Nature Cancer

Melanoma is one of the leading cancer types treated with immune checkpoint blockade (ICB), yet a substantial proportion of patients fail to respond. While tumor mutational burden and PD-L1 expression are established ICB biomarkers, they leave large gaps in predictive accuracy. Somatic copy number alterations (SCNAs) are pervasive in melanoma but their role in shaping the tumor immune microenvironment (TME) and predicting immunotherapy outcomes has been insufficiently characterized. Here we present KaryoTME, an integrated computational framework that systematically links SCNAs to immune phenotypes using genomic, transcriptomic, and clinical data from over 15,000 patients. Applying this framework to skin melanoma (SKCM) within a pan-cancer context, we identify arm-level chromosome 1q gain and 9p loss as the most prominent SCNA events associated with an immune-cold tumor microenvironment. These alterations act through distinct mechanisms: 9p loss preferentially depletes NK and CD8+ T cells, whereas 1q gain is more strongly associated with reduced anti-tumor immune cell infiltration. At the focal level, regions 1q21 and 1q42 show the strongest immune-suppressive associations in melanoma. Applying the TUSON-Immune algorithm, we predict candidate Tumor immune Suppressor Genes (TiSG) and immune Oncogenes (iOG) within these chromosomal regions, revealing enrichment for pathways including IFN signaling, JAK/STAT pathway, and immune-suppressive cytokine secretion. Critically, 1q gain emerged as a strong and independent predictor of poor survival following anti-PD-1/PD-L1 therapy across two independent clinical cohorts: the MSK-IMPACT cohort (p = 0.018, N = 77) and a large real-world Caris Life Sciences dataset (HR = 1.2, p = 0.002, N = 1,167). Multivariate analysis confirmed that 1q gain predicts poor outcomes independently of CD8+ T-cell infiltration, B-cell infiltration, tumor mutational burden, and PD-L1 status. These findings establish chromosome 1q gain as a compelling biomarker of immunotherapy resistance in melanoma and highlight aneuploidies as underappreciated drivers of immune evasion in this disease.

Platinum-based chemotherapy remains a cornerstone of treatment for triple-negative breast cancer (TNBC), yet the molecular determinants governing platinum response remain poorly defined. By leveraging the randomized Phase II INFORM trial, which compared neoadjuvant cisplatin to anthracycline-based therapy in BRCA1/2-mutant breast cancer--we identified miR-362-3p as a specific regulator of cisplatin sensitivity. Higher plasma miR-362-3p expression was exclusively associated with favorable clinical outcome in the cisplatin arm, with no association observed in the AC arm, decoupling platinum-specific vulnerability from general chemotherapy response. We used gain- and loss-of-function TNBC models to establish that miR-362-3p functions as a potent sensitizer to cisplatin in vitro and in vivo. Integrated TCGA analysis and experimental validation identified BCLAF1, a key regulator of DNA damage response, as a direct repression target of miR-362-3p. We uncovered a novel role for the miR-362-3p/BCLAF1 axis in overcoming platinum resistance in TNBC.

Curative-intent immunochemotherapy fails in ~30% of patients with large B-cell lymphoma (LBCL), yet no validated molecular tool enables early identification of high-risk individuals to guide treatment intensification. Using shallow whole genome sequencing (sWGS) of plasma cell-free DNA from 190 LBCL patients, we developed and validated the ACT score (Aberrations, fragment Composition, Terminal motifs), a composite classifier integrating genomic and fragmentomic features from a single post-cycle-1 sample. ACT-positive patients had worse 2-year outcomes versus ACT-negative patients: time-to-progression 29% vs. 83% (HR 4.4, 95% CI 1.9 - 10.0; P = 1.5 x 10 - 4) and overall survival 47% vs. 93% (HR 8.7, 95% CI 3.0 - 25.4; P = 1.8 x 10-6). ACT score was independently prognostic of the International Prognostic Index, and their combination identified the highest-risk patients. Unlike mutation-based approaches, this assay requires neither tumor tissue, germline control nor a baseline plasma sample. Built on open-source tools and sWGS, the ACT score offers a feasible scalable strategy for early risk stratification in aggressive LBCL.

