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DNA and RNA sequencing identified a novel oncogene VPS35 in liver hepatocellular carcinoma

Oncogene volume 39, pages 3229–3244 (2020)Cite this article

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Abstract

Liver hepatocellular carcinoma (LIHC) is the second leading cause of cancer mortality worldwide. Although cancer driver genes identified so far have been considered to be saturated or nearly saturated, challenges remain in discovering novel genes underlying carcinogenesis due to significant tumor heterogeneity. Here, in a small cohort of hepatitis B virus (HBV)-associated LIHC, we investigated the transcriptional patterns of tumor-mutated alleles using both whole-exome and RNA sequencing data. A graph clustering of the transcribed tumor-mutated alleles characterized overlapped functional clusters, and thus prioritized potentially novel oncogenes. We validated the function of the potentially novel oncogenes in vitro and in vivo. We showed that a component of the retromer complex—the vacuolar protein sorting-associated protein 35 (VPS35)—promoted the proliferation of hepatoma cell through the PI3K/AKT signaling pathway. In VPS35-knockout hepatoma cells, a significantly reduced distribution of membrane fibroblast growth factor receptor 3 (FGFR3) demonstrated the effects of VPS35 on sorting and trafficking of transmembrane receptor. This study provides insight into the roles of the retromer complex on carcinogenesis and has important implications for the development of personalized therapeutic strategies for LIHC.

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Fig. 1: Somatic mutations identified by whole-exome sequencing and their transcriptional patterns.
Fig. 2: Identification of a potentially novel oncogene of VPS35.
Fig. 3: VPS35 promoted the proliferation of hepatoma cells by facilitating the G1/S transition.
Fig. 4: VPS35 exerts its oncogenic roles via the PI3K/AKT signaling.
Fig. 5: A xenograft tumor model of VPS35.
Fig. 6: A significantly reduced FGFR3 in VPS35-KO SK-Hep1 cell line.
Fig. 7: A proposed model depicts how VPS35 participates in the trafficking of FGFR3 and its effects in the downstream PI3K/AKT signaling.

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Data availability

Supplementary materials including tables and figures. Whole exome sequencing data for LIHC tumor and its paired cirrhotic tissues, and peripheral blood lymphocytes, as well as RNA sequencing data for LIHC tumor and its paired cirrhotic tissues have been submitted to the Sequence Read Archive (SRA) (https://submit.ncbi.nlm.nih.gov/) under the number SUB6779164. RNA sequencing data for parental and VPS35-KO SK-Hep1 cell lines have been submitted to the SRA under the number SUB6834808. The source code is available upon request. Supplementary information is available at Oncogene’s website.

References

  1. Ferlay J, Soerjomataram I, Dikshit R, Eser S, Mathers C, Rebelo M, et al. Cancer incidence and mortality worldwide: Sources, methods and major patterns in GLOBOCAN 2012. Int J Cancer. 2014;136:E359–86.

    PubMed  Google Scholar 

  2. El-Serag HB, Rudolph KL. Hepatocellular carcinoma: epidemiology and molecular carcinogenesis. Gastroenterology. 2007;132:2557–76.

    CAS  PubMed  Google Scholar 

  3. Vogelstein B, Kinzler KW. The multistep nature of cancer. Trends Genet. 1993;9:138–41.

    CAS  PubMed  Google Scholar 

  4. Villanueva A. Hepatocellular carcinoma. N Engl J Med. 2019;380:1450–62.

    CAS  PubMed  Google Scholar 

  5. Totoki Y, Tatsuno K, Yamamoto S, Arai Y, Hosoda F, Ishikawa S, et al. High-resolution characterization of a hepatocellular carcinoma genome. Nat Genet. 2011;43:464–9.

    CAS  PubMed  Google Scholar 

  6. Huang J, Deng Q, Wang Q, Li K-Y, Dai J-H, Li N, et al. Exome sequencing of hepatitis B virus associated hepatocellular carcinoma. Nat Genet. 2012;44:1117–21.

    CAS  PubMed  Google Scholar 

  7. Sung W-K, Zheng H, Li S, Chen R, Liu X, Li Y, et al. Genome-wide survey of recurrent HBV integration in hepatocellular carcinoma. Nat Genet. 2012;44:765–9.

    CAS  PubMed  Google Scholar 

  8. Kan Z, Zheng H, Liu X, Li S, Barber TD, Gong Z, et al. Whole-genome sequencing identifies recurrent mutations in hepatocellular carcinoma. Genome Res. 2013;23:1422–33.

