Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Genomic and transcriptomic profiling of hepatoid adenocarcinoma of the stomach

Oncogene volume 40, pages 5705–5717 (2021)Cite this article

Subjects

Abstract

Hepatoid adenocarcinoma of the stomach (HAS), a rare subtype of gastric cancer (GC), has a low incidence but a high mortality rate. Little is known about the molecular features of HAS. Here we applied whole-exome sequencing (WES) on 58 tumours and the matched normal controls from 54 HAS patients, transcriptome sequencing on 30 HAS tumours, and single-cell RNA sequencing (scRNA-seq) on one HAS tumour. Our results reveal that the adenocarcinomatous component and hepatocellular-like component of the same HAS tumour originate monoclonally, and HAS is likely to initiate from pluripotent precursor cells. HAS has high stemness and high methionine cycle activity compared to classical GC. Two genes in the methionine cycle, MAT2A, and AHCY are potential targets for HAS treatments. We provide the first integrative genomic profiles of HAS, which may facilitate its diagnosis, prognosis, and treatment.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on SpringerLink
  • Instant access to the full article PDF.

USD 39.95

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Research schematic.
Fig. 2: Genomic landscape.
Fig. 3: Genomic comparison.
Fig. 4: Branched evolution of HAS.
Fig. 5: Transcriptomic analysis.
Fig. 6: Potential drug-targeting pathways.
Fig. 7: Single-cell RNA analyses of HAS.

Similar content being viewed by others

Data availability

The raw sequence data reported in this paper have been deposited in the Genome Sequence Archive in BIG Data Center, Beijing Institute of Genomics (BIG), Chinese Academy of Sciences, under accession numbers HRA000077 (https://bigd.big.ac.cn/gsa-human/). Data are available upon reasonable request.

Code availability

The computer codes used to generate results in this study are available upon reasonable request.

References

  1. Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2018;68:394–424.

    Article  PubMed  Google Scholar 

  2. Lauren P. The two histological main types of gastric carcinoma: diffuse and so-called intestinal-type carcinoma. attempt Histo-Clin classification Acta Pathol Microbiol Scand. 1965;64:31–49.

    Article  CAS  PubMed  Google Scholar 

  3. Ishikura H, Kirimoto K, Shamoto M, Miyamoto Y, Yamagiwa H, Itoh T, et al. Hepatoid adenocarcinomas of the stomach: an analysis of seven cases. Cancer. 1986;58:119–26.

    Article  CAS  PubMed  Google Scholar 

  4. Su JS, Chen YT, Wang RC, Wu CY, Lee SW, Lee TY. Clinicopathological characteristics in the differential diagnosis of hepatoid adenocarcinoma: a literature review. World J Gastroenterol. 2013;19:321–7.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Liu X, Cheng Y, Sheng W, Lu H, Xu X, Xu Y, et al. Analysis of clinicopathologic features and prognostic factors in hepatoid adenocarcinoma of the stomach. Am J Surg Pathol. 2010;34:1465–71.

    Article  PubMed  Google Scholar 

  6. Wang Y, Sun L, Li Z, Gao J, Ge S, Zhang C, et al. Hepatoid adenocarcinoma of the stomach: a unique subgroup with distinct clinicopathological and molecular features. Gastric Cancer. 2019;22:1183–92.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Totoki Y, Tatsuno K, Covington KR, Ueda H, Creighton CJ, Kato M, et al. Trans-ancestry mutational landscape of hepatocellular carcinoma genomes. Nat Genet. 2014;46:1267–73.

    Article  CAS  PubMed  Google Scholar 

  8. Wang K, Yuen ST, Xu J, Lee SP, Yan HH, Shi ST, et al. Whole-genome sequencing and comprehensive molecular profiling identify new driver mutations in gastric cancer. Nat Genet. 2014;46:573–82.

