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      GPNMB +Gal‐3 + hepatic parenchymal cells promote immunosuppression and hepatocellular carcinogenesis

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          Abstract

          Hepatocellular carcinoma (HCC) formation is a multi‐step pathological process that involves evolution of a heterogeneous immunosuppressive tumor microenvironment. However, the specific cell populations involved and their origins and contribution to HCC development remain largely unknown. Here, comprehensive single‐cell transcriptome sequencing was applied to profile rat models of toxin‐induced liver tumorigenesis and HCC patients. Specifically, we identified three populations of hepatic parenchymal cells emerging during HCC progression, termed metabolic hepatocytes (HC Meta), Epcam + population with differentiation potential (EP +Diff) and immunosuppressive malignant transformation subset (MT Immu). These distinct subpopulations form an oncogenic trajectory depicting a dynamic landscape of hepatocarcinogenesis, with signature genes reflecting the transition from EP +Diff to MT Immu. Importantly, GPNMB +Gal‐3 + MT Immu cells exhibit both malignant and immunosuppressive properties. Moreover, SOX18 is required for the generation and malignant transformation of GPNMB +Gal‐3 + MT Immu cells. Enrichment of the GPNMB +Gal‐3 + MT Immu subset was found to be associated with poor prognosis and a higher rate of recurrence in patients. Collectively, we unraveled the single‐cell HCC progression atlas and uncovered GPNMB +Gal‐3 + parenchymal cells as a major subset contributing to the immunosuppressive microenvironment thus malignance in HCC.

          Abstract

          Longitudinal single‐cell profiling of liver cancer in rats and patients unveils an emerging aggressive parenchymal cell population counteracting immune surveillance.

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          Most cited references32

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          SCENIC: Single-cell regulatory network inference and clustering

          Although single-cell RNA-seq is revolutionizing biology, data interpretation remains a challenge. We present SCENIC for the simultaneous reconstruction of gene regulatory networks and identification of cell states. We apply SCENIC to a compendium of single-cell data from tumors and brain, and demonstrate that the genomic regulatory code can be exploited to guide the identification of transcription factors and cell states. SCENIC provides critical biological insights into the mechanisms driving cellular heterogeneity.
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            Hepatocellular Carcinoma

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              Normalization and variance stabilization of single-cell RNA-seq data using regularized negative binomial regression

              Single-cell RNA-seq (scRNA-seq) data exhibits significant cell-to-cell variation due to technical factors, including the number of molecules detected in each cell, which can confound biological heterogeneity with technical effects. To address this, we present a modeling framework for the normalization and variance stabilization of molecular count data from scRNA-seq experiments. We propose that the Pearson residuals from “regularized negative binomial regression,” where cellular sequencing depth is utilized as a covariate in a generalized linear model, successfully remove the influence of technical characteristics from downstream analyses while preserving biological heterogeneity. Importantly, we show that an unconstrained negative binomial model may overfit scRNA-seq data, and overcome this by pooling information across genes with similar abundances to obtain stable parameter estimates. Our procedure omits the need for heuristic steps including pseudocount addition or log-transformation and improves common downstream analytical tasks such as variable gene selection, dimensional reduction, and differential expression. Our approach can be applied to any UMI-based scRNA-seq dataset and is freely available as part of the R package sctransform, with a direct interface to our single-cell toolkit Seurat.
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                Author and article information

                Contributors
                karenmeng_0521@163.com
                aimin@fjmu.edu.cn
                zhouzhaocai@fudan.edu.cn
                weilixin_smmu@163.com
                Journal
                EMBO J
                EMBO J
                10.1002/(ISSN)1460-2075
                EMBJ
                embojnl
                The EMBO Journal
                John Wiley and Sons Inc. (Hoboken )
                0261-4189
                1460-2075
                27 November 2023
                December 2023
                27 November 2023
                : 42
                : 24 ( doiID: 10.1002/embj.v42.24 )
                : e114060
                Affiliations
                [ 1 ] Tumor Immunology and Gene Therapy Center Third Affiliated Hospital of Second Military Medical University Shanghai China
                [ 2 ] Department of Medical Ultrasound, Shanghai Tenth People's Hospital Tongji University Cancer Center, Tongji University School of Medicine Shanghai China
                [ 3 ] Nursing Department Affiliated Hospital of Nantong University, Nantong University Nantong China
                [ 4 ] The School of Basic Medical Sciences of Fujian Medical University, Fujian Medical University Fuzhou China
                [ 5 ] Department of Hepatic Surgery, the Eastern Hepatobiliary Surgery Hospital Second Military Medical University Shanghai China
                [ 6 ] State Key Laboratory of Genetic Engineering, School of Life Sciences, Zhongshan Hospital Fudan University Shanghai China
                Author notes
                [*] [* ] Corresponding author. Tel/Fax: +86 21 81875332; E‐mail: karenmeng_0521@ 123456163.com

                Corresponding author. Tel/Fax: +86 591 22862869; E‐mail: aimin@ 123456fjmu.edu.cn

                Corresponding author. Tel: E‐mail: zhouzhaocai@ 123456fudan.edu.cn

                Corresponding author. Tel/Fax: +86 21 81875332; E‐mail: weilixin_smmu@ 123456163.com

                [ † ]

                These authors contributed equally to this work

                Author information
                https://orcid.org/0009-0009-4240-3282
                https://orcid.org/0000-0002-3884-2575
                https://orcid.org/0000-0003-0856-2318
                https://orcid.org/0000-0003-4099-4882
                https://orcid.org/0000-0002-3141-0315
                https://orcid.org/0000-0002-5441-3922
                https://orcid.org/0000-0002-9526-5348
                Article
                EMBJ2023114060
                10.15252/embj.2023114060
                10711661
                38009297
                0be0f36f-527c-49b7-b0b4-94298850da40
                © 2023 The Authors. Published under the terms of the CC BY NC ND 4.0 license

                This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.

                History
                : 23 September 2023
                : 20 March 2023
                : 04 October 2023
                Page count
                Figures: 9, Tables: 3, Pages: 19, Words: 12425
                Funding
                Funded by: National Key R&D Program of China
                Award ID: 2020YFA0803200
                Funded by: National Natural Science Foundation of China , doi 10.13039/501100001809;
                Award ID: 32070710
                Award ID: 82222052
                Award ID: 81822035
                Award ID: 81725014
                Award ID: 92168116
                Award ID: 82150112
                Award ID: 81972876
                Award ID: 31930026
                Award ID: 81902806
                Award ID: 82373251
                Award ID: 81972599
                Funded by: The Foundation of the Finance Department of Fujian Province of China
                Award ID: 21SCZZX002
                Categories
                Article
                Articles
                Custom metadata
                2.0
                11 December 2023
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.3.5 mode:remove_FC converted:11.12.2023

                Molecular biology
                hepatocellular carcinoma,immunosuppressive microenvironment,malignant transformation,cancer,immunology

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