Acta Neuropathologica CommunicationsCancer BiologyPeer-reviewed journal article
Expression of LTR and LINE1 transposable elements defines atypical teratoid/rhabdoid tumor subtypes
Martin V. Hamann, Shweta GodboleiD, Maisha AdibaiD, Sabrina M. LeddyiD, Jelena NavolićiD, Ghazaleh TabatabaiiD, Daniel J. Merk, Ulrike C. LangeiD, Julia E. NeumanniD
Abstract
Atypical teratoid rhabdoid tumors (ATRTs) are aggressive central nervous system tumors mainly affecting young children. Extensive molecular characterization based on gene expression and DNA methylation patterns has solidly established three major ATRT subtypes (MYC, SHH and TYR), which show distinct clinical features, setting the basis for more effective, targeted treatment regimens. Transcriptional activity of transposable elements (TEs), like LINE1s and LTRs, is tightly linked with human cancers as a direct consequence of lifting epigenetic repression over TEs. The sole recurrent biallelic loss-of-function mutation in SMARCB1 in ATRTs, a core component of the SWI/SNF chromatin remodeling complex, raises the question of how TE transcription contributes to ATRT development. Here, we comprehensively investigate the transcriptional profiles of 1.9M LINE1 and LTR elements across ATRT subtypes in primary human samples. We find TE transcription profiles are unique, allowing sample stratification into ATRT subtypes. The TE activity signature in ATRT-MYC subtype is unique, setting these tumors apart from SHH and TYR ATRTs. More specifically, ATRT-MYC shows broadly reduced transcript levels of LINE1 and ERVL-MaLR subfamilies. ATRT-MYC is also unique in having significantly less LTR and LINE1 loci with bidirectional promoter activity. Furthermore, we identify 849 differentially transcribed TEs in primary samples, which are predictive towards established ATRT-SHH and-MYC cell line models. In summary, including TE transcription profiles into the molecular characterization of ATRTs might reveal new tumor vulnerabilities leading to novel therapeutic interventions, such as immunotherapy.
- organism: human
- assay: bulk RNA-seq
- research focus: cell type annotation
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: statistical model
- approach: diffusion model
- Citations
- 1
- FWCI
- 0.30
- Field percentile
- 48th percentile
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