Immune checkpoint inhibition (ICI) has revolutionised cancer care, but many patients do not mount anti-tumor activity and most develop autoimmune toxicity. Mechanisms and risk factors underlying ICI response and immune related adverse events (irAEs) are incompletely understood. Thus, patient stratification and targeted irAE treatments are significant unmet clinical needs. Here, we use high-throughput spectral cytometry with machine-learning based analytics to characterise longitudinal immune dynamics under ICI. 706 cryopreserved PBMC samples from 137 patients consented to the EXACT study (NCT05331066) were utilised. All patients received standard of care adjuvant or advanced ICI for skin or renal cancer. Best overall response was annotated per RECIST 1.1(Responders: CR, PR, SD > 6 months). Patients on adjuvant ICI were designated as no-relapse at > 6 months from ICI initiation. irAEs were graded per CTCAE v5 and grade ≥3 considered severe. PBMCs were stained with 3 antibody panels comprising 114 markers. Data was acquired on a Sony ID7000 spectral analyser. Systems-level characterisation of 23,906 discrete PBMC subsets per sample was performed using IMU Biosciences’ proprietary machine learning platform. Following data QC, feature selection was refined through titration, variance, and correlation filtering. Predictive PBMC signatures were derived at baseline(BL) and C2 using univariate feature selection with bootstrapping followed by stepwise logistic regression, then validated through 100 iterations of 80:20 cross validation. PBMC types associated with irAE onset(Dev), increasing severity(Inc), and resolution(Res) compared to non-irAE on treatment controls were determined (t-test in a linear mixed effects model). Using these cell types, we then repurposed the Slingshot pseudotime method to derive patient trajectories from BL to Dev, and progression to Inc and/or Res. Benefit(responder/no-relapse) prediction achieved AUCs (mean ± SD) of 0.814±0.11 (BL), and 0.85±0.10 (C2). Severe irAE prediction achieved AUCs of 0.84±0.08 (BL), and 0.82±0.13 (C2). Dev and Inc samples of severe irAEs showed significant enrichment of activated non-classical monocytes, CD4 T, CD8 T, gd T, and NK cells. Dev of non-severe irAEs was indistinguishable from controls. In pseudotime, we found a bifurcating trajectory from BL to severe Dev vs. non-severe Dev. A further bifurcating trajectory distinguished progression from BL to on-treatment, then Dev vs. BL to Dev, then Inc. Res represented a return towards on-treatment controls in both lineages. Here, we used high-content PBMC profiling to generate immune signatures predictive of ICI outcome with compelling accuracy. We additionally gain mechanistic insights into irAE development and progression to severity. Our findings highlight the transformative potential of machine learning-powered immune profiling to identify predictors and drivers of benefit and toxicity outcomes under ICI with clear implications for patient stratification and irAE management. Max Emmerich, Duncan McKenzie, Carla Castignani, Jack Bibby, Jennie Yang, Marija Miletic, Laura Marandino, Zayd Tippu, Jonathan Lim, Taja Barber, Stephanie Hepworth, Paul Rouse, Lilian Williams, Kim Edmonds, Justine Korteweg, Serena Vanzan, James Larkin, Tom Hayday, Adam Laing, Samra Turajlic. Comprehensive blood profiling for immunotherapy outcome prediction and longitudinal immune trajectory characterisation [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Mechanisms of Cancer Immunity and Cancer-related Autoimmunity; 2025 Sep 24-27; Montreal, QC, Canada. Philadelphia (PA): AACR; Cancer Immunol Res 2025;13(9 Suppl):Abstract nr A002.

