Germline genetic variation and predicting immune checkpoint inhibitor induced toxicity

Immune checkpoint inhibitor (ICI) therapy has revolutionised the treatment of various cancer types. ICIs reinstate T-cell function to elicit an anti-cancer immune response. The resulting immune response can however have off-target effects which manifest as autoimmune type serious immune-related adverse events (irAE) in ~10–55% of patients treated. It is currently challenging to predict both who will experience irAEs and to what severity. Identification of patients at high risk of serious irAE would revolutionise patient care. While the pathogenesis driving irAE development is still unclear, host genetic factors are proposed to be key determinants of these events. This review presents current evidence supporting the role of the host genome in determining risk of irAE. We summarise the spectrum and timing of irAEs following treatment with ICIs and describe currently reported germline genetic variation associated with expression of immuno-modulatory factors within the cancer immunity cycle, development of autoimmune disease and irAE occurrence. We propose that germline genetic determinants of host immune function and autoimmune diseases could also explain risk of irAE development. We also endorse genome-wide association studies of patients being treated with ICIs to identify genetic variants that can be used in polygenic risk scores to predict risk of irAE

Retrospective harm benefit analysis of pre-clinical animal research for six treatment interventions

The harm benefit analysis (HBA) is the cornerstone of animal research regulation and is considered to be a key ethical safeguard for animals. The HBA involves weighing the anticipated benefits of animal research against its predicted harms to animals but there are doubts about how objective and accountable this process is.i. To explore the harms to animals involved in pre-clinical animal studies and to assess these against the benefits for humans accruing from these studies; ii. To test the feasibility of conducting this type of retrospective HBA.Data on harms were systematically extracted from a sample of pre-clinical animal studies whose clinical relevance had already been investigated by comparing systematic reviews of the animal studies with systematic reviews of human studies for the same interventions (antifibrinolytics for haemorrhage, bisphosphonates for osteoporosis, corticosteroids for brain injury, Tirilazad for stroke, antenatal corticosteroids for neonatal respiratory distress and thrombolytics for stroke). Clinical relevance was also explored in terms of current clinical practice. Harms were categorised for severity using an expert panel. The quality of the research and its impact were considered. Bateson's Cube was used to conduct the HBA.The most common assessment of animal harms by the expert panel was 'severe'. Reported use of analgesia was rare and some animals (including most neonates) endured significant procedures with no, or only light, anaesthesia reported. Some animals suffered iatrogenic harms. Many were kept alive for long periods post-experimentally but only 1% of studies reported post-operative care. A third of studies reported that some animals died prior to endpoints. All the studies were of poor quality. Having weighed the actual harms to animals against the actual clinical benefits accruing from these studies, and taking into account the quality of the research and its impact, less than 7% of the studies were permissible according to Bateson's Cube: only the moderate bisphosphonate studies appeared to minimise harms to animals whilst being associated with benefit for humans.This is the first time the accountability of the HBA has been systematically explored across a range of pre-clinical animal studies. The regulatory systems in place when these studies were conducted failed to safeguard animals from severe suffering or to ensure that only beneficial, scientifically rigorous research was conducted. Our findings indicate a pressing need to: i. review regulations, particularly those that permit animals to suffer severe harms; ii. reform the processes of prospectively assessing pre-clinical animal studies to make them fit for purpose; and iii. systematically evaluate the benefits of pre-clinical animal research to permit a more realistic assessment of its likely future benefits

Mucosal-associated invariant T (MAIT) cells are activated in the gastrointestinal tissue of patients with combination ipilimumab and nivolumab therapy-related colitis in a pathology distinct from ulcerative colitis

The aim of this study was to investigate the pathogenesis of combination ipilimumab and nivolumab-associated colitis (IN-COL) by measuring gut-derived and peripheral blood mononuclear cell (GMNC; PBMC) profiles. We studied GMNC and PBMC from patients with IN-COL, IN-treated with no adverse-events (IN-NAE), ulcerative colitis (UC) and healthy volunteers using flow cytometry. In the gastrointestinal-derived cells we found high levels of activated CD8+ T cells and mucosal-associated invariant T (MAIT) cells in IN-COL, changes that were not evident in IN-NAE or UC. UC, but not IN-C, was associated with a high proportion of regulatory T cells (Treg). We sought to determine if local tissue responses could be measured in peripheral blood. Peripherally, checkpoint inhibition instigated a rise in activated memory CD4+ and CD8+ T cells, regardless of colitis. Low circulating MAIT cells at baseline was associated with IN-COL patients compared with IN-NAE in one of two cohorts. UC, but not INCOL, was associated with high levels of circulating plasmablasts. In summary, the alterations in T cell subsets measured in IN-COL-affected tissue, characterized by high levels of activated CD8+ T cells and MAIT cells and a low proportion of Treg, reflected a pathology distinct from UC. These tissue changes differed from the periphery, where T cell activation was a widespread on-treatment effect, and circulating MAIT cell count was low but not reliably predictive of colitis

