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Many congratulations to Professor Sir David Weatherall, who was appointed a Knight Grand Cross of the Order of the British Empire (GBE). This is the highest rank in the Order of the British Empire, an honour only bestowed 16 times since 2000.
Risk Stratification in Older Intensively Treated Patients With AML.
PURPOSE: AML is a genetically heterogeneous disease, particularly in older patients. In patients older than 60 years, survival rates are variable after the most important curative approach, intensive chemotherapy followed by allogeneic hematopoietic cell transplantation (allo-HCT). Thus, there is an urgent need in clinical practice for a prognostic model to identify older patients with AML who benefit from curative treatment. METHODS: We studied 1,910 intensively treated patients older than 60 years with AML and high-risk myelodysplastic syndrome (HR-MDS) from two cohorts (NCRI-AML18 and HOVON-SAKK). The median patient age was 67 years. Using a random survival forest, clinical, molecular, and cytogenetic variables were evaluated in an AML development cohort (n = 1,204) for association with overall survival (OS). Relative weights of selected variables determined the prognostic model, which was validated in AML (n = 491) and HR-MDS cohorts (n = 215). RESULTS: The complete cohort had a high frequency of poor-risk features, including 2022 European LeukemiaNet adverse-risk (57.3%), mutated TP53 (14.4%), and myelodysplasia-related genetic features (65.1%). Nine variables were used to construct four groups with highly distinct 4-year OS in the (1) AML development, (2) AML validation, and (3) HR-MDS test cohorts ([1] favorable: 54% ± 4%, intermediate: 38% ± 2%, poor: 21% ± 2%, very poor: 4% ± 1%; [2] 54% ± 9%, 43% ± 4%, 27% ± 4%, 4% ± 3%; and [3] 54% ± 10%, 33% ± 6%, 14% ± 5%, 0% ± 3%, respectively). This new AML60+ classification improves current prognostic classifications. Importantly, patients within the AML60+ intermediate- and very poor-risk group significantly benefited from allo-HCT, whereas the poor-risk patients showed an indication, albeit nonsignificant, for improved outcome after allo-HCT. CONCLUSION: The new AML60+ classification provides prognostic information for intensively treated patients 60 years and older with AML and HR-MDS and identifies patients who benefit from intensive chemotherapy and allo-HCT.
Tracking in situ checkpoint inhibitor-bound target T cells in patients with checkpoint-induced colitis.
The success of checkpoint inhibitors (CPIs) for cancer has been tempered by immune-related adverse effects including colitis. CPI-induced colitis is hallmarked by expansion of resident mucosal IFNγ cytotoxic CD8+ T cells, but how these arise is unclear. Here, we track CPI-bound T cells in intestinal tissue using multimodal single-cell and subcellular spatial transcriptomics (ST). Target occupancy was increased in inflamed tissue, with drug-bound T cells located in distinct microdomains distinguished by specific intercellular signaling and transcriptional gradients. CPI-bound cells were largely CD4+ T cells, including enrichment in CPI-bound peripheral helper, follicular helper, and regulatory T cells. IFNγ CD8+ T cells emerged from both tissue-resident memory (TRM) and peripheral populations, displayed more restricted target occupancy profiles, and co-localized with damaged epithelial microdomains lacking effective regulatory cues. Our multimodal analysis identifies causal pathways and constitutes a resource to inform novel preventive strategies.
HLA-dependent variation in SARS-CoV-2 CD8 + T cell cross-reactivity with human coronaviruses.
The conditions and extent of cross-protective immunity between severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and common-cold human coronaviruses (HCoVs) remain open despite several reports of pre-existing T cell immunity to SARS-CoV-2 in individuals without prior exposure. Using a pool of functionally evaluated SARS-CoV-2 peptides, we report a map of 126 immunogenic peptides with high similarity to 285 MHC-presented peptides from at least one HCoV. Employing this map of SARS-CoV-2-non-homologous and homologous immunogenic peptides, we observe several immunogenic peptides with high similarity to human proteins, some of which have been reported to have elevated expression in severe COVID-19 patients. After combining our map with SARS-CoV-2-specific TCR repertoire data from COVID-19 patients and healthy controls, we show that public repertoires for the majority of convalescent patients are dominated by TCRs cognate to non-homologous SARS-CoV-2 peptides. We find that for a subset of patients, >50% of their public SARS-CoV-2-specific repertoires consist of TCRs cognate to homologous SARS-CoV-2-HCoV peptides. Further analysis suggests that this skewed distribution of TCRs cognate to homologous or non-homologous peptides in COVID-19 patients is likely to be HLA-dependent. Finally, we provide 10 SARS-CoV-2 peptides with known cognate TCRs that are conserved across multiple coronaviruses and are predicted to be recognized by a high proportion of the global population. These findings may have important implications for COVID-19 heterogeneity, vaccine-induced immune responses, and robustness of immunity to SARS-CoV-2 and its variants.
