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<p>Emerging evidence has shown that the N<sup>6</sup>-methyladenosine (m<sup>6</sup>A) modification of RNA plays key roles in tumorigenesis and the progression of various cancers. However, the potential roles of the m<sup>6</sup>A modification of long noncoding RNAs (lncRNAs) in pancreatic cancer (PaCa) are still unknown. To analyze the prognostic value of m<sup>6</sup>A-related lncRNAs in PaCa, an m6A-related lncRNA signature was constructed as a risk model <i>via</i> Pearson’s correlation and univariate Cox regression analyses in The Cancer Genome Atlas (TCGA) database. The tumor microenvironment (TME), tumor mutation burden, and drug sensitivity of PaCa were investigated by m<sup>6</sup>A-related lncRNA risk score analyses. We established an m<sup>6</sup>A-related risk prognostic model consisting of five lncRNAs, namely, LINC01091, AC096733.2, AC092171.5, AC015660.1, and AC005332.6, which not only revealed significant differences in immune cell infiltration associated with the TME between the high-risk and low-risk groups but also predicted the potential benefit of immunotherapy for patients with PaCa. Drugs such as WZ8040, selumetinib, and bortezomib were also identified as more effective for high-risk patients. Our results indicate that the m<sup>6</sup>A-related lncRNA risk model could be an independent prognostic indicator, which may provide valuable insights for identifying therapeutic approaches for PaCa.</p>

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N6-Methylandenosine-related lncRNAs as potential biomarkers for predicting prognosis and the immunotherapy response in pancreatic cancer

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年1月21日

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  • Zhihui Bai,
  • Qianlin Xia,
  • Wanli Xu,
  • Zhirong Wu,
  • Xiaomeng He,
  • Xin Zhang,
  • Zhefeng Wang,
  • Mengting Luo,
  • Huaqin Sun,
  • Songmei Liu,
  • Jin Wang

摘要

Emerging evidence has shown that the N6-methyladenosine (m6A) modification of RNA plays key roles in tumorigenesis and the progression of various cancers. However, the potential roles of the m6A modification of long noncoding RNAs (lncRNAs) in pancreatic cancer (PaCa) are still unknown. To analyze the prognostic value of m6A-related lncRNAs in PaCa, an m6A-related lncRNA signature was constructed as a risk model via Pearson’s correlation and univariate Cox regression analyses in The Cancer Genome Atlas (TCGA) database. The tumor microenvironment (TME), tumor mutation burden, and drug sensitivity of PaCa were investigated by m6A-related lncRNA risk score analyses. We established an m6A-related risk prognostic model consisting of five lncRNAs, namely, LINC01091, AC096733.2, AC092171.5, AC015660.1, and AC005332.6, which not only revealed significant differences in immune cell infiltration associated with the TME between the high-risk and low-risk groups but also predicted the potential benefit of immunotherapy for patients with PaCa. Drugs such as WZ8040, selumetinib, and bortezomib were also identified as more effective for high-risk patients. Our results indicate that the m6A-related lncRNA risk model could be an independent prognostic indicator, which may provide valuable insights for identifying therapeutic approaches for PaCa.