    Article  CAS  PubMed  Google Scholar 

  9. Qing T, Zhu S, Suo C, Zhang L, Zheng Y, Shi L. Somatic mutations in ZFHX4 gene are associated with poor overall survival of Chinese esophageal squamous cell carcinoma patients. Sci Rep. 2017;7:4951.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  10. Scholnick SB, Richter TM. The role of CSMD1 in head and neck carcinogenesis. Genes Chromosomes Cancer. 2003;38:281–3.

    Article  CAS  PubMed  Google Scholar 

  11. Liu P, Morrison C, Wang L, Xiong D, Vedell P, Cui P, et al. Identification of somatic mutations in non-small cell lung carcinomas using whole-exome sequencing. Carcinogenesis. 2012;33:1270–6.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  12. Kim JE, Singh RR, Cho-Vega JH, Drakos E, Davuluri Y, Khokhar FA, et al. Sonic hedgehog signaling proteins and ATP-binding cassette G2 are aberrantly expressed in diffuse large B-cell lymphoma. Mod Pathol. 2009;22:1312–20.

    Article  CAS  PubMed  Google Scholar 

  13. Lan S, Li H, Liu Y, Ma L, Liu X, Liu Y, et al. Somatic mutation of LRP1B is associated with tumor mutational burden in patients with lung cancer. Lung Cancer. 2019;132:154–6.

    Article  PubMed  Google Scholar 

  14. 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.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Takahashi K, Tanabe K, Ohnuki M, Narita M, Ichisaka T, Tomoda K, et al. Induction of pluripotent stem cells from adult human fibroblasts by defined factors. Cell. 2007;131:861–72.

    Article  CAS  PubMed  Google Scholar 

  16. Yonemura Y, Endo Y, Bandou E, Kawamura T, Sasaki T. Participation of hepatocyte growth factor (HGF) and MET autocrine/paracrine loop in liver metastasis of gastric cancer. Eksperimentalʹnai͡a Onkologii͡a. 2002;24:89–98.

    CAS  Google Scholar 

  17. Christensen S, Van der Roest B, Besselink N, Janssen R, Boymans S, Martens JWM, et al. 5-Fluorouracil treatment induces characteristic T > G mutations in human cancer. Nat Commun. 2019;10:4571.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  18. Gao Q, Zhu H, Dong L, Shi W, Chen R, Song Z, et al. Integrated proteogenomic characterization of HBV-related hepatocellular carcinoma. Cell. 2019;179:561–77.

    Article  CAS  PubMed  Google Scholar 

  19. Kim E, Lisby A, Ma C, Lo N, Ehmer U, Hayer KE, et al. Promotion of growth factor signaling as a critical function of beta-catenin during HCC progression. Nat Commun. 2019;10:1909.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  20. Wang K, Kan J, Yuen ST, Shi ST, Chu KM, Law S, et al. Exome sequencing identifies frequent mutation of ARID1A in molecular subtypes of gastric cancer. Nat Genet. 2011;43:1219–23.

    Article  CAS  PubMed  Google Scholar 

  21. Khemlina G, Ikeda S, Kurzrock R. The biology of Hepatocellular carcinoma: implications for genomic and immune therapies. Mol Cancer. 2017;16:149.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  22. Taniguchi K, Roberts LR, Aderca IN, Dong X, Qian C, Murphy LM, et al. Mutational spectrum of β-catenin, AXIN1, and AXIN2 in hepatocellular carcinomas and hepatoblastomas. Oncogene. 2002;21:4863–71.

    Article  CAS  PubMed  Google Scholar 

  23. Jiang H, Cao HJ, Ma N, Bao WD, Wang JJ, Chen TW, et al. Chromatin remodeling factor ARID2 suppresses hepatocellular carcinoma metastasis via DNMT1-Snail axis. Proc Natl Acad Sci USA. 2020;117:4770–80.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Zheng C, Zheng L, Yoo JK, Guo H, Zhang Y, Guo X, et al. Landscape of infiltrating T cells in liver cancer revealed by single-cell sequencing. Cell. 2017;169:1342–56.

