A Systems Biology Comparison of Ovarian Cancers Implicates Putative Somatic Driver Mutations through Protein-Protein Interaction Models.
A Systems Biology Comparison of Ovarian Cancers Implicates Putative Somatic Driver Mutations through Protein-Protein Interaction Models.
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DOI：
10.1371/journal.pone.0163353
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发表时间：
2016
期刊：
影响因子：
3.7
通讯作者：
Elnitski L
中科院分区：
文献类型：
--
作者：
Yang MQ;Elnitski L
卵巢癌可能具有高死亡率的侵袭性（例如，高级别浆液性卵巢癌，或 HGSOC），也可能具有良好的长期结果（例如，低恶性潜能，或 LMP，浆液性卵巢癌）。通过比较 LMP 和 HGSOC 肿瘤，我们可以深入了解卵巢癌恶性进展的机制。然而，之前对这两种亚型的研究主要集中在基因表达分析上。在这里，我们应用了系统生物学方法，将源自包含 LMP 和 HGSOC 肿瘤的两个独立数据集的基因表达谱与蛋白质-蛋白质相互作用数据相整合。这两个数据集涉及的基因和相关网络涉及已知和新的疾病机制，并强调了 BRCA1 和 CREBBP 在两种肿瘤类型中的不同作用。此外，体细胞突变数据的结合表明，PAK4 的扩增与 HGSOC 患者的生存率较差有关。因此，蛋白质相互作用网络的扰动证明了恶性和良性卵巢癌之间网络信息传输的差异。这里确定的基于网络的新型分子特征可用于确定新的干预靶标，并改善浸润性卵巢癌的治疗和早期诊断。
Ovarian carcinomas can be aggressive with a high mortality rate (e.g., high-grade serous ovarian carcinomas, or HGSOCs), or indolent with much better long-term outcomes (e.g., low-malignant-potential, or LMP, serous ovarian carcinomas). By comparing LMP and HGSOC tumors, we can gain insight into the mechanisms underlying malignant progression in ovarian cancer. However, previous studies of the two subtypes have been focused on gene expression analysis. Here, we applied a systems biology approach, integrating gene expression profiles derived from two independent data sets containing both LMP and HGSOC tumors with protein-protein interaction data. Genes and related networks implicated by both data sets involved both known and novel disease mechanisms and highlighted the different roles of BRCA1 and CREBBP in the two tumor types. In addition, the incorporation of somatic mutation data revealed that amplification of PAK4 is associated with poor survival in patients with HGSOC. Thus, perturbations in protein interaction networks demonstrate differential trafficking of network information between malignant and benign ovarian cancers. The novel network-based molecular signatures identified here may be used to identify new targets for intervention and to improve the treatment of invasive ovarian cancer as well as early diagnosis.
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影响因子：
7.3
作者：
Ahmed, Ashour Ahmed;Etemadmoghadam, Dariush;Temple, Jillian;Lynch, Andy G.;Riad, Mohamed;Sharma, Raghwa;Stewart, Colin;Fereday, Sian;Caldas, Carlos;DeFazio, Anna;Bowtell, David;Brenton, James D.
通讯作者：
Brenton, James D.
影响因子：
7.3
作者：
Gao J;Aksoy BA;Dogrusoz U;Dresdner G;Gross B;Sumer SO;Sun Y;Jacobsen A;Sinha R;Larsson E;Cerami E;Sander C;Schultz N
通讯作者：
Schultz N
影响因子：
16.6
作者：
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影响因子：
12.3
作者：
Fraser HB;Plotkin JB
通讯作者：
Plotkin JB
影响因子：
3.7
作者：
Cheng JC;Auersperg N;Leung PC
通讯作者：
Leung PC