Unveiling novel cell clusters and biomarkers in glioblastoma and its peritumoral microenvironment at the single-cell perspective.
Biomarkers
Glioblastoma
Single-cell sequencing
Tumor heterogeneity
Tumor microenvironment
Journal
Journal of translational medicine
ISSN: 1479-5876
Titre abrégé: J Transl Med
Pays: England
ID NLM: 101190741
Informations de publication
Date de publication:
08 Jun 2024
08 Jun 2024
Historique:
received:
20
02
2024
accepted:
20
05
2024
medline:
9
6
2024
pubmed:
9
6
2024
entrez:
8
6
2024
Statut:
epublish
Résumé
Glioblastoma (GBM) is a highly heterogeneous, recurrent and aggressively invasive primary malignant brain tumor. The heterogeneity of GBM results in poor targeted therapy. Therefore, the aim of this study is to depict the cellular landscape of GBM and its peritumor from a single-cell perspective. Discovering new cell subtypes and biomarkers, and providing a theoretical basis for precision therapy. We collected 8 tissue samples from 4 GBM patients to perform 10 × single-cell transcriptome sequencing. Quality control and filtering of data by Seurat package for clustering. Inferring copy number variations to identify malignant cells via the infercnv package. Functional enrichment analysis was performed by GSVA and clusterProfiler packages. STRING database and Cytoscape software were used to construct protein interaction networks. Inferring transcription factors by pySCENIC. Building cell differentiation trajectories via the monocle package. To infer intercellular communication networks by CellPhoneDB software. We observed that the tumor microenvironment (TME) varies among different locations and different GBM patients. We identified a proliferative cluster of oligodendrocytes with high expression of mitochondrial genes. We also identified two clusters of myeloid cells, one primarily located in the peritumor exhibiting an M1 phenotype with elevated TNFAIP8L3 expression, and another in the tumor and peritumor showing a proliferative tendency towards an M2 phenotype with increased DTL expression. We identified XIST, KCNH7, SYT1 and DIAPH3 as potential factors associated with the proliferation of malignant cells in GBM. These biomarkers and cell clusters we discovered may serve as targets for treatment. Targeted drugs developed against these biomarkers and cell clusters may enhance treatment efficacy, optimize immune therapy strategies, and improve the response rates of GBM patients to immunotherapy. Our findings provide a theoretical basis for the development of individualized treatment and precision medicine for GBM, which may be used to improve the survival of GBM patients.
Sections du résumé
BACKGROUND
BACKGROUND
Glioblastoma (GBM) is a highly heterogeneous, recurrent and aggressively invasive primary malignant brain tumor. The heterogeneity of GBM results in poor targeted therapy. Therefore, the aim of this study is to depict the cellular landscape of GBM and its peritumor from a single-cell perspective. Discovering new cell subtypes and biomarkers, and providing a theoretical basis for precision therapy.
METHODS
METHODS
We collected 8 tissue samples from 4 GBM patients to perform 10 × single-cell transcriptome sequencing. Quality control and filtering of data by Seurat package for clustering. Inferring copy number variations to identify malignant cells via the infercnv package. Functional enrichment analysis was performed by GSVA and clusterProfiler packages. STRING database and Cytoscape software were used to construct protein interaction networks. Inferring transcription factors by pySCENIC. Building cell differentiation trajectories via the monocle package. To infer intercellular communication networks by CellPhoneDB software.
RESULTS
RESULTS
We observed that the tumor microenvironment (TME) varies among different locations and different GBM patients. We identified a proliferative cluster of oligodendrocytes with high expression of mitochondrial genes. We also identified two clusters of myeloid cells, one primarily located in the peritumor exhibiting an M1 phenotype with elevated TNFAIP8L3 expression, and another in the tumor and peritumor showing a proliferative tendency towards an M2 phenotype with increased DTL expression. We identified XIST, KCNH7, SYT1 and DIAPH3 as potential factors associated with the proliferation of malignant cells in GBM.
