The clinical significance of sub-total surgical resection in childhood medulloblastoma: a multi-cohort analysis of 1100 patients

\ua9 2024 The Author(s)Background: Medulloblastoma patients with a sub-total surgical resection (STR; >1.5 cm2 primary tumour residuum post-surgery) typically receive intensified treatment. However, the association of STR with poor outcomes has not been observed consistently, questioning the validity of STR as a high-risk disease feature. Methods: We collected extent of resection (EOR) data from 1110 patients (from UK CCLG centres (n = 416, collected between September 1990 and July 2014) and published (n = 694) cohorts), the largest cohort of molecularly and clinically annotated tumours assembled to specifically assess the significance of EOR. We performed association and univariable/multivariable survival analyses, assessing overall survival (OS) cohort-wide and with reference to the four consensus medulloblastoma molecular groups and clinical features. Findings: STR was reported in 20% (226/1110) of patients. Non-WNT (p = 0.047), children <5 years at diagnosis (p = 0.021) and metastatic patients (p < 0.0001) were significantly more likely to have a STR. In cohort-wide analysis, STR was associated with worse survival in univariable analysis (p < 0.0001). Examination of specific disease contexts showed that STR was prognostic in univariate analysis for patients receiving cranio-spinal irradiation (CSI) and chemotherapy (p = 0.016) and for patients with Group 3 tumours receiving CSI (p = 0.039). STR was not independently prognostic in multivariable analyses; outcomes for patients who have STR as their only risk-feature are as per standard-risk disease. Specifically, STR was not prognostic in non-metastatic patients that received upfront CSI. Interpretation: In a cohort of 1100 molecularly characterised medulloblastoma patients, STR (n = 226) predicted significantly lower OS in univariable analysis, but was not an independent prognostic factor. Our data suggest that maximal safe resection can continue to be carried out for patients with medulloblastoma and suggest STR should not inform patient management when observed as a sole, isolated risk-feature. Funding: Cancer Research UK, Newcastle Hospitals Charity, Children\u27s Cancer North, British Division of the International Academy of Pathology

Bottom mixed layer oxygen dynamics in the Celtic Sea

The seasonally stratified continental shelf seas are highly productive, economically important environments which are under considerable pressure from human activity. Global dissolved oxygen concentrations have shown rapid reductions in response to anthropogenic forcing since at least the middle of the twentieth century. Oxygen consumption is at the same time linked to the cycling of atmospheric carbon, with oxygen being a proxy for carbon remineralisation and the release of CO2. In the seasonally stratified seas the bottom mixed layer (BML) is partially isolated from the atmosphere and is thus controlled by interplay between oxygen consumption processes, vertical and horizontal advection. Oxygen consumption rates can be both spatially and temporally dynamic, but these dynamics are often missed with incubation based techniques. Here we adopt a Bayesian approach to determining total BML oxygen consumption rates from a high resolution oxygen time-series. This incorporates both our knowledge and our uncertainty of the various processes which control the oxygen inventory. Total BML rates integrate both processes in the water column and at the sediment interface. These observations span the stratified period of the Celtic Sea and across both sandy and muddy sediment types. We show how horizontal advection, tidal forcing and vertical mixing together control the bottom mixed layer oxygen concentrations at various times over the stratified period. Our muddy-sand site shows cyclic spring-neap mediated changes in oxygen consumption driven by the frequent resuspension or ventilation of the seabed. We see evidence for prolonged periods of increased vertical mixing which provide the ventilation necessary to support the high rates of consumption observed

The molecular landscape and associated clinical experience in infant medulloblastoma: prognostic significance of second-generation subtypes

Aims: Biomarker‐driven therapies have not been developed for infant medulloblastoma (iMB). We sought to robustly sub‐classify iMB, and proffer strategies for personalized, risk‐adapted therapies. Methods: We characterized the iMB molecular landscape, including second‐generation subtyping, and the associated retrospective clinical experience, using large independent discovery/validation cohorts (n = 387). Results: iMBGrp3 (42%) and iMBSHH (40%) subgroups predominated. iMBGrp3 harboured second‐generation subtypes II/III/IV. Subtype II strongly associated with large‐cell/anaplastic pathology (LCA; 23%) and MYC amplification (19%), defining a very‐high‐risk group (0% 10yr overall survival (OS)), which progressed rapidly on all therapies; novel approaches are urgently required. Subtype VII (predominant within iMBGrp4) and subtype IV tumours were standard risk (80% OS) using upfront CSI‐based therapies; randomized‐controlled trials of upfront radiation‐sparing and/or second‐line radiotherapy should be considered. Seventy‐five per cent of iMBSHH showed DN/MBEN histopathology in discovery and validation cohorts (P < 0.0001); central pathology review determined diagnosis of histological variants to WHO standards. In multivariable models, non‐DN/MBEN pathology was associated significantly with worse outcomes within iMBSHH. iMBSHH harboured two distinct subtypes (iMBSHH‐I/II). Within the discriminated favourable‐risk iMBSHH DN/MBEN patient group, iMBSHH‐II had significantly better progression‐free survival than iMBSHH‐I, offering opportunities for risk‐adapted stratification of upfront therapies. Both iMBSHH‐I and iMBSHH‐II showed notable rescue rates (56% combined post‐relapse survival), further supporting delay of irradiation. Survival models and risk factors described were reproducible in independent cohorts, strongly supporting their further investigation and development. Conclusions: Investigations of large, retrospective cohorts have enabled the comprehensive and robust characterization of molecular heterogeneity within iMB. Novel subtypes are clinically significant and subgroup‐dependent survival models highlight opportunities for biomarker‐directed therapies