B-1 cells are innate-like immune cells abundant in serosal cavities with antibodies enriched in bacterial recognition, yet their existence in humans has been controversial1, 2–3. The CD5+ B-1a subset expresses anti-inflammatory molecules including IL-10, PDL1 and CTLA4 and can be immunoregulatory4, 5–6. Unlike conventional B cells that are continuously replenished, B-1a cells are produced early in life and maintained through self-renewal7. Here we show that the transcription factors TCF1 and LEF1 are critical regulators of B-1a cells. LEF1 expression is highest in fetal and bone marrow B-1 progenitors, whereas the levels of TCF1 are higher in splenic and peritoneal B-1 cells than in B-1 progenitors. TCF1–LEF1 double deficient mice have reduced B-1a cells and defective B-1a cell maintenance. These transcription factors promote MYC-dependent metabolic pathways and induce a stem-like population upon activation, partly via IL-10 production. In the absence of TCF1 and LEF1, B-1 cells proliferate excessively and acquire an exhausted phenotype with reduced IL-10 and PDL1 expression. Furthermore, adoptive transfer of B-1 cells lacking TCF1 and LEF1 fails to suppress brain inflammation. These transcription factors are also expressed in human chronic lymphocytic leukaemia B cells and in a B-1-like population that is abundant in pleural fluid and circulation of some patients with pleural infection. Our findings define a TCF1–LEF1-driven transcriptional program that integrates stemness and regulatory function in B-1a cells. The transcription factors TCF1 and LEF1 promote self-renewal and regulatory functions in B-1a cells.

UK Guidelines for the management of uveal melanoma (UM) were first published in 2015 using an evidence-based systematic approach. The primary aim of this guideline was to optimise patient care by providing recommendations based on the best available scientific evidence. The resulting guideline reflected the strengths and weaknesses of the available evidence, made recommendations that were clinically impactful around prognostication, surveillance, and treatment for patients with primary lesions and metastatic disease. The guideline development process and content met the standards required by NICE and were ultimately NICE accredited. Here, we present an update to these guidelines, highlighting where practice or treatment has changed to such an extent that the original recommendations are now out of date. Presented here are updated guidelines on molecular and genetic testing, management of metastatic disease and clinical surveillance.

Immune checkpoint inhibitors (ICI) have had a dramatic effect on cancer outcomes with their use increasing as indications expand. Despite impressive efficacy across a range of tumour types, their role in activating the immune system results in frequent immune-related adverse events (irAE). While gastrointestinal, endocrine, respiratory and cutaneous toxicities are common, neurological irAEs (N-irAEs) occur more rarely. N-irAEs have been well reported in the literature, can affect any part of the nervous system and are associated with significant morbidity and mortality. Treating oncologists have a high index of suspicion for irAEs and a low threshold for initiating treatment. The role of the neurologist is to consider the differential diagnosis, direct investigation according to the clinical syndrome and guide management, efficacy monitoring and rehabilitation. Once alternative aetiologies have been excluded, the ICI should be either paused or discontinued depending on clinical severity, and immunosuppressive treatment commenced. There is no high-level evidence for toxicity management in this emerging field, so there is much variation in clinical practice and the medical literature. While describing the range of neurological toxicities related to ICIs and current experience of management and outcome, this review focuses on the potential utility of predictive biomarkers, the risk of re-ignition of pre-existing neurological autoimmune disease and the question of rechallenge after a N-irAE. Given the paucity of data specifically relating to N-irAE, we also discuss cancer outcomes in the context of irAEs and associated immunosuppression and consider some outstanding questions pertinent to ICI-related neurotoxicity and potential future directions for research.

Immunotherapy has revolutionized survival outcomes for many patients diagnosed with cancer. However, biomarkers that can reliably distinguish treatment responders from nonresponders, predict potential life-threatening and life-changing drug-induced toxicities, or rationalize treatment choices are still lacking. In response to this unmet clinical need, we introduce Multiomic ANalysis of Immunotherapy Features Evidencing Success and Toxicity, a tumor type-agnostic platform to provide deep profiling of patients receiving immunotherapy that will enable integrative identification of biomarkers and discovery of novel targets using artificial intelligence and machine learning.

