A5058904794- Multiple Myeloma Research and Treatments
- Protein Degradation and Inhibitors
- Ubiquitin and proteasome pathways
- Peptidase Inhibition and Analysis
- Acute Myeloid Leukemia Research
- Gene expression and cancer classification
- Bioinformatics and Genomic Networks
- Advanced biosensing and bioanalysis techniques
- vaccines and immunoinformatics approaches
- Genomics and Chromatin Dynamics
- Cutaneous Melanoma Detection and Management
- Analytical Chemistry and Chromatography
- Spectroscopy and Chemometric Analyses
- Melanoma and MAPK Pathways
- Cancer Genomics and Diagnostics
- Myeloproliferative Neoplasms: Diagnosis and Treatment
- BRCA gene mutations in cancer
- Trauma, Hemostasis, Coagulopathy, Resuscitation
- Molecular Biology Techniques and Applications
- Chemokine receptors and signaling
- Retinoids in leukemia and cellular processes
- Hydrology and Drought Analysis
- Glycosylation and Glycoproteins Research
- Cell Image Analysis Techniques
- Food Chemistry and Fat Analysis
Skyline College
2019
Erasmus MC Cancer Institute
2015
Future Diagnostics (Netherlands)
2010-2013
The Netherlands Cancer Institute
2007-2012
Oncode Institute
2012
Delft University of Technology
2005-2012
Unilever (Netherlands)
2004
Women carrying germ-line mutations in BRCA1 are strongly predisposed to developing breast cancers with characteristic features also observed sporadic basal-like cancers. They appear as high-grade tumors high proliferation rates and pushing borders. On the molecular level, they negative for hormone receptors ERBB2, display frequent TP53 mutations, express basal epithelial markers. To study role of P53 loss function cancer development, we generated conditional mouse models tissue-specific...
More than 80% of patients who undergo sentinel lymph node (SLN) biopsy have no nodal metastasis. Here we describe a model that combines clinicopathologic and molecular variables to identify with thin intermediate thickness melanomas may forgo the SLN procedure due their low risk
Several gene expression signatures have been proposed and demonstrated to be predictive of outcome in breast cancer. In the present article we address following issues: Do these perform similarly? Are there (common) molecular processes reported by signatures? Can better prognostic predictors constructed based on identified processes? We performed a comprehensive analysis performance nine seven different cancer datasets. To characterize functional associated with signatures, enlarged each...
Michiels et al. (Lancet 2005; 365: 488–92) employed a resampling strategy to show that the genes identified as predictors of prognosis from resamplings single gene expression dataset are highly variable. The most frequently in separate were put forward 'gold standard'. On higher level, breast cancer datasets collected by different institutions can be considered underlying population. limited overlap between published prognostic signatures confirms trend signature instability strategy. Six...
Breast cancer outcome can be predicted using models derived from gene expression data or clinical data. Only a few studies have created single prediction model both and These often remain inconclusive regarding an obtained improvement in performance. We rigorously compare three different integration strategies (early, intermediate, late integration) as well classifiers employing no (only one type) five of varying complexity. perform our analysis on set 295 breast samples, for which extensive...
Abstract The standard prognostic marker for multiple myeloma (MM) patients is the revised International Staging System (R-ISS). However, there room improvement in guiding treatment. This applies particularly to older patients, whom benefit/risk ratio reduced because of comorbidities and subsequent side effects. We hypothesized that adding gene-expression data R-ISS would generate a stronger marker. was tested by combining with SKY92 classifier (SKY-RISS). HOVON-87/NMSG-18 trial (EudraCT:...
Many cancer treatments are associated with serious side effects, while they often only benefit a subset of the patients. Therefore, there is an urgent clinical need for tools that can aid in selecting right treatment at diagnosis. Here we introduce simulated learning (STL), which enables prediction patient's benefit. STL uses idea patients who received different treatments, but have similar genetic tumor profiles, be used to model their response alternative treatment. We apply two multiple...