CONCLUSIONS
CONCLUSIONS
These biomarkers and cell clusters we discovered may serve as targets for treatment. Targeted drugs developed against these biomarkers and cell clusters may enhance treatment efficacy, optimize immune therapy strategies, and improve the response rates of GBM patients to immunotherapy. Our findings provide a theoretical basis for the development of individualized treatment and precision medicine for GBM, which may be used to improve the survival of GBM patients.
Identifiants
pubmed: 38851695
doi: 10.1186/s12967-024-05313-5
pii: 10.1186/s12967-024-05313-5
doi:
Substances chimiques
Biomarkers, Tumor
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
551Subventions
Organisme : Hubei Technological Innovation Special Fund
ID : YYXKNL2023011
Informations de copyright
© 2024. The Author(s).
Références
D’Alessio A, Proietti G, Sica G, Scicchitano BM. Pathological and molecular features of glioblastoma and its peritumoral tissue. Cancers. 2019;11(4):469.
doi: 10.3390/cancers11040469
pubmed: 30987226
pmcid: 6521241
Louis DN, Perry A, Wesseling P, Brat DJ, Cree IA, Figarella-Branger D, et al. The 2021 WHO classification of tumors of the central nervous system: a summary. Neuro Oncol. 2021;23(8):1231–51.
doi: 10.1093/neuonc/noab106
pubmed: 34185076
pmcid: 8328013
Fernandes C, Costa A, Osório L, Lago RC, Linhares P, Carvalho B, et al. Current standards of care in glioblastoma therapy. In: De Vleeschouwer S, editor., et al., Glioblastoma. Brisbane (AU): Codon Publications Copyright: The Authors; 2017.
Dapash M, Hou D, Castro B, Lee-Chang C, Lesniak MS. The interplay between glioblastoma and its microenvironment. Cells. 2021;10(9):2257.
doi: 10.3390/cells10092257
pubmed: 34571905
pmcid: 8469987
DeCordova S, Shastri A, Tsolaki AG, Yasmin H, Klein L, Singh SK, et al. Molecular heterogeneity and immunosuppressive microenvironment in glioblastoma. Front Immunol. 2020;11:1402.
doi: 10.3389/fimmu.2020.01402
pubmed: 32765498
pmcid: 7379131
Tait SW, Green DR. Mitochondria and cell signalling. J Cell Sci. 2012;125(Pt 4):807–15.
doi: 10.1242/jcs.099234
pubmed: 22448037
pmcid: 3311926
Karimova N, Asadov C, Hasanova A, Bayramov B, Shirinova A, Alimirzoyeva Z. CYP3A5*3, CYP3A4*18 AND CYP2B6*6 genotypes and chronic myeloid leukemia development in Azerbaijan. Adv Biol Earth Sci. 2023;8:204–15.
Amrahov N, Mahmud M, Alizada S. Effect of indole-3- butyric acid on the antioxidant enzymes, no and chlorophyll content of agdash-3 and ap-317 genotypes of upland cotton (Gossypium Hirsutum L.). Adv Biol Earth Sci. 2023;8:147–56.
Wallace DC. Mitochondria and cancer. Nat Rev Cancer. 2012;12(10):685–98.
doi: 10.1038/nrc3365
pubmed: 23001348
pmcid: 4371788
Vander Heiden MG, DeBerardinis RJ. Understanding the intersections between metabolism and cancer biology. Cell. 2017;168(4):657–69.
doi: 10.1016/j.cell.2016.12.039
pubmed: 28187287
Kuo CL, Ponneri Babuharisankar A, Lin YC, Lien HW, Lo YK, Chou HY, et al. Mitochondrial oxidative stress in the tumor microenvironment and cancer immunoescape: foe or friend? J Biomed Sci. 2022;29(1):74.
doi: 10.1186/s12929-022-00859-2
pubmed: 36154922
pmcid: 9511749
Claes A, Idema AJ, Wesseling P. Diffuse glioma growth: a guerilla war. Acta Neuropathol. 2007;114(5):443–58.
