Somatic mutations favorable to patient survival are predominant in ovarian carcinomas.
Somatic mutations favorable to patient survival are predominant in ovarian carcinomas.
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DOI：
10.1371/journal.pone.0112561
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发表时间：
2014
期刊：
影响因子：
3.7
通讯作者：
Zhang K
中科院分区：
文献类型：
--
作者：
Zhang W;Edwards A;Flemington E;Zhang K
体细胞突变积累是细胞异常生长的主要原因。然而，癌细胞中的一些突变可能对癌细胞的生存和增殖有害，从而为患者提供保护作用。我们通过对癌症基因组图谱发布的卵巢癌临床和体细胞突变数据集进行独特分析来研究这一假设。我们定义并筛选了 562 个宏突变特征 (MMS)，以确定它们与 320 名卵巢癌患者的总体生存率之间的关系。每个 MMS 测量每个肿瘤中特定基因本体 (GO) 术语涵盖的成员基因（TP53 除外）上存在的突变数量。我们发现，与那些表明临床结果不佳的体细胞突变相比，有利于患者生存的体细胞突变在卵巢癌中占主导地位。特别是，我们确定了 19 (3) 种预测性 MMS，它们通常通过非线性剂量依赖性效应与患者的良好（不良）生存率相关。 19 个“阳性”预测变量的错误发现率为 0.15。与这些MMS对应的GO术语包括“溶酶体膜”和“对缺氧的反应”，每一个都与癌症的进展和治疗相关。使用这些 MMS 作为特征，我们建立了一个分类树模型，该模型可以有效地将训练样本根据生存时间分为三个预后组。我们在同一疾病的独立数据集（对数秩 p 值 <2.3×10-4）和乳腺癌数据集（对数秩 p 值 <9.3×10−3）上验证了该模型。我们比较了这些 MMS 对应的 GO 术语和那些富含基于表达的预测基因的 GO 术语。分析表明，具有较大相似性的GO术语对主要与位于细胞器上负责物质运输和废物处理的蛋白质有关，表明这些蛋白质在癌症死亡率中发挥着至关重要的作用。
Somatic mutation accumulation is a major cause of abnormal cell growth. However, some mutations in cancer cells may be deleterious to the survival and proliferation of the cancer cells, thus offering a protective effect to the patients. We investigated this hypothesis via a unique analysis of the clinical and somatic mutation datasets of ovarian carcinomas published by the Cancer Genome Atlas. We defined and screened 562 macro mutation signatures (MMSs) for their associations with the overall survival of 320 ovarian cancer patients. Each MMS measures the number of mutations present on the member genes (except for TP53) covered by a specific Gene Ontology (GO) term in each tumor. We found that somatic mutations favorable to the patient survival are predominant in ovarian carcinomas compared to those indicating poor clinical outcomes. Specially, we identified 19 (3) predictive MMSs that are, usually by a nonlinear dose-dependent effect, associated with good (poor) patient survival. The false discovery rate for the 19 “positive” predictors is at the level of 0.15. The GO terms corresponding to these MMSs include “lysosomal membrane” and “response to hypoxia”, each of which is relevant to the progression and therapy of cancer. Using these MMSs as features, we established a classification tree model which can effectively partition the training samples into three prognosis groups regarding the survival time. We validated this model on an independent dataset of the same disease (Log-rank p-value <2.3×10-4) and a dataset of breast cancer (Log-rank p-value <9.3×10−3). We compared the GO terms corresponding to these MMSs and those enriched with expression-based predictive genes. The analysis showed that the GO term pairs with large similarity are mainly pertinent to the proteins located on the cell organelles responsible for material transport and waste disposal, suggesting the crucial role of these proteins in cancer mortality.
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分子对肿瘤细胞缺氧的反应。
影响因子：
37.3
作者：
Kunz, Manfred;Ibrahim, Saleh M
通讯作者：
Ibrahim, Saleh M
DOI：
10.1038/nrc2644
发表时间：
2009-06
期刊：
Nature reviews. Cancer
影响因子：
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DOI：
10.1038/nrc1299
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2004-03
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Nature reviews. Cancer
影响因子：
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DOI：
10.1073/pnas.0408592102
发表时间：
2005-01-04
影响因子：
11.1
作者：
Erdal, H;Berndtsson, M;Linder, S
通讯作者：
Linder, S
DOI：
10.1155/2012/283181
发表时间：
2012
期刊：
Chemotherapy research and practice
影响因子：
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作者：
Aoudjit F;Vuori K
通讯作者：
Vuori K