| 1. |
- Menden, MP, et al.
(författare)
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Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen
- 2019
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Ingår i: Nature communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 10:1, s. 2674-
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Tidskriftsartikel (refereegranskat)abstract
- The effectiveness of most cancer targeted therapies is short-lived. Tumors often develop resistance that might be overcome with drug combinations. However, the number of possible combinations is vast, necessitating data-driven approaches to find optimal patient-specific treatments. Here we report AstraZeneca’s large drug combination dataset, consisting of 11,576 experiments from 910 combinations across 85 molecularly characterized cancer cell lines, and results of a DREAM Challenge to evaluate computational strategies for predicting synergistic drug pairs and biomarkers. 160 teams participated to provide a comprehensive methodological development and benchmarking. Winning methods incorporate prior knowledge of drug-target interactions. Synergy is predicted with an accuracy matching biological replicates for >60% of combinations. However, 20% of drug combinations are poorly predicted by all methods. Genomic rationale for synergy predictions are identified, including ADAM17 inhibitor antagonism when combined with PIK3CB/D inhibition contrasting to synergy when combined with other PI3K-pathway inhibitors in PIK3CA mutant cells.
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| 3. |
- Sieberts, SK, et al.
(författare)
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Crowdsourced assessment of common genetic contribution to predicting anti-TNF treatment response in rheumatoid arthritis
- 2016
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Ingår i: Nature communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 7, s. 12460-
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Tidskriftsartikel (refereegranskat)abstract
- Rheumatoid arthritis (RA) affects millions world-wide. While anti-TNF treatment is widely used to reduce disease progression, treatment fails in ∼one-third of patients. No biomarker currently exists that identifies non-responders before treatment. A rigorous community-based assessment of the utility of SNP data for predicting anti-TNF treatment efficacy in RA patients was performed in the context of a DREAM Challenge (http://www.synapse.org/RA_Challenge). An open challenge framework enabled the comparative evaluation of predictions developed by 73 research groups using the most comprehensive available data and covering a wide range of state-of-the-art modelling methodologies. Despite a significant genetic heritability estimate of treatment non-response trait (h2=0.18, P value=0.02), no significant genetic contribution to prediction accuracy is observed. Results formally confirm the expectations of the rheumatology community that SNP information does not significantly improve predictive performance relative to standard clinical traits, thereby justifying a refocusing of future efforts on collection of other data.
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- Alava, Mikko, et al.
(författare)
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Circumspect descent prevails in solving random constraint satisfaction problems
- 2008
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Ingår i: Proceedings of the National Academy of Sciences of the United States of America. - : Proceedings of the National Academy of Sciences. - 0027-8424 .- 1091-6490. ; 105:40, s. 15253-15257
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Tidskriftsartikel (refereegranskat)abstract
- We study the performance of stochastic local search algorithms for random instances of the K-satisfiability (K-SAT) problem. We present a stochastic local search algorithm, ChainSAT, which moves in the energy landscape of a problem instance by never going upwards in energy. ChainSAT is a focused algorithm in the sense that it focuses on variables occurring in unsatisfied clauses. We show by extensive numerical investigations that ChainSAT and other focused algorithms solve large K-SAT instances almost surely in linear time, up to high clause-to-variable ratios a; for example, for K = 4 we observe linear-time performance well beyond the recently postulated clustering and condensation transitions in the solution space. The performance of ChainSAT is a surprise given that by design the algorithm gets trapped into the first local energy minimum it encounters, yet no such minima are encountered. We also study the geometry of the solution space as accessed by stochastic local search algorithms.
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- Sahin, O, et al.
(författare)
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International Multi-Specialty Expert Physician Preoperative Identification of Extranodal Extension n Oropharyngeal Cancer Patients using Computed Tomography: Prospective Blinded Human Inter-Observer Performance Evaluation
- 2024
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Ingår i: medRxiv : the preprint server for health sciences. - : Cold Spring Harbor Laboratory.
