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2000
Volume 25, Issue 5
  • ISSN: 1389-2029
  • E-ISSN: 1875-5488

Abstract

Background

Targeted therapies have improved the clinical outcomes of most patients with cancer. However, the heterogeneity of gastric cancer remains a major hurdle for precision treatment. Further investigations into tumor microenvironment heterogeneity are required to resolve these problems.

Methods

In this study, bioinformatic analyses, including metabolism analysis, pathway enrichment, differentiation trajectory inference, regulatory network construction, and survival analysis, were applied to gain a comprehensive understanding of tumor microenvironment biology within gastric cancer using single-cell RNA-seq and public datasets and experiments were carried out to confirm the conclusions of these analyses.

Results

We profiled heterogeneous single-cell atlases and identified eight cell populations with differential expression patterns. We identified two cancer-associated fibroblasts (CAFs) subtypes, with particular emphasis on the role of inflammatory cancer-associated fibroblasts (iCAFs) in EMT and lipid metabolic crosstalk within the tumor microenvironment. Notably, we detected two differentiation states of iCAFs that existed in different tissues with discrepant expression of genes involved in immuno-inflammation or ECM remodeling. Moreover, investigation of tumor-infiltrating myeloid cells has revealed the functional diversity of myeloid cell lineages in gastric cancer. Of which a proliferative cell lineage named C1QC+MKI67+TAMs was recognized with high immunosuppressive capacities, suggesting it has immune suppression and cell proliferation functions in the tumor niche. Finally, we explored regulatory networks based on ligand-receptor pairs and found crucial pro-tumor crosstalk between CAFs and myeloid cells in the tumor microenvironment (TME).

Conclusion

These findings provide insights for future cancer treatments and drug discovery.

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2024-10-01
2024-11-22
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References

  1. SungH. FerlayJ. SiegelR.L. LaversanneM. SoerjomataramI. JemalA. BrayF. Global Cancer Statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries.CA Cancer J. Clin.202171320924910.3322/caac.2166033538338
    [Google Scholar]
  2. SundarR. LiuD.H.W. HutchinsG.G.A. SlaneyH.L. SilvaA.N.S. OostingJ. HaydenJ.D. HewittL.C. NgC.C.Y. MangalvedhekarA. NgS.B. TanI.B.H. TanP. GrabschH.I. Spatial profiling of gastric cancer patient-matched primary and locoregional metastases reveals principles of tumour dissemination.Gut202170101823183210.1136/gutjnl‑2020‑32080533229445
    [Google Scholar]
  3. HinshawD.C. ShevdeL.A. The tumor microenvironment innately modulates cancer progression.Cancer Res.201979184557456610.1158/0008‑5472.CAN‑18‑396231350295
    [Google Scholar]
  4. BejaranoL. JordāoM.J.C. JoyceJ.A. Therapeutic targeting of the tumor microenvironment.Cancer Discov.202111493395910.1158/2159‑8290.CD‑20‑180833811125
    [Google Scholar]
  5. JinM.Z. JinW.L. The updated landscape of tumor microenvironment and drug repurposing.Signal Transduct. Target. Ther.20205116610.1038/s41392‑020‑00280‑x32843638
