Tumors foster an immunosuppressive microenvironment to evade the antitumor immune response. However, the influence of intratumoral immunosuppressive steroids on tumor-infiltrating natural killer (NK) cells and their implications for effective immunotherapy has remained largely unexplored. Here, we report that the functional enrichment of glucocorticoid cortisol signaling in the lung tumor microenvironment (TME) impairs NK cell anti-tumor cytotoxicity and exacerbates hypoxic stress. Cancer-associated fibroblasts (CAFs) and macrophages convert inactive cortisone to active cortisol, while T cells, fibroblasts, myeloid cells, macrophages, and cancer cells contribute to de novo steroid biosynthesis, collectively establishing a steroid-rich niche. Pharmacological inhibition of the glucocorticoid receptor (GR) in vivo alleviates cortisol-mediated immune suppression, resulting in reduced tumor growth and enhanced cytotoxicity of tumor-infiltrating NK cells. To overcome the cortisol-induced dysfunction of solid tumor targeting immunotherapy, we engineered chimeric antigen receptor (CAR) -NK cells specific to the Carcinoembryonic antigen-related cell adhesion molecule 5 (CEACAM5) (highly expressed in lung tumors) and rendered them cortisol-resistant by genetic deletion of the cortisol receptor gene NR3C1. In cortisol-rich niches, cortisol-resistant CAR-NK cells sustained antitumor cytotoxicity. Mechanistically, NR3C1 deletion relieved cortisol-mediated suppression of PI3K-AKT-NF-κB signaling, restored anti-tumor activity, and markedly reduced hypoxic stress. In lung metastasis models, cortisol-resistant CAR-NK cells achieved superior tumor control and significantly reduced tumor burden compared with conventional CAR-NK cells. Together, these findings identify local cortisol signaling as a critical barrier to solid tumor immunotherapy and establish cortisol-resistant CAR-NK cells as a promising strategy for targeting steroidogenic solid tumors, which can be combined with therapeutic glucocorticoids.

Multiple myeloma (MM) is associated with skewed T cell activation and function which is present in asymptomatic myeloma precursor conditions, but underlying mechanisms of progression remain undefined. Here, we assemble a large single-cell RNA sequencing dataset of the bone marrow and blood from patients with MM, precursor conditions, and non-cancer controls. We demonstrate that, unlike solid cancers, MM is not characterized by T cell exhaustion, but by antigen-driven terminal memory differentiation. This is influenced by tumour-intrinsic features including tumour burden and expression of antigen-presentation genes. Expanded TCR clones accumulating in MM are not enriched with viral specificities but accumulate in effector states in highly-infiltrated marrows. Additionally, we identify a role for T cell dynamics in patients treated with autologous stem cell transplantation and demonstrate T cell features predict progression from precursor to symptomatic MM. Together, these results suggest that anti-tumour immunity drives a distinctive form of cancer-associated T cell differentiation in MM.

Tumour microenvironments (TME) accumulate immunosuppressive steroids, impairing NK cell anti-tumour immunity. We found glucocorticoid cortisol signalling enrichment in lung TME exacerbates hypoxic stress and impairs NK cell function. Single-cell transcriptomics revealed cancer-associated fibroblasts and macrophages convert inactive cortisone to active cortisol, while T cells, mast cells, and macrophages induce de novo steroid biosynthesis. Inhibiting the glucocorticoid receptor in mice reduced tumour growth and improved NK cell cytotoxicity.To overcome steroid-mediated immunosuppression, we engineered CEACAM5-specific CAR-NK cells with CRISPR-mediated deletion of the glucocorticoid receptor (NR3C1). These cortisol-resistant CAR-NK cells showed enhanced tumour cell killing efficacy, even in the presence of glucocorticoids. This approach offers promising applications against steroidogenic solid tumours and potential use alongside therapeutic glucocorticoids. Our study addresses a critical challenge in CAR-NK cell therapy for lung cancer - the immunosuppressive TME. By targeting CEACAM5, highly expressed in lung tumours, and making CAR-NK cells cortisol-resistant, we’ve developed a novel strategy to enhance the efficacy of immunotherapy in steroid-rich environments. This advancement could significantly improve outcomes for lung cancer patients, addressing limitations of current CAR-NK therapies in solid tumours. The work is supported by CRUK Career Development Fellowship (RCCFEL\100095), NSF-BIO/UKRI-BBSRC project grant (BB/V006126/1), MRC project grant (MR/V028995/1), CRUK Cambridge Centre Cancer Immunology Programme Pump Priming award, and CRUK CC MRes/PhD Studentship. Tumor Immunology: Cellular Responses and Tumor Microevironment (TIME)

