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Anoikis-related gene CDKN2A predicts prognosis and immune response and mediates proliferation and migration in thyroid carcinoma
- Source :
- Translational Oncology, Vol 40, Iss , Pp 101873- (2024)
- Publication Year :
- 2024
- Publisher :
- Elsevier, 2024.
-
Abstract
- Thyroid carcinoma (THCA) is a tumor commonly occurring in the endocrine system, and its incidence rate is increasing yearly. Anoikis is a type of cell death involved in the carcinogenesis process. This study aimed to investigate the prognosis and immune correlations of anoikis in THCA. Our study used several bioinformatics algorithms (co-expression analysis, univariate and multivariate Cox analysis) to screen anoikis-related genes (ARGs) to construct risk models. Through receiver operating characteristic (ROC) curve, nomogram, and independent prognostic analysis found that the constructed model had ideal predictive value for THCA. The consensus clustering method was used to divide ARG patterns into three subgroups, and there were significant differences in survival among the three subgroups. The CIBERSORT algorithm demonstrated strong correlations among immune infiltrating cells, prognostic genes, and risk scores. Univariate and multivariate Cox analysis showed that CDKN2A is an independent prognostic gene. Basic experiments (immunohistochemistry, qRT-PCR, etc.) showed that the expression levels of CDKN2A mRNA and protein were highly expressed in THCA, which was consistent with the results of bioinformatics analysis. In vitro, the knockdown of CDKN2A significantly inhibited the proliferation and migration of THCA cells. In summary, our study utilized eight ARGs to construct an accurate risk model. ARGs, especially CDKN2A, play a crucial role in the occurrence and development of THCA and can become potential targets for treating THCA patients.
Details
- Language :
- English
- ISSN :
- 19365233
- Volume :
- 40
- Issue :
- 101873-
- Database :
- Directory of Open Access Journals
- Journal :
- Translational Oncology
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.087016e533e345babd3fb7b99c0fcf2a
- Document Type :
- article
- Full Text :
- https://doi.org/10.1016/j.tranon.2023.101873