Methylation-Based Signatures for Gastroesophageal Tumor Classification
Methylation-Based Signatures for Gastroesophageal Tumor Classification
复制标题
DOI：
10.3390/cancers12051208
复制
发表时间：
2020-05-01
期刊：
影响因子：
5.2
通讯作者：
Wang, Edwin
中科院分区：
文献类型：
--
作者：
Alabi, Nikolay;Sheka, Dropen;Wang, Edwin
肿瘤学领域对于胃食管结合部（GEJ）肿瘤存在争议，过去，它们被分类为胃癌、食管癌或两者的组合。 GEJ 肿瘤的错误分类最终会影响治疗选择，如果针对错误的癌症属性进行治疗，治疗可能会变得无效。有人认为错误分类率高达 45%，高于报道的交界癌发生率。在这里，我们的目标是利用 GEJ 肿瘤的甲基化谱来改进 GEJ 肿瘤的分类。从基因表达综合数据库和癌症基因组图谱中收集了四组 DNA 甲基化谱，每个样本包含大约 27,000 (27k) 个甲基化位点。肿瘤样本被分配到发现组（n(EC) = 185，n(GC) = 395；EC，食道癌；GC 胃癌）和验证组（n(EC) = 179，n(GC) = 369）组。使用优化的多重生存筛选（MSS）算法来识别能够区分 GEJ 肿瘤的甲基化生物标志物。鉴定出三个甲基化特征：它们与蛋白质结合、基因表达和细胞成分组织细胞过程相关，在验证数据集中实现的精确度和召回率分别为 94.7% 和 99.2%、97.6% 和 96.8%、96.8% 和 97.6%。有趣的是，这些特征的甲基化位点与其下游转录起始位点（TSS）非常接近（即170-270个碱基对），这表明TSS附近的甲基化在肿瘤发生中发挥着更重要的作用。在这里，我们提出了第一组甲基化特征，对于表征胃食管肿瘤具有更高的预测能力。因此，它们可以改善胃食管肿瘤的诊断和治疗。
Contention exists within the field of oncology with regards to gastroesophageal junction (GEJ) tumors, as in the past, they have been classified as gastric cancer, esophageal cancer, or a combination of both. Misclassifications of GEJ tumors ultimately influence treatment options, which may be rendered ineffective if treating for the wrong cancer attributes. It has been suggested that misclassification rates were as high as 45%, which is greater than reported for junctional cancer occurrences. Here, we aimed to use the methylation profiles of GEJ tumors to improve classifications of GEJ tumors. Four cohorts of DNA methylation profiles, containing similar to 27,000 (27k) methylation sites per sample, were collected from the Gene Expression Omnibus and The Cancer Genome Atlas. Tumor samples were assigned into discovery (n(EC) = 185, n(GC) = 395; EC, esophageal cancer; GC gastric cancer) and validation (n(EC) = 179, n(GC) = 369) sets. The optimized Multi-Survival Screening (MSS) algorithm was used to identify methylation biomarkers capable of distinguishing GEJ tumors. Three methylation signatures were identified: They were associated with protein binding, gene expression, and cellular component organization cellular processes, and achieved precision and recall rates of 94.7% and 99.2%, 97.6% and 96.8%, and 96.8% and 97.6%, respectively, in the validation dataset. Interestingly, the methylation sites of the signatures were very close (i.e., 170-270 base pairs) to their downstream transcription start sites (TSSs), suggesting that the methylations near TSSs play much more important roles in tumorigenesis. Here we presented the first set of methylation signatures with a higher predictive power for characterizing gastroesophageal tumors. Thus, they could improve the diagnosis and treatment of gastroesophageal tumors.