Background: Clinical outcomes in transplant eligible (TE) newly diagnosed myeloma (NDMM) patients continue to improve, which highlight the persistent unmet need in patients with genetically high-risk disease. Recently published IMS/IMWG high risk criteria confirms poor outcomes in double-hit [2 high risk cytogenetic abnormalities (HRCA)] disease in comparison to patients with single HRCA (Avet-Loiseau JCO 2025). RADAR aimed to evaluate Isa-VRDc induction followed by single autologous stem cell transplant (ASCT), Isa-VRD consolidation and IsaR maintenance, in patients with ultra-high-risk disease. Study design/ Methods: UK-MRA RADAR is a prospective, national, multi-centre, risk-adapted, response-guided multi-arm, multi-stage (MAMS) phase II/III trial which aims to recruit 1400 patients with NDMM eligible for ASCT. Participants enter a high-risk pathway based on the presence of ≥2 HRCA (t(4;14), t(14;16), t(14:20), del(17p), del1p and gain(1q)) defined by standard-of-care cytogenetic (FISH/MLPA) testing. Participants with high-risk disease in v4 of the protocol (HRv4) received 4 x 21 day cycles of Isa-VRDc (Isa: Weekly C2, D1 and D8 C3, D1 and D15 C4; V: Weekly; R:D1-14; D:Weekly; c: D1 and D8). Participants received an ASCT followed by 4 x 21 day cycles of Isa-VRD consolidation (Isa: Weekly C1, D1 and D8 C2, D1 and D15 C3+; V: Weekly; R:D1-14; D:Weekly) and 28 day cycles of IsaR maintenance (Isa: Weekly C1, D1 and D15 C2; R: D1 – D21) until progression. Flow MRD testing (sensitivity 10-5) was done post-induction, post-transplant and 3, 6,12 and 18 months after starting consolidation. Primary endpoint was the proportion of patients alive and progression-free at 18 months. HRv4 followed a Sargent three-outcome phase II design. It was designed to test the null hypothesis (Ho) that the proportion of patients alive and progression-free at 18 months post-registration was ≤65.9% (based on data from Myeloma XI) against the alternative hypothesis of ≥81.7% (OPTIMUM, Kaiser Blood 2021). 70 patients were required for at least 80% power, testing at the 1-sided maximum 5% significance level with a 5% drop-out rate. Results: 70 participants were registered to HRv4 between 1Sept22 and 4Sept23. Median age was 60 yrs (range, 40-74). 84.3% of individuals were of white ethnicity. R-ISS staging proportions at diagnosis I/II/III/missing was 18.6%/67.1%/10.0%/4.3% respectively. All participants had 2 HRCA and 8/70 had ≥3 HRCA. Median follow up was 24 months (IQR, 21-26). 69/70 participants started induction treatment. 68/69 completed all four cycles. Adequate stem cell harvest was obtained in all eligible patients (62/68), and 61 proceeded to ASCT. 56 participants commenced post-ASCT treatment. Dose delivery was as per the protocol in >90% of all treatment cycles across the entire treatment pathway (induction, consolidation and maintenance). 67/70 participants were evaluable for primary endpoint. The cut-offs for the three-outcome design were: Red (do not reject Ho) ≤47 / 67, Amber (neither accept or reject Ho) 48 - 51 / 67, Green (reject Ho) ≥52 / 67. In total 59/67 participants were alive and progression-free at 18 months (88.1% (95%CI: 77.8-94.7)). ≥VGPR rates increased from 82.9% post induction to 87.5% post-transplant and were 96.2% and 85.7% at 6 and 12 months after starting consolidation. MRD negativity was 26.2% post-induction, 69.5% post-transplant and 69.6% and 59.5% at 6 and 12 months after starting consolidation. Of MRD negative participants post-ASCT with a sample available, 66.7% remained MRD negative 12 months after starting consolidation. A grade 3-4 adverse reaction was reported in 63.8% of participants. No treatment-related deaths have been reported. 47/69 (68.1%) participants had an SAE. Infections were the commonest SAE; 36/85 (42.4%) with 31/36 ≥G3 (86.1%).Conclusions: RADAR HRv4 pathway is the largest analysis of ultra-high risk (double hit) patients reported to date. All participants meet the new IMS/IMWG HR criteria. Isa-VRDc induction, followed by Isa-VRD consolidation post-ASCT and IsaR maintenance met the primary endpoint, with the study crossing the Green design threshold, with 88% (59/67) alive and progression-free at 18 months. These results compare favourably to the TE NDMM GMMG HD-7 trial which included standard and high-risk patients, and high-risk CONCEPT and OPTIMUM NDMM trials with extended consolidation