Acute kidney injury (AKI) is defined as a sudden episode of failure but known to be under-recognized by healthcare professionals. The Kidney Disease Improving Global Outcome (KDIGO) guidelines have formulated criteria facilitate AKI diagnosis comparing changes in plasma creatinine measurements (PCr). To improve awareness, we implemented these an electronic alert (e-alert), our health record (EHR) system.For every new PCr measurement measured the University Medical Center Utrecht that...
Background The availability of large collections microarray datasets (compendia), or knowledge about grouping genes into pathways (gene sets), is typically not exploited when training predictors disease outcome. These can be useful since a compendium increases the number samples, while gene sets reduce size feature space. This should favorable from machine learning perspective and result in more robust predictors. Methodology We extracted modules regulated sets, compendia. Through supervised...
Proteasome inhibitors are widely used in treating multiple myeloma, but can cause serious side effects and response varies among patients. It is, therefore, important to gain more insight into which patients will benefit from proteasome inhibitors.We introduce simulated treatment learned signatures (STLsig), a machine learning method identify predictive gene expression signatures. STLsig uses genetically similar who have received an alternative model than treatment. constructs networks by...
Double (bi-allelic) mutations in the gene encoding CCAAT/enhancer-binding protein-alpha (CEBPA) transcription factor have a favorable prognostic impact acute myeloid leukemia (AML). CEBPA can be detected using various techniques, but it is notoriously difficult to sequence due its high GC-content. Here we developed two-step expression classifier for accurate and standardized detection of double mutations. The key feature that explicitly removes cases with low expression, thereby excluding...
Abstract High levels of BAALC , ERG EVI1 and MN1 expression have been associated with shorter overall survival in AML but standardized clinically validated assays are lacking. We therefore developed optimized an assay for detection these prognostic genes patients intermediate cytogenetic risk AML. In a training set 147 cases we performed cross validations at 5 percentile steps level observed bimodal significance profile unimodal profiles no statistically significant cutoff points near the...
Multiple myeloma (MM) is a heterogeneous hematologic malignancy associated with several risk factors including genetic aberrations which impact disease response and survival. Thorough classification essential to select the best clinical strategy optimize outcomes. The SKY92 molecular signature classifies patients as standard- or high-risk for progression. PRospective Observational Myeloma Impact Study (PROMMIS; NCT02911571) measures of on treatment plan. Newly diagnosed MM had bone marrow...
Typically, prognostic capability of gene expression profiling (GEP) is studied in the context clinical trials, for which 50%-80% patients are not eligible, possibly limiting generalizability findings to routine practice. Here, we evaluate GEP analysis outside aiming improve risk assessment multiple myeloma (MM) patients.A total 155 bone marrow samples from MM were collected RNA was analyzed by microarray. Sixteen previously developed GEP-based markers evaluated, combined with survival data,...
Abstract A mathematical framework was described and discussed that relates the triacylglycerol (TAG) distribution to measurements results. This model is valid for any analytical technique which an unambiguous relation between TAGs experimental data exists. The can be employed estimate TAG based on subset of these techniques. Furthermore future techniques incorporated, eventually enabling computation exact distribution. In current practice from measurement values believed by Coleman 's...
Mutations in the gene encoding nucleophosmin (NPM1) carry a prognostic value for patients with acute myeloid leukemia (AML). Various techniques are currently being used to detect these mutations routine molecular diagnostics. Incorporation of accurate NPM1 mutation detection on expression platform would enable simultaneous various other biomarkers. Here we present an array-based using custom probes WT mRNA and type A, B, D mutant mRNA. This method was 100% training cohort 505 newly diagnosed...
Tumors have been hypothesized to be the result of a mixture oncogenic events, some which will reflected in gene expression tumor. Based on this hypothesis variety data-driven methods employed decompose tumor profiles into component profiles, hypothetically linked these events. Interpretation resulting components is often done by post-hoc comparison to, for instance, functional groupings genes sets. None allow incorporation that type knowledge directly decomposition. We present linear model...