Mining Small Routine Clinical Data: A Population Pharmacokinetic Model and Optimal Sampling Times of Capecitabine and its Metabolites

Purpose: The present study was performed to demonstrate that small amounts of routine clinical data allow to generate valuable knowledge. Concretely, the aims of this research were to build a joint population pharmacokinetic model for capecitabine and three of its metabolites (5-DFUR, 5-FU and 5-FUH2) and to determine optimal sampling times for therapeutic drug monitoring. Methods: We used data of 7 treatment cycles of capecitabine in patients with metastatic colorectal cancer. The population pharmacokinetic model was built as a multicompartmental model using NONMEM and was internally validated by visual predictive check. Optimal sampling times were estimated using PFIM 4.0 following D-optimality criterion. Results: The final model was a multicompartmental model which represented the sequential transformations from capecitabine to its metabolites 5-DFUR, 5-FU and 5-FUH2 and was correctly validated. The optimal sampling times were 0.546, 0.892, 1.562, 4.736 and 8 hours after the administration of the drug. For its correct implementation in clinical practice, the values were rounded to 0.5, 1, 1.5, 5 and 8 hours after the administration of the drug. Conclusions: Capecitabine, 5-DFUR, 5-FU and 5-FUH2 can be correctly described by the joint multicompartmental model presented in this work. The aforementioned times are optimal to maximize the information of samples. Useful knowledge can be obtained for clinical practice from small databases

Cervical lymph node metastasis in high-grade transformation of head and neck adenoid cystic carcinoma: a collective international review

Adenoid cystic carcinoma (AdCC) is among the most common malignant tumors of the salivary glands. It is characterized by a prolonged clinical course, with frequent local recurrences, late onset of metastases and fatal outcome. High-grade transformation (HGT) is an uncommon phenomenon among salivary carcinomas and is associated with increased tumor aggressiveness. In AdCC with high-grade transformation (AdCC-HGT), the clinical course deviates from the natural history of AdCC. It tends to be accelerated, with a high propensity for lymph node metastasis. In order to shed light on this rare event and, in particular, on treatment implications, we undertook this review: searching for all published cases of AdCC-HGT. We conclude that it is mandatory to perform elective neck dissection in patients with AdCC-HGT, due to the high risk of lymph node metastases associated with transformation

Omics approaches in pancreatic adenocarcinoma

Pancreatic ductal adenocarcinoma, which represents 80% of pancreatic cancers, is mainly diagnosed when treatment with curative intent is not possible. Consequently, the overall five-year survival rate is extremely dismal—around 5% to 7%. In addition, pancreatic cancer is expected to become the second leading cause of cancer-related death by 2030. Therefore, advances in screening, prevention and treatment are urgently needed. Fortunately, a wide range of approaches could help shed light in this area. Beyond the use of cytological or histological samples focusing in diagnosis, a plethora of new approaches are currently being used for a deeper characterization of pancreatic ductal adenocarcinoma, including genetic, epigenetic, and/or proteo-transcriptomic techniques. Accordingly, the development of new analytical technologies using body fluids (blood, bile, urine, etc.) to analyze tumor derived molecules has become a priority in pancreatic ductal adenocarcinoma due to the hard accessibility to tumor samples. These types of technologies will lead us to improve the outcome of pancreatic ductal adenocarcinoma patients

Trophic Interactions Are Key to Understanding the Effects of Global Change on the Distribution and Functional Role of the Brown Bear

