Application of Graph Models to the Identification of Transcriptomic Oncometabolic Pathways in Human Hepatocellular Carcinoma

被引:2
作者
Barace, Sergio [1 ]
Santamaria, Eva [1 ,2 ]
Infante, Stefany [1 ,3 ]
Arcelus, Sara [1 ]
de la Fuente, Jesus [4 ]
Goni, Enrique [4 ]
Tamayo, Ibon [4 ]
Ochoa, Idoia [5 ]
Sogbe, Miguel [6 ]
Sangro, Bruno [2 ,6 ,7 ]
Hernaez, Mikel [4 ,7 ]
Avila, Matias A. [2 ,7 ,8 ]
Argemi, Josepmaria [1 ,2 ,6 ,7 ,9 ]
机构
[1] Univ Navarra, Appl Med Res Ctr CIMA, DNA & RNA Med Div, Pamplona 31008, Spain
[2] Ctr Invest Biomed Red Enfermedades Hepat & Digest, Av Monforte Lemos,3-5 Pabellon 11,Planta 0, Madrid 28029, Spain
[3] Univ Piura, Fac Med Humana, Lima 15074, Peru
[4] Univ Navarra, Appl Med Res Ctr CIMA, Bioinformat Platform, Pamplona 31008, Spain
[5] Univ Navarra, Tecnun Sch Engn TECNUN, Pamplona 31008, Spain
[6] Univ Navarra, Tecnun Sch Engn TECNUN, Liver Unit, Pamplona 31008, Spain
[7] Inst Invest Sanitaria Navarra IdisNA, Pamplona 31008, Spain
[8] Univ Navarra, Appl Med Res Ctr CIMA, Solid Tumor Program, Hepatol Lab, C Irunlarrea 3, Pamplona 31008, Spain
[9] Univ Pittsburgh, Div Gastroenterol Hepatol & Nutr, Pittsburgh, PA 15232 USA
关键词
hepatocellular carcinoma; RNA sequencing; metabolism; signature; graph; gene set enrichment analysis; gene set variation analysis; EXPRESSION; PROMOTES; LIVER;
D O I
10.3390/biom14060653
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Whole-tissue transcriptomic analyses have been helpful to characterize molecular subtypes of hepatocellular carcinoma (HCC). Metabolic subtypes of human HCC have been defined, yet whether these different metabolic classes are clinically relevant or derive in actionable cancer vulnerabilities is still an unanswered question. Publicly available gene sets or gene signatures have been used to infer functional changes through gene set enrichment methods. However, metabolism-related gene signatures are poorly co-expressed when applied to a biological context. Here, we apply a simple method to infer highly consistent signatures using graph-based statistics. Using the Cancer Genome Atlas Liver Hepatocellular cohort (LIHC), we describe the main metabolic clusters and their relationship with commonly used molecular classes, and with the presence of TP53 or CTNNB1 driver mutations. We find similar results in our validation cohort, the LIRI-JP cohort. We describe how previously described metabolic subtypes could not have therapeutic relevance due to their overall downregulation when compared to non-tumoral liver, and identify N-glycan, mevalonate and sphingolipid biosynthetic pathways as the hallmark of the oncogenic shift of the use of acetyl-coenzyme A in HCC metabolism. Finally, using DepMap data, we demonstrate metabolic vulnerabilities in HCC cell lines.
引用
收藏
页数:19
相关论文
共 53 条
[1]   Tumor-Selective Altered Glycosylation and Functional Attenuation of CD73 in Human Hepatocellular Carcinoma [J].
Alcedo, Karel P. ;
Guerrero, Andres ;
Basrur, Venkatesha ;
Fu, Dong ;
Richardson, Monea L. ;
McLane, Joshua S. ;
Tsou, Chih-Chiang ;
Nesvizhskii, Alexey, I ;
Welling, Theodore H. ;
Lebrilla, Carlito B. ;
Otey, Carol A. ;
Kim, Hong Jin ;
Omary, M. Bishr ;
Snider, Natasha T. .
HEPATOLOGY COMMUNICATIONS, 2019, 3 (10) :1400-1414
[2]   Aberrant protein glycosylation: Implications on diagnosis and Immunotherapy [J].
