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Cross-platform Data Analysis Reveals a Generic Gene Expression Signature for Microsatellite Instability in Colorectal Cancer

机译:跨平台数据分析揭示了大肠癌微卫星不稳定性的通用基因表达特征

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摘要

The dysfunction of the DNA mismatch repair system results in microsatellite instability (MSI). MSI plays a central role in the development of multiple human cancers. In colon cancer, despite being associated with resistance to 5-fluorouracil treatment, MSI is a favourable prognostic marker. In gastric and endometrial cancers, its prognostic value is not so well established. Nevertheless, recognising the MSI tumours may be important for predicting the therapeutic effect of immune checkpoint inhibitors. Several gene expression signatures were trained on microarray data sets to understand the regulatory mechanisms underlying microsatellite instability in colorectal cancer. A wealth of expression data already exists in the form of microarray data sets. However, the RNA-seq has become a routine for transcriptome analysis. A new MSI gene expression signature presented here is the first to be valid across two different platforms, microarrays and RNA-seq. In the case of colon cancer, its estimated performance was (i) AUC = 0.94, 95% CI = (0.90 – 0.97) on RNA-seq and (ii) AUC = 0.95, 95% CI = (0.92 – 0.97) on microarray. The 25-gene expression signature was also validated in two independent microarray colon cancer data sets. Despite being derived from colorectal cancer, the signature maintained good performance on RNA-seq and microarray gastric cancer data sets (AUC = 0.90, 95% CI = (0.85 – 0.94) and AUC = 0.83, 95% CI = (0.69 – 0.97), respectively). Furthermore, this classifier retained high concordance even when classifying RNA-seq endometrial cancers (AUC = 0.71, 95% CI = (0.62 – 0.81). These results indicate that the new signature was able to remove the platform-specific differences while preserving the underlying biological differences between MSI/MSS phenotypes in colon cancer samples.
机译:DNA错配修复系统的功能异常会导致微卫星不稳定性(MSI)。 MSI在多种人类癌症的发展中起着核心作用。在结肠癌中,尽管与5-氟尿嘧啶治疗耐药相关,但MSI是一个良好的预后指标。在胃癌和子宫内膜癌中,其预后价值还不十分理想。然而,识别MSI肿瘤对于预测免疫检查点抑制剂的治疗效果可能很重要。在微阵列数据集上训练了几个基因表达特征,以了解大肠癌中微卫星不稳定性的调控机制。大量的表达数据已经以微阵列数据集的形式存在。然而,RNA-seq已成为转录组分析的常规方法。此处介绍的新MSI基因表达签名是第一个在两种不同平台(微阵列和RNA序列)上均有效的签名。对于结肠癌,其估计性能为(i)RNA-seq的AUC = 0.94,95%CI =(0.90 – 0.97)和(ii)微阵列的AUC = 0.95,95%CI =(0.92 – 0.97) 。在两个独立的微阵列结肠癌数据集中也验证了25基因表达特征。尽管来自结肠直肠癌,但该签名在RNA-seq和微阵列胃癌数据集上仍保持良好的性能(AUC = 0.90,95%CI =(0.85 – 0.94)和AUC = 0.83,95%CI =(0.69 – 0.97) , 分别)。此外,即使对RNA-seq子宫内膜癌进行分类(AUC = 0.71,95%CI =(0.62 – 0.81)),该分类器仍保持高度一致性,这些结果表明,新签名能够消除平台特异性差异,同时保留基础结肠癌样本中MSI / MSS表型之间的生物学差异。

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