[Using next generation sequencing technology to analyze gene mutations in patients with acute myeloid leukemia and the impact on prognosis]

RNA sequencing of myeloid sarcoma, shed light on myeloid sarcoma stratification

BACKGROUND

Myeloid sarcoma (MS) is a rare, extramedullary tumor consisting of myeloid blasts. Little is known about the genetic background of MS and the prognostic value of genetic abnormalities in MS. In particular, the broad variety of gene fusions that occur in MS is marginally covered by traditional testing methods due to lack of fresh tumor specimens.

METHODS

Here, we analyzed the clinical and genetic features of 61 MS cases. We performed RNA sequencing (RNA-seq) on formalin-fixed paraffin-embedded (FFPE) or fresh samples to analyze fusion genes in 26 cases. In addition, we performed genetic abnormalities-based risk stratification using fusion genes and gene mutations.

RESULTS

A total of 305 fusion genes were identified in 22 cases, including the following five recurrent fusion genes: RUNX1-RUNX1T1, CBFβ-MYH11, ETV6-MECOM, FUS-ERG, and PICALM-MLLT10. The prognosis in the adverse-risk group was significantly worse than that in the favorable/intermediate-risk group (median survival: 12 months vs. not reached; p = 0.0004).

CONCLUSION

These results indicated the efficacy of RNA-seq using FFPE-derived RNA as a clinical routine for detecting fusion genes, which can be used as markers for risk stratification in MS.

A Predictor Combining Clinical and Genetic Factors for AML1-ETO Leukemia Patients

Core Binding Factor (CBF)-AML is one of the most common somatic mutations in acute myeloid leukemia (AML). t(8;21)/AML1-ETO-positive acute myeloid leukemia accounts for 5-10% of all AMLs. In this study, we consecutively included 254 AML1-ETO patients diagnosed and treated at our institute from December 2009 to March 2020, and evaluated molecular mutations by 185-gene NGS platform to explore genetic co-occurrences with clinical outcomes. Our results showed that high KIT VAF(≥15%) correlated with shortened overall survival compared to other cases with no KIT mutation (3-year OS rate 26.6% vs 59.0% vs 69.6%, HR 1.50, 95%CI 0.78-2.89, P=0.0005). However, no difference was found in patients’ OS whether they have KIT mutation in two or three sites. Additionally, we constructed a risk model by combining clinical and molecular factors; this model was validated in other independent cohorts. In summary, our study showed that c-kit other than any other mutations would influence the OS in AML1-ETO patients. A proposed predictor combining both clinical and genetic factors is applicable to prognostic prediction in AML1-ETO patients.