Abstract 5348: Single-cell analysis of mutational heterogeneity in acute myeloid leukemia tumors with high-throughput droplet microfluidics

2018 ◽  
Author(s):  
Dennis J. Eastburn ◽  
Maurizio Pellegrino ◽  
Adam Sciambi ◽  
Sebastian Treusch ◽  
Liwen Xu ◽  
...  
Keyword(s):  
Acute Myeloid Leukemia ◽  
Single Cell ◽  
High Throughput ◽  
Myeloid Leukemia ◽  
Single Cell Analysis ◽  
Droplet Microfluidics ◽  
Cell Analysis ◽  
Acute Myeloid

scholarly journals Massively parallel quantification of phenotypic heterogeneity in single cell drug responses

2020 ◽  
Author(s):  
Benjamin B. Yellen ◽  
Jon S. Zawistowski ◽  
Eric A. Czech ◽  
Caleb I. Sanford ◽  
Elliott D. SoRelle ◽  
...  
Keyword(s):  
Machine Learning ◽  
Acute Myeloid Leukemia ◽  
Single Cell ◽  
Myeloid Leukemia ◽  
Single Cell Analysis ◽  
Phenotypic Heterogeneity ◽  
Massively Parallel ◽  
Cell Analysis ◽  
On Chip ◽  
Acute Myeloid

AbstractSingle cell analysis tools have made significant advances in characterizing genomic heterogeneity, however tools for measuring phenotypic heterogeneity have lagged due to the increased difficulty of handling live biology. Here, we report a single cell phenotyping tool capable of measuring image-based clonal properties at scales approaching 100,000 clones per experiment. These advances are achieved by exploiting a novel flow regime in ladder microfluidic networks that, under appropriate conditions, yield a mathematically perfect cell trap. Machine learning and computer vision tools are used to control the imaging hardware and analyze the cellular phenotypic parameters within these images. Using this platform, we quantified the responses of tens of thousands of single cell-derived acute myeloid leukemia (AML) clones to targeted therapy, identifying rare resistance and morphological phenotypes at frequencies down to 0.05%. This approach can be extended to higher-level cellular architectures such as cell pairs and organoids and on-chip live-cell fluorescence assays.

scholarly journals Heterogeneous resistance to quizartinib in acute myeloid leukemia revealed by single-cell analysis

Blood ◽  
2017 ◽  
Vol 130 (1) ◽  
pp. 48-58 ◽  
Author(s):  
Catherine C. Smith ◽  
Amy Paguirigan ◽  
Grace R. Jeschke ◽  
Kimberly C. Lin ◽  
Evan Massi ◽  
...  
Keyword(s):  
Acute Myeloid Leukemia ◽  
Single Cell ◽  
Myeloid Leukemia ◽  
Single Cell Analysis ◽  
Cell Analysis ◽  
Mechanisms Of Resistance ◽  
Key Points ◽  
Acute Myeloid

Key Points Polyclonal mechanisms of resistance, demonstrated by single-cell analysis, occur in the majority of AML patients who relapse on quizartinib.

scholarly journals High-throughput single-cell DNA sequencing of acute myeloid leukemia tumors with droplet microfluidics

2018 ◽  
Vol 28 (9) ◽  
pp. 1345-1352 ◽  
Author(s):  
Maurizio Pellegrino ◽  
Adam Sciambi ◽  
Sebastian Treusch ◽  
Robert Durruthy-Durruthy ◽  
Kaustubh Gokhale ◽  
...  
Keyword(s):  
Acute Myeloid Leukemia ◽  
Dna Sequencing ◽  
Single Cell ◽  
High Throughput ◽  
Myeloid Leukemia ◽  
Droplet Microfluidics ◽  
Acute Myeloid

scholarly journals Development of Droplet Microfluidics Enabling High-Throughput Single-Cell Analysis

Molecules ◽  
2016 ◽  
Vol 21 (7) ◽  
pp. 881 ◽  
Author(s):  
Na Wen ◽  
Zhan Zhao ◽  
Beiyuan Fan ◽  
Deyong Chen ◽  
Dong Men ◽  
...  
Keyword(s):  
Single Cell ◽  
High Throughput ◽  
Single Cell Analysis ◽  
Droplet Microfluidics ◽  
Cell Analysis

scholarly journals Clonal evolution of acute myeloid leukemia revealed by high-throughput single-cell genomics

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Kiyomi Morita ◽  
Feng Wang ◽  
Katharina Jahn ◽  
Tianyuan Hu ◽  
Tomoyuki Tanaka ◽  
...  
Keyword(s):  
Acute Myeloid Leukemia ◽  
Single Cell ◽  
Myeloid Leukemia ◽  
Single Cell Analysis ◽  
Clonal Evolution ◽  
Evolutionary Process ◽  
Treatment Resistance ◽  
Clonal Diversity ◽  
Clonal Architecture ◽  
Acute Myeloid

