Cancer Cell

GD2-CAR T cell therapy has demonstrated clinical benefit in patients with H3K27M+ diffuse midline glioma (DMG), but the durability of response has been limited in many patients1,2. To identify mechanisms of therapeutic resistance, we conducted longitudinal single-cell RNA and TCR sequencing of cerebrospinal fluid (CSF) lymphocytes from DMG patients receiving intravenous followed by sequential intracerebral GD2-CAR therapy, with lymphodepleting chemotherapy administered once prior to the start of CAR T cell therapy (NCT04196413). CSF GD2-CAR T cells manifested limited persistence and clonal expansion, while non-engineered CSF lymphocytes underwent significant clonal expansion and repertoire stabilization, ultimately dominating the CSF immune compartment. Concurrently, peripheral blood CD4+ and CD8+ T cells manifested anti-CAR immune reactivity targeting epitopes enriched within murine-derived and engineered junctional regions of the CAR construct. This was associated with appearance of circulating Human Anti-CAR Antibodies (HACAs) that bound cells expressing the GD2-CAR, as well as clonal expansion of CSF B cells which produced HACA which impeded the cytotoxic activity of GD2-CAR T cells. In several cases, appearance of circulating HACA temporally correlated with disease progression and across the patient population, and levels of circulating HACA inversely correlated with circulating CAR T cell persistence. These findings reveal robust induction of systemic and CNS adaptive T cell and B cell responses to GD2-CAR T cells following intravenous then sequential intracerebroventricular GD2-CAR therapy and provide strong evidence that anti-CAR immunity is a significant contributor to therapeutic resistance in this setting.

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.

Advancements in immunogenomics and immuno-oncology have enabled the development of personalized cancer vaccines (PCVs) that target cancer cell-specific somatic variants. A subset of these variants produce neoantigens that, when presented on tumor cells by MHC molecules, have the potential to elicit a robust and specific immune response. To date, there are over one hundred interventional studies listed on clinicaltrials.gov that explore the use of PCVs. We have supported a number of these trials through the creation of bioinformatic pipelines, tools, and procedures for the identification of patient-specific neoantigen candidates. While many of these steps have been automated, the final selection of neoantigen candidates often relies on expert manual review, creating a bottleneck that limits scalability and full automation of PCV workflows. Addressing this challenge, we introduce NEAT (Neoantigen Evaluation & Automated Triage), a machine learning-based approach that enables automated neoantigen candidate prioritization and supports the transition toward more scalable and reproducible PCV design. We implemented a prediction model trained and tested on existing vaccine design results from 33 patients and 1,943 peptides, across 3 clinical trials, including 439 peptides prioritized for PCV inclusion. This model uses features such as tumor variant allele frequency, RNA expression, driver gene status, binding/presentation scores, and transcript support level to automatically predict whether a peptide will be accepted, rejected, or require further human review before inclusion in a vaccine. The model achieved a sensitivity of 0.847 and specificity of 0.924, with an area under the curve of 0.955. The model predictions have been incorporated in pVACtools version 7. By integrating this model into the vaccine development pipeline, we foresee a significant reduction in the time required to transition from patient sample collection to vaccine manufacturing, thereby enhancing the efficiency and scalability of PCV production.

