Dataset Information

Leukemic stem cell phenotype is associated with mutational profile in acute myeloid leukemia.

ABSTRACT:

Background/aims

Understanding leukemic stem cell (LSC) is important for acute myeloid leukemia (AML) treatment. However, association of LSC with patient prognosis and genetic information in AML patients is unclear.

Methods

Here we investigated the associations between genetic information and the various LSC phenotypes, namely multipotent progenitor (MPP)-like, lymphoid primed multipotent progenitor (LMPP)-like and granulocyte-macrophage progenitors (GMP)-like LSC in 52 AML patients.

Results

In secondary AML patients, MPP-like LSC was significantly higher than de novo AML (p = 0.0037). The proportion of MPP-like LSC was especially high in post-myeloproliferative neoplasm AML (p = 0.0485). There was no correlation between age and LSC phenotype. Mutations of KRAS and NRAS were observed in MPP-like LSC dominant patients, TP53 and ASXL1 mutations in LMPP-like LSC dominant patients, and CEBPA, DNMT3A and IDH1 mutations in GMP-like LSC dominant patients. Furthermore, KRAS mutation was significantly associated with MPP-like LSC expression (p = 0.0540), and TP53 mutation with LMPP-like LSC expression (p = 0.0276). When the patients were separated according to the combined risk including next generation sequencing data, the poorer the prognosis, the higher the LMPP-like LSC expression (p = 0.0052). This suggests that the dominant phenotype of LSC is one of the important factors in predicting the prognosis and treatment of AML.

Conclusion

LSC phenotype in AML is closely associated with the recurrent mutations which has prognostic implication. Further research to confirm the meaning of LSC phenotype in the context of genetic aberration is warranted.

SUBMITTER: Han H

PROVIDER: S-EPMC7969060 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:IntroductionTreatment failure in acute myeloid leukemia is probably caused by the presence of leukemia initiating cells, also referred to as leukemic stem cells, at diagnosis and their persistence after therapy. Specific identification of leukemia stem cells and their discrimination from normal hematopoietic stem cells would greatly contribute to risk stratification and could predict possible relapses.ResultsFor identification of leukemic stem cells, we developed flow cytometric methods using leukemic stem cell associated markers and newly-defined (light scatter) aberrancies. The nature of the putative leukemic stem cells and normal hematopoietic stem cells, present in the same patient's bone marrow, was demonstrated in eight patients by the presence or absence of molecular aberrancies and/or leukemic engraftment in NOD-SCID IL-2R?-/- mice. At diagnosis (n=88), the frequency of the thus defined neoplastic part of CD34+CD38- putative stem cell compartment had a strong prognostic impact, while the neoplastic parts of the CD34+CD38+ and CD34- putative stem cell compartments had no prognostic impact at all. After different courses of therapy, higher percentages of neoplastic CD34+CD38- cells in complete remission strongly correlated with shorter patient survival (n=91). Moreover, combining neoplastic CD34+CD38- frequencies with frequencies of minimal residual disease cells (n=91), which reflect the total neoplastic burden, revealed four patient groups with different survival.Conclusion and perspectiveDiscrimination between putative leukemia stem cells and normal hematopoietic stem cells in this large-scale study allowed to demonstrate the clinical importance of putative CD34+CD38- leukemia stem cells in AML. Moreover, it offers new opportunities for the development of therapies directed against leukemia stem cells, that would spare normal hematopoietic stem cells, and, moreover, enables in vivo and ex vivo screening for potential efficacy and toxicity of new therapies.

