesting SPATS2L contributes to therapeutic resistance in CML with RUNX1 mutations. This study suggests that SPATS2L and SG induction could be critical to RUNX1-mutant leukemias, and, provides preliminary evidence for a mutationally-targeted approach in CML with RUNX1 aberrations.

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal cancer characterized by a high abundance of cancer-associated fibroblasts (CAFs), which influence therapy response, tumor biology and tumor aggressiveness. CAFs are a heterogeneous cell type and previous single-cell RNA sequencing (scRNAseq) of PDAC tumors identified three main CAF subtypes: myofibroblastic, inflammatory and antigen-presenting CAFs (myCAF, iCAF, apCAF, respectively). However, scRNAseq on large patient cohorts is often not feasible due to costs and technical constraints. Therefore, bulk RNAseq deconvolution can be used to identify cell types within the heterogeneous tumor microenvironment. Here, Statescope deconvolution was used to identify different cell types of the tumor microenvironment within an early onset PDAC cohort, comprising 74 patients aged under 60. Three CAF populations were identified (iCAFs, myCAFs and desmoplastic CAFs), and their correlations with tumor microenvironment components, mutational signatures and survival were examined. iCAFs were associated with classical-like tumor cells, whereas myCAFs and desmoplastic CAFs correlated with basal-like tumor cells. Desmoplastic CAFs are associated with inflammatory granulocytes/neutrophils, while negatively associating with monocyte-derived macrophages and immature/transitional B cells. No associations were observed between mutational signatures and the abundance of CAF and epithelial tumor subtypes. Interestingly, a high abundance of CAFs, and specifically increased iCAF abundance, was associated with improved survival. This iCAF-mediated survival effect was predominantly apparent in female patients. All in all, deconvolution of bulk RNA sequencing data, followed by its integration with clinical and biological parameters, reveals the heterogeneity and prognostic implications of CAF subpopulations in the tumor microenvironment of early onset PDAC patients.

Macrophages/osteoclasts are highly fusogenic cells that interact closely with bone-metastatic breast cancer cells. These cancer cells adapt to bone microenvironments by undergoing osteomimicry, acquiring bone-like phenotypes. Exploration using human breast cancer-bone metastases dataset revealed that a small population of epithelial breast cancer cells express osteoclast-like and osteomimicry genes at the single-cell level. Cell fusion and cell-in-cell (CIC) processes are two uncommon yet prognostically significant mechanisms in cancer. We showed that co-culture between murine breast cancer cells and osteoclasts yielded a unique osteoclast phenotype through dynamic cell-in-cell (CIC) interactions and fusion-like behaviours between pre-osteoclasts/mature osteoclasts and breast tumor cells, resulting in osteoclast-tumor hybrid-like cells. These tumor cell interactions characterized by membrane retention and nuclear adjacency to host nuclei were consistently observed throughout osteoclast differentiation. Single-cell sequencing analysis and interpretative assays on hybrid-like cells revealed altered extracellular matrix (ECM) modification processes, immunoregulatory, and cancer-associated pathways compared to unfused osteoclasts. Tumor cells co-cultured with osteoclasts expressed hematopoietic and osteoclast-lineage factors more strongly than tumor cells cultured alone with their effects amplified under direct cell-cell contact. The presence of these hybrid-like cells was validated in human breast cancer-bone metastases. We propose that disseminated bone-tropic breast cancer cells were stimulated by osteoclasts to undergo a non-canonical, dynamic osteoclast differentiation and CIC formation to form hybrid-like cells that may facilitate bone metastatic lesions.

