Predicting Breast Cancer Response to Neoadjuvant Chemotherapy Using Pretreatment Diffuse Optical Spectroscopic-Texture Analysis

Purpose: Diffuse optical spectroscopy (DOS) has been demonstrated capable of monitoring response to neoadjuvant chemotherapy (NAC) in locally advanced breast cancer (LABC) patients. In this study, we evaluate texture features of pre-treatment DOS functional maps for predicting LABC response to NAC. Methods: LABC patients (n = 37) underwent DOS-breast imaging before starting neoadjuvant chemotherapy. Breast-tissue parametric maps were constructed and texture analyses were performed based on grey level co-occurrence matrices (GLCM) for feature extraction. Ground-truth labels as responders (R) or non-responders (NR) were assigned to patients based on Miller-Payne pathological response criteria. The capability of DOS-textural features computed on volumetric tumour data before the start of treatment (i.e. “pre-treatment”) to predict patient responses to NAC was evaluated using a leave-one-out validation scheme at subject level. Data were analysed using a logistic regression, naïve Bayes, and k-nearest neighbour (k-NN) classifiers. Results: Data indicated that textural characteristics of pre-treatment DOS parametric maps can differentiate between treatment response outcomes. The HbO2-homogeneity resulted in the highest accuracy amongst univariate parameters in predicting response to chemotherapy: sensitivity (%Sn) and specificity (%Sp) were 86.5 and 89.0%, respectively and accuracy was 87.8%. The highest predictors using multivariate (binary) combination features were the Hb-Contrast + HbO2-Homogeneity which resulted in a %Sn/%Sp = 78.0/81.0% and an accuracy of 79.5%. Conclusions: This study demonstrated that pre-treatment tumour DOS-texture features can predict breast cancer response to NAC and potentially guide treatments

Land, Labour and Capital Markets in European Agriculture: Diversity under a Common Policy. CEPS Paperback. October 2013

Well-functioning factor markets are an essential condition for the competitiveness and sustainable development of agriculture and rural areas. At the same time, the functioning of the factor markets themselves is influenced by changes in agriculture and the rural economy. Such changes can be the result of progress in technology, globalisation and European market integration, changing consumer preferences and shifts in policy. Changes in the Common Agricultural Policy (CAP) over the last decade have particularly affected the rural factor markets. This book analyses the functioning of factor markets for agriculture in the EU-27 and several candidate countries. Written by leading academics and policy analysts from various European countries, these chapters compare the different markets, their institutional framework, their impact on agricultural development and structural change, and their interaction with the CAP. As the first comparative study to cover rural factor markets in Europe, highlighting their diversity − despite the Common Agricultural Policy and an integrated single market − Land, Labour & Capital Markets in European Agriculture provides a timely and valuable source of information at a time of further CAP reform and the continuing transformation of the EU's rural areas

Identification of Novel MET Exon 14 Skipping Variants in Non-Small Cell Lung Cancer Patients: A Prototype Workflow Involving in Silico Prediction and RT-PCR

Background and aims: The MET exon 14 skipping (METex14) is an oncogenic driver mutation that provides a therapeutic opportunity in non-small cell lung cancer (NSCLCs) patients. This event often results from sequence changes at the MET canonical splicing sites. We characterize two novel non-canonical splicing site variants of MET that produce METex14. Materials and Methods: Two variants were identified in three advanced-stage NSCLC patients in a next-generation sequencing panel. The potential impact on splicing was predicted using in silico tools. METex14 mutation was confirmed using reverse transcription (RT)-PCR and a Sanger sequencing analysis on RNA extracted from stained cytology smears. Results: The interrogated MET (RefSeq ID NM_000245.3) variants include a single nucleotide substitution, c.3028+3A>T, in intron 14 and a deletion mutation, c.3012_3028del, in exon 14. The in silico prediction analysis exhibited reduced splicing strength in both variants compared with the MET normal transcript. The RT-PCR and subsequent Sanger sequencing analyses confirmed METex14 skipping in all three patients carrying these variants. Conclusion: This study reveals two non-canonical MET splice variants that cause exon 14 skipping, concurrently also proposes a clinical workflow for the classification of such non-canonical splicing site variants detected by routine DNA-based NGS test. It shows the usefulness of in silico prediction to identify potential METex14 driver mutation and exemplifies the opportunity of routine cytology slides for RNA-based testing