Results from a multi-center study show that next-generation sequencing (NGS) more accurately illustrates BCR-ABL1 mutation status than Sanger sequencing in patients with chronic myeloid leukemia (CML) who are not responding to tyrosine kinase inhibitor (TKI) therapy (Blood. 2020;135[8]:534-541).

“Although Sanger sequencing…is considered the gold standard for BCR-ABL1 KD mutation screening, [NGS] has recently been assessed in retrospective studies,” according to Simona Soverini, PhD, Department of Experimental, Diagnostic and Specialty Medicine, Institute of Hematology, University of Bologna, Italy, and co-investigators.

Seeking to evaluate the incidence and clinical relevance of low-level mutations as well as the feasibility, cost, and turnaround times of NGS-based BCR-ABL1 mutation screening in a routine setting, Dr Soverini et al conducted the prospective, multi-center NEXT-in-CML study.

In 1 of 4 reference laboratories, Sanger sequencing and NGS were used to analyze 236 consecutive patients with CML not responding (n = 124) or yielding warning responses (n = 112) to TKI therapy.

Among 51 patients deemed negative for mutations by Sanger sequencing, low-level mutations were detectable via NGS. Additional low-level mutations were detected in 29 of 60 patients who tested positive for mutations via Sanger sequencing.

Overall, this meant that mutations that couldn’t not detected via Sanger sequencing were identified in 80 (34%) of 236 patients through NGS; 42 (18%) of these patients had low-level mutations that affected clinical decision-making in some way.

“Prospective monitoring of mutation kinetics demonstrated that TKI-resistant low-level mutations are invariably selected if the patients are not switched to another TKI or if they are switched to a inappropriate TKI or TKI dose,” Dr Soverini and colleagues said.

“The NEXT-in-CML study provides for the first time robust demonstration of the clinical relevance of low-level mutations, supporting the incorporation of NGS-based BCR-ABL1 KD mutation screening results in the clinical decision algorithms,” they concluded.—Hina Porcelli