Integrated analysis of single-cell and bulk transcriptomics reveals cellular subtypes and molecular features associated with osteosarcoma prognosis.

ABSTRACT:

Background

Osteosarcoma (OS) is the most common primary bone malignancy with variable molecular biology and prognosis. However, our understanding of the association between cell types and OS progression remains poor.

Methods

We generated a human OS cell atlas by integrating over 110,000 single cells from 17 samples. Multiple machine learning algorithms were applied to develop tumor purity prediction models based on transcriptomic profile of OS. The Scissor algorithm and gene enrichment analyses were conducted to delve into cell-intrinsic molecular characteristics linked to OS prognosis. Moreover, the study investigated the impact of ATF6α in OS aggressiveness through genetic and pharmacological loss of function analyses. Lastly, the CellChat algorithm was employed to investi

SUBMITTER: Liu F 

PROVIDER: S-EPMC11834279 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature