Abstract

Abstract Introduction: Gene fusions are frequently associated with tumorigenesismalignant tumors. Highly sensitive and reproducible detection of gene fusions in clinical samples, especially formalin-fixed paraffin-embedded (FFPE) specimens, is important for diagnosis, prognosis, and treatment guidance. Although many clinical tests utilize next-generation-sequencing (NGS) for detection of genetic alterations, reliable detection of gene fusions by NGS in FFPE samples remains a challenge. Methods: Five FFPE non-small cell lung cancer samples confirmed by FISH to contain EML4-ALK or KIF5B-RET fusions were selected for testing along with the Seraseq™ FFPE Tumor Fusion RNA Reference Material, v1, which evaluates forcontains 12 known fusions. Four operators prepared NGS libraries for each sample (89-250ng input) using the commercially available QIAseq RNAscan Oncology Panel, which targets 223 fusion gene pairs or 576 unique breakpoints. The resulting libraries were sequenced on an Illumina® NextSeq 500 sequencer. Demultiplexed FASTQ files were analyzed using cloud-based QIAseq RNAscan Analysis pipeline v1.7.20.2. Detected fusions that are on the panel's target list were reported as curated gene fusions and assigned a score based on unique molecules supporting the transcript. Results: For the Seraseq™ FFPE Tumor Fusion RNA Reference v1 sample, all 12 expectedknown fusions were detected in each of the libraries generated by four different operators. The analysis pipeline correctly called the expected fusion in all four replicates of the five clinical FFPE samples tested, which varied in both input quantityamount and quality. Reproducibility was evaluated by comparing the score values across replicate libraries for each sample; expected fusion detection was 100% consistent between users, and the average correlation coefficient for the fusion score was 0.995. Conclusions: The commercially available QIAseq RNAscan Oncology panel is a highly sensitive and robust product for detection of gene fusions in FFPE samples. QIAseq RNAscan methodology provides a useful tool for studying gene fusions in tumor samples and with optimization, customization, and validation can further fit the specific needs for of clinical laboratories. Citation Format: Jeffrey Falk, Parth Sitlani, Claire Orosco, Maya Panjikaran, Dana Weiner, Song Tian, Raed Samara, John DiCarlo, Yexun Wang, Eric Lader, Frank Reinecke. Robust gene fusion detection in formalin-fixed tissue sample with QIAseq RNAscan Oncology Panel [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 5356.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call