Predicting Ovarian Cancer Treatment Response in Histopathology using Hierarchical Vision Transformers and Multiple Instance Learning

For many patients, current ovarian cancer treatments offer limited clinical benefit. For some therapies, it is not possible to predict patients' responses, potentially exposing them to the adverse effects of treatment without any therapeutic benefit. As part of the automated prediction of treatment effectiveness in ovarian cancer using histopathological images (ATEC23) challenge, we evaluated the effectiveness of deep learning to predict whether a course of treatment including the antiangiogenic drug bevacizumab could contribute to remission or prevent disease progression for at least 6 months in a set of 282 histopathology whole slide images (WSIs) from 78 ovarian cancer patients. Our approach used a pretrained Hierarchical Image Pyramid Transformer (HIPT) to extract region-level features and an attention-based multiple instance learning (ABMIL) model to aggregate features and classify whole slides. The optimal HIPT-ABMIL model had an internal balanced accuracy of 60.2% +- 2.9% and an AUC of 0.646 +- 0.033. Histopathology-specific model pretraining was found to be beneficial to classification performance, though hierarchical transformers were not, with a ResNet feature extractor achieving similar performance. Due to the dataset being small and highly heterogeneous, performance was variable across 5-fold cross-validation folds, and there were some extreme differences between validation and test set performance within folds. The model did not generalise well to tissue microarrays, with accuracy worse than random chance. It is not yet clear whether ovarian cancer WSIs contain information that can be used to accurately predict treatment response, with further validation using larger, higher-quality datasets required.Comment: Submission to ATEC23 challenge at MICCAI 2023 conferenc

Age-related biological features of germ cell tumors.

Germ cell tumors (GCTs) are rare but clinically and pathologically diverse tumors that occur in an extensive range of age groups, from children to older adults and which include both seminomatous and nonseminomatous tumors. Current clinical management for both male and female teenagers and young adults (TYAs) with GCTs remains inconsistent, alternating between pediatric and adult multidisciplinary oncology teams, based on locally defined age cutoffs. Therefore, we reviewed available literature to determine the biological similarities and differences between GCTs in young children (0-12 years), TYAs (13-24 years), and older adults (>24 years). GCTs arising in pediatric and adult populations in general showed marked molecular biological differences within identical histological subtypes, whereas there was a distinct paucity of available data for GCTs in the TYA population. These findings highlight that clinical management based simply on chronological age may be inappropriate for TYA and suggests that the optimal future management of GCTs should consider specific molecular biological factors in addition to clinical parameters in the context of patient-specific age group rather than medical specialty.This is the accepted manuscript. The final version is available at http://onlinelibrary.wiley.com/doi/10.1002/gcc.22131/abstract

A Bayesian view of murine seminal cytokine networks

It has long been established that active agents in seminal fluid are key to initiating and coordinating mating-induced immunomodulation. This is in part governed by the actions of a network of cytokine interactions which, to date, remain largely undefined, and whose interspecific evolutionary conservation is unknown. This study applied Bayesian methods to illustrate the interrelationships between seminal profiles of interleukin (IL)-1alpha, IL-1beta, IL-2, IL-4, IL-5, IL-6, IL-9, IL-10, IL-12 (p70), IL-13, IL-17, eotaxin, granulocyte-colony stimulating factor (G-CSF), granulocyte macrophage-colony stimulating factor (GM-CSF), interferon (IFN)-gamma, keratinocyte-derived chemokine (KC), monocyte chemoattractant protein (MCP-1), macrophage inflammatory protein (MIP-1) alpha, MIP-1beta, regulated on activation normal T cell expressed and secreted (RANTES), tumour necrosis factor (TNF)-alpha, leptin, inducible protein (IP)-10 and vascular endothelial growth factor (VEGF) in a rat model. IL-2, IL-9, IL-12 (p70), IL-13, IL-18, eotaxin, IFN-gamma, IP-10, KC, leptin, MCP-1, MIP-1alpha and TNF-alpha were significantly higher in serum, whilst IL-1beta, IL-5, IL-6, IL-10, IL-17, G-CSF and GM-CSF were significantly higher in seminal fluid. When compared to mouse profiles, only G-CSF was present at significantly higher levels in the seminal fluid in both species. Bayesian modelling highlighted key shared features across mouse and rat networks, namely TNF-alpha as the terminal node in both serum and seminal plasma, and MCP-1 as a central coordinator of seminal cytokine networks through the intermediary of KC and RANTES. These findings reveal a marked interspecific conservation of seminal cytokine networks

Limited Relationship between Cervico-Vaginal Fluid Cytokine Profiles and Cervical Shortening in Women at High Risk of Spontaneous Preterm Birth

Objective: to determine the relationship between high vaginal pro-inflammatory cytokines and cervical shortening in women at high risk of spontaneous preterm labor and to assess the influence of cervical cerclage and vaginal progesterone on this relationship. Methods: this prospective longitudinal observational study assessed 112 women with at least one previous preterm delivery between 16 and 34 weeks’ gestation. Transvaginal cervical length was measured and cervico-vaginal fluid sampled every two weeks until 28 weeks. If the cervix shortened (<25 mm) before 24 weeks’ gestation, women (cases) were randomly assigned to cerclage or progesterone and sampled weekly. Cytokine concentrations were measured in a subset of cervico-vaginal fluid samples (n = 477 from 78 women) by 11-plex fluid-phase immunoassay. Results: all 11 inflammatory cytokines investigated were detected in cervico-vaginal fluid from women at high risk of preterm birth, irrespective of later cervical shortening. At less than 24 weeks’ gestation and prior to intervention, women destined to develop a short cervix (n = 36) exhibited higher cervico-vaginal concentrations than controls (n = 42) of granulocyte-macrophage colony-stimulating factor [(GM-CSF) 16.2 fold increase, confidence interval (CI) 1.8–147; p = 0.01] and monocyte chemotactic protein-1 [(MCP-1) 4.8, CI 1.0–23.0; p = 0.05]. Other cytokines were similar between cases and controls. Progesterone treatment did not suppress cytokine concentrations. Interleukin (IL)-6, IL-8, granulocyte colony-stimulating factor (G-CSF), interferon (IFN)-γ and tumour necrosis factor (TNF)-α concentrations were higher following randomization to cerclage versus progesterone (p<0.05). Cerclage, but not progesterone treatment, was followed by a significant increase in cervical length [mean 11.4 mm, CI 5.0–17.7; p<0.001]. Conclusions: although GM-CSF and MCP-1 cervico-vaginal fluid concentrations were raised, the majority of cervico-vaginal cytokines did not increase in association with cervical shortening. Progesterone treatment showed no significant anti-inflammation action on cytokine concentrations. Cerclage insertion was associated with an increase in the majority of inflammatory markers and cervical length

Omega-3 polyunsaturated fatty acid supplementation versus placebo on vascular health, glycaemic control, and metabolic parameters in people with type 1 diabetes: a randomised controlled preliminary trial

Background: The role of omega-3 polyunsaturated fatty acids (n-3PUFA), and the potential impact of n-3PUFA supplementation, in the treatment and management of type 1 diabetes (T1D) remains unclear and controversial. Therefore, this study aimed to examine the efficacy of daily high-dose-bolus n-3PUFA supplementation on vascular health, glycaemic control, and metabolic parameters in subjects with T1D. Methods: Twenty-seven adults with T1D were recruited to a 6-month randomised, double-blind, placebo-controlled trial. Subjects received either 3.3 g/day of encapsulated n-3PUFA or encapsulated 3.0 g/day corn oil placebo (PLA) for 6-months, with follow-up at 9-months after 3-month washout. Erythrocyte fatty acid composition was determined via gas chromatography. Endpoints included inflammation-associated endothelial biomarkers (vascular cell adhesion molecule-1 [VCAM-1], intercellular adhesion molecule-1 [ICAM-1], E-selectin, P-selectin, pentraxin-3, vascular endothelial growth factor [VEGF]), and their mediator tumor necrosis factor alpha [TNFα] analysed via immunoassay, vascular structure (carotid intima-media thickness [CIMT]) and function (brachial artery flow mediated dilation [FMD]) determined via ultrasound technique, blood pressure, glycosylated haemoglobin (HbA1c), fasting plasma glucose (FPG), and postprandial metabolism. Results: Twenty subjects completed the trial in full. In the n-3PUFA group, the mean ± SD baseline n-3PUFA index of 4.93 ± 0.94% increased to 7.67 ± 1.86% (P  0.05). Conclusions: This study indicates that daily high-dose-bolus of n-3PUFA supplementation for 6-months does not improve vascular health, glucose homeostasis, or metabolic parameters in subjects with T1D. The findings from this preliminary RCT do not support the use of therapeutic n-3PUFA supplementation in the treatment and management of T1D and its associated complications. Trial Registration ISRCTN, ISRCTN40811115. Registered 27 June 2017, http://www.isrctn.com/ISRCTN40811115

Association of Killer Cell Immunoglobulin-Like Receptor Genes with Hodgkin's Lymphoma in a Familial Study

BACKGROUND: Epstein-Barr virus (EBV) is the major environmental factor associated with Hodgkin's lymphoma (HL), a common lymphoma in young adults. Natural killer (NK) cells are key actors of the innate immune response against viruses. The regulation of NK cell function involves activating and inhibitory Killer cell Immunoglobulin-like receptors (KIRs), which are expressed in variable numbers on NK cells. Various viral and virus-related malignant disorders have been associated with the presence/absence of certain KIR genes in case/control studies. We investigated the role of the KIR cluster in HL in a family-based association study. METHODOLOGY: We included 90 families with 90 HL index cases (age 16–35 years) and 255 first-degree relatives (parents and siblings). We developed a procedure for reconstructing full genotypic information (number of gene copies) at each KIR locus from the standard KIR gene content. Out of the 90 collected families, 84 were informative and suitable for further analysis. An association study was then carried out with specific family-based analysis methods on these 84 families. PRINCIPAL FINDINGS: Five KIR genes in strong linkage disequilibrium were found significantly associated with HL. Refined haplotype analysis showed that the association was supported by a dominant protective effect of KIR3DS1 and/or KIR2DS1, both of which are activating receptors. The odds ratios for developing HL in subjects with at least one copy of KIR3DS1 or KIR2DS1 with respect to subjects with neither of these genes were 0.44[95% confidence interval 0.23–0.85] and 0.42[0.21–0.85], respectively. No significant association was found in a tentative replication case/control study of 68 HL cases (age 18–71 years). In the familial study, the protective effect of KIR3DS1/KIR2DS1 tended to be stronger in HL patients with detectable EBV in blood or tumour cells. CONCLUSIONS: This work defines a template for family-based association studies based on full genotypic information for the KIR cluster, and provides the first evidence that activating KIRs can have a protective role in HL

The prognostic significance of tumour-stroma ratio in endometrial carcinoma.

