Introduction: Biomarker testing is mandatory for the clinical management of patients with advanced non-small cell lung cancer (NSCLC). Myriads of technical platforms are now available for biomarker analysis with differences in terms of multiplexing capability, analytical sensitivity, and turnaround time (TAT). We evaluated the technical performance of the diagnostic workflows of 24 representative Italian institutions performing molecular tests on a series of artificial reference specimens built to mimic routine diagnostic samples. Methods: Sample sets of eight slides from cell blocks of artificial reference specimens harboring exon 19 EGFR (epidermal growth factor receptor) p.E746_AT50del, exon 2 KRAS (Kirsten rat sarcoma viral oncogene homologue) p.G12C, ROS1 (c-ros oncogene 1)-unknown gene fusion, and MET (MET proto-oncogene, receptor tyrosine kinase) Δ exon 14 skipping were distributed to each participating institution. Two independent cell block specimens were validated by the University of Naples Federico II before shipment. Methodological and molecular data from reference specimens were annotated. Results: Overall, a median DNA concentration of 3.3 ng/µL (range 0.1–10.0 ng/µL) and 13.4 ng/µL (range 2.0–45.8 ng/µL) were obtained with automated and manual technical procedures, respectively. RNA concentrations of 5.7 ng/µL (range 0.2–11.9 ng/µL) and 9.3 ng/µL (range 0.5–18.0 ng/µL) were also detected. KRAS exon 2 p.G12C, EGFR exon 19 p.E736_A750del hotspot mutations, and ROS1 aberrant transcripts were identified in all tested cases, whereas 15 out of 16 (93.7%) centers detected MET exon 14 skipping mutation. Conclusions: Optimized technical workflows are crucial in the decision-making strategy of patients with NSCLC. Artificial reference specimens enable optimization of diagnostic workflows for predictive molecular analysis in routine clinical practice.

Non-small cell lung cancer testing on reference specimens: an italian multicenter experience

Furlan D.;
2024-01-01

Abstract

Introduction: Biomarker testing is mandatory for the clinical management of patients with advanced non-small cell lung cancer (NSCLC). Myriads of technical platforms are now available for biomarker analysis with differences in terms of multiplexing capability, analytical sensitivity, and turnaround time (TAT). We evaluated the technical performance of the diagnostic workflows of 24 representative Italian institutions performing molecular tests on a series of artificial reference specimens built to mimic routine diagnostic samples. Methods: Sample sets of eight slides from cell blocks of artificial reference specimens harboring exon 19 EGFR (epidermal growth factor receptor) p.E746_AT50del, exon 2 KRAS (Kirsten rat sarcoma viral oncogene homologue) p.G12C, ROS1 (c-ros oncogene 1)-unknown gene fusion, and MET (MET proto-oncogene, receptor tyrosine kinase) Δ exon 14 skipping were distributed to each participating institution. Two independent cell block specimens were validated by the University of Naples Federico II before shipment. Methodological and molecular data from reference specimens were annotated. Results: Overall, a median DNA concentration of 3.3 ng/µL (range 0.1–10.0 ng/µL) and 13.4 ng/µL (range 2.0–45.8 ng/µL) were obtained with automated and manual technical procedures, respectively. RNA concentrations of 5.7 ng/µL (range 0.2–11.9 ng/µL) and 9.3 ng/µL (range 0.5–18.0 ng/µL) were also detected. KRAS exon 2 p.G12C, EGFR exon 19 p.E736_A750del hotspot mutations, and ROS1 aberrant transcripts were identified in all tested cases, whereas 15 out of 16 (93.7%) centers detected MET exon 14 skipping mutation. Conclusions: Optimized technical workflows are crucial in the decision-making strategy of patients with NSCLC. Artificial reference specimens enable optimization of diagnostic workflows for predictive molecular analysis in routine clinical practice.
2024
2024
Lung; Molecular pathology; Tumor biomarker
Pepe, F.; Russo, G.; Venuta, A.; Scimone, C.; Nacchio, M.; Pisapia, P.; Goteri, G.; Barbisan, F.; Chiappetta, C.; Pernazza, A.; Campagna, D.; Giordano, M.; Perrone, G.; Sabarese, G.; Altimari, A.; de Biase, D.; Tallini, G.; Calistri, D.; Chiadini, E.; Capelli, L.; Santinelli, A.; Gulini, A. E.; Pierpaoli, E.; Badiali, M.; Murru, S.; Murgia, R.; Guerini Rocco, E.; Venetis, K.; Fusco, N.; Morotti, D.; Gianatti, A.; Furlan, D.; Rossi, G.; Melocchi, L.; Russo, M.; De Luca, C.; Palumbo, L.; Simonelli, S.; Maffe, A.; Francia di Celle, P.; Venesio, T.; Scatolini, M.; Grosso, E.; Orecchia, S.; Fassan, M.; Balistreri, M.; Zulato, E.; Reghellin, D.; Lazzari, E.; Santacatterina, M.; Piredda, M. L.; Riccardi, M.; Laurino, L.; Roz, E.; Longo, D.; Romeo, D. P.; Fazzari, C.; Moreno-Manuel, A.; Puglia, G. D.; Prjibelski, A. D.; Shafranskaya, D.; Righi, L.; Listi, A.; Vitale, D.; Iaccarino, A.; Malapelle, U.; Troncone, G.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11383/2167254
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