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The clinical significance of small TP53 clones detected with next generation sequencing (NGS) in chronic lymphocytic leukemia is an issue of active debate. According to the official guidelines, treatment decisions should be guided only by variants with variant allele frequency (VAF) ≥10%. We present data on 325 consecutive patients with chronic lymphocytic leukemia analyzed with NGS. In total 47 pathogenic/likely pathogenic (P/LP), TP53 variants were detected in 26 patients (8%). Eleven of these (23%) were in the 5% to 10% VAF range and reported according to our institutional policy. All TP53 variants in the 5% to 10% VAF range were confirmed (100% concordance) with a second NGS panel. Our results where further validated with the performance of Sanger sequencing and digital droplet PCR (ddPCR). In 12 patients with available fluorescence in situ hybridization data and TP53 mutations within 5% to 10% VAF, deletion of chromosome 17p (del(17p)) was detectable in only 1 patient. We propose a robust diagnostic algorithm, which allows the safe detection and reporting of TP53 variants with VAF down to 5% in the clinical setting. Our study provides evidence that NGS is equally potent to detect variants with VAF 5% to 10% compared to those with VAF 10% to 15%, highlighting the urgent need for harmonization of NGS methodologies across diagnostic laboratories.

Objective: The aim of this project was to implement long-read sequencing for BCR-ABL1 TKI resistance mutation screening in a clinical setting for patients undergoing treatment for chronic myeloid leukemia. Materials and Methods: Processes were established for registering and transferring samples from the clinic to an academic sequencing facility for long-read sequencing. An automated analysis pipeline for detecting mutations was established, and an information system was implemented comprising features for data management, analysis and visualization. Clinical validation was performed by identifying BCR-ABL1 TKI resistance mutations by Sanger and long-read sequencing in parallel. The developed software is available as open source via GitHub at https://github.com/pharmbio/clamp Results: The information system enabled traceable transfer of samples from the clinic to the sequencing facility, robust and automated analysis of the long-read sequence data, and communication of results from sequence analysis in a reporting format that could be easily interpreted and acted upon by clinical experts. In a validation study, all 17 resistance mutations found by Sanger sequencing were also detected by long-read sequencing. An additional 16 mutations were found only by long-read sequencing, all of them with frequencies below the limit of detection for Sanger sequencing. The clonal distributions of co-existing mutations were automatically resolved through the long-read data analysis. After the implementation and validation, the clinical laboratory switched their routine protocol from using Sanger to long-read sequencing for this application. Conclusions: Long-read sequencing delivers results with higher sensitivity compared to Sanger sequencing and enables earlier detection of emerging TKI resistance mutations. The developed processes, analysis workflow, and software components lower barriers for adoption and could be extended to other applications.