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Journal of Translational Medicine
Published in: Journal of Translational Medicine 1/2021

Open Access 01-12-2021 | Biomarkers | Research

Single-cell analysis of a tumor-derived exosome signature correlates with prognosis and immunotherapy response

Authors: Jiani Wu, Dongqiang Zeng, Shimeng Zhi, Zilan Ye, Wenjun Qiu, Na Huang, Li Sun, Chunlin Wang, Zhenzhen Wu, Jianping Bin, Yulin Liao, Min Shi, Wangjun Liao

Published in: Journal of Translational Medicine | Issue 1/2021

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Abstract

Background

Tumor-derived exosomes (TEXs) are involved in tumor progression and the immune modulation process and mediate intercellular communication in the tumor microenvironment. Although exosomes are considered promising liquid biomarkers for disease diagnosis, it is difficult to discriminate TEXs and to develop TEX-based predictive biomarkers.

Methods

In this study, the gene expression profiles and clinical information were collected from The Cancer Genome Atlas (TCGA) database, IMvigor210 cohorts, and six independent Gene Expression Omnibus datasets. A TEXs-associated signature named TEXscore was established to predict overall survival in multiple cancer types and in patients undergoing immune checkpoint blockade therapies.

Results

Based on exosome-associated genes, we first constructed a tumor-derived exosome signature named TEXscore using a principal component analysis algorithm. In single-cell RNA-sequencing data analysis, ascending TEXscore was associated with disease progression and poor clinical outcomes. In the TCGA Pan-Cancer cohort, TEXscore was elevated in tumor samples rather than in normal tissues, thereby serving as a reliable biomarker to distinguish cancer from non-cancer sources. Moreover, high TEXscore was associated with shorter overall survival across 12 cancer types. TEXscore showed great potential in predicting immunotherapy response in melanoma, urothelial cancer, and renal cancer. The immunosuppressive microenvironment characterized by macrophages, cancer-associated fibroblasts, and myeloid-derived suppressor cells was associated with high TEXscore in the TCGA and immunotherapy cohorts. Besides, TEXscore-associated miRNAs and gene mutations were also identified. Further experimental research will facilitate the extending of TEXscore in tumor-associated exosomes.