Flow cytometry is a well-established method to analyze cell populations using antibody-based fluorescent detection of protein biomarkers. In this study, we demonstrate the ability to generate intact single cells and perform flow cytometry analysis with two types of formalin fixed tissue: FFPE curls and Representative Samples (RS). RS are homogenized, well-mixed tissue samples from formalin fixed tumors dissected from leftover surgical material. We demonstrate biomarker expression results which correlate with IHC scores. This new method for biomarker quantification may be considered alongside other methods (e.g. digital pathology). Intact single cells were dissociated from RS and FFPE curls using a non-enzymatic, mechanical dissociation method. Cells were stained in suspension for Cytokeratin 8&18 (CK8&18), Ki67, Her2, and DNA content was assessed via DAPI staining and analyzed by flow cytometry. Samples were analyzed on a BD FACSMelody or BD LSR II flow cytometer, and analysis was performed using FCS Express 7 software. Immunohistochemistry (IHC) was performed on the Benchmark ULTRA to compare Ki67 expression (n=78) and Her2 expression (n=16) to the flow analysis. Ki67 expression by IHC was assessed using the international Ki67 working group scoring methods to generate a positive percentage. Her2 expression by IHC was assessed by a pathologist and assigned a score ranging 0 to 3+. Formalin fixed tissue such as RS and FFPE curls can be mechanically dissociated into single cells with intact surface biomarkers. These single cells can be stained in suspension, analyzed via flow cytometry and generate correlating data with both weighted IHC-based scores and clinical IHC scores. The flow analysis of Her2 positive percentage correlates with the IHC scores showing an increasing trend and significant difference between scores for both FFPE and RS. Ki67 expression varied by tumor region using IHC analysis, however by flow cytometry showed a strong correlation with a weighted average across multiregional quantification of Ki67 expression. We demonstrate that millions of intact single cells can be generated from RS and FFPE curls for breast tissue, using non-enzymatic mechanical dissociation methods. Staining in suspension and flow cytometry analysis can be performed in a day for rapid biomarker quantification. Flow cytometry has the potential to analyze FFPE samples using workflows and technologies that have existed in the hematopathology space for decades. Samantha M. Hill, Hannah L. Veloz, Brian Hanley, Tracy Davis, Lisa L. Gallegos, Harold Sasano, Samra Turajlic, Nelson R. Alexander. Optimizing fixed flow cytometry for breast cancer biomarker expression in representative samples and FFPE curls [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 670.

ccRCC is marked by niches of immune evasion in late-stage disease, that are associated with resistance to immune checkpoint inhibitors (CPI). Intratumoral microbes are emerging as key modulators of the tumor immune microenvironment and may therefore play a yet unrecognised role in ccRCC disease progression and therapy resistance, marking them as potential biomarkers, and novel therapeutic targets. We extracted bacterial reads from three cohorts of treatment-naïve primary tumors and one cohort of pre- and post-CPI treated tumors: Genomics England Renal (GEL) (636 patients, WGS), TRACERx Renal (154 patients, 629 samples, WGS); TCGA Renal (494 patients, RNA) & ADAPTeR (15 patients, 56 samples, RNA). Bespoke denoising, and decontamination were applied. Live presence of intratumoral bacteria was confirmed through culture and RNAscope. Genera associated with survival were identified using ElasticNet feature selection. We observed significant heterogeneity in bacterial abundance within and across tumors, driven by differences in Cutibacterium abundance. Cutibacterium makes up ∼90% of bacteria in each tumor sample and is enriched in tumors compared to adjacent normal tissue (p=7.1e-10). 9 of 11 colonies grown from two positive tumors were genotyped as Cutibacterium acnes, confirming its live presence and relative abundance in ccRCC tumors. Cutibacterium is higher in late-stage tumors (III&IV) than early-stage tumors (I&II)(p=7.8e-3). Its abundance also separates patients by progression free survival (PFS) and overall survival (OS) (p=9.9e-3, p=0.016) and is higher in CPI non-responders than responders (p=0.028). Association with survival is confirmed in the TCGA cohort independently of stage (PFS = 0.031, OS = 7.3e-4). While other genera associate with survival in either TRACERx or TCGA, only Cutibacterium is prognostic in both. Enrichment analyses of bulk RNA (TRACERx & TCGA), show upregulation of leukocyte taxis and innate immune response with Cutibacterium abundance. To further probe this interaction with the immune microenvironment we are performing single cell spatial transcriptomics, and in vitro co-cultures. Results of these ongoing experiments will be presented at the conference. Cutibacterium either creates or exploits a disease- and CPI-resistance-promoting environment in ccRCC tumors and can therefore act as a prognostic and predictive biomarker. The genus is known for causing chronic inflammation in sebaceous skin follicles, induces Nf-kB signalling, and M2-macrophage differentiation in vitro, and associates with myeloid response in ccRCC tumors. Together this supports a compelling hypothesis that Cutibacterium reduces survival in ccRCC by creating immunosuppressive niches, thereby fostering disease progression and CPI-resistance. Alice C. Martin, Anne-Laure Cattin, Irene Lobon, Zayd Tippu, Fiona Byrne, Charlotte Spencer, Clara Becker, Martha Zepeda Rivera, Krupa Thakkar, Hongui Cha, Angel Fernandez-Sanroman, Annika Fendler, Taja Barber, Leo Bickley, Daqi Deng, Scott Shepherd, Parise Lockwood, Maximiliano Gutierrez, Susan Bullman, Kevin Litchfield, Samra Turajlic. Intratumoral bacteria predict survival in clear cell renal cell carcinoma (ccRCC) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 2207.

