Steffen Falgreen

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BACKGROUND Recent reports indicate that in vitro drug screens combined with gene expression profiles (GEP) of cancer cell lines may generate informative signatures predicting the clinical outcome of chemotherapy. In multiple myeloma (MM) a range of new drugs have been introduced and now challenge conventional therapy including high dose melphalan.(More)
This report describes a method for the generation of global gene expression profiles from low frequent B-cell subsets by using fluorescence-activated cell sorting and RNA amplification. However, some of the differentiating compartments involve a low number of cells and therefore it is important to optimize and validate each step in the procedure. Normal(More)
Patients suffering from cancer are often treated with a range of chemotherapeutic agents, but the treatment efficacy varies greatly between patients. Based on recent popularisation of regularised regression models the goal of this study was to establish workflows for pharmacogenomic predictors of response to standard multidrug regimens using baseline gene(More)
The presence of different transcripts of a gene across samples can be analysed by whole-transcriptome microarrays. Reproducing results from published microarray data represents a challenge owing to the vast amounts of data and the large variety of preprocessing and filtering steps used before the actual analysis is carried out. To guarantee a firm basis for(More)
In vitro generated dose-response curves of human cancer cell lines are widely used to develop new therapeutics. The curves are summarised by simplified statistics that ignore the conventionally used dose-response curves’ dependency on drug exposure time and growth kinetics. This may lead to suboptimal exploitation of data and biased conclusions on the(More)
BACKGROUND The concept of precision medicine in cancer includes individual molecular studies to predict clinical outcomes. In the present N = 1 case we retrospectively have analysed lymphoma tissue by exome sequencing and global gene expression in a patient with unexpected long-term remission following relaps. The goals were to phenotype the diagnostic and(More)
BACKGROUND Dozens of omics based cancer classification systems have been introduced with prognostic, diagnostic, and predictive capabilities. However, they often employ complex algorithms and are only applicable on whole cohorts of patients, making them difficult to apply in a personalized clinical setting. RESULTS This prompted us to create(More)
Accurate adjustment for the amplification efficiency (AE) is an important part of real-time quantitative polymerase chain reaction (qPCR) experiments. The most commonly used correction strategy is to estimate the AE by dilution experiments and use this as a plug-in when efficiency correcting the Δ Δ C q . Currently, it is recommended to determine the AE(More)
MicroRNAs (miRNAs) are small non-coding RNAs that play important post-transcriptional regulatory roles in a wide range of biological processes. They are fundamental to the normal development of cells, and evidence suggests that the deregulation of specific miRNAs is involved in malignant transformation due to their function as oncogenes or tumor(More)
Malignant cells in tumours of B-cell origin account for 0.1% to 98% of the total cell content, depending on disease entity. Recently, gene expression profiles (GEPs) of B-cell lymphomas based on microarray technologies have contributed significantly to improved sub-classification and diagnostics. However, the varying degrees of malignant B-cell frequencies(More)
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