Guest Editors Asier Unciti-Broceta and Professor Evgeny Rebrov introduce this cross-journal collection of articles, showcasing research work presented at the 2nd International Conference on Unconventional Catalysis, Reactors & Applications held on September 21–23, 2022, in Leamington Spa, UK.

BackgroundOvarian carcinosarcoma (OCS) is an exceptionally aggressive and understudied ovarian cancer type harbouring distinct carcinomatous and sarcomatous compartments. Here, we seek to identify shared and compartment-specific events that may represent potential therapeutic targets and candidate drivers of sarcomatous compartment formation through epithelial-to-mesenchymal transition (EMT).MethodsWe performed multiomic profiling (exome sequencing, RNA-sequencing, microRNA profiling) of paired carcinomatous and sarcomatous components in 12 OCS cases.ResultsWhile paired sarcomatous and carcinomatous compartments demonstrate substantial genomic similarities, multiple loci are recurrently copy number-altered between components; regions containing GNAS and SRC are recurrently gained within the sarcomatous compartment. CCNE1 gain is a common event in OCS, occurring more frequently than in high grade serous ovarian carcinoma (HGSOC). Transcriptomic analysis suggests increased MAPK activity and subtype switching toward poor prognosis HGSOC-derived transcriptomic subtypes within the sarcomatous component. The two compartments show global differences in microRNA profiles, with differentially expressed microRNAs targeting EMT-related genes (SIRT1, ZEB2) and regulators of pro-tumourigenic pathways (TGFβ, NOTCH); chrX is a highly enriched target of these microRNAs and is also frequently deleted across samples. The sarcomatous component harbours significantly fewer CD8-positive cells, suggesting poorer immune engagement.ConclusionCCNE1 gain and chrX loss are frequent in OCS. SRC gain, increased GNAS expression and microRNA dysregulation represent potential mechanisms driving sarcomatous compartment formation.

Deletion of CDKN2A occurs in 50% of glioblastomas (GBM), and IFNA locus deletion in 25%. These genes reside closely on chromosome 9. We investigated whether CDKN2A and IFNA were co-deleted within the same heterogeneous tumour and their prognostic implications. We assessed CDKN2A and IFNA14 deletions in 45 glioma samples using an in-house three-colour FISH probe. We examined the correlation between p16INK4a protein expression (via IHC) and CDKN2A deletion along with the impact of these genomic events on patient survival. FISH analyses demonstrated that grades II and III had either wildtype (wt) or amplified CDKN2A/IFNA14, whilst 44% of GBMs harboured homozygous deletions of both genes. Cores with CDKN2A homozygous deletion (n = 11) were negative for p16INK4a. Twenty p16INK4a positive samples lacked CDKN2A deletion with some of cells showing negative p16INK4a. There was heterogeneity in IFNA14/CDKN2A ploidy within each GBM. Survival analyses of primary GBMs suggested a positive association between increased p16INK4a and longer survival; this persisted when considering CDKN2A/IFNA14 status. Furthermore, wt (intact) CDKN2A/IFNA14 were found to be associated with longer survival in recurrent GBMs. Our data suggest that co-deletion of CDKN2A/IFNA14 in GBM negatively correlates with survival and CDKN2A-wt status correlated with longer survival, and with second surgery, itself a marker for improved patient outcomes.

GDF15, a hormone acting on the brainstem, has been implicated in the nausea and vomiting of pregnancy, including its most severe form, hyperemesis gravidarum (HG), but a full mechanistic understanding is lacking1-4. Here we report that fetal production of GDF15 and maternal sensitivity to it both contribute substantially to the risk of HG. We confirmed that higher GDF15 levels in maternal blood are associated with vomiting in pregnancy and HG. Using mass spectrometry to detect a naturally labelled GDF15 variant, we demonstrate that the vast majority of GDF15 in the maternal plasma is derived from the feto-placental unit. By studying carriers of rare and common genetic variants, we found that low levels of GDF15 in the non-pregnant state increase the risk of developing HG. Conversely, women with β-thalassaemia, a condition in which GDF15 levels are chronically high5, report very low levels of nausea and vomiting of pregnancy. In mice, the acute food intake response to a bolus of GDF15 is influenced bi-directionally by prior levels of circulating GDF15 in a manner suggesting that this system is susceptible to desensitization. Our findings support a putative causal role for fetally derived GDF15 in the nausea and vomiting of human pregnancy, with maternal sensitivity, at least partly determined by prepregnancy exposure to the hormone, being a major influence on its severity. They also suggest mechanism-based approaches to the treatment and prevention of HG.

