Elucidating Prostate Cancer Behaviour During Treatment via Low-pass Whole-genome Sequencing of Circulating Tumour DNA

Cabazitaxel; Cell-free DNA; Tumour fractionCabazitaxel; ADN lliure de cèl·lules; Fracció tumoralCabazitaxel; ADN libre de células; Fracción tumoralBackground Better blood tests to elucidate the behaviour of metastatic castration-resistant prostate cancer (mCRPC) are urgently needed to drive therapeutic decisions. Plasma cell-free DNA (cfDNA) comprises normal and circulating tumour DNA (ctDNA). Low-pass whole-genome sequencing (lpWGS) of ctDNA can provide information on mCRPC behaviour. Objective To validate and clinically qualify plasma lpWGS for mCRPC. Design, setting, and participants Plasma lpWGS data were obtained for mCRPC patients consenting to optional substudies of two prospective phase 3 trials (FIRSTANA and PROSELICA). In FIRSTANA, chemotherapy-naïve patients were randomised to treatment with docetaxel (75 mg/m2) or cabazitaxel (20 or 25 mg/m2). In PROSELICA, patients previously treated with docetaxel were randomised to 20 or 25 mg/m2 cabazitaxel. lpWGS data were generated from 540 samples from 188 mCRPC patients acquired at four different time points (screening, cycle 1, cycle 4, and end of study). Outcome measurements and statistical analysis lpWGS data for ctDNA were evaluated for prognostic, response, and tumour genomic measures. Associations with response and survival data were determined for tumour fraction. Genomic biomarkers including large-scale transition (LST) scores were explored in the context of prior treatments. Results and limitations Plasma tumour fraction was prognostic for overall survival in univariable and stratified multivariable analyses (hazard ratio 1.75, 95% confidence interval 1.08–2.85; p = 0.024) and offered added value compared to existing biomarkers (C index 0.722 vs 0.709; p = 0.021). Longitudinal changes were associated with drug response. PROSELICA samples were enriched for LSTs (p = 0.029) indicating genomic instability, and this enrichment was associated with prior abiraterone and enzalutamide treatment but not taxane or radiation therapy. Higher LSTs were correlated with losses of RB1/RNASEH2B, independent of BRCA2 loss. Conclusions Plasma lpWGS of ctDNA describes CRPC behaviour, providing prognostic and response data of clinical relevance. The added prognostic value of the ctDNA fraction over established biomarkers should be studied further.This work was supported by Prostate Cancer UK and the Movember Foundation through the London Movember Centre of Excellence (CEO13-2-002), Cancer Research UK (Centre Programme grant), Experimental Cancer Medicine Centre grant funding from Cancer Research UK and the Department of Health, and Biomedical Research Centre funding to the Royal Marsden ECMC (CRM064X). George Seed was funded by a Prostate Cancer UK PhD Studentship (grant ref. TLD-S15-006, 2016–2020) and a Prostate Cancer UK research fellowship (grant ref. TLD-PF19-005, from 2021). Semini Sumanasuriya was funded by a Prostate Cancer UK grant (ref. RIA1 5-ST2-O18). The authors are grateful for support and funding from Sanofi Aventis. The sponsor played a role in collection of the data and review and approval of the manuscript

Placental magnetic resonance imaging in chronic hypertension: A case-control study

Introduction We aimed to explore the use of magnetic resonance imaging (MRI) in vivo as a tool to elucidate the placental phenotype in women with chronic hypertension. Methods In case-control study, women with chronic hypertension and those with uncomplicated pregnancies were imaged using either a 3T Achieva or 1.5T Ingenia scanner. T2-weighted images, diffusion weighted and T1/T2* relaxometry data was acquired. Placental T2*, T1 and apparent diffusion coefficient (ADC) maps were calculated. Results 129 women (43 with chronic hypertension and 86 uncomplicated pregnancies) were imaged at a median of 27.7 weeks’ gestation (interquartile range (IQR) 23.9–32.1) and 28.9 (IQR 26.1–32.9) respectively. Visual analysis of T2-weighted imaging demonstrated placentae to be either appropriate for gestation or to have advanced lobulation in women with chronic hypertension, resulting in a greater range of placental mean T2* values for a given gestation, compared to gestation-matched controls. Both skew and kurtosis (derived from histograms of T2* values across the whole placenta) increased with advancing gestational age at imaging in healthy pregnancies; women with chronic hypertension had values overlapping those in the control group range. Upon visual assessment, the mean ADC declined in the third trimester, with a corresponding decline in placental mean T2* values and showed an overlap of values between women with chronic hypertension and the control group. Discussion A combined placental MR examination including T2 weighted imaging, T2*, T1 mapping and diffusion imaging demonstrates varying placental phenotypes in a cohort of women with chronic hypertension, showing overlap with the control group

Clinical Utility of Circulating Tumour Cell Androgen Receptor Splice Variant-7 Status in Metastatic Castration-resistant Prostate Cancer.