Introduction Multiple myeloma has a complex transcriptomic landscape with gene mutations, fusions, and spliced transcript isoforms all contributing to gene expression. Short-read multiomics studies have offered insights but lack the resolution to fully capture this complexity. Long-read RNA sequencing, with its ability to cover full RNA fragments allowing more accurate isoform mapping, could offer improved resolution into the transcriptomic landscape of myeloma. We have generated the first long-read RNA sequencing cohort of newly diagnosed myeloma (NDMM) patients from the UKMRA RADAR trial with the aim to assess its capture of expressed variants alongside gene expression in myeloma. Methods The UKMRA RADAR trial is a prospective, national, multi-centre, risk-adapted, response-guided multi-arm, multi-stage (MAMS) phase II/III trial in NDMM eligible for ASCT (ISRCTN46841867). We optimised both experimental and computational protocols for Oxford Nanopore Technologies (ONT) long-read RNA sequencing. High quality RNA was obtained from CD138+ selected diagnostic bone marrow cells. Primer optimisation using native ONT indexes and in-house homotrimer UMIs minimized concatenation and PCR bias. The resulting cDNA libraries were multiplexed and sequenced on the PromethION platform. We developed a novel quality control tool 'Splitfastqcats’ to ensure full length read filtering (mean length = 1085bp), followed by pre-processing and alignment using our in-house TallyTriN pipeline (mean mapped reads = 6.94 x 106 /sample). Prepublished long-read tools were compared for consensus: gene expression was called with Salmon; isoforms and splicing variants with Bambu and Flair; mutations with Clair3-RNA; and fusions with a consensus between Jaffal, CTAT-LR, genion and FusionSeeker. Stringent filtering was based on variant allele frequency (VAF), read depth, number of supporting reads, and high confidence calls from the given tool filter. Results were compared to targeted region DNA sequencing using the Myeloma Genome Panel (MGP) (PMID:35522533). Results Overall, baseline trial entry samples from 56 NDMM patients were analysed including 75% standard and 25% high risk patients. This represented the general myeloma population with 12%, 14%, and 5% bearing a t(4;14), t(11;14) and t(4;16) by FISH respectively. We were able to identify 100% of t(4;14) patients (n=7) by expression of the NSD2-IGH fusion transcript, as well as a subset of t(11;14) and t(14;16) patients by MYEOV-IGH/KMT5B-IGH (n=2, 25%) and MAF-IGH (n=1, 33%) fusions respectively. We defined a long-read Translocation-Cyclin (TC) classification that captured all IG translocations via overexpressed partner genes. In addition to differential transcript expression and isoform mapping, we also derived the location of the breakpoint of expressed IGH-fused transcripts, especially relevant as t(4;14) breakpoint clusters have been associated with differential risk. We were able to identify expressed known driver mutations described in the literature and concordant with MGP calls, including non-synonymous KRAS (n=17, 30%), NRAS (n=5, 9%) and DIS3 (n=4, 7%) mutations. Final comparison to the MGP will be presented at the conference. RNA editing sites in common driver UTRs and intronic regions were also highlighted, matching consensus sites in the REDIportal database, with the most edited genes including CHEK1 (n=6, 11%), IKZF3 (n=10, 18%), and PSMB2 (n=21, 37%). Conclusion Long-read RNA sequencing enables derivation of cytogenetic variant subgroups and mutation identification alongside reported gene expression-signature based prognostication, and reveals new granularity around driver variant expression, transcript splicing and RNA editing. This is the first study that assesses a large cohort of myeloma patient transcriptomes using long-read RNA sequencing, utilising an in-house designed sequencing pipeline and novel computational algorithms to provide clinically relevant information using one platform. This could allow rapid profiling of patients with minimal sample input and lower cost than current approaches. We continue to add layers of analyses to our dataset, including gene expression profiling and aberrant splicing signatures.

Immunotherapy advances have been hindered by difficulties in tracking the behaviors of lymphocytes after antigen signaling. Here, we assessed the behavior of T cells active within tumors through the development of the antigen receptor signaling reporter (AgRSR) mouse, fate-mapping lymphocytes responding to antigens at specific times and locations. Contrary to reports describing the ready egress of T cells out of the tumor, we find that intratumoral antigen signaling traps CD8+ T cells in the tumor. These clonal populations expand and become increasingly exhausted over time. By contrast, antigen-signaled regulatory T cell (Treg) clonal populations readily recirculate out of the tumor. Consequently, intratumoral antigen signaling acts as a gatekeeper to compartmentalize CD8+ T cell responses, even within the same clonotype, thus enabling exhausted T cells to remain confined to a specific tumor tissue site.

Sensitive cell surface proteomics studies have shown that the number of completely tumour-specific targets for adoptive cellular immunotherapy is extremely low. Even approved CAR T-cell targets appear to have expression in the central nervous system, leading to long-term neurological complications. We propose that this toxicity could be significantly improved by adoption of NOT-gates, which have been shown to limit CAR T-cell activity against healthy tissue expressing a second target that is absent on the tumour. Furthermore, the approach could also target essential, but non-specific proteins on tumour cells. The use of a NOT gate confers the specificity, whilst targeting the essential protein limits antigen escape. Here we explore the feasibility of such an approach for CAR T-cell targeting of primary myeloma. We show that none of the 45 most essential proteins are unique to the myeloma cell. However, whilst widely expressed, one of the most important proteins for myeloma cell survival, the transferrin receptor, could safely be targeted by a NOT-gate approach. Exploring co-expression patterns demonstrate 26 proteins that are not expressed on myeloma cells, but which are coexpressed with the transferrin receptor in all healthy tissues. We also describe a web app, NOTATER, which can be used by scientists with no bioinformatic capabilities to explore potential NOT-gate combinations in myeloma.

