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1569 A 46 Long Non-Coding RNAs Expression Signature Accurately Predicts Relapse and Acts As an Independent Prognostic Factor in Pediatric Acute Myeloid Leukemia

Program: Oral and Poster Abstracts
Session: 617. Acute Myeloid Leukemias: Biomarkers, Molecular Markers and Minimal Residual Disease in Diagnosis and Prognosis: Poster I
Saturday, December 9, 2023, 5:30 PM-7:30 PM

Zhiyao Ren, MD1,2,3*, Jolien Vanhooren1,2,3*, Charlotte Derpoorter1,2,3*, Barbara De Moerloose2,3,4* and Tim Lammens, PhD, MSc2,3,5*

1Department of Pediatric Hematology-Oncology and Stem Cell Transplantation, Ghent University Hospital, Ghent, Belgium
2Cancer Research Institute Ghent (CRIG), Ghent, Belgium
3Department of Internal Medicine and Pediatrics, Ghent University, Ghent, Belgium
4Ghent University Hospital, Ghent, Belgium
5Department of Pediatric Hematology-Oncology and Stem Cell Transplantation, Ghent University Hospital, Ghent, Oost-Vlaanderen, Belgium

Risk stratification using cytogenetics, mutations and minimal residual disease (MRD) has allowed to increase the cure rates of pediatric acute myeloid leukemia (AML), reaching now up to 70% in contemporary protocols. Nevertheless, approximately 30% of patients still experience relapse, indicating that there is a need to optimize stratification strategies. Recently, long non-coding RNA (lncRNA) expression has been shown to hold prognostic power in multiple cancer types. Here, we built a 46 relapse-related lncRNAs prognostic signature, named AMLlnc46, using 790 pediatric acute myeloid leukemia transcriptomes obtained from the Therapeutically Applicable Research To Generate Effective Treatments (TARGET) repository. Bootstrap validation (bootstrap resampling times = 1000) was used for internal validation and showed that the signature performed good in predicting the 1-, 2-, and 3-year relapse-free survival (RFS), with an area under the curve of 0.825, 0.824, and 0.822, respectively. Moreover, external validation using the TARGET repository validated the efficiency of the signature. Most importantly, we demonstrate that AMLlnc46 not only is an independent predictor of RFS, but also identifies patients who were assigned a different risk-group by currently-used classification methods. In conclusion, the identified AMLlnc46 might, after further prospective validation, provide additional information to guide management of pediatric AML patients.

Figure 1. (A) Kaplan–Meier survival curve of relapse-free survival of high-and-low risk AMLlnc46 pediatric AML patients, (B) Univariate and multivariate independent Cox regression analyses of known clinical and molecular characteristics and the AMLlnc46 signature.

Disclosures: No relevant conflicts of interest to declare.

*signifies non-member of ASH