Abstract Background Tumour hypoxia is a major determinant of treatment resistance and poor prognosis in cervical cancer but remains difficult to assess in clinical practice. Gene expression signatures offer a potential means to characterise hypoxia-related biology. This study aimed to develop and validate a hypoxia-associated gene expression signature for cervical cancer. Methods RNA sequencing was performed on five cervical cancer cell lines exposed to normoxia (21% O?) and hypoxia (1% O?). Differentially expressed genes were mapped to The Cancer Genome Atlas cervical cancer cohort (TCGA-CESC) to train a 55-gene hypoxia classifier using k-means clustering and Prediction Analysis for Microarrays. The model was validated in an institutional Manchester cohort (n=153) and two public datasets from Seoul (n=300) and Oslo (n=283). Results The Manchester 55-gene signature was enriched for canonical hypoxia pathways. In the Manchester cohort, hypoxia classification correlated with advanced FIGO stage, nodal involvement, tumour size ? 4 cm, and hydronephrosis (adjusted p<0.05). Hypoxic tumours showed reduced overall survival (OS) and progression-free survival (PFS) in all cohorts. In multivariable models, the signature remained independently prognostic for OS in both TCGA (HR 1.70, 95% CI 1.10-2.60, p=0.012) and Manchester (HR 1.95, 95% CI 1.08-3.51, p=0.026). A direct comparison with a published 6-gene hypoxia signature in the Oslo cohort demonstrated 71% concordance in classification. Conclusions Our 55-gene signature should be tested prospectively in trials to assess its ability to stratify patients for hypoxia-targeted therapies.

Reliable, minimally invasive biomarkers for predicting immunotherapy response in head and neck squamous cell carcinoma (HNSCC) remain an unmet clinical need. Here, using patients from a prospective, multi-institutional phase II clinical trial (NCT02641093), we performed whole genome sequencing of 185 plasma cell-free DNA (cfDNA) samples collected longitudinally from 68 patients with locally advanced, surgically resectable HNSCC undergoing neoadjuvant and adjuvant pembrolizumab treatment. We developed the regional motif diversity score (rMDS), a novel fragmentomic metric quantifying the entropy of cfDNA 5' end motifs across genomic regions. Remarkably, unsupervised analysis revealed that rMDS robustly distinguished immunotherapy responders from non-responders, outperforming established cfDNA fragmentomic metrics and copy number alterations, while demonstrating independence from technical confounders. Longitudinal analysis revealed dynamic rMDS changes in genomic regions enriched for immune, lectin, and keratinization-related genes, hallmarks of squamous cell carcinoma, reflecting the interplay between tumor and peripheral immunity during the immunotherapy treatment. Interestingly, the regions with the most dynamic rMDS changes were highly enriched in telomere proximal loci, suggesting a novel link between telomere biology and cfDNA fragmentation. A machine learning classifier based on rMDS achieved robust predictive performance across multiple validation settings (AUC 0.89-0.99), with the highest accuracy at post-treatment timepoints and superior to PD-L1 expression and tumor fraction in the same sample. Predicted responders demonstrated significant trends toward improved disease-free survival (log rank test p=0.035, hazard ratio: 2.67, 95% confidence interval: 1.03-6.92), underscoring the clinical utility of rMDS-based stratification. These findings position rMDS as a biologically meaningful and clinically actionable biomarker for immunotherapy response in HNSCC, supporting its integration into future risk assessment frameworks and broader cancer care.

BackgroundNeoadjuvant chemoimmunotherapy (nCIT) has become a standard treatment for locally advanced resectable non-small cell lung cancer (NSCLC), yet the spatial biology underlying treatment resistance remains poorly understood. We used spatial transcriptomics to define the microenvironmental architecture of residual cancers in patients who did not achieve major pathologic response (non-MPR) compared with those who did (MPR). MethodsSpatial transcriptomics was performed on 10 formalin-fixed paraffin-embedded (FFPE) tumor blocks (5 MPR, 5 non-MPR) obtained from 8 patients treated with nCIT. A deep learning algorithm was applied to detect viable residual cancer spots from treatment-induced fibrosis and necrosis. Spatial deconvolution, distance modeling, ligand-receptor analysis, and functional pathway scoring were integrated to characterize niche-specific programs. ResultsMPR cancer core displayed an immune-permissive remodeling environment with deep infiltration of cytotoxic CD8+ T cells, mature dendritic cells (LAMP3+, CCR7+), and active efferocytosis signaling (APOE-TREM2), alongside robust MHC class II expression. Non-MPR cancer core, by contrast, exhibited spatial immune exclusion: a dense fibroblast barrier reinforced by TIMP1-CD63 signaling and Treg-enriched boundaries physically restricted effector T cell access to the cancer core. Residual cancer cells in non-MPR samples maintained active cell cycling and independently upregulated cytochrome P450-mediated drug detoxification and DNA damage response pathways without inducing MHC class II expression -- effectively decoupling intrinsic survival from immune recognition. The non-MPR core also showed a hyper-metabolic profile, including elevated glutathione metabolism consistent with antioxidant buffering against chemotherapy-induced oxidative stress. TROP2 was broadly expressed across the non-MPR cancer core and co-localized with DNA damage response and nuclear factor erythroid 2-related factor 2 resistance signatures. ConclusionsResidual cancer cores in non-MPR tumors appear to represent evolved resistant niches sustained by structural immune exclusion, metabolic rewiring, and DNA repair proficiency. These findings highlight the spatial co-localization of epithelial anchors, such as TROP2, with intrinsic resistance pathways, providing a structural rationale for developing novel precision therapeutic strategies to bypass stromal barriers and overcome the cancer cores intrinsic repair capacity.