Introduction: Achievement and maintenance of maximal depth of response to first line therapy is a prerequisite for prolonged progression free survival (PFS) in multiple myeloma (MM) and initial treatment protocols are designed to enhance probability of obtaining a serological complete response (CR) and minimal residual disease (MRD) negativity in the bone marrow (BM). Response adapted treatment can deliver better outcomes than a one-size fits all approach1,2 if serological and BM markers are used to guide treatment selection. Deepening of response following high dose melphalan ASCT (HDM-ASCT) and immunomodulator-based maintenance treatment is well described3, similar response to transplant-sparing chemotherapy consolidation or HDM-ASCT and prolonged proteasome inhibitor (PI)-based maintenance is understudied. The primary endpoint of CARDAMON has been previously reported4, this in depth analysis of MRD conversion pre and post ASCT further describes the benefit of ASCT in improving depth of response compared to chemotherapy alone. Methods: Initial treatment comprised 4 x 28-day cycles of KCd (Carfilzomib 20/56mg days 1,2,8,9,15,16,Cyclophosphamide 500mg D1,8,15 and Dexamethasone 40mg D1,2,8,9,15,16) followed by peripheral blood stem cell harvest and consolidation with either HDM-ASCT or 4 further cycles of KCd. Following consolidation all patients received K maintenance for up to 18 x 28-day cycles. Data on serological response and rates of MRD negativity by FLOW cytometry (10-5) assessed at 3 time points: post induction and harvest (induction), post consolidation (HDM-ASCT or KCd) and post maintenance are presented alongside survival data. Results: A total of 281 patients were registered for the study and 230 patients completed induction, 218 of which were subsequently randomised (109 HDM-ASCT, 109 KCd). Median follow up was 4.8 years (IQR 4.1-5.8). Post-induction, 64 patients were MRD -ve and 153 MRD +ve (MRD status unknown in 13 patients). Patients achieving CR and MRD -ve at any of the 3 timepoints showed no benefit from ASCT over KCd in PFS (HR (ASCT vs KCd) 0.90, 95% CI 0.50-1.62, p=0.7) or OS (HR 2.56, 95% CI 0.70-9.43, p=0.2). Patients who were MRD +ve post induction were more likely to convert to MRD-ve with HDM-ASCT (25/64, 39.1%) than with KCd (10/61, 16.4%) consolidation (p=0.005). This effect continued during maintenance treatment such that 26/58 (44.8%) who were MRD +ve post induction became MRD -ve if they had received HDM-ASCT consolidation compared to 14/63 (22.2%) who received KCd (p=0.01). There was no significant difference between randomised consolidation treatment (HDM-ASCT or KCd) in maintaining MRD negativity if it was achieved at the earliest timepoint post-induction and sustained until the end of consolidation (HDM-ASCT 23/26, 88.5% vs KCd 20/25, 80.0%, p=0.4) or until the end of maintenance (HDM-ASCT 22/25, 88.0% vs KCd 17/21, 81.0% p=0.5). Furthermore, patients with sustained +ve MRD have a significantly worse PFS than those with repeated -ve MRD (Hazard Ratio 1.77, 95% CI 1.12-2.79, p=0.01) or those who convert from MRD +ve to -ve between the end of induction and the end of consolidation (HR 2.71, 95% CI 1.57-4.69, p<0.001). Though not significant, patients who converted from MRD +ve to -ve tended to have better outcomes than those with sustained negativity (HR 0.65, 95% CI 0.35-1.22, p=0.2) suggesting that the superior effect of ASCT continues during K maintenance and a potential synergistic effect of transplantation with PI maintenance. More patients converted from MRD +ve to MRD -ve during maintenance following ASCT (11/39 28.2%) than KCd (8/50 16%) although this difference was not significant (p=0.16). Discussion: This post hoc analysis of the CARDAMON study shows that early assessment of MRD status following induction and response driven choice of consolidation may improve outcome in first line treatment of MM and allow those with an early MRD -ve response to avoid the toxicity of HDM-ASCT. Similarly continued use of transplantation approach may be justified in those who are MRD +ve following induction. These results utilising a PI-based induction and post-ASCT treatment remain to be confirmed with quadruplet induction and IMiD-based maintenance. References: Costa L, et al J Clin Oncol. 2022 1;40(25):2901-2912 Royle K-L et al BMJ Open 2022 17;12(11) Jackson G et al Lancet Oncol. 2019;20(1):57-73 Yong K et al Lancet Hematol. 2023;10(2):E93-106

T cell-redirecting therapies (TCRTs), such as chimeric antigen receptor (CAR) or T cell receptor (TCR) T cells and T cell engagers, have emerged as a highly effective treatment modality, particularly in the B and plasma cell-malignancy setting. However, many patients fail to achieve deep and durable responses; while the lack of truly unique tumor antigens, and concurrent on-target/off-tumor toxicities, have hindered the development of TCRTs for many other cancers. In this review, we discuss the recent developments in TCRT targets for hematological malignancies, as well as novel targeting strategies that aim to address these, and other, challenges.

