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4326 Extensive Fusion Gene Profiling in Acute Myeloid Leukemia Revealed By Whole Transcriptome Sequencing of 1614 Cases

Program: Oral and Poster Abstracts
Session: 618. Acute Myeloid Leukemias: Biomarkers and Molecular Markers in Diagnosis and Prognosis: Poster III
Hematology Disease Topics & Pathways:
Acute Myeloid Malignancies, AML, Bioinformatics, Diseases, Myeloid Malignancies, Technology and Procedures, Profiling, Molecular testing, Omics technologies
Monday, December 9, 2024, 6:00 PM-8:00 PM

Xue Chen, MD1*, Lili Yuan, MD2*, Xiaoli Ma, MD1*, Fang Wang, MD1*, Yang Zhang, MD1*, Panxiang Cao, MD2*, Jiancheng Fang, MD3*, Tong Wang, MD2*, Jiaqi Chen, PhD2*, Xiaosu Zhou, PhD4* and Hongxing Liu, MD2,5

1Department of Clinical Laboratory, Hebei Yanda Lu Daopei Hospital, Langfang, China
2Department of Laboratory Medicine, Hebei Yanda Lu Daopei Hospital, Langfang, China
3Department of Clinical Laboratory, Hebei Yanda Lu Daopei Hospital, Langfang, Hebei, China
4Precision Medicine Center, Beijing Lu Daopei Institute of Hematology, Beijing, AL, China
5Precision Medicine Center, Beijing Lu Daopei Institute of Hematology, Beijing, China

Background

Fusion genes (FGs) are critical molecular abnormalities in acute myeloid leukemia (AML), serving as vital markers for diagnosis, classification, risk stratification, and targeted therapy. In 2021, we published the FG map of acute leukemia revealed by whole transcriptome sequencing (WTS) of 1000 cases, including 539 AML patients (Blood Cancer Journal. PMID: 34135310). Building upon this initial study, we have now expanded our study to include 1614 AML cases, aiming to further elucidate the FG landscape and explore additional insights into the clinical implications of these genetic alterations.

Methods

We enrolled 1614 AML cases diagnosed in our hospital from September 2018 to April 2024, with high-quality WTS data. Among them, 356 (22%) were children (≤18 years, median age 9 years, range 3 months to 18 years), and 1258 (78%) were adults (>18 years, median age 46 years, range 19 to 89 years). We used bone marrow samples from 100 healthy donors as controls. Written informed consent was obtained from all participants or their guardians in accordance with the Declaration of Helsinki.

RNA quality assessment, sequencing library preparation, paired-end sequencing, and FGs detection were conducted as we previously reported.

High-confidence in-frame FGs detected by WTS were classified into 4 tiers based on pathogenicity. (A) pathogenic: well-known FGs or new members of common FG families (FG-FMs) with definite pathogenicity in hematological malignancies. (B) likely pathogenic: FGs reported in hematologic malignancies without functional verification, or novel FGs involving genes associated with these malignancies. (C) uncertain significance: novel FGs involving genes without known associations with these malignancies. (D) non-pathogenic: FGs found in normal samples.

Results

A total of 269 different FGs were detected in 907 AML patients, including 90 tier A, 63 tier B, 108 tier C, and 8 tier D FGs. Tier D FGs were unlikely to be pathogenic and not analyzed further.

982 fusion events (771 tier A, 97 tier B, and 114 tier C, respectively) were detected in 889 (55%) cases. Most patients (n=800; 90%) carried only one FG. Additionally, 85 cases had 2 FGs, and 4 cases had 3 FGs. Only 12 patients had coexisting two tier A FGs, accounting for 0.7% of all cases enrolled in this study and 1.3% of all positive cases.

We found 51 kinds of recurrent FGs that occurred at least twice, including 42 tier A, 4 tier B, and 5 tier C FGs, respectively. The positivity rate of FGs presented a typical long-tail distribution, with only 10 FGs having a positivity rate >1%: RUNX1::RUNX1T1 (12.2%), PML::RARA (6.9%), CBFB::MYH11 (3.7%), NUP98::NSD1 (3.5%), KMT2A::MLLT3 (3.1%), KMT2A::MLLT4 (1.9%), KMT2A::MLLT10 (1.7%), ZNF292::PNRC1(1.6%), DEK::NUP214 (1.1%), KMT2A::AFDN (1%).

Notably, a considerable number of so-far unreported FGs were detected in this study. Totally, 181 kinds of novel FGs were discovered (15 tier A, 58 tier B, and 108 tier C), accounting for 69% of all FGs. However, only 7 of them were recurrent.

We classified the 153 distinct tier A and tier B FGs according to FG-FMs, which referred to FGs that involve one protagonist gene and various fusion partners. More than half of them (99/153, 65%) could be classified into 25 FG-FMs, such as KMT2A-FM, NUP98-FM, and RUNX1-FM. When we focused on tier A FGs, 91% (82/90) could be clustered into FG-FMs, indicating the central involvement of key genes in AML pathogenesis.

Conclusion

This comprehensive analysis of 1614 AML cases using WTS provides an extensive and detailed landscape of FGs in AML. Our findings underscore the significant heterogeneity of FGs in AML, with a substantial proportion of patients harboring novel and previously unreported FGs. The identification of 269 distinct FGs, including 90 well-established pathogenic FGs, highlights the critical role of these genetic alterations in AML pathogenesis. Moreover, the classification into FG-FMs reveals the central involvement of key genes such as KMT2A, NUP98, and RUNX1 in a large proportion of pathogenic FGs. These insights not only enhance our understanding of the molecular complexity of AML but also have important implications for diagnosis, prognosis, and the development of targeted therapies. Future studies should focus on the functional validation of novel FGs and the exploration of their potential as therapeutic targets.

Disclosures: No relevant conflicts of interest to declare.

*signifies non-member of ASH