Challenging Conventional Diagnostic Methods by Comprehensive Molecular Diagnostics: A Nationwide Prospective Comparison in Children With ALL.

Abstract

Purpose: Treatment stratification in ALL includes diverse (cyto)genetic aberrations, requiring diverse tests to yield conclusive data. We optimized the diagnostic workflow to detect all relevant aberrations with a limited number of tests in a clinically relevant time frame.

Methods: In 467 consecutive patients with ALL (0-20 years), we compared RNA sequencing (RNAseq), fluorescence in situ hybridization (FISH), reverse transcriptase polymerase chain reaction (RT-PCR), karyotyping, single-nucleotide polymorphism (SNP) array, and multiplex ligation-dependent probe amplification (MLPA) for technical success, concordance of results, and turnaround time.

Results: To detect stratifying fusions (ETV6::RUNX1, BCR::ABL1, ABL-class, KMT2Ar, TCF3::HLF, IGH::MYC), RNAseq and FISH were conclusive for 97% and 96% of patients, respectively, with 99% concordance. RNAseq performed well in samples with a low leukemic cell percentage or low RNA quality. RT-PCR for six specific fusions was conclusive for >99% but false-negative for six patients with alternatively fused exons. RNAseq also detected gene fusions not yet used for stratification in 14% of B-cell precursor-ALL and 33% of T-ALL. For aneuploidies and intrachromosomal amplification of chromosome 21, SNP array gave a conclusive result in 99%, thereby outperforming karyotyping, which was conclusive for 64%. To identify deletions in eight stratifying genes/regions, SNP array was conclusive in 99% and MLPA in 95% of patients, with 98% concordance. The median turnaround times were 10 days for RNAseq, 9 days for FISH, 10 days for SNP array, and <7 days for MLPA and RT-PCR in this real-world prospective study.

Conclusion: Combining RNAseq and SNP array outperformed current diagnostic tools to detect all stratifying genetic aberrations in ALL. The turnaround time is <15 days matching major treatment decision time points. Moreover, combining RNAseq and SNP array has the advantage of detecting new lesions for studies on prognosis and pathobiology.