RNA binding proteins drive proliferation and tumorigenesis by regulating the translation and stability of specific subsets of messenger RNAs (mRNAs). We have investigated the role of eukaryotic initiation factor 4B (eIF4B) in this process and identify 10-fold more RNA binding sites for eIF4B in tumour cells from patients with diffuse large B-cell lymphoma compared to control B cells and, using individual-nucleotide resolution UV cross-linking and immunoprecipitation, find that eIF4B binds the entire length of mRNA transcripts. eIF4B stimulates the helicase activity of eIF4A, thereby promoting the unwinding of RNA structure within the 5' untranslated regions of mRNAs. We have found that, in addition to its well-documented role in mRNA translation, eIF4B additionally interacts with proteins associated with RNA turnover, including UPF1 (up-frameshift protein 1), which plays a key role in histone mRNA degradation at the end of S phase. Consistent with these data, we locate an eIF4B binding site upstream of the stem-loop structure in histone mRNAs and show that decreased eIF4B expression alters histone mRNA turnover and delays cell cycle progression through S phase. Collectively, these data provide insight into how eIF4B promotes tumorigenesis.

Background. A subset of patients with multiple myeloma (MM), termed “high-risk”, have high rates of early relapse and short survival. The definition of high-risk (HR) has evolved with treatment advances and improved genetic characterisation of patient cohorts. New genetic insights require a test that can detect translocations, copy number alterations (CNA) and small variants for risk assignment. This test must correctly identify the HR cohort and be widely and sustainably deployable in healthcare systems. The Myeloma Genome Project (MGP) Panel is a targeted DNA panel developed to include loci for CNA, translocations and genetic variants (PMID:35522533). It incorporates key disease drivers, therapeutic targets and prognostic features, including detection of genomic double/triple hits and bi-allelic inactivation of tumour suppressor genes via structural change, CNA and somatic variation. The UK-MRA RADAR study is a national, multi-centre, risk-adapted, response-guided multi-arm, multi-stage phase II/III trial which will recruit 1400 patients with newly diagnosed MM eligible for autologous stem cell transplant. Genetic risk classification is performed as standard of care (SoC) testing using Fluorescence in situ hybridization test (FISH)/ multiplex ligation-dependent probe amplification (MLPA). HR is defined as two or more genetic abnormalities incorporating t(4;14), t(14;16), t(14:20), del(17p), del(1p) and gain(1q). Participants who cannot be confirmed as standard risk (SR) or HR are classified as unable to determine (UTD) and treated as SR. The collection of central samples within RADAR affords a unique opportunity to compare the performance of FISH/MLPA to MGP in assigning risk status. We report the first results of this analysis, with more to follow. Methods. DNA was extracted from CD138-magnetic bead enriched MM cells in baseline bone marrow samples at a central lab. Paired germline DNA was obtained from peripheral blood. MGP libraries were prepared in an NHS clinical laboratory from samples that met QC metrics and sequenced as previously reported. SoC testing was done across 23 regional NHS labs using FISH/MLPA. Data were analysed to identify 20% Cancer Clonal Fraction (CCF) of high-risk features as per requirements for the SoC results used in RADAR. Genetic risk classification was derived as per the RADAR definition and agreement between the two methods assessed using Cohen's Kappa. Additional measures (sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV)) were derived using SoC classification as the reference group, in a complete case analysis. Finally, a recently proposed revised IMWG HR definition was applied to the MGP results, and the classification of patients compared descriptively. Results. To 1st July 2024, 876 patients have been recruited to RADAR. Of the first 93 central samples received, we report comparison of the 83 who met QC criteria for performing MGP sequencing/analysis. This set was similar to the overall RADAR population in terms of age, ethnicity, paraprotein type and HR proportion, with numerically more females and ISS1 in the MGP set. In the reported set SoC risk assignment was 63/83 (75.9%) SR, 15/83 (18.1%) HR and 5/83 (6.0%) UTD. MGP-based risk assignment using the RADAR definition was 65/83 (78.3%) SR, 15/83 (18.1%) HR and 3/83 (3.6%) UTD. Cohen's Kappa between the two was 0.64 (95% CI: 0.46, 0.83), with MGP re-designating 2 HR cases to SR, and 3 SR cases to HR. 78/83 (94.0%) participants had confirmed classification (SR or HR) in the SoC method. In these 78 samples with SoC as the reference, the sensitivity of MGP was 80%, the specificity was 97%, the PPV 86% and NPV 95%. Risk assignment by MGP using the new IMWG definition was 48/83 (58%) SR, 32/83 (39%) HR and 3/83 (3.6%) UTD. TP53 variants were present in 8/83 (9.6%), co-existing with other HR events in 6/83 (7.2%). Discussion. These initial results suggest there is substantial agreement between the SoC and MGP methods when classifying HR according to the RADAR trial definition. RADAR's ‘2-hit’ HR definition predates the anticipated IMWG criteria, where single TP53/del(17p) events also define HR status, thus HR incidence by IMWG criteria is higher. MGP detects TP53 variants, but RADAR SoC tests do not. We continue to assess and develop MGP assay performance against SoC, in consideration of its deployment for clinical use.