    [Google Scholar]
  6. ChenX. SongE. Turning foes to friends: Targeting cancer-associated fibroblasts.Nat. Rev. Drug Discov.20191829911510.1038/s41573‑018‑0004‑130470818
    [Google Scholar]
  7. ArandkarS. FurthN. ElishaY. NatarajN.B. van der KuipH. YardenY. AulitzkyW. UlitskyI. GeigerB. OrenM. Altered p53 functionality in cancer-associated fibroblasts contributes to their cancer-supporting features.Proc. Natl. Acad. Sci. USA2018115256410641510.1073/pnas.171907611529866855
    [Google Scholar]
  8. HerreraM. Berral-GonzálezA. López-CadeI. Galindo-PumariñoC. Bueno-FortesS. Martín-MerinoM. CarratoA. OcañaA. De La PintaC. López-AlfonsoA. PeñaC. García-BarberánV. De Las RivasJ. Cancer-associated fibroblast-derived gene signatures determine prognosis in colon cancer patients.Mol. Cancer20212017310.1186/s12943‑021‑01367‑x33926453
    [Google Scholar]
  9. MaoX. XuJ. WangW. LiangC. HuaJ. LiuJ. ZhangB. MengQ. YuX. ShiS. Crosstalk between cancer-associated fibroblasts and immune cells in the tumor microenvironment: New findings and future perspectives.Mol. Cancer202120113110.1186/s12943‑021‑01428‑134635121
    [Google Scholar]
  10. SongM. HeJ. PanQ.Z. YangJ. ZhaoJ. ZhangY.J. HuangY. TangY. WangQ. HeJ. GuJ. LiY. ChenS. ZengJ. ZhouZ.Q. YangC. HanY. ChenH. XiangT. WengD.S. XiaJ.C. Cancer-associated fibroblast-mediated cellular crosstalk supports hepatocellular carcinoma progression.Hepatology20217351717173510.1002/hep.3179233682185
    [Google Scholar]
  11. PengZ. TongZ. RenZ. YeM. HuK. Cancer-associated fibroblasts and its derived exosomes: A new perspective for reshaping the tumor microenvironment.Mol. Med.20232916610.1186/s10020‑023‑00665‑y37217855
    [Google Scholar]
  12. LeiY. TangR. XuJ. WangW. ZhangB. LiuJ. YuX. ShiS. Applications of single-cell sequencing in cancer research: Progress and perspectives.J. Hematol. Oncol.20211419110.1186/s13045‑021‑01105‑234108022
    [Google Scholar]
  13. TavassolyI. GoldfarbJ. IyengarR. Systems biology primer: The basic methods and approaches.Essays Biochem.201862448750010.1042/EBC2018000330287586
    [Google Scholar]
  14. 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]
  15. KumarV. RamnarayananK. SundarR. PadmanabhanN. SrivastavaS. KoiwaM. YasudaT. KohV. HuangK.K. TayS.T. HoS.W.T. TanA.L.K. IshimotoT. KimG. ShabbirA. ChenQ. ZhangB. XuS. LamK.P. LumH.Y.J. TehM. YongW.P. SoJ.B.Y. TanP. Single-cell atlas of lineage states, tumor microenvironment, and subtype-specific expression programs in gastric cancer.Cancer Discov.202212367069110.1158/2159‑8290.CD‑21‑068334642171
    [Google Scholar]
  16. HaoY. HaoS. Andersen-NissenE. MauckW.M.III ZhengS. ButlerA. LeeM.J. WilkA.J. DarbyC. ZagerM. HoffmanP. StoeckiusM. PapalexiE. MimitouE.P. JainJ. SrivastavaA. StuartT. FlemingL.M. YeungB. RogersA.J. McElrathJ.M. BlishC.A. GottardoR. SmibertP. SatijaR. Integrated analysis of multimodal single-cell data.Cell20211841335733587.e2910.1016/j.cell.2021.04.04834062119
    [Google Scholar]
  17. WangT. DangN. TangG. LiZ. LiX. ShiB. XuZ. LiL. YangX. XuC. YeK. Integrating bulk and single-cell RNA sequencing reveals cellular heterogeneity and immune infiltration in hepatocellular carcinoma.Mol. Oncol.202216112195221310.1002/1878‑0261.1319035124891
