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[结肠癌中的基因表达谱分析]

[Gene expression profiling in colon cancer].

作者信息

Barrier Alain, Boelle Pierre-Yves, Lemoine Antoinette, Flahault Antoine, Dudoit Sandrine, Huguier Michel

机构信息

Service de chirurgie digestive, hôpital Tenon, Paris.

出版信息

Bull Acad Natl Med. 2007 Jun;191(6):1091-101; discussion 1102-3.

Abstract

Identification of new prognostic factors for colon cancer with no lymph node involvement may improve the selection of patients for adjuvant chemotherapy. The aim of this study was to assess the possibility of using gene expression profiling for this purpose. Fifty patients operated on for stage II colon cancer were included. Twenty-five of these patients relapsed, while the other 25 remained disease-free for at least 5 years. MRNA was extracted from fresh-frozen biopsies and hybridized to the Affymetrix GeneChip HGU133A. One thousand six hundred random splits of the 50 patients into a training set and a validation set were considered. For each split, a prognostic combination was derived from the training set (selection of the 30 genes most differentially expressed between patients who recurred and those who did not, by linear discriminant analysis), and its prognostic performance was assessed with the validation set. On average, accuracy was 76%, sensitivity 85%, and specificity 68%. A total of 6,124 genes were included in at least one of the 1,600 predictive combinations, and 55 genes were included in more than 100 combinations. This study supports the possibility of predicting the prognosis of non-metastatic colon cancer by tumor gene expression profiling. It also shows the highly variable gene composition of predictive combinations.

摘要

识别无淋巴结转移的结肠癌新预后因素可能会改善辅助化疗患者的选择。本研究的目的是评估为此目的使用基因表达谱分析的可能性。纳入了50例接受II期结肠癌手术的患者。其中25例患者复发,而其他25例患者至少5年无病生存。从新鲜冷冻活检组织中提取mRNA,并与Affymetrix GeneChip HGU133A芯片杂交。将50例患者随机分为训练集和验证集,共进行了1600次划分。对于每次划分,从训练集得出一个预后组合(通过线性判别分析选择复发患者和未复发患者之间差异表达最显著的30个基因),并用验证集评估其预后性能。平均而言,准确率为76%,敏感性为85%,特异性为68%。在1600个预测组合中,至少有一个组合包含6124个基因,超过100个组合包含55个基因。本研究支持通过肿瘤基因表达谱分析预测非转移性结肠癌预后的可能性。它还显示了预测组合中基因组成的高度变异性。

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