1.High prevalence of TP53 mutations is associated with poor survival and an EMT signature in gliosarcoma patients.
Sung Yup CHO ; Changho PARK ; Deukchae NA ; Jee Yun HAN ; Jieun LEE ; Ok Kyoung PARK ; Chengsheng ZHANG ; Chang Ohk SUNG ; Hyo Eun MOON ; Yona KIM ; Jeong Hoon KIM ; Jong Jae KIM ; Shin Kwang KHANG ; Do Hyun NAM ; Jung Won CHOI ; Yeon Lim SUH ; Dong Gyu KIM ; Sung Hye PARK ; Hyewon YOUN ; Kyuson YUN ; Jong Il KIM ; Charles LEE ; Sun Ha PAEK ; Hansoo PARK
Experimental & Molecular Medicine 2017;49(4):e317-
Gliosarcoma (GS) is a rare variant (2%) of glioblastoma (GBM) that poses clinical genomic challenges because of its poor prognosis and limited genomic information. To gain a comprehensive view of the genomic alterations in GS and to understand the molecular etiology of GS, we applied whole-exome sequencing analyses for 28 GS cases (6 blood-matched fresh-frozen tissues for the discovery set, 22 formalin-fixed paraffin-embedded tissues for the validation set) and copy-number variation microarrays for 5 blood-matched fresh-frozen tissues. TP53 mutations were more prevalent in the GS cases (20/28, 70%) compared to the GBM cases (29/90, 32%), and the GS patients with TP53 mutations showed a significantly shorter survival (multivariate Cox analysis, hazard ratio=23.9, 95% confidence interval, 2.87–199.63, P=0.003). A pathway analysis showed recurrent alterations in MAPK signaling (EGFR, RASGRF2 and TP53), phosphatidylinositol/calcium signaling (CACNA1s, PLCs and ITPRs) and focal adhesion/tight junction (PTEN and PAK3) pathways. Genomic profiling of the matched recurrent GS cases detected the occurrence of TP53 mutations in two recurrent GS cases, which suggests that TP53 mutations play a role in treatment resistance. Functionally, we found that TP53 mutations are associated with the epithelial–mesenchymal transition (EMT) process of sarcomatous components of GS. We provide the first comprehensive genome-wide genetic alternation profiling of GS, which suggests novel prognostic subgroups in GS patients based on their TP53 mutation status and provides new insight in the pathogenesis and targeted treatment of GS.
Glioblastoma
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Gliosarcoma*
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Humans
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Prevalence*
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Prognosis
2.A unified deep-learning network to accurately segment insulin granules of different animal models imaged under different electron microscopy methodologies.
Xiaoya ZHANG ; Xiaohong PENG ; Chengsheng HAN ; Wenzhen ZHU ; Lisi WEI ; Yulin ZHANG ; Yi WANG ; Xiuqin ZHANG ; Hao TANG ; Jianshe ZHANG ; Xiaojun XU ; Fengping FENG ; Yanhong XUE ; Erlin YAO ; Guangming TAN ; Tao XU ; Liangyi CHEN
Protein & Cell 2019;10(4):306-311