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Tidskriftsartikel (refereegranskat)abstract
- BackgroundExtranodal extension (ENE) is an important adverse prognostic factor in oropharyngeal cancer (OPC) and is often employed in therapeutic decision making. Clinician-based determination of ENE from radiological imaging is a difficult task with high inter-observer variability. However, the role of clinical specialty on the determination of ENE has been unexplored.MethodsPre-therapy computed tomography (CT) images for 24 human papillomavirus-positive (HPV+) OPC patients were selected for the analysis; 6 scans were randomly chosen to be duplicated, resulting in a total of 30 scans of which 21 had pathologically-confirmed ENE. 34 expert clinician annotators, comprised of 11 radiologists, 12 surgeons, and 11 radiation oncologists separately evaluated the 30 CT scans for ENE and noted the presence or absence of specific radiographic criteria and confidence in their prediction. Discriminative performance was measured using accuracy, sensitivity, specificity, area under the receiver operating characteristic curve (AUC), and Brier score for each physician. Statistical comparisons of discriminative performance were calculated using Mann Whitney U tests. Significant radiographic factors in correct discrimination of ENE status were determined through a logistic regression analysis. Interobserver agreement was measured using Fleiss’ kappa.ResultsThe median accuracy for ENE discrimination across all specialties was 0.57. There were significant differences between radiologists and surgeons for Brier score (0.33 vs. 0.26), radiation oncologists and surgeons for sensitivity (0.48 vs. 0.69), and radiation oncologists and radiologists/surgeons for specificity (0.89 vs. 0.56). There were no significant differences between specialties for accuracy or AUC. Indistinct capsular contour, nodal necrosis, and nodal matting were significant factors in regression analysis. Fleiss’ kappa was less than 0.6 for all the radiographic criteria, regardless of specialty.ConclusionsDetection of ENE in HPV+OPC patients on CT imaging remains a difficult task with high variability, regardless of clinician specialty. Although some differences do exist between the specialists, they are often minimal. Further research in automated analysis of ENE from radiographic images is likely needed.
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- Arbustini, E, et al.
(författare)
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Interpretation and actionability of genetic variants in cardiomyopathies: a position statement from the European Society of Cardiology Council on cardiovascular genomics
- 2022
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Ingår i: European heart journal. - : Oxford University Press (OUP). - 1522-9645 .- 0195-668X. ; 43:20, s. 1901-
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Tidskriftsartikel (refereegranskat)abstract
- This document describes the contribution of clinical criteria to the interpretation of genetic variants using heritable Mendelian cardiomyopathies as an example. The aim is to assist cardiologists in defining the clinical contribution to a genetic diagnosis and the interpretation of molecular genetic reports. The identification of a genetic variant of unknown or uncertain significance is a limitation of genetic testing, but current guidelines for the interpretation of genetic variants include essential contributions from clinical family screening that can establish a de novo assignment of the variant or its segregation with the phenotype in the family. A partnership between clinicians and patients helps to solve major uncertainties and provides reliable and clinically actionable information.
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| 22. |
- Dan, GA, et al.
(författare)
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Corrigendum
- 2018
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Ingår i: Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology. - : Oxford University Press (OUP). - 1532-2092. ; 20:5, s. 738-738
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Tidskriftsartikel (refereegranskat)
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- Hemingway, H, et al.
(författare)
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The effectiveness and cost-effectiveness of biomarkers for the prioritisation of patients awaiting coronary revascularisation: a systematic review and decision model.
