scholarly journals Single cell sequencing reveals cell populations that predict primary resistance to imatinib in chronic myeloid leukemia

Aging ◽  
2020 ◽  
Author(s):  
Weilong Zhang ◽  
Beibei Yang ◽  
Linqian Weng ◽  
Jiangtao Li ◽  
Jiefei Bai ◽  
...  
Keyword(s):  
Chronic Myeloid Leukemia ◽  
Single Cell ◽  
Myeloid Leukemia ◽  
Cell Populations ◽  
Primary Resistance ◽  
Single Cell Sequencing

Characteristics of BCR/ABL1 kinase domain mutations in the patients with chronic myeloid leukemia who are primary resistant to the imatinib therapy

2019 ◽  
Vol 11 (1) ◽  
pp. 27-33
Author(s):  
I Dmytrenko ◽  
J Minchenko ◽  
I Dyagil
Keyword(s):  
Overall Survival ◽  
Chronic Myeloid Leukemia ◽  
Tyrosine Kinase ◽  
Myeloid Leukemia ◽  
High Efficiency ◽  
Kinase Domain ◽  
Imatinib Therapy ◽  
Missense Mutations ◽  
Primary Resistance ◽  
Kinase Domain Mutations

The chronic myeloid leukemia (CML) development is associated with the formation of the BCR/ABL1 fusion gene and the BCR/ABL1 protein with increased tyrosine kinase activity. Despite the high efficiency of targeted therapy, up to 30% of patients do not respond on such therapy i.e. are primary resistant. The presence of BCR/ABL1 kinase domain mutations is considered to be one of the reasons of tyrosin kinase inhibitors resistance. To evaluate the frequency of BCR/ABL1 kinase domain mutations in Ukrainian cohort of CML patients with primary resistance to imatinib therapy, we retrospectively studied BCR/ABL1 kinase domain mutations in peripheral blood of 107 CML patients. The nucleotide sequence was determined by direct sequencing by Sanger. Mutations were reported in 45 of 107 (41.7%) CML patients. Two mutations at a time were revealed in 8 patients. So a total of 53 mutations were found out. Among them 49 were missense-mutations and 4 - deletions of different regions of the BCR/ABL1 kinase domain gene. The missense-mutations F359I/V (12 patients), T315I (8 patients) and G250E (6 patients) were most common. By localization, the mutations majority (23 of 53) was in the P-loop, 10 mutations - in the contact site, 13 mutations - in the catalytic domain and 6 – in the A-loop. Of the detected mutations, 26 (49%) resulted in a disruption of the hydrogen bond between BCR/ABL1-tyrosine kinase and imatinib. Significant reduction in overall survival was found in patients with BCR/ABL1 kinase domain mutations compared with patients with wild-type of BCR/ABL1 gene (p=0.018). The estimated 3-year overall survival was 83.4% (95% CI: 77.0%-89.8%) and 94.3% (95% CI: 91.0%-97.3%), respectively. Therefore, mutations of the BCR/ABL1 kinase domain are one of the mechanisms of primary resistance in CML patients on imatinib therapy. The occurrence of BCR/ABL1 gene mutations impairs the prognosis of imatinib therapy response.

scholarly journals Single-Cell Sequencing: Biological Insight and Potential Clinical Implications in Pediatric Leukemia

Cancers ◽  
2021 ◽  
Vol 13 (22) ◽  
pp. 5658
Author(s):  
Donát Alpár ◽  
Bálint Egyed ◽  
Csaba Bödör ◽  
Gábor T. Kovács
Keyword(s):  
High Resolution ◽  
Single Cell ◽  
Childhood Leukemia ◽  
Clinical Decision Making ◽  
Cellular Heterogeneity ◽  
Therapeutic Interventions ◽  
Cell Populations ◽  
Pediatric Leukemia ◽  
Single Cell Sequencing ◽  
Wide Range

