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Bloodstream infections (BSI) are a frequent complication in patients with hematological and oncological diseases. However, the impact of different bacterial species causing BSI and of multiple BSI remains incompletely understood. We performed a retrospective study profiling 637 bacterial BSI episodes in hematological and oncological patients. Based on the 30-day (30d) overall survival (OS), we analyzed different types of multiple BSI and grouped BSI-associated bacteria into clusters followed by further assessment of clinical and infection-related characteristics. We discovered that polymicrobial BSI (different organisms on the first day of a BSI episode) and sequential BSI (another BSI before the respective BSI episode) were associated with a worse 30d OS. Different bacterial groups could be classified into three BSI outcome clusters based on 30d OS: favorable (FAV) including mainly common skin contaminants, Escherichia spp. and Streptococcus spp.; intermediate (INT) including mainly Enterococcus spp., vancomycin-resistant Enterococcus spp., and multidrug-resistant gram-negative bacteria (MDRGN); and adverse (ADV) including MDRGN with an additional carbapenem-resistance (MDRGN+CR). A polymicrobial or sequential BSI especially influenced the outcome in the combination of two INT cluster BSI. The presence of a polymicrobial BSI and the assignment into the BSI outcome clusters were identified as independent risk factors for 30d mortality in a Cox multivariate regression analysis. The assignment to a BSI outcome cluster and the differentiated perspective of multiple BSI open new insights into the prognosis of patients with BSI and should be further validated in other patient cohorts.
As new generations of targeted therapies emerge and tumor genome sequencing discovers increasingly comprehensive mutation repertoires, the functional relationships of mutations to tumor phenotypes remain largely unknown. Here, we measured ex vivo sensitivity of 246 blood cancers to 63 drugs alongside genome, transcriptome, and DNA methylome analysis to understand determinants of drug response. We assembled a primary blood cancer cell encyclopedia data set that revealed disease-specific sensitivities for each cancer. Within chronic lymphocytic leukemia (CLL), responses to 62% of drugs were associated with 2 or more mutations, and linked the B cell receptor (BCR) pathway to trisomy 12, an important driver of CLL. Based on drug responses, the disease could be organized into phenotypic subgroups characterized by exploitable dependencies on BCR, mTOR, or MEK signaling and associated with mutations, gene expression, and DNA methylation. Fourteen percent of CLLs were driven by mTOR signaling in a non–BCR-dependent manner. Multivariate modeling revealed immunoglobulin heavy chain variable gene (IGHV) mutation status and trisomy 12 as the most important modulators of response to kinase inhibitors in CLL. Ex vivo drug responses were associated with outcome. This study overcomes the perception that most mutations do not influence drug response of cancer, and points to an updated approach to understanding tumor biology, with implications for biomarker discovery and cancer care.
New technologies and therapies designed to facilitate development of personalized treatments are rapidly emerging in the field of biomedicine. Strikingly, the goal of personalized medicine refined the concept of therapy by developing cell-based therapies, the so-called “living drugs”. Breakthrough advancements were achieved in this regard in the fields of gene therapy, cell therapy, tissue-engineered products and advanced therapeutic techniques. The Advanced Therapies in Healthcare symposium, organized by the Clinical Research Center Department of Sidra Medicine, in Doha, Qatar (October 2017), brought together world-renowned experts from the fields of oncology, hematology, immunology, inflammation, autoimmune disorders, and stem cells to offer a comprehensive picture of the status of worldwide advanced therapies in both pre-clinical and clinical development, providing insights to the research phase, clinical data and regulatory aspects of these therapies. Highlights of the meeting are provided in this meeting report.
Background: Von Willebrand disease (VWD) is the most common inherent bleeding disorder. Gingival bleeding is a frequently reported symptom of VWD. However, gingival bleeding is also a leading symptom of plaque-induced gingivitis and untreated periodontal disease. In type 1 VWD gingival bleeding was not increased compared to controls. Thus, this study evaluated whether type 2 and 3 VWD determines an increased susceptibility to gingival bleeding in response to the oral biofilm.
Methods: Twenty-four cases and 24 controls matched for age, sex, periodontal diagnosis, number of teeth and smoking were examined hematologically (VWF antigen, VWF activity, factor VIII activity) and periodontally (Gingival Bleeding Index [GBI]), bleeding on probing [BOP], Plaque Control Record [PCR], periodontal inflamed surface area [PISA], vertical probing attachment level).
Results: BOP (VWD: 14.5±10.1%; controls: 12.3±5.3%; p = 0.542) and GBI (VWD: 10.5±9.9%; controls: 8.8±4.8%; p = 0.852) were similar for VWD and controls. Multiple regressions identified female sex, HbA1c, PCR and PISA to be associated with BOP. HbA1c and PCR were associated with GBI. Number of remaining teeth was negatively correlated with BOP and GBI.
Conclusion: Type 2 and 3 VWD are not associated with a more pronounced inflammatory response to the oral biofilm in terms of BOP and GBI.