BackgroundGlioblastoma (GBM) invasion is clinically decisive but difficult to model systematically. Existing patient-derived xenograft (PDX) resources rarely couple reproducible in vivo invasion phenotypes with matched multi-omic profiles at scale, limiting mechanistic insight and phenotype-informed therapeutic hypotheses. MethodsWe established the HGCC Phenobank, comprising 65 patient-derived GBM stem-like cultures with matched multi-omic profiling and orthotopic engraftment in 449 mice. Blinded histopathology quantified ten invasion traits per case. These phenotypes were integrated with RNA sequencing, DNA methylation, and mass-spectrometry-based proteomics. Multi-Omic Factor Analysis (MOFA) identified latent molecular programs. Phenotype-specific RNA signatures were matched to LINCS drug-perturbation profiles and validated in 3D gliomasphere and ex vivo brain-slice assays. ResultsTwo dominant, reproducible invasion modes emerged across models: diffuse parenchymal infiltration and perivascular/condensed growth. Proneural cultures formed more aggressive tumors in immunodeficient mice, and mouse survival showed a modest correlation with patient survival in matched cases (Pearson r = 0.1832, p = 0.045). MOFA identified 15 latent factors; Factor 1, enriched for ASCL1/OLIG1/OLIG2 programs and associated with TP53/DCHS2/WNK2 alterations, was linked to increased tumor formation, diffuse invasion, and shorter mouse survival, and stratified GBM patients in TCGA and in our matched patient cohort. Drug-signature matching separated mechanisms targeting diffuse versus perivascular invasion. Experimental validation confirmed phenotype-selective sensitivities, and inhibitors PIK-75 and buparlisib suppressed invasion dynamics across representative models in 3D and brain-slice assays. ConclusionsThe HGCC Phenobank provides the first openly available PDX resource that systematically links GBM invasion phenotypes to multi-omic programs and therapeutic predictions. This framework enables reproducible model selection, mechanistic dissection of invasion modes, and phenotype-guided therapeutic discovery. Key PointsO_LIDiffuse and perivascular invasion define orthogonal GBM axes C_LIO_LIASCL1/OLIG factor links initiation, diffuse growth, and survival C_LIO_LIPhenotype-matched drugs validated; PIK-75 and buparlisib curb invasion dynamics C_LI Importance of the StudyGlioblastoma invasion varies substantially between patients, yet existing patient-derived xeno-graft resources rarely combine reproducible in vivo phenotyping with matched multi-omic profiling at scale. The HGCC Phenobank addresses this gap with standardized, blinded scoring of ten invasion traits across 449 orthotopic xenografts from 65 molecularly characterized GBM stem-like cultures, integrated with transcriptomic, methylomic, and proteomic data. We identify two dominant, reproducible invasion modes and a cross-modal neurodevelopmental program, the ASCL1/OLIG1/2-associated Factor 1, that links tumor initiation, diffuse growth, and survival in mice, and stratifies GBM patients in TCGA and in our matched patient cohort. In a spatially resolved xenograft section, Factor 1 signal localizes to the invasive tumor periphery. By matching phenotype-specific RNA signatures to drug-induced transcriptional responses, we show that invasion phenotypes nominate selective vulnerabilities, exemplified by PIK-75. This openly shared resource enables reproducible model selection, mechanistic dissection of invasion programs, and phenotype-guided therapeutic discovery.

Hypermutational processes, including those driven by the APOBEC3 family of cytidine deaminases, generate abundant neoantigens yet give rise to tumors that evade immune recognition. Here, using multi-omics analyses followed by functional validation, we identified a tumor-intrinsic immune-cloaking mechanism in neoantigen-rich epithelial cancers, characterized by coordinated suppression of antigen presentation, immune-recruiting cytokines and immune-checkpoint programs. In bladder cancer, genome-wide copy-number analysis identified recurrent 1q23.3 amplification as a genomic feature of a neoantigen-high/CD8-low tumor state. Within this locus, NECTIN4 emerged as the dominant candidate effector, outperforming extrachromosomal DNA status as a predictor of immune-neoantigen discordance. Similar associations were observed across breast and lung cancers. Functional studies demonstrated that NECTIN4 was sufficient to establish a T-cell-poor tumor microenvironment and confer resistance to PD-1 blockade in immunocompetent mice. Mechanistically, NECTIN4 engaged a DDR1-SHP2 axis that suppressed STAT1 phosphorylation, silencing tumor-cell immune-engagement programs. NECTIN4 blockade restored STAT1 activity and reduced tumor growth, indicating that the cloaked state is pharmacologically reversible. Mutational signature, breakpoint motif, timing and clonality analyses, together with APOBEC3B expression and germline genetic evidence, linked APOBEC3-mediated mutagenesis to recurrent 1q23.3 amplification encompassing NECTIN4. These findings reveal how neoantigen-generating mutational processes can be coupled to structural genome evolution to enable tumor-intrinsic immune cloaking through a therapeutically targetable NECTIN4-DDR1-SHP2 axis.