Single-cell sequencing (SCS) provides high-resolution insight into the genomic, epigenomic, and transcriptomic landscape of oncohematological malignancies including pediatric leukemia, the most common type of childhood cancer. Besides broadening our biological understanding of cellular heterogeneity, sub-clonal architecture, and regulatory network of tumor cell populations, SCS can offer clinically relevant, detailed characterization of distinct compartments affected by leukemia and identify therapeutically exploitable vulnerabilities. In this review, we provide an overview of SCS studies focused on the high-resolution genomic and transcriptomic scrutiny of pediatric leukemia. Our aim is to investigate and summarize how different layers of single-cell omics approaches can expectedly support clinical decision making in the future. Although the clinical management of pediatric leukemia underwent a spectacular improvement during the past decades, resistant disease is a major cause of therapy failure. Currently, only a small proportion of childhood leukemia patients benefit from genomics-driven therapy, as 15–20% of them meet the indication criteria of on-label targeted agents, and their overall response rate falls in a relatively wide range (40–85%). The in-depth scrutiny of various cell populations influencing the development, progression, and treatment resistance of different disease subtypes can potentially uncover a wider range of driver mechanisms for innovative therapeutic interventions.

scholarly journals Mechanisms of Disease Progression and Resistance to Tyrosine Kinase Inhibitor Therapy in Chronic Myeloid Leukemia: An Update

2019 ◽  
Vol 20 (24) ◽  
pp. 6141 ◽  
Author(s):  
Luana Bavaro ◽  
Margherita Martelli ◽  
Michele Cavo ◽  
Simona Soverini
Keyword(s):  
Chronic Myeloid Leukemia ◽  
Tyrosine Kinase ◽  
Disease Progression ◽  
Myeloid Leukemia ◽  
Kinase Inhibitors ◽  
Kinase Inhibitor ◽  
Fusion Gene ◽  
Primary Resistance ◽  
Secondary Resistance ◽  
Dismal Prognosis

Chronic myeloid leukemia (CML) is characterized by the presence of the BCR-ABL1 fusion gene, which encodes a constitutive active tyrosine kinase considered to be the pathogenic driver capable of initiating and maintaining the disease. Despite the remarkable efficacy of tyrosine kinase inhibitors (TKIs) targeting BCR-ABL1, some patients may not respond (primary resistance) or may relapse after an initial response (secondary resistance). In a small proportion of cases, development of resistance is accompanied or shortly followed by progression from chronic to blastic phase (BP), characterized by a dismal prognosis. Evolution from CP into BP is a multifactorial and probably multistep phenomenon. Increase in BCR-ABL1 transcript levels is thought to promote the onset of secondary chromosomal or genetic defects, induce differentiation arrest, perturb RNA transcription, editing and translation that together with epigenetic and metabolic changes may ultimately lead to the expansion of highly proliferating, differentiation-arrested malignant cells. A multitude of studies over the past two decades have investigated the mechanisms underlying the closely intertwined phenomena of drug resistance and disease progression. Here, we provide an update on what is currently known on the mechanisms underlying progression and present the latest acquisitions on BCR-ABL1-independent resistance and leukemia stem cell persistence.

scholarly journals Clonal Architecture of Secondary Acute Myeloid Leukemia Defined by Single-Cell Sequencing

PLoS Genetics ◽  
2014 ◽  
Vol 10 (7) ◽  
pp. e1004462 ◽  
Author(s):  
Andrew E. O. Hughes ◽  
Vincent Magrini ◽  
Ryan Demeter ◽  
Christopher A. Miller ◽  
Robert Fulton ◽  
...  
Keyword(s):  
Acute Myeloid Leukemia ◽  
Single Cell ◽  
Myeloid Leukemia ◽  
Single Cell Sequencing ◽  
Clonal Architecture ◽  
Secondary Acute Myeloid Leukemia ◽  
Acute Myeloid

scholarly journals Computational reconstruction of clonal hierarchies from bulk sequencing data of acute myeloid leukemia samples

2021 ◽  
Author(s):  
Thomas Stiehl ◽  
Anna Marciniak-Czochra
Keyword(s):  
Acute Myeloid Leukemia ◽  
Single Cell ◽  
Myeloid Leukemia ◽  
Clonal Evolution ◽  
Malignant Cell ◽  
Leukemic Cells ◽  
Sequencing Data ◽  
Single Cell Sequencing ◽  
Computational Reconstruction ◽  
Acute Myeloid

