Risk stratification and treatment decisions for leukemia patients are regularly based on clinical markers determined at diagnosis, while measurements on system dynamics are often neglected. However, ...there is increasing evidence that linking quantitative time-course information to disease outcomes can improve the predictions for patient-specific treatment responses. We designed a synthetic experiment simulating response kinetics of 5,000 patients to compare different computational methods with respect to their ability to accurately predict relapse for chronic and acute myeloid leukemia treatment. Technically, we used clinical reference data to first fit a model and then generate de novo model simulations of individual patients' time courses for which we can systematically tune data quality (i.e. measurement error) and quantity (i.e. number of measurements). Based hereon, we compared the prediction accuracy of three different computational methods, namely mechanistic models, generalized linear models, and deep neural networks that have been fitted to the reference data. Reaching prediction accuracies between 60 and close to 100%, our results indicate that data quality has a higher impact on prediction accuracy than the specific choice of the particular method. We further show that adapted treatment and measurement schemes can considerably improve the prediction accuracy by 10 to 20%. Our proof-of-principle study highlights how computational methods and optimized data acquisition strategies can improve risk assessment and treatment of leukemia patients.
Full text
Available for:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
The transfer of new insights from basic or clinical research into clinical routine is usually a lengthy and time-consuming process. Conversely, there are still many barriers to directly provide and ...use routine data in the context of basic and clinical research. In particular, no coherent software solution is available that allows a convenient and immediate bidirectional transfer of data between concrete treatment contexts and research settings. Here, we present a generic framework that integrates health data (e.g., clinical, molecular) and computational analytics (e.g., model predictions, statistical evaluations, visualizations) into a clinical software solution which simultaneously supports both patient-specific healthcare decisions and research efforts, while also adhering to the requirements for data protection and data quality. Specifically, our work is based on a recently established generic data management concept, for which we designed and implemented a web-based software framework that integrates data analysis, visualization as well as computer simulation and model prediction with audit trail functionality and a regulation-compliant pseudonymization service. Within the front-end application, we established two tailored views: a clinical (i.e., treatment context) perspective focusing on patient-specific data visualization, analysis and outcome prediction and a research perspective focusing on the exploration of pseudonymized data. We illustrate the application of our generic framework by two use-cases from the field of haematology/oncology. Our implementation demonstrates the feasibility of an integrated generation and backward propagation of data analysis results and model predictions at an individual patient level into clinical decision-making processes while enabling seamless integration into a clinical information system or an electronic health record.
Risk stratification and treatment decisions for leukemia patients are regularly based on clinical markers determined at diagnosis, while measurements on system dynamics are often neglected. However, ...there is increasing evidence that linking quantitative time-course information to disease outcomes can improve the predictions for patient-specific treatment responses. We designed a synthetic experiment simulating response kinetics of 5,000 patients to compare different computational methods with respect to their ability to accurately predict relapse for chronic and acute myeloid leukemia treatment. Technically, we used clinical reference data to first fit a model and then generate de novo model simulations of individual patients' time courses for which we can systematically tune data quality (i.e. measurement error) and quantity (i.e. number of measurements). Based hereon, we compared the prediction accuracy of three different computational methods, namely mechanistic models, generalized linear models, and deep neural networks that have been fitted to the reference data. Reaching prediction accuracies between 60 and close to 100%, our results indicate that data quality has a higher impact on prediction accuracy than the specific choice of the particular method. We further show that adapted treatment and measurement schemes can considerably improve the prediction accuracy by 10 to 20%. Our proof-of-principle study highlights how computational methods and optimized data acquisition strategies can improve risk assessment and treatment of leukemia patients.
