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Updated: Oct 23, 2025
Multiplexed Immunofluorescence Analysis and Quantification of Intratumoral PD-1+ Tim-3+ CD8+ T Cells
Published on: February 8, 2018
Integrated analysis on the N6-methyladenosine-related long noncoding RNAs prognostic signature, immune checkpoints,
Yuqin Qiu1, Xiaogang Wang2, Zhenjia Fan1
1Third Affiliated Hospital, Beijing University of Chinese Medicine, Beijing, China.
Background:
Patients with advanced clear cell renal cell carcinoma (ccRCC) have a poor prognosis and lack effective prognostic biomarkers. N6-methyladenosine-related lncRNAs (m6A-related long noncoding RNAs [lncRNAs]) have been confirmed to be associated with the development of multiple tumors, but its role in ccRCC is not clear.
Methods:
Gene expression data and clinical information of ccRCC patients were extracted from The Cancer Genome Atlas Database. The prognostic m6A-related lncRNAs were obtained by Pearson's correlation analysis and univariate Cox regression analysis. Afterward, the cluster classification and its correlation with prognosis, clinical characteristics, and immunity were analyzed. LASSO regression was used to establish the prognostic risk model. The predictive performance of the prognostic model was evaluated and validated by survival analysis and receiver operating characteristic curve analysis, et al. The expression of immune checkpoints and immune cell infiltration in patients with different risks were systematically analyzed.
Results:
A total of 27 prognostic m6A-related lncRNAs were identified. These m6A-related lncRNAs were differentially expressed between tumor and normal tissues. Among them, 24 high-risk m6A-related lncRNAs were overexpressed in Cluster 2 and correlated with poor prognosis, low stromal score, high expression of immune checkpoints, and immunosuppressive cells infiltration. Based upon, a prognostic risk model composed of seven m6A-related lncRNAs was constructed. After a series of analyses, it was proved that this model had good sensitivity and specificity, and could predict the prognosis of patients with different clinical stratification. The expression of PD-1, PD-L1, CTLA-4, LAG-3, TIM-3, and TIGIT were significantly increased in the high-risk patients, and there was a correlation between the risk score and immune cell infiltration.
Conclusions:
The seven m6A-related lncRNAs prognostic risk signature showed reliable prognostic predictive power for ccRCC and was associated with the expression of immune checkpoints and immune cell infiltration. This seven m6A-related lncRNAs signature will be helpful in managing ccRCC and guiding individualized immunotherapy.
