Single-cell RNA datasets and bulk RNA datasets analysis demonstrated
biomarker
immune infiltration
osteosarcoma
single-cell sequencing technology
tumor-associated macrophages
Journal
Frontiers in immunology
ISSN: 1664-3224
Titre abrégé: Front Immunol
Pays: Switzerland
ID NLM: 101560960
Informations de publication
Date de publication:
2023
2023
Historique:
received:
02
04
2022
accepted:
23
01
2023
entrez:
23
2
2023
pubmed:
24
2
2023
medline:
25
2
2023
Statut:
epublish
Résumé
Osteosarcoma is the most frequent primary bone tumor with a poor prognosis. Immune infiltration proved to have a strong impact on prognosis. We analyzed single-cell datasets and bulk datasets to confirm the main immune cell populations and their properties in osteosarcoma. The examples in bulk datasets GSE21257 and GSE32981 from the Gene Expression Omnibus database were divided into two immune infiltration level groups, and 34 differentially expressed genes were spotted. Then, we located these genes among nine major cell clusters and their subclusters identified from 99,668 individual cells in single-cell dataset GSE152048 including 11 osteosarcoma patients. Especially, the markers of all kinds of myeloid cells identified in single-cell dataset GSE152048 were set to gene ontology enrichment. We clustered the osteosarcoma samples in the TARGET-OS from the Therapeutically Applicable Research to Generate Effective Treatments dataset into two groups by complete component 1q positive macrophage markers and compared their survival. Compared with the low-immune infiltrated group, the high-immune infiltrated group showed a better prognosis. Almost all the 34 differentially expressed genes expressed higher or exclusively among myeloid cells. A group of complete component 1q-positive macrophages was identified from the myeloid cells. In the bulk dataset TARGET-OS, these markers and the infiltration of complete component 1q-positive macrophages related to longer survival. Complete component 1q-positive tumor-associated macrophages were the major immune cell population in osteosarcoma, which contributed to a better prognosis.
Sections du résumé
Background
Osteosarcoma is the most frequent primary bone tumor with a poor prognosis. Immune infiltration proved to have a strong impact on prognosis. We analyzed single-cell datasets and bulk datasets to confirm the main immune cell populations and their properties in osteosarcoma.
Methods
The examples in bulk datasets GSE21257 and GSE32981 from the Gene Expression Omnibus database were divided into two immune infiltration level groups, and 34 differentially expressed genes were spotted. Then, we located these genes among nine major cell clusters and their subclusters identified from 99,668 individual cells in single-cell dataset GSE152048 including 11 osteosarcoma patients. Especially, the markers of all kinds of myeloid cells identified in single-cell dataset GSE152048 were set to gene ontology enrichment. We clustered the osteosarcoma samples in the TARGET-OS from the Therapeutically Applicable Research to Generate Effective Treatments dataset into two groups by complete component 1q positive macrophage markers and compared their survival.
Results
Compared with the low-immune infiltrated group, the high-immune infiltrated group showed a better prognosis. Almost all the 34 differentially expressed genes expressed higher or exclusively among myeloid cells. A group of complete component 1q-positive macrophages was identified from the myeloid cells. In the bulk dataset TARGET-OS, these markers and the infiltration of complete component 1q-positive macrophages related to longer survival.
Conclusions
Complete component 1q-positive tumor-associated macrophages were the major immune cell population in osteosarcoma, which contributed to a better prognosis.
Identifiants
pubmed: 36814925
doi: 10.3389/fimmu.2023.911368
pmc: PMC9939514
doi:
Substances chimiques
Complement C1q
80295-33-6
RNA
63231-63-0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
911368Informations de copyright
Copyright © 2023 Tu, Wang, Zheng and Liu.
Déclaration de conflit d'intérêts
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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