Cancer Medicine (Feb 2023)

Combining expression of RNF43 and infiltration level of CD163+ tumor associated macrophage predicts prognosis of clear cell renal cell carcinoma

  • Dawei Zhu,
  • Xiaokai Shi,
  • Yijun Tian,
  • Hao Li,
  • Bowen Tang,
  • Ziyi Zhang,
  • Ze Zhang,
  • Li Zuo

DOI
https://doi.org/10.1002/cam4.5229
Journal volume & issue
Vol. 12, no. 4
pp. 3962 – 3971

Abstract

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Abstract Searching for reliable indicators for evaluating prognosis diagnosed with clear cell renal cell carcinoma (ccRCC) is crucial for improving clinical therapies. However, current researches have looked mainly at the prognostic value of a single intratumoral indicator, neglecting tumor‐infiltrating immune cells (TIICs) in the microenvironment. This study examined whether the integration of Ring finger protein 43 (RNF43) expression and CD163+ tumor‐associated macrophage (TAM) infiltration in combination with clinical indexes forecast ccRCC patient outcome with relatively high accuracy. Firstly, the expression of RNF43 and CD163 were detected with immunohistochemistry. Totally, 346 ccRCC patients were random separated evenly into training and validation datasets to make further analyses. We found that RNF43 expression was negatively correlated with infiltration level of CD163+ TAM in ccRCC, which was closely associated with the TNM stage and outcome of these patients. The multiple regression analysis demonstrated that RNF43, CD163, and TNM stage could function as independent risk factors in overall survival (OS) and progression‐free survival (PFS) prediction of ccRCC. Furthermore, a better postoperative prognosis index for ccRCC patients was obtained by combining RNF43 and CD163+ TAMs, which assessed with time‐dependent C‐index analyses and a nomogram. Consequently, combining RNF43 and CD163+ TAMs along with TNM stage acquired robust accuracy in forecasting outcome of patients with ccRCC. In conclusion, combining intratumoral RNF43 expression, CD163+ TAM infiltration, and TNM stage could significantly enhance the veracity in forecasting postoperative outcomes.

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