Convergent epigenetic evolution drives relapse in acute myeloid leukemia

  1. Kevin Nuno
  2. Armon Azizi
  3. Thomas Koehnke
  4. Caleb Lareau
  5. Asiri Ediriwickrema
  6. M Ryan Corces
  7. Ansuman T Satpathy
  8. Ravindra Majeti  Is a corresponding author
  1. Cancer Biology Graduate Program, Stanford University School of Medicine, United States
  2. Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, United States
  3. Cancer Institute, Stanford University School of Medicine, United States
  4. Department of Medicine, Division of Hematology, Stanford University School of Medicine, United States
  5. University of California Irvine School of Medicine, United States
  6. Department of Pathology, Stanford University, United States
  7. Program in Immunology, Stanford University, United States
  8. Gladstone Institute of Neurological Disease, United States
  9. Gladstone Institute of Data Science and Biotechnology, United States
  10. Department of Neurology, University of California, San Francisco, United States
  11. Parker Institute for Cancer Immunotherapy, Stanford University, United States
  12. Gladstone-UCSF Institute of Genomic Immunology, United States
6 figures and 2 additional files

Figures

Figure 1 with 2 supplements
Meta-analysis of genomic change in relapsed AML.

(a) Oncoprint of recurrently mutated genes from published relapsed AML dataset. Genetic alterations are color coded according to dynamics between disease state: stable at relapse, gained at relapse, …

Figure 1—figure supplement 1
Plots depicting change in variant allele frequency for detected ‘pre-leukemic’ epigenetic modifier mutations (a), RAS pathway mutations (b), or WT1 mutations (c) in meta-analysis relapsed AML cohort.

Lines connect samples from the same patient between disease timepoints, color coded according to mutation dynamic (red = stable, blue = gained at relapse, yellow = lost at relapse) (a, c) or …

Figure 1—figure supplement 2
Gene-specific clonal analysis and multivariate analysis of relapse-free-survival based on clonality.

(a) Time to relapse analysis of meta-analysis cohort patients according to WT1 mutation status between diagnosis and relapse (blue = gained WT1 mutation at relapse, red = WT1 mutation stable at …

Figure 2 with 2 supplements
Chromatin accessibility change in stable and non-stable relapsed AML.

(a) Schematic of relapse sample acquisition and preparation. (b) Oncoprint of recurrently mutated genes in samples analyzed from Stanford University patient cohort (n=26). (c) Bar chart depicting …

Figure 2—figure supplement 1
Relapse-free-survival and differential chromatin analysis of the Stanford AML cohort.

(a) Time to relapse analysis of Stanford cohort patients according to clonality assessed by driver mutation genotyping. (b) Volcano plot of differential accessibility between diagnosis and relapse …

Figure 2—figure supplement 2
Projection of bulk AML ATAC samples to healthy hematopoietic single-cell manifold demonstrates shifts in epigenetic differentiation states at relapse.

(a) Healthy cell reference manifold projection of single-cell ATAC-seq data from Granja et al., 2019. Healthy hematopoietic cell categories color coded according to key shown below. (b) Bulk AML …

Figure 3 with 1 supplement
Chromatin change in relapsed AML LSCs.

(a) Cell sorting and library preparation scheme for comparison of chromatin accessibility profiles of LSC vs. non-LSC enriched subpopulations in relapsed AML cohort. (b) Box and whisker plot …

Figure 3—figure supplement 1
Comparison between AML relapse signature and LSC signature.

Relapse signatures were derived by comparing relapse timepoints to diagnosis timepoints in stable AML patients. LSC signatures were derived by comparing LSCs to non-LSC populations at diagnosis …

Figure 4 with 2 supplements
Single-cell ATACseq analysis of relapsed AML.

(a) Scheme for single-cell ATAC-seq sample preparation and cell clustering analysis (b) UMAP projection of all single-cell ATAC-seq patient samples from Stanford diagnosis/relapse cohort (samples …

Figure 4—figure supplement 1
Single-cell SNN clusters and between-cluster epigenetic similarities.

(a) UMAP plots of clustering analyses performed for the four patient samples indicated (diagnosis sample at left, relapse at right). (b) Hierarchical clustering analysis of scATAC-seq data from …

Figure 4—figure supplement 2
Projection of AML scATAC samples to healthy hematopoietic single-cell manifold demonstrates shifts in epigenetic differentiation states at relapse.

(a) Schematic of strategy for healthy cell LSI projection analysis of single-cell ATAC-seq diagnosis/relapse data (b) Healthy cell reference of single-cell ATAC-seq data from Granja et al Nat. Granja…

Figure 5 with 2 supplements
Mitochondrial-based clonal tracing paired with single-cell chromatin accessibility in stable AMLs.

(a) Scheme for sample processing and analysis of mitochondrial single-cell ATAC-seq (mtscATAC-seq). (b) Heatmap of mitochondrial variant heteroplasmy values across all single cells for each …

Figure 5—figure supplement 1
Mitochondrial-based clonal tracing paired with single -cell chromatin accessibility in a genetically non-stable AML.

(a) Comparison of relapse vs diagnosis accessibility fold change across all peaks between mitoclone 1 and mitoclone 2 in SU360 (R=0.41, p<2.2e-16). (b) Heatmap of mitochondrial variant heteroplasmy …

Figure 5—figure supplement 2
Clone-specific epigenetic relapse scores at diagnosis and relapse timepoints.

(a–d) Box plots depicting relapse signature ATAC-seq score calculated for single cells for the indicated patients according to timepoint, diagnosis (left) shown in blue, relapse (right) shown in …

Author response image 1
Volcano plots of differential analysis between mutant vs wildtype of relapse vs diagnosis fold change.

Mutations analyzed include (A) FLT3, (B) DNMT3A, (C) NPM1, (D) TET2. Volcano plots are displayed with unadjusted (left) and adjusted (right) p values. In all analyses but one, p-value adjustment …

Additional files

Supplementary file 1

Supplementary meta-analysis, clinical, treatment, and genotyping data.

(a) List of all publicly available studies utilized in the meta-analysis of relapsed AML genomics. (b) Clinical, treatment, and karyotype information for all patients in the study. (c) Summary of all genotyping information for all paired diagnosis and relapse samples in the study. (d) Detailed genotyping information for all paired diagnosis and relapse samples in the study. (e) Bulk ATAC-seq gene score differential accessibility results from stable AML analysis.

https://cdn.elifesciences.org/articles/93019/elife-93019-supp1-v1.xlsx
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https://cdn.elifesciences.org/articles/93019/elife-93019-mdarchecklist1-v1.pdf

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