School of Science Division of Life Science 37 The Application of Big Data Technologies in Precision Cancer Medicine Supervisor: WANG Jiguang / LIFS Student: LIU Ran / SSCI Course: UROP1000, Summer Whole genome sequencing is the source of data for calculating the evolutionary tree. However, this method has its systematic error. Despite the error can be reduced by improving the quality of sequencing, using high quality sequencing on every sample is quite time and money consuming. Here we create a model to simulate the measuring process and a C++ program to compute the error. This program allows us to estimate the error, unravel the factors affecting the error, infer the real data from the WGS measured data, choose an appropriate sequencing quality, test the validation of this model and hence get a more accurate evolutionary tree. The Application of Big Data Technologies in Precision Cancer Medicine Supervisor: WANG Jiguang / LIFS Student: SHAO Zhihao / BCB Course: UROP2100, Summer Glioblastoma is the most deleterious brain tumor, whereas the contemporary research into this malignant form of glioma is exceedingly limited to the Caucasian race. By sequencing a East Asian-specific cohort consisting of IDH-WT primary glioblastoma patients, we compared the clinical, genomic, and transcriptomic features of the Asian cohort with TCGA Caucasian cohort. Of note, the Asian cohort exhibited significantly better survival. SCNV analysis revealed that patients from the Asian cohort had considerably lower levels of EGFR amplification and PTEN deletion. Such racial difference in EGFR amplification level remained significant in men but diminished in women. This study illuminated the disparities in SCNV characteristics between the East Asian and Caucasian GBM cohorts and examined their correlation with distinct attributes. Study of Blood Cell Development using Zebrafish Model Supervisor: WEN Zilong / LIFS Student: FAN Yining / BCB Course: UROP1100, Fall Our collaborators identified a novel somatic gain-of-function mutation in MAP3K3 associated with Cerebral cavernoma malformation (CCM), a type of vascular malformation characterized by vein and capillary dilation and subsequent hemorrhage. Importantly, they found strong association between MAP3K3 mutation and Type II and Type III CCMs7 . Here we generated zebrafish disease models of MAP3K3(MUT) sporadic CCMs in order to find out the molecular mechanisms of how MAP3K3 mutation contributes to CCM lesions. We first demonstrated that compared with zebrafish injected with hMEKK3(WT) coding construct, zebrafish injected with hMEKK3(MUT) coding construct showed more frequent hemorrhage which is a feature of CCM lesions. More experiments will be carried out afterwards and finally we will conduct drug screening utilizing zebrafish models, hoping to find out a non-invasive cure to CCMs.