Integrating multiple molecular sources into a clinical risk prediction signature by extracting complementary information

Single nucleotide polymorphism (SNP) microarray data. SNP data underlying the finding in this article. (Rdata 50688 kb

The mycotoxin phomoxanthone A disturbs the form and function of the inner mitochondrial membrane.

Mitochondria are cellular organelles with crucial functions in the generation and distribution of ATP, the buffering of cytosolic Ca2+ and the initiation of apoptosis. Compounds that interfere with these functions are termed mitochondrial toxins, many of which are derived from microbes, such as antimycin A, oligomycin A, and ionomycin. Here, we identify the mycotoxin phomoxanthone A (PXA), derived from the endophytic fungus Phomopsis longicolla, as a mitochondrial toxin. We show that PXA elicits a strong release of Ca2+ from the mitochondria but not from the ER. In addition, PXA depolarises the mitochondria similarly to protonophoric uncouplers such as CCCP, yet unlike these, it does not increase but rather inhibits cellular respiration and electron transport chain activity. The respiration-dependent mitochondrial network structure rapidly collapses into fragments upon PXA treatment. Surprisingly, this fragmentation is independent from the canonical mitochondrial fission and fusion mediators DRP1 and OPA1, and exclusively affects the inner mitochondrial membrane, leading to cristae disruption, release of pro-apoptotic proteins, and apoptosis. Taken together, our results suggest that PXA is a mitochondrial toxin with a novel mode of action that might prove a useful tool for the study of mitochondrial ion homoeostasis and membrane dynamics

A concise revised Myeloma Comorbidity Index as a valid prognostic instrument in a large cohort of 801 multiple myeloma patients

With growing numbers of elderly multiple myeloma patients, reliable tools to assess their vulnerability are required. The objective of the analysis herein was to develop and validate an easy to use myeloma risk score (revised Myeloma Comorbidity Index) that allows for risk prediction of overall survival and progression-free survival differences in a large patient cohort. We conducted a comprehensive comorbidity, frailty and disability evaluation in 801 consecutive myeloma patients, including comorbidity risks obtained at diagnosis. The cohort was examined within a training and validation set. Multivariate analysis determined renal, lung and Karnofsky Performance Status impairment, frailty and age as significant risks for overall survival. These were combined in a weighted revised Myeloma Comorbidity Index, allowing for the identification of fit (revised Myeloma Comorbidity Index ≤3 [n=247, 30.8%]), intermediate-fit (revised Myeloma Comorbidity Index 4-6 [n=446, 55.7%]) and frail patients (revised Myeloma Comorbidity Index >6 [n=108, 13.5%]): these subgroups, confirmed validation analysis, showed median overall survival rates of 10.1, 4.4 and 1.2 years, respectively. The revised Myeloma Comorbidity Index was compared to other commonly used comorbidity indices (Charlson Comorbidity Index, Hematopoietic Cell Transplantation-Specific Comorbidity Index, Kaplan-Feinstein Index): if each were divided in risk groups based on 25% and 75% quartiles, highest hazard ratios, best prediction and Brier scores were achieved with the revised Myeloma Comorbidity Index. The advantages of the revised Myeloma Comorbidity Index include its accurate assessment of patients' physical conditions and simple clinical applicability. We propose the revised Myeloma Comorbidity Index to be tested with the "reference" International Myeloma Working Group frailty score in multicenter analyses and future clinical trials. The study was registered at the German Clinical Trials Register (DRKS-00003868)

A concise revised myeloma comorbidity index as a valid prognostic instrument in a large cohort of 801 multiple myeloma patients

