Targeted Genomic Profiling and Chemotherapy Outcomes in Grade 3 Gastro-Entero-Pancreatic Neuroendocrine Tumors (G3 GEP-NET)

Background: Grade 3 gastro-entero-pancreatic neuroendocrine tumors (G3 GEP-NET) are poorly characterized in terms of molecular features and response to treatments. Methods: Patients with G3 GEP-NET were included if they received capecitabine and temozolomide (CAPTEM) or oxaliplatin with either 5-fluorouracile (FOLFOX) or capecitabine (XELOX) as first-line treatment (chemotherapy cohort). G3 NET which successfully undergone next-generation sequencing (NGS) were included in the NGS cohort. Results: In total, 49 patients were included in the chemotherapy cohort: 15 received CAPTEM and 34 received FOLFOX/XELOX. Objective response rate (ORR), progression-free survival (PFS), and overall survival (OS) were 42.9%, 9.0 months, and 33.6 months, respectively. Calculating a Ki67 cutoff using ROC curve analysis, tumors with Ki67 ≥ 40% had lower ORR (51.2% vs. 0%; p = 0.007) and shorter PFS (10.6 months vs. 4.4 months; p < 0.001) and OS (49.4 months vs. 10.0 months; p = 0.023). In patients who received FOLFOX/XELOX as a first-line treatment, ORR, PFS, and OS were 38.2%, 7.9 months, and 30.0 months, respectively. In the NGS cohort (N = 13), the most mutated genes were DAXX/ATRX (N = 5, 38%), MEN1 (N = 4, 31%), TP53 (N = 4, 31%), AKT1 (N = 2, 15%), and PIK3CA (N = 1, 8%). Conclusions: FOLFOX/XELOX chemotherapy is active as the first-line treatment of patients with G3 GEP-NET. The mutational landscape of G3 NET is more similar to well-differentiated NETs than NECs

Prognostic impact of the cumulative dose and dose intensity of everolimus in patients with pancreatic neuroendocrine tumors

The aim of this work is to assess if cumulative dose (CD) and dose intensity (DI) of everolimus may affect survival of advanced pancreatic neuroendocrine tumors (PNETs) patients. One hundred and sixteen patients (62 males and 54 females, median age 55\ua0years) with advanced PNETs were treated with everolimus for 653\ua0months. According to a Receiver operating characteristics (ROC) analysis, patients were stratified into two groups, with CD\ua0 64\ua03000\ua0mg (Group A; n\ua0=\ua068) and CD\ua0>\ua03000\ua0mg (Group B; n\ua0=\ua048). The response rate and toxicity were comparable in the two groups. However, patients in group A experienced more dose modifications than patients in group B. Median OS was 24\ua0months in Group A while in Group B it was not reached (HR: 26.9; 95% CI: 11.0-76.7; P\ua0<\ua00.0001). Patients who maintained a DI higher than 9\ua0mg/day experienced a significantly longer OS and experienced a trend to higher response rate. Overall, our study results showed that both CD and DI of everolimus play a prognostic role for patients with advanced PNETs treated with everolimus. This should prompt efforts to continue everolimus administration in responsive patients up to at least 3000\ua0mg despite delays or temporary interruptions

Baseline BMI and BMI variation during first line pembrolizumab in NSCLC patients with a PD-L1 expression >= 50%: a multicenter study with external validation

Background The association between obesity and outcomes in patients receiving programmed death-1/ programmed death ligand-1 (PD-L1) checkpoint inhibitors has already been confirmed in pre-treated non-small cell lung cancer (NSCLC) patients, regardless of PD-L1 tumor expression. Methods We present the outcomes analysis according to baseline body mass index (BMI) and BMI variation in a large cohort of metastatic NSCLC patients with a PD-L1 expression ≥50%, receiving first line pembrolizumab. We also evaluated a control cohort of metastatic NSCLC patients treated with first line platinum-based chemotherapy. Normal weight was set as control group. Results 962 patients and 426 patients were included in the pembrolizumab and chemotherapy cohorts, respectively. Obese patients had a significantly higher objective response rate (ORR) (OR=1.61 (95% CI: 1.04– 2.50)) in the pembrolizumab cohort, while overweight patients had a significantly lower ORR (OR=0.59 (95% CI: 0.37–0.92)) within the chemotherapy cohort. Obese patients had a significantly longer progression-free survival (PFS) (HR=0.61 (95% CI: 0.45–0.82)) in the pembrolizumab cohort. Conversely, they had a significantly shorter PFS in the chemotherapy cohort (HR=1.27 (95% CI: 1.01–1.60)). Obese patients had a significantly longer overall survival (OS) within the pembrolizumab cohort (HR=0.70 (95% CI: 0.49–0.99)), while no significant differences according to baseline BMI were found in the chemotherapy cohort. BMI variation significantly affected ORR, PFS and OS in both the pembrolizumab and the chemotherapy cohorts. Conclusions Baseline obesity is associated to significantly improved ORR, PFS and OS in metastatic NSCLC patients with a PD-L1 expression of ≥50%, receiving first line pembrolizumab, but not among patients treated with chemotherapy. BMI variation is also significantly related to clinical outcomes

The Ontology for Biomedical Investigations

The Ontology for Biomedical Investigations (OBI) is an ontology that provides terms with precisely defined meanings to describe all aspects of how investigations in the biological and medical domains are conducted. OBI re-uses ontologies that provide a representation of biomedical knowledge from the Open Biological and Biomedical Ontologies (OBO) project and adds the ability to describe how this knowledge was derived. We here describe the state of OBI and several applications that are using it, such as adding semantic expressivity to existing databases, building data entry forms, and enabling interoperability between knowledge resources. OBI covers all phases of the investigation process, such as planning, execution and reporting. It represents information and material entities that participate in these processes, as well as roles and functions. Prior to OBI, it was not possible to use a single internally consistent resource that could be applied to multiple types of experiments for these applications. OBI has made this possible by creating terms for entities involved in biological and medical investigations and by importing parts of other biomedical ontologies such as GO, Chemical Entities of Biological Interest (ChEBI) and Phenotype Attribute and Trait Ontology (PATO) without altering their meaning. OBI is being used in a wide range of projects covering genomics, multi-omics, immunology, and catalogs of services. OBI has also spawned other ontologies (Information Artifact Ontology) and methods for importing parts of ontologies (Minimum information to reference an external ontology term (MIREOT)). The OBI project is an open cross-disciplinary collaborative effort, encompassing multiple research communities from around the globe. To date, OBI has created 2366 classes and 40 relations along with textual and formal definitions. The OBI Consortium maintains a web resource (http://obi-ontology.org) providing details on the people, policies, and issues being addressed in association with OBI. The current release of OBI is available at http://purl.obolibrary.org/obo/obi.owl