Osteosarcoma is a malignant bone tumor with a high risk of metastatic relapse and poor outcomes due to primary and acquired chemoresistance. This highlights the medical need to develop effective targeted approaches to overcome chemoresistance. Recent studies have revealed the roles of metabolic reprogramming and mitochondria-nucleus crosstalk in osteosarcoma progression, indicating the potential of these cellular processes as therapeutic targets. The complex formed by mitochondrial apoptosis-inducing factor (AIF) and coiled-coil-helix-coiled-coil-helix domain-containing protein 4 (CHCHD4) orchestrates the import and oxidative folding of cysteine-rich, nuclear-encoded proteins, thereby regulating key mitochondrial functions and metabolism. Here, we identified mitoxantrone as an inhibitor of the AIF/CHCHD4 mitochondrial import machinery and revealed a new mitoxantrone-induced metabolic vulnerability in some osteosarcoma cell line models, characterized by intracellular glutamine accumulation and an increase in nucleotide synthesis. As a result, synergy was found between mitoxantrone and the glutaminase inhibitor telaglenastat in both in vitro and in vivo osteosarcoma models. Collectively, our findings position the AIF/CHCHD4 complex as a druggable therapeutic target and provide a combination strategy for mitoxantrone/telaglenastat treatment to overcome metabolic adaptations and chemoresistance in osteosarcoma. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=126 SRC="FIGDIR/small/716303v1_ufig1.gif" ALT="Figure 1"> View larger version (22K): org.highwire.dtl.DTLVardef@1229e58org.highwire.dtl.DTLVardef@1c9af45org.highwire.dtl.DTLVardef@120d2borg.highwire.dtl.DTLVardef@11e8216_HPS_FORMAT_FIGEXP M_FIG C_FIG

T cell development in the thymus is a tightly regulated process where epigenetic modifications, such as histone 3 lysine 27 acetylation (H3K27ac), play a crucial role in controlling the activation of genes. The epigenetic regulation of human mucosal-associated invariant T (MAIT) cell development is unknown; we mapped the regulatory chromatin landscape in the three developmental stages of thymic MAIT cells to identify the regulatory elements and enhancer activity involved in thymic maturation and analysed whether these chromatin dynamics are associated with the acquisition of effector programs in developing MAIT cells. Utilising cleavage under target and tagmentation (CUT&Tag), genome-wide H3K27ac profiles were generated and combined with transcriptome data from thymic MAIT cells, which revealed how developmental shifts in enhancer activity correspond to changes in gene expression. In total, 41,958 genomic regions with H3K27ac signal were identified in MAIT cells across the three development stages, of which 1,200 regions showed acetylation changes during differentiation from stage 1 to stage 3. At dynamic regions, the greatest differences were observed between stage 1 and stage 3, highlighting a progressive gain or loss of H3K27ac during MAIT cell development. Overall, MAIT cell maturation was associated with the gradual accumulation of H3K27ac at promoters and enhancers, which closely correlated with gene expression changes during development. Stage-specific enrichment of H3K27ac was observed at key transcription factor gene loci involved in MAIT cell development, including ZBTB16 (PLZF), EOMES, RUNX3, NFATC2, FOXO1, TGIF1, IRF1, and MAF genes. Epigenetic remodelling was also observed at cytokine and cytokine receptors (IL7R, IL18R1, IL23R, IFNG), chemokines and chemokine receptors (CCL4, CCL5, CCR5, CCR9, CXCR4, CXCR6), as well as several surface molecules with known immunological function. Our work reveals a previously uncharacterised epigenetic profile of human MAIT cells that regulates and inuences their development.