Checkpoint Inhibition Reduces the Threshold for Drug-Specific T-Cell Priming and Increases the Incidence of Sulfasalazine Hypersensitivity

An emerging clinical issue associated with immune-oncology agents is the collateral effects on the tolerability of concomitant medications. One report of this phenomenon was the increased incidence of hypersensitivity reactions observed in patients receiving concurrent immune checkpoint inhibitors (ICIs) and sulfasalazine (SLZ). Thus, the aim of this study was to characterize the T cells involved in the pathogenesis of such reactions, and recapitulate the effects of inhibitory checkpoint blockade on de-novo priming responses to compounds within in vitro platforms. A regulatory competent human dendritic cell/T-cell coculture assay was used to model the effects of ICIs on de novo nitroso sulfamethoxazole- and sulfapyridine (SP) (the sulfonamide component of SLZ) hydroxylamine-specific priming responses. The role of T cells in the pathogenesis of the observed reactions was explored in 3 patients through phenotypic characterization of SP/sulfapyridine hydroxylamine (SPHA)-responsive T-cell clones (TCC), and assessment of cross-reactivity and pathways of T-cell activation. Augmentation of the frequency of responding drug-specific T cells and intensity of the T-cell response was observed with PD-1/PD-L1 blockade. Monoclonal populations of SP- and SPHA-responsive T cells were isolated from all 3 patients. A core secretory effector molecule profile (IFN-γ, IL-13, granzyme B, and perforin) was identified for SP and SPHA-responsive TCC, which proceeded through Pi and hapten mechanisms, respectively. Data presented herein provides evidence that drug-responsive T cells are effectors of hypersensitivity reactions observed in oncology patients administered ICIs and SLZ. Perturbation of drug-specific T-cell priming is a plausible explanation for clinical observations of how an increased incidence of these adverse events is occurring

Genome-wide association study identifies a variant in HDAC9 associated with large vessel ischemic stroke

Genetic factors have been implicated in stroke risk but few replicated associations have been reported. We conducted a genome-wide association study (GWAS) in ischemic stroke and its subtypes in 3,548 cases and 5,972 controls, all of European ancestry. Replication of potential signals was performed in 5,859 cases and 6,281 controls. We replicated reported associations between variants close to PITX2 and ZFHX3 with cardioembolic stroke, and a 9p21 locus with large vessel stroke. We identified a novel association for a SNP within the histone deacetylase 9(HDAC9) gene on chromosome 7p21.1 which was associated with large vessel stroke including additional replication in a further 735 cases and 28583 controls (rs11984041, combined P = 1.87×10−11, OR=1.42 (95% CI) 1.28-1.57). All four loci exhibit evidence for heterogeneity of effect across the stroke subtypes, with some, and possibly all, affecting risk for only one subtype. This suggests differing genetic architectures for different stroke subtypes

Language Models (Mostly) Know What They Know

We study whether language models can evaluate the validity of their own claims and predict which questions they will be able to answer correctly. We first show that larger models are well-calibrated on diverse multiple choice and true/false questions when they are provided in the right format. Thus we can approach self-evaluation on open-ended sampling tasks by asking models to first propose answers, and then to evaluate the probability "P(True)" that their answers are correct. We find encouraging performance, calibration, and scaling for P(True) on a diverse array of tasks. Performance at self-evaluation further improves when we allow models to consider many of their own samples before predicting the validity of one specific possibility. Next, we investigate whether models can be trained to predict "P(IK)", the probability that "I know" the answer to a question, without reference to any particular proposed answer. Models perform well at predicting P(IK) and partially generalize across tasks, though they struggle with calibration of P(IK) on new tasks. The predicted P(IK) probabilities also increase appropriately in the presence of relevant source materials in the context, and in the presence of hints towards the solution of mathematical word problems. We hope these observations lay the groundwork for training more honest models, and for investigating how honesty generalizes to cases where models are trained on objectives other than the imitation of human writing.Comment: 23+17 pages; refs added, typos fixe