With growing numbers of elderly multiple myeloma patients, reliable tools to assess their vulnerability are required. The objective of the analysis herein was to develop and validate an easy to use myeloma risk score (revised Myeloma Comorbidity Index) that allows for risk prediction of overall survival and progression-free survival differences in a large patient cohort. We conducted a comprehensive comorbidity, frailty and disability evaluation in 801 consecutive myeloma patients, including comorbidity risks obtained at diagnosis. The cohort was examined within a training and validation set. Multivariate analysis determined renal, lung and Karnofsky Performance Status impairment, frailty and age as significant risks for overall survival. These were combined in a weighted revised Myeloma Comorbidity Index, allowing for the identification of fit (revised Myeloma Comorbidity Index ≤3 [n=247, 30.8%]), intermediate-fit (revised Myeloma Comorbidity Index 4-6 [n=446, 55.7%]) and frail patients (revised Myeloma Comorbidity Index >6 [n=108, 13.5%]): these subgroups, confirmed via validation analysis, showed median overall survival rates of 10.1, 4.4 and 1.2 years, respectively. The revised Myeloma Comorbidity Index was compared to other commonly used comorbidity indices (Charlson Comorbidity Index, Hematopoietic Cell Transplantation-Specific Comorbidity Index, Kaplan-Feinstein Index): if each were divided in risk groups based on 25% and 75% quartiles, highest hazard ratios, best prediction and Brier scores were achieved with the revised Myeloma Comorbidity Index. The advantages of the revised Myeloma Comorbidity Index include its accurate assessment of patients' physical conditions and simple clinical applicability. We propose the revised Myeloma Comorbidity Index to be tested with the “reference” International Myeloma Working Group frailty score in multicenter analyses and future clinical trials

SNP data from a clinical cohort of acute myeloid leukemia patients

Data sets underlying the findings in the manuscript entitled "Identifying prognostic SNPs in clinical cohorts: complementing univariate analyses by resampling and multivariable modeling" submitted to PLOS ONE

Identifying Prognostic SNPs in Clinical Cohorts: Complementing Univariate Analyses by Resampling and Multivariable Modeling.

Clinical cohorts with time-to-event endpoints are increasingly characterized by measurements of a number of single nucleotide polymorphisms that is by a magnitude larger than the number of measurements typically considered at the gene level. At the same time, the size of clinical cohorts often is still limited, calling for novel analysis strategies for identifying potentially prognostic SNPs that can help to better characterize disease processes. We propose such a strategy, drawing on univariate testing ideas from epidemiological case-controls studies on the one hand, and multivariable regression techniques as developed for gene expression data on the other hand. In particular, we focus on stable selection of a small set of SNPs and corresponding genes for subsequent validation. For univariate analysis, a permutation-based approach is proposed to test at the gene level. We use regularized multivariable regression models for considering all SNPs simultaneously and selecting a small set of potentially important prognostic SNPs. Stability is judged according to resampling inclusion frequencies for both the univariate and the multivariable approach. The overall strategy is illustrated with data from a cohort of acute myeloid leukemia patients and explored in a simulation study. The multivariable approach is seen to automatically focus on a smaller set of SNPs compared to the univariate approach, roughly in line with blocks of correlated SNPs. This more targeted extraction of SNPs results in more stable selection at the SNP as well as at the gene level. Thus, the multivariable regression approach with resampling provides a perspective in the proposed analysis strategy for SNP data in clinical cohorts highlighting what can be added by regularized regression techniques compared to univariate analyses

Therapeutic Drug Monitoring of Posaconazole in Hematology Patients: Experience with a New High-Performance Liquid Chromatography-Based Method▿

Parallel administration of the proton pump inhibitor (PPI) esomeprazole has been shown to decrease oral bioavailability of posaconazole in healthy volunteers. We prospectively analyzed serum samples (n = 59) obtained from hematology patients (n = 27) under posaconazole prophylaxis. Patients treated concomitantly with pantoprazole had significantly lower posaconazole levels than patients without PPI treatment (median levels of 630 μg/liter versus 1,125 μg/liter, respectively). These results suggest that drug monitoring is relevant when posaconazole and pantoprazole are administered concomitantly