    CAS  PubMed  PubMed Central  Google Scholar 

  9. Cleary SP, Jeck WR, Zhao X, Chen K, Selitsky SR, Savich GL, et al. Identification of driver genes in hepatocellular carcinoma by exome sequencing. Hepatology. 2013;58:1693–702.

    CAS  PubMed  PubMed Central  Google Scholar 

  10. Shibata T, Aburatani H. Exploration of liver cancer genomes. Nat Rev Gastroenterol Hepatol. 2014;11:340–9.

    CAS  PubMed  Google Scholar 

  11. Schulze K, Nault JC, Villanueva A. Genetic profiling of hepatocellular carcinoma using next-generation sequencing. J Hepatol. 2016;65:1031–42.

    CAS  PubMed  Google Scholar 

  12. Creixell P, Reimand J, Haider S, Wu G, Shibata T, Vazquez M, et al. Pathway and network analysis of cancer genomes. Nat Methods. 2015;12:615–21.

    CAS  PubMed  PubMed Central  Google Scholar 

  13. Ding L, Wendl MC, McMichael JF, Raphael BJ. Expanding the computational toolbox for mining cancer genomes. Nat Rev Genet. 2014;15:556–70.

    CAS  PubMed  PubMed Central  Google Scholar 

  14. Cancer Genome Atlas Research Network. Comprehensive and integrative genomic characterization of hepatocellular carcinoma. Cell. 2017;169:1327–41.e23.

  15. Bailey MH, Tokheim C, Porta-Pardo E, Sengupta S, Bertrand D, Weerasinghe A, et al. Comprehensive characterization of cancer driver genes and mutations. Cell. 2018;173:371–85.e18.

  16. Hsiehchen D, Hsieh A. Nearing saturation of cancer driver gene discovery. J Hum Genet. 2018;63:941–3.

    CAS  PubMed  Google Scholar 

  17. Chen KE, Healy MD, Collins BM. Towards a molecular understanding of endosomal trafficking by retromer and retriever. Traffic. 2019;20:465–78.

    CAS  PubMed  Google Scholar 

  18. Ding K, Wu S, Ying W, Pan Q, Li X, Zhao D, et al. Leveraging a multi-omics strategy for prioritizing personalized candidate mutation-driver genes: a proof-of-concept study. Sci Rep. 2015;5:17564.

    CAS  PubMed  PubMed Central  Google Scholar 

  19. Hoshida Y, Fuchs BC, Bardeesy N, Baumert TF, Chung RT. Pathogenesis and prevention of hepatitis C virus-induced hepatocellular carcinoma. J Hepatol. 2014;61:S79–90.

    CAS  PubMed  PubMed Central  Google Scholar 

  20. Caruso S, Calatayud A-L, Pilet J, La Bella T, Rekik S, Imbeaud S, et al. Analysis of liver cancer cell lines identifies agents with likely efficacy against hepatocellular carcinoma and markers of response. Gastroenterology. 2019;157:760–76.

    CAS  PubMed  Google Scholar 

  21. Sondka Z, Bamford S, Cole CG, Ward SA, Dunham I, Forbes SA. The COSMIC cancer gene census: describing genetic dysfunction across all human cancers. Nat Rev Cancer. 2018;18:696–705.

    CAS  PubMed  PubMed Central  Google Scholar 

  22. Kasprzak A, Adamek A. Mucins: the old, the new and the promising factors in hepatobiliary carcinogenesis. Int J Mol Sci. 2019;20:1288–30.

    CAS  PubMed Central  Google Scholar 

  23. Babu SD, Jayanthi V, Devaraj N, Reis CA, Devaraj H. Expression profile of mucins (MUC2, MUC5AC and MUC6) in helicobacter pylori infected pre-neoplastic and neoplastic human gastric epithelium. Mol Cancer. 2006;5:1–7.

    Google Scholar 

  24. Rao CV, Asch AS, Yamada HY. Frequently mutated genes/pathways and genomic instability as prevention targets in liver cancer. Carcinogenesis. 2017;38:2–11.

    CAS  PubMed  Google Scholar 

  25. Hanawalt PC, Spivak G. Transcription-coupled DNA repair: two decades of progress and surprises. Nat Rev Mol Cell Biol. 2008;9:958–70.

