[This corrects the article DOI: 10.1016/j.euros.2025.12.004.].

Checkpoint inhibitor immunotherapy (CPI) for BRAF mutant advanced melanoma first-line results in a better long-term survival compared to targeted therapy (TT), however TT induction may benefit poor prognosis groups. The parallel-arm, randomised phase II, multicentre, feasibility CAcTUS trial (Clinicaltrials.gov NCT03808441) randomised 21 patients to receive standard of care investigators choice TT or CPI, switching to the alternative upon progression (n = 10), or commencing TT and switching to CPI upon an ≥80% reduction of BRAF variant allele frequency (VAF) in circulating tumour DNA (ctDNA; n = 11). The study achieved its primary endpoints with 100% (95% confidence interval [CI]: 94-100%) of critical results provided within 7 days to inform a decision to switch and 100% of patients commencing TT achieving an ≥80% reduction of BRAF VAF (95% CI: 80-100%). Secondary outcomes included progression-free survival and overall survival. No new safety signals were observed for TT/CPI. Post-hoc analysis of clinical features, circulating cytokines and chemokines at ctDNA nadir following TT induction suggested a more favourable profile prior to CPI initiation. Longitudinal ctDNA dynamics revealed ctDNA provided an early signal of CPI benefit and that rechallenge with TT following CPI progression resulted in a further ctDNA response. These data support the utility of ctDNA to guide treatment decision-making within a clinically relevant timeframe to optimise treatment scheduling strategies. Targeted therapy (with BRAF and MEK inhibitors) and immune checkpoint blockade have improved survival for patients with advanced BRAF-mutant cutaneous melanoma, however, the optimal scheduling for these treatments remain to be further refined in poor prognosis groups. Here the authors present the results of a feasibility trial to determine the role of circulating tumour DNA in guiding a switch between targeted therapy and immune therapy in patients with advanced melanoma.

Immunotherapy has revolutionized cancer treatment, yet only a minority of individuals respond clinically, necessitating alternative strategies that can benefit these patients. Novel immuno-oncology targets may achieve this through bypassing resistance mechanisms to standard therapies. We introduce Mining Immunotherapy Drug tArgetS (MIDAS), a multimodal graph neural network system for immuno-oncology target discovery. MIDAS leverages gene interactions, multi-omic patient profiles, immune cell biology, antigen processing, disease associations and phenotypic consequences of genetic perturbations. It generalizes to time-sliced data, outcompetes state-of-the-art baselines (including OpenTargets) and ranks approved targets above those in clinical development. Moreover, MIDAS recovers immunotherapy-response-associated genes in unseen patients, thereby capturing immunotherapy response determinants. Interpretability analyses reveal a reliance on autoimmunity, regulatory networks and immuno-oncology pathways. Functionally perturbing oncostatin M–oncostatin M receptor signalling, a proposed MIDAS target, in TRACERx melanoma-patient-derived explants yielded reduced dysfunctional CD8+ T cells, which associate with immunotherapy response, and reduced CCL4 levels. Furthermore, oncostatin M and oncostatin M receptor expression is associated with altered T cell and macrophage profiles in bulk transcriptomic data from patient samples. These data are consistent with a role for oncostatin M–oncostatin M in modulating the tumour microenvironment towards immunosuppressive, tumour-promoting phenotypes. Our results present a machine learning framework for analysing multimodal data for immuno-oncology target discovery. Augustine et al. present a multimodal graph neural network that identifies cancer immunotherapy targets. It distinguishes approved and prospective targets, and promising candidates are validated using a clinically relevant patient-derived platform.