Urothelial Plaque Formation in Post-Golgi Compartments

Urothelial plaques are specialized membrane domains in urothelial superficial (umbrella) cells, composed of highly ordered uroplakin particles. We investigated membrane compartments involved in the formation of urothelial plaques in mouse umbrella cells. The Golgi apparatus did not contain uroplakins organized into plaques. In the post-Golgi region, three distinct membrane compartments containing uroplakins were characterized: i) Small rounded vesicles, located close to the Golgi apparatus, were labelled weakly with anti-uroplakin antibodies and they possessed no plaques; we termed them “uroplakin-positive transporting vesicles” (UPTVs). ii) Spherical-to-flattened vesicles, termed “immature fusiform vesicles” (iFVs), were uroplakin-positive in their central regions and contained small urothelial plaques. iii) Flattened “mature fusiform vesicles” (mFVs) contained large plaques, which were densely labelled with anti-uroplakin antibodies. Endoytotic marker horseradish peroxidase was not found in these post-Golgi compartments. We propose a detailed model of de novo urothelial plaque formation in post-Golgi compartments: UPTVs carrying individual 16-nm particles detach from the Golgi apparatus and subsequently fuse into iFV. Concentration of 16-nm particles into plaques and removal of uroplakin-negative membranes takes place in iFVs. With additional fusions and buddings, iFVs mature into mFVs, each carrying two urothelial plaques toward the apical surface of the umbrella cell

Emergence and maintenance of actionable genetic drivers at medulloblastoma relapse

BACKGROUND: 90% of tumors) and established genetic drivers (e.g. SHH/WNT/P53 mutations; 60% of rMB events) were maintained from diagnosis. Critically, acquired and maintained rMB events converged on targetable pathways which were significantly enriched at relapse (e.g. DNA damage-signaling) and specific events (e.g. 3p loss) predicted survival post-relapse. CONCLUSIONS: rMB is defined by the emergence of novel events and pathways, in concert with selective maintenance of established genetic drivers. Together, these define the actionable genetic landscape of rMB and provide a basis for improved clinical management and development of stratified therapeutics, across disease-course

Characterization of ten highly polymorphic microsatellite loci for the intertidal mussel Perna perna, and cross species amplification within the genus

The brown mussel Perna perna (Linnaeus, 1758) is a dominant constituent of intertidal communities and a strong invader with multiple non-native populations distributed around the world. In a previous study, two polymorphic microsatellite loci were developed and used to determine population-level genetic diversity in invasive and native P. perna populations. However, higher number of microsatellite markers are required for reliable population genetic studies. In this context, in order to understand P. perna origins and history of invasion and to compare population genetic structure in native versus invaded areas, we developed 10 polymorphic microsatellite markers. Findings Described microsatellite markers were developed from an enriched genomic library. Analyses and characterization of loci using 20 individuals from a population in Western Sahara revealed on average 11 alleles per locus (range: 5–27) and mean gene diversity of 0.75 (range: 0.31 - 0.95). One primer pair revealed possible linkage disequilibrium while heterozygote deficiency was significant at four loci. Six of these markers cross-amplified in P. canaliculus (origin: New Zealand). Conclusions Developed markers will be useful in addressing a variety of questions concerning P. perna, including dispersal scales, genetic variation and population structure, in both native and invaded areas.Peer Reviewe

Metabolite profiles of medulloblastoma for rapid and non-invasive detection of molecular disease groups

\ua9 2024 The AuthorsBackground: The malignant childhood brain tumour, medulloblastoma, is classified clinically into molecular groups which guide therapy. DNA-methylation profiling is the current classification ‘gold-standard’, typically delivered 3–4 weeks post-surgery. Pre-surgery non-invasive diagnostics thus offer significant potential to improve early diagnosis and clinical management. Here, we determine tumour metabolite profiles of the four medulloblastoma groups, assess their diagnostic utility using tumour tissue and potential for non-invasive diagnosis using in vivo magnetic resonance spectroscopy (MRS). Methods: Metabolite profiles were acquired by high-resolution magic-angle spinning NMR spectroscopy (MAS) from 86 medulloblastomas (from 59 male and 27 female patients), previously classified by DNA-methylation array (WNT (n = 9), SHH (n = 22), Group3 (n = 21), Group4 (n = 34)); RNA-seq data was available for sixty. Unsupervised class-discovery was performed and a support vector machine (SVM) constructed to assess diagnostic performance. The SVM classifier was adapted to use only metabolites (n = 10) routinely quantified from in vivo MRS data, and re-tested. Glutamate was assessed as a predictor of overall survival. Findings: Group-specific metabolite profiles were identified; tumours clustered with good concordance to their reference molecular group (93%). GABA was only detected in WNT, taurine was low in SHH and lipids were high in Group3. The tissue-based metabolite SVM classifier had a cross-validated accuracy of 89% (100% for WNT) and, adapted to use metabolites routinely quantified in vivo, gave a combined classification accuracy of 90% for SHH, Group3 and Group4. Glutamate predicted survival after incorporating known risk-factors (HR = 3.39, 95% CI 1.4–8.1, p = 0.025). Interpretation: Tissue metabolite profiles characterise medulloblastoma molecular groups. Their combination with machine learning can aid rapid diagnosis from tissue and potentially in vivo. Specific metabolites provide important information; GABA identifying WNT and glutamate conferring poor prognosis. Funding: Children with Cancer UK, Cancer Research UK, Children\u27s Cancer North and a Newcastle University PhD studentship