Nicola J. Camp

Primary biliary cirrhosis shows association with genetic polymorphism of tumour necrosis factor alpha promoter region

BACKGROUND/AIMSnPrimary biliary cirrhosis is an autoimmune disease in which increased prevalence in first-degree relatives and an association with HLA DR8 suggest a genetic background. TNFalpha is a mediator of inflammation and immunity, and is implicated in the pathogenesis of primary biliary cirrhosis, ex vivo studies having shown reduced production of TNFalpha by lymphocytes from patients. Our group has previously described a biallelic promoter-region polymorphism of the TNFA gene at position -308, and demonstrated that the rare allele, TNF*2, has increased promoter function compared with the common allele, TNF*1. A further biallelic base change has been described in the TNFA gene at -238. We conducted a case-control study to assess association of these gene polymorphisms with primary biliary cirrhosis.nnnMETHODSnNinety-one patients and 213 controls were genotyped for both TNFA loci using restriction fragment length polymorphism analysis of PCR products.nnnRESULTSnThe high production TNFA-308*2 allele was significantly under-represented among subjects with primary biliary cirrhosis (27.5% PBC, 41.6% controls, p=0.02, pc=0.04, OR for carriage of TNF*1/*1 genotype=1.89, CI=1.10-3.32). No association was shown with the TNFA -238 polymorphism.nnnCONCLUSIONnPrimary biliary cirrhosis is associated with reduced carriage of TNF*2. This is in keeping with a protective role of TNFalpha against the disease.

Functional correlates of the interleukin-1 receptor antagonist gene polymorphism in the colonic mucosa in ulcerative colitis

Association studies have identified the interleukin-1 receptor antagonist gene allele 2(IL-1RN*2) as a marker of susceptibility in ulcerative colitis (UC). This study investigated the significance of the IL-1RN genotype with respect to protein and mRNA expression in the colonic mucosa. Homogenates of rectal biopsies from 99 UC and 54 controls were assayed for cytokines IL-1ra, IL-1a and IL-1b using ELISA. IL1RN, IL1A and IL1B genotypes were determined using restriction-enzyme analysis. The ability of the two IL1RN alleles to generate steady-state mRNA accumulation was assessed in the colonic mucosa of seven heterozygous patients. Stepwise linear regression demonstrated that IL-1RN genotype (P=0.001), diagnosis (P<0.0001) and treatment (P<0.03) were independent factors associated with the IL-1ra protein level whilst IL1RN genotype (P=0.005) and macroscopic inflammatory grade (P<0.0001) were associated with the IL-1ra/ total IL-1 ratio. The IL1RN*2 correlated with reduced IL-1ra and IL-1ra/IL-1 ratio with a gene dosage effect. In heterozygous UC patients the ratio of allele 1 mRNA / allele 2 steady state mRNA was always greater than 1 (range: 1.2–3.1) (P=0.018). The IL-1RN*2 is associated with reduced levels of IL-1ra protein and IL-1RN mRNA in the colonic mucosa, providing a biologically plausible explanation for the observed association of the allele with the disease.

Whole transcriptome profiling of patient-derived xenograft models as a tool to identify both tumor and stromal specific biomarkers.

The tumor microenvironment is emerging as a key regulator of cancer growth and progression, however the exact mechanisms of interaction with the tumor are poorly understood. Whilst the majority of genomic profiling efforts thus far have focused on the tumor, here we investigate RNA-Seq as a hypothesis-free tool to generate independent tumor and stromal biomarkers, and explore tumor-stroma interactions by exploiting the human-murine compartment specificity of patient-derived xenografts (PDX). Across a pan-cancer cohort of 79 PDX models, we determine that mouse stroma can be separated into distinct clusters, each corresponding to a specific stromal cell type. This implies heterogeneous recruitment of mouse stroma to the xenograft independent of tumor type. We then generate cross-species expression networks to recapitulate a known association between tumor epithelial cells and fibroblast activation, and propose a potentially novel relationship between two hypoxia-associated genes, human MIF and mouse Ddx6. Assessment of disease subtype also reveals MMP12 as a putative stromal marker of triple-negative breast cancer. Finally, we establish that our ability to dissect recruited stroma from trans-differentiated tumor cells is crucial to identifying stem-like poor-prognosis signatures in the tumor compartment. In conclusion, RNA-Seq is a powerful, cost-effective solution to global analysis of human tumor and mouse stroma simultaneously, providing new insights into mouse stromal heterogeneity and compartment-specific disease markers that are otherwise overlooked by alternative technologies. The study represents the first comprehensive analysis of its kind across multiple PDX models, and supports adoption of the approach in pre-clinical drug efficacy studies, and compartment-specific biomarker discovery.

Consensus Analysis of Whole Transcriptome Profiles from Two Breast Cancer Patient Cohorts Reveals Long Non-Coding RNAs Associated with Intrinsic Subtype and the Tumour Microenvironment.

Long non-coding RNAs (lncRNAs) are emerging as crucial regulators of cellular processes and diseases such as cancer; however, their functions remain poorly characterised. Several studies have demonstrated that lncRNAs are typically disease and tumour subtype specific, particularly in breast cancer where lncRNA expression alone is sufficient to discriminate samples based on hormone status and molecular intrinsic subtype. However, little attempt has been made to assess the reproducibility of lncRNA signatures across more than one dataset. In this work, we derive consensus lncRNA signatures indicative of breast cancer subtype based on two clinical RNA-Seq datasets: the Utah Breast Cancer Study and The Cancer Genome Atlas, through integration of differential expression and hypothesis-free clustering analyses. The most consistent signature is associated with breast cancers of the basal-like subtype, leading us to generate a putative set of six lncRNA basal-like breast cancer markers, at least two of which may have a role in cis-regulation of known poor prognosis markers. Through in silico functional characterization of individual signatures and integration of expression data from pre-clinical cancer models, we discover that discordance between signatures derived from different clinical cohorts can arise from the strong influence of non-cancerous cells in tumour samples. As a consequence, we identify nine lncRNAs putatively associated with breast cancer associated fibroblasts, or the immune response. Overall, our study establishes the confounding effects of tumour purity on lncRNA signature derivation, and generates several novel hypotheses on the role of lncRNAs in basal-like breast cancers and the tumour microenvironment.