An evidence‐base for developing ambitious yet realistic national biodiversity targets

Biodiversity targets are a key tool, used at a global and national policy level, to align biodiversity goals, promote conservation action, and recover nature. Yet most biodiversity targets are not met. In England, the government has committed to legally-binding targets to halt and recover the decline in species abundance by 2030 and 2042. We present evidence from recent population trends of 670 terrestrial animal species (for which abundance time series are available) as a species abundance indicator, together with a synthesis of case studies on species recovery, to assess the degree to which these targets are achievable. The case studies demonstrate that recovery is possible through a range of approaches. The indicator demonstrates that theoretically targets can be achieved by addressing severe declines in a relatively small number of species, as well as creating smaller benefits for many species through landscape-scale interventions. The fact that multiple pathways exist to achieve the species abundance targets in England presents choices but also raises the possibility that targets might be reached with perverse consequences. We demonstrate that evidence on achievability is a necessary but not sufficient condition for determining what is required to deliver conservation outcomes and restore biodiversity

Priority & hazardous occurrence in domestic wastewater from small scale systems in Ireland

A wide range of household sources may potentially contribute to contaminant loads in domestic wastewater. Typically domestic wastewater is combined and transported as a single waste stream, however, there is considerable variation in the pollutant and pathogen content of wastewater derived from different activities within the home (e.g. toilet flushing, dish washing, bathing etc.). In Ireland, the issue of unsewered wastewater treatment systems often located in rural areas and estimated to number over 400,000, constitutes a significant diffuse risk to both surface & groundwater. DCU & CIT have teamed up with DkIT and their project partners to carry out a preliminary investigation into the levels of priority & hazardous substances in domestic wastewater from a number of single dwelling houses within the Lough Muckno Catchment, Co. Monaghan and an integrated constructed wetland (ICW) on the grounds of the Castle Leslie Estate in Glaslough, Co. Monaghan

ADAM22/LGI1 complex as a new actionable target for breast cancer brain metastasis

Background: Metastatic breast cancer is a major cause of cancer-related deaths in woman. Brain metastasis is a common and devastating site of relapse for several breast cancer molecular subtypes, including oestrogen receptor-positive disease, with life expectancy of less than a year. While efforts have been devoted to developing therapeutics for extra-cranial metastasis, drug penetration of blood–brain barrier (BBB) remains a major clinical challenge. Defining molecular alterations in breast cancer brain metastasis enables the identification of novel actionable targets.Methods: Global transcriptomic analysis of matched primary and metastatic patient tumours (n = 35 patients, 70 tumour samples) identified a putative new actionable target for advanced breast cancer which was further validated in vivo and in breast cancer patient tumour tissue (n = 843 patients). A peptide mimetic of the target's natural ligand was designed in silico and its efficacy assessed in in vitro, ex vivo and in vivo models of breast cancer metastasis.Results: Bioinformatic analysis of over-represented pathways in metastatic breast cancer identified ADAM22 as a top ranked member of the ECM-related druggable genome specific to brain metastases. ADAM22 was validated as an actionable target in in vitro, ex vivo and in patient tumour tissue (n = 843 patients). A peptide mimetic of the ADAM22 ligand LGI1, LGI1MIM, was designed in silico. The efficacy of LGI1MIM and its ability to penetrate the BBB were assessed in vitro, ex vivo and in brain metastasis BBB 3D biometric biohybrid models, respectively. Treatment with LGI1MIM in vivo inhibited disease progression, in particular the development of brain metastasis.Conclusion: ADAM22 expression in advanced breast cancer supports development of breast cancer brain metastasis. Targeting ADAM22 with a peptide mimetic LGI1MIM represents a new therapeutic option to treat metastatic brain disease

Network analysis of SRC-1 reveals a novel transcription factor hub which regulates endocrine resistant breast cancer.

Steroid receptor coactivator 1 (SRC-1) interacts with nuclear receptors and other transcription factors (TFs) to initiate transcriptional networks and regulate downstream genes which enable the cancer cell to evade therapy and metastasise. Here we took a top-down discovery approach to map out the SRC-1 transcriptional network in endocrine resistant breast cancer. First, rapid immunoprecipitation mass spectrometry of endogenous proteins (RIME) was employed to uncover new SRC-1 TF partners. Next, RNA sequencing (RNAseq) was undertaken to investigate SRC-1 TF target genes. Molecular and patient-derived xenograft studies confirmed STAT1 as a new SRC-1 TF partner, important in the regulation of a cadre of four SRC-1 transcription targets, NFIA, SMAD2, E2F7 and ASCL1. Extended network analysis identified a downstream 79 gene network, the clinical relevance of which was investigated in RNAseq studies from matched primary and local-recurrence tumours from endocrine resistant patients. We propose that SRC-1 can partner with STAT1 independently of the estrogen receptor to initiate a transcriptional cascade and control regulation of key endocrine resistant genes

Accuracy, repeatability, and interplatform reproducibility of T1 quantification methods used for DCEâ MRI: Results from a multicenter phantom study

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/142505/1/mrm26903_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/142505/2/mrm26903.pd

Comparative analysis of the AIB1 interactome in breast cancer reveals MTA2 as a repressive partner which silences E-Cadherin to promote EMT and associates with a pro-metastatic phenotype

