Identification of a novel FGFRL1 MicroRNA target site polymorphism for bone mineral density in meta-analyses of genome-wide association studies

MicroRNAs (miRNAs) are critical post-transcriptional regulators. Based on a previous genome-wide association (GWA) scan, we conducted a polymorphism in microRNAs' Target Sites (poly-miRTS)-centric multistage meta-analysis for lumbar spine (LS)-, total hip (HIP)-, and femoral neck (FN)-bone mineral density (BMD). In stage I, 41,102 poly-miRTSs were meta-analyzed in 7 cohorts with a genome-wide significance (GWS) α=0.05/41,102=1.22×10-6. By applying α=5×10-5 (suggestive significance), 11 poly-miRTSs were selected, with FGFRL1 rs4647940 and PRR5 rs3213550 as top signals for FN-BMD (P-value=7.67×10-6 and 1.58×10-5) in gender-combined sample. In stage II in silico replication (two cohorts), FGFRL1 rs4647940 was the only signal marginally replicated for FN-BMD (P-value=5.08×10-3) at α=0.10/11=9.09×10-3. PRR5 rs3213550 was also selected based on biological significance. In stage III de novo genotyping replication (two cohorts), FGFRL1 rs4647940 was the only signal significantly replicated for FN-BMD (P-value=7.55×10-6) at α=0.05/2=0.025 in gender-combined sample. Aggregating three stages, FGFRL1 rs4647940 was the single stage I-discovered and stages II- and III-replicated signal attaining GWS for FN-BMD (P-value=8.87×10-12). Dual-luciferase reporter assays demonstrated that FGFRL1 3' untranslated region harboring rs4647940 appears to be hsa-miR-140-5p's target site. In a zebrafish microinjection experiment, dre-miR-140-5p is shown to exert a dramatic impact on craniofacial skeleton formation. Taken together, we provided functional evidence for a novel FGFRL1 poly-miRTS rs4647940 in a previously known 4p16.3 locus, and experimental and clinical genetics studies have shown both FGFRL1 and hsa-miR-140-5p are important for bone formation. © The Author 2015. Published by Oxford University Press. All rights reserved.

How cancer doctors use personalized medicine to target variations unique to each tumour

The Children’s Cancer Institute in Sydney recently launched an ambitious program. From early next year, scientists will analyse the unique cancer cells of 12 children diagnosed with the most aggressive forms of the disease to find the best treatment for each child. By 2020, they aim to have these individualised treatment options available to all children diagnosed with cancers that have a less than 30% survival rate. This way of tailoring treatment to each person is known as personalised medicine, and advances in DNA sequencing have paved the way for a new era in cancer management.

KAT5 (Tip60) is a potential therapeutic target in malignant pleural mesothelioma

Malignant pleural mesothelioma (MPM) is a rare aggressive cancer of the pleura. Asbestos exposure (through inhalation) is the most well established risk factor for mesothelioma. The current standard of care for patients suffering from MPM is a combination of cisplatin and pemetrexed (or alternatively cisplatin and raltitrexed). Most patients, however, die within 24 months of diagnosis. New therapies are therefore urgently required for this disease. Lysine acetyltransferases (KATs) including KAT5 have been linked with the development of cisplatin resistance. This gene may therefore be altered in MPM and could represent a novel candidate target for intervention. Using RT-PCR screening the expression of all known KAT5 variants was found to be markedly increased in malignant tumors compared to benign pleura. When separated according to histological subtype, KAT5 was significantly overexpressed in both the sarcomatoid and biphasic subgroups for all transcript variants. A panel of MPM cell lines including the normal pleural cells LP9 and Met5A was screened for expression of KAT5 variants. Treatment of cells with a small molecule inhibitor of KAT5 (MG-149) caused significant inhibition of cellular proliferation (p<0.0001), induction of apoptosis and was accompanied by significant induction of pro-inflammatory cytokines/chemokines.

