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Global characterization of megakaryocytes in bone marrow, peripheral blood, and cord blood by single-cell RNA sequencing

Abstract

Megakaryocytes (MK) are mainly derived from bone marrow and are mainly involved in platelet production. Studies have shown that MK derived from bone marrow may have immune function, and that MK from peripheral blood are associated with prostate cancer. Single-cell transcriptome sequencing can help us better understand the heterogeneity and potential function of MK cell populations in bone marrow (BM), peripheral Blood (PB), and cord blood (CB) of healthy and diseased people.We integrated more than 1.2 million single-cell transcriptome data from 132 samples of PB, BM, and CB from healthy individuals and patients from different dataset. We examined the MK (including MK and product of MK) by single-cell RNA sequencing data analysis methods and identification of MK-related protein expression by the Human Protein atlas. We investigate the relationship between the MK subtype and Non-Small Cell Lung Cancer (NSCLC) in 77 non-cancer and 402 NSCLC. We found that MK were widely distributed and the amount of MK in peripheral blood was more than that in bone marrow and there were specificity MK subtypes in peripheral blood. We found classical MK1 with typical MK characteristics and non-classical MK2 closely related to immunity which was the most common subtype in bone marrow and cord blood. Classical MK1 was closely related to Non-Small Cell Lung Cancer (NSCLC) and can be used as a diagnostic marker. MK2 may have potential adaptive immune function and play a role in tumor NSCLC and autoimmune diseases Systemic Lupus Erythematosus. MK have 14 subtypes and are widely distributed in PB, CB, and BM. MK subtypes are closely related to immunity and have potential to be a diagnostic indicator of NSCLC.

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Fig. 1: Identification of MK Cell Population in the bone marrow, peripheral blood, and cord blood samples from healthy and diseased donors.
Fig. 2: MK clustering and subtypes analysis.
Fig. 3: Distributional Difference of MK Subtypes in bone marrow, peripheral blood, and cord blood.
Fig. 4: Overview of MK subtypes in all healthy and diseased samples in bone marrow, peripheral blood, and cord blood.
Fig. 5: MK subtypes associated with immunity.
Fig. 6: Diagnostic efficacy of MK subtypes in NSCLC.

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Data availability

The scRNA-seq data of AML01-35 from GSE116256 in Gene Expression Omnibus (GEO) database, bone marrow01-25 from GSE120446, bone marrow26-31 from GSE116256, peripheral blood06-10 from GSE128066, peripheral blood12 from GSE132802, peripheral blood21-26 from GSE132802, peripheral blood27-31 from GSE96583, peripheral blood32 from GSE127471, and peripheral bloodCLL01-12 from GSE111014. The scRNA-seq data of HSCT01-04, peripheral blood01-05, and P01-11 from 10X Web (https://support.10xgenomics.com/single-cell-gene-expression/datasets) and MantonBM1-8 and MantonCB1-8 from Human Cell Atlas (HCA).

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Acknowledgements

We thank all authors and producers of the datasets derived from open database.

Funding

This work was funded by National Natural Science Foundation of China (81800195 Funding and 81460315), Key Clinical Projects of Peking University Third Hospital Authors’ contributions (BYSYZD2019026), interdisciplinary medicine Seed Fund of Peking University Acknowledgements (BMU2018MB004), Beijing Natural Science Foundation (7132183 and 7182178), Authors’ informationChina Health Promotion Foundation (CHPF-zlkysx-001), Scientific Research Foundation (20141114) from Health Commission of Jiangxi Province, and Science and Technology Research Foundation (GJJ14676) from Educational Commission of Jiangxi Province, China.

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HJ, XY, and XH conceived the project. WZ and CY analyzed the data. WZ, CY, XL, PY, JW, YC, WL, SL, XZ, XH, XY, and HJ contributed towards the interpretation of the data. All authors read and approved the final manuscript.

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Correspondence to Xue He, Xiaoliang Yuan or Hongmei Jing.

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Zhang, W., Yan, C., Liu, X. et al. Global characterization of megakaryocytes in bone marrow, peripheral blood, and cord blood by single-cell RNA sequencing. Cancer Gene Ther 29, 1636–1647 (2022). https://doi.org/10.1038/s41417-022-00476-z

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