Proteogenomic Characterization of Human Early-Onset Gastric Cancer
- Authors
- Mun, Dong-Gi; Bhin, Jinhyuk; Kim, Sangok; Kim, Hyunwoo; Jung, Jae Hun; Jung, Yeonjoo; Jang, Ye Eun; Park, Jong Moon; Kim, Hokeun; Jung, Yeonhwa; Lee, Hangyeore; Bae, Jingi; Back, Seunghoon; Kim, Su-Jin; Kim, Jieun; Park, Heejin; Li, Honglan; Hwang, Kyu-Baek; Park, Young Soo; Yook, Jeong Hwan; Kim, Byung Sik; Kwon, Sun Young; Ryu, Seung Wan; Park, Do Youn; Jeon, Tae Yong; Kim, Dae Hwan; Lee, Jae-Hyuck; Han, Sang-Uk; Song, Kyu Sang; Park, Dongmin; Park, Jun Won; Rodriguez, Henry; Kim, Jaesang; Lee, Hookeun; Kim, Kwang Pyo; Yang, Eun Gyeong; Kim, Hark Kyun; Paek, Eunok; Lee, Sanghyuk; Lee, Sang-Won; Hwang, Daehee
- Issue Date
- Jan-2019
- Publisher
- CELL PRESS
- Keywords
- cancer subtypes; correlation between mRNA and protein abundance changes; correlation between mutation and phosphorylation; diffuse gastric cancer; proteogenomics; somatic nonsynonymous mutations
- Citation
- CANCER CELL, v.35, no.1, pp.111
- Indexed
- SCIE
SCOPUS
- Journal Title
- CANCER CELL
- Volume
- 35
- Number
- 1
- Start Page
- 111
- URI
- https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/148542
- DOI
- 10.1016/j.ccell.2018.12.003
- ISSN
- 1535-6108
- Abstract
- We report proteogenomic analysis of diffuse gastric cancers (GCs) in young populations. Phosphoproteome data elucidated signaling pathways associated with somatic mutations based on mutation-phosphorylation correlations. Moreover, correlations between mRNA and protein abundances provided potential oncogenes and tumor suppressors associated with patient survival. Furthermore, integrated clustering of mRNA, protein, phosphorylation, and N-glycosylation data identified four subtypes of diffuse GCs. Distinguishing these subtypes was possible by proteomic data. Four subtypes were associated with proliferation, immune response, metabolism, and invasion, respectively; and associations of the subtypes with immune-and invasion-related pathways were identified mainly by phosphorylation and N-glycosylation data. Therefore, our proteogenomic analysis provides additional information beyond genomic analyses, which can improve understanding of cancer biology and patient stratification in diffuse GCs.
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