Background: Hepatocellular carcinoma (HCC) is one of the leading causes of tumour-related death. T cells and cytokines play a critical role in tumour progression, but the T cell landscape correlated with HCC prognosis remains undepicted.
Methods: The prognostic significance of intra-tumoural immune cells, chemokines and cytokines were analysed using mass cytometry, bulk RNA sequencing and scRNA-seq data with survival information. The signature of CD4+CD8+ double positive T (DPT) cells was constructed using scRNA-seq and quantified by ssGSEA scores, whose association with the response to atezolizumab plus bevacizumab was evaluated. Cellular cross-talk and spatial patterns were analysed by scRNA-seq and spatial transcriptomics. Flow cytometry, gene knockdown, transwell migration, co-culture assays, qPCR and wound healing assay were performed to further validate the DPT-associated niche.
Findings: Higher intra-tumoural levels of DPT cells, CD45RA+CD4+ conventional T cells, HBEGF and CX3CR1 were associated with unfavourable prognosis in HCC. In contrast, higher infiltration of CD161+CD45RA−CD4+ conventional T cells and CD8+ T cells correlated with prolonged survival. CD45+EpCAM+ and CD45+α-SMA+ cells were more frequent in short-term survivors. DPT infiltration was identified across HCC multi-cohorts and syngeneic mouse models. In patients receiving atezolizumab plus bevacizumab, responders exhibited higher DPT ssGSEA scores than non-responders. Multi-omics analyses indicated cross-talk and spatial association of DPT cells with capillary-associated endothelial cells, supporting a pro-tumour niche. HBEGF was positively correlated with DPT cells and highly expressed in endothelial compartments. Endothelial-derived HBEGF knockdown reduced DPT migration. Moreover, DPT co-culture increased expression of signatures associated with immunosuppressive checkpoints, chemokine signalling, epithelial–mesenchymal transition and stemness in Hep3B cells and promoted their migration.
Conclusion: Our findings depicted the prognostic immune landscape of HCC by identifying distinct T cell populations and molecular interactions. DPT cells emerged as a critical biomarker for poor prognosis, and the endothelial-derived HBEGF–DPT axis could represent a potential therapeutic target.
| [1] |
Rumgay H, Ferlay J, de Martel C, et al. Global, regional and national burden of primary liver cancer by subtype. Eur J Cancer. 2022; 161: 108-118.
|
| [2] |
Singal AG, Kanwal F, Llovet JM. Global trends in hepatocellular carcinoma epidemiology: implications for screening, prevention and therapy. Nat Rev Clin Oncol. 2023; 20(12): 864-884.
|
| [3] |
Llovet JM, Kelley RK, Villanueva A, et al. Hepatocellular carcinoma. Nat Rev Dis Primers. 2021; 7(1): 6.
|
| [4] |
Cheng X, Ge X, Zhang C, et al. Tryptophan suppresses FTH1-driven ferritinophagy, a key correlate of prognosis in hepatocellular carcinoma. Cell Prolif. 2025; 59(1):e70074.
|
| [5] |
Han H, Wang S, Ma L, et al. ASH2L-K312-Lac stimulates angiogenesis in tumors to expedite the malignant progression of hepatocellular carcinoma. Adv Sci (Weinh). 2025; 12(40):e09477.
|
| [6] |
Hong H, Han H, Wang L, et al. ABCF1-K430-Lactylation promotes HCC malignant progression via transcriptional activation of HIF1 signaling pathway. Cell Death Differ. 2025; 32(4): 613-631.
|
| [7] |
Binnewies M, Roberts EW, Kersten K, et al. Understanding the tumor immune microenvironment (TIME) for effective therapy. Nat Med. 2018; 24(5): 541-550.
|
| [8] |
Shen KY, Zhu Y, Xie SZ, Qin LX. Immunosuppressive tumor microenvironment and immunotherapy of hepatocellular carcinoma: current status and prospectives. J Hematol Oncol. 2024; 17(1): 25.
|
| [9] |
Lim CJ, Lee YH, Pan L, et al. Multidimensional analyses reveal distinct immune microenvironment in hepatitis B virus-related hepatocellular carcinoma. Gut. 2019; 68(5): 916-927.
