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Open Access 01-12-2024 | Osteosarcoma | Analysis

Integrated single-cell analysis reveals heterogeneity and therapeutic insights in osteosarcoma

Authors: Dongan He, Xiaoqian Che, Haiming Zhang, Jiandong Guo, Lei Cai, Jian Li, Jinxi Zhang, Xin Jin, Jianfeng Wang

Published in: Discover Oncology | Issue 1/2024

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Abstract

Osteosarcoma (OSA) is a primary bone malignancy characterized by its aggressive nature and high propensity for metastasis. Despite advancements in multimodal therapies, the clinical outcomes for OSA patients remain suboptimal, necessitating deeper molecular insights for improved therapeutic strategies. Here, we employed single-cell RNA sequencing (scRNA-seq) to elucidate the cellular heterogeneity and transcriptional dynamics of OSA tumors. Our study identified eleven distinct tumor cell subpopulations, including osteoblastic, chondroblastic, and myeloid lineages, each exhibiting unique transcriptional profiles associated with disease progression and metastasis. Epithelial-mesenchymal transition (EMT) emerged as a critical process driving aggressive phenotypes, supported by gene set enrichment analyses (GSVA) and transcription factor regulatory network analyses. Integration of copy number variation (CNV) data highlighted genomic alterations in osteoblastic and chondroblastic cells, implicating potential therapeutic targets. Furthermore, immune cell infiltration analyses revealed distinct immune profiles across OSA subtypes, correlating with tumor mutational burden (TMB) and clinical outcomes. Our findings underscore the complexity of OSA biology and provide a foundation for developing personalized treatment strategies targeting tumor heterogeneity and immune interactions.
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Metadata
Title
Integrated single-cell analysis reveals heterogeneity and therapeutic insights in osteosarcoma
Authors
Dongan He
Xiaoqian Che
Haiming Zhang
Jiandong Guo
Lei Cai
Jian Li
Jinxi Zhang
Xin Jin
Jianfeng Wang
Publication date
01-12-2024
Publisher
Springer US
Published in
Discover Oncology / Issue 1/2024
Print ISSN: 1868-8497
Electronic ISSN: 2730-6011
DOI
https://doi.org/10.1007/s12672-024-01523-x

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