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Volume 32, Issue 1
  • ISSN: 0929-8673
  • E-ISSN: 1875-533X

Abstract

Aims

The aim of the present study was to investigate the relationship between the cellular ecosystem and the progression of esophageal carcinoma (ESCA) based on the evolution of macrophages and to analyze the potential of using macrophages as a new therapeutic approach in ESCA treatment.

Background

Macrophage-based immunotherapy could be used for treating ESCA patients, but its clinical application is limited by the intra-tumor heterogeneity of macrophages.

Objective

The objective of this study was to analyze the diversity, differentiation trajectory, and intercellular communication of macrophages in ESCA and its prognostic significance.

Methods

Single-cell RNA sequencing (scRNA-seq) data in the GSE154763 dataset were downloaded from Gene Expression Omnibus (GEO) to identify cell clusters and annotate cell types using the Seurat R package. The scRNA-seq profiles of macrophages were extracted, and cluster analysis was performed to identify macrophage subsets. The differentiation trajectories of macrophage subgroups were visualized employing Monocle2. Finally, ligand-receptor pairs and communication intensity among the classified subgroups were analyzed using Cell Chat.

Results

A total of 8 cell types were identified between ESCA tissues and paracancer tissues. The most abundant macrophages in ESCA tissues were further divided into 5 cell clusters. Compared with the normal tissues, the proportion of HSPA6+ macrophages in ESCA tissues increased the most, and the number of ligand-receptor pairs that mediated the communication of HSPA6+ macrophages with mast cells and monocytes also increased significantly. More importantly, a high proportion of HSPA6+ macrophages was inversely correlated with the survival outcomes for ESCA patients.

Conclusions

This study analyzed the diversity, distribution and differentiation trajectory of macrophages in ESCA tissues at single-cell level and classified a prognostic macrophage subtype (HSPA6+ macrophages) of ESCA, providing a theoretical basis for macrophage-targeted therapy in ESCA.

© 2025 Bentham Science Publishers
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2024-02-14
2024-12-25

