{"title":"多组学分析揭示了代谢亚型,并确定二酰甘油激酶α(DGKA)是肝内胆管癌的潜在治疗靶点。","authors":"Weiren Liu, Huqiang Wang, Qianfu Zhao, Chenyang Tao, Weifeng Qu, Yushan Hou, Run Huang, Zimei Sun, Guiqi Zhu, Xifei Jiang, Yuan Fang, Jun Gao, Xiaoling Wu, Zhixiang Yang, Rongyu Ping, Jiafeng Chen, Rui Yang, Tianhao Chu, Jian Zhou, Jia Fan, Zheng Tang, Dong Yang, Yinghong Shi","doi":"10.1002/cac2.12513","DOIUrl":null,"url":null,"abstract":"<div>\n \n \n <section>\n \n <h3> Background</h3>\n \n <p>Intrahepatic 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.</p>\n </section>\n \n <section>\n \n <h3> Methods</h3>\n \n <p>We 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.</p>\n </section>\n \n <section>\n \n <h3> Results</h3>\n \n <p>Three 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 (<i>KRAS</i>)/AT-rich interactive domain 1A (<i>ARID1A</i>) 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.</p>\n </section>\n \n <section>\n \n <h3> Conclusion</h3>\n \n <p>Via 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.</p>\n </section>\n </div>","PeriodicalId":9495,"journal":{"name":"Cancer Communications","volume":null,"pages":null},"PeriodicalIF":20.1000,"publicationDate":"2023-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cac2.12513","citationCount":"0","resultStr":"{\"title\":\"Multiomics analysis reveals metabolic subtypes and identifies diacylglycerol kinase α (DGKA) as a potential therapeutic target for intrahepatic cholangiocarcinoma\",\"authors\":\"Weiren Liu, Huqiang Wang, Qianfu Zhao, Chenyang Tao, Weifeng Qu, Yushan Hou, Run Huang, Zimei Sun, Guiqi Zhu, Xifei Jiang, Yuan Fang, Jun Gao, Xiaoling Wu, Zhixiang Yang, Rongyu Ping, Jiafeng Chen, Rui Yang, Tianhao Chu, Jian Zhou, Jia Fan, Zheng Tang, Dong Yang, Yinghong Shi\",\"doi\":\"10.1002/cac2.12513\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n \\n <section>\\n \\n <h3> Background</h3>\\n \\n <p>Intrahepatic 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.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Methods</h3>\\n \\n <p>We 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.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Results</h3>\\n \\n <p>Three 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 (<i>KRAS</i>)/AT-rich interactive domain 1A (<i>ARID1A</i>) 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.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Conclusion</h3>\\n \\n <p>Via 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.</p>\\n </section>\\n </div>\",\"PeriodicalId\":9495,\"journal\":{\"name\":\"Cancer Communications\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":20.1000,\"publicationDate\":\"2023-12-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cac2.12513\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Cancer Communications\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/cac2.12513\",\"RegionNum\":1,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ONCOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cancer Communications","FirstCategoryId":"3","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/cac2.12513","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ONCOLOGY","Score":null,"Total":0}
Multiomics analysis reveals metabolic subtypes and identifies diacylglycerol kinase α (DGKA) as a potential therapeutic target for intrahepatic cholangiocarcinoma
Background
Intrahepatic 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.
Methods
We 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.
Results
Three 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.
Conclusion
Via 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.
期刊介绍:
Cancer Communications is an open access, peer-reviewed online journal that encompasses basic, clinical, and translational cancer research. The journal welcomes submissions concerning clinical trials, epidemiology, molecular and cellular biology, and genetics.