폐 선암에서 유해한 승객 돌연변이를 식별하는 모델 개발 및 검증
- In cancer, some of somatic mutations are driver mutations but the vast majority are passenger mutations. According to cancer research, there are passenger mutations that influence various gene categories in the coding regions. Most passenger mutations in cancer are neutral for cancer progression or can be damaging to cancer cells. But passenger mutations have been excluded in cancer research. Here we identify passenger mutations that lowers the rate of lung adenocarcinoma cell growth. In the Somatic mutation data of lung adenocarcinoma cells, all mutations except driver mutations were considered as passenger mutations. Then, in the statistical analysis with non-parametric analysis, the impact of passenger mutations was analyzed by comparing IC 50 values according to occur of the passenger mutation in cells. Our approach confirms the impacts of single passenger mutation and multiple passenger mutations at the module level on lung adenocarcinoma cell. The module for passenger mutation was developed through network analysis. From analysis, we find that the IC50 was low in the presence of certain passenger mutation. A survival analysis of lung adenocarcinoma patients was used to verify if these passenger mutation affects patient survival. But passenger mutations are weak influence individually, which limits the ability to accurately identify deleterious passenger mutations in a single passenger mutation approach. We then identified their deleterious effects at multiple passenger mutations at the module level. We identified modules with low IC50 when mutations were present in all the passenger mutations that consist the module. The module was verified through IC50 values measured by different experimental methods. These modules were related to protein binding, ATP binding, and protein ubiquitination, among molecular functions. And they were related to extracellular region, nucleoplasm, and cytosol, among cellular components. In addition, our study has confirmed that the sensitivity of drugs increases when some passenger mutations occur in drug-injected lung adenocarcinoma cells, especially those injected with the antineoplastic and immunomodulating agents. Our results demonstrate the possibility that some passenger mutations can inhibit lung adenocarcinoma cell growth and this study suggests a model for identifying deleterious passenger mutations that inhibit cancer cell growth and increase drug sensitivity.
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