Funder: Breast Cancer Ireland GR 14-0883Abstract: Steroid regulated cancer cells use nuclear receptors and associated regulatory proteins to orchestrate transcriptional networks to drive disease progression. In primary breast cancer, the coactivator AIB1 promotes estrogen receptor (ER) transcriptional activity to enhance cell proliferation. The function of the coactivator in ER+ metastasis however is not established. Here we describe AIB1 as a survival factor, regulator of pro-metastatic transcriptional pathways and a promising actionable target. Genomic alterations and functional expression of AIB1 associated with reduced disease-free survival in patients and enhanced metastatic capacity in novel CDX and PDX ex-vivo models of ER+ metastatic disease. Comparative analysis of the AIB1 interactome with complementary RNAseq characterized AIB1 as a transcriptional repressor. Specifically, we report that AIB1 interacts with MTA2 to form a repressive complex, inhibiting CDH1 (encoding E-cadherin) to promote EMT and drive progression. We further report that pharmacological and genetic inhibition of AIB1 demonstrates significant anti-proliferative activity in patient-derived models establishing AIB1 as a viable strategy to target endocrine resistant metastasis. This work defines a novel role for AIB1 in the regulation of EMT through transcriptional repression in advanced cancer cells with a considerable implication for prognosis and therapeutic interventions

Comparative analysis of the AIB1 interactome in breast cancer reveals MTA2 as a repressive partner which silences E-Cadherin to promote EMT and associates with a pro-metastatic phenotype

Funder: Breast Cancer Ireland GR 14-0883Abstract: Steroid regulated cancer cells use nuclear receptors and associated regulatory proteins to orchestrate transcriptional networks to drive disease progression. In primary breast cancer, the coactivator AIB1 promotes estrogen receptor (ER) transcriptional activity to enhance cell proliferation. The function of the coactivator in ER+ metastasis however is not established. Here we describe AIB1 as a survival factor, regulator of pro-metastatic transcriptional pathways and a promising actionable target. Genomic alterations and functional expression of AIB1 associated with reduced disease-free survival in patients and enhanced metastatic capacity in novel CDX and PDX ex-vivo models of ER+ metastatic disease. Comparative analysis of the AIB1 interactome with complementary RNAseq characterized AIB1 as a transcriptional repressor. Specifically, we report that AIB1 interacts with MTA2 to form a repressive complex, inhibiting CDH1 (encoding E-cadherin) to promote EMT and drive progression. We further report that pharmacological and genetic inhibition of AIB1 demonstrates significant anti-proliferative activity in patient-derived models establishing AIB1 as a viable strategy to target endocrine resistant metastasis. This work defines a novel role for AIB1 in the regulation of EMT through transcriptional repression in advanced cancer cells with a considerable implication for prognosis and therapeutic interventions

Refined histopathological predictors of BRCA1 and BRCA2 mutation status: A large-scale analysis of breast cancer characteristics from the BCAC, CIMBA, and ENIGMA consortia

Introduction: The distribution of histopathological features of invasive breast tumors in BRCA1 or BRCA2 germline mutation carriers differs from that of individuals with no known mutation. Histopathological features thus have utility for mutation prediction, including statistical modeling to assess pathogenicity of BRCA1 or BRCA2 variants of uncertain clinical significance. We analyzed large pathology datasets accrued by the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA) and the Breast Cancer Association Consortium (BCAC) to reassess histopathological predictors of BRCA1 and BRCA2 mutation status, and provide robust likelihood ratio (LR) estimates for statistical modeling. Methods: Selection criteria for study/center inclusion were estrogen receptor (ER) status or grade data available for invasive breast cancer diagnosed younger than 70 years. The dataset included 4,477 BRCA1 mutation carriers, 2,565 BRCA2 mutation carriers, and 47,565 BCAC breast cancer cases. Country-stratified estimates of the

Refined histopathological predictors of BRCA1 and BRCA2 mutation status : a large-scale analysis of breast cancer characteristics from the BCAC, CIMBA, and ENIGMA consortia

Abstract Introduction The distribution of histopathological features of invasive breast tumors in BRCA1 or BRCA2 germline mutation carriers differs from that of individuals with no known mutation. Histopathological features thus have utility for mutation prediction, including statistical modeling to assess pathogenicity of BRCA1 or BRCA2 variants of uncertain clinical significance. We analyzed large pathology datasets accrued by the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA) and the Breast Cancer Association Consortium (BCAC) to reassess histopathological predictors of BRCA1 and BRCA2 mutation status, and provide robust likelihood ratio (LR) estimates for statistical modeling. Methods Selection criteria for study/center inclusion were estrogen receptor (ER) status or grade data available for invasive breast cancer diagnosed younger than 70 years. The dataset included 4,477 BRCA1 mutation carriers, 2,565 BRCA2 mutation carriers, and 47,565 BCAC breast cancer cases. Country-stratified estimates of the likelihood of mutation status by histopathological markers were derived using a Mantel-Haenszel approach. Results ER-positive phenotype negatively predicted BRCA1 mutation status, irrespective of grade (LRs from 0.08 to 0.90). ER-negative grade 3 histopathology was more predictive of positive BRCA1 mutation status in women 50 years or older (LR = 4.13 (3.70 to 4.62)) versus younger than 50 years (LR = 3.16 (2.96 to 3.37)). For BRCA2, ER-positive grade 3 phenotype modestly predicted positive mutation status irrespective of age (LR = 1.7-fold), whereas ER-negative grade 3 features modestly predicted positive mutation status at 50 years or older (LR = 1.54 (1.27 to 1.88)). Triple-negative tumor status was highly predictive of BRCA1 mutation status for women younger than 50 years (LR = 3.73 (3.43 to 4.05)) and 50 years or older (LR = 4.41 (3.86 to 5.04)), and modestly predictive of positive BRCA2 mutation status in women 50 years or older (LR = 1.79 (1.42 to 2.24)). Conclusions These results refine likelihood-ratio estimates for predicting BRCA1 and BRCA2 mutation status by using commonly measured histopathological features. Age at diagnosis is an important variable for most analyses, and grade is more informative than ER status for BRCA2 mutation carrier prediction. The estimates will improve BRCA1 and BRCA2 variant classification and inform patient mutation testing and clinical management