Implementing a Functional Precision Medicine Tumor Board for Acute Myeloid Leukemia

We generated ex vivo drug-response and multiomics profi ling data for a prospective series of 252 samples from 186 patients with acute myeloid leukemia (AML). A functional precision medicine tumor board (FPMTB) integrated clinical, molecular, and functional data for application in clinical treatment decisions. Actionable drugs were found for 97% of patients with AML, and the recommendations were clinically implemented in 37 relapsed or refractory patients. We report a 59% objective response rate for the individually tailored therapies, including 13 complete responses, as well as bridging five patients with AML to allogeneic hematopoietic stem cell transplantation. Data integration across all cases enabled the identifi cation of drug response biomarkers, such as the association of IL15 overexpression with resistance to FLT3 inhibitors. Integration of molecular profi ling and large-scale drug response data across many patients will enable continuous improvement of the FPMTB recommendations, providing a paradigm for individualized implementation of functional precision cancer medicine. SIGNIFICANCE: Oncogenomics data can guide clinical treatment decisions, but often such data are neither actionable nor predictive. Functional ex vivo drug testing contributes signifi cant additional, clinically actionable therapeutic insights for individual patients with AML. Such data can be generated in four days, enabling rapid translation through FPMTB.Peer reviewe

Implementing a Functional Precision Medicine Tumor Board for Acute Myeloid Leukemia

We generated ex vivo drug-response and multiomics profi ling data for a prospective series of 252 samples from 186 patients with acute myeloid leukemia (AML). A functional precision medicine tumor board (FPMTB) integrated clinical, molecular, and functional data for application in clinical treatment decisions. Actionable drugs were found for 97% of patients with AML, and the recommendations were clinically implemented in 37 relapsed or refractory patients. We report a 59% objective response rate for the individually tailored therapies, including 13 complete responses, as well as bridging five patients with AML to allogeneic hematopoietic stem cell transplantation. Data integration across all cases enabled the identifi cation of drug response biomarkers, such as the association of IL15 overexpression with resistance to FLT3 inhibitors. Integration of molecular profi ling and large-scale drug response data across many patients will enable continuous improvement of the FPMTB recommendations, providing a paradigm for individualized implementation of functional precision cancer medicine. SIGNIFICANCE: Oncogenomics data can guide clinical treatment decisions, but often such data are neither actionable nor predictive. Functional ex vivo drug testing contributes signifi cant additional, clinically actionable therapeutic insights for individual patients with AML. Such data can be generated in four days, enabling rapid translation through FPMTB.Peer reviewe

Genomilääketieteen sovelluksia sairauksien hoidossa

Teema : Genomitieto. English summar

Implementing a Functional Precision Medicine Tumor Board for Acute Myeloid Leukemia

We generated ex vivo drug-response and multiomics profiling data for a prospective series of 252 samples from 186 patients with acute myeloid leukemia (AML). A functional precision medicine tumor board (FPMTB) integrated clinical, molecular, and functional data for application in clinical treatment decisions. Actionable drugs were found for 97% of patients with AML, and the recommendations were clinically implemented in 37 relapsed or refractory patients. We report a 59% objective response rate for the individually tailored therapies, including 13 complete responses, as well as bridging five patients with AML to allogeneic hematopoietic stem cell transplantation. Data integration across all cases enabled the identification of drug response biomarkers, such as the association of IL15 overexpression with resistance to FLT3 inhibitors. Integration of molecular profiling and large-scale drug response data across many patients will enable continuous improvement of the FPMTB recommendations, providing a paradigm for individualized implementation of functional precision cancer medicine. Significance: Oncogenomics data can guide clinical treatment decisions, but often such data are neither actionable nor predictive. Functional ex vivo drug testing contributes significant additional, clinically actionable therapeutic insights for individual patients with AML. Such data can be generated in four days, enabling rapid translation through FPMTB

Ex vivo venetoclax sensitivity testing predicts treatment response in acute myeloid leukemia

Peer reviewe

Antipsychotic medications and sleep problems in patients with schizophrenia

Background: Sleep problems are common and related to a worse quality of life in patients with schizophrenia. Almost all patients with schizophrenia use antipsychotic medications, which usually increase sleep. Still, the differences in subjective sleep outcomes between different antipsychotic medications are not entirely clear. Methods: This study assessed 5466 patients with schizophrenia and is part of the nationwide Finnish SUPER study. We examined how the five most common antipsychotic medications (clozapine, olanzapine, quetiapine, aripiprazole, and risperidone) associate with questionnaire-based sleep problems in logistic regression analyses, including head-to-head analyses between different antipsychotic medications. The sleep problems were difficulties initiating sleep, early morning awakenings, fatigue, poor sleep quality, short (≤6 h) and long sleep duration (≥10 h). Results: The average number of antipsychotic medications was 1.59 per patient. Clozapine was associated with long sleep duration (49.0 % of clozapine users vs 30.2 % of other patients, OR = 2.05, 95 % CI 1.83–2.30, p < .001). Olanzapine and risperidone were in head-to-head analyses associated with less sleep problems than patients using aripiprazole, quetiapine, or no antipsychotic medication. Aripiprazole and quetiapine were associated with more insomnia symptoms and poorer sleep quality. Patients without antipsychotic medications (N = 159) had poorer sleep quality than patients with antipsychotic use, and short sleep duration was common (21.5 % of patients using antipsychotics vs 7.8 % of patients using antipsychotics, OR = 2.97, 95 % CI 1.98–4.44, p < .001). Conclusions: Prevalence of sleep problems is markedly related to the antipsychotic medication the patient uses. These findings underline the importance of considering and assessing sleep problems when treating schizophrenia patients with antipsychotics