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The collective force of cancer research, outreach and care across the city of Oxford, translating discoveries into better care for cancer patients.
Predicting the risk of pancreatic cancer in adults with new-onset diabetes: development and internal-external validation of a clinical risk prediction model.
BACKGROUND: The National Institute for Health and Care Excellence (NICE) recommends that people aged 60+ years with newly diagnosed diabetes and weight loss undergo abdominal imaging to assess for pancreatic cancer. More nuanced stratification could lead to enrichment of these referral pathways. METHODS: Population-based cohort study of adults aged 30-85 years at type 2 diabetes diagnosis (2010-2021) using the QResearch primary care database in England linked to secondary care data, the national cancer registry and mortality registers. Clinical prediction models were developed to estimate risks of pancreatic cancer diagnosis within 2 years and evaluated using internal-external cross-validation. RESULTS: Seven hundred and sixty-seven of 253,766 individuals were diagnosed with pancreatic cancer within 2 years. Models included age, sex, BMI, prior venous thromboembolism, digoxin prescription, HbA1c, ALT, creatinine, haemoglobin, platelet count; and the presence of abdominal pain, weight loss, jaundice, heartburn, indigestion or nausea (previous 6 months). The Cox model had the highest discrimination (Harrell's C-index 0.802 (95% CI: 0.797-0.817)), the highest clinical utility, and was well calibrated. The model's highest 1% of predicted risks captured 12.51% of pancreatic cancer cases. NICE guidance had 3.95% sensitivity. DISCUSSION: A new prediction model could have clinical utility in identifying individuals with recent onset diabetes suitable for fast-track abdominal imaging.
Unravelling B cell heterogeneity: insights into flow cytometry-gated B cells from single-cell multi-omics data
Introduction: B cells play a pivotal role in adaptive immunity which has been extensively characterised primarily via flow cytometry-based gating strategies. This study addresses the discrepancies between flow cytometry-defined B cell subsets and their high-confidence molecular signatures using single-cell multi-omics approaches. Methods: By analysing multi-omics single-cell data from healthy individuals and patients across diseases, we characterised the level and nature of cellular contamination within standard flow cytometric-based gating, resolved some of the ambiguities in the literature surrounding unconventional B cell subsets, and demonstrated the variable effects of flow cytometric-based gating cellular heterogeneity across diseases. Results: We showed that flow cytometric-defined B cell populations are heterogenous, and the composition varies significantly between disease states thus affecting the implications of functional studies performed on these populations. Importantly, this paper draws caution on findings about B cell selection and function of flow cytometric-sorted populations, and their roles in disease. As a solution, we developed a simple tool to identify additional markers that can be used to increase the purity of flow-cytometric gated immune cell populations based on multi-omics data (AlliGateR). Here, we demonstrate that additional non-linear CD20, CD21 and CD24 gating can increase the purity of both naïve and memory populations. Discussion: These findings underscore the need to reconsider B cell subset definitions within the literature and propose leveraging single-cell multi-omics data for refined characterisation. We show that single-cell multi-omics technologies represent a powerful tool to bridge the gap between surface marker-based annotations and the intricate molecular characteristics of B cell subsets.
The Future of Blood Testing Is the Immunome.
It is increasingly clear that an extraordinarily diverse range of clinically important conditions-including infections, vaccinations, autoimmune diseases, transplants, transfusion reactions, aging, and cancers-leave telltale signatures in the millions of V(D)J-rearranged antibody and T cell receptor [TR per the Human Genome Organization (HUGO) nomenclature but more commonly known as TCR] genes collectively expressed by a person's B cells (antibodies) and T cells. We refer to these as the immunome. Because of its diversity and complexity, the immunome provides singular opportunities for advancing personalized medicine by serving as the substrate for a highly multiplexed, near-universal blood test. Here we discuss some of these opportunities, the current state of immunome-based diagnostics, and highlight some of the challenges involved. We conclude with a call to clinicians, researchers, and others to join efforts with the Adaptive Immune Receptor Repertoire Community (AIRR-C) to realize the diagnostic potential of the immunome.