The haematological malignancy multiple myeloma is associated with skewed T-cell activation and function. T-cell alterations are detectable in asymptomatic myeloma precursor conditions and have the potential to identify precursor patients at imminent risk of progression. However, what myeloma-associated T-cells alterations represent mechanistically, how they relate to tumour burden and gene expression, and what influences high inter-patient variability in immune composition remains unknown. Here, we assembled the largest ever dataset of published and newly-generated single-cell RNA and TCR sequencing of the marrow and blood from patients with myeloma, precursor conditions, and age-matched non-cancer controls. We show myeloma is not associated with T-cell exhaustion and instead defined by a pattern of T-cell differentiation resembling antigen-driven terminal memory differentiation. Myeloma-associated T-cell differentiation was dependent on tumour-intrinsic features including tumour burden and tumour expression of antigen-presentation genes. Expanded TCR clones accumulating in myeloma were not enriched for viral specificity and were detected in effector states in highly infiltrated marrows. Together, these results suggest anti-tumour immunity drives a novel form of cancer-associated T-cell memory differentiation in myeloma. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This work was funded by CRUK, the Medical Research Council, and the UCL/UCLH Biomedical Research Centre. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: Ethics committee of Health Research Authority UK (Research ethics committee references: 07/Q0502/17, 07/Q0502/17) gave ethical approval for this work. Ethics committee of the London Central Research Ethics Committee (20/LO/0238) gave ethical approval for this work. Ethics committee of the London City and East Research Ethics Committee (London, UK; date of favourable ethical opinion Feb 23, 2015) gave ethical approval for this work. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes Published datasets were acquired following the instructions in each original publication. Specifically, data shared through the gene expression omnibus (GEO) can be accessed for Maura et al. under accession GSE161195, Bailur et al. under accession GSE163278, Oetjen et al. under accession GSE120221, Granja et al. under accession GSE139369, Zavidij et al. under accession GSE124310, Kfoury et al. under accession GSE143791, and Zheng et al. under accession GSE156728. Data shared via dbGaP for Sklavenitis-Pistofidis et al. can be accessed under accession phs002476.v1.p1. Data shared online can be accessed for Stephenson et al. (via https://covid19cellatlas.org/), Conde et al. (via https://www.tissueimmunecellatlas.org/), and Liu et al. (via https://explore.data.humancellatlas.org/projects/2ad191cd-bd7a-409b-9bd1-e72b5e4cce81). The integrated single-cell RNA and TCR datasets and cohort information are available online (https://zenodo.org/doi/10.5281/zenodo.11047959). CoMMpass data were downloaded from the MMRF researcher gateway (https://research.themmrf.org). Newly-generated raw sequencing data will be made publicly available and uploaded to the GEO upon peer-reviewed publication.

Immunotherapeutics have revolutionised the treatment of multiple myeloma (MM), but BCMA remains the only approved CAR T-cell target. Furthermore, despite impressive responses to these agents, relapses are still inevitable. There is thus an unmet need to expand our repertoire of targets. We have previously used proteomic approaches to demonstrate that classical CAR T-cell targets are inevitably expressed on healthy tissue, resulting in on-target/off-tumour toxicity. Further engineering is therefore required to enable better discrimination between healthy and malignant cells. We have previously identified SEMA4A as an attractive MM immunotherapeutic target, owing to its ubiquitous, obligate expression in primary MM. We also demonstrated that a SEMA4A-targeting CAR T-cell was highly effective in eliminating myeloma cells. However, SEMA4A has modest expression on monocytes, granulocytes, and CD34+ hematopoietic stem and progenitor cells (HSPCs), so on-target/off-tumour pancytopenia was a major risk of our original CAR T-cell. We therefore describe here our use of NOT-gating to enable much safer CAR T-cell targeting of SEMA4A in MM. To identify a suitable inhibitory CAR (iCAR) protein to pair with our primary SEMA4A CAR, we used a high-resolution mass-spectrometry-based proteomics dataset of primary human immune cells to identify cell-surface proteins that were absent on myeloma cells, but which were expressed at levels three-fold greater than SEMA4A, or more, on monocytes, granulocytes, and CD34+ cells. To prevent constitutive cis-inhibition of NOT-gated T-cells, we excluded all potential iCAR proteins also expressed on T-cells. We identified multiple potential iCAR partners, the most promising of which was the protein CLEC12A, based on its expression profile across the different lineages. We profiled multiple healthy and MM-associated bone marrow samples using flow cytometry to confirm the expression profile of this protein. As expected, we saw ubiquitous expression of CLEC12A on SEMA4A-positive monocytes, granulocytes and HSPCs, but a complete absence of expression on T-cells and on MM-associated plasma cells. Having identified CLEC12A as a high-quality iCAR protein partner, we proceeded to engineer the inhibitory machinery. We identified two single domain VHHs against CLEC12A. To confirm that they could bind the extracellular protein in its natural conformation and trigger downstream T-cell signalling, we overexpressed CLEC12A in K562 cells and co-cultured these with a second-generation CAR T-cell engineered with the VHHs to target CLEC12A. This led to robust T-cell activation, confirming the utility of the VHHs. We then cloned the VHHs upstream of the dual intracellular inhibitory regions of LIR-1 and PD-1 and co-expressed these iCARs in both Jurkat reporter cells and primary human T-cells expressing the SEMA4A targeting CAR. Parallel cell-surface expression of both constructs was validated through flow cytometry. Importantly, when co-cultured with CLEC12A-/SEMA4A+ target cells, there was robust T-cell activation and cell killing by the SEM4A-CAR/CLEC12A-iCAR demonstrating that the CLEC12A iCAR does not prevent cytotoxicity in the absence of its target. When co-cultured with CLEC12A+/SEMA4A+ target cells, T-cell activation was reduced, though not completely, indicating partial function of the CLEC12A iCAR. We reasoned that our failure to achieve complete inhibitory function was due to the relatively smaller size of the extracellular domain of CLEC12A relative to that of SEMA4A, leading to steric hindrance. We therefore experimented with different hinge lengths on the iCAR and targeting CAR to enhance performance. By increasing the iCAR/CAR hinge ratio, we were able to demonstrate significantly more inhibition of T-cell activation in the presence of CLEC12A on the target cell, whilst maintaining robust killing when CLEC12A was absent. Ongoing work is seeking to test our SEMA4A-CAR/CLEC12A-iCAR in vivo. In conclusion, we confirm that logic-gating can increase the targeting repertoire of CAR T-cells, and we demonstrate a NOT-gated CAR T-cell that can safely kill myeloma cells via their SEMA4A expression, while limiting on-target off-tumour toxicity of other immune cells. However, this study also illustrates that the increased targeting repertoire comes at the cost of increased engineering complexity.