    Article  CAS  PubMed  Google Scholar 

  25. Cancer Genome Atlas Research Network. Electronic address wbe, Cancer Genome Atlas Research N. Comprehensive and integrative genomic characterization of hepatocellular carcinoma. Cell. 2017;169:1327–41.

    Article  CAS  Google Scholar 

  26. DeLaForest A, Quryshi AF, Frolkis TS, Franklin OD, Battle MA. GATA4 is required for budding morphogenesis of posterior foregut endoderm in a model of human stomach development. Front Med. 2020;7:44.

  27. Bort R, Signore M, Tremblay K, Martinez Barbera JP, Zaret KS. Hex homeobox gene controls the transition of the endoderm to a pseudostratified, cell emergent epithelium for liver bud development. Dev Biol. 2006;290:44–56.

  28. Tschaharganeh DF, Xue W, Calvisi DF, Evert M, Michurina TV, Dow LE, et al. p53-dependent Nestin regulation links tumor suppression to cellular plasticity in liver cancer. Cell. 2014;158:579–92.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Xue R, Chen L, Zhang C, Fujita M, Li R, Yan SM, et al. Genomic and transcriptomic profiling of combined hepatocellular and intrahepatic cholangiocarcinoma reveals distinct molecular subtypes. Cancer Cell. 2019;35:932–47.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Krebs AM, Mitschke J, Lasierra Losada M, Schmalhofer O, Boerries M, Busch H, et al. The EMT-activator Zeb1 is a key factor for cell plasticity and promotes metastasis in pancreatic cancer. Nat Cell Biol. 2017;19:518–29.

    Article  CAS  PubMed  Google Scholar 

  31. Pastushenko I, Blanpain C. EMT transition states during tumor progression and metastasis. Trends Cell Biol. 2019;29:212–26.

    Article  CAS  PubMed  Google Scholar 

  32. Xu W, Wang S, Chen Q, Zhang Y, Ni P, Wu X, et al. TXNL1-XRCC1 pathway regulates cisplatin-induced cell death and contributes to resistance in human gastric cancer. Cell Death Dis. 2014;5:e1055.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Lin L, Li X, Pan C, Lin W, Shao R, Liu Y, et al. ATXN2L upregulated by epidermal growth factor promotes gastric cancer cell invasiveness and oxaliplatin resistance. Cell Death Dis. 2019;10:173.

    Article  PubMed  PubMed Central  Google Scholar 

  34. Shiraki N, Shiraki Y, Tsuyama T, Obata F, Miura M, Nagae G, et al. Methionine metabolism regulates maintenance and differentiation of human pluripotent stem cells. Cell Metab. 2014;19:780–94.

    Article  CAS  PubMed  Google Scholar 

  35. Harvey A, Caretti G, Moresi V, Renzini A, Adamo S. Interplay between metabolites and the epigenome in regulating embryonic and adult stem cell potency and maintenance. Stem Cell Rep. 2019;13:573–89.

    Article  CAS  Google Scholar 

  36. Gaude E, Frezza C. Tissue-specific and convergent metabolic transformation of cancer correlates with metastatic potential and patient survival. Nat Commun. 2016;7:13041.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Wang Z, Yip LY, Lee JHJ, Wu Z, Chew HY, Chong PKW, et al. Methionine is a metabolic dependency of tumor-initiating cells. Nat Med. 2019;25:825–37.

    Article  CAS  PubMed  Google Scholar 

  38. Gao X, Sanderson SM, Dai Z, Reid MA, Cooper DE, Lu M, et al. Dietary methionine influences therapy in mouse cancer models and alters human metabolism. Nature. 2019;572:397–401.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Reid MA, Allen AE, Liu S, Liberti MV, Liu P, Liu X, et al. Serine synthesis through PHGDH coordinates nucleotide levels by maintaining central carbon metabolism. Nature Commun. 2018;9:5442.

