Defining biological remission in Crohn's disease: interest, challenges and future directions.

peer reviewedIn Crohn's disease, the treat-to-target strategy has been highly encouraged and became a standard of care. In this context, defining the target (remission) constitutes a major stake which fuels the literature. Currently, clinical remission (symptoms control) is no longer the only objective of treatments since it does not allow to well control inflammation-induced tissue damage. The introduction of endoscopic remission as a therapeutic target was clearly a progress but this examination remains invasive, costly, not well accepted by patients and does not allow a tight control of disease activity. More fundamentally, morphological techniques (eg, endoscopy, histology, ultrasonography) are limited since they do not evaluate the biological activity of the disease but only its consequences. Besides, emerging evidence suggest that biological signs of disease activity could better guide treatment decisions than clinical parameters. In this context, we stress the necessity to define a novel treatment target: biological remission. Based on our previous work, we propose a conceptual definition of biological remission which goes beyond the classical normalisation of inflammatory markers (C-reactive protein and faecal calprotectin): absence of biological signs associated with the risk of short-term relapse and mid/long-term relapse. The risk of short-term relapse seems essentially characterised by a persistent inflammatory state while the risk of mid/long-term relapse implicates a more heterogeneous biology. We discuss the interest of our proposal (guiding treatment maintenance, escalation or de-escalation) but also the fact that its clinical implementation would require overcoming major challenges. Finally, future directions are proposed to better define biological remission

Challenges for Biomarker Discovery in Body Fluids Using SELDI-TOF-MS

Protein profiling using SELDI-TOF-MS has gained over the past few years an increasing interest in the field of biomarker discovery. The technology presents great potential if some parameters, such as sample handling, SELDI settings, and data analysis, are strictly controlled. Practical considerations to set up a robust and sensitive strategy for biomarker discovery are presented. This paper also reviews biological fluids generally available including a description of their peculiar properties and the preanalytical challenges inherent to sample collection and storage. Finally, some new insights for biomarker identification and validation challenges are provided

GC×GC-(HR)TOFMS in Cancer Research

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How to Apply for and Secure EU Funding for Collaborative IBD Research Projects.

peer reviewedThe European Union offers opportunities for high-level of funding of collaborative European research. Calls are regularly published: after the end of the FP7 funding programme the new round of Horizon 2020 calls started in 2015. Several topics are relevant to inflammatory bowel disease (IBD) challenges, including chronic disease management, biomarker discovery and new treatments developments. The aim of this Viewpoint article is to describe the new Horizon 2020 instrument and the project submission procedures, and to highlight these through the description of tips and tricks, taking advantage of four examples of successful projects in the field of IBD: the SADEL, IBD-BIOM, IBD Character and BIOCYCLE projects

Proteomic mass spectra classification using decision tree based ensemble methods.

MOTIVATION: Modern mass spectrometry allows the determination of proteomic fingerprints of body fluids like serum, saliva or urine. These measurements can be used in many medical applications in order to diagnose the current state or predict the evolution of a disease. Recent developments in machine learning allow one to exploit such datasets, characterized by small numbers of very high-dimensional samples. RESULTS: We propose a systematic approach based on decision tree ensemble methods, which is used to automatically determine proteomic biomarkers and predictive models. The approach is validated on two datasets of surface-enhanced laser desorption/ionization time of flight measurements, for the diagnosis of rheumatoid arthritis and inflammatory bowel diseases. The results suggest that the methodology can handle a broad class of similar problems

Comprehensive Insight into Colorectal Cancer Metabolites and Lipids for Human Serum: A Proof-of-Concept Study.

peer reviewedColorectal cancer (CRC) ranks as the third most frequently diagnosed cancer and the second leading cause of cancer-related deaths. The current endoscopic-based or stool-based diagnostic techniques are either highly invasive or lack sufficient sensitivity. Thus, there is a need for less invasive and more sensitive screening approaches. We, therefore, conducted a study on 64 human serum samples representing three different groups (adenocarcinoma, adenoma, and control) using cutting-edge GC×GC-LR/HR-TOFMS (comprehensive two-dimensional gas chromatography coupled with low/high-resolution time-of-flight mass spectrometry). We analyzed samples with two different specifically tailored sample preparation approaches for lipidomics (fatty acids) (25 μL serum) and metabolomics (50 μL serum). In-depth chemometric screening with supervised and unsupervised approaches and metabolic pathway analysis were applied to both datasets. A lipidomics study revealed that specific PUFA (ω-3) molecules are inversely associated with increased odds of CRC, while some PUFA (ω-6) analytes show a positive correlation. The metabolomics approach revealed downregulation of amino acids (alanine, glutamate, methionine, threonine, tyrosine, and valine) and myo-inositol in CRC, while 3-hydroxybutyrate levels were increased. This unique study provides comprehensive insight into molecular-level changes associated with CRC and allows for a comparison of the efficiency of two different analytical approaches for CRC screening using same serum samples and single instrumentation

Review article: distinctions between ileal and colonic Crohn's disease: from physiology to pathology.

peer reviewedBACKGROUND: Ileal and colonic Crohn's disease seem to be two separate entities. AIMS: To describe the main physiological distinctions between the small and the large intestine and to analyse the differences between ileal and colonic Crohn's disease. METHODS: The relevant literature was critically examined and synthesised. RESULTS: The small and large intestine have fundamental distinctions (anatomy, cellular populations, immune defence, microbiota). The differences between ileal and colonic Crohn's disease are highlighted by a heterogeneous body of evidence including clinical features (natural history of the disease, efficacy of treatments, and monitoring), epidemiological data (smoking status, age, gender) and biological data (genetics, microbiota, immunity, mesenteric fat). However, the contribution of these factors to disease location remains poorly understood. CONCLUSION: The classification of ileal and colonic Crohn's disease as distinct subphenotypes is well supported by the literature. Understanding of these differences could be exploited to develop more individualised patient care

Discovery of new rheumatoid arthritis biomarkers using the surface-enhanced laser desorption/ionization time-of-flight mass spectrometry ProteinChip approach.

peer reviewedOBJECTIVE: To identify serum protein biomarkers specific for rheumatoid arthritis (RA), using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS) technology. METHODS: A total of 103 serum samples from patients and healthy controls were analyzed. Thirty-four of the patients had a diagnosis of RA, based on the American College of Rheumatology criteria. The inflammation control group comprised 20 patients with psoriatic arthritis (PsA), 9 with asthma, and 10 with Crohn's disease. The noninflammation control group comprised 14 patients with knee osteoarthritis and 16 healthy control subjects. Serum protein profiles were obtained by SELDI-TOF-MS and compared in order to identify new biomarkers specific for RA. Data were analyzed by a machine learning algorithm called decision tree boosting, according to different preprocessing steps. RESULTS: The most discriminative mass/charge (m/z) values serving as potential biomarkers for RA were identified on arrays for both patients with RA versus controls and patients with RA versus patients with PsA. From among several candidates, the following peaks were highlighted: m/z values of 2,924 (RA versus controls on H4 arrays), 10,832 and 11,632 (RA versus controls on CM10 arrays), 4,824 (RA versus PsA on H4 arrays), and 4,666 (RA versus PsA on CM10 arrays). Positive results of proteomic analysis were associated with positive results of the anti-cyclic citrullinated peptide test. Our observations suggested that the 10,832 peak could represent myeloid-related protein 8. CONCLUSION: SELDI-TOF-MS technology allows rapid analysis of many serum samples, and use of decision tree boosting analysis as the main statistical method allowed us to propose a pattern of protein peaks specific for RA