Integration of intratumoral RASSF10 expression and tumor-associated macrophages into the established clinical indicators better predicts the prognosis of clear cell renal cell carcinoma patients

将肿瘤内 RASSF10 表达和肿瘤相关巨噬细胞整合到既定的临床指标中可以更好地预测透明细胞肾细胞癌患者的预后

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作者:Chao Wang, Tianyu Hong, Yuning Wang, Sishun Gan, Qifeng Wang, Jian Li, Li Zuo, Xingang Cui

Abstract

A helpful evaluation system is crucial for the postoperative prognosis prediction of clear cell renal cell carcinoma (ccRCC) patients. This study determined the prognostic value of combining intratumoral RASSF10 expression and tumor-associated macrophages (TAMs) with the established clinicopathological indicators in ccRCC patients. RASSF10 expression was analyzed in ccRCC patient data from online databases and ccRCC cell lines. Two independent ccRCC patient cohorts were employed to examine the prognostic value of RASSF10 and other markers by immunohistochemistry (IHC) and statistical analyses. We found that RASSF10 expression was downregulated in ccRCC specimens from the TCGA datasets and three independent institutions. RASSF10 expression was negatively correlated with disease progression and TAM infiltration in ccRCC. In addition, low RASSF10 expression and high TAM infiltration predicted a high TNM stage, SSIGN score, WHO/ISUP grading, and a poor prognosis in two independent ccRCC patient cohorts. Moreover, RASSF10, CD68 or CD163, TNM stage, and SSIGN score were identified as independent risk factors in predicting ccRCC patients' prognosis. Time-dependent c-index analyses revealed that the combination of RASSF10 and TAMs resulted in a higher index than that resulting from each alone in the postoperative prognosis of ccRCC patients, and the integration of RASSF10 and TAMs with the TNM stage or SSIGN score achieved the best accuracy in assessing the prognosis of ccRCC patients. These findings were validated in the randomized training, validation, and combined cohorts. Taken together, the combination of the RASSF10-TAM classifier and current clinical parameters yields superior accuracy in predicting the ccRCC patients' postoperative outcome.

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