  40. Komninou D, Leutzinger Y, Reddy BS, Richie JP Jr. Methionine restriction inhibits colon carcinogenesis. Nutr Cancer. 2006;54:202–8.

    Article  CAS  PubMed  Google Scholar 

  41. Zhang P, Yang M, Zhang Y, Xiao S, Lai X, Tan A, et al. Dissecting the single-cell transcriptome network underlying gastric premalignant lesions and early gastric cancer. Cell Rep. 2019;27:1934–47.

    Article  CAS  PubMed  Google Scholar 

  42. Ding X, Deng G, Liu J, Liu B, Yuan F, Yang X, et al. GOLM1 silencing inhibits the proliferation and motility of human glioblastoma cells via the Wnt/beta-catenin signaling pathway. Brain Res. 2019;1717:117–26.

    Article  CAS  PubMed  Google Scholar 

  43. Comoglio PM, Trusolino L, Boccaccio C. Known and novel roles of the MET oncogene in cancer: a coherent approach to targeted therapy. Nat Rev Cancer. 2018;18:341–58.

    Article  CAS  PubMed  Google Scholar 

  44. Kim K-M, Bilous M, Chu K-M, Kim B-S, Kim W-H, Park YS, et al. Human epidermal growth factor receptor 2 testing in gastric cancer: Recommendations of an Asia-Pacific Task Force. Asia-Pac J Clin Oncol. 2014;10:297–307.

    Article  PubMed  PubMed Central  Google Scholar 

  45. Apte RS, Chen DS, Ferrara N. VEGF in Signaling and Disease: Beyond Discovery and Development. Cell. 2019;176:1248–64.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Puram SV, Tirosh I, Parikh AS, Patel AP, Yizhak K, Gillespie S, et al. Single-cell transcriptomic analysis of primary and metastatic tumor ecosystems in head and neck cancer. Cell. 2017;171:1611–24.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Akazawa Y, Saito T, Hayashi T, Yanai Y, Tsuyama S, Akaike K, et al. Next-generation sequencing analysis for gastric adenocarcinoma with enteroblastic differentiation: emphasis on the relationship with hepatoid adenocarcinoma. Hum Pathol. 2018;78:79–88.

    Article  CAS  PubMed  Google Scholar 

  48. Wang Q, Zou Y, Nowotschin S, Kim SY, Li QV, Soh CL, et al. The p53 family coordinates Wnt and Nodal inputs in mesendodermal differentiation of embryonic stem cells. Cell Stem Cell. 2017;20:70–86.

    Article  CAS  PubMed  Google Scholar 

  49. Fu DJ, Wang L, Chouairi FK, Rose IM, Abetov DA, Miller AD, et al. Gastric squamous-columnar junction contains a large pool of cancer-prone immature osteopontin responsive Lgr5(-)CD44(+) cells. Nat Commun. 2020;11:84.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Nakanishi Y, Seno H, Fukuoka A, Ueo T, Yamaga Y, Maruno T, et al. Dclk1 distinguishes between tumor and normal stem cells in the intestine. Nat Genet. 2013;45:98–103.

    Article  CAS  PubMed  Google Scholar 

  51. Shafiei S, Kalantari E, Saeednejad Zanjani L, Abolhasani M, Asadi Lari MH, Madjd Z. Increased expression of DCLK1, a novel putative CSC maker, is associated with tumor aggressiveness and worse disease-specific survival in patients with bladder carcinomas. Exp Mol Pathol. 2019;108:164–72.

    Article  CAS  PubMed  Google Scholar 

  52. Martin M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet J. 2011;17:3

    Article  Google Scholar 

  53. Li H, Durbin R. Fast and accurate long-read alignment with Burrows-Wheeler transform. Bioinformatics. 2010;26:589–95.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  54. McKenna A, Hanna M, Banks E, Sivachenko A, Cibulskis K, Kernytsky A, et al. The genome analysis toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res. 2010;20:1297–303.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Kim S, Scheffler K, Halpern AL, Bekritsky MA, Noh E, Kallberg M, et al. Strelka2: fast and accurate calling of germline and somatic variants. Nat Methods. 2018;15:591–4.