Clear Cell Renal Cell Carcinoma (ccRCC) is the most common and aggressive type of kidney cancer. ccRCC originates from proximal tubule (PT) epithelial cells in the nephron. Its initiation is characterised by a linear evolution from the loss of one copy of chromosome 3p to the inactivation of the second VHL allele on the remaining copy of 3p. Computational studies established that 3p loss occurs several decades before diagnosis. This offers an unprecedented window of opportunity for early detection, cancer prevention and for broader pan-cancer learning. However, the biological mechanisms driving the pre-cancerous expansion of PT cells harboring these events remain elusive. One of the major unmet needs in ccRCC initiation is the identification of molecular biomarkers for the initially quiescent tumor-initiating cell. Previous studies established that the putative ccRCC cell of origin (COO) is a subtype of PT cells characterized by VCAM1 expression, a marker of tubular injury in human kidneys. Therefore, we hypothesized that VCAM1 can be used as a marker to enrich for cells that have lost a copy of chromosome 3p. Preliminary single-cell whole genome sequencing (WGS) of VCAM1+ PT cells revealed a high incidence of aneuploidies, including chromosome 3-related aneuploidies, indicating that these cells represent a chromosomally unstable epithelial subpopulation within morphologically normal kidney tissue. Therefore, this data supports VCAM1 as a candidate marker for the study of ccRCC initiation in human kidneys.Despite its quasi-ubiquitous role in ccRCC initiation, several studies show that VHL inactivation is insufficient for tumorigenesis in mammalian kidneys. To study this, we used histological analysis of VHL patient-derived normal kidney tissues, where 3p loss occurs on the background of a germline VHL mutation. We demonstrated that VHL inactivation (marked by CAIX expression) occurs in all major cortical epithelial cell types. Surprisingly, only the proportion of CAIX+ distal tubule (DT) cells showed a significant correlation with the age of the patient at the time of tissue collection. In addition, there is a significantly higher proportion of multicellular DT CAIX+ foci compared to CAIX+ PT foci, suggesting clonal expansion after VHL inactivation is favored in DT cells. Only a minority of CAIX+ PT foci were multicellular, indicating that unknown cell-intrinsic or extrinsic factors are necessary for clonal expansion. Results from our cohort show a positive association between the density of VCAM1+ PT cells and CAIX+ PT in VHL patient-derived normal kidney tissues, indicating that tissue stress levels may potentiate the selection and expansion of VHL inactivation in the human kidney. Our data offers novel insight in the putative COO of ccRCC and the mechanisms driving the earliest stages of ccRCC. Moving forward, we plan to expand our cohort and molecularly profile VCAM1+ and CAIX+ cells using multi-omic approaches. Omar Bouricha, Daqi Deng, Anne-Laure Cattin, Matous Elphick, Scott Shepherd, Cathy D. Vocke, W. Marston Linehan, Samra Turajlic. Spatial and molecular profiling of tumor initiation in ccRCC [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 3330.

Neoantigens from somatic tumor mutations are essential for effective anti-tumor immune responses. Frameshift insertions and deletions (fs-indels) represent a rare but highly immunogenic mutation subtype, as they create novel open reading frames (neoORFs) that generate peptides that are significantly distinct from self-antigens. Nevertheless, fs-indels often introduce premature termination codons, leading to transcript degradation via the nonsense-mediated mRNA decay (NMD) pathway, leading to loss of immunogenic neoantigen. For the first time, we pharmacologically inhibited SMG1, a core component of the NMD pathway, across a range of preclinical models, including human and mouse cancer cell lines, patient-derived tumor organoids (PDTOs), patient-derived tumor fragments (PDTFs), and syngeneic mouse xenografts. We analyzed the changes in transcriptome, proteome, and immunopeptidome following SMG1 inhibition (SMG1i) and peptide reactivity in in vitro priming experiments. We then combined tumor-T cell co-cultures and PDTFs to assess the anti-tumor immunogenicity induced by SMG1i. Ex vivo and in vivo immunological responses were assessed by high-dimensional flow cytometry, cytometric bead array, and single-cell RNA- and TCR-sequencing. Using multi-omic and checkpoint inhibitor (CPI) response data from over 1,000 patients, we show that decreased expression of the key NMD mediator, SMG1, correlates with improved CPI response. Inhibiting SMG1 ex vivo and in vivo activates and expands tumor-reactive T cells and sensitizes CPI efficacy. Mechanistically, SMG1 inhibition stabilizes frameshift-derived transcripts, increasing the abundance and surface presentation of immunogenic neoantigens. This results in an increase in neoepitope burden in tumors, similar to that seen in tumors with high tumor mutational burden (TMB), without inducing DNA damage. Co-culturing tumor cells and PDTOs with CD8+ T cells after SMG1i results in strong MHC class I antigen-dependent T cell activation and tumor cell killing. Our findings highlight SMG1 inhibition as a promising strategy to exploit an untapped source of highly immunogenic peptides. It enhances anti-tumor immunogenicity without introducing DNA mutations, regardless of tumor type or TMB status, providing translational evidence for sensitizing ICB responses. Hongchang Fu, Roberto Vendramin, Shanila Fernandez Patel, Yue Zhao, Danwen Qian, Lorena Ligammari, Osnat Bartok, Polina Greenberg, Ronen Levy, Andrea Castro, Krupa Thakkar, Jun Murai, Wei-ting Lu, Christopher C. Sng, Chen Weller, Gordon Beattie, Amandeep Bhamra, Roc Farriol-Duran, Despoina Karagianni, Marcellus Augustine, Krijn Djikstra, Christopher L. Pinder, Benjamin S. Simpson, Gordon Weng-Kit Cheung, TRACERx Consortium, Felipe Galvez Cancino, Petra Vlckova, Silvia Surinova, Manuel Rodriguez-Justo, Mansi Shah, Nicholas McGranahan, Jeremy G. Carlton, Eva Camilla Gronroos, Sergio Quezada, James Luke Reading, Samra Turajlic, Yardena Samuels, Charles Swanton, Kevin Litchfield. Nonsense-mediated mRNA decay inhibition augments in vitro, in vivo, and ex vivo anti-tumor immunity [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 6742.