Somatic copy-number amplification is pervasive in cancer, and the genes it carries are candidate drug targets - but only those whose amplification is transmitted to accessible surface protein can be reached by an antibody-drug conjugate (ADC). We build an integrated map of copy-number-to-protein transmission across six tumour types and ask, for every amplified gene, whether its dosage reaches the surface. Copy number transmits to mRNA (median per-gene r = 0.21) but is attenuated at the protein level in 85% of genes, and the mRNA ranking is largely preserved to protein (rho = 0.70); the ranking is set principally at the chromatin/transcription step - among directly measured regulatory inputs, promoter DNA methylation and tumour chromatin accessibility each explain about an order of magnitude more of the transmission variance than gene structure, and do so complementarily. Critically, transmissibility is a stable, gene-intrinsic property: it is predictable from gene properties alone, with no proteomic input, at a leave-gene-out rank correlation of 0.52 (R2 = 0.29); it is not positional (holding out whole chromosome arms changes accuracy by 0.001); and it transfers across lineages (Kendall W = 0.97 across leave-one-lineage-out refits). This licenses a predictor that nominates surface targets in cancer types that lack a tissue-referenced proteome, combining direct protein measurement where it is available with prediction where it is not. Requiring co-elevation on a recurrent amplicon with measured transmissibility and an accessible extracellular ectodomain nominates 22 surface antigens on 18 distinct recurrent amplicons across four cancer types (renal, endometrial and both lung subtypes) - for example ITGB8+TSPAN13+TTYH3 on lung 7p, NCSTN+HSD17B7+MPZL1 on 1q (recurrent in several types), the transferrin receptor TFRC on squamous 3q, and FZD1 on clear-cell renal 7q; 21 of the 22 are non-driver passengers and 10 are confirmed on the experimental Cell Surface Protein Atlas. In single malignant cells, against a null that controls for per-cell sequencing depth, the co-detected constructs sit at a modest 1.05-1.45x above independence (p < 0.001, donor-block bootstrap intervals clear of 1.0), and at binding-relevant thresholds the normal-tissue co-expression collapses - so an avidity AND-gate that binds stably only where the antigens co-occur would spare normal cells that carry only one. Observed transmissibility itself transfers strongly between the two lung subtypes ({rho} = 0.88) and remains positive across distant lineages, consistent with the shared cell-of-origin regulation the map implies. Single-cell co-detection is demonstrated wherever a malignant single-cell atlas exists (both lung subtypes and glioblastoma - the latter entirely from prediction, using no GBM surface-abundance measurement); the remaining cohorts are nominated on the same genetic and topological evidence. The result is a pan-cancer, confidence-tiered catalogue of multi-antigen ADC co-target sets with a concrete plan to test them.

Mucosal cannabidiol formulations are known regulators of the glioblastoma microenvironment, yet the underlying origin point triggering this stroma-remodeling efficacy remains entirely unknown. Here, by mapping innate cell trafficking pathways, we define a novel baseline neuro-immune-microbiome axis in orthotopic glioblastoma, characterized by diverse microbial communities, likely seeded via blood-brain barrier disruption, paired with dense infiltration of host mast cells and mature, crystalloid-containing eosinophils. Localized intranasal administration of a synthetic cannabidiol formulation achieved striking therapeutic efficacy, driving dramatic tumor regression. Mechanistically, high-throughput 16S rRNA sequencing and quantitative flow cytometry revealed this progression was subverted by taming the tumor ecosystem; cannabidiol restricted chaotic microbial diversity, selectively filtering the landscape toward Delftia and depleting Archaea, while simultaneously suppressing hyper-inflammatory host mast cell and eosinophil populations. This study builds upon established innate trafficking frameworks to present the first therapeutically targetable stromal-microbial axis in neuro-oncology.

Small cell lung cancer (SCLC) is a highly aggressive malignancy with limited therapeutic advances. Unlike many other cancers, its immune landscape, particularly immune competence and T cell recognition, remains poorly characterized. Here, we generate a single-cell transcriptome atlas of the SCLC immune microenvironment with paired T cell receptor (TCR) sequencing. By linking T cell states with clonality and a multilayered functional screening, we identify 6 tumor-reactive TCRs that recognize and eradicate autologous SCLC cell lines. We delineate a novel SCLC-reactive CD8+ T cell signature (SCLC_TR), enabling the identification of 47 further SCLC-reactive TCRs. The SCLC_TR signature performs extremely well in pancreatic ductal adenocarcinoma (PDAC), another immune-cold tumor indication, and, most strikingly, patients with elevated SCLC_TR signature scores exhibited significantly improved survival, underlining its prognostic potential. Comparative cell-cell interaction analyses implicate several immunosuppressive mechanisms, with myeloid cells and CD4+ regulatory T cells possibly acting as counterbalances to effector T cell activity in SCLC. In summary, our study challenges the prevailing notion of SCLC as an immune-cold tumor type by providing direct evidence of tumor-reactive T cell responses and introduces the SCLC_TR signature as a tool to identify tumor-specific T cells and their microenvironmental restraints and escape mechanisms, ultimately shaping next-generation immunotherapeutic strategies.