Evaluating performance of existing computational models in predicting CD8+ T cell pathogenic epitopes and cancer neoantigens.
T cell recognition of a cognate peptide-major histocompatibility complex (pMHC) presented on the surface of infected or malignant cells is of the utmost importance for mediating robust and long-term immune responses. Accurate predictions of cognate pMHC targets for T cell receptors would greatly facilitate identification of vaccine targets for both pathogenic diseases and personalized cancer immunotherapies. Predicting immunogenic peptides therefore has been at the center of intensive research for the past decades but has proven challenging. Although numerous models have been proposed, performance of these models has not been systematically evaluated and their success rate in predicting epitopes in the context of human pathology has not been measured and compared. In this study, we evaluated the performance of several publicly available models, in identifying immunogenic CD8+ T cell targets in the context of pathogens and cancers. We found that for predicting immunogenic peptides from an emerging virus such as severe acute respiratory syndrome coronavirus 2, none of the models perform substantially better than random or offer considerable improvement beyond HLA ligand prediction. We also observed suboptimal performance for predicting cancer neoantigens. Through investigation of potential factors associated with ill performance of models, we highlight several data- and model-associated issues. In particular, we observed that cross-HLA variation in the distribution of immunogenic and non-immunogenic peptides in the training data of the models seems to substantially confound the predictions. We additionally compared key parameters associated with immunogenicity between pathogenic peptides and cancer neoantigens and observed evidence for differences in the thresholds of binding affinity and stability, which suggested the need to modulate different features in identifying immunogenic pathogen versus cancer peptides. Overall, we demonstrate that accurate and reliable predictions of immunogenic CD8+ T cell targets remain unsolved; thus, we hope our work will guide users and model developers regarding potential pitfalls and unsettled questions in existing immunogenicity predictors.
A Revised Prognostic Model for Patients with Acute Myeloid Leukemia and First Relapse.
Most patients with acute myeloid leukemia (AML) may obtain remission upon induction chemotherapy, but relapse is frequent and associated with poor survival. Previous prognostic models for outcomes after relapse lacked analysis of comprehensive molecular data. A validated prognostic model integrating clinical, cytogenetic, and molecular variables may support treatment decisions. We studied 943 AML patients who relapsed after first-line intensive induction treatment in a development cohort (HOVON-SAKK). A random survival forest algorithm was used to evaluate the association of clinical parameters, cytogenetic abnormalities, and molecular variables at diagnosis with overall survival (OS). Relapsing patients (n=377) who were enrolled in the NCRI-AML18 trial were used for model validation. In the development cohort, the median age at relapse was 58 years, and patients were classified as 2022 ELN favorable (22%), intermediate (31%), and adverse (48%) risk. One-third underwent allogeneic transplantation in first complete remission. Variable selection yielded nine variables significantly associated with 1-year OS, including relapse-free interval, age, white blood cell count, mutated TP53, FLT3-ITD, core-binding factor abnormalities, t(v;11q23)/KMT2A-rearranged and complex/monosomal karyotype, which were assigned points according to their estimated hazard ratios. Three prognostic groups were defined with distinct 1-year OS in both development (favorable: 51±3%, intermediate: 29±3% and poor: 14±2%, respectively) and validation cohorts (51±4%, 26±5% and 14±3%, respectively). Independent validation confirmed the improved accuracy in predicting outcomes for AML patients in first relapse. The revised AML relapse model improved on previous classification systems for prognostication of outcomes after first AML relapse. It provides stratification which might support tailoring second line treatment.
Protocol for high-quality RNA sequencing, cell surface protein analysis, and genotyping in single cells using TARGET-seq.
Studying the consequences of somatic mutations in pre-malignant and cancerous tissues is challenging due to noise in single-cell transcriptome data and difficulty in identifying the clonal identity of single cells. We optimized TARGET-seq to develop TARGET-seq+, which combines RNA sequencing (RNA-seq), the analysis of cell surface protein expression, and genotyping in single cells with improved sensitivity. We describe the steps for cell isolation, the preparation of single-cell RNA-seq (scRNA-seq) and genotyping libraries, and sequencing. We also provide guidance on the analysis of single-cell genotyping, transcriptome pre-processing, and data integration. For complete details on the use and execution of this protocol, please refer to Jakobsen et al.1.