OBJECTIVES We sought to identify factors associated with prognosis and bleeding in patients with melanoma brain metastases(BM).Objectives were median overall survival (mOS [months]) and bleeding incidence. METHODS We conducted a retrospective analysis of patients receiving SRS at our center 11/1511/23.Analysis was performed on Prism 10.1.1.Extraction from electronic medical records was undertaken by authors, with local R&D approval(NEU012). RESULTS 81 patients were evaluable. 119 treatment courses were delivered. There were no bleeding events (BE) in the first 7 days , 1 within 28 days(0.8%) and 19 within 90 days(16%).7.6%(N = 9) died within 90 days and 25.2%(N = 30) died within 6 m. There were no deaths within 30 days or related to treatment.mOS was 17.6 m(95% CI 9.20-35.05).Significantly inferior survival outcomes were observed for patients with elevated lactate dehydrogenase(LDH),poor performance status(Karnofsky performance status [KPS]),higher total treated intracranial volume(GTV) and total number of BM.mOS of patients with a normal LDH was 37.0 m vs 5.2 m for those with LDH >ULN(HR 4.40, P<.0001).This was also true on multivariable analysis including KPS, BM number and BM size(HR 3.75 95%CI 1.94-7.30, p = <0.0001).For patients with KPS ≥90 mOS was 35.0 m vs 7.7 m for KPS ≤80(HR 2.55, P<.0004).This was significant using the multivariable analysis described above(HR 2.12 95%CI 1.123-3.948, p = 0.0181). CONCLUSIONS Despite theoretically high risk of bleeding after SRS in MM BM, incidence of bleeding in our cohort was low.mOS was comparable to historical controls of 16-23 months. ADVANCES IN KNOWLEDGE We novelly performed univariate and multivariate analysis demonstrating poor survival outcomes in patients with high LDH, poor performance status and larger brain metastases (both by BM size and number).

The identification of cancer drivers is a cornerstone to delivery of precision oncology. So far sequencing of renal cell cancer (RCC) has largely been confined to the clear cell subtype of RCC. In contrast, sequencing analyses of the less common forms of RCC, papillary RCC (pRCC) and chromophobe RCC (ChRCC), have so far been limited. We analysed whole genome sequencing data on 164 tumour-normal pairs from the Genomics England 100,000 Genomes Project, providing a comprehensive, high-resolution map of copy number alterations, structural variation, and key global genomic features, including mutational signatures, intra-tumour heterogeneity and analysis of extrachromosomal DNA formation. Our research establishes correlations between genomic alterations and histological diversification and the extent to which genetically-mediated immune escape contributes to the development of these RCC subtypes. Implications We demonstrate the distinctive genetics which characterises pRCC and ChRCC and how this information has the potential to inform patient treatment and clinical trials.

Type 1 conventional dendritic cells (cDC1s) acquire and cross-present tumor antigens to prime CD8⁺ T cells. Whether this selects for specific neoantigens is unclear. DNGR-1 (CLEC9A), a cDC1 receptor for F-actin exposed on dead cells, promotes cross-presentation of cell-associated antigens. Here we show that DNGR-1-deficient mice develop chemically induced tumors more rapidly and at higher incidence, and these are more frequently rejected on transplantation into wild-type recipients. Whole-exome sequencing reveals enrichment of predicted neoantigens derived from mutated F-actin-binding proteins. Consistent with this observation, tethering model antigens to F-actin enhances DNGR-1-dependent cross-presentation. These results suggest that DNGR-1-mediated recognition of F-actin exposed by dead cancer cells favors priming of CD8⁺ T cells specific for cytoskeletal neoantigens, which can then drive immune escape of cancer cells lacking or reverting those mutations. Thus, neoantigen cross-presentation by cDC1 can determine the immune visibility of the tumor mutational landscape and sculpt cancer evolution by immunoediting. Here the authors show DNGR-1 expressed by cDC1s promotes CD8⁺ T cell priming to cytoskeletal neoantigens from dying tumor cells, thereby shaping cancer immune visibility and tumor evolution through immunoediting.