    [Google Scholar]
  18. GuoX. ZhangY. ZhengL. ZhengC. SongJ. ZhangQ. KangB. LiuZ. JinL. XingR. GaoR. ZhangL. DongM. HuX. RenX. KirchhoffD. RoiderH.G. YanT. ZhangZ. Global characterization of T cells in non-small-cell lung cancer by single-cell sequencing.Nat. Med.201824797898510.1038/s41591‑018‑0045‑329942094
    [Google Scholar]
  19. HänzelmannS. CasteloR. GuinneyJ. GSVA: Gene set variation analysis for microarray and RNA-Seq data.BMC Bioinformatics2013141710.1186/1471‑2105‑14‑723323831
    [Google Scholar]
  20. ForoutanM. BhuvaD.D. LyuR. HoranK. CursonsJ. DavisM.J. Single sample scoring of molecular phenotypes.BMC Bioinformatics201819140410.1186/s12859‑018‑2435‑430400809
    [Google Scholar]
  21. WuY. YangS. MaJ. ChenZ. SongG. RaoD. ChengY. HuangS. LiuY. JiangS. LiuJ. HuangX. WangX. QiuS. XuJ. XiR. BaiF. ZhouJ. FanJ. ZhangX. GaoQ. Spatiotemporal immune landscape of colorectal cancer liver metastasis at single-cell level.Cancer Discov.202212113415310.1158/2159‑8290.CD‑21‑031634417225
    [Google Scholar]
  22. DeTomasoD. JonesM.G. SubramaniamM. AshuachT. YeC.J. YosefN. Functional interpretation of single cell similarity maps.Nat. Commun.2019101437610.1038/s41467‑019‑12235‑031558714
    [Google Scholar]
  23. QiuX. MaoQ. TangY. WangL. ChawlaR. PlinerH.A. TrapnellC. Reversed graph embedding resolves complex single- cell trajectories.Nat. Methods2017141097998210.1038/nmeth.440228825705
    [Google Scholar]
  24. AranD. LooneyA.P. LiuL. WuE. FongV. HsuA. ChakS. NaikawadiR.P. WoltersP.J. AbateA.R. ButteA.J. BhattacharyaM. Reference-based analysis of lung single-cell sequencing reveals a transitional profibrotic macrophage.Nat. Immunol.201920216317210.1038/s41590‑018‑0276‑y30643263
    [Google Scholar]
  25. WangH. GongP. ChenT. GaoS. WuZ. WangX. LiJ. MarjaniS.L. CostaJ. WeissmanS.M. QiF. PanX. LiuL. Colorectal cancer stem cell states uncovered by simultaneous single-cell analysis of transcriptome and telomeres.Adv. Sci.202188200432010.1002/advs.20200432033898197
    [Google Scholar]
  26. ZhangP. YangM. ZhangY. XiaoS. LaiX. TanA. DuS. LiS. Dissecting the single-cell transcriptome network underlying gastric premalignant lesions and early gastric cancer.Cell Rep.201927619341947.e510.1016/j.celrep.2019.04.05231067475
    [Google Scholar]
  27. ZhangM. HuS. MinM. NiY. LuZ. SunX. WuJ. LiuB. YingX. LiuY. Dissecting transcriptional heterogeneity in primary gastric adenocarcinoma by single cell RNA sequencing.Gut202170346447510.1136/gutjnl‑2019‑32036832532891
    [Google Scholar]
  28. LiH. CourtoisE.T. SenguptaD. TanY. ChenK.H. GohJ.J.L. KongS.L. ChuaC. HonL.K. TanW.S. WongM. ChoiP.J. WeeL.J.K. HillmerA.M. TanI.B. RobsonP. PrabhakarS. Reference component analysis of single-cell transcriptomes elucidates cellular heterogeneity in human colorectal tumors.Nat. Genet.201749570871810.1038/ng.381828319088
    [Google Scholar]
  29. ChenZ. ZhouL. LiuL. HouY. XiongM. YangY. HuJ. ChenK. Single-cell RNA sequencing highlights the role of inflammatory cancer-associated fibroblasts in bladder urothelial carcinoma.Nat. Commun.2020111507710.1038/s41467‑020‑18916‑533033240
    [Google Scholar]