Differentiating sequencing errors from true variants is a central genomics challenge, calling for error suppression strategies that balance costs and sensitivity. For example, circulating cell-free DNA (ccfDNA) sequencing for cancer monitoring is limited by sparsity of circulating tumor DNA, abundance of genomic material in samples and preanalytical error rates. Whole-genome sequencing (WGS) can overcome the low abundance of ccfDNA by integrating signals across the mutation landscape, but higher costs limit its wide adoption. Here, we applied deep (~120×) lower-cost WGS (Ultima Genomics) for tumor-informed circulating tumor DNA detection within the part-per-million range. We further leveraged lower-cost sequencing by developing duplex error-corrected WGS of ccfDNA, achieving 7.7 × 10−7 error rates, allowing us to assess disease burden in individuals with melanoma and urothelial cancer without matched tumor sequencing. This error-corrected WGS approach will have broad applicability across genomics, allowing for accurate calling of low-abundance variants at efficient cost and enabling deeper mapping of somatic mosaicism as an emerging central aspect of aging and disease. This work integrates duplex sequencing with cost-effective Ultima sequencing to enhance the accuracy of whole-genome circulating cell-free DNA profiling.

572 Background: Anti-vascular endothelial growth factor (VEGF) tyrosine kinase inhibitors and checkpoint inhibitors (CPI) a standard-of-care treatment for clear cell renal cell carcinoma (ccRCC). We investigated the biology underpinning benefit of anti-VEGFR TKI in the phase II A-PREDICT trial (NCT01693822), evaluating pre- and post-treatment, fresh multiregion tumour biopsies in patients with metastatic ccRCC treated with first-line axitinib. Methods: We analysed 123 tumour samples from 52 patients, 28 with paired pre/post-treatment samples. Post-treatment samples included week-9, nephrectomy, and on-progression timepoints. ‘Responders’ had progression-free survival (PFS) ≥6 months (n=35), ‘non-responders’ with PFS <6 months (n=17). We applied a custom Nanostring panel for gene expression analysis and multiplex immunofluorescence (mIF) for orthogonal validation. Wilcoxin test was used to analyze paired observations. Results: At baseline, angiogenesis scores were similar between responders and non-responders (p=0.22). Post-treatment, the angiogenesis, vascular sprouting, and endothelial cell proliferation signature scores were significantly decreased (p=0.023, 0.0034, & 0.0082, respectively) in all patients, suggesting suppression of angiogenesis and neovascularisation irrespective of clinical outcomes. mIF in 3 patients (with PFS of 3, 5.6, & 100 months) confirms widespread intratumoral vessel depletion. Immune deconvolution analysis shows total levels of T cells and CD8 + T cells were similar pre- and post-treatment, suggesting axitinib did not enhance immune cell trafficking. Rather, axitinib promoted increased levels of exhausted CD8 + T cells post-treatment (p=0.01). M2 tumour-associated macrophages increased post-treatment in responders (p=0.033) but not in non-responders (p=0.44). A minority of patients had durable (>2 years) responses to axitinib (n=7/65, 6 with tissue for analysis). In these patients, we found higher levels of pre-treatment intratumoral cytotoxic immune cells (p=0.041) and NK cells (p=0.015) compared to patients with primary resistant disease. Conclusions: Axitinib suppressed angiogenesis and neovascularisation leading to intratumoral vessel depletion, and therapy response associates with features of an immunosuppressive TME. Baseline endogenous immune priming appears critical for durable response to anti-VEGF therapy. These data are relevant to understanding the clinical efficacy of combined anti-VEGF and CPI regimens. Clinical trial information: NCT01693822 .