Modelling Cued-Target Recall using Quantum Inspired Models of Target Activation

This article presents and evaluates Quantum Inspired models of Target Activation using Cued-Target Recall Memory Modelling over multiple sources of Free Association data. Two components were evaluated: Whether Quantum Inspired models of Target Activation would provide a better framework than their classical psychological counterparts and how robust these models are across the different sources of Free Association data. In previous work, a formal model of cued-target recall did not exist and as such Target Activation was unable to be assessed directly. Further to that, the data source used was suspected of suffering from temporal and geographical bias. As a consequence, Target Activation was measured against cued-target recall data as an approximation of performance. Since then, a formal model of cued-target recall (PIER3) has been developed [10] with alternative sources of data also becoming available. This allowed us to directly model target activation in cued-target recall with human cued-target recall pairs and use multiply sources of Free Association Data. Featural Characteristics known to be important to Target Activation were measured for each of the data sources to identify any major differences that may explain variations in performance for each of the models. Each of the activation models were used in the PIER3 memory model for each of the data sources and was benchmarked against cued-target recall pairs provided by the University of South Florida (USF). Two methods where used to evaluate performance. The first involved measuring the divergence between the sets of results using the Kullback Leibler (KL) divergence with the second utilizing a previous statistical analysis of the errors [9]. Of the three sources of data, two were sourced from human subjects being the USF Free Association Norms and the University of Leuven (UL) Free Association Networks. The third was sourced from a new method put forward by Galea and Bruza, 2015 in which pseudo Free Association Networks (Corpus Based Association Networks - CANs) are built using co-occurrence statistics on large text corpus. It was found that the Quantum Inspired Models of Target Activation not only outperformed the classical psychological model but was more robust across a variety of data sources.

Decomposition analysis to examine Australia’s 2030 GHGs emissions target: How hard will it be to achieve?

The Australian government has recently pledged a reduction in GHGs emissions of 26–28% below the 2005 level by 2030. How big is the challenge for the country to achieve this target in terms of its present emissions profile, recent historical trends, and the contributions to those trends from key proximate factors contributing to emissions? In this paper, we attempt a quantitative judgement of the challenge by using decomposition analysis. Based on the analysis it appears the announced target will be quite challenging to achieve if the average annual mitigating effects from economic restructuring, energy efficiency improvements and movement towards less emissions-intensive energy sources in evidence over 2002–2013 continued through to 2030; however, if the contribution from these mitigating sources in evidence over 2006–2013 can be sustained, achievement of the target will be much less challenging. The challenge for government then will be to provide a policy framework to ensure the more pronounced beneficial impacts of the mitigating factors evidenced during 2006–2013 can be maintained over the years to 2030.

Proteomic identification of putative microRNA394 target genes in Arabidopsis thaliana identifies MLP family members critical for normal development

Expression of the F-Box protein Leaf Curling Responsiveness (LCR) is regulated by microRNA, miR394, and alterations to this interplay in Arabidopsis thaliana produce defects in leaf polarity and shoot apical meristem (SAM) organisation. Although the miR394-LCR node has been documented in Arabidopsis, the identification of proteins targeted by LCR F-box itself has proven problematic. Here, a proteomic analysis of shoot apices from plants with altered LCR levels identified a member of the Major Latex Protein (MLP) family gene as a potential LCR F-box target. Bioinformatic and molecular analyses also suggested that other MLP family members are likely to be targets for this post-translational regulation. Direct interaction between LCR F-Box and MLP423 was validated. Additional MLP members had reduction in protein accumulation, in varying degrees, mediated by LCR F-Box. Transgenic Arabidopsis lines, in which MLP28 expression was reduced through an artificial miRNA technology, displayed severe developmental defects, including changes in leaf patterning and morphology, shoot apex defects, and eventual premature death. These phenotypic characteristics resemble those of Arabidopsis plants modified to over-express LCR. Taken together, the results demonstrate that MLPs are driven to degradation by LCR, and indicate that MLP gene family is target of miR394-LCR regulatory node, representing potential targets for directly post-translational regulation mediated by LCR F-Box. In addition, MLP28 family member is associated with the LCR regulation that is critical for normal Arabidopsis development.