  30. ZhangY. SongJ. ZhaoZ. YangM. ChenM. LiuC. JiJ. ZhuD. Single-cell transcriptome analysis reveals tumor immune microenvironment heterogenicity and granulocytes enrichment in colorectal cancer liver metastases.Cancer Lett.2020470849410.1016/j.canlet.2019.10.01631610266
    [Google Scholar]
  31. HamiltonP.T. AnholtB.R. NelsonB.H. Tumour immunotherapy: Lessons from predator–prey theory.Nat. Rev. Immunol.2022221276577510.1038/s41577‑022‑00719‑y35513493
    [Google Scholar]
  32. El-KenawiA. HänggiK. RuffellB. The immune microenvironment and cancer metastasis.Cold Spring Harb. Perspect. Med.2020104a03742410.1101/cshperspect.a03742431501262
    [Google Scholar]
  33. SuhailY. CainM.P. VanajaK. KurywchakP.A. LevchenkoA. KalluriR. Kshitiz Systems biology of cancer metastasis.Cell Syst.20199210912710.1016/j.cels.2019.07.00331465728
    [Google Scholar]
  34. HanC. LiuT. YinR. Biomarkers for cancer-associated fibroblasts.Biomark. Res.2020816410.1186/s40364‑020‑00245‑w33292666
    [Google Scholar]
  35. ElyadaE. BolisettyM. LaiseP. FlynnW.F. CourtoisE.T. BurkhartR.A. TeinorJ.A. BelleauP. BiffiG. LucitoM.S. SivajothiS. ArmstrongT.D. EngleD.D. YuK.H. HaoY. WolfgangC.L. ParkY. PreallJ. JaffeeE.M. CalifanoA. RobsonP. TuvesonD.A. Cross-species single-cell analysis of pancreatic ductal adenocarcinoma reveals antigen-presenting cancer-associated fibroblasts.Cancer Discov.2019981102112310.1158/2159‑8290.CD‑19‑009431197017
    [Google Scholar]
  36. Martínez-ReyesI. ChandelN.S. Cancer metabolism: Looking forward.Nat. Rev. Cancer2021211066968010.1038/s41568‑021‑00378‑634272515
    [Google Scholar]
  37. GongJ. LinY. ZhangH. LiuC. ChengZ. YangX. ZhangJ. XiaoY. SangN. QianX. WangL. CenX. DuX. ZhaoY. Reprogramming of lipid metabolism in cancer-associated fibroblasts potentiates migration of colorectal cancer cells.Cell Death Dis.202011426710.1038/s41419‑020‑2434‑z32327627
    [Google Scholar]
  38. SongG. XuS. ZhangH. WangY. XiaoC. JiangT. WuL. ZhangT. SunX. ZhongL. ZhouC. WangZ. PengZ. ChenJ. WangX. TIMP1 is a prognostic marker for the progression and metastasis of colon cancer through FAK-PI3K/AKT and MAPK pathway.J. Exp. Clin. Cancer Res.201635114810.1186/s13046‑016‑0427‑727644693
    [Google Scholar]
  39. XuQ. ChiaoP. SunY. Amphiregulin in cancer: New insights for translational medicine.Trends Cancer20162311111310.1016/j.trecan.2016.02.00228741529
    [Google Scholar]
  40. ZhouZ. CuiD. SunM.H. HuangJ.L. DengZ. HanB.M. SunX.W. XiaS.J. SunF. ShiF. CAFs-derived MFAP5 promotes bladder cancer malignant behavior through NOTCH2/HEY1 signaling.FASEB J.20203467970798810.1096/fj.201902659R32293074
    [Google Scholar]
  41. MichelisR. MilhemL. GaloukE. StemerG. AvivA. TadmorT. ShehadehM. ShvidelL. BarhoumM. BraesterA. Increased serum level of alpha-2 macroglobulin and its production by B-lymphocytes in chronic lymphocytic leukemia.Front. Immunol.20221395364410.3389/fimmu.2022.95364436119042
    [Google Scholar]
  42. YangH. SunB. FanL. MaW. XuK. HallS.R.R. WangZ. SchmidR.A. PengR.W. MartiT.M. GaoW. XuJ. YangW. YaoF. Multi-scale integrative analyses identify THBS2 + cancer-associated fibroblasts as a key orchestrator promoting aggressiveness in early-stage lung adenocarcinoma.Theranostics20221273104313010.7150/thno.6959035547750
    [Google Scholar]
