1. Cancer Biology
  2. Genetics and Genomics

Single-cell multiomics analysis of chronic myeloid leukemia links cellular heterogeneity to therapy response

  1. Rebecca Warfvinge
  2. Linda Geironson Ulfsson
  3. Parashar Dhapola
  4. Fatemeh Safi
  5. Mikael Sommarin
  6. Shamit Soneji
  7. Henrik Hjorth-Hansen
  8. Satu Mustjoki
  9. Johan Richter
  10. Ram Krishna Thakur  Is a corresponding author
  11. Göran Karlsson  Is a corresponding author
  1. Division of Molecular Hematology, Lund Stem Cell Center, Lund University, Sweden
  2. Department of Hematology, St Olavs Hospital, Norway
  3. Department of Cancer Research and Molecular Medicine, Norwegian University of Science and Technology (NTNU), Norway
  4. Translational Immunology Research Program and Department of Clinical Chemistry and Hematology, University of Helsinki, Finland
  5. Hematology Research Unit Helsinki, Helsinki University Hospital Comprehensive Cancer Center, Norway
  6. iCAN Digital Precision Cancer Medicine Flagship, Finland
  7. Division of Molecular Medicine and Gene Therapy, Lund Stem Cell Center, Lund University, Sweden
  8. Department of Hematology, Oncology and Radiation Physics, Skåne University Hospital, Sweden
https://doi.org/10.7554/eLife.92074.3
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Cite this article
  1. Rebecca Warfvinge
  2. Linda Geironson Ulfsson
  3. Parashar Dhapola
  4. Fatemeh Safi
  5. Mikael Sommarin
  6. Shamit Soneji
  7. Henrik Hjorth-Hansen
  8. Satu Mustjoki
  9. Johan Richter
  10. Ram Krishna Thakur
  11. Göran Karlsson
(2024)
Single-cell multiomics analysis of chronic myeloid leukemia links cellular heterogeneity to therapy response
eLife 12:RP92074.
https://doi.org/10.7554/eLife.92074.3
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7 figures and 8 additional files

Figures

Figure 1 with 1 supplement
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Single-cell multiomics analysis of chronic myeloid leukemia (CML) and normal bone marrow (nBM) by CITE-seq.

(A) CML LSC and progenitor populations from nine CML bone marrow (BM) samples at diagnosis were FACS sorted and subjected to cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq). CML heterogeneity was defined by label transfer through cell projection onto a reference UMAP of age-matched nBM from two donors (Sommarin et al., 2021). Diagnostic samples were retrospectively stratified by BCR::ABL1 International Scale (IS) % after 12 months of TKI treatment, according to the European LeukemiaNet recommendations. (B) UMAP embedding of 4,696 Lin-CD34+ nBM cells (n=2) with 11 clusters identified by Leiden clustering; annotated by marker genes and ADT expression (HSC = hematopoietic stem cell; MPP = multipotent progenitor population 1; My/Ly = myeloid, lymphoid progenitors; My = myeloid progenitors; Ly/pDC/mono = lymphoid, dendritic, monocytic progenitors; MPP2=multipotent progenitor population 2; MEP = megakaryocytic erythroid progenitors); MkP = megakaryocytic erythroid progenitors; ErP = erythroid progenitors; Baso/mc = basophilic, mast cell progenitors; Cycling = Cycling progenitors. The bar plot below shows the percentage of cells per cluster. (C) Dot plot showing the antibody-derived tags (ADT) expression within clusters. The color indicates mean ADT expression (red = high expression, blue = low expression); dot size represents the fraction of cells with expression. (D) Dot plot showing mRNA expression of the top 10 marker genes per cluster. The color indicates mean RNA expression (red = high expression, blue = low expression); dot size represents the fraction of cells with expression.

Figure 1—figure supplement 1
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Cluster annotation by marker genes and surface protein expression.

(A) Distribution of annotated cell clusters across the two Lin-CD34 + nBM samples. (B) Cell cycle scoring: G1, S, G2/M of Uniform Manifold Approximation and Projection (UMAP) embedded Lin-CD34 + cells from nBM using Scarf. (C) Visualization of the relative mRNA (left panels) and antibody-derived tags (ADT) expression (right panels) of a selection of genes and surface markers within the Lin-CD34 + nBM reference.

