Transcriptomic Profiles Differentiate Normal Rectal Epithelium and Adenocarcinoma
Transcriptomic Profiles Differentiate Normal Rectal Epithelium and Adenocarcinoma
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DOI：
10.9738/intsurg-d-14-00272.1
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发表时间：
2015-05-01
影响因子：
0.1
通讯作者：
Kalady, M. F.
中科院分区：
文献类型：
--
作者：
Hogan, J.;Dejulius, K.;Kalady, M. F.
腺癌是一种基于主观发现的组织学诊断。转录谱已被用于区分正常组织与疾病，并可提供一种鉴定恶性肿瘤的方法。本研究的目的是生成和测试区分正常和腺癌直肠的转录组学谱。比较了正常上皮和直肠腺癌的cDNA微阵列。根据标准偏差过滤结果以仅保留高度失调的基因。进一步分析两组t检验（P < 0.05，Bonferroni P值调整）中癌组织与正常组织差异表达的基因。基因按下降倍数变化进行排序。对于每次比较（肿瘤与正常上皮），将具有最大正倍数变化的那5个基因分组在分类器中。五个独立的测试，以评估每个分类器的区分能力。遗传分类器比较正常上皮细胞与恶性直肠上皮细胞从汇总阶段的平均敏感性和特异性分别为99.6%和98.2%。通过比较正常和I期癌症得到的分类器具有可比的平均灵敏度和特异性（分别为97%和98%）。每个分类器的受试者-操作者特征曲线下的面积分别为0.981和0.972。有一个基因是两种分类器共有的。在独立的基因表达Omnibus衍生数据集中测试分类器。这两个分类器都保留了它们的预测特性。包括少至5个基因的转录组学谱在区分正常直肠上皮与腺癌直肠上皮（包括早期疾病）方面是高度准确的。
Adenocarcinoma is a histologic diagnosis based on subjective findings. Transcriptional profiles have been used to differentiate normal tissue from disease and could provide a means of identifying malignancy. The goal of this study was to generate and test transcriptomic profiles that differentiate normal from adenocarcinomatous rectum. Comparisons were made between cDNA microarrays derived from normal epithelium and rectal adenocarcinoma. Results were filtered according to standard deviation to retain only highly dysregulated genes. Genes differentially expressed between cancer and normal tissue on two-groups t test (P < 0.05, Bonferroni P value adjustment) were further analyzed. Genes were rank ordered in terms of descending fold change. For each comparison (tumor versus normal epithelium), those 5 genes with the greatest positive fold change were grouped in a classifier. Five separate tests were applied to evaluate the discriminatory capacity of each classifier. Genetic classifiers derived comparing normal epithelium with malignant rectal epithelium from pooled stages had a mean sensitivity and specificity of 99.6% and 98.2%, respectively. The classifiers derived from comparing normal and stage I cancer had comparable mean sensitivities and specificities (97% and 98%, respectively). Areas under the summary receiver-operator characteristic curves for each classifier were 0.981 and 0.972, respectively. One gene was common to both classifiers. Classifiers were tested in an independent Gene Expression Omnibus-derived dataset. Both classifiers retained their predictive properties. Transcriptomic profiles comprising as few as 5 genes are highly accurate in differentiating normal from adenocarcinomatous rectal epithelium, including early-stage disease.