Cooperation Between Distinct Cancer Driver Genes Underlies Intertumor Heterogeneity in Hepatocellular Carcinoma
Open accessAbstract
Background and aims The pattern of genetic alterations in cancer driver genes in patients with hepatocellular carcinoma (HCC) is highly diverse, which partially explains the low efficacy of available therapies. In spite of this, the existing mouse models only recapitulate a small portion of HCC inter-tumor heterogeneity, limiting the understanding of the disease and the nomination of personalized therapies. Here, we aimed at establishing a novel collection of HCC mouse models that captured human HCC diversity. Methods By performing hydrodynamic tail-vein injections, we tested the impact of altering a well-established HCC oncogene (either MYC or β-catenin) in combination with an additional alteration in one of eleven other genes frequently mutated in HCC. Of the 23 unique pairs of genetic alterations that we interrogated, 9 were able to induce HCC. The established HCC mouse models were characterized at histopathological, immune, and transcriptomic level to identify the unique features of each model. Murine HCC cell lines were generated from each tumor model, characterized transcriptionally, and used to identify specific therapies that were validated in vivo. Results Cooperation between pairs of driver genes produced HCCs with diverse histopathology, immune microenvironments, transcriptomes, and drug responses. Interestingly, MYC expression levels strongly influenced β-catenin activity, indicating that inter-tumor heterogeneity emerges not only from specific combinations of genetic alterations but also from the acquisition of expression-dependent phenotypes. Conclusions This novel collection of murine HCC models and corresponding cell lines establishes the role of driver genes in diverse contexts and enables mechanistic and translational studies.
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CTNNB1 or MYC alone was insufficient to drive cancer within 4 weeks.
“CTNNB1 or MYC alone was insufficient to drive cancer within 4 weeks (38), but delivering both led to carcinogenesis within 1 to 2 weeks on the FVB strain background.”
From The origin of hepatocellular carcinoma depends on metabolic zonation (2026) · cites this paper as [38]
The Results section (‘In vivo screen identifies cooperating driver genes in HCC’; page unavailable) reports that individual genetic alterations were not associated with mortality within eight months and that two drivers were required for efficient liver tumorigenesis in C57BL/6 mice. It does not establish that CTNNB1 or MYC alone failed to produce cancer specifically within four weeks; mortality is not the same measure as tumor formation. (LLM, conf=0.82)
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Cites
The Molecular Signatures Database Hallmark Gene Set Collection
Liberzon, A., Birger, C., Thorvaldsdóttir, H., Ghandi, M., Mesirov, J. P., & Tamayo, P. (2015) · Cell Systems · doi:10.1016/j.cels.2015.12.004 · Cited by 13,807 · see citing works
Identification of an Immune-specific Class of Hepatocellular Carcinoma, Based on Molecular Features
Sia, D., Jiao, Y., Martinez-Quetglas, I., Kuchuk, O., Villacorta-Martin, C., Castro de Moura, M., Putra, J., Camprecios, G., Bassaganyas, L., Akers, N., et al. (2017) · Gastroenterology · doi:10.1053/j.gastro.2017.06.007 · Cited by 976 · see citing works
Ruiz de Galarreta, M., Bresnahan, E., Molina-Sánchez, P., Lindblad, K. E., Maier, B., Sia, D., Puigvehi, M., Miguela, V., Casanova-Acebes, M., Dhainaut, M., et al. (2019) · Cancer Discovery · doi:10.1158/2159-8290.cd-19-0074 · Cited by 912 · see citing works
