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癌症中反复突变基因的基因组格局及突变影响

Genomic landscape and mutational impacts of recurrently mutated genes in cancers.

作者信息

Liu Baolin, Hu Fei-Fei, Zhang Qiong, Hu Hui, Ye Zheng, Tang Qin, Guo An-Yuan

机构信息

Department of Bioinformatics and Systems Biology, Key Laboratory of Molecular Biophysics of the Ministry of Education, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China.

Department of Biochemistry and Molecular Biology, Tianjin Key Laboratory of Medical Epigenetics, Tianjin Medical University, Tianjin, China.

出版信息

Mol Genet Genomic Med. 2018 Nov;6(6):910-923. doi: 10.1002/mgg3.458. Epub 2018 Aug 14.

Abstract

BACKGROUND

Cancer genes tend to be highly mutated under positive selection. Better understanding the recurrently mutated genes (RMGs) in cancer is critical for explicating the mechanisms of tumorigenesis and providing vital clues for therapy. Although some studies have investigated functional impacts of RMGs in specific cancer types, a comprehensive analysis of RMGs and their mutational impacts across cancers is still needed.

METHODS

We obtained data from The Cancer Genome Atlas (TCGA) and calculated mutation rate of each gene in 31 cancer types. Functional analysis was performed to identify the important signaling pathways and enriched protein types of RMGs. In order to evaluate functional impacts of RMGs, differential expression, survival, and pairwise mutation patterns analyses were performed.

RESULTS

Totally, we identified 897 RMGs and 624 of them were specifically mutant in only a single cancer type. Functional analysis demonstrated that these RMGs were enriched in hydrolases, cytoskeletal protein, and pathways like MAPK, cell cycle, PI3K-Akt, ECM receptor interaction, and energy metabolism. The differentially expressed genes potentially affected by the same common RMG showed a relatively low overlap across different cancer types. For the 19 Mucin (MUC) family genes, nine of them were RMGs and four of them (MUC17, MUC5B, MUC4, and MUC16) were common RMGs shared in 8 to 17 cancer types. The results showed that recurrent mutations in MUC genes were significantly associated with better survival prognosis. Only a small part of RMGs was differentially expressed due to their own mutations and most of them were downregulated. In addition, pairwise mutation pattern analysis revealed the high frequency of co-occurred mutations among RMGs in STAD.

CONCLUSION

Through the functional analysis of RMGs, we found that six signaling pathways were disrupted in most cancer types and that energy metabolism was abnormal in tumors. The results also revealed a strong correlation between recurrently mutated genes from MUC family and human survival. In addition, gene expression and survival prognosis were associated with different mutation types of RMGs.

摘要

背景

癌症基因在正选择下往往高度突变。更好地了解癌症中反复突变的基因(RMG)对于阐明肿瘤发生机制和为治疗提供重要线索至关重要。尽管一些研究已经调查了RMG在特定癌症类型中的功能影响,但仍需要对RMG及其在各种癌症中的突变影响进行全面分析。

方法

我们从癌症基因组图谱(TCGA)获取数据,并计算了31种癌症类型中每个基因的突变率。进行功能分析以确定RMG的重要信号通路和富集的蛋白质类型。为了评估RMG的功能影响,进行了差异表达、生存和成对突变模式分析。

结果

我们总共鉴定出897个RMG,其中624个仅在单一癌症类型中特异性突变。功能分析表明,这些RMG在水解酶、细胞骨架蛋白以及丝裂原活化蛋白激酶(MAPK)、细胞周期、磷脂酰肌醇-3-激酶-蛋白激酶B(PI3K-Akt)、细胞外基质受体相互作用和能量代谢等信号通路中富集。受相同常见RMG潜在影响的差异表达基因在不同癌症类型之间的重叠相对较低。对于19个粘蛋白(MUC)家族基因,其中9个是RMG,4个(MUC17、MUC5B、MUC4和MUC16)是在8至17种癌症类型中共享的常见RMG。结果表明,MUC基因的反复突变与更好的生存预后显著相关。只有一小部分RMG因其自身突变而差异表达,且大多数RMG表达下调。此外,成对突变模式分析揭示了胃癌(STAD)中RMG之间共发突变的高频率。

结论

通过对RMG的功能分析,我们发现大多数癌症类型中有6条信号通路被破坏,肿瘤中的能量代谢异常。结果还揭示了MUC家族反复突变基因与人类生存之间的强相关性。此外,基因表达和生存预后与RMG的不同突变类型相关。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3ea2/6305651/c1f88dba2946/MGG3-6-910-g001.jpg

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