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Methods to Enable Spatial Transcriptomics of Bone Tissues
Published on: May 3, 2024
Single-Cell Transcriptomic Profiling Reveals Cellular Heterogeneity and Identifies Novel Therapeutic Targets in
Hui Li1, Changjiang Sun2, Minjie Yang3
1Department of Endocrinology, Shaanxi Provincial People's Hospital, Xi'an City, Shaanxi Province, China.
Background:
Osteosarcoma is the most prevalent primary malignant bone tumor predominantly affecting children and adolescents, yet prognosis for metastatic disease remains dismal. Understanding the cellular complexity within the tumor microenvironment is essential for developing targeted therapeutic strategies.
Methods:
We performed comprehensive single-cell RNA sequencing analysis on an osteosarcoma tissue sample (GSM4952363) using the Seurat pipeline (v4.3.0). Following rigorous quality control (200-6000 genes per cell, < 15% mitochondrial reads), cells were filtered for downstream analysis. Dimensionality reduction (PCA and UMAP) and unsupervised clustering (Louvain algorithm, resolution = 0.8) identified seven distinct cellular clusters. Differential expression analysis (Wilcoxon rank-sum test, |log₂FC| > 0.25, adjusted p < 0.05) identified cluster-specific markers, while Gene Ontology and KEGG pathway enrichment analyses (clusterProfiler, adjusted p < 0.05) revealed functional programs. Four candidate genes (F11, ACRP2, LEPR, and POSTN) were selected for validation by quantitative real-time PCR (mRNA level) and ELISA (protein level) in MG-63 osteosarcoma cells compared to hFOB 1.19 normal osteoblasts.
Results:
Single-cell transcriptomic profiling identified seven distinct cellular clusters within the osteosarcoma microenvironment, including macrophages (Cluster 0, 28.0%), osteoblasts (Cluster 1, 24.2%), fibroblasts (Cluster 2, Fibro_COMP, 14.7%), proliferating cells (Cluster 3, 12.3%), osteoclasts (Cluster 4, 11.6%), monocytes (Cluster 5, 6.3%), and T cells (Cluster 6, 2.9%). Functional enrichment analysis highlighted activation of PI3K-Akt signaling, focal adhesion, and extracellular matrix organization as core pathways. qRT-PCR validation (mRNA level) demonstrated that F11 was significantly downregulated (0.31 ± 0.04 vs. 1.00 ± 0.07, 69% reduction, p < 0.001), whereas ACRP2 (2.87 ± 0.33-fold), LEPR (4.52 ± 0.48-fold), and POSTN (6.23 ± 0.57-fold) were significantly upregulated (all p < 0.001). ELISA validation (protein level) confirmed consistent trends: F11 protein decreased by 65% (0.35 ± 0.05 vs. 1.00 ± 0.08, p < 0.001), whereas ACRP2 (2.64 ± 0.29-fold), LEPR (4.18 ± 0.44-fold), and POSTN (5.89 ± 0.53-fold) protein levels were elevated (all p < 0.001). Among the four candidates, POSTN exhibited the most pronounced changes at both mRNA and protein levels, suggesting its involvement in osteosarcoma matrix remodeling.
Conclusions:
This study provides a single-cell transcriptomic atlas of the osteosarcoma microenvironment, revealing substantial cellular heterogeneity. The differentially expressed genes F11, ACRP2, LEPR, and POSTN represent candidate biomarkers that warrant further investigation for their potential roles in osteosarcoma biology and as putative therapeutic targets.
Insights
This study reveals the cellular complexity of osteosarcoma using single-cell RNA sequencing, identifying key genes like POSTN that may drive tumor progression and offer new therapeutic targets for this bone cancer.
Area of Science:
- Oncology
- Genomics
- Molecular Biology
Background:
- Osteosarcoma is a prevalent pediatric bone cancer with poor prognosis for metastatic disease.
- Understanding the tumor microenvironment's cellular complexity is crucial for targeted therapies.
Purpose of the Study:
- To perform single-cell RNA sequencing on osteosarcoma to identify cellular heterogeneity.
- To discover novel candidate genes and pathways involved in osteosarcoma progression.
Main Methods:
- Single-cell RNA sequencing and bioinformatic analysis (Seurat, PCA, UMAP, Louvain clustering).
- Differential gene expression analysis and functional enrichment (Gene Ontology, KEGG pathways).
- Validation of candidate genes (F11, ACRP2, LEPR, POSTN) using qRT-PCR and ELISA.
Main Results:
- Seven distinct cell clusters were identified, including macrophages, osteoblasts, fibroblasts, proliferating cells, osteoclasts, monocytes, and T cells.
- Key pathways identified include PI3K-Akt signaling and extracellular matrix organization.
- POSTN, LEPR, and ACRP2 were significantly upregulated, while F11 was downregulated at both mRNA and protein levels.
Conclusions:
- Single-cell transcriptomics provides an atlas of osteosarcoma cellular heterogeneity.
- F11, ACRP2, LEPR, and POSTN are potential biomarkers for osteosarcoma.
- POSTN shows significant upregulation and may play a role in matrix remodeling, warranting further investigation as a therapeutic target.
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