Bangarh, Rashmi ;
Khatana, Chainika ;
Kaur, Simranjeet ;
Sharma, Anchita ;
Kaushal, Ankur ;
Siwal, Samarjeet Singh ;
Tuli, Hardeep Singh ;
Dhama, Kuldeep ;
Thakur, Vijay Kumar ;
Saini, Reena, V ;
Saini, Adesh K. .
BIOTECHNOLOGY ADVANCES, 2023, 66
[3]   Novel 4-(4-Aryl)cyclohexyl-1-(2-pyridyl)piperazines as Δ8-Δ7 Sterol Isomerase (Emopamil Binding Protein) Selective Ligands with Antiproliferative Activity [J].
Berardi, Francesco ;
Abate, Carmen ;
Ferorelli, Savina ;
de Robertis, Anna F. ;
Leopoldo, Marcello ;
Colabufo, Nicola A. ;
Niso, Mauro ;
Perrone, Roberto .
JOURNAL OF MEDICINAL CHEMISTRY, 2008, 51 (23) :7523-7531
[4]   Loss of liver function in chronic liver disease: An identity crisis [J].
Berasain, Carmen ;
Arechederra, Maria ;
Argemi, Josepmaria ;
Fernandez-Barrena, Maite G. ;
Avila, Matias A. .
JOURNAL OF HEPATOLOGY, 2023, 78 (02) :401-414
[5]   Metabolic Network-Based Identification and Prioritization o f Anticancer Targets Based on Expression Data in Hepatocellular Carcinoma [J].
Bidkhori, Gholamreza ;
Benfeitas, Rui ;
Elmas, Ezgi ;
Kararoudi, Meisam Naeimi ;
Arif, Muhammad ;
Uhlen, Mathias ;
Nielsen, Jens ;
Mardinoglu, Adil .
FRONTIERS IN PHYSIOLOGY, 2018, 9
[6]   Acetyl-CoA metabolism as a therapeutic target for cancer [J].
Chen, Guo ;
Bao, Banghe ;
Cheng, Yang ;
Tian, Minxiu ;
Song, Jiyu ;
Zheng, Liduan ;
Tong, Qiangsong .
BIOMEDICINE & PHARMACOTHERAPY, 2023, 168
[7]   FDPS promotes glioma growth and macrophage recruitment by regulating CCL20 via Wnt/β-catenin signalling pathway [J].
Chen, Zhuo ;
Chen, Guangyong ;
Zhao, Hang .
JOURNAL OF CELLULAR AND MOLECULAR MEDICINE, 2020, 24 (16) :9055-9066
[8]  
Cheng AL, 2022, J HEPATOL, V76, P862, DOI [10.1016/j.jhep.2021.11.030, 10.1016/j.jceh.2022.07.003]
[9]   HBV-infected hepatocellular carcinoma can be robustly classified into three clinically relevant subgroups by a novel analytical protocol [J].
Cheng, Zhiwei ;
Li, Leijie ;
Zhang, Yuening ;
Ren, Yongyong ;
Gu, Jianlei ;
Wang, Xinbo ;
Zhao, Hongyu ;
Lu, Hui .
BRIEFINGS IN BIOINFORMATICS, 2023, 24 (02)
[10]   Focal gains of VEGFA and molecular classification of hepatocellular carcinoma [J].
Chiang, Derek Y. ;
Villanueva, Augusto ;
Hoshida, Yujin ;
Peix, Judit ;
Newell, Philippa ;
Minguez, Beatriz ;
LeBlanc, Amanda C. ;
Donovan, Diana J. ;
Thung, Swan N. ;
Sole, Manel ;
Tovar, Victoria ;
Alsinet, Clara ;
Ramos, Alex H. ;
Barretina, Jordi ;
Roayaie, Sasan ;
Schwartz, Myron ;
Waxman, Samuel ;
Bruix, Jordi ;
Mazzaferro, Vincenzo ;
Ligon, Azra H. ;
Najfeld, Vesna ;
Friedman, Scott L. ;
Sellers, William R. ;
Meyerson, Matthew ;
Llovet, Josep M. .
CANCER RESEARCH, 2008, 68 (16) :6779-6788