AbstractAcute myeloid leukemia is an aggressive cancer of the blood forming system. The malignant cell population is composed of multiple clones that evolve over time. Clonal data reflect the mechanisms governing treatment response and relapse. Single cell sequencing provides most direct insights into the clonal composition of the leukemic cells, however it is still not routinely available in clinical practice. In this work we develop a computational algorithm that allows identifying all clonal hierarchies that are compatible with bulk variant allele frequencies measured in a patient sample. The clonal hierarchies represent descendance relations between the different clones and reveal the order in which mutations have been acquired. The proposed computational approach is tested using single cell sequencing data that allow comparing the outcome of the algorithm with the true structure of the clonal hierarchy. We investigate which problems occur during reconstruction of clonal hierarchies from bulk sequencing data. Our results suggest that in many cases only a small number of possible hierarchies fits the bulk data. This implies that bulk sequencing data can be used to obtain insights in clonal evolution.

scholarly journals Mathematical modeling with single-cell sequencing data

2019 ◽  
Author(s):  
Heyrim Cho ◽  
Russell C. Rockne
Keyword(s):  
Mathematical Modeling ◽  
Mathematical Models ◽  
Single Cell ◽  
Myeloid Leukemia ◽  
State Transitions ◽  
Sequencing Data ◽  
Modeling Framework ◽  
Single Cell Sequencing ◽  
Cell State ◽  
Compare And Contrast

AbstractSingle-cell sequencing technologies have revolutionized molecular and cellular biology and stimulated the development of computational tools to analyze the data generated from these technology platforms. However, despite the recent explosion of computational analysis tools, relatively few mathematical models have been developed to utilize these data. Here we compare and contrast two approaches for building mathematical models of cell state-transitions with single-cell RNA-sequencing data with hematopoeisis as a model system; by solving partial differential equations on a graph representing discrete cell state relationships, and by solving the equations on a continuous cell state-space. We demonstrate how to calibrate model parameters from single or multiple time-point single-cell sequencing data, and examine the effects of data processing algorithms on the model calibration and predictions. As an application of our approach, we demonstrate how the calibrated models may be used to mathematically perturb normal hematopoeisis to simulate, predict, and study the emergence of novel cell types during the pathogenesis of acute myeloid leukemia. The mathematical modeling framework we present is general and can be applied to study cell state-transitions in any single-cell genome sequencing dataset.Author summaryHere we compare and contrast graph- and continuum-based approaches for constructing mathematical models of cell state-transitions using single-cell RNA-sequencing data. Using two publicly available datasets, we demonstrate how to calibrate mathematical models of hematopoeisis and how to use the models to predict dynamics of acute myeloid leukemia pathogenesis by mathematically perturbing the process of cellular proliferation and differentiation. We apply these modeling approaches to study the effects of perturbing individual or sets of genes in subsets of cells, or by modeling the dynamics of cell state-transitions directly in a reduced dimensional space. We examine the effects of different graph abstraction and trajectory inference algorithms on calibrating the models and the subsequent model predictions. We conclude that both the graph- and continuum-based modeling approaches can be equally well calibrated to data and discuss situations in which one method may be preferable over the other. This work presents a general mathematical modeling framework, applicable to any single-cell sequencing dataset where cell state-transitions are of interest.

