Abstract 455: Consistent multi-lab performance of highly multiplexed RNA fusion detection with low RNA input and limit of detection
Authors: David N. Debruyne, Chenyu Li, Julia Spencer, Vidushi Kapoor, Lily Y. Liu, Lucie Lee, Rounak Feigelman, Grayson Burdon, Jeffrey Liu, Guoying Liu, Zhitong Liu
Journal: Cancer Research (2021)

Abstract Gene fusions, which are usually caused by chromosomal rearrangements, are frequently associated with various cancers. Detection of fusion mutations is an important part of cancer management, and are usually detected in RNA purified from biopsies of fresh tissue or FFPE sections. The amount of RNA from these samples, however, is usually limited. We developed a new, PCR-based fusion detection method, which even allows detection of unknown and novel fusion mutations. We demonstrate its consistent performance across various RNA inputs, and sequencing depths, in terms of technical performance and limit of detection. A multiplex PCR RNA fusion panel was designed to cover known RNA fusion targets and unknown fusion targets for target enrichment via single primer multiplex PCR. SeraSeq fusion Reference RNA was used to evaluate the limit of detection of the method. The amplicons were about 110 bp on average to allow for target amplification from challenging fragmented samples such as FFPE RNA. After reverse transcription, the panel was used in a multiplex PCR to amplify the targets, and a final PCR was used to add sequencing adapters and sample indexes. The resulting libraries were sequenced in Illumina sequencers. The library was analyzed for the detection of known fusion variants across different initial input of targets, as well as the mapping rate, onto the target, and the presence of human ribosomal RNA. We found that the lengths of the fragmented RNA had little effect on the performance of the libraries. With various amount of input RNA, the required numbers of PCR cycles were optimized. We observe a linear relationship between the library yields and input amounts of RNA from 10 to 50ng, which had R1 mapping rates above 95% and 98%, respectively. We report the detection of all twelve fusion variants, which are present in the panel and in the Seraseq Fusion RNA Mix v4 reference standard and covered by our panel on each NGS platform with an average sequencing depth of 0.2M reads, or 3600 reads/amplicon across all assays. Even at inputs as low as 3 ng, all 12 fusions were typically detected. In general, the results for individual fusions among the different replicates were concordant, with limited observed variance in reads across some fusion junctions between assays and replicates. Over 90% of reads supported the fusion call from all inputs (ranging from 1.6 to 50 ng). Over 97% of reads supported the fusion call between 12 and 50 ng. A multi-lab validation confirmed the above results, and were also comparable when using an additional distinct CleanPlex fusion panel. CleanPlex fusion technology allows for reliable and simultaneous detection of 12 designed clinically relevant RNA fusions even at low input amounts. The data from a multi-lab study support the use of this technology for targeted NGS RNA fusion assays. The CleanPlex fusion technology provides consistent and sensitive results for a wide variety of sample inputs. Citation Format: David N. Debruyne, Chenyu Li, Julia Spencer, Vidushi Kapoor, Lily Y. Liu, Lucie Lee, Rounak Feigelman, Grayson Burdon, Jeffrey Liu, Guoying Liu, Zhitong Liu. Consistent multi-lab performance of highly multiplexed RNA fusion detection with low RNA input and limit of detection [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 455.