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Single-cell and bulk RNA sequencing reveals Anoikis related genes to guide prognosis and immunotherapy in osteosarcoma

Authors :
Cheng Zhong
Dongliang Yang
Liping Zhong
Weixing Xie
Guodong Sun
Daxiang Jin
Yuming Li
Source :
Scientific Reports, Vol 13, Iss 1, Pp 1-16 (2023)
Publication Year :
2023
Publisher :
Nature Portfolio, 2023.

Abstract

Abstract Anoikis resistance, a notable factor in osteosarcoma, plays a significant role in tumor invasion and metastasis. This study seeks to identify a distinct gene signature that is specifically associated with the anoikis subcluster in osteosarcoma. Clinical, single-cell, and transcriptional data from TARGET and GEO datasets were used to develop a gene signature for osteosarcoma based on the anoikis subcluster. Univariate Cox and LASSO regression analyses were employed. The signature's predictive value was evaluated using time-dependent ROC and Kaplan–Meier analyses. Functional enrichment analyses and drug sensitivity analyses were conducted. Validation of three modular genes was performed using RT-qPCR and Western blotting. Signature (ZNF583, CGNL1, CXCL13) was developed to predict overall survival in osteosarcoma patients, targeting the anoikis subcluster. The signature demonstrated good performance in external validation. Stratification based on the signature revealed significantly different prognoses. The signature was an independent prognostic factor. The low-risk group showed enhanced immune cell infiltration and improved immune function. Drug sensitivity analysis indicated efficacy of chemotherapy agents. Prognostic nomograms incorporating the signature provided greater predictive accuracy and clinical utility. Signatures related to the anoikis subcluster play a significant role in osteosarcoma progression. Incorporating these findings into clinical decision-making can improve osteosarcoma treatment and patient outcomes.

Subjects

Subjects :
Medicine
Science

Details

Language :
English
ISSN :
20452322
Volume :
13
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Scientific Reports
Publication Type :
Academic Journal
Accession number :
edsdoj.70925668ca4cd68ba06412cafb7ac2
Document Type :
article
Full Text :
https://doi.org/10.1038/s41598-023-47367-3