A global study to identify a potential basis for policy options when integrating animal welfare into the UN Sustainable Development Goals

A previously developed methodology to rate the strength of the impact of improving animal welfare on achieving each of the 17 SDGs and the impact of achieving each SDG on animal welfare was used at the third Animal Welfare Global Forum of the World Organisation for Animal Health. Data from 95 participants from key stakeholder categories and organisations involved in animal welfare were analysed. The resulting ‘map’ of the relative strengths of these associations confirmed the expected co-benefits of improving animal welfare and achieving the SDGs. Differences at regional level and according to the economic classification of the country were also identified. This paper focuses on using this ‘map’ as a potential guide for how organisations interested in improving animal welfare could identify potential new allies for strategic partnerships to facilitate the implementation of different policy options. For example, a strategy can be to collaborate with those organisations where the impact is of similar mutual benefit, e.g. between improving animal welfare and achieving SDG 3 (Good health and well-being). Organisations in these two areas are already aligning themselves in the ‘One Health’ movement. Another strategy can be to align with organisations for whom achievement of their goal has the greatest impact on animal welfare, even if the impact is not mutual e.g. by collaborating with organisations working to achieve SDG 16 (Peace justice and strong institutions) and SDG 4 (Quality education). Achieving these goals was considered to have a large impact on improving animal welfare, equivalent to that of achieving SDG 3. In summary, this study can help organisations working in the area of animal welfare identify previously untapped areas of potential support, so tailoring their efforts efficiently, while at the same time themselves supporting movement towards the Agenda 2030. Simply put, the co-benefits make collaboration worthwhile, potentially opening up opportunities that would be unavailable when organisations are working independently towards their own respective goals

R/Bioconductor software for Illumina's Infinium whole-genome genotyping BeadChips

Summary: Illumina produces a number of microarray-based technologies for human genotyping. An Infinium BeadChip is a two-color platform that types between 105 and 106 single nucleotide polymorphisms (SNPs) per sample. Despite being widely used, there is a shortage of open source software to process the raw intensities from this platform into genotype calls. To this end, we have developed the R/Bioconductor package crlmm for analyzing BeadChip data. After careful preprocessing, our software applies the CRLMM algorithm to produce genotype calls, confidence scores and other quality metrics at both the SNP and sample levels. We provide access to the raw summary-level intensity data, allowing users to develop their own methods for genotype calling or copy number analysis if they wish

Statistical model-based testing to evaluate the recurrence of genomic aberrations

Motivation: In cancer genomes, chromosomal regions harboring cancer genes are often subjected to genomic aberrations like copy number alteration and loss of heterozygosity. Given this, finding recurrent genomic aberrations is considered an apt approach for screening cancer genes. Although several permutation-based tests have been proposed for this purpose, none of them are designed to find recurrent aberrations from the genomic dataset without paired normal sample controls. Their application to unpaired genomic data may lead to false discoveries, because they retrieve pseudo-aberrations that exist in normal genomes as polymorphisms

RNA sequencing-based single sample predictors of molecular subtype and risk of recurrence for clinical assessment of early-stage breast cancer

BackgroundMultigene expression assays for molecular subtypes and biomarkers can aid clinical management of early invasive breast cancer. Based on RNA-sequencing we aimed to develop single-sample predictor (SSP) models for conventional clinical markers, molecular intrinsic subtype and risk of recurrence (ROR).MethodsA uniformly accrued breast cancer cohort of 7743 patients with RNA-sequencing data from fresh tissue was divided into a training set and a reserved test set. We trained SSPs for PAM50 molecular subtypes and ROR assigned by nearest-centroid (NC) and SSPs for conventional clinical markers from histopathology data. Additionally, SSP classifications were compared with Prosigna® in two external cohorts. Prognostic value was assessed using distant recurrence-free interval.ResultsIn the test set, agreement between SSP and NC classifications for PAM50 (five subtypes) and Subtype (four subtypes) was high (85%, Kappa=0.78) and very high (90%, Kappa=0.84) respectively. Accuracy for ROR risk category was high (84%, Kappa=0.75, weighted Kappa=0.90). The prognostic value for SSP and NC was assessed as equivalent. Agreement for SSP and histopathology was very high or high for receptor status, while moderate and poor for Ki67 status and Nottingham histological grade, respectively. SSP concordance with Prosigna® was high for subtype and moderate and high for ROR risk category. In pooled analysis, concordance between SSP and Prosigna® for emulated treatment recommendation for chemotherapy (yes vs. no) was high (85%, Kappa=0.66). In postmenopausal ER+/HER2-/N0 patients SSP application suggested changed treatment recommendations for up to 17% of patients, with nearly balanced escalation and de-escalation of chemotherapy.ConclusionsSSP models for histopathological variables, PAM50, and ROR classifications can be derived from RNA-sequencing that closely matches clinical tests. Agreement and outcome analyses suggest that NC and SSP models are interchangeable on a group-level and nearly so on a patient level. Retrospective evaluation in postmenopausal ER+/HER2-/N0 patients suggested that molecular testing could lead to a changed therapy recommendation for almost one-fifth of patients

Landscape of somatic allelic imbalances and copy number alterations in HER2-amplified breast cancer

Introduction: Human epidermal growth factor receptor 2 (HER2)-amplified breast cancer represents a clinically well-defined subgroup due to availability of targeted treatment. However, HER2-amplified tumors have been shown to be heterogeneous at the genomic level by genome-wide microarray analyses, pointing towards a need of further investigations for identification of recurrent copy number alterations and delineation of patterns of allelic imbalance. Methods: High-density whole genome array-based comparative genomic hybridization (aCGH) and single nucleotide polymorphism (SNP) array data from 260 HER2-amplified breast tumors or cell lines, and 346 HER2-negative breast cancers with molecular subtype information were assembled from different repositories. Copy number alteration (CNA), loss-of-heterozygosity (LOH), copy number neutral allelic imbalance (CNN-AI), subclonal CNA and patterns of tumor DNA ploidy were analyzed using bioinformatical methods such as genomic identification of significant targets in cancer (GISTIC) and genome alteration print (GAP). The patterns of tumor ploidy were confirmed in 338 unrelated breast cancers analyzed by DNA flow cytometry with concurrent BAC aCGH and gene expression data. Results: A core set of 36 genomic regions commonly affected by copy number gain or loss was identified by integrating results with a previous study, together comprising > 400 HER2-amplified tumors. While CNN-AI frequency appeared evenly distributed over chromosomes in HER2-amplified tumors, not targeting specific regions and often < 20% in frequency, the occurrence of LOH was strongly associated with regions of copy number loss. HER2-amplified and HER2-negative tumors stratified by molecular subtypes displayed different patterns of LOH and CNN-AI, with basal-like tumors showing highest frequencies followed by HER2-amplified and luminal B cases. Tumor aneuploidy was strongly associated with increasing levels of LOH, CNN-AI, CNAs and occurrence of subclonal copy number events, irrespective of subtype. Finally, SNP data from individual tumors indicated that genomic amplification in general appears as monoallelic, that is, it preferentially targets one parental chromosome in HER2-amplified tumors. Conclusions: We have delineated the genomic landscape of CNAs, amplifications, LOH, and CNN-AI in HER2-amplified breast cancer, but also demonstrated a strong association between different types of genomic aberrations and tumor aneuploidy irrespective of molecular subtype

Tooth development standards for South Australia

The document attached has been archived with permission from the Australian Dental Association. An external link to the publisher’s copy is included.Background: Chronological age, as recorded by registration of birth date, is referred to throughout an individual's life. This information is relevant in medical and dental practice for evaluating developmental progress, for educational purposes, and in legal matters, particularly in the application of criminal law. The absence of birth date information raises particular concerns, and estimates of chronological age are often required. Standards of dental maturation may be used to estimate age, but they have been shown to be gender and population sensitive. Methods: The revised Demirjian' system of dental age estimation was applied to a sample of 615 South Australian children in order to assess its accuracy. Results: The results of our study have shown that the Demirjian system is of limited accuracy when used to estimate the age of South Australian children. Conclusions: Generation of new standard curves, specific to the Australian population, is indicated.CJ McKenna, H James, JA Taylor, GC Townsen