Figure 2
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Single-cell maps of heterogeneity across patients and identification of a pan-stem and progenitor gene signature for CML.

(A) Uniform Manifold Approximation and Projection (UMAP) embedding of Lin-CD34+ sorted chronic myeloid leukemia (CML) bone marrow (BM) cells from nine CML patients at diagnosis (14, 274 cells across patients). Cell color indicates cluster identity after label transfer through cell projection onto an aged-matched normal bone marrow (nBM) reference (the first UMAP from the left). (B) Bar plots showing the log2 fold change in cluster distribution (%) of Lin-CD34+ CML BM cells (n=9) compared to Lin-CD34+ from nBM. Error bars depict standard deviation. (C) Volcano plots showing differentially expressed genes between the Lin-CD34+ CML clusters (across all patients, n=9) and the corresponding clusters from nBM (adjusted p-value <.01, log2 fold change >1/< –1). Red and black dots represent genes uniquely up- or down-regulated per cluster comparison (genes not found significantly changed in any other cluster DEG analysis). The top 10 significant, unique genes are labeled in plot. Vertical dotted lines mark a log2 fold change equal to 1 and –1. (D) Heatmap showing the average expression of the 50 significantly up-regulated and 21 down-regulated CML signature genes (genes significantly changed and consistent through all clusters DEG analyses) across clusters from all CML patients as well as nBM (adjusted p-value <.01, log2 fold change >1/< –1). Red indicates high expression, blue low expression.

Figure 3 with 2 supplements
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Cell heterogeneity at diagnosis relates to tyrosine kinase inhibitor (TKI) therapy outcome in chronic myeloid leukemia (CML).

(A) Stacked bar plots showing the cluster distribution within Lin-CD34+ compartment in all CML patients at diagnosis as well as normal bone marrow (nBM). CML patients are ordered by BCR::ABL1IS (%) following 12 months of TKI therapy (M12) and retrospectively stratified as per European LeukemiaNet recommendations; Optimal = CML1-4 (≤0.1%), Warning = CML5-7 (>0.1–1%), Failure = CML8-9 (>1 %). The total number of Lin-CD34+ cells from individual patients is indicated at the bottom. (B) Box plots comparing cluster proportions in optimal responders (n=4, CML patients 1–4) and treatment failures (n=2, CML patients 8–9) at diagnosis; the patients were retrospectively stratified according to BCR::ABL1IS (%) after 12 months of TKI therapy (Optimal ≤1 %), Failure >1 %. (C) A scheme for computational deconvolution of bulk transcriptomes from patients into constituent cell populations; using cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) derived gene signatures from Lin-CD34+ nBM as reference, an independent bulk CD34+ microarray dataset from CML patients (n=59 McWeeney et al., 2010) was deconvoluted into constituent cell populations using CIBERSORTx (Newman et al., 2019). (D) Stacked bar plots showing the percentage of specific clusters within CD34+ cells from individual CML patients (n=59). The x-axis shows individual GSE ID for patients, y-axis shows the percentage of clusters with similar color codes as used in Figures 1–2 UMAPs. Annotation of individual patients as per the original study (McWeeney et al., 2010); non-responders with >65% Ph + metaphases (did not achieve even a minor cytogenetic response), responders with 0% Ph + metaphases after 12 months of Imatinib therapy (achieved CCyR). BM and PB represent CD34+ cells isolated from bone marrow, and peripheral blood, respectively. (E) The fold change in proportions for cell clusters between non-responders and responders (annotation as described above) for CD34+ cells isolated from bone marrow; statistical significance shown by asterisk *; student t-test, p-value <0.05.

Figure 3—figure supplement 1
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Heterogeneity of CML patient HSPCs at diagnosis.

(A) Uniform Manifold Approximation and Projection (UMAP) plots showing the mapping score for the individual Lin-CD34+ chronic myeloid leukemia (CML) samples at diagnosis when mapped onto the nBM reference; mapping was performed using Scarf (Dhapola et al., 2022). Circle size indicates mapping score and circle color specify the cluster identity of the reference cell. (B) Bar plots showing the log2 fold change in cluster distribution (%) within the CML Lin-CD34+ compartment at diagnosis when compared to nBM for the individual CML patients.

Figure 3—figure supplement 2
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Molecular chararacterization of CML HSPC clusters.

