ImmUniverse Consortium: Multi-omics integrative approach in personalized medicine for immune-mediated inflammatory diseases.

Immune mediated inflammatory diseases (IMIDs) are a heterogeneous group of debilitating, multifactorial and unrelated conditions featured by a dysregulated immune response leading to destructive chronic inflammation. The immune dysregulation can affect various organ systems: gut (e.g., inflammatory bowel disease), joints (e.g., rheumatoid arthritis), skin (e.g., psoriasis, atopic dermatitis), resulting in significant morbidity, reduced quality of life, increased risk for comorbidities, and premature death. As there are no reliable disease progression and therapy response biomarkers currently available, it is very hard to predict how the disease will develop and which treatments will be effective in a given patient. In addition, a considerable proportion of patients do not respond sufficiently to the treatment. ImmUniverse is a large collaborative consortium of 27 partners funded by the Innovative Medicine Initiative (IMI), which is sponsored by the European Union (Horizon 2020) and in-kind contributions of participating pharmaceutical companies within the European Federation of Pharmaceutical Industries and Associations (EFPIA). ImmUniverse aims to advance our understanding of the molecular mechanisms underlying two immune-mediated diseases, ulcerative colitis (UC) and atopic dermatitis (AD), by pursuing an integrative multi-omics approach. As a consequence of the heterogeneity among IMIDs patients, a comprehensive, evidence-based identification of novel biomarkers is necessary to enable appropriate patient stratification that would account for the inter-individual differences in disease severity, drug efficacy, side effects or prognosis. This would guide clinicians in the management of patients and represent a major step towards personalized medicine. ImmUniverse will combine the existing and novel advanced technologies, including multi-omics, to characterize both the tissue microenvironment and blood. This comprehensive, systems biology-oriented approach will allow for identification and validation of tissue and circulating biomarker signatures as well as mechanistic principles, which will provide information about disease severity and future disease progression. This truly makes the ImmUniverse Consortium an unparalleled approach.

Implications and pitfalls for cancer diagnostics exploiting extracellular vesicles.

Early detection of cancer in order to facilitate timely therapeutic interventions is an unsolved problem in today's clinical diagnostics. Tumors are detected so far mostly after pathological symptoms have emerged (usually already in progressed disease states), within preventive screenings, or occasionally as incidental finding. The emergence of extracellular vesicle (EV) analytics in combination with liquid biopsy sampling opened a plethora of new possibilities for the detection of tumors (and other diseases). This review gives an overview of the diversity of currently known EV species and the relevant cargo molecules representing potential biomarkers to detect, identify and characterize tumor cells. A number of molecules reported in recent years to be valuable targets for different aspects of cancer diagnostics, are presented. Furthermore, we discuss (technical) challenges and pitfalls related to the various potential applications (screening, diagnosis, prognosis, monitoring) of liquid biopsy based EV analytics, and give an outlook to possible future directions of this emerging field in oncology.

Multiplexed and Sensitive DNA Methylation Testing Using Methylation-Sensitive Restriction Enzymes "MSRE-qPCR".

DNA methylation is a chemically stable key-player in epigenetics. In the vertebrate genome the 5-methyl cytosine (5mC) has been found almost exclusively in the CpG dinucleotide context. CpG dinucleotides are enriched in CpG islands very frequently located within or close to gene promoters. Analyses of DNA methylation changes in human diagnostics have been conducted classically using methylation-sensitive restriction enzymes (MSRE). Since the discovery of bisulfite conversion-based sequencing and PCR assays, MSRE-based PCR assays have been less frequently used, although especially in the field of cancer epigenetics MSRE-based genome-wide discovery and targeted screening applications have been and are still performed successfully. Even though epigenome-wide discovery of altered DNA methylation patterns has found its way into various fields of human disease and molecular genetics research, the validation of findings upon discovery is still a bottleneck. Usually several multiples of 10 up to 100 candidate biomarkers from discovery have to be confirmed or are of interest for further work. In particular, bisulfite PCR assays are often limited in the number of candidates which can be analyzed, due to their low multiplexing capability, especially, if only small amounts of DNA are available from for example clinical specimens. In clinical research and diagnostics a similar situation arises for the analyses of cell-free DNA (cfDNA) in body fluids or circulating tumor cells (CTCs). Although tissue- or disease- (e.g., cancer) specific DNA methylation patterns can be deduced very efficiently in a genome-wide manner if around 100 ng of DNA are available, confirming these candidates and selecting target-sequences for studying methylation changes in liquid biopsies using cfDNA or CTCs remains a big challenge. Along these lines we have developed MSRE-qPCR and introduce here method details, which have been found very suitable for the efficient confirmation and testing of DNA methylation in a quantitative multiplexed manner (e.g., 48-96 plex) from ng amounts of DNA. The method is applicable in a standard qPCR setting as well for nanoliter scaled high-throughput qPCR, enabling detection of <10 copies of targets, thus suitable to pick up 0.1-1% of specific methylated DNA in an unmethylated background.

Strategies for validation and testing of DNA methylation biomarkers.

DNA methylation is a stable covalent epigenetic modification of primarily CpG dinucleotides that has recently gained considerable attention for its use as a biomarker in different clinical settings, including disease diagnosis, prognosis and therapeutic response prediction. Although the advent of genome-wide DNA methylation profiling in primary disease tissue has provided a manifold resource for biomarker development, only a tiny fraction of DNA methylation-based assays have reached clinical testing. Here, we provide a critical overview of different analytical methods that are suitable for biomarker validation, including general study design considerations, which might help to streamline epigenetic marker development. Furthermore, we highlight some of the recent marker validation studies and established markers that are currently commercially available for assisting in clinical management of different cancers.

