ArticleHeliyon2024
Establishment of RNA modification regulators index predicting clinical outcomes and immune relevance of kidney cancer patients.
Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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7 authors.
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Abstract
Increasing evidence indicates that RNA modifications are misregulated in human cancers, which might be optimal targets of cancer therapy. However, important RNA regulators in kidney cancer still need further exploration. In this study, we collected regulators representing different types of RNA modification and identified the prognosis-related RNA regulators in kidney cancer patients. We further constructed a 4-gene RNA regulators signature and index called prognosis-related RNA regulators index (PRRI) by the Lasso-Cox regression algorithm. We found that PRRI could precisely predict prognosis of patients in the KIRC training (AUC at 3-/5-/7-years = 0.7132/0.7220/0.7283) and testing cohorts (AUC at 3-/5-/7-years = 0.7141/0.7403/0.7305) and two independent RCC cohorts - E-MTAB-1980 (AUC at 3-/5-/7-years = 0.7036/0.7385/0.7143) and KIRP (AUC at 3-/5-/7-years = 0.6203/0.6365/0.6941). Moreover, the high PRRI group showed a worse clinical outcome than the low PRRI group. PRRI demonstrated strong robustness and was related to histological grade and pathologic stage, which was also found to be an independent prognosis factor when other clinical variables adjusted it. We further found several immune-related pathways differentially enriched in the high or low PRRI group. The regulation of T cell migration, which has been proven to be an immunosuppressive cell, shows a high enrichment in the high PRRI group. Further analysis reveals that PRRI also shows a highly positive correlation with the activity of Tregs. TIDE analysis and two independent immune therapy cohorts revealed that the high PRRI group might resist immune therapy, while the low PRRI group might benefit from the treatment, indicating that PRRI could be a marker for predicting immune therapeutic response. All in all, we determined 4 potentially essential RNA regulators and illustrated their mechanisms concretely. Furthermore, we constructed a 4-gene index called PRRI to predict patients' outcomes and immunotherapy response.
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