Fibrosis is a common pathology in cardiovascular disease1. In the heart, fibrosis causes mechanical and electrical dysfunction1,2 and in the kidney, it predicts the onset of renal failure3. Transforming growth factor β1 (TGFβ1) is the principal pro-fibrotic factor4,5, but its inhibition is associated with side effects due to its pleiotropic roles6,7. We hypothesized that downstream effectors of TGFβ1 in fibroblasts could be attractive therapeutic targets and lack upstream toxicity. Here we show, using integrated imaging–genomics analyses of primary human fibroblasts, that upregulation of interleukin-11 (IL-11) is the dominant transcriptional response to TGFβ1 exposure and required for its pro-fibrotic effect. IL-11 and its receptor (IL11RA) are expressed specifically in fibroblasts, in which they drive non-canonical, ERK-dependent autocrine signalling that is required for fibrogenic protein synthesis. In mice, fibroblast-specific Il11 transgene expression or Il-11 injection causes heart and kidney fibrosis and organ failure, whereas genetic deletion of Il11ra1 protects against disease. Therefore, inhibition of IL-11 prevents fibroblast activation across organs and species in response to a range of important pro-fibrotic stimuli. These results reveal a central role of IL-11 in fibrosis and we propose that inhibition of IL-11 is a potential therapeutic strategy to treat fibrotic diseases.

Inherited cardiac conditions (ICCs) are characterised by marked genetic and allelic heterogeneity and require extensive sequencing for genetic characterisation. We iteratively optimised a targeted gene capture panel for ICCs that includes disease-causing, putatively pathogenic, research and phenocopy genes (n = 174 genes). We achieved high coverage of the target region on both MiSeq (>99.8 % at ≥20× read depth, n = 12) and NextSeq (>99.9 % at ≥20×, n = 48) platforms with 100 % sensitivity and precision for single nucleotide variants and indels across the protein-coding target on the MiSeq. In the final assay, 40 out of 43 established ICC genes informative in clinical practice achieved complete coverage (100 % at ≥20×). By comparison, whole exome sequencing (WES; ∼80×), deep WES (∼500×) and whole genome sequencing (WGS; ∼70×) had poorer performance (88.1, 99.2 and 99.3 % respectively at ≥20×) across the ICC target. The assay described here delivers highly accurate and affordable sequencing of ICC genes, complemented by accessible cloud-based computation and informatics. See Editorial in this issue (DOI: 10.1007/s12265-015-9667-8).Electronic supplementary materialThe online version of this article (doi:10.1007/s12265-016-9673-5) contains supplementary material, which is available to authorized users.

Amphidiploid species in the Brassicaceae family, such as Brassica napus, are more tolerant to environmental stress than their diploid ancestors.A relatively salt tolerant B. napus line, N119, identified in our previous study, was used. N119 maintained lower Na+ content, and Na+/K+ and Na+/Ca2+ ratios in the leaves than a susceptible line. The transcriptome profiles of both the leaves and the roots 1 h and 12 h after stress were investigated. De novo assembly of individual transcriptome followed by sequence clustering yielded 161,537 nonredundant sequences. A total of 14,719 transcripts were differentially expressed in either organs at either time points. GO and KO enrichment analyses indicated that the same 49 GO terms and seven KO terms were, respectively, overrepresented in upregulated transcripts in both organs at 1 h after stress. Certain overrepresented GO term of genes upregulated at 1 h after stress in the leaves became overrepresented in genes downregulated at 12 h. A total of 582 transcription factors and 438 transporter genes were differentially regulated in both organs in response to salt shock. The transcriptome depicting gene network in the leaves and the roots regulated by salt shock provides valuable information on salt resistance genes for future application to crop improvement.

The epidermal growth factor receptor (EGFR) is genetically altered in nearly 60% of glioblastoma tumors; however, tyrosine kinase inhibitors (TKIs) against EGFR have failed to show efficacy for patients with these lethal brain tumors. This failure is attributed to the inability of clinically tested EGFR TKIs to cross the blood–brain barrier (BBB) and achieve adequate pharmacological levels to inhibit various oncogenic forms of EGFR that drive glioblastoma. Through SAR analysis, we developed compound 5 (JCN037) from an anilinoquinazoline scaffold by ring fusion of the 6,7-dialkoxy groups to reduce the number of rotatable bonds and polar surface area and by introduction of an ortho-fluorine and meta-bromine on the aniline ring for improved potency and BBB penetration. Relative to the conventional EGFR TKIs erlotinib and lapatinib, JCN037 displayed potent activity against EGFR amplified/mutant patient-derived cell cultures, significant BBB penetration (2:1 brain-to-plasma ratio), and superior efficacy in an EGFR-driven orthotopic glioblastoma xenograft model.

The lipidome has a broad range of biological and signaling functions, including serving as a structural scaffold for membranes and initiating and resolving inflammation. To investigate the biological activity of phospholipids and their bioactive metabolites, precise analytical techniques are necessary to identify specific lipids and quantify their levels. Simultaneous quantification of a set of lipids can be achieved using high sensitivity mass spectrometry (MS) techniques, whose technological advancements have significantly improved over the last decade. This has unlocked the power of metabolomics/lipidomics allowing the dynamic characterization of metabolic systems. Lipidomics is a subset of metabolomics for multianalyte identification and quantification of endogenous lipids and their metabolites. Lipidomics-based technology has the potential to drive novel biomarker discovery and therapeutic development programs; however, appropriate standards have not been established for the field. Standardization would improve lipidomic analyses and accelerate the development of innovative therapies. This review aims to summarize considerations for lipidomic study designs including instrumentation, sample stabilization, data validation, and data analysis. In addition, this review highlights how lipidomics can be applied to biomarker discovery and drug mechanism dissection in various inflammatory diseases including cardiovascular disease, neurodegeneration, lung disease, and autoimmune disease.