Transcript Fusions Research Articles

Swinger RNAs with sharp switches between regular transcription and transcription systematically exchanging ribonucleotides: Case studies

During RNA transcription, DNA nucleotides A,C,G, T are usually matched by ribonucleotides A, C, G and U. However occasionally, this rule does not apply: transcript-DNA homologies are detectable only assuming systematic exchanges between ribonucleotides. Nine symmetric (X↔Y, e.g. A↔C) and fourteen asymmetric (X↔Y↔Z, e.g. A↔C↔G) exchanges exist, called swinger transcriptions. Putatively, polymerases occasionally stabilize in unspecified swinger conformations, possibly similar to transient conformations causing punctual misinsertions. This predicts chimeric transcripts, part regular, part swinger-transformed, reflecting polymerases switching to swinger polymerization conformation(s). Four chimeric Genbank transcripts (three from human mitochondrion and one murine cytosolic) are described here: (a) the 5′ and 3′ extremities reflect regular polymerization, the intervening sequence exchanges systematically between ribonucleotides (swinger rule G↔U, transcript (1), with sharp switches between regular and swinger sequences; (b) the 5′ half is ‘normal’, the 3′ half systematically exchanges ribonucleotides (swinger rule C↔G, transcript (2), with an intercalated sequence lacking homology; (c) the 3′ extremity fits A↔G exchanges (10% of transcript length), the 5′ half follows regular transcription; the intervening region seems a mix of regular and A↔G transcriptions (transcript 3); (d) murine cytosolic transcript 4 switches to A↔U+C↔G, and is fused with A↔U+C↔G swinger transformed precursor rRNA. In (c), each concomitant transcript 5′ and 3′ extremities match opposite genome strands. Transcripts 3 and 4 combine transcript fusions with partial swinger transcriptions. Occasional (usually sharp) switches between regular and swinger transcriptions reveal greater coding potential than detected until now, suggest stable polymerase swinger conformations.

The landscape and therapeutic relevance of cancer-associated transcript fusions.

Transcript fusions as a result of chromosomal rearrangements have been a focus of attention in cancer as they provide attractive therapeutic targets. To identify novel fusion transcripts with the potential to be exploited therapeutically, we analyzed RNA sequencing, DNA copy number and gene mutation data from 4,366 primary tumor samples. To avoid false positives, we implemented stringent quality criteria that included filtering of fusions detected in RNAseq data from 364 normal tissue samples. Our analysis identified 7,887 high confidence fusion transcripts across 13 tumor types. Our fusion prediction was validated by evidence of a genomic rearrangement for 78 of 79 fusions in 48 glioma samples where whole genome sequencing data was available. Cancers with higher levels of genomic instability showed a corresponding increase in fusion transcript frequency, whereas tumor samples harboring fusions contained statistically significantly fewer driver gene mutations, suggesting an important role for tumorigenesis. We identified at least one in-frame protein kinase fusion in 324 of 4,366 samples (7.4%). Potentially druggable kinase fusions involving ALK, ROS, RET, NTRK, and FGFR gene families were detected in bladder carcinoma (3.3%), glioblastoma (4.4%), head and neck cancer (1.0%), low grade glioma (1.5%), lung adenocarcinoma (1.6%), lung squamous cell carcinoma (2.3%), and thyroid carcinoma (8.7%), suggesting a potential for application of kinase inhibitors across tumor types. In-frame fusion transcripts involving histone methyltransferase or histone demethylase genes were detected in 111 samples (2.5%) and may additionally be considered as therapeutic targets. In summary, we described the landscape of transcript fusions detected across a large number of tumor samples and revealed fusion events with clinical relevance that have not been previously recognized. Our results support the concept of basket clinical trials where patients are matched with experimental therapies based on their genomic profile rather than the tissue where the tumor originated.