AUTHOR=Gao Yang , Zhang Enchong , Fei Xiang , Kong Lingming , Liu Peng , Tan Xiaodong 

TITLE=Identification of Novel Metabolism-Associated Subtypes for Pancreatic Cancer to Establish an Eighteen-Gene Risk Prediction Model

JOURNAL=Frontiers in Cell and Developmental Biology

VOLUME=Volume 9 - 2021

YEAR=2021

URL=https://www.frontiersin.org/journals/cell-and-developmental-biology/articles/10.3389/fcell.2021.691161

DOI=10.3389/fcell.2021.691161

ISSN=2296-634X

ABSTRACT=<p>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 <italic>KRAS</italic>. After further characterizing the subtypes, we constructed a risk score algorithm involving multiple genes (i.e., <italic>NEU2</italic>, <italic>GMPS</italic>, <italic>PRIM2</italic>, <italic>PNPT1</italic>, <italic>LDHA</italic>, <italic>INPP4B</italic>, <italic>DPYD</italic>, <italic>PYGL</italic>, <italic>CA12</italic>, <italic>DHRS9</italic>, <italic>SULT1E1</italic>, <italic>ENPP2</italic>, <italic>PDE1C</italic>, <italic>TPH1</italic>, <italic>CHST12</italic>, <italic>POLR3GL</italic>, <italic>DNMT3A</italic>, and <italic>PGS1</italic>). 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.</p>