Population-based prospective studies, such as UK Biobank, are valuable for generating and testing hypotheses about the potential causes of human disease. We describe how UK Biobank's study design, data access policies, and approaches to statistical analysis can help to minimize error and improve the interpretability of research findings, with implications for other population-based prospective studies being established worldwide.

Drug-induced autoimmunity (DIA) is an idiosyncratic adverse drug reaction. Although first reported in the mid-1940’s, the mechanisms underlying DIA remain unclear, and there is little understanding of why it is only associated with some drugs. Because it only occurs in a small number of patients, DIA is not normally detected until a drug has reached the market. We describe an ensemble machine learning approach using transcriptional data to predict DIA. The genes comprising the signature implicate dysregulation of cell cycling or proliferation as part of the mechanism of DIA. This approach could be adapted by pharmaceutical companies as an additional preclinical safety screen, reducing the risk of drugs with the potential to cause autoimmunity reaching the market.

Tissue homeostasis is maintained by the behaviours of lymphocyte clones responding to antigenic triggers in the face of pathogen, environmental, and developmental challenges. Current methodologies for tracking the behaviour of specific lymphocytes identify clones of a defined antigen-receptor—antigen binding affinity. However, lymphocytes can receive antigenic signals from undefined or endogenous antigens, and the strength of each signal, even for the same lymphocyte, varies with accessory signalling, across tissues and across time. We present a novel fate-mapping mouse, that, by tracking lymphocyte clones and their progenies from induced antigen signals, overcomes these hurdles and provides novel insights into the maintenance of tissue homeostasis. We demonstrate the systems use by investigating the maintenance of localised T cell tolerance in tumour immunity. In a murine tumour model, our system reveals how Tregs differentiate to a reversible, tolerance inducing state within the tumour, and recirculate, while CD8+ T cells failing to recirculate, differentiate to an increasingly exhausted, tolerant state in the tumour. These contrasting T cell behaviours provide means by which immunity can tolerate a particular anatomical niche while maintaining systemic clonal protection. Our system can thus explore lymphocyte behaviours that cannot be tracked by previous methods and will therefore provide novel insights into the fundamental mechanisms underlying immunity’s role in tissue homeostasis.

