Screening a Targeted Panel of Genes by Next-Generation Sequencing Improves Risk Stratification in Real World Patients with Acute Myeloid Leukemia

Although mutation profiling of defined genes is recommended for classification of acute myeloid leukemia (AML) patients, screening of targeted gene panels using next-generation sequencing (NGS) is not always routinely used as standard of care. The objective of this study was to prospectively assess whether extended molecular monitoring using NGS adds clinical value for risk assessment in real-world AML patients. We analyzed a cohort of 268 newly diagnosed AML patients. We compared the prognostic stratification of our study population according to the European LeukemiaNet recommendations, before and after the incorporation of the extended mutational profile information obtained by NGS. Without access to NGS data, 63 patients (23%) failed to be stratified into risk groups. After NGS data, only 27 patients (10%) failed risk stratification. Another 33 patients were re-classified as adverse-risk patients once the NGS data was incorporated. In total, access to NGS data refined risk assessment for 62 patients (23%). We further compared clinical outcomes with prognostic stratification, and observed unexpected outcomes associated with FLT3 mutations. In conclusion, this study demonstrates the prognostic utility of screening AML patients for multiple gene mutations by NGS and underscores the need for further studies to refine the current risk classification criteria.info:eu-repo/semantics/publishedVersio

Effects of defoliation by the pine processionary moth Thaumetopoea pityocampa on biomass growth of young stands of Pinus pinaster in northern Portugal

Biomass growth models for 13-year-old maritime pine tree stands (Pinus pinaster Ait.) in the north-eastern Portugal were developed and used to analyse the effects of the defoliation by the pine processionary moth, Thaumetopoea pityocampa (Den. & Schiff.) on biomass increment. For the adjustment of the models, 30 individual pine trees were destructively sampled and non-linear models were tested, using the diameter at 10 centimetre height (d0.10), the total height (h), both variables (d0.10+h) and d0.102h as preditors of biomass growth. The results showed that the best predictor was d0.10+h. Application of models to analyse tree biomass after attack by the pine processionary moth showed that the decrease of biomass increment was proportional to the severity of the insect attack, with average values of losses in biomass increment ranging from 37% to 73%, depending on defoliation intensity