doi: 10.1007/s00401-007-0293-7
pubmed: 17805551
pmcid: 2039798
Trevisi G, Mangiola A. Current knowledge about the peritumoral microenvironment in glioblastoma. Cancers. 2023;15(22):5460.
doi: 10.3390/cancers15225460
pubmed: 38001721
pmcid: 10670229
Perlman K, Couturier CP, Yaqubi M, Tanti A, Cui QL, Pernin F, et al. Developmental trajectory of oligodendrocyte progenitor cells in the human brain revealed by single cell RNA sequencing. Glia. 2020;68(6):1291–303.
doi: 10.1002/glia.23777
pubmed: 31958186
Zhong S, Zhang S, Fan X, Wu Q, Yan L, Dong J, et al. A single-cell RNA-seq survey of the developmental landscape of the human prefrontal cortex. Nature. 2018;555(7697):524–8.
doi: 10.1038/nature25980
pubmed: 29539641
Nagaeva E, Zubarev I, Bengtsson Gonzales C, Forss M, Nikouei K, de Miguel E, et al. Heterogeneous somatostatin-expressing neuron population in mouse ventral tegmental area. Elife. 2020. https://doi.org/10.7554/eLife.59328 .
doi: 10.7554/eLife.59328
pubmed: 32749220
pmcid: 7440918
Paul A, Crow M, Raudales R, He M, Gillis J, Huang ZJ. Transcriptional architecture of synaptic communication delineates GABAergic neuron identity. Cell. 2017;171(3):522-39.e20.
doi: 10.1016/j.cell.2017.08.032
pubmed: 28942923
pmcid: 5772785
Bennett ML, Bennett FC, Liddelow SA, Ajami B, Zamanian JL, Fernhoff NB, et al. New tools for studying microglia in the mouse and human CNS. Proc Natl Acad Sci USA. 2016;113(12):E1738–46.
doi: 10.1073/pnas.1525528113
pubmed: 26884166
pmcid: 4812770
Ochocka N, Segit P, Walentynowicz KA, Wojnicki K, Cyranowski S, Swatler J, et al. Single-cell RNA sequencing reveals functional heterogeneity of glioma-associated brain macrophages. Nat Commun. 2021;12(1):1151.
doi: 10.1038/s41467-021-21407-w
pubmed: 33608526
pmcid: 7895824
You G, Zheng Z, Huang Y, Liu G, Luo W, Huang J, et al. scRNA-seq and proteomics reveal the distinction of M2-like macrophages between primary and recurrent malignant glioma and its critical role in the recurrence. CNS Neurosci Ther. 2023;29(11):3391–405.
doi: 10.1111/cns.14269
pubmed: 37194413
pmcid: 10580349
Chen X, Chen Y, Chen X, Wei P, Lin Y, Wu Z, et al. Single-cell RNA sequencing reveals intra-tumoral heterogeneity of glioblastoma and a pro-tumor subset of tumor-associated macrophages characterized by EZH2 overexpression. Biochim Biophys Acta BBA Mol Basis Dis. 2022;1868(12):166534.
doi: 10.1016/j.bbadis.2022.166534
Su J, Li Y, Liu Q, Peng G, Qin C, Li Y. Identification of SSBP1 as a ferroptosis-related biomarker of glioblastoma based on a novel mitochondria-related gene risk model and in vitro experiments. J Transl Med. 2022;20(1):440.
doi: 10.1186/s12967-022-03657-4
pubmed: 36180956
pmcid: 9524046
De Leo A, Ugolini A, Veglia F. Myeloid Cells in glioblastoma microenvironment. Cells. 2020;10(1):18.
doi: 10.3390/cells10010018
pubmed: 33374253
pmcid: 7824606
Kerneur C, Cano CE, Olive D. Major pathways involved in macrophage polarization in cancer. Front Immunol. 2022;13:1026954.