    CAS  PubMed  Google Scholar 

  26. Nepusz T, Yu H, Paccanaro A. Detecting overlapping protein complexes in protein-protein interaction networks. Nat Methods. 2012;9:471–2.

    CAS  PubMed  PubMed Central  Google Scholar 

  27. Zaki N, Efimov D, Berengueres J. Protein complex detection using interaction reliability assessment and weighted clustering coefficient. BMC Bioinform. 2013;14:163.

  28. Wang J, Zhong J, Chen G, Li M, Wu F-x, Pan Y. ClusterViz: a cytoscape APP for cluster analysis of biological network. IEEE/ACM Trans Comput Biol Bioinform. 2015;12:815–22.

    PubMed  Google Scholar 

  29. Chin C-H, Chen S-H, Wu H-H, Ho C-W, Ko M-T, Lin C-Y. cytoHubba: identifying hub objects and sub- networks from complex interactome. BMC Syst Biol. 2014;8:S11.

    PubMed  PubMed Central  Google Scholar 

  30. Fuse A, Furuya N, Kakuta S, Inose A, Sato M, Koike M, et al. VPS29-VPS35 intermediate of retromer is stable and may be involved in the retromer complex assembly process. FEBS Lett. 2015;589:1430–6.

    CAS  PubMed  Google Scholar 

  31. McLaren W, Gil L, Hunt SE, Riat HS, Ritchie GRS, Thormann A, et al. The ensembl variant effect predictor. Genome Biol. 2016;17:122.

  32. Zhang J, Baran J, Cros A, Guberman JM, Haider S, Hsu J, et al. International Cancer Genome Consortium Data Portal–a one-stop shop for cancer genomics data. Database. 2011;2011:1–10.

    Google Scholar 

  33. Schulze K, Imbeaud S, eacute EL, Alexandrov LB, Calderaro J, Rebouissou S, et al. Exome sequencing of hepatocellular carcinomas identifies new mutational signatures and potential therapeutic targets. Nat Genet. 2015;47:1–10.

    Google Scholar 

  34. Ahn S-M, Jang SJ. Genomic portrait of resectable hepatocellular carcinomas: implications of RB1 and FGF19 aberrations for patient stratification. Hepatology. 2014;60:1972–82.

    CAS  PubMed  Google Scholar 

  35. Zheng J, Sadot E, Vigidal JA, Klimstra DS, Balachandran VP, Kingham TP, et al. Characterization of hepatocellular adenoma and carcinoma using microRNA profiling and targeted gene sequencing. PLoS ONE. 2018;13:e0200776.

  36. Fujimoto A, Totoki Y, Abe T, Boroevich KA, Hosoda F, Nguyen HH, et al. Whole-genome sequencing of liver cancers identifies etiological influences on mutation patterns and recurrent mutations in chromatin regulators. Nat Genet. 2012;44:760–4.

    CAS  PubMed  Google Scholar 

  37. Knight M, Lee S, Das GC. Activation of the insulin-like growth factor II transcription by aflatoxin B1 induced p53 mutant 249 is caused by activation of transcription complexes; implications for a gain-of-function during the formation of hepatocellular carcinoma. Oncogene. 2000;19:3717–26.

    Google Scholar 

  38. Huang W-Y, Hsu S-D, Huang H-Y, Sun Y-M, Chou C-H, Weng S-L, et al. MethHC: a database of DNA methylation and gene expression in human cancer. Nucleic Acids Res. 2014;43:D856–D861.

    PubMed  PubMed Central  Google Scholar 

  39. Shaw RJ, Cantley LCRas. PI(3)K and mTOR signaling controls tumor cell growth. Nature. 2006;441:424–30.

    CAS  PubMed  Google Scholar 

  40. Wang J, Fedoseienko A, Chen B, Burstein E, Jia D, Billadeau DD. Endosomal receptor trafficking: retromer and beyond. Traffic. 2018;19:578–90.

    CAS  PubMed  PubMed Central  Google Scholar 

  41. Small SA, Kent K, Pierce A, Leung C, Kang MS, Okada H, et al. Model-guided microarray implicates the retromer complex in Alzheimer’s disease. Ann Neurol. 2005;58:909–19.

    CAS  PubMed  Google Scholar 

  42. Deng H, Gao K, Jankovic J. The VPS35 gene and Parkinson’s disease. Mov Disord. 2013;28:569–75.

    CAS  PubMed  Google Scholar 

  43. Temkin P, Morishita W, Goswami D, Arendt K, Chen L, Malenka R. The retromer supports AMPA receptor trafficking during LTP. Neuron. 2017;94:74–82.