Biotic interactions are expected to influence species' responses to global changes, but they are rarely considered across broad spatial extents. Abiotic factors are thought to operate at larger spatial scales, while biotic factors, such as species interactions, are considered more important at local scales within communities, in part because of the knowledge gap on species interactions at large spatial scales (i.e., the Eltonian shortfall). We assessed, at a continental scale, (i) the importance of biotic interactions, through food webs, on species distributions, and (ii) how biotic interactions under scenarios of climate and land-use change may affect the distribution of the brown bear (Ursus arctos). We built a highly detailed, spatially dynamic, and empirically sampled food web based on the energy contribution of 276 brown bear food species from different taxa (plants, vertebrates, and invertebrates) and their ensemble habitat models at high resolution across Europe. Then, combining energy contribution and predicted habitat of food species, we modelled energy contribution across space and included these layers within Bayesian-based models of the brown bear distribution in Europe. The inclusion of biotic interactions considerably improved our understanding of brown bear distribution at large (continental) scales compared with Bayesian models including only abiotic factors (climate and land use). Predicted future range shifts, which included changes in the distribution of food species, varied greatly when considering various scenarios of change in biotic factors, providing a warning that future indirect climate and land-use change are likely to have strong but highly uncertain impacts on species biogeography. Our study confirmed that advancing our understanding of ecological networks of species interactions will improve future projections of biodiversity change, especially for modelling species distributions and their functional role under climate and land-use change scenarios, which is key for effective conservation of biodiversity and ecosystem services

The Energy Landscape Analysis of Cancer Mutations in Protein Kinases

The growing interest in quantifying the molecular basis of protein kinase activation and allosteric regulation by cancer mutations has fueled computational studies of allosteric signaling in protein kinases. In the present study, we combined computer simulations and the energy landscape analysis of protein kinases to characterize the interplay between oncogenic mutations and locally frustrated sites as important catalysts of allostetric kinase activation. While structurally rigid kinase core constitutes a minimally frustrated hub of the catalytic domain, locally frustrated residue clusters, whose interaction networks are not energetically optimized, are prone to dynamic modulation and could enable allosteric conformational transitions. The results of this study have shown that the energy landscape effect of oncogenic mutations may be allosteric eliciting global changes in the spatial distribution of highly frustrated residues. We have found that mutation-induced allosteric signaling may involve a dynamic coupling between structurally rigid (minimally frustrated) and plastic (locally frustrated) clusters of residues. The presented study has demonstrated that activation cancer mutations may affect the thermodynamic equilibrium between kinase states by allosterically altering the distribution of locally frustrated sites and increasing the local frustration in the inactive form, while eliminating locally frustrated sites and restoring structural rigidity of the active form. The energy landsape analysis of protein kinases and the proposed role of locally frustrated sites in activation mechanisms may have useful implications for bioinformatics-based screening and detection of functional sites critical for allosteric regulation in complex biomolecular systems

Effectiveness of empirical <i>Helicobacter pylori</i> eradication therapy with furazolidone in Russia: results from the European Registry on <i>Helicobacter pylori</i> Management (Hp-EuReg)

Background. First-line therapy does not always provide a high level of Helicobacter pylori eradication due to the increase of H. pylori resistance to antibiotics; therefore, it remains necessary to identify the most effective rescue treatments. The purpose of this study was to evaluate the efficacy and safety of empirical H. pylori furazolidone-containing regimens. Materials and methods. Adult H. pylori infected patients empirically treated with furazolidone-containing eradication regimens were registered in an international, prospective, multicenter non-intervention European registry on H. pylori management (Hp-EuReg). Data were collected at AEG-REDCap e-CRF from 2013 to 2021 and the quality was reviewed. Modified intention-to-treat (mITT) effectiveness analyses were performed. Results. Overall 106 patients received empirical furazolidone-containing therapy in Russia. Furazolidone was prescribed in a sequential scheme along with amoxicillin, clarithromycin and a proton pump inhibitor in 68 (64%) cases, triple regimens were prescribed in 28 (26%) patients and quadruple regimens in 10 (9.4%). Treatment duration of 7 days was assigned to 2 (1.9%) patients, 10-day eradication therapy in case of 80 (75%) and 14 days in 24 (23%) patients. Furazolidone was mainly used in first- (79%) and second-line (21%) regimens. The methods used to diagnose H. pylori infection were: histology (81%), stool antigen test (64%), 13C-urea breath test (6.6%), and rapid urease test (1.9%). The mITT effectiveness of sequential therapy was 100%; 93% with the triple therapy and 75.5% with quadruple therapy. Compliance was reported in 98% of cases. Adverse events were revealed in 5.7% of patients, mostly nausea (3.8%). No serious adverse events were reported. Conclusion. Furazolidone containing eradication regimens appear to be an effective and safe empirical therapy in Russia