Dataset Information

State-transition modeling of blood transcriptome predicts disease evolution and treatment response in chronic myeloid leukemia.

ABSTRACT: Chronic myeloid leukemia (CML) is initiated and maintained by BCR::ABL which is clinically targeted using tyrosine kinase inhibitors (TKIs). TKIs can induce long-term remission but are also not curative. Thus, CML is an ideal system to test our hypothesis that transcriptome-based state-transition models accurately predict cancer evolution and treatment response. We collected time-sequential blood samples from tetracycline-off (Tet-Off) BCR::ABL-inducible transgenic mice and wild-type controls. From the transcriptome, we constructed a CML state-space and a three-well leukemogenic potential landscape. The potential's stable critical points defined observable disease states. Early states were characterized by anti-CML genes opposing leukemia; late states were characterized by pro-CML genes. Genes with expression patterns shaped similarly to the potential landscape were identified as drivers of disease transition. Re-introduction of tetracycline to silence the BCR::ABL gene returned diseased mice transcriptomes to a near healthy state, without reaching it, suggesting parts of the transition are irreversible. TKI only reverted the transcriptome to an intermediate disease state, without approaching a state of health; disease relapse occurred soon after treatment. Using only the earliest time-point as initial conditions, our state-transition models accurately predicted both disease progression and treatment response, supporting this as a potentially valuable approach to time clinical intervention, before phenotypic changes become detectable.

SUBMITTER: Frankhouser DE

PROVIDER: S-EPMC10997512 | biostudies-literature | 2024 Apr

REPOSITORIES: biostudies-literature

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State-transition modeling of blood transcriptome predicts disease evolution and treatment response in chronic myeloid leukemia.

Frankhouser David E DE Rockne Russell C RC Uechi Lisa L Zhao Dandan D Branciamore Sergio S O'Meally Denis D Irizarry Jihyun J Ghoda Lucy L Ali Haris H Trent Jeffery M JM Forman Stephen S Fu Yu-Hsuan YH Kuo Ya-Huei YH Zhang Bin B Marcucci Guido G

Leukemia 20240202 4

Chronic myeloid leukemia (CML) is initiated and maintained by BCR::ABL which is clinically targeted using tyrosine kinase inhibitors (TKIs). TKIs can induce long-term remission but are also not curative. Thus, CML is an ideal system to test our hypothesis that transcriptome-based state-transition models accurately predict cancer evolution and treatment response. We collected time-sequential blood samples from tetracycline-off (Tet-Off) BCR::ABL-inducible transgenic mice and wild-type controls. F ...[more]

PMID: 38307941

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Project description:BackgroundAberrant DNA methylation plays a crucial role in the progression of myeloid neoplasms. Previously, our literature reported that slit guidance ligand 2 (SLIT2) promoter methylation was associated with disease progression and indicated a poor prognosis in patients with myelodysplastic syndrome. Herein, we further investigated the clinical implications and role of SLIT2 promoter methylation in patients with chronic myeloid leukemia (CML).MethodsThe level of SLIT2 promoter methylation was determined in 104 CML patients, and its clinical significance was analyzed. Moreover, demethylation studies were performed in K562 cells to determine the epigenetic mechanism by which SLIT2 promoter methylation is regulated in CML.ResultsThe level of SLIT2 promoter methylation was similar between CML patients and controls. However, deeper analysis revealed that the SLIT2 promoter methylation level in the accelerated phase (AP) and blast crisis (BC) was markedly higher than that in the chronic phase (CP) and controls. Additionally, a marked difference was identified between the SLIT2 promoter hypermethylated and non-hypermethylated groups among CML patients grouped by clinical stage. The frequency of SLIT2 hypermethylation was markedly increased with the progression of clinical stage, that is, it was the lowest in CP samples (12/80, 15%), higher in AP samples (4/8, 50%) and the highest in BC samples (11/16, 69%). Importantly, the level/density of SLIT2 promoter methylation was significantly higher in the advanced stage than in the early stage among the 6 tested paired CML patients. Epigenetically, the expression of the SLIT2-embedded non-coding genes SLIT2-IT1 and miR-218 expression was decreased in patients with CML. SLIT2 promoter hypermethylated cases had a markedly lower SLIT2-IT1 expression level than SLIT2 promoter non-hypermethylated cases. Moreover, SLIT2-IT1 and miR-218 expression was remarkably upregulated in a dose-dependent manner after demethylation treatment of K562 cells.ConclusionsHypermethylation of the SLIT2 promoter is correlated with disease progression in CML. Furthermore, SLIT2 promoter methylation may function by regulating the expression of the SLIT2-embedded non-coding genes SLIT2-IT1 and miR-218 during CML progression.

Project description:BackgroundAcute myeloid leukemia (AML) is a highly heterogenous disease with varying clinical outcomes among patients. Epithelial-mesenchymal transition (EMT) is an important mechanism underlying cancer metastasis and chemotherapy resistance. However, few EMT-based signatures have been established to predict AML prognosis and treatment efficacy.MethodsBy conducting comparative RNA-seq analysis, we discovered the differential expression of EMT genes between AML patients with relapse and those without relapse. Based on the prognostic analysis of the differentially expressed EMT genes, a metastasis-related EMT signature (MEMTs) was constructed. An analysis was conducted on both TARGET and TCGA cohorts to explore the possible association between MEMTs and prognosis in AML. Three separate chemotherapy treatment cohorts were utilized to assess the predictive efficacy of MEMTs for chemotherapy response. In addition, the potential correlation between MEMTs and the tumor microenvironment was also investigated. Finally, random forest analysis and functional experiments were conducted to verify the key MEMTs gene associated with AML metastasis.ResultsBased on expression and prognostic analysis, we constructed MEMTs that include three EMT genes (CDH2, LOX, and COL3A1). Our findings suggested that the MEMTs could act as a prognostic factor for AML patients, and furthermore, it proved to be a predictor of their response to chemotherapy. Specifically, high MEMTs was associated with worse prognosis and poor response to chemotherapy, while low MEMTs was linked to better prognosis and higher response rates. Random forest and functional experiments demonstrate that CDH2 is a key gene promoting leukemia cell metastasis among the three MEMTs genes.ConclusionThe identification of MEMTs could potentially act as a predictor for the prognosis and the response to chemotherapy in AML patients. Individual tumor evaluation based on MEMTs could provide personalized treatment options for AML patients in the future.

Dataset Information

State-transition modeling of blood transcriptome predicts disease evolution and treatment response in chronic myeloid leukemia.

Publications

State-transition modeling of blood transcriptome predicts disease evolution and treatment response in chronic myeloid leukemia.

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