Open AccessDevelopment of a membrane lipid metabolism–based signature to predict overall survival for personalized medicine in ccRCC patients
Author(s) -
Maode Bao,
Run Shi,
Kai Zhang,
Yanbo Zhao,
Yanfang Wang,
Xuanwen Bao
Publication year - 2019
Publication title -
the epma journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.177
H-Index - 34
eISSN - 1878-5085
pISSN - 1878-5077
DOI - 10.1007/s13167-019-00189-8
Subject(s) - lipid metabolism , clear cell renal cell carcinoma , proportional hazards model , medicine , biology , bioinformatics , oncology , computational biology , renal cell carcinoma
Clear cell renal cell carcinoma (ccRCC) is the most common type of renal cell carcinoma and is characterized by a dysregulation of changes in cellular metabolism. Altered lipid metabolism contributes to ccRCC progression and malignancy.