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References

  1. SheikhM. RoshandelG. McCormackV. MalekzadehR. Current status and future prospects for esophageal cancer.Cancers202315376510.3390/cancers1503076536765722
     [Google Scholar]
  2. RaiV. AbdoJ. AgrawalD.K. Biomarkers for early detection, prognosis, and therapeutics of esophageal cancers.Int. J. Mol. Sci.2023244331610.3390/ijms2404331636834728
     [Google Scholar]
  3. VisaggiP. BarberioB. GhisaM. RibolsiM. SavarinoV. FassanM. ValmasoniM. MarchiS. de BortoliN. SavarinoE. Modern diagnosis of early esophageal cancer: From blood biomarkers to advanced endoscopy and artificial intelligence.Cancers20211313316210.3390/cancers1313316234202763
     [Google Scholar]
  4. LiQ. LiuT. DingZ. Neoadjuvant immunotherapy for resectable esophageal cancer: A review.Front. Immunol.202213105184110.3389/fimmu.2022.105184136569908
     [Google Scholar]
  5. LiM. WeiJ. XuG. LiuY. ZhuJ. Surgery combined with molecular targeted therapy successfully treated giant esophageal gastrointestinal stromal tumor.Oncologie202224234935610.32604/oncologie.2022.022436
     [Google Scholar]
  6. PichelR.C. AraújoA. DominguesV.D.S. SantosJ.N. FreireE. MendesA.S. RomãoR. AraújoA. Best supportive care of the patient with oesophageal cancer.Cancers20221424626810.3390/cancers1424626836551753
     [Google Scholar]
  7. LagergrenJ. SmythE. CunninghamD. LagergrenP. Oesophageal cancer.Lancet2017390101102383239610.1016/S0140‑6736(17)31462‑928648400
     [Google Scholar]
  8. ChenL. LuL. GongX. XuY. ChuX. HuangG. Gastric cancer with bone marrow invasion and disseminated intravascular coagulation: A case report.Oncologie202224359960410.32604/oncologie.2022.023310
     [Google Scholar]
  9. SiegelR.L. MillerK.D. WagleN.S. JemalA. Cancer statistics, 2023.CA Cancer J. Clin.2023731174810.3322/caac.2176336633525
     [Google Scholar]
  10. MorganE. SoerjomataramI. RumgayH. ColemanH.G. ThriftA.P. VignatJ. LaversanneM. FerlayJ. ArnoldM. The global landscape of esophageal squamous cell carcinoma and esophageal adenocarcinoma incidence and mortality in 2020 and projections to 2040: New estimates from globocan 2020.Gastroenterology2022163364965810.1053/j.gastro.2022.05.05435671803
     [Google Scholar]
  11. LiJ. LiL. YouP. WeiY. XuB. Towards artificial intelligence to multi-omics characterization of tumor heterogeneity in esophageal cancer.Semin. Cancer Biol.202391354910.1016/j.semcancer.2023.02.00936868394
     [Google Scholar]
  12. di PietroM. CantoM.I. FitzgeraldR.C. Endoscopic management of early adenocarcinoma and squamous cell carcinoma of the esophagus: Screening, diagnosis, and therapy.Gastroenterology2018154242143610.1053/j.gastro.2017.07.04128778650
     [Google Scholar]
  13. AndersonN.R. MinutoloN.G. GillS. KlichinskyM. Macrophage-based approaches for cancer immunotherapy.Cancer Res.20218151201120810.1158/0008‑5472.CAN‑20‑299033203697
     [Google Scholar]
  14. ChenS. SaeedA.F.U.H. LiuQ. JiangQ. XuH. XiaoG.G. RaoL. DuoY. Macrophages in immunoregulation and therapeutics.Signal Transduct. Target. Ther.20238120710.1038/s41392‑023‑01452‑137211559
     [Google Scholar]
  15. DuX. ShiH. LiuH. ZhouL. XieA. GuoJ. Angiogenic gene PTK2 is a potential biomarker of gestational diabetes mellitus and is significantly associated with breast cancer immune infiltration.Oncologie202224476978710.32604/oncologie.2022.026248
     [Google Scholar]
  16. BiedM. HoW.W. GinhouxF. BlériotC. Roles of macrophages in tumor development: A spatiotemporal perspective.Cell. Mol. Immunol.202320998399210.1038/s41423‑023‑01061‑637429944
     [Google Scholar]
  17. EftekhariA. KryschiC. PamiesD. GulecS. AhmadianE. JanasD. DavaranS. KhalilovR. Natural and synthetic nanovectors for cancer therapy.Nanotheranostics20237323625710.7150/ntno.7756437064613
     [Google Scholar]
  18. NasibovaA. Generation of nanoparticles in biological systems and their application prospects.Adv. Biol. Earth Sci20238140146
     [Google Scholar]
  19. AhmadianE. DizajS.M. SharifiS. ShahiS. KhalilovR. EftekhariA. HasanzadehM. The potential of nanomaterials in theranostics of oral squamous cell carcinoma: Recent progress.Trends Analyt. Chem.201911616717610.1016/j.trac.2019.05.009
     [Google Scholar]
  20. KhalilovR. A comprehensive review of advanced nano-biomaterials in regenerative medicine and drug delivery.Adv. Biol. Earth Sci.202381518
     [Google Scholar]
  21. ButlerA. HoffmanP. SmibertP. PapalexiE. SatijaR. Integrating single-cell transcriptomic data across different conditions, technologies, and species.Nat. Biotechnol.201836541142010.1038/nbt.409629608179
     [Google Scholar]
  22. ChengS. LiZ. GaoR. XingB. GaoY. YangY. QinS. ZhangL. OuyangH. DuP. JiangL. ZhangB. YangY. WangX. RenX. BeiJ.X. HuX. BuZ. JiJ. ZhangZ. A pan-cancer single-cell transcriptional atlas of tumor infiltrating myeloid cells.Cell20211843792809.e2310.1016/j.cell.2021.01.01033545035
     [Google Scholar]
  23. HuC. LiT. XuY. ZhangX. LiF. BaiJ. ChenJ. JiangW. YangK. OuQ. LiX. WangP. ZhangY. CellMarker 2.0: An updated database of manually curated cell markers in human/mouse and web tools based on scRNA-seq data.Nucleic Acids Res.202351D1D870D87610.1093/nar/gkac94736300619