In high-grade serous carcinoma (HGSC), extensive intra-tumoral heterogeneity hinders complete eradication and remains a major obstacle to developing combination therapies capable of eliminating subpopulations resistant to standard-of-care treatment. Using single-cell RNA sequencing of 72 samples from 54 HGSC patients spanning treatment-naive, post-neoadjuvant chemotherapy and relapse stages, we established a carboplatin-anchored framework that identifies transcriptional signatures of intrinsic (pre-existing) and adaptive (therapy-induced) resistance in individual tumors and prioritizes mechanistically matched drugs to potentiate carboplatin efficacy. Candidate compounds were ranked by integrating orthogonal resources--viability (GDSC, PRISM) and perturbational transcriptomics (L1000, Perturb-seq)--to reduce context bias. Among 64 candidates, three carboplatin adjuvants enhanced long-term efficacy in patient-derived organoids (PDOs), and pevonedistat further significantly reduced tumor burden in orthotopic xenografts. This tiered validation pipeline--from short-term and long-term PDOs and in vivo orthoptic xenografts--establishes a translational framework linking single cell resistance programs to actionable, tumor-specific, carboplatin-anchored combinations for HGSC.

Conventional short-read sequencing cannot determine whether co-occurring variants within a cancer gene reside on the same allele (cis) or on opposing alleles (trans), a distinction with direct biological and therapeutic consequences. Trans configurations confirm biallelic tumor suppressor inactivation and inform therapy selection, while cis configurations generate compound oncogenic alleles with enhanced activity. We analyzed 768 patients with prostate, breast, or ovarian cancers in the PROBLEM cohort, using mutational signatures to nominate cryptic genomic instability cases where the causative biallelic event was not apparent from short-read sequencing. Long-read nanopore sequencing resolved 32 of 46 cryptic cases (69.6%), leveraging its unique advantages in direct methylation detection, long insertion resolution, and complex structural variant characterization, confirming trans biallelic inactivation in all resolved tumor suppressor cases. Systematic analysis of 4,496 MiOncoSeq samples identified 17,519 multi-hit gene pairs, of which 78.7% exceeded the 500 bp short-read phasing limit. Long-read phasing further revealed recurrent compound cis oncogenic alleles in NOTCH1, PIK3CA, PDGFRB, and KIT with functionally synergistic activity. Haplotype phasing resolves a systematically overlooked gap in cancer variant interpretation and warrants broader integration into precision oncology workflows. Statement of SignificanceShort-read sequencing cannot resolve whether co-occurring variants within a cancer gene are cis or trans, a distinction critical for clinical interpretation. Long-read nanopore sequencing addresses this gap through direct haplotype phasing, methylation detection, and complex structural variant resolution, confirming biallelic tumor suppressor inactivation and revealing compound cis oncogenic alleles with enhanced activity.

Anti-CD19 chimeric antigen receptor (CAR) T-cell therapy can induce durable remissions in patients with large B-cell lymphoma (LBCL), yet outcomes remain variable. Reliable pre-treatment predictors of durable response remain limited, leaving a critical gap in patient management. To address this, we profiled pre-treatment plasma cell-free RNA (cfRNA) from 91 LBCL patients treated with axicabtagene ciloleucel (axi-cel, Yescarta) across three independent cohorts. We first demonstrated that signatures of "lymph node-like" tumor microenvironments (TMEs), previously identified in tumor biopsies and shown to correlate with favorable outcomes, are specifically elevated in the pre-treatment plasma cfRNA of responders, but not in matched peripheral blood mononuclear cells (PBMCs). These observations indicate that cfRNA captures TME tissue-derived signals not reflected in circulating immune cells. Next, using unbiased approaches, we identified additional cfRNA signatures associated with one-year clinical outcomes that capture the underlying biological landscape of treatment response. Collectively, these findings support pre-treatment plasma cfRNA as a minimally invasive surrogate of TME state to prospectively inform durable CAR T-cell therapy outcomes and guide risk stratification and TME-modulating adjunct therapies.

