Integrative analysis of mutational and transcriptional profiles reveals driver mutations of metastatic breast cancers

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作者
Ji-Hyun Lee
Xing-Ming Zhao
Ina Yoon
Jin Young Lee
Nam Hoon Kwon
Yin-Ying Wang
Kyung-Min Lee
Min-Joo Lee
Jisun Kim
Hyeong-Gon Moon
Yongho In
Jin-Kao Hao
Kyung-Mii Park
Dong-Young Noh
Wonshik Han
Sunghoon Kim
机构
[1] Medicinal Bioconvergence Research Center,Department of Computer Science and Technology
[2] College of Pharmacy,Department of Surgery
[3] Seoul National University,Department of Molecular Medicine and Biopharmaceutical Sciences
[4] Research Institute of Pharmaceutical Sciences,undefined
[5] College of Pharmacy,undefined
[6] Seoul National University,undefined
[7] Tongji University,undefined
[8] Seoul National University College of Medicine,undefined
[9] LERIA,undefined
[10] University of Angers,undefined
[11] Cancer Research Institute,undefined
[12] Seoul National University,undefined
[13] Seoul National University,undefined
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摘要
Despite the explosion in the numbers of cancer genomic studies, metastasis is still the major cause of cancer mortality. In breast cancer, approximately one-fifth of metastatic patients survive 5 years. Therefore, detecting the patients at a high risk of developing distant metastasis at first diagnosis is critical for effective treatment strategy. We hereby present a novel systems biology approach to identify driver mutations escalating the risk of metastasis based on both exome and RNA sequencing of our collected 78 normal-paired breast cancers. Unlike driver mutations occurring commonly in cancers as reported in the literature, the mutations detected here are relatively rare mutations occurring in less than half metastatic samples. By supposing that the driver mutations should affect the metastasis gene signatures, we develop a novel computational pipeline to identify the driver mutations that affect transcription factors regulating metastasis gene signatures. We identify driver mutations in ADPGK, NUP93, PCGF6, PKP2 and SLC22A5, which are verified to enhance cancer cell migration and prompt metastasis with in vitro experiments. The discovered somatic mutations may be helpful for identifying patients who are likely to develop distant metastasis.
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