BackgroundEpigenetic scores (EpiScores) can provide biomarkers of lifestyle and disease risk. Projecting new datasets onto a reference panel is challenging due to separation of technical and biological variation with array data. Normalisation can standardise data distributions but may also remove population-level biological variation.ResultsWe compare two birth cohorts (Lothian Birth Cohorts of 1921 and 1936 — nLBC1921 = 387 and nLBC1936 = 498) with blood-based DNA methylation assessed at the same chronological age (79 years) and processed in the same lab but in different years and experimental batches. We examine the effect of 16 normalisation methods on a novel BMI EpiScore (trained in an external cohort, n = 18,413), and Horvath’s pan-tissue DNA methylation age, when the cohorts are normalised separately and together. The BMI EpiScore explains a maximum variance of R2=24.5% in BMI in LBC1936 (SWAN normalisation). Although there are cross-cohort R2 differences, the normalisation method makes a minimal difference to within-cohort estimates. Conversely, a range of absolute differences are seen for individual-level EpiScore estimates for BMI and age when cohorts are normalised separately versus together. While within-array methods result in identical EpiScores whether a cohort is normalised on its own or together with the second dataset, a range of differences is observed for between-array methods.ConclusionsNormalisation methods returning similar EpiScores, whether cohorts are analysed separately or together, will minimise technical variation when projecting new data onto a reference panel. These methods are important for cases where raw data is unavailable and joint normalisation of cohorts is computationally expensive.

Historically, clinical trials in cancer medicine are, unfortunately, often poorly representative of the diverse populations who ultimately receive the intervention in real-world settings. This discrepancy could relate to age, extent of comorbidity, ethnicity, socioeconomic status (SES), and/or disability. This is particularly important, as medication efficacy and/or toxicity are known to be influenced by such variables. Many cancers also disproportionately affect individuals in underserved communities. If a highly selected cohort of individuals are recruited to a trial, theoretically, the findings should only be translated to equivalent cohorts in the community. Therefore, the more representative a trial cohort is of the target population, the more generalisable and applicable findings will be. If we aim to lessen disparities and improve equity, clinical trials must strive to become more inclusive, improving our knowledge of disease in these underserved groups, and therefore improving the care we provide to them in wider clinical practice. This review summarises the current European perspective on this topical issue, suggesting potential strategies to proactively improve inclusivity and diversity in cancer trials, by encouraging enthusiastic collaboration between the pharmaceutical industry, healthcare authorities, study sponsors, research networks, and clinicians.

In a living cell, proteins interact to assemble both transient and constant molecular complexes, which transfer signals/information around internal pathways. Modern proteomic techniques can identify the constituent components of these complexes, but more detailed analysis demands a network approach linking the molecules together and analyzing the emergent architectural properties. The Bioconductor package BioNAR combines a selection of existing R protocols for network analysis with newly designed original methodological features to support step-by-step analysis of biological/biomedical . Critically, BioNAR supports a pipeline approach whereby many networks and iterative analyses can be performed. Here we present a network analysis pipeline that starts from initiating a network model from a list of components/proteins and their interactions through to identifying its functional components based solely on network topology. We demonstrate that BioNAR can help users achieve a number of network analysis goals that are difficult to achieve anywhere else. This includes how users can choose the optimal clustering algorithm from a range of options based on independent annotation enrichment, and predict a protein's influence within and across multiple subcomplexes in the network and estimate the co-occurrence or linkage between metadata at the network level (e.g., diseases and functions across the network, identifying the clusters whose components are likely to share common function and mechanisms). The package is freely available in Bioconductor release 3.17: https://bioconductor.org/packages/3.17/bioc/html/BioNAR.html. © 2023 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Creating and annotating the network Support Protocol 1: Installing BioNAR from RStudio Support Protocol 2: Building the sample network from synaptome.db Basic Protocol 2: Network properties and centrality Basic Protocol 3: Network communities Basic protocol 4: Choosing the optimal clustering algorithm based on the enrichment with annotation terms Basic Protocol 5: Influencing network components and bridgeness Basic Protocol 6: Co-occurrence of the annotations.