The Tracking Cancer Evolution Through Therapy (TRACERx) program represents the most comprehensive effort to characterize tumor evolution in real time. Through longitudinal, multiregion, and multiomic profiling of tumors—and particularly of non-small-cell lung cancer and clear cell renal cell carcinoma—TRACERx has illuminated the dynamic interplay between genetic, nongenetic, and (micro)environmental factors that drive cancer progression, immune evasion, and therapeutic resistance. A central insight from TRACERx has been that not all tumor evolution is genomic: Transcriptomic diversity, epigenetic alterations, RNA editing, and changes in cell–cell interactions also drive adaptation. Methodological innovations—including tumor-informed and ultrasensitive circulating tumor DNA assays, representative sequencing, and integrative immune–genomic analyses—have yielded biomarkers resistant to sampling bias and/or predictive of recurrence, metastasis, and treatment response. By demonstrating that intratumor heterogeneity is a key determinant of clinical outcome and revealing its molecular, transcriptional, and ecosystem-level drivers, TRACERx has established a framework for linking evolutionary dynamics to patient care. As both a scientific framework and a clinical paradigm, TRACERx demonstrates how adaptive, iterative research can refine evolutionary models, improve patient risk stratification, and inspire next-generation cancer evolution studies across malignancies.

The extent to which exogenous sources, including cancer treatment, contribute to somatic evolution in normal tissue remains unclear. Here we used high-depth duplex sequencing1 (more than 30,000× coverage) to analyse 168 cancer-free samples representing 16 organs from 22 patients with metastatic cancer enroled in the PEACE research autopsy study. In every sample, we identified somatic mutations (range 305–2,854 mutations) at low variant allele frequencies (median 0.0000323). We extracted 16 distinct single-base substitution mutational signatures, reflecting processes that have moulded the genomes of normal cells. We identified alcohol-induced mutation acquisition in liver, smoking-induced mutagenesis in lung and cardiac tissue, and multiple treatment-induced processes, which correlated with therapy type and duration. Exogenous sources, including treatment, underpinned, on average, more than 40% of mutations in liver but less than 10% of mutations in brain samples. Finally, we observed tissue-specific selection, with positive selection in tissues such as lung (PTEN and PIK3CA), liver (NF2L2) and spleen (BRAF and NOTCH2), and limited selection in others, such as brain and cardiac tissue. More than 25% of driver mutations in normal tissue exposed to systemic anti-cancer therapy, including in TP53, could be attributed to treatment. Immunotherapy, although not associated with increased mutagenesis, was linked to driver mutations in PPM1D and TP53, illustrating how non-mutagenic treatment can sculpt somatic evolution. Our study reveals the rich tapestry of mutational processes and driver mutations in normal tissue, and the profound effect of lifetime exposures, including cancer treatment, on somatic evolution. High-depth sequencing of non-cancerous tissue from patients with metastatic cancer reveals single-base mutational signatures of alcohol, smoking and cancer treatments, and reveals how exogenous factors, including cancer therapies, affect somatic cell evolution.

Driver mutations in IDH1 and IDH2 are initiating events in the evolution of chondrosarcoma and several other cancer types. Here, we present evidence that mutant IDH1 is recurrently lost in metastatic central chondrosarcoma. This may reflect either relaxed positive selection for the mutant IDH1 locus, or negative selection for the hypermethylation phenotype later in tumor evolution. This finding highlights the challenge for therapeutic intervention by mutant IDH1 inhibitors in chondrosarcoma.

Classical models of cancer focus on tumour-intrinsic genetic aberrations and immune dynamics and often overlook how the metabolic environment of healthy tissues shapes tumour development and immune efficacy. Here, we propose that tissue-intrinsic metabolic intensity and waste-handling capacity act as an upstream gatekeeper of anti-tumour immunity, determining whether immune infiltration translates into effective immune function and safeguards the tissue from tumourigenesis. Across human cancers, tumours arising in high-metabolism tissues – like kidney, brain, and eye – tend to show high T cell infiltration but poor prognosis, suggesting pre-existing metabolic environments prior to malignant transformation may undermine immune function. This pattern is mirrored across species: large mammals with lower mass-specific metabolic rates (e.g., elephants, whales) accumulate fewer metabolic byproducts and show lower cancer incidence (Peto’s paradox), while long-lived small mammals like bats and naked mole-rats resist tumourigenesis via suppressed glycolysis or altered hypoxia responses leading to lower metabolic rates and/or byproduct accumulation. Through integrative synthesis spanning human single-cell expression data and cross-species comparisons, we outline a framework of “immunometabolic gatekeeping,” where tissues with high metabolic rate and poor waste clearance foster immune-exhausting niches even before transformation. This unifying framework reconciles multiple paradoxes in cancer biology: Peto’s paradox, T cell infiltration non-prognosticity, tissue tropisms, sex-based inequalities, and size-based tipping points (e.g., the 3 cm rule in ccRCC), and suggests new principles for identifying high-risk patients and metabolic-immune combination strategies for prevention and treatment. By shifting focus from tumour-intrinsic mutations to host-tissue metabolism, this work offers a novel, integrative lens on cancer vulnerability and immune failure.