{Reference Type}: Journal Article
{Title}: Genomic mutation patterns and prognostic value in de novo and secondary acute myeloid leukemia: A multicenter study from China.
{Author}: Dou X;Dan C;Zhang D;Zhou H;He R;Zhou G;Zhu Y;Fu N;Niu B;Xu S;Liao Y;Luo Z;Yang L;Zhang H;Xu Y;Zhan Q;Chen W;Yang Z;Tang X;Zhang H;Xiao Q;Chen J;Liu L;Wang Y;Pei L;Wang L;
{Journal}: Int J Cancer
{Volume}: 0
{Issue}: 0
{Year}: 2024 Aug 7
{Factor}: 7.316
{DOI}: 10.1002/ijc.35125
{Abstract}: Acute myeloid leukemia (AML) can manifest as de novo AML (dn-AML) or secondary AML (s-AML), with s-AML being associated with inferior survival and distinct genomic characteristics. The underlying reasons for this disparity remain to be elucidated. In this multicenter study, next-generation sequencing (NGS) was employed to investigate the mutational landscape of AML in 721 patients from June 2020 to May 2023.Genetic mutations were observed in 93.34% of the individuals, with complex variations (more than three gene mutations) present in 63.10% of them. TET2, ASXL1, DNMT3A, TP53 and SRSF2 mutations showed a higher prevalence among older individuals, whereas WT1 and KIT mutations were more commonly observed in younger patients. BCOR, BCORL1, ZRSR2, ASXL1 and SRSF2 exhibited higher mutation frequencies in males. Additionally, ASXL1, NRAS, PPMID, SRSF2, TP53 and U2AF1 mutations were more common in patients with s-AML, which PPM1D was more frequently associated with therapy-related AML (t-AML). Advanced age and hyperleukocytosis independently served as adverse prognostic factors for both types of AML; however, s-AML patients demonstrated a greater number of monogenic adverse prognostic factors compared to dn-AML cases (ASXL1, PPM1D, TP53 and U2AF1 in s-AML vs. FLT3, TP53 and U2AF1 in dn-AML). Age and sex-related gene mutations suggest epigenetic changes may be key in AML pathogenesis. The worse prognosis of s-AML compared to dn-AML could be due to the older age of s-AML patients and more poor-prognosis gene mutations. These findings could improve AML diagnosis and treatment by identifying potential therapeutic targets and risk stratification biomarkers.