Publicaties
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Deciphering molecular heterogeneity in pediatric AML using a cancer vs normal transcriptomic approach Universiteit Gent
From methylation to myelination: epigenomic and transcriptomic profiling of chronic inactive demyelinated multiple sclerosis lesions KU Leuven Universiteit Hasselt
In the progressive phase of multiple sclerosis (MS), the hampered differentiation capacity of oligodendrocyte precursor cells (OPCs) eventually results in remyelination failure. We have previously shown that DNA methylation of Id2/Id4 is highly involved in OPC differentiation and remyelination. In this study, we took an unbiased approach by determining genome-wide DNA methylation patterns within chronically demyelinated MS lesions and ...
Lipidomic and Transcriptomic Basis of Lysosomal Dysfunction in Progranulin Deficiency Universiteit Antwerpen
Defective lysosomal function defines many neurodegenerative diseases, such as neuronal ceroid lipofuscinoses (NCL) and Niemann-Pick type C (NPC), and is implicated in Alzheimer's disease (AD) and frontotemporal lobar degeneration (FTLD-TDP) with progranulin (PGRN) deficiency. Here, we show that PGRN is involved in lysosomal homeostasis and lipid metabolism. PGRN deficiency alters lysosome abundance and morphology in mouse neurons. Using an ...
Genomic-transcriptomic evolution in lung cancer and metastasis KU Leuven Vlaams Instituut voor Biotechnologie
Intratumour heterogeneity (ITH) fuels lung cancer evolution, which leads to immune evasion and resistance to therapy1. Here, using paired whole-exome and RNA sequencing data, we investigate intratumour transcriptomic diversity in 354 non-small cell lung cancer tumours from 347 out of the first 421 patients prospectively recruited into the TRACERx study2,3. Analyses of 947 tumour regions, representing both primary and metastatic disease, ...
Identification of coding and non-coding cancer drivers using gene regulatory network analysis KU Leuven
Identification of coding and non-coding cancer drivers using gene regulatory network analysis Regulation of gene transcription is an essential process, governing complex spatio-temporal expression patterns in every living cell. Gene regulation underlies processes such as the development of embryonic stem cells into various differentiated cell types, or the reprogramming of normal cells into cancer cells. Cancer is characterized by high intra- ...
Single Cell Genomics: Advances and Future Perspectives KU Leuven
Advances in whole-genome and whole-transcriptome amplification have permitted the sequencing of the minute amounts of DNA and RNA present in a single cell, offering a window into the extent and nature of genomic and transcriptomic heterogeneity which occurs in both normal development and disease. Single-cell approaches stand poised to revolutionise our capacity to understand the scale of genomic, epigenomic, and transcriptomic diversity that ...
Bioinformatics for single-cell genome sequence analyses to study genome instability and intra-tumour genetic heterogeneity at high resolution KU Leuven
Although all cells in a human body are descendant from a single cell –i.e. the zygote– the genetic content in the different cells is not necessarily identical due to the accumulation of mutations during development and aging, making every individual a genetic mosaic. Such mutations may lead to the development of disease, like cancer or developmental disorders. Hence, it is important to study the spectrum of mutations that accumulate in a human ...
Innovative translational research approaches for unmet clinical needs in breast cancer KU Leuven
This thesis explores innovative translational research approaches in breast cancer, aiming to increase biological understanding of the disease and thereby help advance precision medicine. It does so in two groups of patients with a high clinical unmet need. First, it investigates patients with early breast cancer in the context of adiposity (body fat accumulation). Secondly, it investigates metastatic breast cancer, which is the ultimate reason ...
Multiple nested reductions of single data modes as a tool to deal with large data sets KU Leuven
The increased accessibility and concerted use of novel measurement technologies give rise to a data tsunami with matrices that comprise both a high number of variables and a high number of objects. As an example, one may think of transcriptomics data pertaining to the expression of a large number of genes in a large number of samples or tissues (as included in various compendia). The analysis of such data typically implies ill-conditioned ...