Identification of a biomarker panel for colorectal cancer diagnosis.
Identification of a biomarker panel for colorectal cancer diagnosis.
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DOI：
10.1186/1471-2407-12-43
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发表时间：
2012-01-26
期刊：
影响因子：
3.8
通讯作者：
Betanzos M
中科院分区：
文献类型：
--
作者：
García-Bilbao A;Armañanzas R;Ispizua Z;Calvo B;Alonso-Varona A;Inza I;Larrañaga P;López-Vivanco G;Suárez-Merino B;Betanzos M
在西方世界，大肠癌是第二大癌症死亡原因。尽管在过去的几十年中取得了进展，但结直肠癌仍然是西方国家最常见和最致命的肿瘤之一。人类结直肠癌的基因组研究已经在总共31个肿瘤样品（对应于疾病的不同阶段）和33个非肿瘤样品上进行。该研究通过使用Agilent Human 1A 60-mer oligo微阵列将肿瘤样品与非肿瘤样品的参考池杂交来进行。通过qRT-PCR验证所得结果。在随后的生物信息学分析中，通过贝叶斯分类器、变量选择和自举回归建立了基因网络。所有归纳模型的一致性产生了一个依赖关系的层次结构，从而也产生了变量的层次结构。经过一个详尽的预处理过程，以确保数据质量-损失值填补，探针质量，数据平滑和组内变异性过滤-最终数据集包括总共8104个探针。接下来，进行监督分类方法和数据分析以获得最相关的基因。其中两种直接参与癌症进展，特别是结肠直肠癌。最后，一个监督分类器被诱导来分类新的看不见的样本。我们已经开发了一种基于生物标志物面板的结直肠癌诊断的试验模型。我们的结果表明，本文所述的基因谱可以使用不同的监督分类器（AUC值在0.997和0.955的范围内）以94.45%的准确度区分非癌性和癌性样品。
Malignancies arising in the large bowel cause the second largest number of deaths from cancer in the Western World. Despite progresses made during the last decades, colorectal cancer remains one of the most frequent and deadly neoplasias in the western countries. A genomic study of human colorectal cancer has been carried out on a total of 31 tumoral samples, corresponding to different stages of the disease, and 33 non-tumoral samples. The study was carried out by hybridisation of the tumour samples against a reference pool of non-tumoral samples using Agilent Human 1A 60-mer oligo microarrays. The results obtained were validated by qRT-PCR. In the subsequent bioinformatics analysis, gene networks by means of Bayesian classifiers, variable selection and bootstrap resampling were built. The consensus among all the induced models produced a hierarchy of dependences and, thus, of variables. After an exhaustive process of pre-processing to ensure data quality--lost values imputation, probes quality, data smoothing and intraclass variability filtering--the final dataset comprised a total of 8, 104 probes. Next, a supervised classification approach and data analysis was carried out to obtain the most relevant genes. Two of them are directly involved in cancer progression and in particular in colorectal cancer. Finally, a supervised classifier was induced to classify new unseen samples. We have developed a tentative model for the diagnosis of colorectal cancer based on a biomarker panel. Our results indicate that the gene profile described herein can discriminate between non-cancerous and cancerous samples with 94.45% accuracy using different supervised classifiers (AUC values in the range of 0.997 and 0.955).
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影响因子：
4
作者：
De Roock, Wendy;Biesmans, Bart;Tejpar, Sabine
通讯作者：
Tejpar, Sabine
DOI：
10.1083/jcb.141.3.553
发表时间：
1998-05-04
期刊：
The Journal of cell biology
影响因子：
--
作者：
Kim TA;Lim J;Ota S;Raja S;Rogers R;Rivnay B;Avraham H;Avraham S
通讯作者：
Avraham S
影响因子：
6.1
作者：
Armananzas, Ruben;Inza, Inaki;Larranaga, Pedro
通讯作者：
Larranaga, Pedro
DOI：
10.1093/bioinformatics/btp191
发表时间：
2009-06-15
期刊：
Bioinformatics (Oxford, England)
影响因子：
--
作者：
Abeel T;Van de Peer Y;Saeys Y
通讯作者：
Saeys Y
影响因子：
5.3
作者：
Dai, MS;Zeng, SX;Lu, H
通讯作者：
Lu, H