A lot of predictive biomarkers have to be tested in advanced non-small cell lung cancer (NSCLC), like EGFR, ALK, ROS1, BRAF, RET, NTRK, and MET. According to the 2020 European Society for Medical Oncology (ESMO) guidelines, all patients with advanced adenocarcinoma of the lung should be tested for the above-reported markers, then it is clear that multi-gene approach analyses would be more cost-effective. Aim of this review is to focus on the next-generation techniques currently available for the characterization of lung tumors in clinical practice for predictive purposes. The low amount of material available from fine-needle aspiration biopsy (FNAB) specimens may be successfully overcome by implementing the simultaneous analysis of multiple biomarkers using the same analytical technique. Moreover, liquid biopsy can provide valuable material for the molecular diagnosis of lung cancer. Next-generation sequencing allows for simultaneously screening of multiple markers starting from a small amount of DNA/RNA. Digital polymerase chain reaction (dPCR) is a very highly sensitive method for the analysis of alteration both in biopsies, cytological smears, and in circulating tumor DNA from patients with NSCLC. NanoString nCounter technology is a dual-probe system that allows performing direct profiling of target nucleic acid molecules in a single reaction, without the need for retro-transcription and amplification, and with a very high degree of multiplexing. NanoString has been successfully applied in NSCLC for the detection of rearrangement. In conclusion, nowadays a lot of “next-generation tools” are available for molecular characterization of NSCLC, and the laboratories should apply the best available technique for each specific clinical question.

de Biase, D., Maloberti, T., De Leo, A., Sanza, V., Visani, M., Gruppioni, E., et al. (2022). Next-generation technologies in predictive molecular pathology of lung cancers, 7, 1-13 [10.21037/jxym-22-2].

Next-generation technologies in predictive molecular pathology of lung cancers

de Biase, Dario
;
Maloberti, Thais;De Leo, Antonio;Visani, Michela;Gruppioni, Elisa;Gelsomino, Francesco;Ferrari, Marco;Ardizzoni, Andrea;Tallini, Giovanni
2022

Abstract

A lot of predictive biomarkers have to be tested in advanced non-small cell lung cancer (NSCLC), like EGFR, ALK, ROS1, BRAF, RET, NTRK, and MET. According to the 2020 European Society for Medical Oncology (ESMO) guidelines, all patients with advanced adenocarcinoma of the lung should be tested for the above-reported markers, then it is clear that multi-gene approach analyses would be more cost-effective. Aim of this review is to focus on the next-generation techniques currently available for the characterization of lung tumors in clinical practice for predictive purposes. The low amount of material available from fine-needle aspiration biopsy (FNAB) specimens may be successfully overcome by implementing the simultaneous analysis of multiple biomarkers using the same analytical technique. Moreover, liquid biopsy can provide valuable material for the molecular diagnosis of lung cancer. Next-generation sequencing allows for simultaneously screening of multiple markers starting from a small amount of DNA/RNA. Digital polymerase chain reaction (dPCR) is a very highly sensitive method for the analysis of alteration both in biopsies, cytological smears, and in circulating tumor DNA from patients with NSCLC. NanoString nCounter technology is a dual-probe system that allows performing direct profiling of target nucleic acid molecules in a single reaction, without the need for retro-transcription and amplification, and with a very high degree of multiplexing. NanoString has been successfully applied in NSCLC for the detection of rearrangement. In conclusion, nowadays a lot of “next-generation tools” are available for molecular characterization of NSCLC, and the laboratories should apply the best available technique for each specific clinical question.
2022
de Biase, D., Maloberti, T., De Leo, A., Sanza, V., Visani, M., Gruppioni, E., et al. (2022). Next-generation technologies in predictive molecular pathology of lung cancers, 7, 1-13 [10.21037/jxym-22-2].
de Biase, Dario; Maloberti, Thais; De Leo, Antonio; Sanza, Viviana; Visani, Michela; Gruppioni, Elisa; Altimari, Annalisa; Grillini, Alessia; Gelsomin...espandi
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/887308
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