Combenefit: an interactive platform for the analysis and visualization of drug combinations.

Motivation: Many drug combinations are routinely assessed to identify synergistic interactions in the attempt to develop novel treatment strategies. Appropriate software is required to analyze the results of these studies. Results: We present Combenefit, new free software tool that enables the visualization, analysis and quantification of drug combination effects in terms of synergy and/or antagonism. Data from combinations assays can be processed using classical Synergy models (Loewe, Bliss, HSA), as single experiments or in batch for High Throughput Screens. This user-friendly tool provides laboratory scientists with an easy and systematic way to analyze their data. The companion package provides bioinformaticians with critical implementations of routines enabling the processing of combination data. Availability and Implementation: Combenefit is provided as a Matlab package but also as standalone software for Windows (http://sourceforge.net/projects/combenefit/). Contact: [email protected]. Supplementary information:Supplementary data are available at Bioinformatics online

Choice of Frontline Tyrosine-Kinase Inhibitor and Early Events in Very Elderly Patients With Chronic Myeloid Leukemia in Chronic Phase: A "Campus CML" Study

Objectives: The study aimed to evaluate the utilization of frontline TKI therapy in a large cohort of elderly CP-CML patients. Methods: A retrospective analysis was conducted on 332 CP-CML patients aged 75 years or older among 1929 diagnosed from January 2012 to December 2019 followed at 36 participating Hematology Centers involved in the "Campus CML" project. Results: Among the patients analyzed, 85.8% received imatinib (IM) while 14.2% received second-generation TKIs (2G-TKI), 59.5% dasatinib, and 40.5% nilotinib. Most patients initiated IM at standard dose (67.3%) while 32.7% at reduced dose. A similar trend was observed with 2G-TKIs. The cumulative incidence of permanent TKI discontinuation at 12 months was 28.4%, primarily due to primary resistance (10.1%) and extra-hematologic toxicity (9.5%), with no significant difference between IM and 2G-TKI groups. Following the introduction of generic IM in Italy in 2018, IM usage increased significantly compared with 2G-TKIs. Conclusions: IM was in our Centers the preferred frontline therapy for older CP-CML patients, with increasing utilization after the introduction of generic formulations. However, 2G-TKIs are still used in a substantial proportion of patients, suggesting individualized physician assessments regarding patient suitability and expectations. Further investigation is needed to assess efficacy and safety of reduced TKI doses in this patient population

Retinoic acid-induced 1 gene haploinsufficiency alters lipid metabolism and causes autophagy defects in Smith-Magenis syndrome

Smith-Magenis syndrome (SMS) is a neurodevelopmental disorder characterized by cognitive and behavioral symptoms, obesity, and sleep disturbance, and no therapy has been developed to alleviate its symptoms or delay disease onset. SMS occurs due to haploinsufficiency of the retinoic acid-induced-1 (RAI1) gene caused by either chromosomal deletion (SMS-del) or RAI1 missense/nonsense mutation. The molecular mechanisms underlying SMS are unknown. Here, we generated and characterized primary cells derived from four SMS patients (two with SMS-del and two carrying RAI1 point mutations) and four control subjects to investigate the pathogenetic processes underlying SMS. By combining transcriptomic and lipidomic analyses, we found altered expression of lipid and lysosomal genes, deregulation of lipid metabolism, accumulation of lipid droplets, and blocked autophagic flux. We also found that SMS cells exhibited increased cell death associated with the mitochondrial pathology and the production of reactive oxygen species. Treatment with N-acetylcysteine reduced cell death and lipid accumulation, which suggests a causative link between metabolic dyshomeostasis and cell viability. Our results highlight the pathological processes in human SMS cells involving lipid metabolism, autophagy defects and mitochondrial dysfunction and suggest new potential therapeutic targets for patient treatment

Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen

The effectiveness of most cancer targeted therapies is short-lived. Tumors often develop resistance that might be overcome with drug combinations. However, the number of possible combinations is vast, necessitating data-driven approaches to find optimal patient-specific treatments. Here we report AstraZeneca's large drug combination dataset, consisting of 11,576 experiments from 910 combinations across 85 molecularly characterized cancer cell lines, and results of a DREAM Challenge to evaluate computational strategies for predicting synergistic drug pairs and biomarkers. 160 teams participated to provide a comprehensive methodological development and benchmarking. Winning methods incorporate prior knowledge of drug-target interactions. Synergy is predicted with an accuracy matching biological replicates for >60% of combinations. However, 20% of drug combinations are poorly predicted by all methods. Genomic rationale for synergy predictions are identified, including ADAM17 inhibitor antagonism when combined with PIK3CB/D inhibition contrasting to synergy when combined with other PI3K-pathway inhibitors in PIK3CA mutant cells