Self-citationHarding, J. J., Nandakumar, S., Armenia, J., Khalil, D. N., Albano, M., Ly, M., Shia, J., Hechtman, J. F., Kundra, R., El Dika, I., et al. (2019) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-18-2293 · Cited by 602 · see citing works
Activating CAR and β-catenin induces uncontrolled liver growth and tumorigenesis
Dong, B., Lee, J.-S., Park, Y.-Y., Yang, F., Xu, G., Huang, W., Finegold, M. J., & Moore, D. D. (2015) · Nature Communications · doi:10.1038/ncomms6944 · Cited by 97 · see citing works
Flagged first, then by citations
Research works printed but not linked: 23
- [1]Villanueva A Hepatocellular Carcinoma. N Engl J Med 2019; 380: 1450– 1462. 30970190
- [2]Zhu S, Hoshida Y. Molecular heterogeneity in hepatocellular carcinoma. Hepat Oncol 2018; 5: HEP10. 30302198 PMC6168045
- [3]Schulze K, Imbeaud S, Letouze E, Exome sequencing of hepatocellular carcinomas identifies new mutational signatures and potential therapeutic targets. Nat Genet 2015; 47: 505– 11. 25822088 PMC4587544
- [4]Network. CGAR. Comprehensive and Integrative Genomic Characterization of Hepatocellular Carcinoma. Cell 2017; 169: 1327– 1341 e23. 28622513 PMC5680778
- [5]Totoki Y, Tatsuno K, Yamamoto S, High-resolution characterization of a hepatocellular carcinoma genome. Nat Genet 2011; 43: 464– 9. 21499249
- [6]Nault JC, Villanueva A. Intratumor molecular and phenotypic diversity in hepatocellular carcinoma. Clin Cancer Res 2015; 21: 1786– 8. 25628398
- [7]Sawai H, Nishida N, Khor SS, Genome-wide association study identified new susceptible genetic variants in HLA class I region for hepatitis B virus-related hepatocellular carcinoma. Sci Rep 2018; 8: 7958. 29784950 PMC5962604
- [8]Schwabe RF, Greten TF. Gut microbiome in HCC - Mechanisms, diagnosis and therapy. J Hepatol 2020; 72: 230– 238. 31954488
- [9]Dow M, Pyke RM, Tsui BY, Integrative genomic analysis of mouse and human hepatocellular carcinoma. Proc Natl Acad Sci U S A 2018; 115: E9879– E9888. 30287485 PMC6196518
- [10]Chen X, Calvisi DF. Hydrodynamic transfection for generation of novel mouse models for liver cancer research. Am J Pathol 2014; 184: 912– 23. 24480331 PMC3969989
- [11]Nusse R, Clevers H. Wnt/beta-Catenin Signaling, Disease, and Emerging Therapeutic Modalities. Cell 2017; 169: 985– 999. 28575679
- [12]Cadoret A, Ovejero C, Terris B, New targets of beta-catenin signaling in the liver are involved in the glutamine metabolism. Oncogene 2002; 21: 8293– 301. 12447692
- [13]Calderaro J, Couchy G, Imbeaud S, Histological subtypes of hepatocellular carcinoma are related to gene mutations and molecular tumour classification. J Hepatol 2017; 67: 727– 738. 28532995
- [16]Boyault S, Rickman DS, de Reynies A, Transcriptome classification of HCC is related to gene alterations and to new therapeutic targets. Hepatology 2007; 45: 42– 52. 17187432
- [17]Hoshida Y, Nijman SM, Kobayashi M, Integrative transcriptome analysis reveals common molecular subclasses of human hepatocellular carcinoma. Cancer research 2009; 69: 7385– 92. 19723656 PMC3549578
- [18]Tan PS, Nakagawa S, Goossens N, Clinicopathological indices to predict hepatocellular carcinoma molecular classification. Liver Int 2016; 36: 108– 18. 26058462 PMC4674393
- [20]Chiang DY, Villanueva A, Hoshida Y, Focal gains of VEGFA and molecular classification of hepatocellular carcinoma. Cancer research 2008; 68: 6779– 88. 18701503 PMC2587454
- [21]Bisso A, Filipuzzi M, Gamarra Figueroa GP, Cooperation between MYC and beta-catenin in liver tumorigenesis requires Yap/Taz. Hepatology 2020. 31965581
- [23]Abitbol S, Dahmani R, Coulouarn C, AXIN deficiency in human and mouse hepatocytes induces hepatocellular carcinoma in the absence of beta-catenin activation. J Hepatol 2018; 68: 1203– 1213. 29525529