  43. ZhengS. ZouY. TangY. YangA. LiangJ.Y. WuL. TianW. XiaoW. XieX. YangL. XieJ. WeiW. XieX. Landscape of cancer-associated fibroblasts identifies the secreted biglycan as a protumor and immunosuppressive factor in triple-negative breast cancer.OncoImmunology2022111202098410.1080/2162402X.2021.202098435003899
    [Google Scholar]
  44. ZhangL. LiZ. SkrzypczynskaK.M. FangQ. ZhangW. O’BrienS.A. HeY. WangL. ZhangQ. KimA. GaoR. OrfJ. WangT. SawantD. KangJ. BhattD. LuD. LiC.M. RapaportA.S. PerezK. YeY. WangS. HuX. RenX. OuyangW. ShenZ. EgenJ.G. ZhangZ. YuX. Single- cell analyses inform mechanisms of myeloid-targeted therapies in colon cancer.Cell20201812442459.e2910.1016/j.cell.2020.03.04832302573
    [Google Scholar]
  45. BrownC.C. GudjonsonH. PritykinY. DeepD. LavalléeV.P. MendozaA. FrommeR. MazutisL. AriyanC. LeslieC. Pe’erD. RudenskyA.Y. Transcriptional basis of mouse and human dendritic cell heterogeneity.Cell20191794846863.e2410.1016/j.cell.2019.09.03531668803
    [Google Scholar]
  46. GubinM.M. EsaulovaE. WardJ.P. MalkovaO.N. RunciD. WongP. NoguchiT. ArthurC.D. MengW. AlspachE. MedranoR.F.V. FronickC. FehlingsM. NewellE.W. FultonR.S. SheehanK.C.F. OhS.T. SchreiberR.D. ArtyomovM.N. High-dimensional analysis delineates myeloid and lymphoid compartment remodeling during successful immune-checkpoint cancer therapy.Cell2018175410141030.e1910.1016/j.cell.2018.09.03030343900
    [Google Scholar]
  47. ZhangR. QiF. ZhaoF. LiG. ShaoS. ZhangX. YuanL. FengY. Cancer-associated fibroblasts enhance tumor-associated macrophages enrichment and suppress NK cells function in colorectal cancer.Cell Death Dis.201910427310.1038/s41419‑019‑1435‑230894509
    [Google Scholar]
  48. de AzevedoR.A. ShoshanE. WhangS. MarkelG. JaiswalA.R. LiuA. CurranM.A. TravassosL.R. Bar-EliM. MIF inhibition as a strategy for overcoming resistance to immune checkpoint blockade therapy in melanoma.OncoImmunology202091184691510.1080/2162402X.2020.184691533344042
    [Google Scholar]
  49. MoonH.G. KimS. JeongJ.J. HanS.S. JarjourN.N. LeeH. Abboud-WernerS.L. ChungS. ChoiH.S. NatarajanV. AckermanS.J. ChristmanJ.W. ParkG.Y. Airway epithelial cell-derived colony stimulating factor-1 promotes allergen sensitization.Immunity2018492275287.e510.1016/j.immuni.2018.06.00930054206
    [Google Scholar]
  50. LinW. XuD. AustinC.D. CaplaziP. SengerK. SunY. JeetS. YoungJ. DelarosaD. SutoE. HuangZ. ZhangJ. YanD. CorzoC. BarckK. RajanS. LooneyC. GandhamV. LeschJ. LiangW.C. MaiE. NguH. RattiN. ChenY. MisnerD. LinT. DanilenkoD. KatavolosP. DoudemontE. UppalH. EasthamJ. MakJ. de AlmeidaP.E. BaoK. HadadianpourA. KeirM. CaranoR.A.D. DiehlL. XuM. WuY. WeimerR.M. DeVossJ. LeeW.P. BalazsM. WalshK. AlatsisK.R. MartinF. ZarrinA.A. Function of CSF1 and IL34 in macrophage homeostasis, inflammation, and cancer.Front. Immunol.201910201910.3389/fimmu.2019.0201931552020
    [Google Scholar]
  51. LiL. ZhuZ. ZhaoY. ZhangQ. WuX. MiaoB. CaoJ. FeiS. FN1, SPARC, and SERPINE1 are highly expressed and significantly related to a poor prognosis of gastric adenocarcinoma revealed by microarray and bioinformatics.Sci. Rep.201991782710.1038/s41598‑019‑43924‑x31127138
    [Google Scholar]