Frequency of left ventricular hypertrophy in non-valvular atrial fibrillation

Left ventricular hypertrophy (LVH) is significantly related to adverse clinical outcomes in patients at high risk of cardiovascular events. In patients with atrial fibrillation (AF), data on LVH, that is, prevalence and determinants, are inconsistent mainly because of different definitions and heterogeneity of study populations. We determined echocardiographic-based LVH prevalence and clinical factors independently associated with its development in a prospective cohort of patients with non-valvular (NV) AF. From the "Atrial Fibrillation Registry for Ankle-brachial Index Prevalence Assessment: Collaborative Italian Study" (ARAPACIS) population, 1,184 patients with NVAF (mean age 72 \ub1 11 years; 56% men) with complete data to define LVH were selected. ARAPACIS is a multicenter, observational, prospective, longitudinal on-going study designed to estimate prevalence of peripheral artery disease in patients with NVAF. We found a high prevalence of LVH (52%) in patients with NVAF. Compared to those without LVH, patients with AF with LVH were older and had a higher prevalence of hypertension, diabetes, and previous myocardial infarction (MI). A higher prevalence of ankle-brachial index 640.90 was seen in patients with LVH (22 vs 17%, p = 0.0392). Patients with LVH were at significantly higher thromboembolic risk, with CHA2DS2-VASc 652 seen in 93% of LVH and in 73% of patients without LVH (p <0.05). Women with LVH had a higher prevalence of concentric hypertrophy than men (46% vs 29%, p = 0.0003). Logistic regression analysis demonstrated that female gender (odds ratio [OR] 2.80, p <0.0001), age (OR 1.03 per year, p <0.001), hypertension (OR 2.30, p <0.001), diabetes (OR 1.62, p = 0.004), and previous MI (OR 1.96, p = 0.001) were independently associated with LVH. In conclusion, patients with NVAF have a high prevalence of LVH, which is related to female gender, older age, hypertension, and previous MI. These patients are at high thromboembolic risk and deserve a holistic approach to cardiovascular prevention

Enhanced triacylglycerol catabolism by carboxylesterase 1 promotes aggressive colorectal carcinoma

The ability to adapt to low-nutrient microenvironments is essential for tumor cell survival and progression in solid cancers, such as colorectal carcinoma (CRC). Signaling by the NF-κB transcription factor pathway associates with advanced disease stages and shorter survival in patients with CRC. NF-κB has been shown to drive tumor-promoting inflammation, cancer cell survival, and intestinal epithelial cell (IEC) dedifferentiation in mouse models of CRC. However, whether NF-κB affects the metabolic adaptations that fuel aggressive disease in patients with CRC is unknown. Here, we identified carboxylesterase 1 (CES1) as an essential NF-κB–regulated lipase linking obesity-associated inflammation with fat metabolism and adaptation to energy stress in aggressive CRC. CES1 promoted CRC cell survival via cell-autonomous mechanisms that fuel fatty acid oxidation (FAO) and prevent the toxic build-up of triacylglycerols. We found that elevated CES1 expression correlated with worse outcomes in overweight patients with CRC. Accordingly, NF-κB drove CES1 expression in CRC consensus molecular subtype 4 (CMS4), which is associated with obesity, stemness, and inflammation. CES1 was also upregulated by gene amplifications of its transcriptional regulator HNF4A in CMS2 tumors, reinforcing its clinical relevance as a driver of CRC. This subtype-based distribution and unfavorable prognostic correlation distinguished CES1 from other intracellular triacylglycerol lipases and suggest CES1 could provide a route to treat aggressive CRC

Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen

The effectiveness of most cancer targeted therapies is short-lived. Tumors often develop resistance that might be overcome with drug combinations. However, the number of possible combinations is vast, necessitating data-driven approaches to find optimal patient-specific treatments. Here we report AstraZeneca’s large drug combination dataset, consisting of 11,576 experiments from 910 combinations across 85 molecularly characterized cancer cell lines, and results of a DREAM Challenge to evaluate computational strategies for predicting synergistic drug pairs and biomarkers. 160 teams participated to provide a comprehensive methodological development and benchmarking. Winning methods incorporate prior knowledge of drug-target interactions. Synergy is predicted with an accuracy matching biological replicates for >60% of combinations. However, 20% of drug combinations are poorly predicted by all methods. Genomic rationale for synergy predictions are identified, including ADAM17 inhibitor antagonism when combined with PIK3CB/D inhibition contrasting to synergy when combined with other PI3K-pathway inhibitors in PIK3CA mutant cells.Peer reviewe

Spotlight on landmark oncology trials: the latest evidence and novel trial designs

The era of precision oncology is marked with prominent successes in the therapy of advanced soft tissue sarcomas, breast cancer, ovarian cancer and haematological neoplasms, among others. Moreover, recent trials of immune checkpoint inhibitors in melanoma, non-small cell lung carcinoma, and head and neck cancers have significantly influenced the therapeutic landscape by providing promising evidence for immunotherapy efficacy in the adjuvant setting in high-risk locoregional disease. To speed up the introduction of targeted therapy for cancer patients, novel phase II trials are being designed, and may likely form the basis for the 'landmark trials' of the future. A special article collection in BMC Medicine, "Spotlight on landmark oncology trials", features articles from invited experts on recent clinical practice-changing trials

Método híbrido para categorización de texto basado en aprendizaje y reglas

En este artículo se presenta un nuevo método híbrido de categorización automática de texto, que combina un algoritmo de aprendizaje computacional, que permite construir un modelo base de clasificación sin mucho esfuerzo a partir de un corpus etiquetado, con un sistema basado en reglas en cascada que se emplea para filtrar y reordenar los resultados de dicho modelo base. El modelo puede afinarse añadiendo reglas específicas para aquellas categorías difíciles que no se han entrenado de forma satisfactoria. Se describe una implementación realizada mediante el algoritmo kNN y un lenguaje básico de reglas basado en listas de términos que aparecen en el texto a clasificar. El sistema se ha evaluado en diferentes escenarios incluyendo el corpus de noticias Reuters-21578 para comparación con otros enfoques, y los modelos IPTC y EUROVOC. Los resultados demuestran que el sistema obtiene una precisión y cobertura comparables con las de los mejores métodos del estado del arte