Gastric cancer is the fifth leading cause of cancer-related mortality in humans globally and remains a clinical challenge with limited treatment options and poor survival. Dogs develop spontaneous gastric cancer that parallels the clinical presentation and histology of human disease, supporting their value as a comparative oncology model. Here we present a comprehensive transcriptomic characterization of canine gastric cancer through single-nucleus RNA-sequencing, bulk RNA-sequencing, and Visium HD 3' spatial transcriptomics of treatment-naive tumor and normal stomach tissues from Belgian Tervuren and Belgian Sheepdogs. Across 107,085 nuclei, we identified 44 distinct cell populations, including tumor-enriched states as well as profound depletion of the normal parietal and chief cell gastric lineages. Cell-cell communication analysis revealed enhanced epithelial-fibroblast crosstalk driving epithelial-mesenchymal transition. Bulk RNA-sequencing further identified enrichment of signaling pathways implicated in H. pylori associated human gastric carcinogenesis, including Hippo, PI3K-Akt, and Wnt. Notably, we observed cell-type-specific altered expression of KLHL29, PDZRN3, and PLAU, which are among our previously identified canine gastric cancer susceptibility genes, linking germline risk to specific tumor cellular contexts. These data establish the first transcriptomic atlas of canine gastric cancer and demonstrate substantial molecular homology between canine and human disease.

BackgroundSingle-cell atlases have described diverse stem cell states in colorectal cancer (CRC), however, the overarching trajectories of those states and the underlying functional mechanisms, including their relevance for drug sensitivity, need better understanding. MethodsWe established 64 patient-derived organoids from microsatellite-stable colorectal cancers, characterized their transcriptomes and genomes, and performed drug screening with 62-140 clinically approved substances. We analyzed additional published transcriptome data from patient-derived organoids (72 patients from three independent datasets), TCGA-CRC data (466 patients), and single-cell transcriptomes of tumor biopsies (123,000 cells from six independent cohorts) to establish a functional and molecular landscape of CRC stem cells. We performed mechanistic follow-up analyses by mass-spectrometry-based proteomics, large-scale kinase inhibition assays and immunofluorescence analyses. ResultsWe find a continuous landscape of CRC stem cells that is characterized by distinct developmental programs: adult stem cell-to fetal-like regenerative states and transition between differentiation programs. By large-scale drug perturbations and multi-omics modeling, we identify a regenerative/fetal-like stem cell trajectory characterized by PI3K/mTOR dependency. We find the identified developmental axes conserved in organoid, clinical, as well as single-cell data, and the fetal-like PI3K/mTOR-dependent state to be associated with poor clinical prognosis. Mechanistically, PI3K/mTOR vulnerability is linked to a lack of adaptive capability due to suppressed mRNA translation and associated with an upregulated SRC signaling network. ConclusionsOur work moves beyond a molecular CRC landscape by combined functional perturbation analyses in organoids. This enables mechanistic modeling of stem cell state regulation and identifies an SRC/mTOR-dependent regenerative state in CRC, which might allow improved therapeutic targeting in the future.

Across cancers, tumor-infiltrating CD8+ T cells expressing the tissue-resident memory T cell (TRM) markers CD69 and CD103 are strongly associated with favorable clinical outcomes. However, a substantial fraction of these cells in human tumors are not tumor-specific, but instead recognize unrelated viral antigens. These virus-specific bystander TRM-like cells are prevalent in tumors and retain functional potential, raising interest in strategies that leverage pre-existing antiviral immunity for cancer immunotherapy. Yet their origins and differentiation states remain poorly defined, limiting both the interpretation of residency-based tumor-infiltrating lymphocyte (TIL) phenotyping and efforts to rationally harness these TRM-like cells. Here, using mouse models of GBM and melanoma, we demonstrate that resting circulating memory T cells trafficked into tumors via GPCR-dependent signaling and rapidly adopted a tissue-resident phenotype, independent of cognate antigen. Strikingly, in GBM, but not melanoma, pre-existing brain TRM contributed substantially to the bystander TIL compartment and were the dominant source of CD69+/CD103+ bystander T cells, revealing a tumor- and tissue-specific origin for this subset. These findings were further supported by transcriptional analysis of T cell receptor clones present in both paired patient GBM tumor and peritumoral brain, which identified shared features with TRM-derived TILs in mouse GBM. Overall, this work provides new insight into tumor immunosurveillance, inform the interpretation of CD69+/CD103- and CD103+ TIL populations, and lay a foundation for immunotherapeutic strategies aimed at harnessing circulating and pre-existing virus-specific TRM populations in tumors.

