Cancer Medicine (Dec 2023)

Comprehensive analysis of clinical prognosis and biological significance of CNIH4 in cervical cancer

  • Jiajia Wang,
  • Shudan Wang,
  • Junli Wang,
  • Jingjing Huang,
  • Haishan Lu,
  • Bin Pan,
  • Hanyi Pan,
  • Yanlun Song,
  • Qianqian Deng,
  • Xiaojun Jin,
  • Guiling Shi

DOI
https://doi.org/10.1002/cam4.6734
Journal volume & issue
Vol. 12, no. 24
pp. 22381 – 22394

Abstract

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Abstract Background Cornichon homolog 4 (CNIH4) belongs to the CNIH family. It functions as an oncogene in many tumors. However, CNIH4's significance in the immune landscape and its predictive potential in cervical cancer (CESC) is unexplored. Methods CNIH4 levels and its effect on the survival of patients with CESC were evaluated using data retrieved from The Cancer Genome Atlas (TCGA). The oncogenic effect of CNIH4 in CESC was determined using small interfering RNA‐mediated transfected cell lines and tumorigenesis experiments in animal models. Results Higher expression of CNIH4 was found in advanced tumor and pathological stages, as well as lymph node metastasis. CNIH4 expression correlated positively with the infiltration of macrophages M2 and resting dendritic cells into the affected tissue. Additionally, functional enrichment of RNA‐sequencing of CNIH4‐knocked down CESC cell lines showed the association of CNIH4 to the PI3K‐Akt signaling pathway. Single‐sample gene set enrichment analysis highlighted several immune pathways that were elevated in the CESC samples with enhanced levels of CNIH4, including Type‐I and Type‐II IFN‐response pathways. The impact of CNIH4 on drug sensitivity was further assessed using the GDSC database. As CNIH4 is linked to the immune landscape in CESC, this study determined a four‐gene risk prediction signature utilizing CNIH4‐related immunomodulators. The risk score quantified from the prediction signature was an independent predictive indicator in CESC. Receiver operating characteristic curve analysis verified the good predictive ability of the four‐gene signature in TCGA‐CESC cohort. Thus, the CNIH4‐related model showed potential as an auxiliary TNM staging system tool. Conclusion CNIH4 may be an effective predictive biomarker for patients with cervical cancer, thus providing new ideas and research directions for CESC.

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