Single-Cell Multiomics Reveals Clonal T-Cell Expansions and Exhaustion in Blastic Plasmacytoid Dendritic Cell Neoplasm

DePasquale, Erica A. K.; Ssozi, Daniel; Ainciburu, Marina; Good, Jonathan; Noel, J.; Villanueva, Martin Arreola; Couturier, Céline; Shalek, Alex K.; Aranki, Sary F.; Mallidi, Hari R.; Griffin, Gabriel K.; Lane, Andrew A.; Galen, Peter van

doi:10.3389/fimmu.2022.809414

Cited by 7 publications

(6 citation statements)

References 51 publications

(66 reference statements)

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“…As expected in a healthy individual, we did not observe any expanded T-cell clones dominating the sample. Nonetheless, the largest detected clones belong mainly to CD8 Memory T-cell subsets, in accordance with previous findings (Supplementary Figure 4) (DePasquale et al, 2021;Penter et al, 2021).…”

Section: Resultssupporting

confidence: 92%

WAT3R: recovery of T-cell receptor variable regions from 3′ single-cell RNA-sequencing

et al. 2022

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Summary Diversity of the T-cell receptor (TCR) repertoire is central to adaptive immunity. The TCR is composed of α and β chains, encoded by the TRA and TRB genes, of which the variable regions determine antigen specificity. To generate novel biological insights into the complex functioning of immune cells, combined capture of variable regions and single-cell transcriptomes provides a compelling approach. Recent developments enable the enrichment of TRA and TRB variable regions from widely used technologies for 3′-based single-cell RNA-sequencing (scRNA-seq). However, a comprehensive computational pipeline to process TCR-enriched data from 3′ scRNA-seq is not available. Here, we present an analysis pipeline to process TCR variable regions enriched from 3′ scRNA-seq cDNA. The tool reports TRA and TRB nucleotide and amino acid sequences linked to cell barcodes, enabling the reconstruction of T-cell clonotypes with associated transcriptomes. We demonstrate the software using peripheral blood mononuclear cells from a healthy donor and detect TCR sequences in a high proportion of single T cells. Detection of TCR sequences is low in non-T-cell populations, demonstrating specificity. Finally, we show that TCR clones are larger in CD8 Memory T cells than in other T-cell types, indicating an association between T-cell clonotypes and differentiation states. Availability and implementation The Workflow for Association of T-cell receptors from 3′ single-cell RNA-seq (WAT3R), including test data, is available on GitHub (https://github.com/mainciburu/WAT3R), Docker Hub (https://hub.docker.com/r/mainciburu/wat3r) and a workflow on the Terra platform (https://app.terra.bio). The test dataset is available on GEO (accession number GSE195956). Supplementary information Supplementary data are available at Bioinformatics online.

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Section: Resultssupporting

confidence: 92%

WAT3R: recovery of T-cell receptor variable regions from 3′ single-cell RNA-sequencing

et al. 2022

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“…To validate our transcriptional approach for leukemia cell classification, we projected scRNA-seq profiles from leukemia samples with clearly defined lineage features. As expected, Pro-B cells were expanded in B-acute lymphoblastic leukemia (B-ALL) 47 ( Figure 3A ), multipotent MLPs were expanded in mixed-phenotype acute leukemia (MPAL) 36 ( Figure 3B ), pDCs were expanded in blastic plasmacytoid dendritic cell neoplasm (BPDCN) 48 ( Figure 3C ), Mk precursors (MkP) were expanded in acute megakaryoblastic leukemia (AMKL) 49 ( Figure 3D ), and erythroblasts were expanded in acute erythroid leukemia (AEL) 50 ( Figure 3E ).…”

Section: Resultssupporting

confidence: 64%

Single-cell transcriptional mapping reveals genetic and non-genetic determinants of aberrant differentiation in AML

Zeng,

Iacobucci,

Shah

et al. 2023

Preprint

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Initial classification of acute leukemia involves the assignment of blasts to cell states within the hematopoietic hierarchy based on morphological and immunophenotypic features. Yet, these traditional classification approaches lack precision, especially at the level of immature blasts. Single-cell RNA-sequencing (scRNA-seq) enables precise determination of cell state using thousands of markers, thus providing an opportunity to re-examine present-day classification schemes of acute leukemia. Here, we developed a detailed reference map of human bone marrow hematopoiesis from 263,519 single-cell transcriptomes spanning 55 cellular states. Cell state annotations were benchmarked against purified cell populations, and in-depth characterization of gene expression programs underlying hematopoietic differentiation was undertaken. Projection of single-cell transcriptomes from 175 samples spanning acute myeloid leukemia (AML), mixed phenotype acute leukemia (MPAL), and acute erythroid leukemia (AEL) revealed 11 subtypes involving distinct stages of hematopoietic differentiation. These included AML subtypes with notable lymphoid or erythroid lineage priming, challenging traditional diagnostic boundaries between AML, MPAL, and AEL. Quantification of lineage priming in bulk patient cohorts revealed specific genetic alterations associated with this unconventional lineage priming. Integration of transcriptional and genetic information at the single-cell level revealed how genetic subclones can induce lineage restriction, differentiation blocks, or expansion of mature myeloid cells. Furthermore, we demonstrate that distinct cellular hierarchies can co-exist within individual patients, providing insight into AML evolution in response to varying selection pressures. Together, precise mapping of hematopoietic cell states can serve as a foundation for refining disease classification in acute leukemia and understanding response or resistance to emerging therapies.

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“…Thus, CH-intrinsic signaling and transcriptional changes are likely intermingled with CH-extrinsic effects on non-mutated cell populations. Future investigation of T cell function and specificity could help decipher the role of adaptive immune processes in CH and define microenvironmental shifts in response to these alterations 32 .…”

Section: Discussionmentioning

confidence: 99%

Multiomic Profiling of Human Clonal Hematopoiesis Reveals Genotype and Cell-Specific Inflammatory Pathway Activation

Heimlich

Bhat

Parker

et al. 2022

Preprint

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Clonal hematopoiesis (CH) is an age-associated phenomenon that increases risk for hematologic malignancy and cardiovascular disease. CH is thought to increase cardiovascular disease risk through inflammation in the peripheral blood1. Here, we profile peripheral blood gene expression in 104,566 single cells from a cohort of 17 CH patients and 6 controls. We discovered that patients harboring DNMT3A and TET2 CH mutations at baseline and in response to IL-6 stimulation confer a pro-inflammatory profile to CD14+ monocytes through previously unrecognized pathways including Macrophage Inhibitory Factor (MIF). A germline genetic variant in MIF modifies TET2 CH cardiovascular disease risk. Using mitochondrial lineage tracing, we used a novel method to compare gene expression between mutated and non-mutated cells within individual CH patients. We found that the mutated CH monocytes, but not non-mutated monocytes are pro-inflammatory, explaining why patients with larger CH clones have increased cardiovascular disease risk.

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Single-Cell Multiomics Reveals Clonal T-Cell Expansions and Exhaustion in Blastic Plasmacytoid Dendritic Cell Neoplasm

Cited by 7 publications

References 51 publications

WAT3R: recovery of T-cell receptor variable regions from 3′ single-cell RNA-sequencing

WAT3R: recovery of T-cell receptor variable regions from 3′ single-cell RNA-sequencing

Single-cell transcriptional mapping reveals genetic and non-genetic determinants of aberrant differentiation in AML

Multiomic Profiling of Human Clonal Hematopoiesis Reveals Genotype and Cell-Specific Inflammatory Pathway Activation

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