A clinically applicable molecular-based classification for endometrial cancers.
A clinically applicable molecular-based classification for endometrial cancers.
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DOI：
10.1038/bjc.2015.190
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发表时间：
2015-07-14
影响因子：
8.8
通讯作者：
McAlpine JN
中科院分区：
文献类型：
--
作者：
Talhouk A;McConechy MK;Leung S;Li-Chang HH;Kwon JS;Melnyk N;Yang W;Senz J;Boyd N;Karnezis AN;Huntsman DG;Gilks CB;McAlpine JN
子宫内膜癌(ECs)的形态特征分类不一致，提供的预后和预测信息有限。提出了一种基于癌症基因组图谱中识别的分子类别的新的分类系统。来自癌症基因组图谱(TCGA)的基因组数据支持将子宫内膜癌分为四个具有预后意义的亚组；我们使用TCGA数据集开发了替代分析，可以复制TCGA分类，但不需要劳动密集型和成本高昂的基因组方法学。在152例子宫内膜癌患者的新的独立队列中，进行了最相关分析的组合并进行了测试，并比较了分子和临床危险组分层。使用多种不同的分子分类模型(共测试16个)，获得具有统计学意义的TCGA生存曲线的重复性。内部验证支持基于以下组件的分类器：错配修复蛋白免疫组织化学、极点突变分析和P53免疫组织化学作为‘拷贝数’状态的替代。所建议的分子分类器与临床结果相关，如分期、分级、淋巴-血管间隙侵犯、淋巴结侵犯和辅助治疗。在多变量分析中，分子分类和临床风险组都与预后相关，但在每种类型的病例构成上有很大差异，一半的极点和错配修复丢失亚组位于临床定义的高危组中。将分子分类器与临床病理特征或危险组相结合，可提供最高的C指数来区分预后生存曲线。在福尔马林固定的石蜡包埋样本上，可以使用临床适用的方法对内皮细胞进行分子分类，并提供超过既定危险因素的独立预后信息。这种实用的分子分类工具有可能被常规用于指导子宫内膜癌患者的治疗，并在未来的临床试验中对病例进行分层。
Classification of endometrial carcinomas (ECs) by morphologic features is inconsistent, and yields limited prognostic and predictive information. A new system for classification based on the molecular categories identified in The Cancer Genome Atlas is proposed. Genomic data from the Cancer Genome Atlas (TCGA) support classification of endometrial carcinomas into four prognostically significant subgroups; we used the TCGA data set to develop surrogate assays that could replicate the TCGA classification, but without the need for the labor-intensive and cost-prohibitive genomic methodology. Combinations of the most relevant assays were carried forward and tested on a new independent cohort of 152 endometrial carcinoma cases, and molecular vs clinical risk group stratification was compared. Replication of TCGA survival curves was achieved with statistical significance using multiple different molecular classification models (16 total tested). Internal validation supported carrying forward a classifier based on the following components: mismatch repair protein immunohistochemistry, POLE mutational analysis and p53 immunohistochemistry as a surrogate for ‘copy-number' status. The proposed molecular classifier was associated with clinical outcomes, as was stage, grade, lymph-vascular space invasion, nodal involvement and adjuvant treatment. In multivariable analysis both molecular classification and clinical risk groups were associated with outcomes, but differed greatly in composition of cases within each category, with half of POLE and mismatch repair loss subgroups residing within the clinically defined ‘high-risk' group. Combining the molecular classifier with clinicopathologic features or risk groups provided the highest C-index for discrimination of outcome survival curves. Molecular classification of ECs can be achieved using clinically applicable methods on formalin-fixed paraffin-embedded samples, and provides independent prognostic information beyond established risk factors. This pragmatic molecular classification tool has potential to be used routinely in guiding treatment for individuals with endometrial carcinoma and in stratifying cases in future clinical trials.