| Summary: | 碩士 === 國立陽明大學 === 生物醫學資訊研究所 === 98 === The prevalence of breast cancer is higher than before. Currently, the strategy of treatment is combing surgical operation and additional treatment to avoid recurrence or metastasis. Based on the histological grade system and biomarkers, we can divide patients into many subgroups and use difference way to treat but those methods are not enough to show all the patients’ situations. We need more biomarkers and combine to diverse states to separate patients.
We used three methods, optimum p-value, bimodal and median, to find the cut points and test the survival rate difference between 2 sub-groups. Finally, we based on the bimodal feature and used GSE4922 microarray gene expression downloaded from NCBI-GEO database, clinical data and survival analysis to find out the possible potential biomarkers. In order to understand the gene-gene interaction affects, we further test the gene combinations. The results show that 36 potential biomarkers and 226 gene-gene interactions on patient’s survival called synergistic effects. The results show 226 synergistic effects including 144 positive and 82 negative synergistic effects found in this study. This phenomenon is similar with synthetic lethal found in the yeast. There is 2 possible mechanisms can explain this phenomenon: alternative pathway and kinetic synergism. At least one synergistic effect pair had biological signature: SCN4B and TWF1 genes are implicated in cell adhesion and cell motility, respectively. Therefore, this gene pair might be involved in the Epithelial Mesenchymal Transition (EMT), which may lead to metastasis and poor survival.
We also analysis the correlation between the number of bad synergistic effect on a patients and DFS time, the results shown there is high correlation between them. Moreover, this correlation also shown in histological grade: the malignant grade patients had more bad synergistic effects than the benignant grade patients in average. While we selected 5 markers from our study, 249 patients may separate to 31 sub-groups. It also means that the ability to group patients into significant subgroups could find in our markers, which is important for either diagnosis or treatment and this is the basis for future personal diagnosis and tailored treatment.
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