Prior knowledge transfer across transcriptional data sets and technologies using compositional statistics yields new mislabelled ovarian cell line

Here, we describe gene expression compositional assignment (GECA), a powerful, yet simple method based on compositional statistics that can validate the transfer of prior knowledge, such as gene lists, into independent data sets, platforms and technologies. Transcriptional profiling has been used to derive gene lists that stratify patients into prognostic molecular subgroups and assess biomarker performance in the pre-clinical setting. Archived public data sets are an invaluable resource for subsequent in silico validation, though their use can lead to data integration issues. We show that GECA can be used without the need for normalising expression levels between data sets and can outperform rank-based correlation methods. To validate GECA, we demonstrate its success in the cross-platform transfer of gene lists in different domains including: bladder cancer staging, tumour site of origin and mislabelled cell lines. We also show its effectiveness in transferring an epithelial ovarian cancer prognostic gene signature across technologies, from a microarray to a next-generation sequencing setting. In a final case study, we predict the tumour site of origin and histopathology of epithelial ovarian cancer cell lines. In particular, we identify and validate the commonly-used cell line OVCAR-5 as non-ovarian, being gastrointestinal in origin. GECA is available as an open-source R package.

Epigenetic Therapy for the Treatment of Hypertension-Induced Cardiac Hypertrophy and Fibrosis

BACKGROUND: The development of heart failure is associated with changes in the size, shape, and structure of the heart that has a negative impact on cardiac function. These pathological changes involve excessive extracellular matrix deposition within the myocardial interstitium and myocyte hypertrophy. Alterations in fibroblast phenotype and myocyte activity are associated with reprogramming of gene transcriptional profiles that likely requires epigenetic alterations in chromatin structure. The aim of our work was to investigate the potential of a currently licensed anticancer epigenetic modifier as a treatment option for cardiac diseases associated with hypertension-induced cardiac hypertrophy and fibrosis.

METHODS AND RESULTS: The effects of DNA methylation inhibition with 5-azacytidine (5-aza) were examined in a human primary fibroblast cell line and in a spontaneously hypertensive rat (SHR) model. The results from this work allude to novel in vivo antifibrotic and antihypertrophic actions of 5-aza. Administration of the DNA methylation inhibitor significantly improved several echocardiographic parameters associated with hypertrophy and diastolic dysfunction. Myocardial collagen levels and myocyte size were reduced in 5-aza-treated SHRs. These findings are supported by beneficial in vitro effects in cardiac fibroblasts. Collagen I, collagen III, and α-smooth muscle actin were reduced in a human ventricular cardiac fibroblast cell line treated with 5-aza.

CONCLUSION: These findings suggest a role for epigenetic modifications in contributing to the profibrotic and hypertrophic changes evident during disease progression. Therapeutic intervention with 5-aza demonstrated favorable effects highlighting the potential use of this epigenetic modifier as a treatment option for cardiac pathologies associated with hypertrophy and fibrosis.

Attenuation of monocyte chemotaxis--a novel anti-inflammatory mechanism of action for the cardio-protective hormone B-type natriuretic peptide

B-type natriuretic peptide (BNP) is a prognostic and diagnostic marker for heart failure (HF). An anti-inflammatory, cardio-protective role for BNP was proposed. In cardiovascular diseases including pressure overload-induced HF, perivascular inflammation and cardiac fibrosis are, in part, mediated by monocyte chemoattractant protein (MCP)1-driven monocyte migration. We aimed to determine the role of BNP in monocyte motility to MCP1. A functional BNP receptor, natriuretic peptide receptor-A (NPRA) was identified in human monocytes. BNP treatment inhibited MCP1-induced THP1 (monocytic leukemia cells) and primary monocyte chemotaxis (70 and 50 %, respectively). BNP did not interfere with MCP1 receptor expression or with calcium. BNP inhibited activation of the cytoskeletal protein RhoA in MCP1-stimulated THP1 (70 %). Finally, BNP failed to inhibit MCP1-directed motility of monocytes from patients with hypertension (n = 10) and HF (n = 6) suggesting attenuation of this anti-inflammatory mechanism in chronic heart disease. We provide novel evidence for a direct role of BNP/NPRA in opposing human monocyte migration and support a role for BNP as a cardio-protective hormone up-regulated as part of an adaptive compensatory response to combat excess inflammation.

Efficient Genotyping of KRAS Mutant Non-Small Cell Lung Cancer Using a Multiplexed Droplet Digital PCR Approach.

Droplet digital PCR (ddPCR) can be used to detect low frequency mutations in oncogene-driven lung cancer. The range of KRAS point mutations observed in NSCLC necessitates a multiplex approach to efficient mutation detection in circulating DNA. Here we report the design and optimisation of three discriminatory ddPCR multiplex assays investigating nine different KRAS mutations using PrimePCR™ ddPCR™ Mutation Assays and the Bio-Rad QX100 system. Together these mutations account for 95% of the nucleotide changes found in KRAS in human cancer. Multiplex reactions were optimised on genomic DNA extracted from KRAS mutant cell lines and tested on DNA extracted from fixed tumour tissue from a cohort of lung cancer patients without prior knowledge of the specific KRAS genotype. The multiplex ddPCR assays had a limit of detection of better than 1 mutant KRAS molecule in 2,000 wild-type KRAS molecules, which compared favourably with a limit of detection of 1 in 50 for next generation sequencing and 1 in 10 for Sanger sequencing. Multiplex ddPCR assays thus provide a highly efficient methodology to identify KRAS mutations in lung adenocarcinoma.