Using de novo assembly to identify structural variation of complex immune system gene regions
AbstractDriven by the necessity to survive environmental pathogens, the human immune system has evolved exceptional diversity and plasticity, to which several factors contribute including inheritable structural polymorphism of the underlying genes. Characterizing this variation is challenging due to the complexity of these loci, which contain extensive regions of paralogy, segmental duplication and high copy-number repeats, but recent progress in long-read sequencing and optical mapping techniques suggests this problem may now be tractable. Here we assess this by using long-read sequencing platforms from PacBio and Oxford Nanopore, supplemented with short-read sequencing and Bionano optical mapping, to sequence DNA extracted from CD14+ monocytes and peripheral blood mononuclear cells from a single European individual identified as HV31. We use this data to build a de novo assembly of eight genomic regions encoding four key components of the immune system, namely the human leukocyte antigen, immunoglobulins, T cell receptors, and killer-cell immunoglobulin-like receptors. Validation of our assembly using k-mer based and alignment approaches suggests that it has high accuracy, with estimated base-level error rates below 1 in 10 kb, although we identify a small number of remaining structural errors. We use the assembly to identify heterozygous and homozygous structural variation in comparison to GRCh38. Despite analyzing only a single individual, we find multiple large structural variants affecting core genes at all three immunoglobulin regions and at two of the three T cell receptor regions. Several of these variants are not accurately callable using current algorithms, implying that further methodological improvements are needed. Our results demonstrate that assessing haplotype variation in these regions is possible given sufficiently accurate long-read and associated data; application of these methods to larger samples would provide a broader catalogue of germline structural variation at these loci, an important step toward making these regions accessible to large-scale genetic association studies.
Predictability of B cell clonal persistence and immunosurveillance in breast cancer
AbstractB cells and T cells are important components of the adaptive immune system and mediate anticancer immunity. The T cell landscape in cancer is well characterized, but the contribution of B cells to anticancer immunosurveillance is less well explored. Here we show an integrative analysis of the B cell and T cell receptor repertoire from individuals with metastatic breast cancer and individuals with early breast cancer during neoadjuvant therapy. Using immune receptor, RNA and whole-exome sequencing, we show that both B cell and T cell responses seem to coevolve with the metastatic cancer genomes and mirror tumor mutational and neoantigen architecture. B cell clones associated with metastatic immunosurveillance and temporal persistence were more expanded and distinct from site-specific clones. B cell clonal immunosurveillance and temporal persistence are predictable from the clonal structure, with higher-centrality B cell antigen receptors more likely to be detected across multiple metastases or across time. This predictability was generalizable across other immune-mediated disorders. This work lays a foundation for prioritizing antibody sequences for therapeutic targeting in cancer.
HIV/HBV co-infection remodels the immune landscape and Natural Killer cell ADCC functional responses
Background: HBV and HIV co-infection is a common occurrence globally, with significant morbidity and mortality. Both viruses lead to immune dysregulation including changes in NK cells, a key component of antiviral defense and a promising target for HBV cure strategies. Here we used high-throughput single cell analysis to explore the immune cell landscape in people with HBV mono-infection and HIV/HBV co-infection, on antiviral therapy, with emphasis on identifying the distinctive characteristics of NK cell subsets that can be therapeutically harnessed. Results: Our data show striking differences in the transcriptional programs of NK cells. HIV/HBV co-infection was characterized by an overrepresentation of adaptive, KLRC2 expressing NK cells, including a higher abundance of a chemokine enriched (CCL3/CCL4) adaptive cluster. The NK cell remodeling in HIV/HBV co-infection was reflected in enriched activation pathways, including CD3ζ phosphorylation and ZAP-70 translocation that can mediate stronger ADCC responses and a bias towards chemokine/cytokine signaling. By contrast HBV mono-infection imposed a stronger cytotoxic profile on NK cells and a more prominent signature of ‘exhaustion’ with higher circulating levels of HBsAg. Phenotypic alterations in the NK cell pool in co-infection were consistent with increased ‘adaptiveness’ and better capacity for ADCC compared to HBV mono-infection. Overall, an adaptive NK cell signature correlated inversely with circulating levels of HBsAg and HBV-RNA in our cohort. Conclusions: This study provides new insights into the differential signature and functional profile of NK cells in HBV and HIV/HBV co-infection, highlighting pathways that can be manipulated to tailor NK cell-focused approaches to advance HBV cure strategies in different patient groups.
Clinical trial protocol for PanDox: a phase I study of targeted chemotherapy delivery to non-resectable primary pancreatic tumours using thermosensitive liposomal doxorubicin (ThermoDox®) and focused ultrasound.
