Aims: Next-generation sequencing (NGS) is becoming a new gold standard for determining molecular predictive biomarkers. This study aimed to evaluate the reliability of NGS in detecting gene fusions, focusing on comparing gene fusions with known and unknown partners. Methods: We collected all gene fusions from a consecutive case series using an amplicon-based DNA/RNA NGS platform and subdivided them into two groups: gene fusions with known partners and gene fusions with unknown partners. Gene fusions involving ALK, ROS1 and RET were also examined by immunohistochemistry (IHC) and/or fluorescent in situ hybridization (FISH). Results: Overall, 1174 malignancies underwent NGS analysis. NGS detected gene fusions in 67 cases (5.7%), further subdivided into 43 (64.2%) with known partners and 24 (35.8%) with unknown partners. Gene fusions were predominantly found in non-small cell lung carcinomas (52/67, 77.6%). Gene fusions with known partners frequently involved ALK (20/43, 46.5%) and MET (9/43, 20.9%), while gene fusions with unknown partners mostly involved RET (18/24, 75.0%). FISH/IHC confirmed rearrangement status in most (89.3%) of the gene fusions with known partners, but in only one (4.8%) of the gene fusions with unknown partners, with a significant difference (p < 0.001). In 17 patients undergoing targeted therapy, the log-rank test revealed that the overall survival was higher in the known partner group than in the unknown partner group (p = 0.002). Conclusions: NGS is a reliable method for detecting gene fusions with known partners, but it is less accurate in identifying gene fusions with unknown partners, for which further analyses (such as FISH) are required.

The role of next-generation sequencing in detecting gene fusions with known and unknown partners: a single-center experience with methodologies’ integration / Ambrosini-Spaltro A.; Farnedi A.; Calistri D.; Rengucci C.; Prisinzano G.; Chiadini E.; Capelli L.; Angeli D.; Bennati C.; Valli M.; De Luca G.; Caruso D.; Ulivi P.; Rossi G.. - In: HUMAN PATHOLOGY. - ISSN 0046-8177. - ELETTRONICO. - 123:(2022), pp. 20-30. [10.1016/j.humpath.2022.02.005]

The role of next-generation sequencing in detecting gene fusions with known and unknown partners: a single-center experience with methodologies’ integration

Farnedi A.;Prisinzano G.;Ulivi P.;
2022

Abstract

Aims: Next-generation sequencing (NGS) is becoming a new gold standard for determining molecular predictive biomarkers. This study aimed to evaluate the reliability of NGS in detecting gene fusions, focusing on comparing gene fusions with known and unknown partners. Methods: We collected all gene fusions from a consecutive case series using an amplicon-based DNA/RNA NGS platform and subdivided them into two groups: gene fusions with known partners and gene fusions with unknown partners. Gene fusions involving ALK, ROS1 and RET were also examined by immunohistochemistry (IHC) and/or fluorescent in situ hybridization (FISH). Results: Overall, 1174 malignancies underwent NGS analysis. NGS detected gene fusions in 67 cases (5.7%), further subdivided into 43 (64.2%) with known partners and 24 (35.8%) with unknown partners. Gene fusions were predominantly found in non-small cell lung carcinomas (52/67, 77.6%). Gene fusions with known partners frequently involved ALK (20/43, 46.5%) and MET (9/43, 20.9%), while gene fusions with unknown partners mostly involved RET (18/24, 75.0%). FISH/IHC confirmed rearrangement status in most (89.3%) of the gene fusions with known partners, but in only one (4.8%) of the gene fusions with unknown partners, with a significant difference (p < 0.001). In 17 patients undergoing targeted therapy, the log-rank test revealed that the overall survival was higher in the known partner group than in the unknown partner group (p = 0.002). Conclusions: NGS is a reliable method for detecting gene fusions with known partners, but it is less accurate in identifying gene fusions with unknown partners, for which further analyses (such as FISH) are required.
2022
The role of next-generation sequencing in detecting gene fusions with known and unknown partners: a single-center experience with methodologies’ integration / Ambrosini-Spaltro A.; Farnedi A.; Calistri D.; Rengucci C.; Prisinzano G.; Chiadini E.; Capelli L.; Angeli D.; Bennati C.; Valli M.; De Luca G.; Caruso D.; Ulivi P.; Rossi G.. - In: HUMAN PATHOLOGY. - ISSN 0046-8177. - ELETTRONICO. - 123:(2022), pp. 20-30. [10.1016/j.humpath.2022.02.005]
Ambrosini-Spaltro A.; Farnedi A.; Calistri D.; Rengucci C.; Prisinzano G.; Chiadini E.; Capelli L.; Angeli D.; Bennati C.; Valli M.; De Luca G.; Caruso D.; Ulivi P.; Rossi G.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/965357
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