The contribution of neoantigen-specific T cells to PD-(L)1 efficacy has largely been inferred from tumor mutational burden. We functionally profiled circulating T cell responses against 7,038 predicted HLA-I-restricted and 21,453 HLA-II-restricted neopeptides in 27 patients with advanced non-small cell lung cancer treated with anti-PD-(L)1. CD4 responses were frequent and correlated with neoantigen availability but not clinical benefit. In contrast, the magnitude and breadth of neoantigen-specific CD8 T cell responses were associated with clinical benefit, progression-free and overall survival, independently of tumor mutational burden. Patients mounting coordinated CD4 and CD8 responses experienced improved progression-free survival. Tumors from CD8 responders displayed immune signatures indicative of both T cell priming and effector functions. Circulating neoantigen-specific CD8 T cells recognized endogenously processed antigens, trafficked to tumors, and selectively expanded under therapy while retaining CD28, CD226, and CXCR3 expression. These findings identify coordinated, functionally engaged neoantigen-specific T cell responses as central determinants of PD-(L)1 efficacy.

Children with relapsed or refractory acute lymphoblastic leukemia (ALL) require more effective and less toxic therapies. We established a prospective, multicenter Drug Response Profiling (DRP) registry (NCT06550102) integrating functional testing into precision-guided treatment. DRP was performed for 340 patients from 17 European countries with a turn-around time of two-weeks. Image-based drug screening with over 135000 unique perturbations revealed a heterogeneous landscape of ex vivo responses to 88 drugs on average. Ranking drug responses across the patient cohort defined individual drug fingerprints, identifying "DRP twins" by similarity in sensitivity and resistance independent of genetic ALL subtypes. Of 239 high-risk patients with follow-up, DRP-informed interventions were reported for 63 patients (26%). Patients received combination therapies based on venetoclax, tyrosine kinase inhibitors, trametinib, bortezomib or selinexor, resulting in objective clinical responses in 43 cases (68%). Precision-guided treatments allowed bridging to cellular therapies in 42 patients among whom 28 (67%) were still alive with a median follow-up of 21 months after DRP (IQR: 14.7-26.6 months). Top responders to venetoclax, ranked within the first tertile of the cohort, had superior 1-year event-survival compared to venetoclax non-responders (0.57 [95% CI, 0.39-0.85] vs. 0.25 [95% CI, 0.11-0.58]). Collectively, these findings demonstrate the feasibility and clinical relevance of functional profiling within an international network. This scalable framework enables individualized therapy selection for enrolment in adaptive precision trials for high-risk pediatric ALL.

Neoadjuvant chemoradiotherapy (CRT) is standard for locally advanced rectal cancer (LARC), yet many patients retain residual disease. To resolve CRT-associated remodeling of the tumor microenvironment, we generated a multimodal spatial atlas from serial sections of paired pretreatment and post-treatment specimens from 24 patients using Xenium single-cell spatial transcriptomics and PhenoCycler multiplex proteomics, profiling 2.8 million cells; matched Visium HD datasets were generated on adjacent serial sections. Resistance was most strongly associated with fibroblast and myeloid programs adjacent to residual tumor. We identify a periostin (POSTN)-expressing CAF subset selectively enriched around residual tumor cells in non-responders, displaying a myofibroblastic phenotype and activating extracellular matrix remodeling, noncanonical WNT signaling, and immunosuppressive pathways. Tumor cells neighboring POSTN+ CAFs show consistent epithelial-mesenchymal transition signatures. Together, this atlas enables interrogation of CRT-induced spatial remodeling and nominates POSTN+ CAFs as key mediators and targets of CRT resistance, with direct relevance to CRT-based combination strategies.

A substantial proportion of cancer patients fail to benefit from their prescribed combination regimens, yet identifying superior alternatives from the vast pharmacological space prior to treatment failure remains an unsolved clinical challenge. Existing computational approaches either rely on multi-omics profiles unavailable in standard oncological practice or reduce drug efficacy to scalar metrics that discard the dose-dependent resolution essential for therapeutic optimization. Here, we present XACT, a hierarchical deep learning framework that reconstructs full dose-dependent drug responses for both monotherapy and drug combinations using only clinically accessible transcriptomic profiles. By leveraging an asymmetric X-Linear Attention mechanism that models second-order interactions between molecular drug substructures and intracellular signaling pathway activities, XACT captures concentration-dependent pharmacodynamics with state-of-the-art accuracy and generalizability to unseen transcriptomic landscapes. When applied to the TCGA pan-cancer cohort, XACT-derived resistance scores were significantly associated with clinical treatment outcomes and stratified overall survival as the strongest independent prognostic factor after multivariate adjustment for tumor stage and cancer type. Systematic virtual screening revealed therapeutic vulnerabilities and nominated alternative regimens for treatment-refractory sarcoma and pancreatic adenocarcinoma. These results establish XACT as a scalable, interpretable, and clinically translatable framework that advances precision oncology from computational prediction toward data-driven therapeutic prescription.