Conclusions

TEXscore capturing tumor-derived exosome features might be a robust biomarker for prognosis and treatment responses in independent cohorts.
Appendix
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Literature
1.
Kalluri R, LeBleu VS. The biology function and biomedical applications of exosomes. Science. 2020;367(6478):eaau977.CrossRef
2.
3.
Ludwig A-K, Giebel B. Exosomes: small vesicles participating in intercellular communication. Int J Biochem Cell Biol. 2012;44(1):11–5.PubMedCrossRef
4.
Hellwinkel JE, Redzic JS, Harland TA, Gunaydin D, Anchordoquy TJ, Graner MW. Glioma-derived extracellular vesicles selectively suppress immune responses. Neuro Oncol. 2016;18(4):497–506.PubMedCrossRef
5.
Mashouri L, Yousefi H, Aref AR, Ahadi AM, Molaei F, Alahari SK. Exosomes: composition, biogenesis, and mechanisms in cancer metastasis and drug resistance. Mol Cancer. 2019;18(1):75.PubMedPubMedCentralCrossRef
6.
7.
8.
Chen IH, Xue L, Hsu C-C, Paez JSP, Pan L, Andaluz H, et al. Phosphoproteins in extracellular vesicles as candidate markers for breast cancer. Proc Natl Acad Sci USA. 2017;114(12):3175–80.PubMedPubMedCentralCrossRef
9.
Keller S, Ridinger J, Rupp A-K, Janssen JWG, Altevogt P. Body fluid derived exosomes as a novel template for clinical diagnostics. J Transl Med. 2011;9:86.PubMedPubMedCentralCrossRef
10.
Song Z, Mao J, Barrero RA, Wang P, Zhang F, Wang T. Development of a CD63 aptamer for efficient cancer immunochemistry and immunoaffinity-based exosome isolation. Molecules (Basel, Switzerland). 2020;25(23):5585.PubMedCentralCrossRef
11.
Yang D, Zhang W, Zhang H, Zhang F, Chen L, Ma L, et al. Progress, opportunity, and perspective on exosome isolation—efforts for efficient exosome-based theranostics. Theranostics. 2020;10(8):3684–707.PubMedPubMedCentralCrossRef
12.
Lugini L, Matarrese P, Tinari A, Lozupone F, Federici C, Iessi E, et al. Cannibalism of live lymphocytes by human metastatic but not primary melanoma cells. Cancer Res. 2006;66(7):3629–38.PubMedCrossRef
13.
Tahir SA, Ren C, Timme TL, Gdor Y, Hoogeveen R, Morrisett JD, et al. Development of an immunoassay for serum caveolin-1: a novel biomarker for prostate cancer. Clin Cancer Res. 2003;9(10 Pt 1):3653–9.PubMed
14.
Logozzi M, De Milito A, Lugini L, Borghi M, Calabrò L, Spada M, et al. High levels of exosomes expressing CD63 and caveolin-1 in plasma of melanoma patients. PLoS ONE. 2009;4(4):e5219.PubMedPubMedCentralCrossRef
15.
Melo SA, Luecke LB, Kahlert C, Fernandez AF, Gammon ST, Kaye J, et al. Glypican-1 identifies cancer exosomes and detects early pancreatic cancer. Nature. 2015;523(7559):177–82.PubMedPubMedCentralCrossRef
16.
17.
Chen G, Huang AC, Zhang W, Zhang G, Wu M, Xu W, et al. Exosomal PD-L1 contributes to immunosuppression and is associated with anti-PD-1 response. Nature. 2018;560(7718):382–6.PubMedPubMedCentralCrossRef
18.
Crow J, Samuel G, Godwin AK. Beyond tumor mutational burden: potential and limitations in using exosomes to predict response to immunotherapy. Expert Rev Mol Diagn. 2019;19(12):1079–88.PubMedCrossRef
19.
20.
Maynard A, McCoach CE, Rotow JK, Harris L, Haderk F, Kerr DL, et al. Therapy-induced evolution of human lung cancer revealed by single-cell RNA sequencing. Cell. 2020;182(5).
21.
Tang F, Barbacioru C, Wang Y, Nordman E, Lee C, Xu N, et al. mRNA-Seq whole-transcriptome analysis of a single cell. Nat Methods. 2009;6(5):377–82.PubMedCrossRef
22.
Zeng D, Li M, Zhou R, Zhang J, Sun H, Shi M, et al. Tumor microenvironment characterization in gastric cancer identifies prognostic and immunotherapeutically relevant gene signatures. Cancer Immunol Res. 2019;7(5):737–50.PubMedCrossRef
23.
Zeng D, Ye Z, Wu J, Zhou R, Fan X, Wang G, et al. Macrophage correlates with immunophenotype and predicts anti-PD-L1 response of urothelial cancer. Theranostics. 2020;10(15):7002–14.PubMedPubMedCentralCrossRef
24.
