干旱区生态环境知识资源中心(Arid): Identification of Novel Metabolism-Associated Subtypes for Pancreatic Cancer to Establish an Eighteen-Gene Risk Prediction

Arid

DOI	10.3389/fcell.2021.691161
	Identification of Novel Metabolism-Associated Subtypes for Pancreatic Cancer to Establish an Eighteen-Gene Risk Prediction
	Gao, Yang; Zhang, Enchong; Fei, Xiang; Kong, Lingming; Liu, Peng; Tan, Xiaodong
通讯作者	Tan, XD (corresponding author), China Med Univ, Shengjing Hosp, Dept Gen Surg, Shenyang, Peoples R China.
来源期刊	FRONTIERS IN CELL AND DEVELOPMENTAL BIOLOGY
ISSN	2296-634X
出版年	2021
卷号	9
英文摘要	Pancreatic cancer (PanC) is an intractable malignancy with a high mortality. Metabolic processes contribute to cancer progression and therapeutic responses, and histopathological subtypes are insufficient for determining prognosis and treatment strategies. In this study, PanC subtypes based on metabolism-related genes were identified and further utilized to construct a prognostic model. Using a cohort of 171 patients from The Cancer Genome Atlas (TCGA) database, transcriptome data, simple nucleotide variants (SNV), and clinical information were analyzed. We divided patients with PanC into metabolic gene-enriched and metabolic gene-desert subtypes. The metabolic gene-enriched subgroup is a high-risk subtype with worse outcomes and a higher frequency of SNVs, especially in KRAS. After further characterizing the subtypes, we constructed a risk score algorithm involving multiple genes (i.e., NEU2, GMPS, PRIM2, PNPT1, LDHA, INPP4B, DPYD, PYGL, CA12, DHRS9, SULT1E1, ENPP2, PDE1C, TPH1, CHST12, POLR3GL, DNMT3A, and PGS1). We verified the reproducibility and reliability of the risk score using three validation cohorts (i.e., independent datasets from TCGA, Gene Expression Omnibus, and Ensemble databases). Finally, drug prediction was completed using a ridge regression model, yielding nine candidate drugs for high-risk patients. These findings support the classification of PanC into two metabolic subtypes and further suggest that the metabolic gene-enriched subgroup is associated with worse outcomes. The newly established risk model for prognosis and therapeutic responses may improve outcomes in patients with PanC.
英文关键词	pancreatic cancer transcriptome metabolic genes subtype risk model
类型	Article
语种	英语
开放获取类型	Green Published, gold
收录类别	SCI-E
WOS记录号	WOS:000684954500009
WOS关键词	MOLECULAR SUBTYPES ; PRECISION MEDICINE ; GENE ; TUMOR ; METHYLATION ; BALANCE
WOS类目	Cell Biology ; Developmental Biology
WOS研究方向	Cell Biology ; Developmental Biology
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/363277
作者单位	[Gao, Yang; Fei, Xiang; Kong, Lingming; Liu, Peng; Tan, Xiaodong] China Med Univ, Shengjing Hosp, Dept Gen Surg, Shenyang, Peoples R China; [Zhang, Enchong] China Med Univ, Shengjing Hosp, Dept Urol, Shenyang, Peoples R China
推荐引用方式 GB/T 7714	Gao, Yang,Zhang, Enchong,Fei, Xiang,et al. Identification of Novel Metabolism-Associated Subtypes for Pancreatic Cancer to Establish an Eighteen-Gene Risk Prediction[J],2021,9.
APA	Gao, Yang,Zhang, Enchong,Fei, Xiang,Kong, Lingming,Liu, Peng,&Tan, Xiaodong.(2021).Identification of Novel Metabolism-Associated Subtypes for Pancreatic Cancer to Establish an Eighteen-Gene Risk Prediction.FRONTIERS IN CELL AND DEVELOPMENTAL BIOLOGY,9.
MLA	Gao, Yang,et al."Identification of Novel Metabolism-Associated Subtypes for Pancreatic Cancer to Establish an Eighteen-Gene Risk Prediction".FRONTIERS IN CELL AND DEVELOPMENTAL BIOLOGY 9(2021).