Gene expression profile of papillary thyroid cancer: Sources of variability and diagnostic implications
Gene expression profile of papillary thyroid cancer: Sources of variability and diagnostic implications
复制标题
DOI：
10.1158/0008-5472.can-04-3078
复制
发表时间：
2005-02-15
期刊：
影响因子：
11.2
通讯作者：
Swierniak, A
中科院分区：
文献类型：
--
作者：
Jarzab, B;Wiench, M;Swierniak, A
该研究寻找了区分乳头状甲状腺癌（PTC）和正常甲状腺组织的最佳基因组，并评估了基因表达谱变异的来源。通过寡核苷酸微阵列（GeneChip HG-U133 A）对33例患者（23例PTC患者和10例其他甲状腺疾病患者）术中采集的50份组织样本进行分析。在初始组的16 PTC和16个正常样本，我们评估的来源的变异基因表达谱的奇异值分解，指定三个主要模式的变异。第一个和最明显的模式将转录物分组，区分肿瘤和正常组织。两个连续的模式包含了很大比例的免疫相关基因。为了生成肿瘤-正常差异的多基因分类器，我们使用基于支持向量机的技术（递归特征替换）。它包括以下19个基因：DPP 4、GJB 3、ST 14、SERPINA 1、LKP 4、MET、EVA 1、SPUVE、LGALS 3、HBB、MKRN 2、MRC 2、IGSF 1、KIAA 0830、RXRG、P4 HA 2、CDH 3、IL 13 RA 1和MTMR 4，并正确区分了18个额外PTC/正常甲状腺样本中的17个和先前微阵列研究中发表的所有16个样本。通过Q-PCR确认所选择的新基因（LKP 4、EVA 1、TKPRSS 4、QPCT和SLC 34 A2）。我们的研究结果证明，PTC的基因表达信号是很容易检测，即使癌细胞不占优势的肿瘤间质。我们指出并分离与免疫应答相关的混杂变异性。最后，我们提出了一个有效的分子分类器，能够区分PTC和非恶性甲状腺在90%以上的调查样本。
The study looked for an optimal set of genes differentiating between papillary thyroid cancer (PTC) and normal thyroid tissue and assessed the sources of variability in gene expression profiles. The analysis was done by oligonucleotide microarrays (GeneChip HG-U133A) in 50 tissue samples taken intraoperatively from 33 patients (23 PTC patients and 10 patients with other thyroid disease). In the initial group of 16 PTC and 16 normal samples, we assessed the sources of variability in the gene expression profile by singular value decomposition which specified three major patterns of variability. The first and the most distinct mode grouped transcripts differentiating between tumor and normal tissues. Two consecutive modes contained a large proportion of immunity-related genes. To generate a multigene classifier for tumor-normal difference, we used support vector machines-based technique (recursive feature replacement). It included the following 19 genes: DPP4, GJB3, ST14, SERPINA1, LKP4, MET, EVA1, SPUVE, LGALS3, HBB, MKRN2, MRC2, IGSF1, KIAA0830, RXRG, P4HA2, CDH3, IL13RA1, and MTMR4, and correctly discriminated 17 of 18 additional PTC/normal thyroid samples and all 16 samples published in a previous microarray study. Selected novel genes (LKP4, EVA1, TKPRSS4, QPCT, and SLC34A2) were confirmed by Q-PCR. Our results prove that the gene expression signal of PTC is easily detectable even when cancer cells do not prevail over tumor stroma. We indicate and separate the confounding variability related to the immune response. Finally, we propose a potent molecular classifier able to discriminate between PTC and nonmalignant thyroid in more than 90% of investigated samples.