ena-STUDY-JiHyun_Lee-13-04-2015-06:48:41:770-227
Integrative systematic analyses of mutational and transcriptional profiles reveal driver mutations escalating the risk of distant metastasis in Korean breast cancers
Despite the explosion in 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 conducted comprehensive genetic analyses to discover driver mutations escalating the risk of metastasis, using Exome and RNA sequencing of the samples of 22 HRM (high-risk for distant metastasis) and 56 LRM (low-risk for distant metastasis) breast cancer patients. We hypothesized that the genetic mutations responsible for the metastasis may be associated with TFs (transcription factors) to perturb the downstream processes which result in DEGs (differentially expressed genes). Based on this, we developed a new integrated systematic approach to predict candidate driver mutations by measuring the sample coverage and the weight of the pathways linking mutations to TFs. The analysis led to the discovery of HRM-specific mutations in ADPGK, NUP93, PCGF6, PKP2, and SLC22A5 which significantly enhanced cancer cell migration and metastatic signaling pathways. The discovered somatic mutations may be useful for identifying patients who are likely to develop distant metastasis. Furthermore, our integrative systematic analyses suggest a new way to discover and understand driver mutations without relying on simple frequency-based analyses.
Despite the explosion in 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 conducted comprehensive genetic analyses to discover driver mutations escalating the risk of metastasis, using Exome and RNA sequencing of the samples of 22 HRM (high-risk for distant metastasis) and 56 LRM (low-risk for distant metastasis) breast cancer patients. We hypothesized that the genetic mutations responsible for the metastasis may be associated with TFs (transcription factors) to perturb the downstream processes which result in DEGs (differentially expressed genes). Based on this, we developed a new integrated systematic approach to predict candidate driver mutations by measuring the sample coverage and the weight of the pathways linking mutations to TFs. The analysis led to the discovery of HRM-specific mutations in ADPGK, NUP93, PCGF6, PKP2, and SLC22A5 which significantly enhanced cancer cell migration and metastatic signaling pathways. The discovered somatic mutations may be useful for identifying patients who are likely to develop distant metastasis. Furthermore, our integrative systematic analyses suggest a new way to discover and understand driver mutations without relying on simple frequency-based analyses.