Full text
Available for:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Reverse transcription quantitative PCR (RT-qPCR) with intercalating dyes is one of the main techniques to assess gene expression levels used in basic and applied research as well as in diagnostics. ...However, primer design for RT-qPCR can be complex due to the high demands on primer quality. Primers are best placed on exon junctions, should avoid polymorphic regions, be specific to the target transcripts and also prevent genomic amplification accurately, among others. Current software tools manage to meet all the necessary criteria only insufficiently. Here, we present ExonSurfer, a novel, user-friendly web-tool for qPCR primer design. ExonSurfer combines the different steps of the primer design process, encompassing target selection, specificity and self-complementarity assessment, and the avoidance of issues arising from polymorphisms. Amplification of potentially contaminating genomic DNA is avoided by designing primers on exon-exon junctions, moreover, a genomic alignment is performed to filter the primers accordingly and inform the user of any predicted interaction. In order to test the whole performance of the application, we designed primer pairs for 26 targets and checked both primer efficiency, amplicon melting temperature and length and confirmed the targeted amplicon by Sanger sequencing. Most of the tested primers accurately and selectively amplified the corresponding targets. ExonSurfer offers a comprehensive end-to-end primer design, guaranteeing transcript-specific amplification. The user interface is intuitive, providing essential specificity and amplicon details. The tool can also be used by command line and the source code is available. Overall, we expect ExonSurfer to facilitate RT-qPCR set-up for researchers in many fields.
Full text
Available for:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
RNA interference (RNAi) can be induced by intracellular expression of a short hairpin RNA (shRNA). Processing of the shRNA requires the RNaseIII-like Dicer enzyme to remove the loop and to release ...the biologically active small interfering RNA (siRNA). Dicer is also involved in microRNA (miRNA) processing to liberate the mature miRNA duplex, but recent studies indicate that miR-451 is not processed by Dicer. Instead, this miRNA is processed by the Argonaute 2 (Ago2) protein, which also executes the subsequent cleavage of a complementary mRNA target. Interestingly, shRNAs that structurally resemble miR-451 can also be processed by Ago2 instead of Dicer. The key determinant of these "AgoshRNA" molecules is a relatively short basepaired stem, which avoids Dicer recognition and consequently allows alternative processing by Ago2. AgoshRNA processing yields a single active RNA strand, whereas standard shRNAs produce a duplex with guide and passenger strands and the latter may cause adverse off-target effects. In this study, we converted previously tested active anti-HIV-1 shRNA molecules into AgoshRNA. We tested several designs that could potentially improve AgoshRNA activity, including extension of the complementarity between the guide strand and the mRNA target and reduction of the thermodynamic stability of the hairpins. We demonstrate that active AgoshRNAs can be generated. However, the RNAi activity is reduced compared to the matching shRNAs. Despite reduced RNAi activity, comparison of an active AgoshRNA and the matching shRNA in a sensitive cell toxicity assay revealed that the AgoshRNA is much less toxic.
Full text
Available for:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Short hairpin RNAs (shRNAs) are widely used for gene knockdown by inducing the RNA interference (RNAi) mechanism, both for research and therapeutic purposes. The shRNA precursor is processed by the ...RNase III-like enzyme Dicer into biologically active small interfering RNA (siRNA). This effector molecule subsequently targets a complementary mRNA for destruction via the Argonaute 2 (AGO2) complex. The cellular role of Dicer concerns the processing of pre-miRNAs into mature microRNA (miRNA). Recently, a non-canonical pathway was reported for the biogenesis of miR-451, which bypasses Dicer and is processed instead by the slicer activity of AGO2, followed by the regular AGO2-mediated mRNA targeting step. Interestingly, shRNA designs that are characterized by a relatively short basepaired stem also bypass Dicer to be processed by AGO2. We named this design AgoshRNA as these molecules depend on AGO2 both for processing and silencing activity. In this study, we investigated diverse mechanistic aspects of this new class of AgoshRNA molecules. We probed the requirements for AGO2-mediated processing of AgoshRNAs by modification of the proposed cleavage site in the hairpin. We demonstrate by deep sequencing that AGO2-processed AgoshRNAs produce RNA effector molecules with more discrete ends than the products of the regular shRNA design. Furthermore, we tested whether trimming and tailing occurs upon AGO2-mediated processing of AgoshRNAs, similar to what has been described for miR-451. Finally, we tested the prediction that AgoshRNA activity, unlike that of regular shRNAs, is maintained in Dicer-deficient cell types. These mechanistic insights could aid in the design of optimised AgoshRNA tools and therapeutics.
