Construction of the Prediction Model for Locally Advanced Rectal Cancer Following Neoadjuvant Chemoradiotherapy Based on Pretreatment Tumor-Infiltrating Macrophage-Associated Biomarkers

基于治疗前肿瘤浸润巨噬细胞相关生物标志物构建局部晚期直肠癌新辅助放化疗后预测模型

阅读:9
作者:Xing Liu, Shuping Zheng, Yong Peng, Jinfu Zhuang, Yuanfeng Yang, Yunlu Xu, Guoxian Guan

Conclusion

The expression levels of macrophage-related biomarkers CD163, CD68, MCSF, and CCL2 were associated with chemoradiotherapy resistance and prognosis in LARC patients following NCRT. A risk score model was constructed which could be used to predict LARC outcome.

Methods

We enrolled 191 patients who underwent neoadjuvant chemoradiotherapy and radical resection between 2011 and 2015. Tumor tissues were collected before NCRT with a colonoscope and post-surgery and were subjected to immunohistochemical analysis.

Purpose

To assess the value of macrophage-related biomarkers (CD163, CD68, MCSF, and CCL2) for predicting the response to neo-chemoradiotherapy (NCRT) and the prognosis of locally advanced rectal cancer (LARC).

Results

The expression levels of macrophage-related biomarkers (CD163, CD68, MCSF, and CCL2) were lower in the pathological complete response (pCR) group when compared with the non-pCR group (all P<0.05). Based on X-tile plots, we divided the tumors in two groups and found that lower pre-NCRT/post-surgical CD163, CD68, MCSF, CCL2 scores correlated with improved DFS. Cox regression analysis demonstrated that pre-NCRT CD163 (HR=1.008, 95% CI 1.003-1.013, P=0.003) and MCSF (HR=2.187, 95% CI 1.343-3.564, P=0.002) scores were independent predictors of DFS. Based on Cox multivariate analysis, we constructed a risk score model with a powerful ability to predict pCR in LARC patients. Moreover, COX regression analysis was performed to explore the role of the risk score in LARC patients. The results demonstrated that tumor size (HR=1.291, P=0.041), worse pathological TNM stage (HR=1.789, P=0.005, and higher risk score (HR=1.084, P<0.001) were significantly associated with impaired disease-free survival. Based on the above results, a nomogram and decision curve analysis were generated.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。