Natural killer (NK) cell-based therapies are a promising approach in cancer, but their efficacy is limited by impaired effector function and tumor-intrinsic resistance. To systematically identify therapeutic strategies that target both sides of the cancer-immune interface, we designed a multimodal immunopharmacologic screening platform comprising high-throughput co-culture drug screens, cytokine secretome profiling, single-cell perturbation screens, and genome-scale CRISPR screening, followed by validation in biobanked patient-derived models. Applying the platform across five blood cancer types, we identified protein kinase C (PKC) activation to simultaneously increase effector cytotoxicity and cytokine secretion through transcriptomic rewiring, and tumor susceptibility to NK cell killing through tumor-intrinsic PKC-{delta}. In patient samples, PKC activation sensitized NK-resistant leukemic progenitors to NK cell killing. In addition, NEDD8 inhibition enhanced NK function and shifted tumor TNF signaling towards pro-apoptotic pathways. Our platform provides a systematic approach to identify drugs rewiring both sides of the cancer-immune interface to circumvent tumor immune resistance.

T-cell receptor (TCR) repertoires encode the organization of adaptive immunity and its reshaping by cancer and therapy, but disentangling treatment-associated structure from V(D)J recombination constraints remains challenging. We present CRAFT (Cancer Repertoire Anomaly Finding Transformer), a conditional sequence-to-sequence transformer that learns a nucleotide-level generative grammar of productive TCR-beta CDR3 sequences from healthy-donor repertoires, conditioned on germline V(D)J assignments. A dual-head decoder mirrors the independence of V-D and D-J recombination, and curriculum training yields embeddings that serve as a reference coordinate system for quantifying structured deviations in cancer-associated repertoires. In proof-of-concept analyses of a checkpoint blockade cohort (n=18) and a two-patient single-cell study of oncolytic immunotherapy, CRAFT-derived geometric metrics capture response-associated immune remodeling, including longitudinal shifts in repertoire organization. In antigen-labeled benchmarks, CRAFT yields coherent organization across specificity classes while highlighting settings where CDR3-beta alone provides partial signal.

Chemo-immunotherapy is a first-line treatment for advanced gastric cancer, yet response rates remain limited and resistance mechanisms are poorly defined. Here we generate a single-cell atlas of 542,121 cells from 35 patients treated with anti-PD-1 plus chemotherapy, profiling pre- and post-treatment tumors linked to clinical response. Integrating spatial transcriptomics, immunohistochemistry, and bulk RNA sequencing, we identify two temporally distinct resistance programs. Intrinsic resistance in pre-treatment non-responders is marked by enrichment of CEACAM5/6 tumor cells that form immune-excluded spatial niches characterized by macrophage recruitment and CD8 T-cell exhaustion. Acquired resistance in post-treatment non-responders is driven by expansion of IL-1{beta} macrophages, which induces coordinated NF-{kappa}B activation across tumor and stromal compartments, promoting PD-L1 upregulation, epithelial-mesenchymal transition, and chronic inflammation. These findings delineate an evolutionary trajectory of resistance and nominate CEACAM5/6 and IL-1{beta} as predictive biomarkers and therapeutic targets to improve anti-PD-1-based combination strategies.

