Background: Pediatric acute myeloid leukemia (pAML) is the second most common type of childhood leukemia, behind acute lymphoblastic leukemia. High-throughput technologies have enabled the identification of increasing molecular alterations linked to AML prognosis, revealing genomic heterogeneity among individual patients and providing clinically valuable diagnostic and prognostic information. This study systematically analyzed the correlation between high-frequency mutated genes and prognosis in pAML by performing whole-transcriptome sequencing (WTS) of bone marrow samples from newly diagnosed AML children in Southwest China and mapping their genetic profiles.
Methods: pAML patients treated at the Department of Hematology and Oncology, Children’s Hospital of Chongqing Medical University, from January 2015 to October 2024, were enrolled, and WTS was performed. The study described the frequency, pathogenicity classification, and risk stratification of mutation genes and fusion genes, and constructed a genetic landscape. For high-frequency pAML mutations, the impact on early induction remission rate (CR) and long-term event-free survival (EFS) was evaluated.
Results: A total of 134 pediatric AML patients from Southwest China were included, with a male-to-female ratio of 74:60 and a median diagnosis age of 5.96 years. Based on pathogenicity classification using WTS, fusion genes were categorized into level 1, level 2, and level 3 genes, as well as mutation genes. The study identified five fusion genes of level 1, the most frequent being
RUNX1::RUNX1T1 (32/134, 23.88%),
KMT2A rearrangements (29/134, 21.64%), and
CBFB::MYH11 (13/134, 9.7%). Sixteen mutation genes of level 1 were detected, seven of which recurred in over 5% of patients, including
NRAS (31/134, 23.13%),
FLT3 (25/134, 18.66%),
KIT (24/134, 17.91%),
CEBPA (14/134, 10.45%),
WT1 (13/134, 9.7%),
KRAS (11/134, 8.2%), and
PTPN11 (7/134, 5.22%). Sex-based analysis revealed that
PTPN11 mutations were significantly more frequent in males (9.45% vs. 0%,
p = 0.023), as were
KIT mutations (24.32% vs. 10.00%,
p = 0.044). Risk-stratified analysis showed that
WT1 mutations (14.13% vs. 0%,
p = 0.031) and
FLT3-ITD mutations (13.19% vs. 0%,
p = 0.042) were enriched in intermediate- and high-risk groups, whereas
CEBPA (25.64% vs. 5.43%,
p = 0.012),
KIT (35.90% vs. 10.87%,
p = 0.003), and
KIT-E8 (20.51% vs. 1.10%,
p < 0.001) mutations were more prevalent in low-risk groups. Prognostic analysis indicated that
PTPN11 and
KIT mutations did not affect CR or EFS across sexes, nor did
WT1,
CEBPA, or
KIT mutations influence outcomes by risk stratification. However,
FLT3-ITD-positive patients had significantly lower CRs (χ
2 value = 11.965,
p = 0.007), although EFS differences were nonsignificant. In contrast,
WT1 mutations were associated with inferior EFS compared to wild-type (
p = 0.036). Furthermore, the univariate and multivariate Cox regression revealed consistent results with the above findings, indicating that
WT1 mutation was an independent adverse prognostic factor for EFS (HR = 2.400, 95% CI: 1.101–5.233,
p = 0.028). The results of univariate and multivariate logistic regression analyses also confirmed that
FLT3-ITD mutation was an independent predictor of initial treatment response in our cohort (OR = 10.699, 95% CI: 2.108–54.302,
p = 0.004).
Conclusions: This study delineated the genetic landscape of pAML in Southwest China and explored the prognostic value of gene fusions and mutations in early and long-term outcomes. These findings provide a foundation for understanding the genetic heterogeneity of pAML and offer evidence for the development of precision medicine approaches.
Full article