Integrative genomic data mining for discovery of potential blood-borne biomarkers for early diagnosis of cancer.
Integrative genomic data mining for discovery of potential blood-borne biomarkers for early diagnosis of cancer.
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综合基因组数据挖掘，发现潜在的血源性生物标志物，用于癌症的早期诊断。
DOI：
10.1371/journal.pone.0003661
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发表时间：
2008
期刊：
影响因子：
3.7
通讯作者：
Kassis, Amin I.
中科院分区：
文献类型：
--
作者：
Yang, Yongliang;Iyer, Lakshmanan K.;Adelstein, S. James;Kassis, Amin I.
随着后基因组时代的到来，人们对发现用于癌症的准确诊断、预后和早期检测的生物标志物越来越感兴趣。血液传播的癌症标志物受到临床医生的青睐，因为血液样本可以相对容易地获得和分析。我们使用基于集成癌症微阵列平台Oncomine和独创性路径分析（IPA）计划的生物标志物模块的组合挖掘策略来识别六种常见人类癌症类型的潜在血液标志物。在Oncomine平台中，通过Gene Ontology关键词过滤癌组织中相对于其相应正常组织过表达的基因，规定细胞外环境并实施校正的Q值（错误发现率）截止值。将鉴定的基因导入IPA生物标志物模块，以分离出编码推定的分泌或细胞表面蛋白的那些基因作为血液传播（血液/血清/血浆）癌症标志物。根据标准化的绝对Student t值对过滤后的潜在指标进行排序和优先级排序。检索到的许多标记基因已经在临床上有用或正在积极调查证实了我们的挖掘策略的有效性。为了鉴定每种癌症类型独特的生物标志物，还通过IPA生物标志物比较功能分析了六种人类肿瘤中每两种肿瘤类型之间共同的上调标志物基因。在六种癌症类型中共享的上调标志物基因可以作为补充组织病理学检查的分子工具，并且通常上调的和独特的生物标志物的组合可以作为特定癌症的区分标志物。随着“组学”时代大量微阵列数据的持续增长，这种方法将越来越有助于发现诊断特征。
With the arrival of the postgenomic era, there is increasing interest in the discovery of biomarkers for the accurate diagnosis, prognosis, and early detection of cancer. Blood-borne cancer markers are favored by clinicians, because blood samples can be obtained and analyzed with relative ease. We have used a combined mining strategy based on an integrated cancer microarray platform, Oncomine, and the biomarker module of the Ingenuity Pathways Analysis (IPA) program to identify potential blood-based markers for six common human cancer types. In the Oncomine platform, the genes overexpressed in cancer tissues relative to their corresponding normal tissues were filtered by Gene Ontology keywords, with the extracellular environment stipulated and a corrected Q value (false discovery rate) cut-off implemented. The identified genes were imported to the IPA biomarker module to separate out those genes encoding putative secreted or cell-surface proteins as blood-borne (blood/serum/plasma) cancer markers. The filtered potential indicators were ranked and prioritized according to normalized absolute Student t values. The retrieval of numerous marker genes that are already clinically useful or under active investigation confirmed the effectiveness of our mining strategy. To identify the biomarkers that are unique for each cancer type, the upregulated marker genes that are in common between each two tumor types across the six human tumors were also analyzed by the IPA biomarker comparison function. The upregulated marker genes shared among the six cancer types may serve as a molecular tool to complement histopathologic examination, and the combination of the commonly upregulated and unique biomarkers may serve as differentiating markers for a specific cancer. This approach will be increasingly useful to discover diagnostic signatures as the mass of microarray data continues to grow in the ‘omics’ era.
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癌组学对癌症生物标志物发现的贡献。
影响因子：
37.3
作者：
Cho, William C S
通讯作者：
Cho, William C S
影响因子：
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作者：
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影响因子：
11.2
作者：
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通讯作者：
Langdon, SP
影响因子：
3
作者：
Campagne F;Skrabanek L
通讯作者：
Skrabanek L