A signature-based method for indexing cell cycle phase distribution from microarray profiles.
A signature-based method for indexing cell cycle phase distribution from microarray profiles.
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DOI：
10.1186/1471-2164-10-137
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发表时间：
2009-03-30
期刊：
影响因子：
4.4
通讯作者：
Kitada K
中科院分区：
文献类型：
--
作者：
Mizuno H;Nakanishi Y;Ishii N;Sarai A;Kitada K
细胞周期机制解释致癌信号并反映癌症的生物学。到目前为止，细胞周期时相估计的各种方法，如有丝分裂指数、S时相比例和免疫组织化学方法，都提供了关于癌症的有价值的信息(如增殖率)。然而，这些方法依赖于一次或几次测量，信息的范围有限。需要更系统的细胞周期分析方法。我们开发了一种基于签名的方法，在考虑细胞周期和非周期细胞的情况下，从微阵列轮廓中索引细胞周期时相分布。创建了一个细胞周期特征主集，由在周期细胞中优先表达的基因组成，并以细胞周期调节的方式组成，以索引样本中周期细胞的比例。还创建了细胞周期特征子集，由其表达在细胞周期特定阶段达到峰值的基因组成，以索引相应阶段的细胞比例。使用细胞周期数据集和静止诱导的细胞数据集对该方法进行了验证。对小鼠肿瘤模型数据集和人类乳腺癌数据集的分析表明，周期细胞的比例存在差异。当考虑到非周期细胞的影响时，在小鼠肿瘤模型数据集中描绘了“埋藏”的细胞周期时相分布，这些分布在小鼠肿瘤模型数据集中是致癌事件特异性的，并且在人类乳腺癌数据集中与患者预后相关。这份报告中提出的基于签名的细胞周期分析方法，将对癌症的表征和诊断具有潜在的价值。
The cell cycle machinery interprets oncogenic signals and reflects the biology of cancers. To date, various methods for cell cycle phase estimation such as mitotic index, S phase fraction, and immunohistochemistry have provided valuable information on cancers (e.g. proliferation rate). However, those methods rely on one or few measurements and the scope of the information is limited. There is a need for more systematic cell cycle analysis methods. We developed a signature-based method for indexing cell cycle phase distribution from microarray profiles under consideration of cycling and non-cycling cells. A cell cycle signature masterset, composed of genes which express preferentially in cycling cells and in a cell cycle-regulated manner, was created to index the proportion of cycling cells in the sample. Cell cycle signature subsets, composed of genes whose expressions peak at specific stages of the cell cycle, were also created to index the proportion of cells in the corresponding stages. The method was validated using cell cycle datasets and quiescence-induced cell datasets. Analyses of a mouse tumor model dataset and human breast cancer datasets revealed variations in the proportion of cycling cells. When the influence of non-cycling cells was taken into account, "buried" cell cycle phase distributions were depicted that were oncogenic-event specific in the mouse tumor model dataset and were associated with patients' prognosis in the human breast cancer datasets. The signature-based cell cycle analysis method presented in this report, would potentially be of value for cancer characterization and diagnostics.
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影响因子：
8.8
作者：
通讯作者：
--
影响因子：
12.3
作者：
Herschkowitz JI;Simin K;Weigman VJ;Mikaelian I;Usary J;Hu Z;Rasmussen KE;Jones LP;Assefnia S;Chandrasekharan S;Backlund MG;Yin Y;Khramtsov AI;Bastein R;Quackenbush J;Glazer RI;Brown PH;Green JE;Kopelovich L;Furth PA;Palazzo JP;Olopade OI;Bernard PS;Churchill GA;Van Dyke T;Perou CM
通讯作者：
Perou CM
影响因子：
3.8
作者：
Barnes, DM;Gillett, CE
通讯作者：
Gillett, CE
影响因子：
7.3
作者：
Gonzalez, MA;Tachibana, KK;Coleman, N
通讯作者：
Coleman, N
DOI：
10.1186/bcr1675
发表时间：
2007
期刊：
Breast cancer research : BCR
影响因子：
--
作者：
Langerød A;Zhao H;Borgan Ø;Nesland JM;Bukholm IR;Ikdahl T;Kåresen R;Børresen-Dale AL;Jeffrey SS
通讯作者：
Jeffrey SS