A genomic and transcriptomic analysis of patients with clear-cell renal cell carcinoma reveals clinically relevant patterns of nongenetic evolution, including progressive immune dysfunction and cGAS–STING suppression.

Self-supervised foundation models for digital pathology encode small patches from H\&E whole slide images into latent representations used for downstream tasks. However, the invariance of these representations to patch rotation remains unexplored. This study investigates the rotational invariance of latent representations across twelve foundation models by quantifying the alignment between non-rotated and rotated patches using mutual $k$-nearest neighbours and cosine distance. Models that incorporated rotation augmentation during self-supervised training exhibited significantly greater invariance to rotations. We hypothesise that the absence of rotational inductive bias in the transformer architecture necessitates rotation augmentation during training to achieve learned invariance. Code: https://github.com/MatousE/rot-invariance-analysis.

VHL disease is an inherited and autosomal dominant disorder affecting 1 in 36,0000 individuals worldwide. It is caused by von Hippel-Lindau (VHL) gene mutations and can affect both genders and all ethnic backgrounds (Nordstrom-O'Brien et al., 2009; Maher, 2004). Here, we generated and characterised two iPSC lines derived from patients with histopathologically confirmed clear cell renal cell carcinoma (ccRCC) and VHL Type 1 enrolled in the TRACERx Renal (TRAcking Renal Cell Carcinoma Evolution Through Therapy (Rx)). PBMCs were reprogrammed to pluripotency using a genome non-integrating Sendai virus (SeV) vectors protocol. Both human iPSC lines displayed normal morphology, expressed markers associated with stemness and differentiated into the three germ layers. The iPSC lines could be used as a disease-specific cellular model to understand furtherthe inherited disorder of Type 1 von Hippel-Lindau (VHL) disease.

CONTEXT Immune-oncology strategies are revolutionising the perioperative treatment in several tumour types. The perioperative setting of renal cell carcinoma (RCC) is an evolving field, and the advent of immunotherapy is producing significant advances. OBJECTIVE To critically review the potential pros and cons of adjuvant and neoadjuvant immune-based therapeutic strategies in RCC, and to provide insights for future research in this field. EVIDENCE ACQUISITION We performed a collaborative narrative review of the existing literature. EVIDENCE SYNTHESIS Adjuvant immunotherapy with pembrolizumab is a new standard of care for patients at a higher risk of recurrence after nephrectomy, demonstrating a disease-free survival and overall survival benefit in the phase 3 KEYNOTE-564 trial. Current data do not support neoadjuvant therapy use outside clinical trials. While both adjuvant and neoadjuvant immune-based approaches are driven by robust biological rationale, neoadjuvant immunotherapy may enable a stronger and more durable antitumour immune response. If neoadjuvant single-agent immune checkpoint inhibitors demonstrated limited activity on the primary tumour, immune-based combinations may show increased activity. Overtreatment and a risk of relevant toxicity for patients who are cured by surgery alone are common concerns for both neoadjuvant and adjuvant strategies. Biomarkers helping patient selection and treatment deintensification are lacking in RCC. No results from randomised trials comparing neoadjuvant or perioperative immune-based therapy with adjuvant immunotherapy are available. CONCLUSIONS Adjuvant immunotherapy is a new standard of care in RCC. Both neoadjuvant and adjuvant immunotherapy strategies have potential advantages and disadvantages. Optimising perioperative treatment strategies is nuanced, with the role of neoadjuvant immune-based therapies yet to be defined. Given strong biological rationale for a pre/perioperative approach, there is a need for prospective clinical trials to determine clinical efficacy. Research investigating biomarkers aiding patient selection and treatment deintensification strategies is needed. PATIENT SUMMARY Immunotherapy is transforming the treatment of kidney cancer. In this review, we looked at the studies investigating immunotherapy strategies before and/or after surgery for patients with kidney cancer to assess potential pros and cons. We concluded that both neoadjuvant and adjuvant immunotherapy strategies may have potential advantages and disadvantages. While immunotherapy administered after surgery is already a standard of care, immunotherapy before surgery should be better investigated in future studies. Future trials should also focus on the selection of patients in order to spare toxicity for patients who will be cured by surgery alone.