Background Standard-of-care treatment for patients with newly diagnosed multiple myeloma is bortezomib-based induction followed by high-dose melphalan and autologous haematopoietic stem-cell transplantation (HSCT) and lenalidomide maintenance. We aimed to evaluate whether an immunomodulatory-free carfilzomib-based induction, consolidation, and maintenance protocol without autologous HSCT was non-inferior to the same induction regimen followed by autologous HSCT and maintenance. Methods CARDAMON is a randomised, open-label, phase 2 trial in 19 hospitals in England and Wales, UK. Newly diagnosed, transplantation-eligible patients with multiple myeloma aged 18 years or older with an Eastern Cooperative Oncology Group (ECOG) performance status of 0-2 received four 28-day cycles of carfilzomib (56 mg/m2 intravenously on days 1, 2, 8, 9, 15, and 16), cyclophosphamide (500 mg orally on days 1, 8, and 15), and dexamethasone (40 mg orally on days 1, 8, 15, and 22; KCd), followed by peripheral blood stem cell mobilisation. Patients with at least a partial response were randomly assigned (1:1) to either high-dose melphalan and autologous HSCT or four cycles of KCd. All randomised patients received 18 cycles of carfilzomib maintenance (56 mg/m2 intravenously on days 1, 8, and 15). The primary outcomes were the proportion of patients with at least a very good partial response after induction and difference in progression-free survival rate at 2 years from randomisation (non-inferiority margin 10%), both assessed by intention to treat. Safety was assessed in all patients who started treatment. The trial is registered with ClinicalTrials. gov (NCT02315716); recruitment is complete and all patients are in follow-up. Findings Between June 16, 2015, and July 8, 2019, 281 patients were enrolled, with 218 proceeding to randomisation (109 assigned to the KCd consolidation group [99 of whom completed consolidation] and 109 to the HSCT group [104 of whom underwent transplantation]). A further seven patients withdrew before initiation of carfilzomib maintenance (two in the KCd consolidation group vs five in the HSCT group). Median age was 59 years (IQR 52 to 64); 166 (59%) of 281 patients were male and 115 (41%) were female. 152 (71%) of 214 patients with known ethnicity were White, 37 (17%) were Black, 18 (8%) were Asian, 5 (2%) identified as Mixed, and 2 (1%) identified as other. Median follow-up from randomisation was 40 center dot 2 months (IQR 32 center dot 7 to 51 center dot 8). After induction, 162 (57 center dot 7%; 95% CI 51 center dot 6 to 63 center dot 5) of 281 patients had at least a very good partial response. The 2-year progression-free survival was 75% (95% CI 65 to 82) in the HSCT group versus 68% (95% CI 58 to 76) in the KCd group (difference -7 center dot 2%, 70% CI -11 center dot 1 to -2 center dot 8), exceeding the non-inferiority margin. The most common grade 3-4 events during KCd induction and consolidation were lymphocytopenia (72 [26%] of 278 patients who started induction; 15 [14%] of 109 patients who started consolidation) and infection (50 [18%] of 278 for induction; 15 [14%] of 109 for consolidation), and during carfilzomib maintenance were hypertension (20 [21%] of 97 patients in the KCd consolidation group vs 23 [23%] of 99 patients in the HSCT group) and infection (16 [16%] of 97 patients vs 25 [25%] of 99). Treatment-related serious adverse events at any point during the trial were reported in 109 (39%) of 278 patients who started induction, with infections (80 [29%]) being the most common. Treatment-emergent deaths were reported in five (2%) of 278 patients during induction (three from infection, one from cardiac event, and one from renal failure) and one of 99 patients during maintenance after autologous HSCT (oesophageal carcinoma). Interpretation KCd did not meet the criteria for non-inferiority compared with autologous HSCT, but the marginal difference in progression-free survival suggests that further studies are warranted to explore deferred autologous HSCT in some subgroups, such as individuals who are MRD negative after induction. Funding Cancer Research UK and Amgen.

Precision medicine holds great promise to improve outcomes in cancer, including haematological malignancies. However, there are few biomarkers that influence choice of chemotherapy in clinical practice. In particular, multiple myeloma requires an individualized approach as there exist several active therapies, but little agreement on how and when they should be used and combined. We have previously shown that a transcriptomic signature can identify specific bortezomib- and lenalidomide-sensitivity. However, gene expression signatures are challenging to implement clinically. We reasoned that signatures based on the presence or absence of gene mutations would be more tractable in the clinical setting, though examples of such signatures are rare. We performed whole exome sequencing as part of the CARDAMON trial, which employed carfilzomib-based therapy. We applied advanced machine learning approaches to discover mutational patterns predictive of treatment outcome. The resulting model accurately predicted progression-free survival (PFS) both in CARDAMON patients and in an external validation set of patients from the CoMMpass study who had received carfilzomib. The signature was specific for carfilzomib therapy and was strongly driven by genes on chromosome 1p36. Importantly, patients predicted to be carfilzomib-sensitive had a longer PFS when treated with carfilzomib/lenalidomide/dexamethasone than with bortezomib/carfilzomib/dexamethasone. However, in those predicted to be carfilzomib-insensitive, the latter therapy may have been capable of eradicating carfilzomib-resistant clones. We propose that the signature can be used to make rational therapeutic decisions and could be incorporated into future clinical trials. ### Competing Interest Statement Walker: Abbvie & Janssen: Honoraria. Popat: Takeda: Research Funding; GSK: Honoraria, Research Funding; Janssen, Takeda, Celgene, and GSK: Honoraria; Janssen, Takeda, GSK: Other: Travel expenses from Janssen, Takeda GSK; Roche:Honoraria; BMS: Honoraria; Janssen: Honoraria; Takeda, AbbVie, GlaxoSmithKline, and Celgene: Consultancy. Benjamin:Bristol Myers Squibb/Celgene: Research Funding; Amgen: Research Funding. Clifton-Hadley: Astra Zeneca, GSK, Pfizer, MSD, BMS, Amgen, Millennium Takeda: Other: CRUK and UCL CTC have received research funding in the past 24 months, Research Funding. Owen: Astra Zeneca: Honoraria; Janssen: Honoraria Membership on an entity's Board of Directors or advisory committees; Beigene: Honoraria ;Membership on an entity's Board of Directors or advisory committees. Chapman:Sanofi: Honoraria. ### Clinical Protocols ### Funding Statement IGW is supported by the Kay Kendall Leukaemia Fund KKL1442 also received support from the UK Myeloma Society UKMS, VdA has received support from the UKMS. MAC is supported by the Medical Research Council Toxicology Unit MC UU 00025 10. KY and RP are supported by the National Institute for Health Research University College London Hospitals Biomedical Research Centre. The Cardamon trial was funded by Amgen and endorsed by Cancer Research UK C9203 A17750. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The London City and East Research Ethics Committee London, UK gave full approval of study. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes All data produced in the present study are available upon reasonable request to the authors. Data and code will be made publicly available on acceptance in a peer reviewed journal