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基于基因表达的回顾性研究:构建并验证整合免疫相关基因特征与临床病理特征的列线图模型以改善三阴性乳腺癌患者的预后和预测价值。

Development and validation of nomograms integrating immune-related genomic signatures with clinicopathologic features to improve prognosis and predictive value of triple-negative breast cancer: A gene expression-based retrospective study.

机构信息

Department of the Endocrine and Breast Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing Medical University, Chongqing, China.

Department of Gastrointestinal Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing Medical University, Chongqing, China.

出版信息

Cancer Med. 2019 Feb;8(2):686-700. doi: 10.1002/cam4.1880. Epub 2019 Jan 24.

Abstract

PURPOSE

Accumulating evidence indicated that triple-negative breast cancer (TNBC) can stimulate stronger immune responses than other subtypes of breast cancer. We hypothesized that integrating immune-related genomic signatures with clinicopathologic factors may yield a predictive accuracy exceeding that of the currently available system.

METHODS

Ten signatures that reflect specific immunogenic or immune microenvironmental features of TNBC were identified and re-analyzed using bioinformatic methods. Then, clinically annotated TNBC (n = 711) with the corresponding expression profiles, which predicted a patient's probability of disease-free survival (DFS) and overall survival (OS), was pooled to evaluate their prognostic values and establish a clinicopathologic-genomic nomogram. Three and two immune features were, respectively, selected out of 10 immune features to construct nomogram for DFS and OS prediction based on multivariate backward stepwise Cox regression analyses.

RESULTS

By integrating the above immune expression signatures with prognostic clinicopathologic features, clinicopathologic-genomic nomograms were cautiously constructed, which showed reasonable prediction accuracies (DFS: HR, 1.79; 95% CI, 1.46-2.18, P < 0.001; AUC, 0.71; OS: HR, 1.96; 95% CI, 1.54-2.49; P < 0.001; AUC, 0.73). The nomogram showed low-risk subgroup had higher immune checkpoint molecules (PD-L1, PD-1, CTLA-4, LAG-3) expression and benefited from radiotherapy (HR, 0.2, 95% CI, 0.05-0.89; P = 0.034) rather than chemotherapy (HR, 1.26, 95% CI, 0.66-2.43; P = 0.485).

CONCLUSIONS

These findings offer evidence that immune-related genomic data provide independent and complementary prognostic information for TNBC, and the nomogram might be a practical predictive tool to identify TNBC patients who would benefit from chemotherapy, radiotherapy, and upcoming popularity of immunotherapy.

摘要

目的

越来越多的证据表明,三阴性乳腺癌(TNBC)比其他乳腺癌亚型能激发更强的免疫反应。我们假设,将免疫相关的基因组特征与临床病理因素相结合,可能会产生超过现有系统的预测准确性。

方法

采用生物信息学方法鉴定并重新分析了 10 个反映 TNBC 特定免疫原性或免疫微环境特征的特征。然后,我们将具有相应表达谱的临床注释 TNBC(n=711)汇集在一起进行评估,这些表达谱可预测患者无病生存(DFS)和总生存(OS)的概率,并建立临床病理-基因组列线图。基于多变量向后逐步 Cox 回归分析,从 10 个免疫特征中分别选择 3 个和 2 个免疫特征,构建用于 DFS 和 OS 预测的列线图。

结果

通过将上述免疫表达特征与预后临床病理特征相结合,我们谨慎构建了临床病理-基因组列线图,这些列线图显示了合理的预测准确性(DFS:HR,1.79;95%CI,1.46-2.18,P<0.001;AUC,0.71;OS:HR,1.96;95%CI,1.54-2.49;P<0.001;AUC,0.73)。列线图显示低风险亚组具有更高的免疫检查点分子(PD-L1、PD-1、CTLA-4、LAG-3)表达,并受益于放疗(HR,0.2,95%CI,0.05-0.89;P=0.034)而非化疗(HR,1.26,95%CI,0.66-2.43;P=0.485)。

结论

这些发现为免疫相关基因组数据为 TNBC 提供独立和补充的预后信息提供了证据,并且该列线图可能是一种实用的预测工具,可识别从化疗、放疗和即将普及的免疫治疗中获益的 TNBC 患者。

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