BackgroundLong non-coding RNAs (lncRNAs) have emerged as key regulators of tumor biology, however, thus far none have translated to cancer therapies. The lncRNA MALAT1 is overexpressed in more than 20 cancers, including breast cancer and has been shown to function via various mechanisms in a context-dependent manner, in 2D cell lines and mouse models. However, its functional role and therapeutic potential have not been evaluated in clinically relevant patient-derived models. MethodsWe investigated the therapeutic potential of a MALAT1-targeting antisense oligonucleotide (ASO) for breast cancer, using clinically relevant 3D human patient-derived organoids (PDOs) and PDO-xenograft (PDO-X) models. We systematically evaluated the efficiency of MALAT1-targeting ASOs using a biobank of 28 PDO models. Using three independent PDO-X models of triple negative breast cancer (TNBC), we targeted MALAT1 in vivo to study its impact on transcription, alternative splicing, stromal remodeling and metastasis. ResultsAcross PDO-X models, MALAT1 depletion reproducibly drove widespread alternative splicing changes across all event types, particularly intron retention events, accompanied by modest gene expression alterations. Differentially spliced transcripts were enriched for targets of shared cancer-associated transcription factors, and MALAT1 knockdown altered the relative abundance of previously unannotated splicing isoforms. Beyond tumor-intrinsic effects, tumor-specific MALAT1 depletion induced a consistent reduction in macrophage-associated gene signatures and reduced lung metastatic burden. ConclusionsOur data define MALAT1s multifaceted role in TNBC, coordinating alternative splicing, transcriptional fine-tuning, tumor-stroma crosstalk, and metastatic progression. Our study provides strong preclinical evidence supporting MALAT1-targeted ASO therapy and establishes PDO-X models as a clinically relevant platform for functional interrogation of TNBC therapies.

The PBAF is one of three biochemically distinct BAF chromatin remodelers in humans. We previously proposed the role of ARID2, a PBAF component, as a bonafide tumor suppressor in colorectal cancer (CRC). Here, we validated loss of tumor suppression under conditions of ARID2 deficiency emanating from a marked reduction in PBAF complex assembly resulting from destabilization of PBAF-specific components BRD7, PHF10, and PBRM1. Transcriptome profiling of ARID2 deficient CRC cells revealed perturbation of disease processes, including CRC and neurodegenerative disorders, as well as CRC relevant pathways including Wnt/{beta}-catenin signalling, but transcript levels of PBAF-specific components remained unchanged, confirmed by RT-qPCR and TCGA data analysis. Our study establishes ARID2 as a critical stabilizer of the PBAF complex of relevance to CRC.

Lymph nodes (LN) are key secondary lymphoid organs (SLO) for a coordinated immune response. They have been extensively characterized by numerous investigative techniques chiefly as single cell suspensions because they are composed of vagile yet crowded hematolymphoid elements, unfriendly to spatial tissue organization-saving techniques. We comprehensively classify in situ all cells of 19 human LN free of pathology with a 78-marker antibody panel, an hyperplexed cyclic staining method, MILAN, and an analytical bioinformatic pipeline, BRAQUE. A total of 77 cell types were classified, encompassing T, B, innate immune and stromal cells. CD4 and CD8 T-cells were classified into 27 unique subsets by leveraging the expression profiles of TCF7, the presence of co-inhibitory receptors and the spatial distribution. CD5 and TCF7 expression defined novel B-cell types. CD27+ mature B-cells occupied previously unrecognized nodal spaces non-overlapping with the cortex and the plasma-cell rich medullary cords. Type 2 conventional dendritic cells were located in nodular paracortical aggregates. Statistically controlled pairwise neighborhood analysis showed sparse cell-cell interactions, known and new neighbors, established and novel LN landscape niches. A high-dimensional proteomic interrogation of the normal human LN provides spatial allocation of known cell types, novel interactions and the landscape organization.