- [24]Caruso S, Calatayud AL, Pilet J, Analysis of Liver Cancer Cell Lines Identifies Agents With Likely Efficacy Against Hepatocellular Carcinoma and Markers of Response. Gastroenterology 2019; 157: 760– 776. 31063779
- [26]Barretina J, Taylor BS, Banerji S, Subtype-specific genomic alterations define new targets for soft-tissue sarcoma therapy. Nature genetics 2010; 42: 715– 21. 20601955 PMC2911503
- [27]Qiu Z, Li H, Zhang Z, A Pharmacogenomic Landscape in Human Liver Cancers. Cancer Cell 2019; 36: 179– 193 e11. 31378681 PMC7505724
- [28]Hao YH, Lafita-Navarro MC, Zacharias L, Induction of LEF1 by MYC activates the WNT pathway and maintains cell proliferation. Cell Commun Signal 2019; 17: 129. 31623618 PMC6798382
Cited by
Sorted by citations
WNT as a Driver and Dependency in Cancer
Parsons, M. J., Tammela, T., & Dow, L. E. (2021) · Cancer Discovery · doi:10.1158/2159-8290.cd-21-0190 · Cited by 257 · see citing works
The origin of hepatocellular carcinoma depends on metabolic zonation
Guo, J., Liang, R., Chung, A., Li, Z., Li, B., Chen, E., Li, L., Wang, J., Hsieh, M.-H., Fang, I. X., et al. (2026) · Science · doi:10.1126/science.adv7129 · Cited by 24 · see citing works
FGF19 and its analog Aldafermin cooperate with MYC to induce aggressive hepatocarcinogenesis
Ursic-Bedoya, J., Desandré, G., Chavey, C., Marie, P., Polizzi, A., Rivière, B., Guillou, H., Assenat, E., Hibner, U., & Gregoire, D. (2024) · EMBO Molecular Medicine · doi:10.1038/s44321-023-00021-x · Cited by 11 · see citing works
- Authors
- Molina-Sánchez, P., Ruiz de Galarreta, M., Yao, M. A., Lindblad, K. E., Bresnahan, E., Bitterman, E., Martin, T. C., Rubenstein, T., Nie, K., Golas, J., Choudhary, S., Bárcena-Varela, M., Elmas, A., Miguela, V., Ding, Y., Kan, Z., Grinspan, L. T., Huang, K.-L., Parsons, R. E., Shields, D. J., Rollins, R. A., & Lujambio, A.
- Affiliations
- Tisch Cancer Institute (US)
- Pfizer (United States) (US)
- Corresponding author
- Shields, David J.
- Rollins, Robert A.
- Lujambio, Amaia
- ORCID
- Venue
- Gastroenterology
- Publisher
- Elsevier BV
- Published
- 2020-12
- Volume
- 159
- Issue
- 6
- Pages
- 2203-2220.e14
- ISSN
- 0016-5085 (ISSN-L)
- PMC
- PMC7726023
- OpenAlex
- W3049585391
- Cited by
- 117
- References
- 5
- Citations by year
- 2026: 22 · 2025: 24 · 2024: 26 · 2023: 21 · 2022: 11 · 2021: 13
- FWCI
- 6.62
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Gastroenterology (acceptedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- Damon Runyon Cancer Research Foundation
- Pfizer
- Asociación Española para el Estudio del Hígado
- U.S. Department of Defense
- Philippe Foundation
- Fundación Alfonso Martín Escudero
- National Cancer Institute
- Topics
- Health Sciences › Medicine › Hepatology › Hepatocellular Carcinoma Treatment and Prognosis
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer Genomics and Diagnostics
- Health Sciences › Medicine › Hepatology › Liver physiology and pathology
- Keywords
- hepatocellular carcinoma, intertumoral heterogeneity, cancer driver genes, c-Myc, β-catenin, oncogene cooperation, mouse tumor model, hydrodynamic injection, tumor immune microenvironment, tumor transcriptome, drug response, personalized treatment
- MeSH terms
- Animals, Disease Models, Animal, Female, Carcinoma, Hepatocellular, Humans, Liver Neoplasms, Male, Mice, Transgenic, Proto-Oncogenes, Gene Expression Regulation, Neoplastic, Genetic Heterogeneity, Drug Resistance, Neoplasm, Tumor Escape, Computational Biology, Cell Line, Tumor, Mice, Tumor Microenvironment
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