    Article  CAS  PubMed  Google Scholar 

  56. Cingolani P, Platts A, Wang le L, Coon M, Nguyen T, Wang L, et al. A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff: SNPs in the genome of Drosophila melanogaster strain w1118; iso-2; iso-3. Fly. 2012;6:80–92.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Lawrence MS, Stojanov P, Polak P, Kryukov GV, Cibulskis K, Sivachenko A, et al. Mutational heterogeneity in cancer and the search for new cancer-associated genes. Nature. 2013;499:214–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Alexandrov Ludmil B, Nik-Zainal S, Wedge David C, Campbell Peter J, Stratton, Michael R. Deciphering signatures of mutational processes operative in human cancer. Cell Rep. 2013;3:246–59.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Favero F, Joshi T, Marquard AM, Birkbak NJ, Krzystanek M, Li Q, et al. Sequenza: allele-specific copy number and mutation profiles from tumor sequencing data. Ann Oncol. 2015;26:64–70.

    Article  CAS  PubMed  Google Scholar 

  60. Mermel CH, Schumacher SE, Hill B, Meyerson ML, Beroukhim R, Getz G. GISTIC2.0 facilitates sensitive and confident localization of the targets of focal somatic copy-number alteration in human cancers. Genome Biol. 2011;12:R41.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  61. Sanchez-Vega F, Mina M, Armenia J, Chatila WK, Luna A, La KC, et al. Oncogenic signaling pathways in the cancer genome Atlas. Cell. 2018;173:321–37. e310

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Roth A, Khattra J, Yap D, Wan A, Laks E, Biele J, et al. PyClone: statistical inference of clonal population structure in cancer. Nat Methods. 2014;11:396–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Yu G, Wang LG, Han Y, He QY. clusterProfiler: an R package for comparing biological themes among gene clusters. OMICS. 2012;16:284–7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Malta TM, Sokolov A, Gentles AJ, Burzykowski T, Poisson L, Weinstein JN, et al. Machine learning identifies stemness features associated with oncogenic dedifferentiation. Cell. 2018;173:338–54.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Hänzelmann S, Castelo R, Guinney J. GSVA: gene set variation analysis for microarray and RNA-Seq data. BMC Bioinforma. 2013;14:7.

    Article  Google Scholar 

  66. Gibbons DL, Creighton CJ. Pan-cancer survey of epithelial-mesenchymal transition markers across the Cancer Genome Atlas. Dev Dyn. 2018;247:555–64.

    Article  CAS  PubMed  Google Scholar 

  67. Tang Z, Kang B, Li C, Chen T, Zhang Z. GEPIA2: an enhanced web server for large-scale expression profiling and interactive analysis. Nucleic Acids Res. 2019;47:W556–60.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Stuart T, Butler A, Hoffman P, Hafemeister C, Papalexi E, Mauck WM 3rd, et al. Comprehensive integration of single-cell data. Cell. 2019;177:1888–902.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  69. Patel AP, Tirosh I, Trombetta JJ, Shalek AK, Gillespie SM, Wakimoto H, et al. Single-cell RNA-seq highlights intratumoral heterogeneity in primary glioblastoma. Science. 2014;344:1396–401.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. Newman AM, Steen CB, Liu CL, Gentles AJ, Chaudhuri AA, Scherer F, et al. Determining cell type abundance and expression from bulk tissues with digital cytometry. Nat Biotechnol. 2019;37:773–82.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

This work was financially supported by the National Science and Technology Major Project (2018ZX10302205, 2019YFC1315702), the Guangdong Province Key Research and Development Program (2019B020226002) to F. Bai; Peking University Clinical Scientist Program (BMU2019LCKXJ011); National Science Foundation for Young Scientists of China (No. 81802735); Beijing Youth Talent Plan (No. QML20191101); ‘San Ming’ Project of Shenzhen city, China (No. SZSM201612051) and Beijing Municipal Science and Technology Commission NOVA Program (2010B033).

