Inhibiting epigenetic modulators can transcriptionally reactivate transposable elements (TEs). These TE transcripts often generate unique peptides that can serve as immunogenic antigens for immunotherapy. Here, we ask whether TEs activated by epigenetic therapy could appreciably increase the antigen repertoire in glioblastoma, an aggressive brain cancer with low mutation and neoantigen burden.
View Article and Find Full Text PDFRecent studies have shown that the noncoding genome can produce unannotated proteins as antigens that induce immune response. One major source of this activity is the aberrant epigenetic reactivation of transposable elements (TEs). In tumors, TEs often provide cryptic or alternate promoters, which can generate transcripts that encode tumor-specific unannotated proteins.
View Article and Find Full Text PDFCryptic promoters within transposable elements (TEs) can be transcriptionally reactivated in tumors to create new TE-chimeric transcripts, which can produce immunogenic antigens. We performed a comprehensive screen for these TE exaptation events in 33 TCGA tumor types, 30 GTEx adult tissues and 675 cancer cell lines, and identified 1,068 TE-exapted candidates with the potential to generate shared tumor-specific TE-chimeric antigens (TS-TEAs). Whole-lysate and HLA-pulldown mass spectrometry data confirmed that TS-TEAs are presented on the surface of cancer cells.
View Article and Find Full Text PDFTransposable elements (TEs) encode regulatory elements that impact gene expression in multiple species, yet a comprehensive analysis of zebrafish TEs in the context of gene regulation is lacking. Here, we systematically investigate the epigenomic and transcriptomic landscape of TEs across 11 adult zebrafish tissues using multidimensional sequencing data. We find that TEs contribute substantially to a diverse array of regulatory elements in the zebrafish genome and that 37% of TEs are positioned in active regulatory states in adult zebrafish tissues.
View Article and Find Full Text PDFAccurate genome-wide detection of somatic mutations with low variant allele frequency (VAF, <1%) has proven difficult, for which generalized, scalable methods are lacking. Herein, we describe a new computational method, called RePlow, that we developed to detect low-VAF somatic mutations based on simple, library-level replicates for next-generation sequencing on any platform. Through joint analysis of replicates, RePlow is able to remove prevailing background errors in next-generation sequencing analysis, facilitating remarkable improvement in the detection accuracy for low-VAF somatic mutations (up to ~99% reduction in false positives).
View Article and Find Full Text PDFMotivation: Advances in sequencing technologies have remarkably lowered the detection limit of somatic variants to a low frequency. However, calling mutations at this range is still confounded by many factors including environmental contamination. Vector contamination is a continuously occurring issue and is especially problematic since vector inserts are hardly distinguishable from the sample sequences.
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