François Rustenburg

Bio: François Rustenburg is an academic researcher from VU University Medical Center. The author has contributed to research in topics: Gene expression profiling & Rheumatoid arthritis. The author has an hindex of 16, co-authored 21 publications receiving 1921 citations. Previous affiliations of François Rustenburg include VU University Amsterdam.

DNA copy number analysis of fresh and formalin-fixed specimens by shallow whole-genome sequencing with identification and exclusion of problematic regions in the genome assembly

Abstract: Detection of DNA copy number aberrations by shallow whole-genome sequencing (WGS) faces many challenges, including lack of completion and errors in the human reference genome, repetitive sequences, polymorphisms, variable sample quality, and biases in the sequencing procedures. Formalin-fixed paraffin-embedded (FFPE) archival material, the analysis of which is important for studies of cancer, presents particular analytical difficulties due to degradation of the DNA and frequent lack of matched reference samples. We present a robust, cost-effective WGS method for DNA copy number analysis that addresses these challenges more successfully than currently available procedures. In practice, very useful profiles can be obtained with ∼0.1× genome coverage. We improve on previous methods by first implementing a combined correction for sequence mappability and GC content, and second, by applying this procedure to sequence data from the 1000 Genomes Project in order to develop a blacklist of problematic genome regions. A small subset of these blacklisted regions was previously identified by ENCODE, but the vast majority are novel unappreciated problematic regions. Our procedures are implemented in a pipeline called QDNAseq. We have analyzed over 1000 samples, most of which were obtained from the fixed tissue archives of more than 25 institutions. We demonstrate that for most samples our sequencing and analysis procedures yield genome profiles with noise levels near the statistical limit imposed by read counting. The described procedures also provide better correction of artifacts introduced by low DNA quality than prior approaches and better copy number data than high-resolution microarrays at a substantially lower cost.

Rheumatoid Arthritis subtypes identified by genomic profiling of peripheral blood cells: Assignment of a type I interferon signature in a subpopulation of patients

Abstract: Objective: Rheumatoid arthritis (RA) is a heterogeneous disease with unknown etiology. Here we aimed to identify peripheral blood gene expression profiles that may distinguish RA subtypes. Methods: Large-scale expression profiling by cDNA microarrays was performed on peripheral blood from 35 patients and 15 healthy individuals. Differential gene expression was analyzed by Significance Analysis of Microarrays (SAM), followed by Gene Ontology analysis of the significant genes. Gene Set Enrichment Analysis (GSEA) was applied to identify pathways relevant to disease. Results: We found a remarkably elevated expression of a spectrum of genes involved in immune defense in the peripheral blood of RA patients compared to healthy individuals. SAM analysis revealed a highly significant elevated expression of interferon (IFN) type I regulated genes in RA compared to healthy individuals, which was confirmed by Gene Ontology and Pathway analysis, suggesting that this pathway was activated systemically in RA. A quantitative analysis revealed that increased expression of IFN-response genes was characteristic of approximately half of the patients (IFN high patients). Application of pathway analysis revealed that the IFN high group was largely different from the controls, with evidence for upregulated pathways involved in coagulation and complement cascades, and fatty acid metabolism, while the IFNlow group was similar to the controls. Conclusion: The IFN type I signature defines a subgroup of RA patients, with a distinct biomolecular phenotype, characterized by increased activity of the innate defense system.

Regulation of IFN response gene activity during infliximab treatment in rheumatoid arthritis is associated with clinical response to treatment

Abstract: Introduction: Cross-regulation between TNF and type I IFN has been postulated to play an important role in autoimmune diseases. Therefore, we determined the effect of TNF blockade in rheumatoid arthritis (RA) on the type I IFN response gene activity in relation to clinical response. Methods: Peripheral blood from 33 RA patients was collected in PAXgene tubes before and after the start of infliximab treatment. In a first group of 15 patients the baseline expression of type I IFN-regulated genes was determined using cDNA microarrays and compared to levels one month after treatment. The remaining 18 patients were studied as an independent group for validation using quantitative polymerase chain reaction (qPCR). Results: Gene expression analysis revealed that anti-TNF antibody treatment induced a significant increase in type I IFN response gene activity in a subset of RA patients, whereas expression levels remained similar or were slightly decreased in others. The findings appear clinically relevant since patients with an increased IFN response gene activity after antiTNF therapy had a poor clinical outcome. This association was confirmed and extended for an IFN response gene set consisting of OAS1, LGALS3BP, Mx2, OAS2 and SERPING1 in five EULAR good and five EULAR poor responders, by qPCR. Conclusions: Regulation of IFN response gene activity upon TNF blockade in RA is not as consistent as previously described, but varies between patients. The differential changes in IFN response gene activity appear relevant to the clinical outcome of TNF blockade in RA.