|
| [10] |
Chew V, Lai L, Pan L, et al. Delineation of an immunosuppressive gradient in hepatocellular carcinoma using high-dimensional proteomic and transcriptomic analyses. Proc Natl Acad Sci U S A. 2017; 114(29): E5900-E5909.
|
| [11] |
Zheng B, Wang D, Qiu X, et al. Trajectory and functional analysis of PD-1(high) CD4(+)CD8(+) T cells in hepatocellular carcinoma by single-cell cytometry and transcriptome sequencing. Adv Sci (Weinh). 2020; 7(13):2000224.
|
| [12] |
Prawira A, Xu H, Mei Y, et al. Targeting Treg-fibroblast interaction to enhance immunotherapy in steatotic liver disease-related hepatocellular carcinoma. Gut. 2025; 75(1): 105-118.
|
| [13] |
Lee YH, Chuah S, Nguyen PHD, et al. IFNgamma(-)IL-17(+) CD8 T cells contribute to immunosuppression and tumor progression in human hepatocellular carcinoma. Cancer Lett. 2023; 552:215977.
|
| [14] |
Xue R, Zhang Q, Cao Q, et al. Liver tumour immune microenvironment subtypes and neutrophil heterogeneity. Nature. 2022; 612(7938): 141-147.
|
| [15] |
Zhu AX, Abbas AR, de Galarreta MR, et al. Molecular correlates of clinical response and resistance to atezolizumab in combination with bevacizumab in advanced hepatocellular carcinoma. Nat Med. 2022; 28(8): 1599-1611.
|
| [16] |
Johnson WE, Li C, Rabinovic A. Adjusting batch effects in microarray expression data using empirical Bayes methods. Biostatistics. 2006; 8(1): 118-127.
|
| [17] |
Li Z, Pai R, Gupta S, et al. Presence of onco-fetal neighborhoods in hepatocellular carcinoma is associated with relapse and response to immunotherapy. Nat Cancer. 2024; 5(1): 167-186.
|
| [18] |
Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014; 15(12): 550.
|
| [19] |
Hao Y, Hao S, Andersen-Nissen E, et al. Integrated analysis of multimodal single-cell data. Cell. 2021; 184(13): 3573-3587.e29.
|
| [20] |
Germain P-L, Lun A, Garcia Meixide C, Macnair W, Robinson MD. Doublet identification in single-cell sequencing data using scDblFinder. F1000Res. 2021; 10: 979.
|
| [21] |
Korsunsky I, Millard N, Fan J, et al. Fast, sensitive and accurate integration of single-cell data with harmony. Nat Methods. 2019; 16(12): 1289-1296.
|
| [22] |
Becht E, McInnes L, Healy J, et al. Dimensionality reduction for visualizing single-cell data using UMAP. Nat Biotechnol. 2018; 37: 38-44.
|
| [23] |
Zhang L, Yu X, Zheng L, et al. Lineage tracking reveals dynamic relationships of T cells in colorectal cancer. Nature. 2018; 564(7735): 268-272.
|
| [24] |
Zheng L, Qin S, Si W, et al. Pan-cancer single-cell landscape of tumor-infiltrating T cells. Science. 2021; 374(6574):abe6474.
|
| [25] |
Hänzelmann S, Castelo R, Guinney J. GSVA: gene set variation analysis for microarray and RNA-seq data. BMC Bioinformatics. 2013; 14: 7.
|
| [26] |
Trapnell C, Cacchiarelli D, Grimsby J, et al. The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells. Nat Biotechnol. 2014; 32(4): 381-386.
|
| [27] |
Jin S, Guerrero-Juarez CF, Zhang L, et al. Inference and analysis of cell-cell communication using CellChat. Nat Communs. 2021; 12(1): 1088.
|
| [28] |
Schad SE, Chow A, Mangarin L, et al. Tumor-induced double positive T cells display distinct lineage commitment mechanisms and functions. J Exp Med. 2022; 219(6):e20212169.
