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In forced-choice questionnaires, respondents have to make choices between two or more items presented at the same time. Several IRT models have been developed to link respondent choices to underlying psychological attributes, including the recent MUPP (Stark et al. in Appl Psychol Meas 29:184–203,  2005 ) and Thurstonian IRT (Brown and Maydeu-Olivares in Educ Psychol Meas 71:460–502,  2011 ) models. In the present article, a common framework is proposed that describes forced-choice models along three axes: (1) the forced-choice format used; (2) the measurement model for the relationships between items and psychological attributes they measure; and (3) the decision model for choice behavior. Using the framework, fundamental properties of forced-choice measurement of individual differences are considered. It is shown that the scale origin for the attributes is generally identified in questionnaires using either unidimensional or multidimensional comparisons. Both dominance and ideal point models can be used to provide accurate forced-choice measurement; and the rules governing accurate person score estimation with these models are remarkably similar.

Identifying driver mutations in cancer is notoriously difficult. To date, recurrence of a mutation in patients remains one of the most reliable markers of mutation driver status. However, some mutations are more likely to occur than others due to differences in background mutation rates arising from various forms of infidelity of DNA replication and repair machinery, endogenous, and exogenous mutagens. We calculated nucleotide and codon mutability to study the contribution of background processes in shaping the observed mutational spectrum in cancer. We developed and tested probabilistic pan-cancer and cancer-specific models that adjust the number of mutation recurrences in patients by background mutability in order to find mutations which may be under selection in cancer. We showed that mutations with higher mutability values had higher observed recurrence frequency, especially in tumor suppressor genes. This trend was prominent for nonsense and silent mutations or mutations with neutral functional impact. In oncogenes, however, highly recurring mutations were characterized by relatively low mutability, resulting in an inversed U-shaped trend. Mutations not yet observed in any tumor had relatively low mutability values, indicating that background mutability might limit mutation occurrence. We compiled a dataset of missense mutations from 58 genes with experimentally validated functional and transforming impacts from various studies. We found that mutability of driver mutations was lower than that of passengers and consequently adjusting mutation recurrence frequency by mutability significantly improved ranking of mutations and driver mutation prediction. Even though no training on existing data was involved, our approach performed similarly or better to the state-of-the-art methods.

Immune checkpoint blockade (ICB) benefits only a small subset of patients with small cell lung cancer (SCLC), yet the mechanisms driving benefit are poorly understood. To identify predictors of clinical benefit to ICB, we performed immunogenomic profiling of tumor samples from patients with relapsed SCLC. Tumors of patients who derive clinical benefit from ICB exhibit cytotoxic T-cell infiltration, high expression of antigen processing and presentation machinery (APM) genes, and low neuroendocrine (NE) differentiation. However, elevated Notch signaling, which positively correlates with low NE differentiation, most significantly predicts clinical benefit to ICB. Activation of Notch signaling in a NE human SCLC cell line induces a low NE phenotype, marked by increased expression of APM genes, demonstrating a mechanistic link between Notch activation, low NE differentiation and increased intrinsic tumor immunity. Our findings suggest Notch signaling as a determinant of response to ICB in SCLC. Immune checkpoint blockade (ICB) benefits only a small subset of patients with small cell lung cancer (SCLC) and the mechanisms driving benefit are poorly understood. Here, the authors show that elevated Notch signaling predicts clinical benefit in ICB in relapsed SCLC.

TDP-43 is an RNA-binding protein with a crucial nuclear role in splicing, and mislocalises from the nucleus to the cytoplasm in a range of neurodegenerative disorders. TDP-43 proteinopathy spans a spectrum of incurable, heterogeneous, and increasingly prevalent neurodegenerative diseases, including the amyotrophic lateral sclerosis and frontotemporal dementia disease spectrum and a significant fraction of Alzheimer’s disease. There are currently no directed disease-modifying therapies for TDP-43 proteinopathies, and no way to distinguish who is affected before death. It is now clear that TDP-43 proteinopathy leads to a number of molecular changes, including the de-repression and inclusion of cryptic exons. Importantly, some of these cryptic exons lead to the loss of crucial neuronal proteins and have been shown to be key pathogenic players in disease pathogenesis (e.g. , STMN2 ), as well as being able to modify disease progression (e.g. , UNC13A ). Thus, these aberrant splicing events make promising novel therapeutic targets to restore functional gene expression. Moreover, presence of these cryptic exons is highly specific to patients and areas of the brain affected by TDP-43 proteinopathy, offering the potential to develop biomarkers for early detection and stratification of patients. In summary, the discovery of cryptic exons gives hope for novel diagnostics and therapeutics on the horizon for TDP-43 proteinopathies.

