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Updated: Sep 20, 2025
Author Spotlight: Investigating Immune Cell Dynamics in the Tumor Microenvironment — Challenges and Innovations in Cancer Prognosis
Published on: April 12, 2024
Prognostic value of p16, p53, and pcna in sarcoma and an evaluation of immune infiltration
Dechao Cai1, Xiao Ma1, Huihui Guo1
1Department of Orthopedics, The Second Hospital of Anhui Medical University, 678 Furong Road, Hefei, 230601, China.
Background:
p16, p53, and proliferating cell nuclear antigen (pcna) genes play significant roles in many chromatin modifications and have been found to be highly expressed in a variety of tumor tissues. Therefore, they have been used as target genes for some tumor therapies. However, the differential expressions of the p16, p53, and pcna genes in human sarcomas and their effects on prognosis have not been widely reported.
Methods:
The Oncomine dataset was used to analyze the transcription levels of p16, p53, and pcna genes, and the gene expression profile interactive analysis (GEPIA) dataset was used to analyze the differential expressions of p16, p53, and pcna. The expression levels of p16, p53, and pcna were further analyzed by Western Blotting. GEPIA and Kaplan-Meier analyses were used to analyze the prognostic value of p16, p53, and pcna. Furthermore, p16, p53, and pcna gene mutations and their association with overall survival (OS) and disease-free survival (DFS) were analyzed using cBioPortal datasets. In addition, genes co-expressed with p16, p53, and pcna were analyzed using Oncomine. The DAVID dataset was used to analyze the functional enrichment of p16, p53, pcna, and their co-expressed genes by Gene Ontology (GO) and Metascape were used to construct a network map. Finally, the immune cell infiltration of p16, p53, and pcna in patients with sarcoma was reported by Tumor Immune Estimation Resource (TIMER).
Results:
p16, p53, and pcna were up-regulated in human sarcoma tissues and almost all sarcoma cell lines. Western Blotting showed that the expression of p16, p53, and pcna was elevated in osteosarcoma cell lines. The expression of pcna was correlated with OS, the expression of p16, p53, and pcna was correlated with relapse-free survival, and the genetic mutation of p16 was negatively correlated with OS and DFS. We also found that p16, p53, and pcna genes were positively/negatively correlated with immune cell infiltration in sarcoma.
Conclusions:
The results of this study showed that p16, p53, and pcna can significantly affect the survival and immune status of sarcoma patients. Therefore, p16, p53, and pcna could be used as potential biomarkers of prognosis and immune infiltration in human sarcoma and provide a possible therapeutic target for sarcoma.