Clonal Evolution through Loss of Chromosomes and Subsequent Polyploidization in Chondrosarcoma

Near-haploid chromosome numbers have been found in less than 1% of cytogenetically reported tumors, but seem to be more common in certain neoplasms including the malignant cartilage-producing tumor chondrosarcoma. By a literature survey of published karyotypes from chondrosarcomas we could confirm that loss of chromosomes resulting in hyperhaploid-hypodiploid cells is common and that these cells may polyploidize. Sixteen chondrosarcomas were investigated by single nucleotide polymorphism (SNP) array and the majority displayed SNP patterns indicative of a hyperhaploid-hypodiploid origin, with or without subsequent polyploidization. Except for chromosomes 5, 7, 19, 20 and 21, autosomal loss of heterozygosity was commonly found, resulting from chromosome loss and subsequent duplication of monosomic chromosomes giving rise to uniparental disomy. Additional gains, losses and rearrangements of genetic material, and even repeated rounds of polyploidization, may affect chondrosarcoma cells resulting in highly complex karyotypes. Loss of chromosomes and subsequent polyploidization was not restricted to a particular chondrosarcoma subtype and, although commonly found in chondrosarcoma, binucleated cells did not seem to be involved in these events

High expression of ZNF703 independent of amplification indicates worse prognosis in patients with luminal B breast cancer

Peer reviewe

Molecular subtypes of breast cancer are associated with characteristic DNA methylation patterns

Introduction: Five different molecular subtypes of breast cancer have been identified through gene expression profiling. Each subtype has a characteristic expression pattern suggested to partly depend on cellular origin. We aimed to investigate whether the molecular subtypes also display distinct methylation profiles. Methods: We analysed methylation status of 807 cancer-related genes in 189 fresh frozen primary breast tumours and four normal breast tissue samples using an array-based methylation assay. Results: Unsupervised analysis revealed three groups of breast cancer with characteristic methylation patterns. The three groups were associated with the luminal A, luminal B and basal-like molecular subtypes of breast cancer, respectively, whereas cancers of the HER2-enriched and normal-like subtypes were distributed among the three groups. The methylation frequencies were significantly different between subtypes, with luminal B and basal-like tumours being most and least frequently methylated, respectively. Moreover, targets of the polycomb repressor complex in breast cancer and embryonic stem cells were more methylated in luminal B tumours than in other tumours. BRCA2-mutated tumours had a particularly high degree of methylation. Finally, by utilizing gene expression data, we observed that a large fraction of genes reported as having subtype-specific expression patterns might be regulated through methylation. Conclusions: We have found that breast cancers of the basal-like, luminal A and luminal B molecular subtypes harbour specific methylation profiles. Our results suggest that methylation may play an important role in the development of breast cancers

Towards the reconstruction of the genome-scale metabolic model of Lactobacillus acidophilus La-14

Lactobacillus acidophilus is a probiotic lactic acid bacterium used in food and dietary supplements for many years. However, despite its importance for industrial development and recognized health-promoting effects, no genome-scale metabolic model has been reported. A GSM model for L. acidophilus La-14 was developed, accounting 494 genes and 783 reactions. A genome annotation was performed to identify the metabolic potential of the bacterium. The biomass composition was determined based on information available in literature and previously published models. The model was validated by comparing in silico simulations with experimental data, regarding the aerobic and anaerobic growth. The reconstruction of the metabolic model has confirmed the fastidious requirements of L. acidophilus for amino acids, fatty acids, and vitamins. This model can be used for a better understanding of the metabolism of this bacterium and identification of industrially desirable compounds.This study was performed under the scope of the project “BIODATA.PT – Portuguese Biological Data Network” (ref. LISBOA-01-0145-FEDER-022231), funded by FCT/MCTES, through national funds of PIDDAC, Fundo Europeu de Desenvolvimento Regional (FEDER), Programa Operacional de Competitividade e Internacionalização (POCI) and Programa Operacional Regional de Lisboa (Lisboa 2020).info:eu-repo/semantics/publishedVersio