Clonal tracing with somatic epimutations reveals dynamics of blood ageing.
Current approaches used to track stem cell clones through differentiation require genetic engineering1,2 or rely on sparse somatic DNA variants3,4, which limits their wide application. Here we discover that DNA methylation of a subset of CpG sites reflects cellular differentiation, whereas another subset undergoes stochastic epimutations and can serve as digital barcodes of clonal identity. We demonstrate that targeted single-cell profiling of DNA methylation5 at single-CpG resolution can accurately extract both layers of information. To that end, we develop EPI-Clone, a method for transgene-free lineage tracing at scale. Applied to mouse and human haematopoiesis, we capture hundreds of clonal differentiation trajectories across tens of individuals and 230,358 single cells. In mouse ageing, we demonstrate that myeloid bias and low output of old haematopoietic stem cells6 are restricted to a small number of expanded clones, whereas many functionally young-like clones persist in old age. In human ageing, clones with and without known driver mutations of clonal haematopoieis7 are part of a spectrum of age-related clonal expansions that display similar lineage biases. EPI-Clone enables accurate and transgene-free single-cell lineage tracing on hematopoietic cell state landscapes at scale.
Data from A phase Ib/II study of ivosidenib with venetoclax +/- azacitidine in IDH1-mutated myeloid malignancies
<div>Abstract<p>The safety and efficacy of combining the IDH1 inhibitor ivosidenib (IVO) with the BCL2 inhibitor venetoclax (VEN; IVO+VEN) +/- azacitidine (AZA; IVO+VEN+AZA) was evaluated in four cohorts of patients with IDH1-mutated myeloid malignancies (n=31). Most (91%) adverse events were grade 1 or 2. The maximal tolerated dose was not reached. Composite complete remission with IVO+VEN+AZA vs. IVO+VEN was 90% vs. 83%. Among MRD-evaluable patients (N=16) 63% attained MRD-negative remissions; IDH1 mutation clearance occurred in 64% of patients receiving ≥5 treatment cycles (N=14). Median EFS and OS were 36 (95% CI: 23-NR) and 42 (95% CI: 42-NR) months. Patients with signaling gene mutations appeared to particularly benefit from the triplet regimen. Longitudinal single-cell proteogenomic analyses linked co-occurring mutations, anti-apoptotic protein expression, and cell maturation to therapeutic sensitivity of IDH1-mutated clones. No IDH isoform switching or second-site IDH1 mutations were observed, indicating combination therapy may overcome established resistance pathways to single-agent IVO.</p></div>
Pleural fluid proteomics from patients with pleural infection shows signatures of diverse neutrophilic responses: The Oxford Pleural Infection Endotyping Study (TORPIDS-2).
BACKGROUND: Pleural infection is a complex disease with poor clinical outcomes and increasing incidence worldwide, yet its biological endotypes remain unknown. METHODS: We analysed 80 pleural fluid samples from the PILOT study, a prospective study on pleural infection, using unlabelled mass spectrometry. A total of 449 proteins were retained after filtering. Unsupervised hierarchical clustering and UMAP analyses were used to cluster samples and pathway analysis was performed to identify the biological processes. Protein signatures as identified by the pathway analysis were compared to microbiology as defined by 16S rRNA next generation sequencing. Spearman and exact Fischer's methods were used for correlation assessment. RESULTS: Higher neutrophil degranulation was correlated with increased glycolysis (OR=281, p<2.2E-16) and pentose phosphate activation (OR=371.45, p<2.2E-16). Samples dominated by Streptococcus pneumoniae exhibited higher neutrophil degranulation (OR=12.08, p=0.005), glycolysis (OR=11.4, p=0.006), and pentose phosphate activity (OR=12.82, p=0.004). On the other hand, samples dominated by anaerobes and Gram-negative bacteria exhibited lower neutrophil degranulation (OR=0.15, p=0.01, glycolysis (OR=0.14, p=0.01), and pentose phosphate activity (OR=0.07, p=0.001). Increased activity of the liver and retinoid X receptors (LXR-RXR) pathway was associated with lower risk of one-year mortality (OR=0.24, p=0.04). CONCLUSIONS: These findings suggest that pleural infection patients exhibit diverse responses of neutrophil mediated immunity, glycolysis, and pentose phosphate activation which are associated with microbiology. Therapeutic targeting of the LXR-RXR pathway with agonists is a possible treatment approach.
Long term health outcomes in people with diabetes 12 months after hospitalisation with COVID-19 in the UK: a prospective cohort study.