Project description:ContextIn many cancers, specific subpopulations of cells appear to be uniquely capable of initiating and maintaining tumors. The strongest support for this cancer stem cell model comes from transplantation assays in immunodeficient mice, which indicate that human acute myeloid leukemia (AML) is driven by self-renewing leukemic stem cells (LSCs). This model has significant implications for the development of novel therapies, but its clinical relevance has yet to be determined.ObjectiveTo identify an LSC gene expression signature and test its association with clinical outcomes in AML.Design, setting, and patientsRetrospective study of global gene expression (microarray) profiles of LSC-enriched subpopulations from primary AML and normal patient samples, which were obtained at a US medical center between April 2005 and July 2007, and validation data sets of global transcriptional profiles of AML tumors from 4 independent cohorts (n = 1047).Main outcome measuresIdentification of genes discriminating LSC-enriched populations from other subpopulations in AML tumors; and association of LSC-specific genes with overall, event-free, and relapse-free survival and with therapeutic response.ResultsExpression levels of 52 genes distinguished LSC-enriched populations from other subpopulations in cell-sorted AML samples. An LSC score summarizing expression of these genes in bulk primary AML tumor samples was associated with clinical outcomes in the 4 independent patient cohorts. High LSC scores were associated with worse overall, event-free, and relapse-free survival among patients with either normal karyotypes or chromosomal abnormalities. For the largest cohort of patients with normal karyotypes (n = 163), the LSC score was significantly associated with overall survival as a continuous variable (hazard ratio [HR], 1.15; 95% confidence interval [CI], 1.08-1.22; log-likelihood P <.001). The absolute risk of death by 3 years was 57% (95% CI, 43%-67%) for the low LSC score group compared with 78% (95% CI, 66%-86%) for the high LSC score group (HR, 1.9 [95% CI, 1.3-2.7]; log-rank P = .002). In another cohort with available data on event-free survival for 70 patients with normal karyotypes, the risk of an event by 3 years was 48% (95% CI, 27%-63%) in the low LSC score group vs 81% (95% CI, 60%-91%) in the high LSC score group (HR, 2.4 [95% CI, 1.3-4.5]; log-rank P = .006). In multivariate Cox regression including age, mutations in FLT3 and NPM1, and cytogenetic abnormalities, the HRs for LSC score in the 3 cohorts with data on all variables were 1.07 (95% CI, 1.01-1.13; P = .02), 1.10 (95% CI, 1.03-1.17; P = .005), and 1.17 (95% CI, 1.05-1.30; P = .005).ConclusionHigh expression of an LSC gene signature is independently associated with adverse outcomes in patients with AML.

Project description:Background: Previous studies have reported that genes highly expressed in leukemic stem cells (LSC) may dictate the survival probability of patients and expression-based cellular deconvolution may be informative in forecasting prognosis. However, whether the prognosis of acute myeloid leukemia (AML) can be predicted using gene expression and deconvoluted cellular abundances is debatable. Methods: Nine different cell-type abundances of a training set composed of the AML samples of 422 patients, were used to build a model for predicting prognosis by least absolute shrinkage and selection operator Cox regression. This model was validated in two different validation sets, TCGA-LAML and Beat AML (n = 179 and 451, respectively). Results: We introduce a new prognosis predicting model for AML called the LSC activity (LSCA) score, which incorporates the abundance of 5 cell types, granulocyte-monocyte progenitors, common myeloid progenitors, CD45RA + cells, megakaryocyte-erythrocyte progenitors, and multipotent progenitors. Overall survival probabilities between the high and low LSCA score groups were significantly different in TCGA-LAML and Beat AML cohorts (log-rank p-value = 3.3×10-4 and 4.3×10-3, respectively). Also, multivariate Cox regression analysis on these two validation sets shows that LSCA score is independent prognostic factor when considering age, sex, and cytogenetic risk (hazard ratio, HR = 2.17; 95% CI 1.40-3.34; p < 0.001 and HR = 1.20; 95% CI 1.02-1.43; p < 0.03, respectively). The performance of the LSCA score was comparable to other prognostic models, LSC17, APS, and CTC scores, as indicated by the area under the curve. Gene set variation analysis with six LSC-related functional gene sets indicated that high and low LSCA scores are associated with upregulated and downregulated genes in LSCs. Conclusion: We have developed a new prognosis prediction scoring system for AML patients, the LSCA score, which uses deconvoluted cell-type abundance only.