We introduce QuEST, the Quantum Exact Simulation Toolkit, and compare it to ProjectQ, qHipster and a recent distributed implementation of Quantum++. QuEST is the first open source, hybrid multithreaded and distributed, GPU accelerated simulator of universal quantum circuits. Embodied as a C library, it is designed so that a user’s code can be deployed seamlessly to any platform from a laptop to a supercomputer. QuEST is capable of simulating generic quantum circuits of general one and two-qubit gates and multi-qubit controlled gates, on pure and mixed states, represented as state-vectors and density matrices, and under the presence of decoherence. Using the ARCUS and ARCHER supercomputers, we benchmark QuEST’s simulation of random circuits of up to 38 qubits, distributed over up to 2048 compute nodes, each with up to 24 cores. We directly compare QuEST’s performance to ProjectQ’s on single machines, and discuss the differences in distribution strategies of QuEST, qHipster and Quantum++. QuEST shows excellent scaling, both strong and weak, on multicore and distributed architectures.

Germline RUNX1 variants have been identified in relation to myeloid malignancy predisposition, with lymphoid hematological malignancies present at a lower frequency in families. In this issue of the JCI, Li and Yang et al. examined the frequency and type of germline RUNX1 variants in pediatric patients with acute lymphoblastic leukemia (ALL). Patients with T cell ALL (T-ALL) harbored rare, damaging RUNX1 mutations that were not seen in patients with B cell ALL (B-ALL). Further, several of the T-ALL-associated RUNX1 variants had potential dominant-negative activity. RUNX1-mutated T-ALL cases were also associated with somatic JAK3 mutations and enriched for the early T cell precursor (ETP) leukemia subtype, a finding that was validated when RUNX1 and JAK3 mutations were combined in mice. This study confirms germline RUNX1 predisposition beyond myeloid malignancy, demonstrates the importance of examining both germline and somatic mutations in malignancy cohorts, and demarcates the ETP ALL subtype as a flag for germline predisposition in patients.

Imaging has traditionally played a minor role in the diagnosis and staging of prostate cancer. However, recent controversies generated by the use of prostate-specific antigen (PSA) screening followed by random biopsy have encouraged the development of new imaging methods for prostate cancer. Multiparametric magnetic resonance imaging (mpMRI) has emerged as the imaging method best able to detect clinically significant prostate cancers and to guide biopsies. Here, the authors explain what mpMRI is and how it is used clinically, especially with regard to high-risk populations, and we discuss the impact of mpMRI on treatment decisions for men with prostate cancer.

Heterogeneous nuclear ribonucleoproteins (HnRNPs) are a group of ubiquitously expressed RNA-binding proteins implicated in the regulation of all aspects of nucleic acid metabolism. HnRNP K is a member of this highly versatile hnRNP family. Pathological redistribution of hnRNP K to the cytoplasm has been linked to the pathogenesis of several malignancies but, until now, has been underexplored in the context of neurodegenerative disease. Here we show hnRNP K mislocalisation in pyramidal neurons of the frontal cortex to be a novel neuropathological feature that is associated with both frontotemporal lobar degeneration and ageing. HnRNP K mislocalisation is mutually exclusive to TDP-43 and tau pathological inclusions in neurons and was not observed to colocalise with mitochondrial, autophagosomal or stress granule markers. De-repression of cryptic exons in RNA targets following TDP-43 nuclear depletion is an emerging mechanism of potential neurotoxicity in frontotemporal lobar degeneration and the mechanistically overlapping disorder amyotrophic lateral sclerosis. We silenced hnRNP K in neuronal cells to identify the transcriptomic consequences of hnRNP K nuclear depletion. Intriguingly, by performing RNA-seq analysis we find that depletion of hnRNP K induces 101 novel cryptic exon events. We validated cryptic exon inclusion in an SH-SY5Y hnRNP K knockdown and in FTLD brain exhibiting hnRNP K nuclear depletion. We, therefore, present evidence for hnRNP K mislocalisation to be associated with FTLD and for this to induce widespread changes in splicing.