Regional lymph node (LN) metastasis critically influences distant metastatic progression, anti-tumour immunity, and patient prognosis. While tumour-induced immune modulation in tumour-draining LNs (TDLNs) has been extensively studied using murine models, the systematic reconstruction of the immune system from primary tumours through TDLNs and subsequent lymph nodes in human cancer progression remains understudied. Here, we utilised integrated multi-omics approaches, including imaging mass cytometry, single-cell RNA sequencing, Visium and Xenium spatial transcriptomics, and multi-colour immunofluorescence to systematically characterise immune cell dynamics across 147 paired primary tumours, sentinel TDLNs (S-TDLNs), and secondary axillary LNs (ALNs) obtained from 50 treatment-naive triple-negative breast cancer patients with different progression statuses. Our comprehensive profiling revealed critical immune alterations, such as decreased type-2 conventional dendritic cells (cDC2), naive T cells, and B cells, along with an increase in immunosuppressive macrophages. Developing a novel single-cell transformer model, we identified substantial alterations in various immune cell populations, notably MARCO+ macrophages, which strongly correlated with breast cancer patient survival outcomes. Spatial analysis combined with our newly integrated cell-cell interaction platform revealed diminished immune cell communication and impaired priming interactions among dendritic cells, B cells, and T cells within metastatic lymph nodes and primary tumour sites. In an independent neoadjuvant immunotherapy cohort of 36 TNBC patients with 52 lymph node samples, we found preservation of CD1c cDC2 in lymph nodes predicted pathological complete response and longer event-free survival, highlighting cDC2 as a potential biomarker and therapeutic target. Collectively, this systematic mapping of immune landscape alterations during human sequential LN metastasis provides essential insights for understanding cancer metastasis mechanisms and paves the way for innovative immunotherapeutic strategies.

The vast diversity of B and T cell receptors generated through the recombination of Variable (V), Diversity (D), and Joining (J) gene segments plays a critical role in adaptive immunity. Profiling immune repertoires at the DNA level provides a robust and stable approach to capture the clonal composition of these receptors. immunoPETE is an assay designed to target recombined human T-cell Receptor Beta (TRB), T-cell Receptor Delta (TRD), and Immunoglobulin Heavy (IGH) chain genes directly from genomic DNA. Simultaneous profiling of B and T cell receptor chains in a single reaction provides internally normalized clone counts and facilitates the study of B-T cell interactions. Full-length amplicon consensus sequences representative of original template DNA molecules are accurately reconstructed using Unique Molecular Identifiers (UMIs). An in-house pipeline compiles VDJ rearrangements from the Complementarity-Determining Region 3 (CDR3) of TRB, TRD and IGH chains into comprehensive readouts at cell-level resolution. In this study, we describe the immunoPETE end-to-end workflow, followed by a comprehensive benchmarking of its performance in adaptive immune profiling. Where applicable, we used both natural and contrived samples and characterized the assays accuracy, linearity, and reproducibility across several metrics: retrieving CDR3 sequences, determining B and T cell ratios, total cell count, yield, fraction of functional rearrangements, clonal diversity, composition of dominant clones, pairwise similarity, and V/J gene usage frequencies. Furthermore, we assessed its quantitative limits concerning the total number of lymphocytes and the detection of rare clones. As an example of its applications, we show that adding immune biomarkers extracted from immunoPETE data to clinical factors improves prediction of progression-free survival in a cohort of non-muscle invasive bladder cancer (NMIBC) patients. Finally, we discuss the broad applications of immunoPETE in the study of aging, cancers, infections, and autoimmune disorders with reference to select published studies.