Breast cancer is a highly heterogeneous disease shaped by dynamic interactions between malignant cells, immune infiltrates, stromal compartments, and the extracellular matrix. Among the molecular regulators of these interactions, cysteine cathepsins and legumain have emerged as important proteases involved in tissue remodeling, immune regulation, and tumor progression, yet their distribution and functional status across human breast cancer ecosystems remain insufficiently defined. Here, we performed an integrated protease-centric analysis of breast cancer specimens from 66 patients using high-dimensional single-cell mass cytometry of matched peripheral blood and tumor samples, imaging mass cytometry of intact tissues, and activity-based TOF probes for in situ detection of active proteases. Systemic immune profiling identified two patient clusters associated primarily with neoadjuvant therapy and tumor grade, accompanied by distinct cytokine and circulating protease patterns. In tumors, single-cell analysis revealed pronounced interpatient heterogeneity in tissue architecture and immune infiltration, while protease profiling uncovered reproducible cell type-associated modules, including cathepsin B/L-cystatin C and legumain-cystatin E/M axes. Cathepsins B and L were prominent in tumor-infiltrating immune cells and variably expressed in epithelial cells, whereas cathepsin D showed broader tumor distribution and cathepsin S remained more restricted. In epithelial cells, HER2 expression did not consistently coincide with high cathepsin B or L abundance, enabling identification of a limited subgroup of patients with combined HER2-high/protease-high states relevant to protease-cleavable antibody-drug conjugates. Spatial imaging further localized cathepsins B and D to tumor-stroma interfaces and macrophage-rich niches, and activity-based IMC confirmed the presence of catalytically active cathepsin B in human breast tumor tissue. Together, these findings define cysteine cathepsins as spatially and cellularly organized components of breast tumor ecosystems and provide a framework for protease-informed patient stratification and biomarker-protease pairing in targeted therapy.

Triple-negative breast cancer (TNBC) commonly develops resistance to taxane-based chemotherapy, resulting in recurrence and poor clinical outcomes. Defining the molecular mechanisms that sustain chemoresistance is essential for improving therapeutic efficacy. Using unbiased insertional mutagenesis, we identified the RNA methyltransferase METTL16 as a previously unrecognized epi-transcriptomic driver of taxane resistance. METTL16 overexpression conferred resistance to docetaxel and paclitaxel across multiple TNBC models, and METTL16 expression was elevated in paclitaxel-resistant cells. Genetic depletion of METTL16 in paclitaxel-resistant cells restored taxane sensitivity. Because enhanced drug efflux is a well-established mechanism of taxane resistance, we investigated whether METTL16 regulates the multidrug transporter ABCB1 (P-glycoprotein). Paclitaxel-resistant TNBC cells exhibited elevated METTL16 and ABCB1 expression compared to parental cells. METTL16 binds to ABCB1 mRNA and catalyzes its N6-methyladenosine (m6A) modification, promoting increased ribosome loading and translational upregulation without altering transcript abundance. Inactivation of METTL16 impaired ABCB1 polysome association and restored paclitaxel sensitivity, demonstrating that the methyltransferase activity is essential for resistance. Consistent with this mechanism, METTL16 overexpression increased ABCB1 protein levels, whereas METTL16 down-regulation increased intracellular paclitaxel accumulation. Analysis of TNBC patient datasets revealed a positive correlation between METTL16 and ABCB1 expression, supporting the clinical relevance of this mechanism. Antisense-mediated inhibition of METTL16 using a translation-blocking Vivo-Morpholino reduced the survival of resistant TNBC cells and suppressed tumor growth in vivo. Surprisingly, genetic ablation of METTL16 caused profound loss of TNBC cell viability, while having only modest effects on nonmalignant mammary epithelial cells, indicating a cancer-selective dependency. Collectively, these findings define a METTL16-ABCB1 interaction that drives taxane resistance and establish METTL16 as a therapeutic target in TNBC.