Cancers with similar histology often exhibit divergent clinical behavior, reflecting molecular heterogeneity not captured by current classification systems. Although driver mutations are central to tumorigenesis, their broader systems-level consequences have not been systematically leveraged. We integrated genomic and transcriptomic data across cancers to define driver mutation signatures (DMS), coordinated transcriptional programs associated with cancer driver mutations. From 121 candidate drivers, we derived 90 robust signatures and quantified their activity in individual tumors using mutation signature scores (MSS). DMS analysis revealed a hierarchical organization of tumors into molecular subgroups that transcended tissue boundaries while preserving driver-associated features. Continuous MSS profiles further defined high-resolution molecular fingerprints for individual tumors. DMS provides a quantitative framework for tumor classification and patient stratification and links driver-associated programs to potential therapeutic vulnerabilities. Together, these findings establish a pan-cancer molecular taxonomy that bridges genotype and phenotype and may inform precision oncology.

Genomics-guided precision oncology has improved survival in cancer entities with actionable mutations but cannot capture oncogenic signaling that manifests at the protein level. Here, we report a prospective, real-world pan-cancer study profiling proteomes and phosphoproteomes of 1,998 tumor samples from adults and children with rare or advanced cancers enrolled in the German precision oncology programs DKFZ/NCT/DKTK MASTER, CATCH and INFORM and their molecular tumor boards (MTBs). We developed tumor proteome activity status (TOPAS) scores for 46 clinically relevant kinases, an immune activity score capturing antigen presentation and T-cell activation and identified therapeutically targetable cell-surface proteins for 94% of patients. These readouts enhance MTB recommendations by exposing actionable non-genomic kinase activity, refining interpretation of oncogenic genome alterations, and highlighting cell-surface treatment options. Three proof-of-concept analyses indicate clinical utility including kinase activity-stratified pazopanib response in sarcoma, immune activity score-tracked checkpoint-inhibitor outcomes pan-cancer, and a phosphoproteomic biomarker distinguishing EGFR-inhibitor response in chordoma.

Background: Glioblastoma remains resistant to most immune-based therapies. Surgery may create a perioperative window in which systemic immune activation and tumor antigen release intersect. We evaluated whether COVID-19 vaccination shortly before first glioblastoma surgery was associated with survival. Methods: We performed a retrospective single-center cohort study of adults with newly diagnosed glioblastoma undergoing initial biopsy or resection from 2021 to 2025. The primary exposure was documented COVID-19 vaccination within 100 days before first tumor surgery. Overall survival was analyzed from surgery using Kaplan-Meier and Cox models, with 1:1 propensity matching and sensitivity analyses addressing treatment completion, calendar time, surgical selection, steroid exposure, immune-cell variables, COVID severity, and negative-control vaccination. Results: The cohort included 187 patients: 64 perioperatively vaccinated and 123 non-perioperative comparators. Among vaccinated patients, 59/64 (92.2%) received mRNA vaccines; median vaccination-to-surgery interval was 81 days (IQR 71-90). Median overall survival was 743 days in vaccinated patients versus 318 days in comparators (unmatched HR 0.48, 95% CI 0.30-0.76; p=0.002). After 1:1 matching, median survival was 743 versus 349 days (HR 0.52, 95% CI 0.34-0.80). Sensitivity analyses accounting for adjuvant therapy, surgery year, extent of resection, steroid exposure, immune-cell measures, and COVID hospitalization were directionally consistent. Influenza vaccination was not associated with survival. Conclusions: COVID-19 vaccination within 100 days before first glioblastoma surgery was associated with longer overall survival. These findings identify perioperative vaccination timing as a potentially relevant and modifiable variable in glioblastoma outcomes.

