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整合肿瘤基质生物标志物与临床指标用于结肠癌生存分层

Integrating Tumor Stroma Biomarkers With Clinical Indicators for Colon Cancer Survival Stratification.

作者信息

Chen Yong, Wang Wenlong, Jiang Bo, Yao Lei, Xia Fada, Li Xinying

机构信息

Department of General Surgery, Xiangya Hospital, Central South University, Changsha, China.

出版信息

Front Med (Lausanne). 2020 Dec 7;7:584747. doi: 10.3389/fmed.2020.584747. eCollection 2020.

Abstract

The tumor stroma plays an important role in tumor progression and chemotherapeutic resistance; however, its role in colon cancer (CC) survival prognosis remains to be investigated. Here, we identified tumor stroma biomarkers and evaluated their role in CC prognosis stratification. Four independent datasets containing a total of 1,313 patients were included in this study and were divided into training and testing sets. Stromal scores calculated using the estimation of stromal and immune cells in malignant tumors using expression data (ESTIMATE) algorithm were used to assess the tumor stroma level. Kaplan-Meier curves and the log-rank test were used to identify relationships between stromal score and prognosis. Tumor stroma biomarkers were identified by cross-validation of multiple datasets and bioinformatics methods. Cox proportional hazards regression models were constructed using four prognosis factors (age, tumor stage, the ESTIMATE stromal score, and the biomarker stromal score) in different combinations for prognosis prediction and compared. Patients with high stromal scores had a lower overall survival rate ( = 0.00016), higher risk of recurrence ( < 0.0001), and higher probability of chemotherapeutic resistance ( < 0.0001) than those with low scores. We identified 16 tumor stroma biomarkers and generated a new prognosis indicator termed the biomarker stromal score (ranging from 0 to 16) based on their expression levels. Its addition to an age/tumor stage-based model significantly improved prognosis prediction accuracy. In conclusion, the tumor stromal score is significantly negatively associated with CC survival prognosis, and the new tumor stroma indicator can improve CC prognosis stratification.

摘要

肿瘤基质在肿瘤进展和化疗耐药中起重要作用;然而,其在结肠癌(CC)生存预后中的作用仍有待研究。在此,我们鉴定了肿瘤基质生物标志物,并评估了它们在CC预后分层中的作用。本研究纳入了四个独立数据集,共1313例患者,并将其分为训练集和测试集。使用基于表达数据估算恶性肿瘤中的基质和免疫细胞(ESTIMATE)算法计算的基质分数来评估肿瘤基质水平。采用Kaplan-Meier曲线和对数秩检验来确定基质分数与预后之间的关系。通过多个数据集的交叉验证和生物信息学方法鉴定肿瘤基质生物标志物。使用四个预后因素(年龄、肿瘤分期、ESTIMATE基质分数和生物标志物基质分数)以不同组合构建Cox比例风险回归模型进行预后预测并比较。与基质分数低的患者相比,基质分数高的患者总生存率较低( = 0.00016),复发风险较高( < 0.0001),化疗耐药概率较高( < 0.0001)。我们鉴定了16种肿瘤基质生物标志物,并根据它们的表达水平生成了一个新的预后指标,称为生物标志物基质分数(范围为0至十六)。将其添加到基于年龄/肿瘤分期的模型中可显著提高预后预测准确性。总之,肿瘤基质分数与CC生存预后显著负相关,新的肿瘤基质指标可改善CC预后分层。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a268/7750539/720c03a2a574/fmed-07-584747-g0001.jpg

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