  52. WangD. WangX. SiM. YangJ. SunS. WuH. CuiS. QuX. YuX. Exosome-encapsulated miRNAs contribute to CXCL12/CXCR4-induced liver metastasis of colorectal cancer by enhancing M2 polarization of macrophages.Cancer Lett.2020474365210.1016/j.canlet.2020.01.00531931030
    [Google Scholar]
  53. RodriguezH. ZenklusenJ.C. StaudtL.M. DoroshowJ.H. LowyD.R. The next horizon in precision oncology: Proteogenomics to inform cancer diagnosis and treatment.Cell202118471661167010.1016/j.cell.2021.02.05533798439
    [Google Scholar]
  54. MateoJ. SteutenL. AftimosP. AndréF. DaviesM. GarraldaE. GeisslerJ. HusereauD. Martinez-LopezI. NormannoN. Reis-FilhoJ.S. StefaniS. ThomasD.M. WestphalenC.B. VoestE. Delivering precision oncology to patients with cancer.Nat. Med.202228465866510.1038/s41591‑022‑01717‑235440717
    [Google Scholar]
  55. SundarR. TanI.B.H. CheeC.E. Negative predictive biomarkers in colorectal cancer: PRESSING ahead.J. Clin. Oncol.201937333066306810.1200/JCO.19.0197731550189
    [Google Scholar]
  56. WangJ. XuB. Targeted therapeutic options and future perspectives for HER2-positive breast cancer.Signal Transduct. Target. Ther.2019413410.1038/s41392‑019‑0069‑231637013
    [Google Scholar]
  57. SundarR. TanP. Genomic analyses and precision oncology in gastroesophageal cancer: Forwards or backwards?Cancer Discov.201881141610.1158/2159‑8290.CD‑17‑129529311223
    [Google Scholar]
  58. XiaoY. YuD. Tumor microenvironment as a therapeutic target in cancer.Pharmacol. Ther.202122110775310.1016/j.pharmthera.2020.10775333259885
    [Google Scholar]
  59. BaderJ.E. VossK. RathmellJ.C. Targeting metabolism to improve the tumor microenvironment for cancer immunotherapy.Mol. Cell20207861019103310.1016/j.molcel.2020.05.03432559423
    [Google Scholar]
  60. PengC. XuY. WuJ. WuD. ZhouL. XiaX. TME-related biomimetic strategies against cancer.Int. J. Nanomedicine20241910913510.2147/IJN.S44113538192633
    [Google Scholar]
  61. JovicD. LiangX. ZengH. LinL. XuF. LuoY. Single-cell RNA sequencing technologies and applications: A brief overview.Clin. Transl. Med.2022123e69410.1002/ctm2.69435352511
    [Google Scholar]
  62. PapalexiE. SatijaR. Single-cell RNA sequencing to explore immune cell heterogeneity.Nat. Rev. Immunol.2018181354510.1038/nri.2017.7628787399
    [Google Scholar]
  63. DengG. ZhangX. ChenY. LiangS. LiuS. YuZ. LüM. Single-cell transcriptome sequencing reveals heterogeneity of gastric cancer: Progress and prospects.Front. Oncol.202313107426810.3389/fonc.2023.107426837305583
    [Google Scholar]
  64. GretenF.R. GrivennikovS.I. Inflammation and cancer: Triggers, mechanisms, and consequences.Immunity2019511274110.1016/j.immuni.2019.06.02531315034
    [Google Scholar]
  65. SahaiE. AstsaturovI. CukiermanE. DeNardoD.G. EgebladM. EvansR.M. FearonD. GretenF.R. HingoraniS.R. HunterT. HynesR.O. JainR.K. JanowitzT. JorgensenC. KimmelmanA.C. KoloninM.G. MakiR.G. PowersR.S. PuréE. RamirezD.C. Scherz-ShouvalR. ShermanM.H. StewartS. TlstyT.D. TuvesonD.A. WattF.M. WeaverV. WeeraratnaA.T. WerbZ. A framework for advancing our understanding of cancer-associated fibroblasts.Nat. Rev. Cancer202020317418610.1038/s41568‑019‑0238‑131980749
    [Google Scholar]
  66. ParkD. SahaiE. RullanA. SnapShot: Cancer-associated fibroblasts.Cell20201812486486.e110.1016/j.cell.2020.03.01332302576
    [Google Scholar]