NRAS-mutated melanoma remains a major unmet clinical need, with no approved targeted therapy and rapid progression on standard treatment. Tri-complex RAS(ON) inhibitors such as daraxonrasib (RMC-6236) and RMC-7977 have shown early clinical activity, but the mutation-specific sensitivity landscape and adaptive resistance programs in melanoma remain undefined. To address this, we generated an isogenic 3D melanoma platform and performed a saturation mutagenesis screen across 95 NRAS missense variants (>99% of clinically recurrent variants), profiling oncogenic fitness and responses to six RAS-targeting agents in spheroids and xenografts. RMC-6236 and RMC-7977 showed the broadest activity and stratified recurrent NRAS mutants into hypersensitive (G12 variants and Q61R/K/L; [~]95% of cases), moderately sensitive (G13D/R/V; [~]4%), and resistant (G60E and Q61P; [~]1%) classes. Structural analyses supported distinct mechanisms underlying reduced susceptibility in a restricted subset of variants. In sensitive genotypes, RAS(ON) inhibition elicited an adaptive cytokine- and RTK-associated survival program converging on STAT3. Co-inhibition of STAT3 enhanced apoptosis, suppressed MYC, and induced tumor regression in NRAS-mutant melanoma models. Together, these findings define a mutation-resolved therapeutic landscape for NRAS-mutant melanoma and identify adaptive STAT3 signaling as a rational target for combination therapy. Statement of Translational SignificanceNRAS-mutated melanoma lacks effective targeted treatments, and clinical responses to immunotherapy are suboptimal. This study presents the first comprehensive drug sensitivity map across 95 NRAS mutations in melanoma, identifying the pan-RAS(ON) inhibitors RMC-6236 and RMC-7977 as broadly effective agents. Multiple mutants with reduced susceptibility are identified, providing mutation-informed guidance for patient selection and clinical trial stratification. Mechanistic analyses reveal that RTK/cytokine-driven STAT3 activation functions as a key survival pathway under RAS(ON) blockade, and its inhibition markedly enhances the efficacy of pan-RAS(ON) inhibitors. These findings support mutation-guided use of RAS(ON) inhibition and highlight STAT3 co-targeting as a rational strategy to strengthen and prolong therapeutic responses in NRAS-mutated melanoma. Highlights- A functional and therapeutic atlas defines 95 recurrent and nonrecurrent NRAS missense variants in melanoma - RMC-6236 and RMC-7977 show broad but genotype-selective activity across major NRAS mutations - A restricted subset of recurrent NRAS mutants shows reduced susceptibility to RAS(ON) inhibition - RAS(ON) inhibition induces an adaptive STAT3 survival program that is therapeutically targetable

The microbiome plays a critical role in immune health and response to immune-stimulating treatments, including cancer immunotherapy. However, the molecular mechanisms by which commensal microbes influence cancer immunology remain poorly understood. Here, we report a class of microbiome-derived metabolites called hydroxyphenyl propanoates (HPP) that enhance tumour immune surveillance and response to immune checkpoint blockade (ICB) therapy in mice. HPPs function as potentiators of innate immune signalling in tumour-associated myeloid cells by promoting cleavage of the pore-forming protein gasdermin D (GSDMD), a critical effector of inflammasome function. This enhances the secretion of proinflammatory cytokines, such as IL-1 family members, while simultaneously protecting against pyroptosis. Secreted IL-1 family cytokines in turn elicit autocrine and paracrine inflammatory signaling in tumour-infiltrating leukocytes. HPP supplementation increases anticancer T cell function, improves disease control and extends overall survival (OS) in tumour-bearing mice harboring complex microbiomes or those treated with broad-spectrum antibiotics. In humans, GSDMD activation is associated with a favourable response to PD-1 blockade therapy in patients with advanced stage melanoma. Our study uncovers a molecular mechanism of regulation over host antitumour immunity that is modifiable and can be harnessed for improved cancer immunotherapy in a broad spectrum of patients.

Brain metastasis (BM) in renal cell carcinoma (RCC) remains poorly understood and often resistant to immune checkpoint inhibitors. We generated a large single-nucleus RNA-seq data of RCC BM, profiling 14 BM samples alongside matched extracranial metastases and primary tumors. Tumor cells in BM displayed neuronal infiltration, neural-like adaptation, and marked remodeling of the microenvironment, including expansion of immunosuppressive myeloid cells and depletion of antigen-presenting dendritic cells. Tumor, immune, and stromal cells exhibited metabolic rewiring characterized by fatty-acid metabolism, oxidative phosphorylation, and MYC-driven programs. CD8 T cells showed terminal exhaustion and impaired proliferative capacity, and tertiary lymphoid structures were absent. Spatial profiling of 12 BM samples (13,128 cells) validated key cellular interactions, while ligand-receptor analysis revealed immunoregulatory circuits between tumor, stromal, and immune cells. These findings define BM-specific adaptations that promote immune evasion and resistance, revealing therapeutic vulnerabilities in RCC BM. SIGNIFICANCESingle-nucleus RNA-sequencing profiling reveals tumor, immune, and metabolic adaptations in renal cell carcinoma (RCC) brain metastases, including neuroglial remodelling and immunosuppressive niche formation. These findings identify immune evasion mechanisms that could contribute to therapeutic resistance, providing new avenues for site-specific therapeutic interventions to improve treatment efficacy and outcomes in patients with RCC BM.