Combination targeted therapy with BRAF/MEK inhibitors and immune therapy show promising therapeutic outcomes in melanoma; however, the development of drug resistance still represents a formidable challenge. Remaining unexplored is the possibility that BRAF/MEK inhibitors themselves inadvertently compromise the tumor immune microenvironment, limiting the efficacy of immunotherapy when it is used in combination with targeted inhibitors. Herein, we profiled the landscape of the BRAF regulatome identifying a novel transcription factor, TFAP2A, newly linking BRAF/MEK drug resistance to antitumor immunity. Specifically, we found that BRAF/MEK inhibitors significantly upregulate TFAP2A. Further, genetic disruption of TFAP2A overcomes BRAF/MEK-inhibitor resistance, promotes stromal enrichment, and enhances intratumoral infiltration of macrophages in an immune-compromised mouse model. In a syngeneic mouse model, TFAP2a knockout not only suppresses tumor growth but also induces potent anti-tumor tertiary lymphoid structures (TLSs). Single cell transcriptomics revealed that the absence of TFAP2A shapes the antitumor microenvironment with an influx of M1-like macrophages, CD8+ T cells and mature dendritic cells. By identifying TFAP2A as a shared driver of both targeted therapy resistance and immunosuppression, our work offers a one-stone-two-bird strategy to overcome drug resistance and elicit antitumor immunity.

Circulating tumor cells (CTCs) and immune cells form dynamic multicellular ecosystems in blood, but their spatial organization and clinical relevance have not been systematically characterized. We developed the Cell and Cluster Identification Program (CCIP), an artificial intelligence-based framework that analyzes routine multiplex immunofluorescence blood scans to segment cells, identify CTCs and five immune lineages with high accuracy, and quantify multicellular clusters and tumor-immune interactions. Applying CCIP to 2,693 blood scans from 1,399 patients, we profiled over 60 million cells (>7 million multi-cell clusters) and linked imaging-derived features to patient outcomes. Correlated with circulating-tumor DNA mutation burdens, a 14-feature image model predicted overall survival in breast cancer, outperformed clinicopathologic variables and CTC enumeration, and generalized to prostate cancer. Prognostic imaging signatures were also associated with therapy response-related progression-free survival as well as with single-cell RNA sequencing-derived immune suppression states, connecting circulating tumor-immune architecture with systemic immune dysfunction.

Most high-dimensional studies of tumor-immune interactions focus on metastatic models, limiting insight into how immune remodeling in primary tumors shapes metastatic competence. Here, integrating single-cell RNA sequencing, CyTOF, and functional studies across metastatic (4T1) and non-invasive (EMT6) triple-negative breast cancer (TNBC) murine models, we define tumor state-specific immune programs that distinguish metastatic competence. Tumors with metastatic capacity uniquely drive early bone marrow expansion of CXCR2 neutrophils, which infiltrate primary tumors acquiring a CXCL2-producing phenotype that promotes EMT-associated cancer stem cell (CSC) plasticity. This program depends on TGF-{beta}/CEBPD-mediated induction of S100A9. Elevated CXCL2, together with G-CSF, establishes a feed-forward circuit that drives systemic neutrophil mobilization and recruitment to distant organs, where neutrophil-derived S100A8/A9 (calprotectin) promotes MET-driven CSC outgrowth and metastatic colonization. Clinically, gene signatures associated with CXCR2 neutrophils predict poor survival in TNBC patients, whereas monocyte/macrophage (CX3CR1) and T cell activation signatures correlate with improved outcomes. S100A9 ablation disrupts this cascade and enhances immunotherapy responsiveness, defining a TGF-{beta}/S100A9/CXCR2 axis linking immune remodeling, CSC plasticity and metastasis. HighlightsO_LIMetastatic TNBC engages a TGF-{beta}/C/EBP{delta}/S100A9 axis that expands CXCR2 neutrophils C_LIO_LINon-invasive EMT6 tumors retain a CX3CR1 monocyte/macrophage and T-cell landscape C_LIO_LICXCR2+ neutrophils in pre-metastatic niches suppress T cell response while promoting tumor cell proliferation C_LIO_LIS100A9 loss redirects myelopoiesis and potentiates anti-PD-L1 in TNBC models C_LI In BriefAlkan et al. dissect how tumor state programs the myeloid compartment in TNBC. Metastatic 4T1 tumors uniquely engage a TGF-{beta}/C/EBP{delta}/S100A9 axis driving CXCR2 neutrophil expansion and CXCL2/G-CSF-dependent systemic mobilization, coupling immune remodeling to EMT/MET cancer-stem-cell plasticity, while S100A9 loss restores CX3CR1 myeloid identity and unlocks checkpoint-inhibitor responsiveness.