(A) Volcano plots showing differentially expressed genes between Lin-CD34+ CML (n=9) at diagnosis and narrow bone marrow (nBM) cells across clusters (DESeq2). Red and black dots represent genes found to be consistently significant up- or down-regulated across all cluster comparisons in chronic myeloid leukemia (CML), respectively (adjusted p-value <0.01, log2 fold change = >1/< – 1). Vertical dotted line marks a log2 fold change equal to 1 and – 1. (B) The fold change in proportions for cell clusters between all non-responders and responders (CD34+ cells isolated from both PB and BM); statistical significance shown by asterisk *; student t-test, p-value <.05. (C) Assessment of the CML-related antibody-derived tags (ADTs); CD25, CD26, CD93 capacity to capture primitive cells, and specific progenitors across patients by gating on their expression within the Lin-CD34+ compartment (x-axis shows specific clusters, y-axis: percentage of specific cluster captured; each white circle represents a patient sample).

Figure 4 with 4 supplements
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Identification of BCR::ABL1+ and BCR::ABL1- primitive cells and their surface markers by joint analysis of single-cell gene expression and multiplexed antibody-derived sequence tags (ADTs).

(A) Overview of analysis steps to generate (B) (1) Lin-CD34+CD38-/low cells were projected onto Lin-CD34+ nBM. Subsequently, the primitive cluster CITE-seq data from all CML patients and nBM (negative control) were merged and visualized together in one Uniform Manifold Approximation and Projection (UMAP). BCR::ABL1+ gene signatures from BCR::ABL1 targeted SMART-seq (Giustacchini et al., 2017) was used to define primitive cluster cells from the individual patients as either BCR::ABL1+ or BCR::ABL1- (2) Lin-CD34+ and Lin-CD34+CD38-/low CITE-seq data from the same patient was merged and visualized together in a UMAP (3) BCR-ABL status from the Lin-CD34+CD38-/low primitive cells was linked to the joint UMAPs by matching cell IDs and cell were colored as either red (BCR::ABL1+) or black (BCR::ABL1-) (4) The log2 fold change in antibody-derived tags ADT expression between primitive Lin-CD34+CD38-/low BCR::ABL1+ (red) and BCR::ABL1- (black) cells was calculated and the remaining cells were colored according to their cluster annotation given after projection onto Lin-CD34+ nBM. (B) UMAP plots showing the merged CITE-seq data of Lin-CD34+ and Lin-CD34+CD38-/low sorted populations for CML2-9 individually. Cells are color-coded according to cluster annotation given following projection onto Lin-CD34+ nBM. Lin-CD34+CD38-/low primitive cluster cells are annotated as BCR::ABL1+ (red) or BCR::ABL1- (black) and display enrichment of BCR::ABL1+ LSC signatures and non-leukemic stem cell signatures, respectively. The red and black bars in the bar plot below indicate ADTs with significant changes in expression (p-value <.05, log2 fold change >1 / < –1) for BCR::ABL1+ and BCR::ABL1- cells, respectively. (C) Volcano plot showing differentially expressed genes between CML Lin-CD34+CD38-/low Primitive BCR::ABL1+ and BCR::ABL1- cells. Red and black dots represent significant up- and down-regulated genes (adjusted p-value <.01, log2 fold change >1 / < –1). The top 10 significant genes are labeled. Vertical dotted lines mark a fold change equal to 1 and –1. (D) UMAP embedding of CML Lin-CD34+ cells from one representative CML patient at diagnosis (CML5). First plot from the left shows cells colored according to the cluster identity given after mapping to nBM, the primitive cells are colored yellow. The following two UMAPs of Lin-CD34+ show the relative mRNA expression of the BCR::ABL1+ LSC signature and BCR::ABL1- non-leukemic stem cell gene signature; scale: red = high expression, blue = low expression.

Figure 4—figure supplement 1
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Identification of BCR::ABL+ stem cells.

