Properties of Leukemic Stem Cells in Regulating Drug Resistance in Acute and Chronic Myeloid Leukemias

Bone Marrow CD34+/lin- Cells of Patients with Chronic-Phase Chronic Myeloid Leukemia (CP-CML) After 12 Months of Nilotinib Treatment Exhibit a Different Gene Expression Signature Compared to the Diagnosis and the Corresponding Cells from Healthy Subjects

BACKGROUND

Chronic-Phase Chronic Myeloid Leukemia (C-PCML) is defined by the presence of the BCR-ABL1 fusion gene, which encodes a tyrosine kinase protein that drives the uncontrolled proliferation and survival of leukemic stem cells (LSCs). Nilotinib, a tyrosine kinase inhibitor, targets the activity of BCR-ABL1 by reducing aberrant signaling pathways, which drive the regeneration of LSCs. Despite nilotinib's action, a population of resilient LSCs persist in the bone marrow (BM) and can indeed drive relapse and progression in CML patients.

METHODS

Our study investigated the gene expression profiling (GEP) of BM CD34+/lin- cells from 79 CP-CML patients at diagnosis, compared to the BM CD34+/lin- cells from the same patients after 12 months of nilotinib treatment and to the normal counterpart cells from 10 donors (CTRLs).

RESULTS

GEP analyses identified 3012 significantly differentially expressed genes across these comparisons. Among these, we focused on certain key genes associated with eight crucial KEGG pathways: CML, cell cycle, JAK-STAT, PI3K-Akt, MAPK, Ras, NF-kB, and ABC transporters. Within these pathways, we observed the up-regulation of several genes at diagnosis compared to both 12 months of nilotinib treatment and the CTRLs.

CONCLUSIONS

We observed that certain transcriptome features present at diagnosis persisted after 12 months of nilotinib treatment, compared to CTRLs. This suggests that nilotinib may exert selective pressure, potentially supporting the survival and self-renewal of LSCs. Future insights into these pathways could help identify therapeutic targets to improve outcomes in CML.

Clinical Insights into Structure, Regulation, and Targeting of ABL Kinases in Human Leukemia

Chronic myeloid leukemia is a multistep, multi-lineage myeloproliferative disease that originates from a translocation event between chromosome 9 and chromosome 22 within the hematopoietic stem cell compartment. The resultant fusion protein BCR::ABL1 is a constitutively active tyrosine kinase that can phosphorylate multiple downstream signaling molecules to promote cellular survival and inhibit apoptosis. Currently, tyrosine kinase inhibitors (TKIs), which impair ABL1 kinase activity by preventing ATP entry, are widely used as a successful therapeutic in CML treatment. However, disease relapses and the emergence of resistant clones have become a critical issue for CML therapeutics. Two main reasons behind the persisting obstacles to treatment are the acquired mutations in the ABL1 kinase domain and the presence of quiescent CML leukemia stem cells (LSCs) in the bone marrow, both of which can confer resistance to TKI therapy. In this article, we systemically review the structural and molecular properties of the critical domains of BCR::ABL1 and how understanding the essential role of BCR::ABL1 kinase activity has provided a solid foundation for the successful development of molecularly targeted therapy in CML. Comparison of responses and resistance to multiple BCR::ABL1 TKIs in clinical studies and current combination treatment strategies are also extensively discussed in this article.

Cellular abundance-based prognostic model associated with deregulated gene expression of leukemic stem cells in acute myeloid leukemia

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.