    CAS  PubMed  Google Scholar 

  44. McGough IJ, Steinberg F, Jia D, Barbuti PA, McMillan KJ, Heesom KJ, et al. Retromer binding to FAM21 and the WASH complex is perturbed by the parkinson disease-linked VPS35(D620N) mutation. Curr Biol. 2014;24:1670–6.

    CAS  PubMed  PubMed Central  Google Scholar 

  45. Franch-Marro X, Wendler F, Guidato S, Griffith J, Baena-Lopez A, Itasaki N, et al. Wingless secretion requires endosome-to-golgi retrieval of Wntless/Evi/Sprinter by the retromer complex. Nat Cell Biol. 2008;10:170–7.

    CAS  PubMed  Google Scholar 

  46. Yang P-T, Lorenowicz MJ, Silhankova M, Coudreuse DYM, Betist MC, Korswagen HC. Wnt signaling requires retromer-dependent recycling of MIG-14/Wntless in Wnt-producing cells. Dev Cell. 2008;14:140–7.

    CAS  PubMed  Google Scholar 

  47. Belenkaya TY, Wu Y, Tang X, Zhou B, Cheng L, Sharma YV, et al. The retromer complex influences Wnt secretion by recycling wntless from endosomes to the trans-golgi network. Dev Cell. 2008;14:120–31.

    CAS  PubMed  Google Scholar 

  48. Farmer T, Reinecke JB, Xie S, Bahl K, Naslavsky N, Caplan S. Control of mitochondrial homeostasis by endocytic regulatory proteins. J Cell Sci. 2017;130:2359–70.

    CAS  PubMed  PubMed Central  Google Scholar 

  49. Cui Y, Carosi JM, Yang Z, Ariotti N, Kerr MC, Parton RG, et al. Retromer has a selective function in cargo sorting via endosome transport carriers. J Cell Biol. 2019;218:615–31.

    CAS  PubMed  PubMed Central  Google Scholar 

  50. Zhou M, Philips MR. Where no Ras has gone before: VPS35 steers N-Ras through the cytosol. Small GTPases. 2019;10:20–25.

    CAS  PubMed  Google Scholar 

  51. Zhou M, Wiener H, Su W, Zhou Y, Liot C, Ahearn I, et al. VPS35 binds farnesylated N-Ras in the cytosol to regulate N-Ras trafficking. J Cell Biol. 2016;214:445–58.

    CAS  PubMed  PubMed Central  Google Scholar 

  52. Farmer T, O’Neill KL, Naslavsky N, Luo X, Caplan S. Retromer facilitates the localization of Bcl-xL to the mitochondrial outer membrane. Mol Biol Cell. 2019;30:1138–46.

    CAS  PubMed  PubMed Central  Google Scholar 

  53. Qiu W-H, Zhou B-S, Chu P-G, Chen W-G, Chung C, Shih J, et al. Over-expression of fibroblast growth factor receptor 3 in human hepatocellular carcinoma. World J Gastroenterol. 2005;11:5266–72.

    CAS  PubMed  PubMed Central  Google Scholar 

  54. Paur J, Nika L, Maier C, Moscu-Gregor A, Kostka J, Huber D, et al. Fibroblast growth factor receptor 3 isoforms: novel therapeutic targets for hepatocellular carcinoma? Hepatology. 2015;62:1767–78.

    CAS  PubMed  Google Scholar 

  55. Cho JY, Guo C, Torello M, Lunstrum GP, Iwata T, Deng C, et al. Defective lysosomal targeting of activated fibroblast growth factor receptor 3 in achondroplasia. Proc Natl Acad Sci USA. 2004;101:609–14.

    CAS  PubMed  Google Scholar 

  56. Haugsten EM, Sørensen V, Brech A, Olsnes S, Wesche J. Different intracellular trafficking of FGF1 endocytosed by the four homologous FGF receptors. J Cell Sci. 2005;118:3869–81.

    CAS  PubMed  Google Scholar 

  57. Javidi-Sharifi N, Traer E, Martinez J, Gupta A, Taguchi T, Dunlap J, et al. Crosstalk between KIT and FGFR3 promotes gastrointestinal stromal tumor cell growth and drug resistance. Cancer Res. 2015;75:880–91.