AbstractClonal diversity is a consequence of cancer cell evolution driven by Darwinian selection. Precise characterization of clonal architecture is essential to understand the evolutionary history of tumor development and its association with treatment resistance. Here, using a single-cell DNA sequencing, we report the clonal architecture and mutational histories of 123 acute myeloid leukemia (AML) patients. The single-cell data reveals cell-level mutation co-occurrence and enables reconstruction of mutational histories characterized by linear and branching patterns of clonal evolution, with the latter including convergent evolution. Through xenotransplantion, we show leukemia initiating capabilities of individual subclones evolving in parallel. Also, by simultaneous single-cell DNA and cell surface protein analysis, we illustrate both genetic and phenotypic evolution in AML. Lastly, single-cell analysis of longitudinal samples reveals underlying evolutionary process of therapeutic resistance. Together, these data unravel clonal diversity and evolution patterns of AML, and highlight their clinical relevance in the era of precision medicine.

scholarly journals Clonal Evolution of Acute Myeloid Leukemia Revealed by High-Throughput Single-Cell Genomics

2020 ◽  
Author(s):  
Kiyomi Morita ◽  
Feng Wang ◽  
Katharina Jahn ◽  
Jack Kuipers ◽  
Yuanqing Yan ◽  
...  
Keyword(s):  
Acute Myeloid Leukemia ◽  
Dna Sequencing ◽  
Single Cell ◽  
High Throughput ◽  
Myeloid Leukemia ◽  
Clonal Evolution ◽  
Treatment Resistance ◽  
Clonal Diversity ◽  
History Of ◽  
Acute Myeloid

SummaryOne of the pervasive features of cancer is the diversity of mutations found in malignant cells within the same tumor; a phenomenon called clonal diversity or intratumor heterogeneity. Clonal diversity allows tumors to adapt to the selective pressure of treatment and likely contributes to the development of treatment resistance and cancer recurrence. Thus, the ability to precisely delineate the clonal substructure of a tumor, including the evolutionary history of its development and the co-occurrence of its mutations, is necessary to understand and overcome treatment resistance. However, DNA sequencing of bulk tumor samples cannot accurately resolve complex clonal architectures. Here, we performed high-throughput single-cell DNA sequencing to quantitatively assess the clonal architecture of acute myeloid leukemia (AML). We sequenced a total of 556,951 cells from 77 patients with AML for 19 genes known to be recurrently mutated in AML. The data revealed clonal relationship among AML driver mutations and identified mutations that often co-occurred (e.g., NPM1/FLT3-ITD, DNMT3A/NPM1, SRSF2/IDH2, and WT1/FLT3-ITD) and those that were mutually exclusive (e.g., NRAS/KRAS, FLT3-D835/ITD, and IDH1/IDH2) at single-cell resolution. Reconstruction of the tumor phylogeny uncovered history of tumor development that is characterized by linear and branching clonal evolution patterns with latter involving functional convergence of separately evolved clones. Analysis of longitudinal samples revealed remodeling of clonal architecture in response to therapeutic pressure that is driven by clonal selection. Furthermore, in this AML cohort, higher clonal diversity (≥4 subclones) was associated with significantly worse overall survival. These data portray clonal relationship, architecture, and evolution of AML driver genes with unprecedented resolution, and illuminate the role of clonal diversity in therapeutic resistance, relapse and clinical outcome in AML.

scholarly journals Author Correction: Clonal evolution of acute myeloid leukemia revealed by high-throughput single-cell genomics

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Kiyomi Morita ◽  
Feng Wang ◽  
Katharina Jahn ◽  
Tianyuan Hu ◽  
Tomoyuki Tanaka ◽  
...  
Keyword(s):  
Acute Myeloid Leukemia ◽  
Single Cell ◽  
High Throughput ◽  
Myeloid Leukemia ◽  
Clonal Evolution ◽  
Single Cell Genomics ◽  
Acute Myeloid

scholarly journals Single cell analysis reveals altered tumor microenvironments of relapse- and remission-associated pediatric acute myeloid leukemia

2021 ◽  
Author(s):  
Gulay Ulukaya ◽  
Beena Thomas ◽  
Swati Bhasin ◽  
Hope Mumme ◽  
Bhakti Dwivedi ◽  
...  
Keyword(s):  
T Cells ◽  
Acute Myeloid Leukemia ◽  
Single Cell ◽  
Myeloid Leukemia ◽  
Single Cell Analysis ◽  
Acid Oxidation ◽  
P Value ◽  
Pediatric Acute Myeloid Leukemia ◽  
Tumor Microenvironments ◽  
Acute Myeloid

Abstract Relapse- and continuous complete remission (CCR)-associated pediatric acute myeloid leukemia (AML) patient bone marrows collected at the time of diagnosis (Dx), end of induction (EOI) and relapse were analyzed by single cell RNA sequencing. A novel AML blasts-associated 7-genes signature (CLEC11A, PRAME, AZU1, NREP, ARMH1, C1QBP, TRH) displayed a strong correlation with blast percentages and overall survival in the TARGET AML dataset (HR=2.3; P-value=.007). Distinct clusters of AML-blasts at Dx were observed for relapse- and CCR-associated samples with differential expression of genes associated with survival. Relapse-associated samples demonstrated enrichment of exhausted T cells and M2 macrophages as opposed to inflammatory M1 macrophages in CCR-associated samples at Dx. EOI treatment resistant blast cells overexpressed fatty acid oxidation, tumor growth and stemness genes. Also, a relapse-associated EOI samples T cells subset showed downregulation of MHC Class I and regulatory genes. Altogether, this study deeply characterizes pediatric AML relapse-/CCR-associated tumor microenvironment transcriptome landscape.

Sign in / Sign up

Export Citation Format

Share Document