Abstract Gene fusions have long been considered strong drivers of cellular transformation, making the accurate and precise assessment of these variants a necessity for any tumor profiling assay. Recent studies have indicated the utility of next-generation sequencing (NGS) for tumor profiling due to increasing data output and decreasing costs of the technology. Unfortunately, because a critical facet of NGS is the evaluation of short DNA fragments, sufficiently covering all possible breakpoint regions (many of which are intronic) has proven difficult and costly. Recent studies have indicated that NGS may prove better at detecting gene fusions using RNA instead of DNA, given the higher probability of breakpoint-spanning reads. This allows for de-novo discovery of fusion partners without knowing the precise breakpoint and guarantees expression of the fusion transcript. To that end, Illumina is developing a novel method for simultaneous library preparation from low input amounts of degraded DNA and RNA from a single FFPE tumor sample. With a turnaround time from nucleic acid to data of less than 4 days, this enrichment-based assay surveys 170 genes for single nucleotide variants and small indels, 57 genes for gene amplifications, 55 genes for fusions and four genes for splice variants. To determine the limit of detection for gene fusions, a panel of different synthetic RNA transcripts were prepared in vitro, pooled at equal molar amounts, and spiked into 20ng of cell line RNA (MCF-7). Fusions were detected over several orders of magnitude down to 1×10-8 picomoles, equivalent to 3 to 15 fusion transcripts per cell. In addition, a similar range of fusion detection was observed when RNA from two different cell lines were mixed, as when RNA from a cell line with high expression of an FGFR2-COL14A1 fusion was mixed in proportional amounts with RNA from a different cell line where FGFR2 is minimally expressed. Importantly, our method allowed for fusion detection from as little as 100 picograms of cell line RNA. We then tested our new method on previously characterized FFPE solid tumor samples harboring known gene rearrangements identified by FISH and other methods. Not only was the NGS method able to detect the majority of previously characterized variants, including EML4-ALK and SDC4-ROS1, it also identified the gene fusions and their uncharacterized fusions partners by combining the non-targeted sequence information gained from using an enrichment-based assay with novel fusion calling algorithms. From this information, we were able to glean new insights into the structure of the rearrangements and how the gene fusions may be involved in tumorigenesis. These results indicate that NGS can identify fusions from the low amounts of degraded RNA from solid tumor samples, identify fusion partners not uncovered by current technologies, and further emphasizes the advantage of NGS in solid tumor profiling. Citation Format: Julianna Tdr Parks, Luo Byron, Brian Crain, Snedecor June, Zhao Chen, Tingting Du, Gabriel L. Sica, Taofee K. Owonikoko, Stewart G. Neill, Scott Newman, Debra F. Saxe, Jennifer S. LoCoco, Han-Yu Chuang, Charles Lin, Kathryn M. Stephens, Michael R. Rossi, Matthew C. Friedenberg. An evaluation of NGS to identify gene fusions using RNA from FFPE solid tumor samples. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 3607.
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