Zeng D, Ye Z, Shen R, Yu G, Wu J, Xiong Y, et al. IOBR: multi-omics immuno-oncology biological research to decode tumor microenvironment and signatures. Front Immunol. 2021;12:687975.PubMedPubMedCentralCrossRef
25.
Wagner GP, Kin K, Lynch VJ. Measurement of mRNA abundance using RNA-seq data: RPKM measure is inconsistent among samples. Theory Biosci. 2012;131(4):281–5.PubMedCrossRef
26.
Colaprico A, Silva TC, Olsen C, Garofano L, Cava C, Garolini D, et al. TCGAbiolinks: an R/Bioconductor package for integrative analysis of TCGA data. Nucleic Acids Res. 2016;44(8):e71.PubMedCrossRef
27.
Newman AM, Liu CL, Green MR, Gentles AJ, Feng W, Xu Y, et al. Robust enumeration of cell subsets from tissue expression profiles. Nat Methods. 2015;12(5):453–7.PubMedPubMedCentralCrossRef
28.
Mariathasan S, Turley SJ, Nickles D, Castiglioni A, Yuen K, Wang Y, et al. TGFβ attenuates tumour response to PD-L1 blockade by contributing to exclusion of T cells. Nature. 2018;554(7693):544–8.PubMedPubMedCentralCrossRef
29.
Cristescu R, Mogg R, Ayers M, Albright A, Murphy E, Yearley J, et al. Pan-tumor genomic biomarkers for PD-1 checkpoint blockade-based immunotherapy. Science. 2018;362(6411):eaar3593.PubMedPubMedCentralCrossRef
30.
Rooney MS, Shukla SA, Wu CJ, Getz G, Hacohen N. Molecular and genetic properties of tumors associated with local immune cytolytic activity. Cell. 2015;160(1–2):48–61.PubMedPubMedCentralCrossRef
31.
Rosario SR, Long MD, Affronti HC, Rowsam AM, Eng KH, Smiraglia DJ. Pan-cancer analysis of transcriptional metabolic dysregulation using The Cancer Genome Atlas. Nat Commun. 2018;9(1):5330.PubMedPubMedCentralCrossRef
32.
33.
Puoliväli T, Palva S, Palva JM. Influence of multiple hypothesis testing on reproducibility in neuroimaging research: a simulation study and Python-based software. J Neurosci Methods. 2020;337:108654.PubMedCrossRef
34.
35.
Consortium TGO. The gene ontology resource: 20 years and still GOing strong. Nucleic Acids Res. 2019;47(D1):D330–8.CrossRef
36.
Kanehisa M, Sato Y, Kawashima M, Furumichi M, Tanabe M. KEGG as a reference resource for gene and protein annotation. Nucleic Acids Res. 2016;44(D1):D457–62.PubMedCrossRef
37.
Chen Y, Wang X. miRDB: an online database for prediction of functional microRNA targets. Nucleic Acids Res. 2020;48(D1):D127–31.PubMedCrossRef
38.
39.
40.
Robin X, Turck N, Hainard A, Tiberti N, Lisacek F, Sanchez J-C, et al. pROC: an open-source package for R and S+ to analyze and compare ROC curves. BMC Bioinformat. 2011;12:77.CrossRef
41.
Cao B, Dai W, Ma S, Wang Q, Lan M, Luo H, et al. An EV-associated gene signature correlates with hypoxic microenvironment and predicts recurrence in lung adenocarcinoma. Mol Ther Nucleic Acids. 2019;17:879–90.PubMedPubMedCentralCrossRef
42.
43.
44.
Mascaux C, Angelova M, Vasaturo A, Beane J, Hijazi K, Anthoine G, et al. Immune evasion before tumour invasion in early lung squamous carcinogenesis. Nature. 2019;571(7766):570–5.PubMedCrossRef
45.
Mohan V, Das A, Sagi I. Emerging roles of ECM remodeling processes in cancer. Semin Cancer Biol. 2020;62:192–200.PubMedCrossRef
46.
Xie F, Zhou X, Fang M, Li H, Su P, Tu Y, et al. Extracellular vesicles in cancer immune microenvironment and cancer immunotherapy. Adv Sci (Weinh). 2019;6(24):1901779.CrossRef
47.
Jiang P, Gu S, Pan D, Fu J, Sahu A, Hu X, et al. Signatures of T cell dysfunction and exclusion predict cancer immunotherapy response. Nat Med. 2018;24(10):1550–8.PubMedPubMedCentralCrossRef
48.
Zhang C, Xiao X, Chen M, Aldharee H, Chen Y, Long W. Liver kinase B1 restoration promotes exosome secretion and motility of lung cancer cells. Oncol Rep. 2018;39(1):376–82.PubMedCrossRef
49.
Shi Y, Au JS-K, Thongprasert S, Srinivasan S, Tsai C-M, Khoa MT, et al. A prospective, molecular epidemiology study of EGFR mutations in Asian patients with advanced non-small-cell lung cancer of adenocarcinoma histology (PIONEER). J Thorac Oncol Off Publ Int Assoc Study Lung Cancer. 2014;9(2):154–62.
50.