BACKGROUND: People with diabetes are at increased risk of hospitalisation, morbidity, and mortality following SARS-CoV-2 infection. Long-term outcomes for people with diabetes previously hospitalised with COVID-19 are, however, unknown. This study aimed to determine the longer-term physical and mental health effects of COVID-19 in people with and without diabetes. METHODS: The PHOSP-COVID study is a multicentre, long-term follow-up study of adults discharged from hospital between 1 February 2020 and 31 March 2021 in the UK following COVID-19, involving detailed assessment at 5 and 12 months after discharge. The association between diabetes status and outcomes were explored using multivariable linear and logistic regressions. FINDINGS: People with diabetes who survived hospital admission with COVID-19 display worse physical outcomes compared to those without diabetes at 5- and 12-month follow-up. People with diabetes displayed higher fatigue (only at 5 months), frailty, lower physical performance, and health-related quality of life and poorer cognitive function. Differences in outcomes between diabetes status groups were largely consistent from 5 to 12-months. In regression models, differences at 5 and 12 months were attenuated after adjustment for BMI and presence of other long-term conditions. INTERPRETATION: People with diabetes reported worse physical outcomes up to 12 months after hospital discharge with COVID-19 compared to those without diabetes. These data support the need to reduce inequalities in long-term physical and mental health effects of SARS-CoV-2 infection in people with diabetes. FUNDING: UK Research and Innovation and National Institute for Health Research. The study was approved by the Leeds West Research Ethics Committee (20/YH/0225) and is registered on the ISRCTN Registry (ISRCTN10980107).
Advancing atmospheric solids analysis probe mass spectrometry applications: a multifaceted approach to optimising clinical data set generation.
The use of rapid mass spectrometry techniques, such as atmospheric-solids-analysis-probe mass spectrometry (ASAP-MS), in the analysis of metabolite patterns in clinical samples holds significant promise for developing new diagnostic tools and enabling rapid disease screening. The rapid measurement times, ease of use, and relatively low cost of ASAP-MS makes it an appealing option for use in clinical settings. However, despite the potential of such approaches, a number of important experimental considerations are often overlooked. As well as instrument-specific choices and settings, these include the treatment of background noise and/or contaminant peaks in the mass spectra, and the influence of consumables, different users, and batch effects more generally. The present study assesses the impact of these various factors on measurement accuracy and reproducibility, using human brain and cerebrospinal fluid samples as examples. Based on our results, we make a series of recommendations relating to optimisation of measurement and cleaning protocols, consumable selection, and batch effect detection and correction, in order to optimise the reliability and reproducibility of ASAP-MS measurements in clinical settings.
Immune-epithelial-stromal networks define the cellular ecosystem of the small intestine in celiac disease.
The immune-epithelial-stromal interactions underpinning intestinal damage in celiac disease (CD) are incompletely understood. To address this, we performed single-cell transcriptomics (RNA sequencing; 86,442 immune, parenchymal and epithelial cells; 35 participants) and spatial transcriptomics (20 participants) on CD intestinal biopsy samples. Here we show that in CD, epithelial populations shifted toward a progenitor state, with interferon-driven transcriptional responses, and perturbation of secretory and enteroendocrine populations. Mucosal T cells showed numeric and functional changes in regulatory and follicular helper-like CD4+ T cells, intraepithelial lymphocytes, CD8+ and γδ T cell subsets, with skewed T cell antigen receptor repertoires. Mucosal changes remained detectable despite treatment, representing a persistent immune-epithelial 'scar'. Spatial transcriptomics defined transcriptional niches beyond those captured in conventional histological scores, including CD-specific lymphoid aggregates containing T cell-B cell interactions. Receptor-ligand spatial analyses integrated with disease susceptibility gene expression defined networks of altered chemokine and morphogen signaling, and provide potential therapeutic targets for CD prevention and treatment.
Resistance to immunomodulatory drugs in multiple myeloma: the cereblon pathway and beyond
Acquired resistance to immunomodulatory drugs (IMiD) remains a significant unmet need in the treatment landscape of multiple myeloma (MM). The cereblon (CRBN) pathway-dependent mechanisms are known to be vital contributors to IMiD resistance; however, they may account for only a small proportion. Recent research has unveiled additional mechanisms of acquired IMiD resistance that are independent of the CRBN pathway. In this review, we provide a comprehensive overview of the existing work on IMiD resistance in MM, focusing specifically on the emerging evidence of CRBN pathway-independent mechanisms. Finally, we discuss the plausible actionable strategies and outlook for IMiD-based therapies moving forward.