BACKGROUND: The dense stroma of pancreatic ductal adenocarcinomas is a major barrier to drug delivery. To increase the local drug diffusion gradient, high doses of chemotherapeutic agent doxorubicin can be released from thermally-sensitive liposomes (ThermoDox®) using ultrasound-mediated hyperthermia at the tumour target. PanDox is designed as a Phase 1 single centre study to investigate enhancing drug delivery to adult patients with non-operable pancreatic ductal adenocarcinomas. The study compares a single cycle of either conventional doxorubicin alone or ThermoDox® with focused ultrasound-induced hyperthermia for targeted drug release. METHODS: Adults with non-resectable pancreatic ductal adenocarcinoma are allocated to receive a single cycle of either doxorubicin alone (Arm A) or ThermoDox® with focused ultrasound-induced hyperthermia (Arm B), based on patient- and tumour-specific safety conditions. Participants in Arm B will undergo a general anaesthetic and pre-heating of the tumour by extra-corporal focused ultrasound (FUS). Rather than employing invasive thermometry, ultrasound parameters are derived from a patient-specific treatment planning model to reach the 41 °C target temperature for drug release. ThermoDox® is then concurrently infused with further ultrasound exposure. Tumour biopsies at the targeted site from all patients are analysed post-treatment using high performance liquid chromatography to quantify doxorubicin delivered to the tumour. The primary endpoint is defined as a statistically significant enhancement in concentration of total intra-tumoural doxorubicin, comparing samples from patients receiving liposomal drug with FUS to free drug alone. Participants are followed for 21 days post-treatment to assess secondary endpoints, including radiological assessment to measure changes in tumour activity by Positron Emission Tomography Response Criteria in Solid Tumours (PERCIST) criteria, adverse events and patient-reported symptoms. DISCUSSION: This early phase study builds on previous work targeting tumours in the liver to investigate whether enhancement of chemotherapy delivery using ultrasound-mediated hyperthermia can be translated to the stroma-dense environment of pancreatic ductal adenocarcinoma. If successful, it could herald a new approach towards managing these difficult-to-treat tumours. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT04852367 . Registered 21st April 2022. EudraCT number: 2019-003950-10 (Registered 2019) Iras Project ID: 272253 (Registered 2019) Ethics Number: 20/EE/0284.
Tissue-resident B cells orchestrate macrophage polarisation and function.
B cells play a central role in humoral immunity but also have antibody-independent functions. Studies to date have focused on B cells in blood and secondary lymphoid organs but whether B cells reside in non-lymphoid organs (NLO) in homeostasis is unknown. Here we identify, using intravenous labeling and parabiosis, a bona-fide tissue-resident B cell population in lung, liver, kidney and urinary bladder, a substantial proportion of which are B-1a cells. Tissue-resident B cells are present in neonatal tissues and also in germ-free mice NLOs, albeit in lower numbers than in specific pathogen-free mice and following co-housing with 'pet-store' mice. They spatially co-localise with macrophages and regulate their polarization and function, promoting an anti-inflammatory phenotype, in-part via interleukin-10 production, with effects on bacterial clearance during urinary tract infection. Thus, our data reveal a critical role for tissue-resident B cells in determining the homeostatic 'inflammatory set-point' of myeloid cells, with important consequences for tissue immunity.
Constructing custom-made radiotranscriptomic signatures of vascular inflammation from routine CT angiograms: a prospective outcomes validation study in COVID-19.
BACKGROUND: Direct evaluation of vascular inflammation in patients with COVID-19 would facilitate more efficient trials of new treatments and identify patients at risk of long-term complications who might respond to treatment. We aimed to develop a novel artificial intelligence (AI)-assisted image analysis platform that quantifies cytokine-driven vascular inflammation from routine CT angiograms, and sought to validate its prognostic value in COVID-19. METHODS: For this prospective outcomes validation study, we developed a radiotranscriptomic platform that uses RNA sequencing data from human internal mammary artery biopsies to develop novel radiomic signatures of vascular inflammation from CT angiography images. We then used this platform to train a radiotranscriptomic signature (C19-RS), derived from the perivascular space around the aorta and the internal mammary artery, to best describe cytokine-driven vascular inflammation. The prognostic value of C19-RS was validated externally in 435 patients (331 from study arm 3 and 104 from study arm 4) admitted to hospital with or without COVID-19, undergoing clinically indicated pulmonary CT angiography, in three UK National Health Service (NHS) trusts (Oxford, Leicester, and Bath). We evaluated the diagnostic and prognostic value of C19-RS for death in hospital