Abstract Background Detection of androgen receptor splice variant-7 (AR-V7) mRNA in circulating tumour cells (CTCs) is associated with worse outcome in metastatic castration-resistant prostate cancer (mCRPC). However, studies rarely report comparisons with CTC counts and biopsy AR-V7 protein expression. Objective To determine the reproducibility of AdnaTest CTC AR-V7 testing, and associations with clinical characteristics, CellSearch CTC counts, tumour biopsy AR-V7 protein expression and overall survival (OS). Design, setting, and participants CTC AR-V7 status was determined for 227 peripheral blood samples, from 181 mCRPC patients with CTC counts (202 samples; 136 patients) and matched mCRPC biopsies (65 samples; 58 patients). Outcome measurements and statistical analysis CTC AR-V7 status was associated with clinical characteristics, CTC counts, and tissue biopsy AR-V7 protein expression. The association of CTC AR-V7 status and other baseline variables with OS was determined. Results and limitations Of the samples, 35% were CTC+/AR-V7+. CTC+/AR-V7+ samples had higher CellSearch CTC counts (median CTC; interquartile range [IQR]: 60, 19–184 vs 9, 2–64; Mann-Whitney test p Conclusions Studies reporting the prognostic relevance of CTC AR-V7 status must account for CTC counts. Discordant CTC AR-V7 results and AR-V7 protein expression in matched, same-patient biopsies are reported. Patient summary Liquid biopsies that determine circulating tumour cell androgen receptor splice variant-7 status have the potential to impact treatment decisions in metastatic castration-resistant prostate cancer patients. Robust clinical qualification of these assays is required before their routine use

Bacterial Signatures of Paediatric Respiratory Disease : An Individual Participant Data Meta-Analysis

Introduction: The airway microbiota has been linked to specific paediatric respiratory diseases, but studies are often small. It remains unclear whether particular bacteria are associated with a given disease, or if a more general, non-specific microbiota association with disease exists, as suggested for the gut. We investigated overarching patterns of bacterial association with acute and chronic paediatric respiratory disease in an individual participant data (IPD) meta-analysis of 16S rRNA gene sequences from published respiratory microbiota studies.Methods: We obtained raw microbiota data from public repositories or via communication with corresponding authors. Cross-sectional analyses of the paediatric (10 case subjects were included. Sequence data were processed using a uniform bioinformatics pipeline, removing a potentially substantial source of variation. Microbiota differences across diagnoses were assessed using alpha- and beta-diversity approaches, machine learning, and biomarker analyses.Results: We ultimately included 20 studies containing individual data from 2624 children. Disease was associated with lower bacterial diversity in nasal and lower airway samples and higher relative abundances of specific nasal taxa including Streptococcus and Haemophilus. Machine learning success in assigning samples to diagnostic groupings varied with anatomical site, with positive predictive value and sensitivity ranging from 43 to 100 and 8 to 99%, respectively.Conclusion: IPD meta-analysis of the respiratory microbiota across multiple diseases allowed identification of a non-specific disease association which cannot be recognised by studying a single disease. Whilst imperfect, machine learning offers promise as a potential additional tool to aid clinical diagnosis.Peer reviewe

To Eat and To Be : food as Differenciation Policy in Spanish America, 16th and 17th Centuries

ABSTRACT: This paper demonstrates that food served as a marker of social differentiation during the 16th and 17th centuries in the Spanish possessions in America, not only in economic terms but also in the sense that food was associated with the social stratum to which a person belonged. Each one was oblidged to eat foods associated with his or her "natural" stratum. This complex hierarchical model of society was based on European patterns coming from the Middle Ages, such as the Great Chain of Being and humoral theory. This model was reinforced in the early modern period, and it took on new characteristics in America, where it was used to differentiate Spaniards, Creoles, Mestizos and Indians.RESUMEN: Este artículo muestra cómo la alimentación servía como un elemento de diferenciación social durante los siglos XVI y XVII, en la América española, no solo como un factor económico, sino asociado a la calidad o estado al que pertenecieran las personas. En este sentido, a cada uno le correspondía comer aquello que era propio de su condición estamental. Este complejo modelo de jerarquización social estaba basado en principios europeos que venían desde la Edad Media, como la gran cadena del ser y la teoría humoral. En la edad moderna, el modelo se reforzó y en América tomó nuevas características, por la forma en que se buscó diferenciar entre españoles, criollos, mestizos e indios

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2–4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Colliding Worlds: Asteroid research and the legitimization of war in space

Accepted versio

External validation of prognostic models predicting pre-eclampsia : individual participant data meta-analysis

Abstract Background Pre-eclampsia is a leading cause of maternal and perinatal mortality and morbidity. Early identification of women at risk during pregnancy is required to plan management. Although there are many published prediction models for pre-eclampsia, few have been validated in external data. Our objective was to externally validate published prediction models for pre-eclampsia using individual participant data (IPD) from UK studies, to evaluate whether any of the models can accurately predict the condition when used within the UK healthcare setting. Methods IPD from 11 UK cohort studies (217,415 pregnant women) within the International Prediction of Pregnancy Complications (IPPIC) pre-eclampsia network contributed to external validation of published prediction models, identified by systematic review. Cohorts that measured all predictor variables in at least one of the identified models and reported pre-eclampsia as an outcome were included for validation. We reported the model predictive performance as discrimination (C-statistic), calibration (calibration plots, calibration slope, calibration-in-the-large), and net benefit. Performance measures were estimated separately in each available study and then, where possible, combined across studies in a random-effects meta-analysis. Results Of 131 published models, 67 provided the full model equation and 24 could be validated in 11 UK cohorts. Most of the models showed modest discrimination with summary C-statistics between 0.6 and 0.7. The calibration of the predicted compared to observed risk was generally poor for most models with observed calibration slopes less than 1, indicating that predictions were generally too extreme, although confidence intervals were wide. There was large between-study heterogeneity in each model’s calibration-in-the-large, suggesting poor calibration of the predicted overall risk across populations. In a subset of models, the net benefit of using the models to inform clinical decisions appeared small and limited to probability thresholds between 5 and 7%. Conclusions The evaluated models had modest predictive performance, with key limitations such as poor calibration (likely due to overfitting in the original development datasets), substantial heterogeneity, and small net benefit across settings. The evidence to support the use of these prediction models for pre-eclampsia in clinical decision-making is limited. Any models that we could not validate should be examined in terms of their predictive performance, net benefit, and heterogeneity across multiple UK settings before consideration for use in practice. Trial registration PROSPERO ID: CRD42015029349