Comprehensive analysis of the LINC01122/TPD52 axis as a predictive biomarker in prostate adenocarcinoma

Prostate cancer (PCa) ranks among the most prevalent malignant tumors worldwide. The pivotal role of competitive endogenous RNA (ceRNA) regulatory networks in numerous cancer types has been underscored. However, the specific characteristics of the ceRNA network in PCa remained unknown. This study aims to elucidate the ceRNA regulatory network associated with phosphatase and tensin homolog (PTEN) and to identify potential prognostic markers for PCa. The Cancer Genome Atlas (TCGA) database was employed to extract the expression patterns of long non-coding RNAs (lncRNAs), microRNAs (miRNAs), and messenger RNAs (mRNAs). LINC01122-hsa-miR-34c-5p/hsa-miR-449a-TPD52 ceRNA network regarding the prognosis of PCa was explored via bioinformatics analysis. Through correlation analysis, we investigated the LINC01122/TPD52 axis within the ceRNA network, identifying it as a significant clinical prognostic marker for PCa. Subsequent analyses indicated that hypomethylation was responsible for the abnormal upregulation of the LINC01122/TPD52 axis. Furthermore, immune infiltration analysis revealed the impact of the LINC01122/TPD52 axis on the tumor immune microenvironment and the progression of PCa. Finally, a nomogram was constructed to forecast the 1-year, 3-year, and 5-year survival probabilities of PCa patients. In summary, our study demonstrates the significant role of the ceRNA-based LINC01122/TPD52 axis in the progression of PCa and its correlation with prognosis.

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Publication Details

Journal
Scientific Reports
Published
2025-05-08
DOI
https://doi.org/10.1038/s41598-025-98219-1
Citations
1
Primary Topic
Cancer-related molecular mechanisms research
Type
article
Field-Weighted Citation Impact
0.94

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article

Comprehensive analysis of the LINC01122/TPD52 axis as a predictive biomarker in prostate adenocarcinoma

Shengming Jin, Zhe Hong, Junlong Wu, Zhi Shang et al.
1 citations
Scientific Reports
Cancer-related molecular mechanisms research
0.94
article

Comprehensive analysis of the LINC01122/TPD52 axis as a predictive biomarker in prostate adenocarcinoma

Shengming Jin, Zhe Hong, Junlong Wu, Zhi Shang, Yandong He, Yiping Zhu, Hailiang Zhang, Dingwei Ye
article en
1 citations

Abstract

Prostate cancer (PCa) ranks among the most prevalent malignant tumors worldwide. The pivotal role of competitive endogenous RNA (ceRNA) regulatory networks in numerous cancer types has been underscored. However, the specific characteristics of the ceRNA network in PCa remained unknown. This study aims to elucidate the ceRNA regulatory network associated with phosphatase and tensin homolog (PTEN) and to identify potential prognostic markers for PCa. The Cancer Genome Atlas (TCGA) database was employed to extract the expression patterns of long non-coding RNAs (lncRNAs), microRNAs (miRNAs), and messenger RNAs (mRNAs). LINC01122-hsa-miR-34c-5p/hsa-miR-449a-TPD52 ceRNA network regarding the prognosis of PCa was explored via bioinformatics analysis. Through correlation analysis, we investigated the LINC01122/TPD52 axis within the ceRNA network, identifying it as a significant clinical prognostic marker for PCa. Subsequent analyses indicated that hypomethylation was responsible for the abnormal upregulation of the LINC01122/TPD52 axis. Furthermore, immune infiltration analysis revealed the impact of the LINC01122/TPD52 axis on the tumor immune microenvironment and the progression of PCa. Finally, a nomogram was constructed to forecast the 1-year, 3-year, and 5-year survival probabilities of PCa patients. In summary, our study demonstrates the significant role of the ceRNA-based LINC01122/TPD52 axis in the progression of PCa and its correlation with prognosis.

Scientific ReportsVol. 15(1)
Shanghai Medical College of Fudan University (CN), Fudan University Shanghai Cancer Center (CN), Shanghai Cancer Institute (CN)
Natural Science Foundation of Shanghai, Beijing Xisike Clinical Oncology Research Foundation, National Natural Science Foundation of China, Shanghai Municipal Health Bureau
Good health and well-being
Openalex Percentile: Top 25%
Cancer-related molecular mechanisms research
0.94
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