doi: 10.3389/fimmu.2022.1026954
pubmed: 36325334
pmcid: 9618889
Sørensen MD, Dahlrot RH, Boldt HB, Hansen S, Kristensen BW. Tumour-associated microglia/macrophages predict poor prognosis in high-grade gliomas and correlate with an aggressive tumour subtype. Neuropathol Appl Neurobiol. 2018;44(2):185–206.
doi: 10.1111/nan.12428
pubmed: 28767130
Müller S, Kohanbash G, Liu SJ, Alvarado B, Carrera D, Bhaduri A, et al. Single-cell profiling of human gliomas reveals macrophage ontogeny as a basis for regional differences in macrophage activation in the tumor microenvironment. Genome Biol. 2017;18(1):234.
doi: 10.1186/s13059-017-1362-4
pubmed: 29262845
pmcid: 5738907
Andersen RS, Anand A, Harwood DSL, Kristensen BW. Tumor-associated microglia and macrophages in the glioblastoma microenvironment and their implications for therapy. Cancers. 2021;13(17):4255.
doi: 10.3390/cancers13174255
pubmed: 34503065
pmcid: 8428223
Luo C, Quan Z, Zhong B, Zhang M, Zhou B, Wang S, et al. lncRNA XIST promotes glioma proliferation and metastasis through miR-133a/SOX4. Exp Ther Med. 2020;19(3):1641–8.
pubmed: 32104215
pmcid: 7027044
Eldesouki S, Samara KA, Qadri R, Obaideen AA, Otour AH, Habbal O, et al. XIST in brain cancer. Clin Chim Acta. 2022;531:283–90.
doi: 10.1016/j.cca.2022.04.993
pubmed: 35483442
Zhang J, Ren G, Huang T, Sang Y, Zhong Y, Yi Y. miRNA-363–3p hinders proliferation, migration, invasion and autophagy of thyroid cancer cells by controlling SYT1 transcription to affect NF-κB. Endocr Metab Immune Disord Drug Targets. 2023. https://doi.org/10.2174/1871530323666230504112553 .
doi: 10.2174/1871530323666230504112553
pubmed: 37937558
pmcid: 10514520
Chen X, Xie L, Qiao K, Zhu X, Ren J, Tan Y. The pan-cancer analysis identified DIAPH3 as a diagnostic biomarker of clinical cancer. Aging. 2023;15(3):689–704.
doi: 10.18632/aging.204459
pubmed: 36750200
pmcid: 9970313
Zhang Z, Dai F, Luo F, Wu W, Zhang S, Zhou R, et al. Diaphanous related formin 3 knockdown suppresses cell proliferation and metastasis of osteosarcoma cells. Discov Oncol. 2021;12(1):20.
doi: 10.1007/s12672-021-00415-8
pubmed: 35201449
pmcid: 8777534
Li X, Geng X, Chen Z, Yuan Z. Recent advances in glioma microenvironment-response nanoplatforms for phototherapy and sonotherapy. Pharmacol Res. 2022;179: 106218.
doi: 10.1016/j.phrs.2022.106218
pubmed: 35413423
Pinto MP, Arce M, Yameen B, Vilos C. Targeted brain delivery nanoparticles for malignant gliomas. Nanomedicine. 2017;12(1):59–72.
doi: 10.2217/nnm-2016-0307
pubmed: 27876436
Kim J, Zhu Y, Chen S, Wang D, Zhang S, Xia J, et al. Anti-glioma effect of ginseng-derived exosomes-like nanoparticles by active blood-brain-barrier penetration and tumor microenvironment modulation. J Nanobiotechnol. 2023;21(1):253.
doi: 10.1186/s12951-023-02006-x
Eftekhari A, Maleki Dizaj S, Sharifi S, Salatin S, Khalilov R, Samiei M, et al. Chapter six—salivary biomarkers in cancer. In: Makowski GS, editor., et al., Advances in clinical chemistry, vol. 110. Amsterdam: Elsevier; 2022. p. 171–92.
Binate G, Ganbarov K. Biological activity of chalcones as carbonyl compound derivatives, vol. 8. Amsterdam: Elseiver; 2023. p. 19–26.