     [Google Scholar]
  24. MartinezF.O. HelmingL. GordonS. Alternative activation of macrophages: An immunologic functional perspective.Annu. Rev. Immunol.200927145148310.1146/annurev.immunol.021908.13253219105661
     [Google Scholar]
  25. TrapnellC. CacchiarelliD. GrimsbyJ. PokharelP. LiS. MorseM. LennonN.J. LivakK.J. MikkelsenT.S. RinnJ.L. The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells.Nat. Biotechnol.201432438138610.1038/nbt.285924658644
     [Google Scholar]
  26. JinS. Guerrero-JuarezC.F. ZhangL. ChangI. RamosR. KuanC.H. MyungP. PlikusM.V. NieQ. Inference and analysis of Cell-Cell communication using CellChat.Nat. Commun.2021121108810.1038/s41467‑021‑21246‑933597522
     [Google Scholar]
  27. QianB.Z. PollardJ.W. Macrophage diversity enhances tumor progression and metastasis.Cell20101411395110.1016/j.cell.2010.03.01420371344
     [Google Scholar]
  28. MovahediK. LaouiD. GysemansC. BaetenM. StangéG. Van den BosscheJ. MackM. PipeleersD. In’t VeldP. De BaetselierP. Van GinderachterJ.A. Different tumor microenvironments contain functionally distinct subsets of macrophages derived from Ly6C(high) monocytes.Cancer Res.201070145728573910.1158/0008‑5472.CAN‑09‑467220570887
     [Google Scholar]
  29. SiefertJ.C. CioniB. MuraroM.J. AlshalalfaM. ViviéJ. van der PoelH.G. SchootsI.G. BekersE. FengF.Y. WesselsL.F.A. ZwartW. BergmanA.M. The prognostic potential of human prostate cancer-associated macrophage subtypes as revealed by single-cell transcriptomics.Mol. Cancer Res.202119101778179110.1158/1541‑7786.MCR‑20‑074034131070
     [Google Scholar]
  30. YangQ. ZhangH. WeiT. LinA. SunY. LuoP. ZhangJ. Single-cell RNA sequencing reveals the heterogeneity of tumor-associated macrophage in non-small cell lung cancer and differences between sexes.Front. Immunol.20211275672210.3389/fimmu.2021.75672234804043
     [Google Scholar]
  31. ChenA.X. GartrellR.D. ZhaoJ. UpadhyayulaP.S. ZhaoW. YuanJ. MinnsH.E. DovasA. BruceJ.N. LasorellaA. IavaroneA. CanollP. SimsP.A. RabadanR. Single-cell characterization of macrophages in glioblastoma reveals MARCO as a mesenchymal pro-tumor marker.Genome Med.20211318810.1186/s13073‑021‑00906‑x34011400
     [Google Scholar]
  32. BauerA.K. VelmuruganK. XiongK.N. AlexanderC.M. XiongJ. BrooksR. Epiregulin is required for lung tumor promotion in a murine two-stage carcinogenesis model.Mol. Carcinog.20175619410510.1002/mc.2247526894620
     [Google Scholar]
  33. YangJ. LiuL. LiM. HuangX. YangH. LiK. Naringenin inhibits pro-inflammatory cytokine production in macrophages through inducing MT1G to suppress the activation of NF-κB.Mol. Immunol.202113715516210.1016/j.molimm.2021.07.00334252709
     [Google Scholar]
  34. ShermanM.H. Lipid carriers in cancer: Context matters.Cancer Res.202181164186418710.1158/0008‑5472.CAN‑21‑193034400469
     [Google Scholar]
  35. HuiB. LuC. LiH. HaoX. LiuH. ZhuoD. WangQ. LiZ. LiuL. WangX. GuY. TangW. Inhibition of APOE potentiates immune checkpoint therapy for cancer.Int. J. Biol. Sci.202218145230524010.7150/ijbs.7011736147474
     [Google Scholar]
  36. SmithK.J. TwalW.O. SoodavarF. VirellaG. Lopes-VirellaM.F. HammadS.M. Heat shock protein 70B′ (HSP70B′) expression and release in response to human oxidized low density lipoprotein immune complexes in macrophages.J. Biol. Chem.201028521159851599310.1074/jbc.M110.11360520348092
     [Google Scholar]
  37. ChengK. CaiN. ZhuJ. YangX. LiangH. ZhangW. Tumor-associated macrophages in liver cancer: From mechanisms to therapy.Cancer Commun.202242111112114010.1002/cac2.1234536069342
     [Google Scholar]
  38. BuechlerM.B. FuW. TurleyS.J. Fibroblast-macrophage reciprocal interactions in health, fibrosis, and cancer.Immunity202154590391510.1016/j.immuni.2021.04.02133979587
     [Google Scholar]
  39. MatsudaM. SekiE. Hepatic stellate cell–macrophage crosstalk in liver fibrosis and carcinogenesis.Semin. Liver Dis.202040330732010.1055/s‑0040‑170887632242330
     [Google Scholar]
  40. DehneN. MoraJ. NamgaladzeD. WeigertA. BrüneB. Cancer cell and macrophage cross-talk in the tumor microenvironment.Curr. Opin. Pharmacol.201735121910.1016/j.coph.2017.04.00728538141
     [Google Scholar]
  41. CruzM.S. LoureiroJ.P. OliveiraM.J. MacedoM.F. The iNKT cell–macrophage axis in homeostasis and disease.Int. J. Mol. Sci.2022233164010.3390/ijms2303164035163561
     [Google Scholar]
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Identification and Characterization of Prognostic Macrophage Subpopulations for Human Esophageal Carcinoma
Curr. Med. Chem. 32, 123 (2025); https://doi.org/10.2174/0109298673284207240108105724
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Supplementary material is available on the publisher’s website along with the published article. Fig. Cluster analysis after quality control. Fig. Heatmap and bubble map.

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  • Article Type:     Research Article
Keyword(s): cell differentiation trajectory; cellular communication; Esophageal carcinoma; heterogeneity; macrophages; prognosis

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