Kubota Shigehisa, Yoshida Tetsuya, Kageyama Susumu, Isono Takahiro, Yuasa Takeshi, Yonese Junji, Kushima Ryoji, Kawauchi Akihiro, Chano Tokuhiro
Department of Urology, Shiga University of Medical Science, SetaTshukinowa-cho, Otsu, Shiga, 520-2192, Japan.
Central Research Laboratory, Shiga University of Medical Science, SetaTshukinowa-cho, Otsu, Shiga, 520-2192, Japan.
World J Surg Oncol. 2020 Oct 22;18(1):270. doi: 10.1186/s12957-020-02046-9.
Accurate prediction of the prognosis of RCC using a single biomarker is challenging due to the genetic heterogeneity of the disease. However, it is essential to develop an accurate system to allow better patient selection for optimal treatment strategies. ARL4C, ECT2, SOD2, and STEAP3 are novel molecular biomarkers identified in earlier studies as survival-related genes by comprehensive analyses of 43 primary RCC tissues and RCC cell lines.
To develop a prognostic model based on these multiple biomarkers, the expression of four biomarkers ARL4C, ECT2, SOD2, and STEAP3 in primary RCC tissue were semi-quantitatively investigated by immunohistochemical analysis in an independent cohort of 97 patients who underwent nephrectomy, and the clinical significance of these biomarkers were analyzed by survival analysis using Kaplan-Meier curves. The prognostic model was constructed by calculation of the contribution score to prognosis of each biomarker on Cox regression analysis, and its prognostic performance was validated.
Patients whose tumors had high expression of the individual biomarkers had shorter cancer-specific survival (CSS) from the time of primary nephrectomy. The prognostic model based on four biomarkers segregated the patients into a high- and low-risk scored group according to defined cut-off value. This approach was more robust in predicting CSS compared to each single biomarker alone in the total of 97 patients with RCC. Especially in the 36 metastatic RCC patients, our prognostic model could more accurately predict early events within 2 years of diagnosis of metastasis. In addition, high risk-scored patients with particular strong SOD2 expression had a much worse prognosis in 25 patients with metastatic RCC who were treated with molecular targeting agents.
Our findings indicate that a prognostic model based on four novel biomarkers provides valuable data for prediction of clinical prognosis and useful information for considering the follow-up conditions and therapeutic strategies for patients with primary and metastatic RCC.
由于肾癌的基因异质性，使用单一生物标志物准确预测肾癌的预后具有挑战性。然而，开发一个准确的系统以更好地选择患者进行最佳治疗策略至关重要。ARL4C、ECT2、SOD2和STEAP3是早期研究中通过对43例原发性肾癌组织和肾癌细胞系进行综合分析而鉴定出的与生存相关的新型分子生物标志物。
为了基于这些多种生物标志物开发一种预后模型，通过免疫组织化学分析对97例行肾切除术的独立队列患者的原发性肾癌组织中四种生物标志物ARL4C、ECT2、SOD2和STEAP3的表达进行半定量研究，并使用Kaplan-Meier曲线通过生存分析来分析这些生物标志物的临床意义。通过Cox回归分析计算每个生物标志物对预后的贡献得分来构建预后模型，并对其预后性能进行验证。
肿瘤中单个生物标志物高表达的患者自初次肾切除术后的癌症特异性生存（CSS）时间较短。基于四种生物标志物的预后模型根据定义的临界值将患者分为高风险评分组和低风险评分组。在总共97例肾癌患者中，与单独使用每个单一生物标志物相比，这种方法在预测CSS方面更可靠。特别是在36例转移性肾癌患者中，我们的预后模型能够更准确地预测转移诊断后2年内的早期事件。此外，在接受分子靶向药物治疗的25例转移性肾癌患者中，SOD2表达特别强的高风险评分患者预后更差。
我们的研究结果表明，基于四种新型生物标志物的预后模型为预测临床预后提供了有价值的数据，并为考虑原发性和转移性肾癌患者的随访情况和治疗策略提供了有用信息。
