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Cited by 27Immune cells in cancerSarcoma Diagnosis and TreatmentCancer Immunotherapy and Biomarkers

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Single-cell RNA datasets and bulk RNA datasets analysis demonstrated C1Q+ tumor-associated macrophage as a major and antitumor immune cell population in osteosarcoma

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Tu, Jihao, Wang, Duo, Zheng, XiaoTian, Liu, Bin·2023·Frontiers in Immunology
DOI 10.3389/fimmu.2023.911368PMC PMC9939514
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Abstract

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.

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Crossref · 10.3389/fimmu.2023.911368

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Figure 1 Workflow of this research.
Figure 1 Workflow of this research.CC BY · PubMed Central
Figure 2 The overview of analyzing GSE21257. (A) There were 53 examples clustered into two groups by immune metagenes. (B) The score of 28 kinds of immune cells calculated by ssGSEA. The 53 examples were ordered by their immune groups instead of getting clustered. (C) The survival plot of high- and low- immune infiltrated groups. (D) Biological process enrichment of the 34 overlapped DEGs. (E) GSEA of the 34 overlapped genes; the top 5 terms were selected. All p-values are 1e-10, and all p.adjust are 1.447826e-09. (F) The survival plot of overlapped genes.
Figure 2 The overview of analyzing GSE21257. (A) There were 53 examples clustered into two groups by immune metagenes. (B) The score of 28 kinds of immune cells calculated by ssGSEA. The 53 examples were ordered by their immune groups instead of getting clustered. (C) The survival plot of high- and low- immune infiltrated groups. (D) Biological process enrichment of the 34 overlapped DEGs. (E) GSEA of the 34 overlapped genes; the top 5 terms were selected. All p-values are 1e-10, and all p.adjust are 1.447826e-09. (F) The survival plot of overlapped genes.CC BY · PubMed Central
Figure 3 Single-cell transcriptomic analysis reveals the transcriptome of cells in the microenvironment of OS. (A) The t-distributed stochastic neighbor embedding (t-SNE) plot of the nine identified main cell types in OS lesions. (B) Violin plots showed the normalized expression levels of eight representative canonical markers across the nine clusters. (C) Representative marker expression in nine clusters of cells. Dot size indicates the proportion of cells expressing markers. Dot color shows the average expression level of the markers. (D) Distribution of the nine clusters among 11 patients with OS. (E) Dot plot of the 34 overlapped DEGs showing their expressing proportion and level among nine clusters.
Figure 3 Single-cell transcriptomic analysis reveals the transcriptome of cells in the microenvironment of OS. (A) The t-distributed stochastic neighbor embedding (t-SNE) plot of the nine identified main cell types in OS lesions. (B) Violin plots showed the normalized expression levels of eight representative canonical markers across the nine clusters. (C) Representative marker expression in nine clusters of cells. Dot size indicates the proportion of cells expressing markers. Dot color shows the average expression level of the markers. (D) Distribution of the nine clusters among 11 patients with OS. (E) Dot plot of the 34 overlapped DEGs showing their expressing proportion and level among nine clusters.CC BY · PubMed Central
Figure 4 Myeloid cells subclustered and DEGs combined with these six cell groups. (A) The t-SNE plot of the nine identified clusters or six cell groups. (B) Violin plots showed the normalized expression levels of representative markers across the six cell groups (C) Representative markers expression in six cell groups. Dot size and color delivered the same meaning as the previous dot plot (D) Distribution of the nine clusters among 11 patients with OS. (E) Dot plot of the overlapped DEGs, which represented as C1Q+ TAM markers. The plot showed expressing proportion and level among six cell groups of these DEGs. (F) Biological process enrichment of C1Q+ TAM markers.
Figure 4 Myeloid cells subclustered and DEGs combined with these six cell groups. (A) The t-SNE plot of the nine identified clusters or six cell groups. (B) Violin plots showed the normalized expression levels of representative markers across the six cell groups (C) Representative markers expression in six cell groups. Dot size and color delivered the same meaning as the previous dot plot (D) Distribution of the nine clusters among 11 patients with OS. (E) Dot plot of the overlapped DEGs, which represented as C1Q+ TAM markers. The plot showed expressing proportion and level among six cell groups of these DEGs. (F) Biological process enrichment of C1Q+ TAM markers.CC BY · PubMed Central
Figure 5 Overview of analyzing C1Q+ TAMs group and its marker. (A) The survival plots of C1QA, C1QB, FOLR2, LGMN, and APOE. (B) Cluster 88 examples in TARGET-OS into two groups by C1Q+ TAM markers with a fold change larger than 0.25. (C) The survival plot of high- and low- C1Q+ TAM infiltration groups. (D) The co-expression among C1Q+ TAM markers. The larger co-expression coefficient gets redder and wider lines. (E) Bubble plots show ligand–receptor pairs between C1Q+ TAMs and other cell groups.
Figure 5 Overview of analyzing C1Q+ TAMs group and its marker. (A) The survival plots of C1QA, C1QB, FOLR2, LGMN, and APOE. (B) Cluster 88 examples in TARGET-OS into two groups by C1Q+ TAM markers with a fold change larger than 0.25. (C) The survival plot of high- and low- C1Q+ TAM infiltration groups. (D) The co-expression among C1Q+ TAM markers. The larger co-expression coefficient gets redder and wider lines. (E) Bubble plots show ligand–receptor pairs between C1Q+ TAMs and other cell groups.CC BY · PubMed Central

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Metadata

Authors
Tu, J., Wang, D., Zheng, X., & Liu, B.
Affiliations
First Hospital of Jilin University (CN)
Corresponding author
Liu, Bin
ORCID
Venue
Frontiers in Immunology
Publisher
Frontiers Media SA
Published
2023-02-06
Volume
14
Pages
911368-911368
ISSN
1664-3224 (ISSN-L)
DOI
10.3389/fimmu.2023.911368
PMC
PMC9939514
OpenAlex
W4319321889
Cited by
27
References
59
Citations by year
2026: 6 · 2025: 8 · 2024: 8 · 2023: 5
FWCI
2.95
Type
journal article
Language
en
Open access
Licence
Locations
  • Frontiers in Immunology (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Topics
  • Life Sciences › Immunology and Microbiology › Immunology › Immune cells in cancer
  • Health Sciences › Medicine › Oncology › Sarcoma Diagnosis and Treatment
  • Health Sciences › Medicine › Oncology › Cancer Immunotherapy and Biomarkers
Keywords
osteosarcoma, tumor-associated macrophages, tumor immune microenvironment, immune cell infiltration, myeloid cells, prognostic factors, survival, differentially expressed genes, single-cell RNA sequencing, bulk RNA-seq
MeSH terms
Tumor-Associated Macrophages, Bone Neoplasms, Humans, RNA, Osteosarcoma, Complement C1q

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