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Background <p>RNA editing is recognized as a crucial factor in cancer biology. Its potential application in predicting the prognosis of colon adenocarcinoma (COAD) remains unexplored.</p> Methods <p>RNA editing data of COAD patients were downloaded from the Synapse database. LASSO regression was used to construct the risk model and verified by the receiver operating characteristic (ROC) curve. GO and KEGG enrichment analyses were performed to delineate the biological significance of the differentially expressed genes. Finally, differential analysis and immunohistochemistry were used to verify the expression of adenosine deaminase 1 (ADAR1).</p> Results <p>We evaluated a total of 4079 RNA editing sites in 514 COAD patients from Synapse database. A prognostic signature was constructed based on five genes were significantly associated with the prognosis of COAD patients including GNL3L, NUP43, MAGT1, EMP2, and ARSD. Univariate and multivariate Cox regression analysis revealed that RNA editing-related genes (RERGs)-related signature was an independent risk factor for COAD. Moreover, Experimental evidence shows that ADAR1 is highly expressed in colon adenocarcinoma and silencing ADAR1 can inhibit cancer cell proliferation.</p> Conclusion <p>We established a prognostic model based on five RERGs with strong predictive value. This model not only serves as a foundation for a novel prognostic tool but also facilitates the identification of potential drug candidates for treating COAD.</p>

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Unveiling the prognostic significance of RNA editing-related genes in colon cancer: evidence from bioinformatics and experiment

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年2月12日

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  • Zhengcong Deng,
  • Xueqin Jin,
  • Bingxue Liu,
  • Hongyan Zhen,
  • Xiang Wang

摘要

Background

RNA editing is recognized as a crucial factor in cancer biology. Its potential application in predicting the prognosis of colon adenocarcinoma (COAD) remains unexplored.

Methods

RNA editing data of COAD patients were downloaded from the Synapse database. LASSO regression was used to construct the risk model and verified by the receiver operating characteristic (ROC) curve. GO and KEGG enrichment analyses were performed to delineate the biological significance of the differentially expressed genes. Finally, differential analysis and immunohistochemistry were used to verify the expression of adenosine deaminase 1 (ADAR1).

Results

We evaluated a total of 4079 RNA editing sites in 514 COAD patients from Synapse database. A prognostic signature was constructed based on five genes were significantly associated with the prognosis of COAD patients including GNL3L, NUP43, MAGT1, EMP2, and ARSD. Univariate and multivariate Cox regression analysis revealed that RNA editing-related genes (RERGs)-related signature was an independent risk factor for COAD. Moreover, Experimental evidence shows that ADAR1 is highly expressed in colon adenocarcinoma and silencing ADAR1 can inhibit cancer cell proliferation.

Conclusion

We established a prognostic model based on five RERGs with strong predictive value. This model not only serves as a foundation for a novel prognostic tool but also facilitates the identification of potential drug candidates for treating COAD.