Full text
Available for:
BFBNIB, GIS, IJS, KISLJ, NUK, PNG, UL, UM, UPUK
Purpose
To assess how the current practice of newborn screening (NBS) for homocystinurias compares with published recommendations.
Methods
Twenty‐two of 32 NBS programmes from 18 countries screened ...for at least one form of homocystinuria. Centres provided pseudonymised NBS data from patients with cystathionine beta‐synthase deficiency (CBSD, n = 19), methionine adenosyltransferase I/III deficiency (MATI/IIID, n = 28), combined remethylation disorder (cRMD, n = 56) and isolated remethylation disorder (iRMD), including methylenetetrahydrofolate reductase deficiency (MTHFRD) (n = 8). Markers and decision limits were converted to multiples of the median (MoM) to allow comparison between centres.
Results
NBS programmes, algorithms and decision limits varied considerably. Only nine centres used the recommended second‐tier marker total homocysteine (tHcy). The median decision limits of all centres were ≥ 2.35 for high and ≤ 0.44 MoM for low methionine, ≥ 1.95 for high and ≤ 0.47 MoM for low methionine/phenylalanine, ≥ 2.54 for high propionylcarnitine and ≥ 2.78 MoM for propionylcarnitine/acetylcarnitine. These decision limits alone had a 100%, 100%, 86% and 84% sensitivity for the detection of CBSD, MATI/IIID, iRMD and cRMD, respectively, but failed to detect six individuals with cRMD. To enhance sensitivity and decrease second‐tier testing costs, we further adapted these decision limits using the data of 15 000 healthy newborns.
Conclusions
Due to the favorable outcome of early treated patients, NBS for homocystinurias is recommended. To improve NBS, decision limits should be revised considering the population median. Relevant markers should be combined; use of the postanalytical tools offered by the CLIR project (Collaborative Laboratory Integrated Reports, which considers, for example, birth weight and gestational age) is recommended. tHcy and methylmalonic acid should be implemented as second‐tier markers.
Full text
Available for:
FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
RNA interference (RNAi) can be induced by intracellular expression of a short hairpin RNA (shRNA). Processing of the shRNA requires the RNaseIII-like Dicer enzyme to remove the loop and to release ...the biologically active small interfering RNA (siRNA). Dicer is also involved in microRNA (miRNA) processing to liberate the mature miRNA duplex, but recent studies indicate that miR-451 is not processed by Dicer. Instead, this miRNA is processed by the Argonaute 2 (Ago2) protein, which also executes the subsequent cleavage of a complementary mRNA target. Interestingly, shRNAs that structurally resemble miR-451 can also be processed by Ago2 instead of Dicer. The key determinant of these "AgoshRNA" molecules is a relatively short basepaired stem, which avoids Dicer recognition and consequently allows alternative processing by Ago2. AgoshRNA processing yields a single active RNA strand, whereas standard shRNAs produce a duplex with guide and passenger strands and the latter may cause adverse off-target effects. In this study, we converted previously tested active anti-HIV-1 shRNA molecules into AgoshRNA. We tested several designs that could potentially improve AgoshRNA activity, including extension of the complementarity between the guide strand and the mRNA target and reduction of the thermodynamic stability of the hairpins. We demonstrate that active AgoshRNAs can be generated. However, the RNAi activity is reduced compared to the matching shRNAs. Despite reduced RNAi activity, comparison of an active AgoshRNA and the matching shRNA in a sensitive cell toxicity assay revealed that the AgoshRNA is much less toxic.
Full text
Available for:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
PDF