Muller L, Hong C-S, Stolz DB, Watkins SC, Whiteside TL. Isolation of biologically-active exosomes from human plasma. J Immunol Methods. 2014;411:55–65.PubMedPubMedCentralCrossRef
51.
52.
Chen L, Guo P, He Y, Chen Z, Chen L, Luo Y, et al. HCC-derived exosomes elicit HCC progression and recurrence by epithelial–mesenchymal transition through MAPK/ERK signalling pathway. Cell Death Dis. 2018;9(5):513.PubMedPubMedCentralCrossRef
53.
Saadatpour L, Fadaee E, Fadaei S, Nassiri Mansour R, Mohammadi M, Mousavi SM, et al. Glioblastoma: exosome and microRNA as novel diagnosis biomarkers. Cancer Gene Ther. 2016;23(12):415–8.PubMedCrossRef
54.
Casey SC, Amedei A, Aquilano K, Azmi AS, Benencia F, Bhakta D, et al. Cancer prevention and therapy through the modulation of the tumor microenvironment. Semin Cancer Biol. 2015;35(Suppl):S199–223.PubMedPubMedCentralCrossRef
55.
Hinshaw DC, Shevde LA. The tumor microenvironment innately modulates cancer progression. Can Res. 2019;79(18):4557–66.CrossRef
56.
57.
Liang Z-X, Liu H-S, Wang F-W, Xiong L, Zhou C, Hu T, et al. LncRNA RPPH1 promotes colorectal cancer metastasis by interacting with TUBB3 and by promoting exosomes-mediated macrophage M2 polarization. Cell Death Dis. 2019;10(11):829.PubMedPubMedCentralCrossRef
58.
Qian M, Wang S, Guo X, Wang J, Zhang Z, Qiu W, et al. Hypoxic glioma-derived exosomes deliver microRNA-1246 to induce M2 macrophage polarization by targeting TERF2IP via the STAT3 and NF-κB pathways. Oncogene. 2020;39(2):428–42.PubMedCrossRef
59.
Ringuette Goulet C, Bernard G, Tremblay S, Chabaud S, Bolduc S, Pouliot F. Exosomes induce fibroblast differentiation into cancer-associated fibroblasts through TGFβ signaling. Mol Cancer Res. 2018;16(7):1196–204.PubMedCrossRef
60.
Li X, Lian Z, Wang S, Xing L, Yu J. Interactions between EGFR and PD-1/PD-L1 pathway: implications for treatment of NSCLC. Cancer Lett. 2018;418:1–9.PubMedCrossRef
61.
Balar AV, Galsky MD, Rosenberg JE, Powles T, Petrylak DP, Bellmunt J, et al. Atezolizumab as first-line treatment in cisplatin-ineligible patients with locally advanced and metastatic urothelial carcinoma: a single-arm, multicentre, phase 2 trial. Lancet. 2017;389(10064):67–76.PubMedCrossRef
62.
Azuma K, Ota K, Kawahara A, Hattori S, Iwama E, Harada T, et al. Association of PD-L1 overexpression with activating EGFR mutations in surgically resected nonsmall-cell lung cancer. Ann Oncol. 2014;25(10):1935–40.PubMedCrossRef
63.
Hui R, Gandhi L, Costa EC, Felip E, Ahn M-J, Eder JP, et al. Long-term OS for patients with advanced NSCLC enrolled in the KEYNOTE-001 study of pembrolizumab (pembro). J Clin Oncol. 2016;34(15_Suppl):9026–9026.CrossRef
64.
Lee CK, Man J, Lord S, Links M, Gebski V, Mok T, et al. Checkpoint inhibitors in metastatic EGFR-mutated non-small cell lung cancer-a meta-analysis. J Thorac Oncol Off Publ Int Assoc Study Lung Cancer. 2017;12(2):403–7.
65.
Ma Y-S, Yu F, Zhong X-M, Lu G-X, Cong X-L, Xue S-B, et al. miR-30 family reduction maintains self-renewal and promotes tumorigenesis in NSCLC-initiating cells by targeting oncogene TM4SF1. Mol Ther. 2018;26(12):2751–65.PubMedPubMedCentralCrossRef
66.
Croset M, Pantano F, Kan CWS, Bonnelye E, Descotes F, Alix-Panabières C, et al. miRNA-30 family members inhibit breast cancer invasion, osteomimicry, and bone destruction by directly targeting multiple bone metastasis-associated genes. Can Res. 2018;78(18):5259–73.CrossRef
67.
Metadata
Title
Single-cell analysis of a tumor-derived exosome signature correlates with prognosis and immunotherapy response
Authors
Jiani Wu
Dongqiang Zeng
Shimeng Zhi
Zilan Ye
Wenjun Qiu
Na Huang
Li Sun
Chunlin Wang
Zhenzhen Wu
Jianping Bin
Yulin Liao
Min Shi
Wangjun Liao
Publication date
01-12-2021
Publisher
BioMed Central
Keyword
Biomarkers
Published in
Journal of Translational Medicine / Issue 1/2021
Electronic ISSN: 1479-5876
DOI
https://doi.org/10.1186/s12967-021-03053-4

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