due to COVID-19, did sensitivity analyses based on dexamethasone treatment, and investigated the correlation of C19-RS with systemic transcriptomic changes. FINDINGS: Patients with COVID-19 had higher C19-RS than those without (adjusted odds ratio [OR] 2·97 [95% CI 1·43-6·27], p=0·0038), and those infected with the B.1.1.7 (alpha) SARS-CoV-2 variant had higher C19-RS values than those infected with the wild-type SARS-CoV-2 variant (adjusted OR 1·89 [95% CI 1·17-3·20] per SD, p=0·012). C19-RS had prognostic value for in-hospital mortality in COVID-19 in two testing cohorts (high [≥6·99] vs low [<6·99] C19-RS; hazard ratio [HR] 3·31 [95% CI 1·49-7·33], p=0·0033; and 2·58 [1·10-6·05], p=0·028), adjusted for clinical factors, biochemical biomarkers of inflammation and myocardial injury, and technical parameters. The adjusted HR for in-hospital mortality was 8·24 (95% CI 2·16-31·36, p=0·0019) in patients who received no dexamethasone treatment, but 2·27 (0·69-7·55, p=0·18) in those who received dexamethasone after the scan, suggesting that vascular inflammation might have been a therapeutic target of dexamethasone in COVID-19. Finally, C19-RS was strongly associated (r=0·61, p=0·00031) with a whole blood transcriptional module representing dysregulation of coagulation and platelet aggregation pathways. INTERPRETATION: Radiotranscriptomic analysis of CT angiography scans introduces a potentially powerful new platform for the development of non-invasive imaging biomarkers. Application of this platform in routine CT pulmonary angiography scans done in patients with COVID-19 produced the radiotranscriptomic signature C19-RS, a marker of cytokine-driven inflammation driving systemic activation of coagulation and responsible for adverse clinical outcomes, which predicts in-hospital mortality and might allow targeted therapy. FUNDING: Engineering and Physical Sciences Research Council, British Heart Foundation, Oxford BHF Centre of Research Excellence, Innovate UK, NIHR Oxford Biomedical Research Centre, Wellcome Trust, Onassis Foundation.
Pseudotime dynamics of T cells in pancreatic ductal adenocarcinoma inform distinct functional states within the regulatory and cytotoxic T cells
Pancreatic ductal adenocarcinoma (PDAC) is among the deadliest types of cancer and has a 5-year survival of less than 8% owing to its complex biology. As PDAC is refractory to immunotherapy, we need to understand the functional dynamics of T cells in the PDAC microenvironment to develop alternative therapeutic strategies. In this study, we performed RNA velocity-based pseudotime analysis on a scRNA-seq dataset from surgically resected human PDAC specimens to gain insight into temporal gene expression patterns that best characterize the cell fates. The tumor microenvironment was seen to encompass a range of terminal states for the T cell trajectories with suppressive and non-tumor-responsive T cells dominating them. However, the results also reveal the existence of a functional branch of the T cell population that was not transitioning to exhausted and senescent states. These findings reveal various microenvironmental signals driving T cell patterns which can be useful in identifying new therapeutic avenues.
Temporality of body mass index, blood tests, comorbidities and medication use as early markers for pancreatic ductal adenocarcinoma (PDAC): a nested case-control study.
OBJECTIVE: Prior studies identified clinical factors associated with increased risk of pancreatic ductal adenocarcinoma (PDAC). However, little is known regarding their time-varying nature, which could inform earlier diagnosis. This study assessed temporality of body mass index (BMI), blood-based markers, comorbidities and medication use with PDAC risk . DESIGN: We performed a population-based nested case-control study of 28 137 PDAC cases and 261 219 matched-controls in England. We described the associations of biomarkers with risk of PDAC using fractional polynomials and 5-year time trends using joinpoint regression. Associations with comorbidities and medication use were evaluated using conditional logistic regression. RESULTS: Risk of PDAC increased with raised HbA1c, liver markers, white blood cell and platelets, while following a U-shaped relationship for BMI and haemoglobin. Five-year trends showed biphasic BMI decrease and HbA1c increase prior to PDAC; early-gradual changes 2-3 years prior, followed by late-rapid changes 1-2 years prior. Liver markers and blood counts (white blood cell, platelets) showed monophasic rapid-increase approximately 1 year prior. Recent diagnosis of pancreatic cyst, pancreatitis, type 2 diabetes and initiation of certain glucose-lowering and acid-regulating therapies were associated with highest risk of PDAC. CONCLUSION: Risk of PDAC increased with raised HbA1c, liver markers, white blood cell and platelets, while followed a U-shaped relationship for BMI and haemoglobin. BMI and HbA1c derange biphasically approximately 3 years prior while liver markers and blood counts (white blood cell, platelets) derange monophasically approximately 1 year prior to PDAC. Profiling these in combination with their temporality could inform earlier PDAC diagnosis.