The 17‐gene stemness score associates with relapse risk and long‐term outcomes following allogeneic haematopoietic cell transplantation in acute myeloid leukaemia

Abstract

A 17-gene stemness (LSC17) score determines risk in acute myeloid leukaemia patients treated with standard chemotherapy regimens. The present study further analysed the impact of the LSC17 score at diagnosis on outcomes following allogeneic haematopoietic cell transplantation (HCT). Out of 452 patients with available LSC17 score, 123 patients received allogeneic HCT. Transplant outcomes, including overall (OS), leukaemia-free survival (LFS), relapse incidence (RI) and non-relapse mortality (NRM), were compared according to the LSC17 scored group. The patients with a low LSC17 score had higher OS (56.2%) and LFS (54.4%) at 2 years compared to patients

Identification of a Complex Karyotype Signature with Clinical Implications in AML and MDS-EB Using Gene Expression Profiling

“…As the prognostic impact of CKS was evaluated, we further performed a comparison between CKS and previously developed models, namely, LSC17 score and APS, in the prediction of outcomes in patients with AML. The LSC17 score is a model based on the expression of 17 leukemic stem cell-enriched genes and accurately predicts poor prognosis in patients with AML [18,19,37,38]. APS is a 16-gene expression signature model developed to improve risk stratification of patients with AML [17].…”

“…Extensive transcriptomic analyses of myeloid neoplasms for the development of prognostic gene expression signatures have been beneficial in prognosis prediction and the detection of potential actionable targets [15][16][17][18][19][20][21]. However, transcriptomic analyses of prognostic gene expression signatures in myeloid neoplasms with specific cytogenetic abnormalities, particularly the CK subgroup, have rarely been conducted [17][18][19][20][21][22].…”

“…Extensive transcriptomic analyses of myeloid neoplasms for the development of prognostic gene expression signatures have been beneficial in prognosis prediction and the detection of potential actionable targets [15][16][17][18][19][20][21]. However, transcriptomic analyses of prognostic gene expression signatures in myeloid neoplasms with specific cytogenetic abnormalities, particularly the CK subgroup, have rarely been conducted [17][18][19][20][21][22]. While the resolution of CK detection using gene expression signatures may be lower than conventional copy number variation detection methods such as SNP array, implementation of CK gene signature have the potential to add to the understanding of the impact of fusion transcript as well as the copy number variations associated with CK.…”