  67. BrechbuhlH.M. Finlay-SchultzJ. YamamotoT.M. GillenA.E. CittellyD.M. TanA.C. SamsS.B. PillaiM.M. EliasA.D. RobinsonW.A. SartoriusC.A. KabosP. Fibroblast subtypes regulate responsiveness of luminal breast cancer to estrogen.Clin. Cancer Res.20172371710172110.1158/1078‑0432.CCR‑15‑285127702820
    [Google Scholar]
  68. FanhchaksaiK. OkadaF. NagaiN. PothacharoenP. KongtawelertP. HatanoS. MakinoS. NakamuraT. WatanabeH. Host stromal versican is essential for cancer-associated fibroblast function to inhibit cancer growth.Int. J. Cancer2016138363064110.1002/ijc.2980426270355
    [Google Scholar]
  69. McAndrewsK.M. ChenY. DarpolorJ.K. ZhengX. YangS. CarstensJ.L. LiB. WangH. MiyakeT. Correa de SampaioP. KirtleyM.L. NataleM. WuC.C. SugimotoH. LeBleuV.S. KalluriR. Identification of functional heterogeneity of carcinoma-associated fibroblasts with distinct il6-mediated therapy resistance in pancreatic cancer.Cancer Discov.20221261580159710.1158/2159‑8290.CD‑20‑148435348629
    [Google Scholar]
  70. SebastianA. HumN.R. MartinK.A. GilmoreS.F. PeranI. ByersS.W. WheelerE.K. ColemanM.A. LootsG.G. Single- cell transcriptomic analysis of tumor-derived fibroblasts and normal tissue-resident fibroblasts reveals fibroblast heterogeneity in breast cancer.Cancers2020125130710.3390/cancers1205130732455670
    [Google Scholar]
  71. PengS. ChenD. CaiJ. YuanZ. HuangB. LiY. WangH. LuoQ. KuangY. LiangW. LiuZ. WangQ. CuiY. WangH. LiuX. Enhancing cancer-associated fibroblast fatty acid catabolism within a metabolically challenging tumor microenvironment drives colon cancer peritoneal metastasis.Mol. Oncol.20211551391141110.1002/1878‑0261.1291733528867
    [Google Scholar]
  72. PengZ. YeM. DingH. FengZ. HuK. Spatial transcriptomics atlas reveals the crosstalk between cancer-associated fibroblasts and tumor microenvironment components in colorectal cancer.J. Transl. Med.202220130210.1186/s12967‑022‑03510‑835794563
    [Google Scholar]
  73. IsellaC. TerrasiA. BellomoS.E. PettiC. GalatolaG. MuratoreA. MellanoA. SenettaR. CassentiA. SonettoC. InghiramiG. TrusolinoL. FeketeZ. De RidderM. CassoniP. StormeG. BertottiA. MedicoE. Stromal contribution to the colorectal cancer transcriptome.Nat. Genet.201547431231910.1038/ng.322425706627
    [Google Scholar]
  74. ZhangQ. HeY. LuoN. PatelS.J. HanY. GaoR. ModakM. CarottaS. HaslingerC. KindD. PeetG.W. ZhongG. LuS. ZhuW. MaoY. XiaoM. BergmannM. HuX. KerkarS.P. VogtA.B. PflanzS. LiuK. PengJ. RenX. ZhangZ. Landscape and dynamics of single immune cells in hepatocellular carcinoma.Cell20191794829845.e2010.1016/j.cell.2019.10.00331675496
    [Google Scholar]
  75. DeNardoD.G. RuffellB. Macrophages as regulators of tumour immunity and immunotherapy.Nat. Rev. Immunol.201919636938210.1038/s41577‑019‑0127‑630718830
    [Google Scholar]
  76. ZilionisR. EngblomC. PfirschkeC. SavovaV. ZemmourD. SaatciogluH.D. KrishnanI. MaroniG. MeyerovitzC.V. KerwinC.M. ChoiS. RichardsW.G. De RienzoA. TenenD.G. BuenoR. LevantiniE. PittetM.J. KleinA.M. Single- cell transcriptomics of human and mouse lung cancers reveals conserved myeloid populations across individuals and species.Immunity201950513171334.e1010.1016/j.immuni.2019.03.00930979687
    [Google Scholar]
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