BACKGROUND Molecular characterization of individual cancer patients is important because cancer is a complex and heterogeneous disease with many possible genetic and environmental causes. Many studies have been conducted to identify diagnostic or prognostic gene signatures for cancer from gene expression profiles. However, some gene signatures may fail to serve as diagnostic or prognostic biomarkers and gene signatures may not be found in gene expression profiles. METHODS In this study, we developed a general method for constructing patient-specific gene correlation networks and for identifying prognostic gene pairs from the networks. A patient-specific gene correlation network was constructed by comparing a reference gene correlation network from normal samples to a network perturbed by a single patient sample. The main difference of our method from previous ones includes (1) it is focused on finding prognostic gene pairs rather than prognostic genes and (2) it can identify prognostic gene pairs from gene expression profiles even when no significant prognostic genes exist. RESULTS Evaluation of our method with extensive data sets of three cancer types (breast invasive carcinoma, colon adenocarcinoma, and lung adenocarcinoma) showed that our approach is general and that gene pairs can serve as more reliable prognostic signatures for cancer than genes. CONCLUSIONS Our study revealed that prognosis of individual cancer patients is associated with the existence of prognostic gene pairs in the patient-specific network and the size of a subnetwork of the prognostic gene pairs in the patient-specific network. Although preliminary, our approach will be useful for finding gene pairs to predict survival time of patients and to tailor treatments to individual characteristics. The program for dynamically constructing patient-specific gene networks and for finding prognostic gene pairs is available at http://bclab.inha.ac.kr/pancancer.

中文翻译：

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从患者特异性基因网络中寻找癌症的预后基因对。

背景技术个体癌症患者的分子表征是重要的，因为癌症是具有许多可能的遗传和环境原因的复杂且异质的疾病。已经进行了许多研究以从基因表达谱中鉴定癌症的诊断或预后基因标志。但是，某些基因签名可能无法用作诊断或预后生物标记，并且在基因表达谱中可能找不到基因签名。方法在这项研究中，我们开发了一种构建患者特异性基因相关网络并从网络中鉴定预后基因对的通用方法。通过将正常样本的参考基因相关网络与单个患者样本干扰的网络进行比较，构建了患者特异性基因相关网络。我们的方法与以前的方法的主要区别包括：（1）侧重于查找预后基因对而不是预后基因；（2）即使没有明显的预后基因，也可以从基因表达谱中识别预后基因对。结果使用三种癌症类型（乳腺癌，结肠腺癌和肺腺癌）的广泛数据集对我们的方法进行评估，结果表明我们的方法是通用的，基因对可以比基因更可靠地预测癌症。结论我们的研究表明，个别癌症患者的预后与患者特异性网络中预后基因对的存在以及患者特异性网络中预后基因对子网络的大小有关。虽然是初步的，我们的方法将有助于发现基因对以预测患者的生存时间并根据个体特征调整治疗方案。动态构建患者特定基因网络和查找预后基因对的程序可从http://bclab.inha.ac.kr/pancancer获得。