Comparison of Multiple Clinical Testing Modalities for Assessment of NPM1-Mutant AML.

Background: mutation status can influence prognosis and management in AML. Accordingly, clinical testing (i.e., RT-PCR, NGS and IHC) for mutant is increasing in order to detect residual disease in AML, alongside flow cytometry (FC). However, the relationship of the results from RT-PCR to traditional NGS, IHC and FC is not widely known among many practitioners. Herein, we aim to: i) describe the performance of RT-PCR compared to traditional NGS and IHC for the detection of mutant in clinical practice, and also compare it to FC, and ii) provide our observations regarding the advantages and disadvantages of each approach in order to inform future clinical testing algorithms.

Methods: Peripheral blood and bone marrow samples collected for clinical testing at variable time points during patient management were tested by quantitative, real-time, RT-PCR and results were compared to findings from a Myeloid NGS panel, mutant NPM1 IHC and FC.

Results: RT-PCR showed superior sensitivity compared to NGS, IHC and FC with the main challenge of NGS, IHC and FC being the ability to identify a low disease burden (<0.5% NCN by RT-PCR). Nevertheless, the positive predictive value of NGS, IHC and FC were each ≥ 80% indicating that positive results by those assays are typically associated with RT-PCR positivity. IHC, unlike bulk methods (RT-PCR, NGS and FC), is able provide information regarding cellular/architectural context of disease in biopsies. FC did not identify any -mutated residual disease not already detected by RT-PCR, NGS or IHC.

Conclusion: Overall, our findings demonstrate that RT-PCR shows superior sensitivity compared to a traditional Myeloid NGS, suggesting the need for "deep-sequencing" NGS panels for NGS-based monitoring of residual disease in -mutant AML. IHC provides complementary cytomorphologic information to RT-PCR. Lastly, FC may not be necessary in the setting of post-therapy follow up for -mutated AML. Together, these findings can help inform future clinical testing algorithms.