Plasma miRNA-based signatures in CRC screening programs

Colorectal cancer (CRC) screening programs help diagnose cancer precursors and early cancers and help reduce CRC mortality. However, currently recommended tests, the fecal immunochemical test (FIT) and colonoscopy, have low uptake. There is therefore a pressing need for screening strategies that are minimally invasive and consequently more acceptable to patients, most likely blood based, to increase early CRC identification. MicroRNAs (miRNAs) released from cancer cells are detectable in plasma in a remarkably stable form, making them ideal cancer biomarkers. Using plasma samples from FIT-positive (FIT+) subjects in an Italian CRC screening program, we aimed to identify plasma circulating miRNAs that detect early CRC. miRNAs were initially investigated by quantitative real-time PCR in plasma from 60 FIT+ subjects undergoing colonoscopy at Fondazione IRCCS Istituto Nazionale dei Tumori, then tested on an internal validation cohort (IVC, 201 cases) and finally in a large multicenter prospective series (external validation cohort [EVC], 1121 cases). For each endoscopic lesion (low-grade adenoma [LgA], high-grade adenoma [HgA], cancer lesion [CL]), specific signatures were identified in the IVC and confirmed on the EVC. A two-miRNA-based signature for CL and six-miRNA signatures for LgA and HgA were selected. In a multivariate analysis including sex and age at blood collection, the areas under the receiver operating characteristic curve (95% confidence interval) of the signatures were 0.644 (0.607–0.682), 0.670 (0.626–0.714) and 0.682 (0.580–0.785) for LgA, HgA and CL, respectively. A miRNA-based test could be introduced into the FIT+ workflow of CRC screening programs so as to schedule colonoscopies only for subjects likely to benefit most.     

Tractostorm: The what,why, and how of tractography dissection reproducibility

Investigative studies of white matter (WM) brain structures using diffusion MRI (dMRI) tractography frequently require manual WM bundle segmentation, often called “virtual dissection.” Human errors and personal decisions make these manual segmentations hard to reproduce, which have not yet been quantified by the dMRI community. It is our opinion that if the field of dMRI tractography wants to be taken seriously as a widespread clinical tool, it is imperative to harmonize WM bundle segmentations and develop protocols aimed to be used in clinical settings. The EADC‐ADNI Harmonized Hippocampal Protocol achieved such standardization through a series of steps that must be reproduced for every WM bundle. This article is an observation of the problematic. A specific bundle segmentation protocol was used in order to provide a real‐life example, but the contribution of this article is to discuss the need for reproducibility and standardized protocol, as for any measurement tool. This study required the participation of 11 experts and 13 nonexperts in neuroanatomy and “virtual dissection” across various laboratories and hospitals. Intra‐rater agreement (Dice score) was approximately 0.77, while inter‐rater was approximately 0.65. The protocol provided to participants was not necessarily optimal, but its design mimics, in essence, what will be required in future protocols. Reporting tractometry results such as average fractional anisotropy, volume or streamline count of a particular bundle without a sufficient reproducibility score could make the analysis and interpretations more difficult. Coordinated efforts by the diffusion MRI tractography community are needed to quantify and account for reproducibility of WM bundle extraction protocols in this era of open and collaborative science.     

Pharmacotherapeutic strategies for critical asthma syndrome: a look at the state of the art

ABSTRACT

Introduction

‘Critical Asthma Syndrome’ (CAS) is an umbrella term proposed to include several forms of asthma, responsible for acute and life-threatening exacerbations. CAS requires urgent and adequate supportive and pharmacological treatments to prevent serious outcomes.