Research progress of single cell sequencing in osteosarcoma
10.3760/cma.j.cn121113-20240129-00066
- VernacularTitle:单细胞测序技术在骨肉瘤中的研究进展
- Author:
Weijie YAN
1
;
Yun LIU
;
Kai LUO
;
Mingxiu YANG
;
Shanhang LI
;
Juliang HE
Author Information
1. 广西医科大学附属肿瘤医院骨软组织外科，南宁 530021
- Keywords:
Osteosarcoma;
Tumor microenvironment;
Drug resistance, neoplasm;
Single-cell sequencing
- From:
Chinese Journal of Orthopaedics
2024;44(9):636-643
- CountryChina
- Language:Chinese
-
Abstract:
Osteosarcoma, a highly malignant tumor originating from bone tissue, is characterized by a high mortality along with a poor prognosis. The heterogeneity of the tumor microenvironment plays a pivotal role in its development and prognosis. Single-cell sequencing technology emerges as a crucial tool in elucidating this heterogeneity by delineating the functional characteristics and gene expression patterns of tumor cells, immune cells, and stromal cells within osteosarcoma tissues. This technology enables the depiction of the intricate interaction network between these cells. Utilizing the high-resolution advantage of single-cell sequencing, novel cell subtypes such as SPP1 (+) macrophages, C1QC (+) macrophages, and CLEC11A (+) B cells have been identified in osteosarcoma tissues, contributing to tumor growth and invasion within the tumor microenvironment. Identification of osteosarcoma stem cell subpopulations suggests that SERPINA1_CSCL1, FUS_CSCL2, and SPP1_CSCL3 populations may serve as the origin of osteosarcoma cells. Moreover, single-cell sequencing has revealed that mregDCs promote immune escape and tumor progression by selectively expressing CCR7, CCL17, CCL19, and CCL22 factors, thereby recruiting Treg cells. Additionally, this technology aids in the development of personalized chemotherapy regimens by pinpointing potential drug resistance targets in osteosarcoma, leading to the establishment of a drug resistance risk score model. In terms of disease prognosis, single-cell sequencing has identified immune infiltration-associated genes in osteosarcoma (e.g., EPHX2, FDPS, GBP1, MMD, ZYX), facilitating the construction of a prognostic analysis model for osteosarcoma patients, thus aiding in prognostic prediction.
