Multiomics analysis reveals metabolic subtypes and identifies diacylglycerol kinase α (DGKA) as a potential therapeutic target for intrahepatic cholangiocarcinoma
Multiomics analysis reveals metabolic subtypes and identifies diacylglycerol kinase α (DGKA) as a potential therapeutic target for intrahepatic cholangiocarcinoma
AbstractBackgroundIntrahepatic cholangiocarcinoma (iCCA) is a highly heterogeneous and lethal hepatobiliary tumor with few therapeutic strategies. The metabolic reprogramming of tumor cells plays an essential role in the development of tumors, while the metabolic molecular classification of iCCA is largely unknown. Here, we performed an integrated multiomics analysis and metabolic classification to depict differences in metabolic characteristics of iCCA patients, hoping to provide a novel perspective to understand and treat iCCA.MethodsWe performed integrated multiomics analysis in 116 iCCA samples, including whole‐exome sequencing, bulk RNA‐sequencing and proteome analysis. Based on the non‐negative matrix factorization method and the protein abundance of metabolic genes in human genome‐scale metabolic models, the metabolic subtype of iCCA was determined. Survival and prognostic gene analyses were used to compare overall survival (OS) differences between metabolic subtypes. Cell proliferation analysis, 5‐ethynyl‐2'‐deoxyuridine (EdU) assay, colony formation assay, RNA‐sequencing and Western blotting were performed to investigate the molecular mechanisms of diacylglycerol kinase α (DGKA) in iCCA cells.ResultsThree metabolic subtypes (S1‐S3) with subtype‐specific biomarkers of iCCA were identified. These metabolic subtypes presented with distinct prognoses, metabolic features, immune microenvironments, and genetic alterations. The S2 subtype with the worst survival showed the activation of some special metabolic processes, immune‐suppressed microenvironment and Kirsten rat sarcoma viral oncogene homolog (KRAS)/AT‐rich interactive domain 1A (ARID1A) mutations. Among the S2 subtype‐specific upregulated proteins, DGKA was further identified as a potential drug target for iCCA, which promoted cell proliferation by enhancing phosphatidic acid (PA) metabolism and activating mitogen‐activated protein kinase (MAPK) signaling.ConclusionVia multiomics analyses, we identified three metabolic subtypes of iCCA, revealing that the S2 subtype exhibited the poorest survival outcomes. We further identified DGKA as a potential target for the S2 subtype.
- China Academy of Chinese Medical Sciences China (People's Republic of)
- Chinese Academy of Medical Sciences & Peking Union Medical College China (People's Republic of)
- Beijing Proteome Research Center China (People's Republic of)
- Chinese Academy of Medical Sciences China (People's Republic of)
- State Key Laboratory of Proteomics China (People's Republic of)
Diacylglycerol Kinase, metabolic classification, phosphatidic acid metabolism, multiomics analysis, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, MAPK signaling, Original Articles, Multiomics, Cholangiocarcinoma, Bile Ducts, Intrahepatic, Bile Duct Neoplasms, intrahepatic cholangiocarcinoma, Tumor Microenvironment, Humans, RNA, RC254-282, diacylglycerol kinase α
Diacylglycerol Kinase, metabolic classification, phosphatidic acid metabolism, multiomics analysis, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, MAPK signaling, Original Articles, Multiomics, Cholangiocarcinoma, Bile Ducts, Intrahepatic, Bile Duct Neoplasms, intrahepatic cholangiocarcinoma, Tumor Microenvironment, Humans, RNA, RC254-282, diacylglycerol kinase α
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