Anthracycline-induced cardiotoxicity has a variable incidence, and the development of left ventricular dysfunction is preceded by elevations in cardiac troponin concentrations. Beta-adrenergic receptor blocker and renin-angiotensin system inhibitor therapies have been associated with modest cardioprotective effects in unselected patients receiving anthracycline chemotherapy. In a multicenter, prospective, randomized, open-label, blinded end-point trial, patients with breast cancer and non-Hodgkin lymphoma receiving anthracycline chemotherapy underwent serial high-sensitivity cardiac troponin testing and cardiac magnetic resonance imaging before and 6 months after anthracycline treatment. Patients at high risk of cardiotoxicity (cardiac troponin I concentrations in the upper tertile during chemotherapy) were randomized to standard care plus cardioprotection (combination carvedilol and candesartan therapy) or standard care alone. The primary outcome was adjusted change in left ventricular ejection fraction at 6 months. In low-risk nonrandomized patients with cardiac troponin I concentrations in the lower 2 tertiles, we hypothesized the absence of a 6-month change in left ventricular ejection fraction and tested for equivalence of ±2%. Between October 2017 and June 2021, 175 patients (mean age, 53 years; 87% female; 71% with breast cancer) were recruited. Patients randomized to cardioprotection (n=29) or standard care (n=28) had left ventricular ejection fractions of 69.4±7.4% and 69.1±6.1% at baseline and 65.7±6.6% and 64.9±5.9% 6 months after completion of chemotherapy, respectively. After adjustment for age, pretreatment left ventricular ejection fraction, and planned anthracycline dose, the estimated mean difference in 6-month left ventricular ejection fraction between the cardioprotection and standard care groups was -0.37% (95% CI, -3.59% to 2.85%; P=0.82). In low-risk nonrandomized patients, baseline and 6-month left ventricular ejection fractions were 69.3±5.7% and 66.4±6.3%, respectively: estimated mean difference, 2.87% (95% CI, 1.63%-4.10%; P=0.92, not equivalent). Combination candesartan and carvedilol therapy had no demonstrable cardioprotective effect in patients receiving anthracycline-based chemotherapy with high-risk on-treatment cardiac troponin I concentrations. Low-risk nonrandomized patients had similar declines in left ventricular ejection fraction, bringing into question the utility of routine cardiac troponin monitoring. Furthermore, the modest declines in left ventricular ejection fraction suggest that the value and clinical impact of early cardioprotection therapy need to be better defined in patients receiving high-dose anthracycline. URL: https://doi.org; Unique identifier: 10.1186/ISRCTN24439460. URL: https://www.clinicaltrialsregister.eu/ctr-search/search; Unique identifier: 2017-000896-99.

AbstractIn the developing liver, bipotent epithelial progenitor cells known as hepatoblasts undergo lineage segregation to form the two major epithelial cell types, hepatocytes that constitute the bulk of the liver parenchyma and biliary epithelial cells (cholangiocytes) which comprise the bile duct, a complex tubular network which is critical for normal liver function. Notch and TGFβ signalling promote the formation of a sheet of biliary epithelial cells, the ductal plate that organises into discontinuous tubular structures. How these structures elongate and connect to form a continuous duct remains undefined. Here, we show that the planar cell polarity protein, VANGL2 is expressed late in intrahepatic bile duct development and patterns the formation of cell-cell contacts between biliary cells. The patterning of these cell contacts regulates the normal polarisation of the actin cytoskeleton within biliary cells and loss ofVangl2-function results in the abnormal distribution of cortical actin remodelling resulting in the failure of bile duct formation. Planar cell polarity is a critical step in the post-specification sculpture of the bile duct and is essential for establishing normal tissue architecture.

Electron microscopy (EM) images of axons and their ensheathing myelin from both the central and peripheral nervous system are used for assessing myelin formation, degeneration (demyelination) and regeneration (remyelination). The g-ratio is the gold standard measure of assessing myelin thickness and quality, and traditionally is determined from measurements made manually from EM images-a time-consuming endeavour with limited reproducibility. These measurements have also historically neglected the innermost uncompacted myelin sheath, known as the inner tongue. Nonetheless, the inner tongue has been shown to be important for myelin growth and some studies have reported that certain conditions can elicit its enlargement. Ignoring this fact may bias the standard g-ratio analysis, whereas quantifying the uncompacted myelin has the potential to provide novel insights in the myelin field. In this regard, we have developed AimSeg, a bioimage analysis tool for axon, inner tongue and myelin segmentation. Aided by machine learning classifiers trained on transmission EM (TEM) images of tissue undergoing remyelination, AimSeg can be used either as an automated workflow or as a user-assisted segmentation tool. Validation results on TEM data from both healthy and remyelinating samples show good performance in segmenting all three fibre components, with the assisted segmentation showing the potential for further improvement with minimal user intervention. This results in a considerable reduction in time for analysis compared with manual annotation. AimSeg could also be used to build larger, high quality ground truth datasets to train novel deep learning models. Implemented in Fiji, AimSeg can use machine learning classifiers trained in ilastik. This, combined with a user-friendly interface and the ability to quantify uncompacted myelin, makes AimSeg a unique tool to assess myelin growth.