- 2010
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Ingår i: Health Technology Assessment. - : National Coordinating Centre for Health Technology Assessment. - 1366-5278 .- 2046-4924. ; 14:9, s. 1-178
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Tidskriftsartikel (refereegranskat)abstract
- OBJECTIVE: To determine the effectiveness and cost-effectiveness of a range of strategies based on conventional clinical information and novel circulating biomarkers for prioritising patients with stable angina awaiting coronary artery bypass grafting (CABG).DATA SOURCES: MEDLINE and EMBASE were searched from 1966 until 30 November 2008.REVIEW METHODS: We carried out systematic reviews and meta-analyses of literature-based estimates of the prognostic effects of circulating biomarkers in stable coronary disease. We assessed five routinely measured biomarkers and the eight emerging (i.e. not currently routinely measured) biomarkers recommended by the European Society of Cardiology Angina guidelines. The cost-effectiveness of prioritising patients on the waiting list for CABG using circulating biomarkers was compared against a range of alternative formal approaches to prioritisation as well as no formal prioritisation. A decision-analytic model was developed to synthesise data on a range of effectiveness, resource use and value parameters necessary to determine cost-effectiveness. A total of seven strategies was evaluated in the final model.RESULTS: We included 390 reports of biomarker effects in our review. The quality of individual study reports was variable, with evidence of small study (publication) bias and incomplete adjustment for simple clinical information such as age, sex, smoking, diabetes and obesity. The risk of cardiovascular events while on the waiting list for CABG was 3 per 10,000 patients per day within the first 90 days (184 events in 9935 patients with a mean of 59 days at risk). Risk factors associated with an increased risk, and included in the basic risk equation, were age, diabetes, heart failure, previous myocardial infarction and involvement of the left main coronary artery or three-vessel disease. The optimal strategy in terms of cost-effectiveness considerations was a prioritisation strategy employing biomarker information. Evaluating shorter maximum waiting times did not alter the conclusion that a prioritisation strategy with a risk score using estimated glomerular filtration rate (eGFR) was cost-effective. These results were robust to most alternative scenarios investigating other sources of uncertainty. However, the cost-effectiveness of the strategy using a risk score with both eGFR and C-reactive protein (CRP) was potentially sensitive to the cost of the CRP test itself (assumed to be 6 pounds in the base-case scenario).CONCLUSIONS: Formally employing more information in the prioritisation of patients awaiting CABG appears to be a cost-effective approach and may result in improved health outcomes. The most robust results relate to a strategy employing a risk score using conventional clinical information together with a single biomarker (eGFR). The additional prognostic information conferred by collecting the more costly novel circulating biomarker CRP, singly or in combination with other biomarkers, in terms of waiting list prioritisation is unlikely to be cost-effective.
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| 25. |
- Kohonen, P, et al.
(författare)
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A transcriptomics data-driven gene space accurately predicts liver cytopathology and drug-induced liver injury
- 2017
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Ingår i: Nature communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 8, s. 15932-
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Tidskriftsartikel (refereegranskat)abstract
- Predicting unanticipated harmful effects of chemicals and drug molecules is a difficult and costly task. Here we utilize a ‘big data compacting and data fusion’—concept to capture diverse adverse outcomes on cellular and organismal levels. The approach generates from transcriptomics data set a ‘predictive toxicogenomics space’ (PTGS) tool composed of 1,331 genes distributed over 14 overlapping cytotoxicity-related gene space components. Involving ∼2.5 × 108 data points and 1,300 compounds to construct and validate the PTGS, the tool serves to: explain dose-dependent cytotoxicity effects, provide a virtual cytotoxicity probability estimate intrinsic to omics data, predict chemically-induced pathological states in liver resulting from repeated dosing of rats, and furthermore, predict human drug-induced liver injury (DILI) from hepatocyte experiments. Analysing 68 DILI-annotated drugs, the PTGS tool outperforms and complements existing tests, leading to a hereto-unseen level of DILI prediction accuracy.
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| 28. |
- Sahlsten, J, et al.
(författare)
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Application of simultaneous uncertainty quantification for image segmentation with probabilistic deep learning: Performance benchmarking of oropharyngeal cancer target delineation as a use-case
- 2023
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Ingår i: medRxiv : the preprint server for health sciences. - : Cold Spring Harbor Laboratory.