Multiple myeloma (MM) is a clonal plasma cell malignancy characterized by bone marrow infiltration, monoclonal immunoglobulin production, and microenvironmental dysregulation that leads to systemic organ damage. The advent of B-cell maturation antigen (BCMA)-directed chimeric antigen receptor (CAR) T-cell therapy has induced unprecedented responses and durability for patients with relapsed/refractory MM. These outcomes are rarely observed with prior salvage strategies, although relapse remains the predominant long-term challenge for most patients. The two currently approved BCMA CAR-T cell products use viral vectors to semi-randomly insert the CAR gene, which results in heterogeneous genomic composition and variability in efficacy, safety, and product consistency. To address these challenges, we integrated targeted CRISPR genome engineering with precise CAR transgene insertion at the T-cell receptor alpha constant (TRAC) locus, 1XX CAR signaling architecture to enhance potency and durability, and non-viral manufacturing with a single-stranded DNA repair template to improve efficiency and yield. This approach confers physiological CAR expression, reduces insertional mutagenesis, and improves persistence by mitigating tonic signaling and exhaustion. Our GMP manufacturing process consistently achieved high CAR integration (37.7-72.7%) and yields across all full-scale runs and met predefined release criteria for identity, purity, safety, and quality. In NSG mouse models of MM, the UCCT-BCMA-1 product exhibited exceptionally potent tumor control, CAR-T cell expansion 100-1000-fold greater than that of lentiviral constructs, and durable clearance of myeloma cells after multiple rechallenges. These findings establish a CRISPR-edited, fully non-viral manufacturing platform for next-generation 1XX-BCMA CAR-T therapies with enhanced persistence, safety, and efficacy. One Sentence SummaryCRISPR-engineered, TRAC-targeted 1XX-BCMA CAR-T therapy with improved safety, potency, and persistence in relapsed and refractory multiple myeloma.

Pancreatic ductal adenocarcinoma (PDAC) is typically diagnosed at advanced stages, yet single-cell datasets that capture late-stage and treated disease remain sparse, hindering progress in understanding tumour heterogeneity and therapy resistance. Here, we have generated integrated single-cell transcriptomic atlases of human and mouse PDAC to define the cellular and molecular landscape of the disease, from early to advanced and metastatic stages, including post-treatment disease, and to enable direct cross-species comparison. Using scANVI to harmonize 16 human studies comprising 257 donors and representative mouse models (101 tumours), we compiled over 1.6 million cells and established a four-level hierarchical taxonomy of more than 60 distinct cell states spanning malignant, stromal, immune, endothelial, adipose, exocrine and endocrine compartments. We resolve ten malignant programmes linked to progression and uncover rare immune phenotypes, including CD4CD8 double-positive T cells that remain poorly characterized in PDAC. Notably, we show that radiotherapy (RT) exposure is associated with enrichment of an EMT-persistent malignant state and an immunosuppressive microenvironment characterized by expansion of tumour-associated endothelium, depletion of intratumoral T cells and heightened laminin-CD44 signalling, with RT-associated genes linked to adverse prognosis in independent cohorts. Cross-species mapping reveals that orthotopic syngeneic allografts more faithfully recapitulate the cellular diversity and EMT-enriched states of advanced human PDAC, underrepresented in autochthonous genetically engineered models, with differences driven primarily by cell-type composition rather than pathway divergence. Together, these atlases and pretrained models provide a broadly accessible reference for benchmarking PDAC model fidelity and for interrogating mechanisms of tumour progression, microenvironmental remodelling and therapy response and resistance.