Fibroblast heterogeneity shapes tumor progression, yet the transitional states linking normal-associated fibroblasts to cancer-associated fibroblasts (CAFs) remain poorly defined. Here, we integrated single-cell transcriptomic profiles of more than 90,000 stromal cells from 281 samples across nine cancer types to construct a pan-cancer atlas of fibroblast diversity. We identified a distinct CAF-like population positioned between normal-activated fibroblasts and established CAF subsets along the inferred fibroblast activation trajectory. Integration with single-nucleus chromatin accessibility data identified FOXF1 and FOXF2 as candidate regulators of this CAF-like state. Functionally, CAF-like fibroblasts were characterized by non-canonical WNT signaling, WNT5A-associated stromal communication, and a candidate GZMA-F2R/PAR immune-stromal signaling axis supported by spatial transcriptomic analysis. Clinically, the CAF-like signature demonstrated context-dependent prognostic relevance, with high expression associated with poorer survival in the tumor compartment of TCGA stomach adenocarcinoma. Together, this study identifies a FOXF1/FOXF2-associated transitional CAF-like fibroblast state and links it to stromal signaling, immune-stromal communication, and cancer type-specific clinical relevance.

Rectal cancers are often treated with neoadjuvant chemoradiotherapy (CRT), yet 85% of patients do not achieve a pathological complete response. To identify the molecular determinants of CRT response, we profiled the single-cell signalling, DNA-damage, cell-cycle, apoptotic, and cell-fate responses of 2,769 patient-derived organoid cultures treated with CRT, cancer-associated fibroblasts (CAFs), and signal-rewiring agents. We find that CRT response is determined by stem cell-fate. CRT triggers comparable DNA-damage in isogenic proliferative (proCSC) and revival (revCSC) colonic stem cells, but proCSC retain damage and die whereas revCSC resolve damage and persist. Both CRT and CAFs drive proCSC to a common treatment-resistant revCSC fate and high revCSC predicts worse survival in patients. Pharmacologically constraining stem-cell plasticity increases CRT sensitivity, and Spatial Perturbation of ARrayed Tumour Assembloids (SPARTA) confirms YAP/TEAD inhibition improves chemotherapy responses in human stromal-tumour models. These results suggest that cancer cell-fate, not genotoxic damage itself, ultimately governs response to standard-of-care chemoradiotherapy. HIGHLIGHTSO_LIRectal cancer stem cell-fate determines chemoradiotherapy-induced apoptosis C_LIO_LIproCSCs retain DNA-damage and die, whereas revCSCs repair damage and persist C_LIO_LICAFs and chemoradiotherapy converge on a common chemo-radioresistant revCSC state C_LIO_LISPARTA reveals TEAD inhibition blocks DNA-repair persisters in stromal assembloids C_LI

Cytotoxic T lymphocytes (CTLs) play a central role in antitumor immunity; however, metabolic reprogramming within the tumor microenvironment often compromises their effector function, making metabolic targeting crucial for the improvement of T cell function. Folate-dependent purine synthesis, a core pathway sustaining the nucleotide pool, is highly activated in tumors, yet its role in regulating tumor immune sensitivity remains unclear. Here, by establishing a co-culture system of melanoma cells and human T Cell Receptor (TCR)-engineered T cells, we systematically evaluated the effects of folate-dependent purine synthesis inhibitors on tumor cell response to CD8+ T cell cytotoxicity. We found that inhibition of key enzymes such as methylenetetrahydrofolate dehydrogenase 2 (MTHFD2) and glycinamide ribonucleotide transformylase (GART) markedly enhanced tumor cell sensitivity to T cell killing, an effect also observed with exogenous nucleoside supplementation. Mechanistically, inhibition of folate-dependent purine synthesis suppresses glycolysis by downregulating critical glycolytic enzymes, thereby reducing lactate production. Reduction in lactate further weakens lactylation and stability of the immune checkpoint protein PD-L1. In parallel, impaired purine synthesis disrupts uridine metabolism, blocks ribose salvage, and distally influences glycolysis. Collectively, our study identified the folate-dependent purine synthesis-glycolysis axis as key regulator of tumor immune response and highlights metabolic targeting as a promising strategy to improve cancer immunotherapy.