(A) Uniform Manifold Approximation and Projection (UMAP) plots showing the mapping score for individual Lin-CD34+CD38-/low CML samples (CML2-8) at diagnosis and Lin-CD34+CD38-/low normal BM when mapped onto the Lin-CD34+ nBM reference; mapping was performed using Scarf. Circle size indicates mapping score and circle color specify the cluster identity of the reference cell. (B) UMAP embedding of Lin-CD34+CD38-/low primitive cluster CML (n=8, a total of 2778 cells) and normal bone marrow (BM) cells showing clusters following Leiden clustering analysis. (C) UMAP embedding of Lin-CD34+CD38-/low primitive cluster chronic myeloid leukemia (CML) (n=8, a total of 2778 cells) at diagnosis and normal BM cells where cells are colored by sample identity. (D) Same UMAP as in B-C above, showing the relative expression of BCR::ABL1+ LSC (left panel) and BCR::ABL1- LSC signature genes (right panel) used to define BCR::ABL1+ primitive cells (Signature genes are from DEG analysis comparing CP-CML Lin-CD34+CD38-/low BCR::ABL1+ and BCR::ABL1- Giustacchini et al., 2017). (E) Same UMAP as in B-C above, showing the relative expression of BCR::ABL1+ LSC (left panel) and nBM HSC signature genes (right panel) used to define BCR::ABL1+ primitive cells (Signature genes are from DEG analysis comparing CP-CML Lin-CD34+CD38-/low BCR::ABL1+ and nBM Lin-CD34+CD38-/low cells Giustacchini et al., 2017). (F) Quantification of Lin-CD34+CD38-/low primitive BCR::ABL1+ (red) and BCR::ABL1- (black) cells per CML patient at diagnosis. Total primitive cells per patient is indicated at the bottom.

Figure 4—figure supplement 2
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Mapping of BCR::ABL+ stem cells.

(A) Uniform Manifold Approximation and Projection (UMAP) plots where CITE-seq data from Lin-CD34+ and Lin-CD34+CD38-/low sorted cells from the same chronic myeloid leukemia (CML) patients have been merged, and Lin-CD34+CD38-/low cells are highlighted in blue. (B) UMAP plots where CITE-seq data from Lin-CD34+ and Lin-CD34+CD38-/low sorted cells from the same CML patients have been merged, where Lin-CD34+CD38-/low primitive annotated cells are highlighted in blue.

Figure 4—figure supplement 3
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Mapping of BCR::ABL+ stem cells in individual patients.

(A) Uniform Manifold Approximation and Projection (UMAP) plots of Lin-CD34+ cells from chronic myeloid leukemia (CML) patients 1–4 and 6–9, showing cells colored according to cluster identity given after mapping to narrow bone marrow (nBM) (left panel); the relative expression of Lin-CD34+CD38-/low Primitive BCR::ABL1+ signature genes (center panel) and the relative expression of Lin-CD34+CD38-/low Primitive BCR::ABL1- signature genes (right panel). DEG analysis is shown in Figure 4C and relative expression of signatures for CML5 is found in Figure 4D. (red = high expression, blue = low expression).

Figure 4—figure supplement 4
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Mapping of BCR::ABL+ stem cells in individual patients.

(A) Uniform Manifold Approximation and Projection (UMAP) plots of chronic myeloid leukemia (CML) Lin-CD34+ primitive cluster cells from all CML patients (n=9, a total of 1106 cells) showing clusters following Leiden clustering analysis. (B) UMAP plots of CML Lin-CD34+ primitive cluster from all CML patients (n=9, a total of 1106 cells) where the cells are colored as per the sample identity. (C) UMAP plots of CML Lin-CD34+ primitive cluster cells from all CML patients showing the relative expression of two DEG signatures used to define BCR::ABL1+ primitive cells: (1) BCR::ABL1+ LSC vs nBM HSC signature genes (top row, left panel = up-regulated genes in BCR::ABL1+ LSCs, right panel = genes up-regulated in nBM HSCs), (2) BCR::ABL1+ LSC vs BCR::ABL1- LSC (bottom row, left panel = genes up-regulated in BCR::ABL1+ LSC, right panel = genes up-regulated in BCR::ABL1- LSC Giustacchini et al., 2017). (D) UMAP plots of Lin-CD34+ cells from individual CML patients (1-9) showing primitive cluster cells (yellow cluster, left panel) annotated as BCR::ABL1+ (red) and BCR::ABL1- (black)(right panel). (E) Quantification of Lin-CD34+ primitive BCR::ABL1+ (red, cluster 2–3 in A) and BCR::ABL1- (black, cluster 1 in A) cells per CML patient at diagnosis. Total primitive cells are indicated at the bottom.

