期刊
AGING-US
卷 12, 期 22, 页码 22840-22858出版社
IMPACT JOURNALS LLC
关键词
pancreatic cancer; prognostic signature; miRNA sets; GSVA; metabolic pathways
资金
- National Key R&D Program of China [2017YFC1308600]
- National Natural Science Foundation of China [81672382]
- Clinical Research Foundation of TMMU [SWH2017ZDCX2004]
- Science and Technology Plan Project of Guangdong Province [2015A020214012, 2016B090917001, 2015B020214005]
Pancreatic cancer (PC) is a severe disease with the highest mortality rate among various cancers. It is urgent to find an effective and accurate way to predict the survival of PC patients. Gene set variation analysis (GSVA) was used to establish and validate a miRNA set-based pathway prognostic signature for PC (miPPSPC) and a mRNA set-based pathway prognostic signature for PC (mPPSPC) in independent datasets. An optimized miPPSPC was constructed by combining clinical parameters. The miPPSPC, optimized miPPSPC and mPPSPC were established and validated to predict the survival of PC patients and showed excellent predictive ability. Four metabolic pathways and one oxidative stress pathway were identified in the miPPSPC, whereas linoleic acid metabolism and the pentose phosphate pathway were identified in the mPPSPC. Key factors of the pentose phosphate pathway and linoleic acid metabolism, G6PD and CYP2C8/9/18/19, respectively, are related to the survival of PC patients according to our tissue microarray. Thus, the miPPSPC, optimized miPPSPC and mPPSPC can predict the survival of PC patients efficiently and precisely. The metabolic and oxidative stress pathways may participate in PC progression.
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