Genome-wide methylome sequencing of serial samples obtained from patients with acute myeloid leukemia reveals that epigenetic alleles and genetic alleles follow independent courses during disease evolution. Genetic heterogeneity contributes to clinical outcome and progression of most tumors, but little is known about allelic diversity for epigenetic compartments, and almost no data exist for acute myeloid leukemia (AML). We examined epigenetic heterogeneity as assessed by cytosine methylation within defined genomic loci with four CpGs (epialleles), somatic mutations, and transcriptomes of AML patient samples at serial time points. We observed that epigenetic allele burden is linked to inferior outcome and varies considerably during disease progression. Epigenetic and genetic allelic burden and patterning followed different patterns and kinetics during disease progression. We observed a subset of AMLs with high epiallele and low somatic mutation burden at diagnosis, a subset with high somatic mutation and lower epiallele burdens at diagnosis, and a subset with a mixed profile, suggesting distinct modes of tumor heterogeneity. Genes linked to promoter-associated epiallele shifts during tumor progression showed increased single-cell transcriptional variance and differential expression, suggesting functional impact on gene regulation. Thus, genetic and epigenetic heterogeneity can occur with distinct kinetics likely to affect the biological and clinical features of tumors.

Individuals with cancer, particularly those who are receiving systemic anticancer treatments, have been postulated to be at increased risk of mortality from COVID-19. This conjecture has considerable effect on the treatment of patients with cancer and data from large, multicentre studies to support this assumption are scarce because of the contingencies of the pandemic. We aimed to describe the clinical and demographic characteristics and COVID-19 outcomes in patients with cancer. In this prospective observational study, all patients with active cancer and presenting to our network of cancer centres were eligible for enrolment into the UK Coronavirus Cancer Monitoring Project (UKCCMP). The UKCCMP is the first COVID-19 clinical registry that enables near real-time reports to frontline doctors about the effects of COVID-19 on patients with cancer. Eligible patients tested positive for severe acute respiratory syndrome coronavirus 2 on RT-PCR assay from a nose or throat swab. We excluded patients with a radiological or clinical diagnosis of COVID-19, without a positive RT-PCR test. The primary endpoint was all-cause mortality, or discharge from hospital, as assessed by the reporting sites during the patient hospital admission. From March 18, to April 26, 2020, we analysed 800 patients with a diagnosis of cancer and symptomatic COVID-19. 412 (52%) patients had a mild COVID-19 disease course. 226 (28%) patients died and risk of death was significantly associated with advancing patient age (odds ratio 9·42 [95% CI 6·56–10·02]; p<0·0001), being male (1·67 [1·19–2·34]; p=0·003), and the presence of other comorbidities such as hypertension (1·95 [1·36–2·80]; p<0·001) and cardiovascular disease (2·32 [1·47–3·64]). 281 (35%) patients had received cytotoxic chemotherapy within 4 weeks before testing positive for COVID-19. After adjusting for age, gender, and comorbidities, chemotherapy in the past 4 weeks had no significant effect on mortality from COVID-19 disease, when compared with patients with cancer who had not received recent chemotherapy (1·18 [0·81–1·72]; p=0·380). We found no significant effect on mortality for patients with immunotherapy, hormonal therapy, targeted therapy, radiotherapy use within the past 4 weeks. Mortality from COVID-19 in cancer patients appears to be principally driven by age, gender, and comorbidities. We are not able to identify evidence that cancer patients on cytotoxic chemotherapy or other anticancer treatment are at an increased risk of mortality from COVID-19 disease compared with those not on active treatment. University of Birmingham, University of Oxford.