Background: High tumour stromal content has been found to predict adverse clinical outcome in a range of epithelial tumours. The aim of this study was to assess the prognostic significance of tumour-stroma ratio (TSR) in endometrial adenocarcinomas and investigate its relationship with other clinicopathological parameters. Methods: Clinicopathological and 5-year follow-up data were obtained for a retrospective series of endometrial adenocarcinoma patients (n = 400). TSR was measured using a morphometric approach (point counting) on digitised histologic hysterectomy specimens. Inter-observer agreement was determined using Cohen’s Kappa statistic. TSR cut-offs were optimised using log-rank functions and prognostic significance of TSR on overall survival (OS) and disease-free survival (DFS) were determined using Cox Proportional Hazards regression analysis and Kaplan-Meier curves generated. Associations of TSR with other clinicopathological parameters were determined using non-parametric tests followed by Holm-Bonferroni correction for multiple comparisons. Results: TSR as a continuous variable associated with worse OS (P = 0.034) in univariable Cox-regression analysis. Using the optimal cut-off TSR value of 1.3, TSR-high (i.e. low stroma) was associated with worse OS (HR = 2.51; 95 % CI = 1.22–5.12; P = 0.021) and DFS (HR = 2.19; 95 % CI = 1.15–4.17; P = 0.017) in univariable analysis. However, TSR did not have independent prognostic significance in multivariable analysis, when adjusted for known prognostic variables. A highly significant association was found between TSR and tumour grade (P < 0.001) and lymphovascular space invasion (P < 0.001), both of which had independent prognostic significance in this study population. Conclusions: Low tumour stromal content associates with both poor outcome and with other adverse prognostic indicators in endometrial cancer, although it is not independently prognostic. These findings contrast with studies on many - although not all - cancers and suggest that the biology of tumour-stroma interactions may differ amongst cancer types

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Data Descriptor: A global multiproxy database for temperature reconstructions of the Common Era

Reproducible climate reconstructions of the Common Era (1 CE to present) are key to placing industrial-era warming into the context of natural climatic variability. Here we present a community-sourced database of temperature-sensitive proxy records from the PAGES2k initiative. The database gathers 692 records from 648 locations, including all continental regions and major ocean basins. The records are from trees, ice, sediment, corals, speleothems, documentary evidence, and other archives. They range in length from 50 to 2000 years, with a median of 547 years, while temporal resolution ranges from biweekly to centennial. Nearly half of the proxy time series are significantly correlated with HadCRUT4.2 surface temperature over the period 1850-2014. Global temperature composites show a remarkable degree of coherence between high-and low-resolution archives, with broadly similar patterns across archive types, terrestrial versus marine locations, and screening criteria. The database is suited to investigations of global and regional temperature variability over the Common Era, and is shared in the Linked Paleo Data (LiPD) format, including serializations in Matlab, R and Python.(TABLE)Since the pioneering work of D'Arrigo and Jacoby1-3, as well as Mann et al. 4,5, temperature reconstructions of the Common Era have become a key component of climate assessments6-9. Such reconstructions depend strongly on the composition of the underlying network of climate proxies10, and it is therefore critical for the climate community to have access to a community-vetted, quality-controlled database of temperature-sensitive records stored in a self-describing format. The Past Global Changes (PAGES) 2k consortium, a self-organized, international group of experts, recently assembled such a database, and used it to reconstruct surface temperature over continental-scale regions11 (hereafter, ` PAGES2k-2013').This data descriptor presents version 2.0.0 of the PAGES2k proxy temperature database (Data Citation 1). It augments the PAGES2k-2013 collection of terrestrial records with marine records assembled by the Ocean2k working group at centennial12 and annual13 time scales. In addition to these previously published data compilations, this version includes substantially more records, extensive new metadata, and validation. Furthermore, the selection criteria for records included in this version are applied more uniformly and transparently across regions, resulting in a more cohesive data product.This data descriptor describes the contents of the database, the criteria for inclusion, and quantifies the relation of each record with instrumental temperature. In addition, the paleotemperature time series are summarized as composites to highlight the most salient decadal-to centennial-scale behaviour of the dataset and check mutual consistency between paleoclimate archives. We provide extensive Matlab code to probe the database-processing, filtering and aggregating it in various ways to investigate temperature variability over the Common Era. The unique approach to data stewardship and code-sharing employed here is designed to enable an unprecedented scale of investigation of the temperature history of the Common Era, by the scientific community and citizen-scientists alike