Abstract

Abstract Introduction: Fusion transcript are mRNA containing sequences from more than one gene and can be produced through chromosomal rearrangement or special splicing events. Some fusions have strong connection to certain cancers. For example, EML4-ALK fusion was identified in 6.7% of all non-small cell lung carcinoma patients. Patients with this fusion can be effectively treated with ALK inhibitors, making this fusion an ideal biomarker. Our protocol aims to target these actionable biomarkers. Previously fusions have been detected using FISH, RT-PCR, RNA-seq and targeted sequencing. Targeted sequencing provides better sensitivity and accuracy than the other methods mentioned above. In addition, our protocol incorporates Xenonucleic Acid (XNA), a molecule that can bind to and block the amplification of targeted wildtype sequences. It has been shown to improve assay sensitivity in detecting mutant sequences. In this case, XNA can block the amplification of wildtype transcripts and improve the sensitivity of fusion transcript detection. The addition of XNA can provide higher sensitivity than any currently commercially available kits. Methods: Total RNA was converted to cDNA using 5' RACE (Rapid amplification of cDNA ends) technology, adding a common tail to one end of all cDNA transcripts for PCR steps. Targeted multiplex PCR with XNA spike in was then performed, followed by another nesting multiplex PCR to further improve sensitivity. The libraries were indexed with an additional PCR step. Libraries were then pooled and sequenced using Illumina MiSeq. Data was analyzed with Qiagen CLC Genomic Workbench using a custom workflow. Results: TACC3 XNA can successfully block the amplification of wild type TACC3 gene while allow amplification of FGFR3-TACC3 fusion transcripts. FGFR3-TACC3 fusion read percentage (fusion reads/[fusion read+ WT reads]) increased noticeably from 2.68% to 60.12%. No false positive was detected in the negative control. Negative control also exhibit decrease in wild type TACC3 reads following the introduction of TACC3 XNA, from 10.45% of total reads (fusion/total reads) to 0.88%. This indicated that wildtype was blocked effetely by XNA. Preliminary tests with NTRK1 and ROS1 XNA showed no interference in detecting TPM3-NTRK1, CD74-ROS1, and SLC34A-ROS1 fusions, but increase its detection. Conclusion: XNA can effectively suppress the amplification from WT RNA transcript and enhances fusion transcripts detection during target sequencing. TACC3 XNA successfully increased fusion read percentage from 2.68% to 60.12%. More studies are being conducted to evaluate the effectiveness of XNA on other fusions. Citation Format: Simni Tang, Andrew Y. Fu, Michael J. Powell, Aiguo Zhang, Michael Y. Sha. A novel xenonucleic acid-mediated fusion gene detection method for cancer diagnostic [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr LB-284.

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