Bibliographic Details
| Title: |
Identification of a Costimulatory Molecule-Related Signature for Predicting Prognostic Risk in Prostate Cancer |
| Authors: |
Shengdong Ge, Xiaoliang Hua, Juan Chen, Haibing Xiao, Li Zhang, Jun Zhou, Chaozhao Liang, Sheng Tai |
| Source: |
Frontiers in Genetics, Vol 12 (2021) |
| Publisher Information: |
Frontiers Media S.A., 2021. |
| Publication Year: |
2021 |
| Collection: |
LCC:Genetics |
| Subject Terms: |
prostate cancer, costimulatory molecules, bioinformatics, biomarker, prognostic signature, Genetics, QH426-470 |
| More Details: |
Costimulatory molecules have been proven to enhance antitumor immune responses, but their roles in prostate cancer (PCa) remain unexplored. In this study, we aimed to explore the gene expression profiles of costimulatory molecule genes in PCa and construct a prognostic signature to improve treatment decision making and clinical outcomes. Five prognosis-related costimulatory molecule genes (RELT, TNFRSF25, EDA2R, TNFSF18, and TNFSF10) were identified, and a prognostic signature was constructed based on these five genes. This signature was an independent prognostic factor according to multivariate Cox regression analysis; it could stratify PCa patients into two subgroups with different prognoses and was highly associated with clinical features. The prognostic significance of the signature was well validated in four different independent external datasets. Moreover, patients identified as high risk based on our prognostic signature exhibited a high mutation frequency, a high level of immune cell infiltration and an immunosuppressive microenvironment. Therefore, our signature could provide clinicians with prognosis predictions and help guide treatment for PCa patients. |
| Document Type: |
article |
| File Description: |
electronic resource |
| Language: |
English |
| ISSN: |
1664-8021 |
| Relation: |
https://www.frontiersin.org/articles/10.3389/fgene.2021.666300/full; https://doaj.org/toc/1664-8021 |
| DOI: |
10.3389/fgene.2021.666300 |
| Access URL: |
https://doaj.org/article/4330ef3178b64bc3b9b5dcd90b0b9c7f |
| Accession Number: |
edsdoj.4330ef3178b64bc3b9b5dcd90b0b9c7f |
| Database: |
Directory of Open Access Journals |