|
| [29] |
Germain RN. T-cell development and the CD4-CD8 lineage decision. Nat Rev Immunol. 2002; 2(5): 309-322.
|
| [30] |
Menard LC, Fischer P, Kakrecha B, et al. Renal cell carcinoma (RCC) tumors display large expansion of double positive (DP) CD4+CD8+ T cells with expression of exhaustion markers. Front Immunol. 2018; 9: 2728.
|
| [31] |
Bohner P, Chevalier MF, Cesson V, et al. Double positive CD4(+)CD8(+) T cells are enriched in urological cancers and favor T helper-2 polarization. Front Immunol. 2019; 10: 622.
|
| [32] |
Tang Y, Cui G, Liu H, et al. Converting “cold” to “hot”: epigenetics strategies to improve immune therapy effect by regulating tumor-associated immune suppressive cells. Cancer Commun (Lond). 2024; 44(6): 601-636.
|
| [33] |
Dong ZR, Sun D, Yang YF, et al. TMPRSS4 drives angiogenesis in hepatocellular carcinoma by promoting HB-EGF expression and proteolytic cleavage. Hepatology. 2020; 72(3): 923-939.
|
| [34] |
Korbecki J, Siminska D, Kojder K, et al. Fractalkine/CX3CL1 in neoplastic processes. Int J Mol Sci. 2020; 21(10): 3723.
|
| [35] |
Alsuliman A, Muftuoglu M, Khoder A, et al. A subset of virus-specific CD161(+) T cells selectively express the multidrug transporter MDR1 and are resistant to chemotherapy in AML. Blood. 2017; 129(6): 740-758.
|
| [36] |
Kamada T, Togashi Y, Tay C, et al. PD-1(+) regulatory T cells amplified by PD-1 blockade promote hyperprogression of cancer. Proc Natl Acad Sci U S A. 2019; 116(20): 9999-10008.
|
| [37] |
Kannappan V, Butcher K, Trela M, Nicholl I, Wang W, Attridge K. Interleukin 21 inhibits cancer-mediated FOXP3 induction in naive human CD4 T cells. Cancer Immunol Immunother. 2017; 66(5): 637-645.
|
| [38] |
Ruf B, Bruhns M, Babaei S, et al. Tumor-associated macrophages trigger MAIT cell dysfunction at the HCC invasive margin. Cell. 2023; 186(17):3686-3705 e32.
|
| [39] |
Lizier M, Anselmo A, Mantero S, et al. Fusion between cancer cells and macrophages occurs in a murine model of spontaneous neu+ breast cancer without increasing its metastatic potential. Oncotarget. 2016; 7(38): 60793-60806.
|
| [40] |
Manjunath Y, Porciani D, Mitchem JB, et al. Tumor-cell-macrophage fusion cells as liquid biomarkers and tumor enhancers in cancer. Int J Mol Sci. 2020; 21(5): 1872.
|
| [41] |
Xia C, Zhang Q, Pu Y, Hu Q, Wang Y. Cell fusion between tumor cells and macrophages promotes the metastasis of OSCC patient through the activation of the chemokine signaling pathway. Cancer Med. 2024; 13(4):e6940.
|
| [42] |
Shultes PV, Weaver DT, Tadele DS, Barker-Clarke RJ, Scott JG. Cell-cell fusion in cancer: the next cancer hallmark?. Int J Biochem Cell Biol. 2024; 175:106649.
|
| [43] |
Akhter MZ, Sharawat SK, Kumar V, et al. Aggressive serous epithelial ovarian cancer is potentially propagated by EpCAM(+)CD45(+) phenotype. Oncogene. 2018; 37(16): 2089-2103.
|
| [44] |
Reduzzi C, Vismara M, Gerratana L, et al. The curious phenomenon of dual-positive circulating cells: longtime overlooked tumor cells. Semin Cancer Biol. 2020; 60: 344-350.
|
RIGHTS & PERMISSIONS
2026 The Author(s). Clinical and Translational Medicine published by John Wiley & Sons Australia, Ltd on behalf of Shanghai Institute of Clinical Bioinformatics.
PDF
(7896KB)