Figure 5 with 2 supplements
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Assessment of surface marker combinations to capture molecularly defined BCR::ABL1+ and BCR::ABL1- primitive cells.

(A) Heatmap comparing antibody-derived tags (ADT) expression between BCR::ABL1+ and BCR::ABL1- cells within the Lin-CD34+CD38-/low primitive cluster across chronic myeloid leukemia (CML) patients (black = surface markers significantly up-regulated in BCR::ABL1- cells (log2 fold change < –1, p-value <.05); red = surface markers significantly up-regulated in BCR::ABL1+ cells (log2 fold change >1, p-value <.05); gray = non-significant change in ADT expression; white = surface marker was not present in the ADT panel used for the specific patient). (B) Visualization of the relative ADT expression of CD25, CD26, CD93, CD117, and CD35 in the UMAPs of Lin-CD34+ cells from CML patients 5 and 9 (red = high expression, blue = low expression). (C) Assessment of a selection of ADTs; CD25, CD26, CD93, CD117, and CD35 capacity to capture BCR::ABL1+ primitive, BCR::ABL1- primitive, all primitive cells, and specific progenitors across patients by gating on their expression within the Lin-CD34+ compartment (x-axis shows specific clusters, y-axis: percentage of specific cluster captured; each white circle represents a patient sample). (D) Assessment of specific ADTs: CD26, CD25, and CD35 capacity to capture BCR::ABL1+ primitive versus BCR::ABL1- primitive cluster within the Lin-CD34+CD38-/low compartment across patients; x-axis shows specific clusters, y-axis: percentage of specific cluster captured; each white circle represents a patient sample. (E) Assessment of specific combinations of ADTs: CD26+CD35-, CD26-CD35+, CD26-CD35-, and CD26+CD35+ capacity to capture BCR::ABL1+ primitive versus BCR::ABL1- primitive cluster within the Lin-CD34+CD38-/low compartment across patients; x-axis shows specific clusters, y-axis: percentage of specific cluster captured; each white circle represents a patient sample.

Figure 5—figure supplement 1
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Expression of ADTs across pateints.

(A) Uniform Manifold Approximation and Projection (UMAP) plots of Lin-CD34+ cells from chronic myeloid leukemia (CML) patients 1–4 and 6–8 showing the relative antibody-derived tags (ADT) expression of a selection of markers (CD25, CD26, CD93, CD117, CD35) (red = high expression, blue = low expression).

ADT expression for CML patients 5 and 9 is shown in Figure 5B.

Figure 5—figure supplement 2
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Validation of CD26 and CD35 stem cell populations.

(A) Plots showing representative gates on antibody-derived tags (ADT) expression for CD26, CD35, CD117, CD25, CD93 within the Lin-CD34+ CITE-seq data using FlowJo. Gates are shown for CML5 and CML9. (B) Plots showing the gating on CD26 and CD35 ADT expression within the Lin-CD34+CD38-/low CITE-seq data for chronic myeloid leukemia (CML) patients 2–3, 5–7, and 9 using FlowJo. Plots for CML patients 4 and 8 is shown in Figure 6D. (C) Cumulative plots of time to first division kinetics from Lin-CD34+CD38-/lowCD45RA-CD26+CD35- and CD26-CD35+ single cells for two individual CML patients at diagnosis (n=2, CML patients 10 and 11). Dead cells and non-dividing cells were excluded from the analysis. (D) Mean time to first division (hours) for Lin-CD34+CD38-/lowCD45RA- CD26+CD35- or CD26-CD35+ single-cells from the two CML patients shown in C (n=2, CML patients 10 and 11 P-value = ns.,.84; paired t-test). (E) Mean cell cycle status of ADT gated CD26+CD35- or CD26-CD35+ cells, after running Scarf’s cell cycle scoring on the Lin-CD34+CD38-/low CITE-seq data for patients individually (n=8, CML2-9). (F) Mean cell cycle status of ADT gated CD26+CD35- or CD26-CD35+ cells, after running Scarf’s cell cycle scoring on Lin-CD34+CD38-/low Primitive cluster for patients individually (n=8, CML2-9).

Figure 6
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Analysis of CD26+CD35 vs. CD26-CD35+ cells for BCR::ABL1 transcript expression, and response to tyrosine kinase inhibitor (TKI) therapy.

(A) Real-time qPCR for BCR::ABL1 in CD26-CD35+ (n=7, CML patients 10–12, 14–15, 17–18) vs. CD26+CD35- (n=9, chronic myeloid leukemia (CML) patients 10–15, 17–18, and 20) within the Lin-CD34+CD38-/low compartment at diagnosis and following 3 months of Bosutinib therapy (n=3, CML patients 17, 18, 21). GAPDH served as control. (B) Real-time qPCR for GAS2 in CD26-CD35+ (n=3, CML patients 14, 17–18) vs. CD26+CD35- (n=4, CML patients 13–14, 17–18) within the Lin-CD34+CD38-/low compartment at diagnosis and following 3 months of Bosutinib therapy (n=3, CML patients 17–18, 21). GAPDH served as control. (C) Representative FACS plots showing the percentage CD26+CD35- (leukemic stem cells, LSC) and CD26-CD35+ (hematopoietic stem cell, HSC) cells within the Lin-CD34+CD38-/low compartment. Left panel: antibody-derived tags (ADT)-gated CD26+CD35- and CD26-CD35+ cells within Lin-CD34+CD38-/low CITE-seq data from selected optimal responder (CML4) and treatment failure (CML8) at diagnosis. Right panel: FACS gated Lin-CD34+CD38-/lowCD26+CD35- and CD26-CD35+ cells in selected optimal responder (CML12) and treatment failure (CML13) at diagnosis versus 3 months of TKI therapy (Bosutinib). (D) Bar plots showing the percentage of CD26+CD35- and CD26-CD35+ cells within Lin-CD34+CD38-/low compartment from optimal responders and treatment failures at diagnosis n=11; optimal = 6 (≤0.1%, CML patients 12, 14–18), failure = 5 (>1%, CML patients 13, 19, 22–23, 25) and following 3 months of Bosutinib therapy n=11; optimal = 6 (≤0.1%, CML patients 12, 14–18), failure = 5 (>1%, CML patients 13, 19, 22–23, 24) determined using FACS.

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Additional files

Supplementary file 1

Chronic myeloid leukemia (CML) sample cohort.

https://cdn.elifesciences.org/articles/92074/elife-92074-supp1-v1.xlsx
Supplementary file 2

Cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) antibodies.

https://cdn.elifesciences.org/articles/92074/elife-92074-supp2-v1.xlsx
Supplementary file 3

FACS antibodies.

https://cdn.elifesciences.org/articles/92074/elife-92074-supp3-v1.xlsx
Supplementary file 4

List of marker genes for narrow bone marrow (nBM) clusters.

https://cdn.elifesciences.org/articles/92074/elife-92074-supp4-v1.xlsx
Supplementary file 5

List of DEG uniquely changed per cluster in chronic myeloid leukemia (CML) vs. narrow bone marrow (nBM) clusters 1–11 along with their fold change.

https://cdn.elifesciences.org/articles/92074/elife-92074-supp5-v1.xlsx
Supplementary file 6

List of DEG along with their fold change between BCR::ABL1+ LSCs vs. BCR::ABL1- stem cells.

https://cdn.elifesciences.org/articles/92074/elife-92074-supp6-v1.xlsx
Supplementary file 7

List of DEG up- and down-regulated in all clusters in chronic myeloid leukemia (CML) vs. narrow bone marrow (nBM) clusters 1–11.

https://cdn.elifesciences.org/articles/92074/elife-92074-supp7-v1.xlsx
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https://cdn.elifesciences.org/articles/92074/elife-92074-mdarchecklist1-v1.docx

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  1. Rebecca Warfvinge
  2. Linda Geironson Ulfsson
  3. Parashar Dhapola
  4. Fatemeh Safi
  5. Mikael Sommarin
  6. Shamit Soneji
  7. Henrik Hjorth-Hansen
  8. Satu Mustjoki
  9. Johan Richter
  10. Ram Krishna Thakur
  11. Göran Karlsson
(2024)
Single-cell multiomics analysis of chronic myeloid leukemia links cellular heterogeneity to therapy response
eLife 12:RP92074.
https://doi.org/10.7554/eLife.92074.3