Cytokines in the pathogenesis of rheumatoid arthritis

Abstract: Cytokines regulate a broad range of inflammatory processes that are implicated in the pathogenesis of rheumatoid arthritis. In rheumatoid joints, it is well known that an imbalance between pro- and anti-inflammatory cytokine activities favours the induction of autoimmunity, chronic inflammation and thereby joint damage. However, it remains less clear how cytokines are organized within a hierarchical regulatory network, and therefore which cytokines may be the best targets for clinical intervention a priori. Here, we discuss the crucial effector function of cytokines in the immunological processes that are central to the pathogenesis of rheumatoid arthritis.

Large-scale gene function analysis with the PANTHER classification system

Abstract: The PANTHER (protein annotation through evolutionary relationship) classification system (http://wwwpantherdborg/) is a comprehensive system that combines gene function, ontology, pathways and statistical analysis tools that enable biologists to analyze large-scale, genome-wide data from sequencing, proteomics or gene expression experiments The system is built with 82 complete genomes organized into gene families and subfamilies, and their evolutionary relationships are captured in phylogenetic trees, multiple sequence alignments and statistical models (hidden Markov models or HMMs) Genes are classified according to their function in several different ways: families and subfamilies are annotated with ontology terms (Gene Ontology (GO) and PANTHER protein class), and sequences are assigned to PANTHER pathways The PANTHER website includes a suite of tools that enable users to browse and query gene functions, and to analyze large-scale experimental data with a number of statistical tests It is widely used by bench scientists, bioinformaticians, computer scientists and systems biologists In the 2013 release of PANTHER (v80), in addition to an update of the data content, we redesigned the website interface to improve both user experience and the system's analytical capability This protocol provides a detailed description of how to analyze genome-wide experimental data with the PANTHER classification system

Liquid biopsies come of age: towards implementation of circulating tumour DNA

Abstract: Improvements in genomic and molecular methods are expanding the range of potential applications for circulating tumour DNA (ctDNA), both in a research setting and as a 'liquid biopsy' for cancer management. Proof-of-principle studies have demonstrated the translational potential of ctDNA for prognostication, molecular profiling and monitoring. The field is now in an exciting transitional period in which ctDNA analysis is beginning to be applied clinically, although there is still much to learn about the biology of cell-free DNA. This is an opportune time to appraise potential approaches to ctDNA analysis, and to consider their applications in personalized oncology and in cancer research.

Clinical Applications of Circulating Tumor Cells and Circulating Tumor DNA as Liquid Biopsy.

Abstract: “Liquid biopsy” focusing on the analysis of circulating tumor cells (CTC) and circulating cell-free tumor DNA (ctDNA) in the blood of patients with cancer has received enormous attention because of its obvious clinical implications for personalized medicine. Analyses of CTCs and ctDNA have paved new diagnostic avenues and are, to date, the cornerstones of liquid biopsy diagnostics. The present review focuses on key areas of clinical applications of CTCs and ctDNA, including detection of cancer, prediction of prognosis in patients with curable disease, monitoring systemic therapies, and stratification of patients based on the detection of therapeutic targets or resistance mechanisms. Significance: The application of CTCs and ctDNA for the early detection of cancer is of high public interest, but it faces serious challenges regarding specificity and sensitivity of the current assays. Prediction of prognosis in patients with curable disease can already be achieved in several tumor entities, particularly in breast cancer. Monitoring the success or failure of systemic therapies (i.e., chemotherapy, hormonal therapy, or other targeted therapies) by sequential measurements of CTCs or ctDNA is also feasible. Interventional studies on treatment stratification based on the analysis of CTCs and ctDNA are needed to implement liquid biopsy into personalized medicine. Cancer Discov; 6(5); 479–91. ©2016 AACR.

Current and future perspectives of liquid biopsies in genomics-driven oncology.

Abstract: Precision oncology seeks to leverage molecular information about cancer to improve patient outcomes. Tissue biopsy samples are widely used to characterize tumours but are limited by constraints on sampling frequency and their incomplete representation of the entire tumour bulk. Now, attention is turning to minimally invasive liquid biopsies, which enable analysis of tumour components (including circulating tumour cells and circulating tumour DNA) in bodily fluids such as blood. The potential of liquid biopsies is highlighted by studies that show they can track the evolutionary dynamics and heterogeneity of tumours and can detect very early emergence of therapy resistance, residual disease and recurrence. However, the analytical validity and clinical utility of liquid biopsies must be rigorously demonstrated before this potential can be realized.