Somatic copy number variations (CNV; i.e., amplifications and deletions) have been implicated in the origin and development of multiple cancers and some of these aberrations are designated targets for therapies. Although FISH is still considered the gold standard for CNV detection, the increasing number of potentially druggable amplifications to be assessed makes a gene-by-gene approach time- and tissue-consuming. Here we investigated the potential of next generation sequencing (NGS) custom panels to simultaneously determine CNVs across FFPE solid tumor samples. DNA was purified from cell lines and FFPE samples and analyzed by NGS sequencing using a 20-gene custom panel in the GeneReader Platform®. CNVs were identified using an in-house algorithm based on the UMI read coverage. Retrospective validation of in-house algorithm to identify CNVs showed 97.1% concordance rate with the NGS custom panel. The prospective analysis was performed in a cohort of 243 FFPE samples from patients arriving at our hospital, which included 74 NSCLC tumors, 148 CRC tumors, and 21 other tumors. Of them, 33% presented CNVs by NGS and in 14 cases (5.9%) the CNV was the only alteration detected. We have identified CNV alterations in about one-third of our cohort, including FGFR1, CDK6, CDK4, EGFR, MET, ERBB2, BRAF, or KRAS. Our work highlights the need to include CNV testing as a part of routine NGS analysis in order to uncover clinically relevant gene amplifications that can guide the selection of therapies.

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Background: Fusions involving the tyrosine kinase receptor genes ALK, ROS1, RET, NTRK or MET exon 14 skipping variant (METex14) are present in a significant percentage of advanced solid tumors and their accurate identification is critical to guide targeted therapies. While FISH has traditionally been considered the gold standard for fusion analysis, it is costly and shows biases. GeneReader Next Generation Sequencing (NGS) (Qiagen) and nCounter (Nanostring) are two technologies allowing simultaneous detection of fusion transcripts and splicing variants. In this work we compared the performance of both platforms for fusion and splicing variant detection in advanced solid tumor patients. Methods: RNAs from 40 selected solid tumors were purified using High Pure FFPET RNA Isolation Kit (Hoffman-La Roche) and prospectively analyzed by GeneReader and nCounter. The custom nCounter codeset used targets fusions involving ALK, ROS1, RET, NTRK1-3, NRG1 and MET exon 14 skipping variant based on a dual strategy: detection of specific fusion transcripts and imbalances between the 3' and 5' mRNA regions, enabling the recognition of even those fusions not identified with the specific primers. Reporter counts from nCounter were collected with the nSolver Analysis software (Nanostring) and analyzed using an algorithm developed in the laboratory. The design of QIAact Lung Fusion Custom GeneReader panel contains specific junction probes for the detection of fusions in ALK, ROS1, RET, FGFR1- 3, NRG1, NTRK1- 3, EGFR, BRAF, and MET exon 14 skipping variant. GeneReader analysis and interpretation were performed with the QCI-Analyze and QCI-Interpret software's (Qiagen). Results: Valid results were obtained for 40/40 (100%) of samples tested. Paired analysis showed a 97.5% concordance (39/40 cases) between the results obtained by nCounter and GeneReader NGS, corresponding to a Cohen's kappa of 0.935 [CI=0.809-1.0]. Overall, 8 samples tested positive for fusion transcripts, namely EML4-ALK (n=4), CCDC6-RET (n=1), KIF5B-RET (n=1), EZR-ROS1 (n=1) and ETV6-NTRK3 (n=1). In addition, MET exon 14 skipping variant was detected in two samples. The discordant case between nCounter and NGS corresponded to a rare RET fusion only detected by 3'-5' imbalance using nCounter, while the remaining 29 patients were pan-negative. In one of them, an uncommon HLA-DRB1-MET fusion not included in the nCounter codeset, was found by the GeneReader custom panel. Conclusions: RNA-based NGS and nCounter show excellent concordance for detection of gene fusions and MET splicing variant in advanced solid tumors. Citation Format: Mónica Garzón Ibañez, Ana Gimenez-Capitán, Marta Vives Usano, Ruth Román Lladó, Sonia Rodriguez, Erika Aldeguer, Beatriz García Pelaez, Nuria Jordana Ariza, Cristina Aguado, Santiago Viteri, Andrés Aguilar, Irene Moya, Carlos Cabrera, Maria Jose Catalán, Maria Gonzalez cao, Silvia Garcia-Roman, Jordi Bertran Alamillo, Florencia Garcia Casabal, Rafael Rosell, Miguel Angel Molina-Vila, Clara De La Caridad Mayo De Las Casas. Comparison of clinically relevant fusions detection using two multiplexing RNA based platforms: nCounter and GeneReader [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 290.