Mechanisms of Resistance to Targeted Therapies in Acute Myeloid Leukemia and Chronic Myeloid Leukemia

2012 ◽  
pp. 685-689
Author(s):  
Catherine C. Smith ◽  
Neil P. Shah
Keyword(s):  
Acute Myeloid Leukemia ◽  
Chronic Myeloid Leukemia ◽  
Targeted Therapies ◽  
Myeloid Leukemia ◽  
Kinase Inhibitors ◽  
Oncogenic Signaling ◽  
Primary Resistance ◽  
Secondary Resistance ◽  
Clinical Resistance ◽  
Acute Myeloid

Overview: Small molecule kinase inhibitors of BCR-ABL in chronic myeloid leukemia (CML) and of FMS-like tyrosine kinase 3 internal tandem duplication (FLT3-ITD) in acute myeloid leukemia (AML) have been successful at achieving remissions in these diseases as monotherapy, but these leukemias do not initially respond in a subset of patients (primary resistance) and they progress in an additional group of patients after an initial response (secondary resistance). Resistance to these agents can be divided into mechanisms that allow reactivation kinase activity and those that bypass reliance on oncogenic signaling mediated by the target kinase. Elucidation of clinical resistance mechanisms to targeted therapies for patients can provide important insights into disease pathogenesis and signaling.

Retrospective Application of European LeukemiaNet Provisional Criteria for Second-Generation TKI Chronic Myeloid Leukemia

Blood ◽  
2010 ◽  
Vol 116 (21) ◽  
pp. 2270-2270
Author(s):  
Massimo Breccia ◽  
Roberto Latagliata ◽  
Fabio Stagno ◽  
Antonella Gozzini ◽  
Elisabetta Abruzzese ◽  
...  
Keyword(s):  
Chronic Myeloid Leukemia ◽  
Myeloid Leukemia ◽  
Second Generation ◽  
Conflicts Of Interest ◽  
Acquired Resistance ◽  
Chronic Phase ◽  
Primary Resistance ◽  
Free Survival ◽  
Optimal Response ◽  
Monitoring Response

Abstract Abstract 2270 An update of the European LeukemiaNet criteria for monitoring response of chronic myeloid leukemia patients was recently published and provisional criteria to evaluate patients during second generation TKI therapy after resistance to imatinib were proposed. In our study we retrospectively tested these criteria in a large series of CML patients resistant to imatinib further treated with second generation TKIs with the aim to analyze the outcome of suboptimal response and failure patients compared to those with optimal response and to validate the provisional criteria for monitoring response. One hundred twenty-seven CML patients resistant to imatinib were collected from 6 different Italian hematologic centers. There were 66 males and 61 females, median age 54 years (range 25–80). Twenty-seven patients were in late chronic phase after IFN resistance. Ninety-seven patients received second-generation TKI after acquired resistance, whereas 30 patients had primary resistance. We found that at different time points (3, 6 and 12 months), patients classified as failure showed significantly worse 2-year overall survival (OS), progression-free survival (PFS) and event-free survival (EFS) than sub-optimal and optimal response patients. At 3 months, “failure” patients, had an OS of 83% compared to 86% of sub-optimal and 97% of optimal response patients (p=0.001); PFS was 77% for failure patients compared to 92% and 99% for sub-optimal and optimal response patients, respectively (p=0.001), whereas EFS was 41% for failure vs 59% for sub-optimal (p=0.001) and 85% and optimal response patients, respectively (sub-optimal vs optimal p<0.001). At 6 months, OS was 82%, 88% and 99% for failure, sub-optimal and optimal response patients (p=0.05), respectively; PFS was 82% for failure compared to 94% and 99% for sub-optimal and optimal response patients, respectively (p=0.001); EFS was 47% vs 69% for failure and sub-optimal response (p=0.001) and 86% for optimal response patients (sub-optimal vs optimal, p<0.001). At 12 months again OS was 84% for failure patients compared to 95% and 99% for sub-optimal and optimal response patients (p=0.04); PFS was 86%, 95% and 99% for failure, sub-optimal and optimal response patients, respectively (p=0.001) and EFS was 48% for failure, 67% for sub-optimal response patients (p=0.002) and 89% for optimal response patients (sub-optimal vs optimal, p<0.001). We found that ELN provisional criteria identified at any times worse EFS for sub-optimal response patients, similar to that of failure patients, and failure criteria at 3 months identified patients who had worse PFS and EFS. ELN provisional criteria for second-generation TKIs treated patients appear to clearly predict outcome and can be useful to identify patients at high risk of progression. Disclosures: No relevant conflicts of interest to declare.

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