Biology subjects

Meijer, G. A.

Publications and source records attributed to Meijer, G. A..

3 recordsLinked to original sources

bioRxiv2024

Tumor break load quantitates structural variant-associated genomic instability with biological and clinical relevance across cancers

While structural variants (SVs) are a clear sign of genomic instability, they have not been systematically quantified per patient. Therefore, the biological and clinical impact of high numbers of SVs in patients is unknown. We introduce tumor break load (TBL), defined as the sum of unbalanced SVs, as a measure for SV-associated genomic instability. Using pan-cancer data from TCGA, PCAWG, and CCLE, we show that a high TBL is associated with significant changes in gene expression in 26/31 cancer types that consistently involve upregulation of DNA damage repair and downregulation of immune response pathways. Patients with a high TBL show a higher risk of recurrence and shorter median survival times for 5/15 cancer types. Our data demonstrate that TBL is a biologically and clinically relevant feature of genomic instability that may aid patient prognostication and treatment stratification. For the datasets analyzed in this study, TBL has been made available in cBioPortal.

cancer biology↗

bioRxiv2021

Detection of fusion transcripts and their genomic breakpoints from RNA sequencing data

Spliced fusion-transcripts are typically identified by RNA-seq without elucidating the causal genomic breakpoints. However, non poly(A)-enriched RNA-seq contains large proportions of intronic reads spanning also genomic breakpoints. Using 1.274 RNA-seq samples, we investigated what additional information is embedded in non poly(A)-enriched RNA-seq data. Here, we present our novel, graph-based, Dr. Disco algorithm that makes use of both intronic and exonic RNA-seq reads to identify not only fusion transcripts but also genomic breakpoints in gene but also in intergenic regions. Dr. Disco identified TMPRSS2-ERG fusions with genomic breakpoints and other transcribed rearrangements from multiple RNA-sequencing cohorts. In breast cancer and glioma samples Dr. Disco identified rearrangement hotspots near CCND1 and MDM2 and could directly associate this with increased expression. A comparison with matched DNA-sequencing revealed that most genomic breakpoints are not, or minimally, transcribed while also revealing highly expressed translocations missed by DNA-seq. By using the full potential of non poly(A)-enriched RNA-seq data, Dr. Disco can reliably identify expressed genomic breakpoints and their transcriptional effects.

bioinformatics↗

bioRxiv2020

TraIT, Translational research IT bridging the valley of death in translational medicine

Translating new technology and biological findings into clinical applications is hampered by insufficient translational research IT. The Dutch Translational research IT (TraIT) initiative organizes, deploys, and manages data and workflows in an on-line "office suite", supplemented with efficient training and user support. TraIT has been adopted by a wide user community providing an excellent large-scale demonstrator for the nation-wide Health-RI initiative.

bioinformatics↗