    CAS  PubMed  Google Scholar 

  58. Tang X, Feng D, Li M, Zhou J, Li X, Zhao D, et al. Transcriptomic analysis of mRNA-lncRNA-miRNA interactions in hepatocellular carcinoma. Sci Rep. 2019;9:16096.

  59. Liang L, Song L, Yang Y, Tian L, Li X, Wu S, et al. Validation of a multi-omics strategy for prioritizing personalized candidate driver genes. Oncotarget. 2016;7:38440–50.

    PubMed  PubMed Central  Google Scholar 

  60. Gao Q, Wang K, Chen K, Liang L, Zheng Y, Zhang Y, et al. HBx protein-mediated ATOH1 downregulation suppresses ARID2 expression and promotes hepatocellular carcinoma. Cancer Surv. 2017;108:1328–37.

    CAS  Google Scholar 

  61. Pan Q, Long X, Song L, Zhao D, Li X, Li D, et al. Transcriptome sequencing identified hub genes for hepatocellular carcinoma by weighted-gene co-expression analysis. Oncotarget. 2016;7:38487–99.

    PubMed  PubMed Central  Google Scholar 

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Acknowledgements

We thank Dr. T-C He (University of Chicago, Chicago, IL) for providing the plasmids pAdEasy system, Dr. Ding Xue (School of Life Sciences, Tsinghua University) for supplying the CRISPR/Cas9 system, and Ms Yihong Sun and Ms Fang Huang for preparing the Supplementary materials.

Funding

This work was funded by the China National Natural Science Foundation (no. 81672780, KD, nos. 81872270 and 81572683, NT, and 81602417, KW), the Major National S&T program (2017ZX10202203-004 to NT), the Recruitment Program of Global Youth Experts in China (KD), the program of Artificial Intelligence in Medicine of CQ CSTC (ZHYX2019004, KD), Natural Science Foundation Project of CQ CSTC (cstc2018jcyjAX0254 to NT), the Program for Innovation Team of Higher Education in Chongqing (grant no. CXTDX201601015), the Leading Talent Program of CQ CSTC (grant no. CSTCCXLJRC201719 to NT) and Talent Development Program of CQMU for Postgraduate (grant no. BJRC201728).

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  1. These authors contributed equally: Guiji Zhang, Xia Tang, Li Liang

Authors and Affiliations

  1. Key Laboratory of Molecular Biology for Infectious Diseases (Ministry of Education), Institute for Viral Hepatitis, Department of Infectious Diseases, The Second Affiliated Hospital, Chongqing Medical University, Chongqing, China

    Guiji Zhang, Xia Tang, Li Liang, Yaqiu Zheng, Kai Wang & Ni Tang

  2. Department of Bioinformatics, School of Basic Medicine, Chongqing Medical University, Chongqing, China

    Xia Tang, Wanfeng Zhang & Keyue Ding

  3. Department of Hepatobiliary Surgery, The First Affiliated Hospital, Chongqing Medical University, Chongqing, China

    Dewei Li

  4. Department of Oncology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China

    Xiaoyuan Li

  5. Department of Pathology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China

    Dachun Zhao

  6. Medical Genetic Institute of Henan Province, Henan Provincial Key Laboratory of Genetic Diseases and Functional Genomics, Henan Provincial People’s Hospital, People’s Hospital of Zhengzhou University, People’s Hospital of Henan University, Zhengzhou, Henan, China

    Yanhong Chen & Bingtao Hao

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Contributions

GZ and LL performed in vitro and in vivo experiments; XT and KD performed data analysis; WZ participated in bioinformatics analysis; YC conducted FACS analysis; YZ generated recombinant adenoviruses; DL and XL collected clinical samples; DZ performed pathological review; BH and KW participated in the discussion and design; GZ, XT, and KD wrote the manuscript with input from BH and NT; and KD and NT conceived and designed the study. All authors read and approved the final manuscript.

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Correspondence to Kai Wang, Ni Tang or Keyue Ding.

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The collection of human tumor samples and the protocols for the investigations were approved by the Institutional Review Board (IRB) in each site where the patients were recruited.

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Written informed consent was obtained from the patients. All animal studies were conducted according to the animal protocol approved by Chongqing Medical University (2017012).

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Zhang, G., Tang, X., Liang, L. et al. DNA and RNA sequencing identified a novel oncogene VPS35 in liver hepatocellular carcinoma. Oncogene 39, 3229–3244 (2020). https://doi.org/10.1038/s41388-020-1215-6

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