摘要
BACKGROUND In their everyday life,clinicians face an overabundance of biological indicators potentially helpful during a disease therapy.In this context,to be able to reliably identify a reduced number of those markers showing the ability of optimising the classification of treatment outcomes becomes a factor of vital importance to medical prognosis.In this work,we focus our interest in inflammatory bowel disease(IBD),a long-life threaten with a continuous increasing prevalence worldwide.In particular,IBD can be described as a set of autoimmune conditions affecting the gastrointestinal tract whose two main types are Crohn’s disease and ulcerative colitis.AIM To identify the minimal signature of microRNA(miRNA)associated with colorectal cancer(CRC)in patients with one chronic IBD.METHODS We provide a framework of well-established statistical and computational learning methods wisely adapted to reconstructing a CRC network leveraged to stratify these patients.RESULTS Our strategy resulted in an adjusted signature of 5 miRNAs out of approximately 2600 in Crohn’s Disease(resp.8 in Ulcerative Colitis)with a percentage of success in patient classification of 82%(resp.81%).CONCLUSION Importantly,these two signatures optimally balance the proportion between the number of significant miRNAs and their percentage of success in patients’stratification.