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- BackgroundOropharyngeal cancer (OPC) is a widespread disease, with radiotherapy being a core treatment modality. Manual segmentation of the primary gross tumor volume (GTVp) is currently employed for OPC radiotherapy planning, but is subject to significant interobserver variability. Deep learning (DL) approaches have shown promise in automating GTVp segmentation, but comparative (auto)confidence metrics of these models predictions has not been well-explored. Quantifying instance-specific DL model uncertainty is crucial to improving clinician trust and facilitating broad clinical implementation. Therefore, in this study, probabilistic DL models for GTVp auto-segmentation were developed using large-scale PET/CT datasets, and various uncertainty auto-estimation methods were systematically investigated and benchmarked.MethodsWe utilized the publicly available 2021 HECKTOR Challenge training dataset with 224 co-registered PET/CT scans of OPC patients with corresponding GTVp segmentations as a development set. A separate set of 67 co-registered PET/CT scans of OPC patients with corresponding GTVp segmentations was used for external validation. Two approximate Bayesian deep learning methods, the MC Dropout Ensemble and Deep Ensemble, both with five submodels, were evaluated for GTVp segmentation and uncertainty performance. The segmentation performance was evaluated using the volumetric Dice similarity coefficient (DSC), mean surface distance (MSD), and Hausdorff distance at 95% (95HD). The uncertainty was evaluated using four measures from literature: coefficient of variation (CV), structure expected entropy, structure predictive entropy, and structure mutual information, and additionally with our novelDice-riskmeasure. The utility of uncertainty information was evaluated with the accuracy of uncertainty-based segmentation performance prediction using the Accuracy vs Uncertainty (AvU) metric, and by examining the linear correlation between uncertainty estimates and DSC. In addition, batch-based and instance-based referral processes were examined, where the patients with high uncertainty were rejected from the set. In the batch referral process, the area under the referral curve with DSC (R-DSC AUC) was used for evaluation, whereas in the instance referral process, the DSC at various uncertainty thresholds were examined.ResultsBoth models behaved similarly in terms of the segmentation performance and uncertainty estimation. Specifically, the MC Dropout Ensemble had 0.776 DSC, 1.703 mm MSD, and 5.385 mm 95HD. The Deep Ensemble had 0.767 DSC, 1.717 mm MSD, and 5.477 mm 95HD. The uncertainty measure with the highest DSC correlation was structure predictive entropy with correlation coefficients of 0.699 and 0.692 for the MC Dropout Ensemble and the Deep Ensemble, respectively. The highest AvU value was 0.866 for both models. The best performing uncertainty measure for both models was the CV which had R-DSC AUC of 0.783 and 0.782 for the MC Dropout Ensemble and Deep Ensemble, respectively. With referring patients based on uncertainty thresholds from 0.85 validation DSC for all uncertainty measures, on average the DSC improved from the full dataset by 4.7% and 5.0% while referring 21.8% and 22% patients for MC Dropout Ensemble and Deep Ensemble, respectively.ConclusionWe found that many of the investigated methods provide overall similar but distinct utility in terms of predicting segmentation quality and referral performance. These findings are a critical first-step towards more widespread implementation of uncertainty quantification in OPC GTVp segmentation.
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| 32. |
- Zhou, Junhua, et al.
(författare)
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Somatic mutations of GNA11 and GNAQ in CTNNB1-mutant aldosterone-producing adenomas presenting in puberty, pregnancy or menopause
- 2021
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Ingår i: Nature Genetics. - : Springer Nature. - 1061-4036 .- 1546-1718. ; 53:9, s. 1360-1372
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Tidskriftsartikel (refereegranskat)abstract
- Sequence analysis identifies gain-of-function somatic mutations in GNA11 or GNAQ in CTNNB1-mutant aldosterone-producing adenomas. Most patients with these mutations presented during puberty, pregnancy or menopause, with elevated LHCGR expression. Most aldosterone-producing adenomas (APAs) have gain-of-function somatic mutations of ion channels or transporters. However, their frequency in aldosterone-producing cell clusters of normal adrenal gland suggests a requirement for codriver mutations in APAs. Here we identified gain-of-function mutations in both CTNNB1 and GNA11 by whole-exome sequencing of 3/41 APAs. Further sequencing of known CTNNB1-mutant APAs led to a total of 16 of 27 (59%) with a somatic p.Gln209His, p.Gln209Pro or p.Gln209Leu mutation of GNA11 or GNAQ. Solitary GNA11 mutations were found in hyperplastic zona glomerulosa adjacent to double-mutant APAs. Nine of ten patients in our UK/Irish cohort presented in puberty, pregnancy or menopause. Among multiple transcripts upregulated more than tenfold in double-mutant APAs was LHCGR, the receptor for luteinizing or pregnancy hormone (human chorionic gonadotropin). Transfections of adrenocortical cells demonstrated additive effects of GNA11 and CTNNB1 mutations on aldosterone secretion and expression of genes upregulated in double-mutant APAs. In adrenal cortex, GNA11/Q mutations appear clinically silent without a codriver mutation of CTNNB1.
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