Soluble ST2 is regulated by p75 neurotrophin receptor and predicts mortality in diabetic patients with critical limb ischemia.

OBJECTIVE: The p75 neurotrophin receptor (p75(NTR)) contributes to diabetes mellitus-induced defective postischemic neovascularization. The interleukin-33 receptor ST2 is expressed as transmembrane (ST2L) and soluble (sST2) isoforms. Here, we studied the following: (1) the impact of p75(NTR) in the healing of ischemic and diabetic calf wounds; (2) the link between p75(NTR) and ST2; and (3) circulating sST2 levels in critical limb ischemia (CLI) patients. METHODS AND RESULTS: Diabetes mellitus was induced in p75(NTR) knockout (p75KO) mice and wild-type (WT) littermates by streptozotocin. Diabetic and nondiabetic p75KO and WT mice received left limb ischemia induction and a full-thickness wound on the ipsilateral calf. Diabetes mellitus impaired wound closure and angiogenesis and increased ST2 expression in WT, but not in p75KO wounds. In cultured endothelial cells, p75(NTR) promoted ST2 (both isoforms) expression through p38(MAPK)/activating transcription factor 2 pathway activation. Next, sST2 was measured in the serum of patients with CLI undergoing either revascularization or limb amputation and in the 2 nondiabetic groups (with CLI or nonischemic individuals). Serum sST2 increased in diabetic patients with CLI and was directly associated with higher mortality at 1 year from revascularization. CONCLUSIONS: p75(NTR) inhibits the healing of ischemic lower limb wounds in diabetes mellitus and promotes ST2 expression. Circulating sST2 predicts mortality in diabetic CLI patients.

Consensus genes of the literature to predict breast cancer recurrence.

BACKGROUND: Extensive efforts have been undertaken to discover genes relevant for breast cancer prognosis. Yet, in current opinion, with little overlap in findings. We aimed to reanalyze molecular prediction of breast cancer recurrence. METHODS: From 44 published gene lists relevant for breast cancer prognosis, we extracted 374 genes, which, besides other quality criteria, are recorded at least twice. From eight published microarray datasets, a single dataset of 1,067 breast cancer patients was created, using transformation to 'probability of expression' scale. For recurrence analysis, the Cox proportional hazards model was applied. RESULTS: The 374 genes, termed '374 Gene Set', are highly enriched in cell cycle genes. The '374 Gene Set' is significantly associated with breast cancer recurrence (p = 2 x 10(-12), log-rank test) in the meta set of 1,067 patients, showing an estimated Hazard Ratio of recurrence for the 'poor' prognosis group compared to the 'good' prognosis group of 2.03 (95% confidence interval, 1.66-2.48). Notably, the '374 Gene Set' is significantly associated with recurrence in untreated patients. In multivariate analysis, including the standard histopathological parameters, only tumor size and the '374 Gene Set' remain independent predictors of recurrence. External validation further confirmed the prognostic relevance of the gene set (253 patients, p = 0.001, log-rank test). CONCLUSIONS: The '374 Gene Set' comprises a molecular basis of metastatic breast cancer progression. Starting from this gene set it might be possible to construct a clinically relevant classifier, which then again needs to be validated.

Comparison of RNA amplification techniques meeting the demands for the expression profiling of clinical cancer samples.

Available ribonucleic acid (RNA) amplification methods are extensively tested for reproducibility, but only a few studies additionally deal with potential amplification bias. On targeted arrays, we evaluated three amplification protocols, which are less time consuming than the commonly used T7-RNA polymerase based in vitro transcription protocols and therefore may be more suitable for clinical use: Template-switching polymerase chain reaction (PCR), Ribo-single primer isothermal amplification and a random primer-based PCR. Additionally, a more sensitive labelling method, Dendrimer labelling, was evaluated. All methods were compared to unamplified RNA labelled at reverse transcription. From our results, we conclude that RNA amplification with template-switching PCR is highly reproducible and results in a reliable representation of the starting RNA population. We then assessed whether RNA amplification of clinical breast and thyroid cancer samples with template-switching PCR showed robust performance when altered cycle numbers or partially degraded RNA were used. Template-switching PCR proved to be a very reliable method for global RNA amplification, even when starting from partially degraded RNA down to a RNA Integrity Number of 4.3. In conclusion, template-switching PCR amplification promises to help micro-array expression profiling of limited amounts of human samples on its way to a clinical routine.

Characterization of the drugged human genome.

Human drug targets are a part of our genome of special relevance to human disease. However, the number and nature of drug target genes has not yet been conclusively assessed. We analyzed involvement in biochemical functions, biological processes and pathways, with chromosome, cellular and tissue distribution of the 392 human drug targets collected in DrugBank. Comparison with the whole human genome reveals their scarcely diverse characteristics, largely dominated by rhodopsin-like 7 transmembrane receptors involved in the neuroactive ligand-receptor interaction pathway and located in the plasma membrane. Drug target genes are frequently expressed in multiple tissues, suggesting drug application in distinct disease classes. Intersections with other clinically relevant gene sets, such as the Mendelian disorder-linked genes and various molecular cancer signatures, are discussed.