ABSTRACT
BACKGROUND: There are emerging reports of Takotsubo syndrome (TTS) in cancer patients treated with immune checkpoint inhibitors (ICIs); however, the association of the two remains uncertain. METHODS: A systematic literature review was performed in the PubMed database and web sources (Google Scholar) according to the Preferred Reporting Items for Systematic reviews and Meta-analyses (PRISMA) guidelines. Case reports/series or studies including cancer patients treated with ICIs and presenting with TTS were considered. RESULTS: Seventeen cases were included in the systematic review. Most patients were males (59%) with median age of 70 years (30-83). Most common tumor types were lung cancer (35%) and melanoma (29%). Most patients were on first-line immunotherapy (35%) and after the first cycle (54%) of treatment. The median time on immunotherapy at the time of TTS presentation was 77 days (1-450). The most used agents were pembrolizumab and the combination of nivolumab-ipilimumab (35%, respectively). Potential stressors were recognized in 12 cases (80%). Six patients (35%) presented with concurrent cardiac complications. Corticosteroids were used in the management of eight patients (50%). Fifteen patients (88%) recovered from TTS, two patients (12%) relapsed, and one patient died. Immunotherapy was reintroduced in five cases (50%). CONCLUSION: TTS may be associated with immunotherapy for cancer. Physicians should be alert for TTS diagnosis in any patient with myocardial infarction-like presentation under treatment with ICIs.
ABSTRACT
Cockayne syndrome (CS) is a DNA repair syndrome characterized by a broad spectrum of clinical manifestations such as neurodegeneration, premature aging, developmental impairment, photosensitivity and other symptoms. Mutations in Cockayne syndrome protein B (CSB) are present in the vast majority of CS patients and in other DNA repair-related pathologies. In the literature, the role of CSB in different DNA repair pathways has been highlighted, however, new CSB functions have been identified in DNA transcription, mitochondrial biology, telomere maintenance and p53 regulation. Herein, we present an overview of identified structural elements and processes that impact on CSB activity and its post-translational modifications, known to balance the different roles of the protein not only during normal conditions but most importantly in stress situations. Moreover, since CSB has been found to be overexpressed in a number of different tumors, its role in cancer is presented and possible therapeutic targeting is discussed.
Subject(s)
Cockayne Syndrome/genetics , DNA Helicases/genetics , DNA Repair Enzymes/genetics , Neoplasms/genetics , Poly-ADP-Ribose Binding Proteins/genetics , Animals , Cockayne Syndrome/metabolism , DNA Damage , DNA Helicases/chemistry , DNA Helicases/metabolism , DNA Repair , DNA Repair Enzymes/chemistry , DNA Repair Enzymes/metabolism , Gene Expression Regulation, Neoplastic , Humans , Models, Molecular , Mutation , Neoplasms/metabolism , Poly-ADP-Ribose Binding Proteins/chemistry , Poly-ADP-Ribose Binding Proteins/metabolism , Protein Conformation , Protein Processing, Post-TranslationalABSTRACT
Computer-vision based measurements of phenotypic variation have implications for crop improvement and food security because they are intrinsically objective. It should be possible therefore to use such approaches to select robust genotypes. However, plants are morphologically complex and identification of meaningful traits from automatically acquired image data is not straightforward. Bespoke algorithms can be designed to capture and/or quantitate specific features but this approach is inflexible and is not generally applicable to a wide range of traits. In this paper, we have used industry-standard computer vision techniques to extract a wide range of features from images of genetically diverse Arabidopsis rosettes growing under non-stimulated conditions, and then used statistical analysis to identify those features that provide good discrimination between ecotypes. This analysis indicates that almost all the observed shape variation can be described by 5 principal components. We describe an easily implemented pipeline including image segmentation, feature extraction and statistical analysis. This pipeline provides a cost-effective and inherently scalable method to parameterise and analyse variation in rosette shape. The acquisition of images does not require any specialised equipment and the computer routines for image processing and data analysis have been implemented using open source software. Source code for data analysis is written using the R package. The equations to calculate image descriptors have been also provided.