Author information

Author notes

  1. These authors contributed equally: Ziyang Liu, Anqiang Wang, Yingying Pu, Zhongwu Li.

Authors and Affiliations

  1. Biomedical Pioneering Innovation Center (BIOPIC), School of Life Sciences, Peking University, Beijing, China

    Ziyang Liu, Yingying Pu, Ruidong Xue, Chong Zhang & Fan Bai

  2. Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Department of Gastrointestinal Surgery, Peking University Cancer Hospital and Institute, Beijing, China

    Anqiang Wang, Zhaode Bu & Jiafu Ji

  3. Frontier Science Center for Immunology and Metabolism, Medical Research Institute, School of Medicine, Wuhan University, Wuhan, China

    Yingying Pu

  4. State Key Laboratory Breeding Base of Basic Science of Stomatology (Hubei-MOST) and Key Laboratory for Oral Biomedicine of Ministry of Education (KLOBM), School and Hospital of Stomatology, Wuhan University, Wuhan, China

    Yingying Pu

  5. Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Department of Pathology, Peking University Cancer Hospital and Institute, Beijing, China

    Zhongwu Li

  6. Translational Cancer Research Center, Peking University First Hospital, Beijing, China

    Ruidong Xue

  7. Department of Hepatobilliary Surgery, Beijing Key Surgical Basic Research Laboratory of Liver Cirrhosis and Liver Cancer, Peking University People’s Hospital, Beijing, China

    Xiao Xiang

  8. Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, US

    Jian-Yu E

  9. Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Department of Biobank, Peking University Cancer Hospital and Institute, Beijing, China

    Jiafu Ji

Authors
  1. Ziyang Liu
    View author publications

    Search author on:PubMed Google Scholar

  2. Anqiang Wang
    View author publications

    Search author on:PubMed Google Scholar

  3. Yingying Pu
    View author publications

    Search author on:PubMed Google Scholar

  4. Zhongwu Li
    View author publications

    Search author on:PubMed Google Scholar

  5. Ruidong Xue
    View author publications

    Search author on:PubMed Google Scholar

  6. Chong Zhang
    View author publications

    Search author on:PubMed Google Scholar

  7. Xiao Xiang
    View author publications

    Search author on:PubMed Google Scholar

  8. Jian-Yu E
    View author publications

    Search author on:PubMed Google Scholar

  9. Zhaode Bu
    View author publications

    Search author on:PubMed Google Scholar

  10. Fan Bai
    View author publications

    Search author on:PubMed Google Scholar

  11. Jiafu Ji
    View author publications

    Search author on:PubMed Google Scholar

Contributions

Study conception and supervision: J.J., F.B., and Z.B. Bioinformatic analyses: Z.Y.L. and A.W. Patient enrollment: A.W. Whole-exome sequencing and transcriptome sequencing experiments: Y.P. Histopathological reviews and the H&E and IHC staining: Z.W.L. Data interpretation: Z.Y.L., A.W., Y.P., Z.W.L., R.X., C.Z., X.X., and J.-Y.E. Paper drafting: Z.Y.L and F.B., with the help from all authors.

Corresponding authors

Correspondence to Zhaode Bu, Fan Bai or Jiafu Ji.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Liu, Z., Wang, A., Pu, Y. et al. Genomic and transcriptomic profiling of hepatoid adenocarcinoma of the stomach. Oncogene 40, 5705–5717 (2021). https://doi.org/10.1038/s41388-021-01976-2

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Version of record:

  • Issue date:

  • DOI: https://doi.org/10.1038/s41388-021-01976-2

This article is cited by

Search

Advanced search

Quick links