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The role of CXCL8 and CCNB1 in predicting hepatocellular carcinoma in the context of cirrhosis: implications for early detection and immune-based therapies

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Abstract

Background

Cirrhosis is a serious condition characterized by the replacement of healthy liver tissue with scar tissue, which can progress to liver failure if left untreated. Hepatocellular carcinoma (HCC) is a concerning complication of cirrhosis. It can be challenge to identify individuals with cirrhosis who are at high risk of developing HCC, particularly in the absence of known risk factors.

Methods

In this study, statistical and bioinformatics methods were utilized to construct a protein–protein interaction network and identify disease-related hub genes. We analyzed two hub genes, CXCL8 and CCNB1, and developed a mathematical model to predict the likelihood of developing HCC in individuals with cirrhosis. We also investigated immune cell infiltration, functional analysis under ontology terms, pathway analysis, distinct clusters of cells, and protein–drug interactions.

Results

The results indicated that CXCL8 and CCNB1 were associated with the development of cirrhosis-induced HCC. A prognostic model based on these two genes was able to predict the occurrence and survival time of HCC. In addition, the candidate drugs were also discovered based on our model.

Conclusion

The findings offer the potential for earlier detection of cirrhosis-induced HCC and provide a new instrument for clinical diagnosis, prognostication, and the development of immunological medications. This study also identified distinct clusters of cells in HCC patients using UMAP plot analysis and analyzed the expression of CXCL8 and CCNB1 within these cells, indicating potential therapeutic opportunities for targeted drug therapies to benefit HCC patients.

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Data availability

The datasets analysed during the current study are available from the corresponding author on reasonable request.

References

  • Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, Cherry JM et al (2000) Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat Genet 25(1):25–29

    CAS  PubMed  PubMed Central  Google Scholar 

  • Barrett T, Wilhite SE, Ledoux P, Evangelista C, Kim IF, Tomashevsky M et al (2013) NCBI GEO: archive for functional genomics data sets-update. Nucleic Acids Res 41(Database issue):D991–D995

    CAS  PubMed  Google Scholar 

  • Bidkhori G, Benfeitas R, Klevstig M, Zhang C, Nielsen J, Uhlen M et al (2018) Metabolic network-based stratification of hepatocellular carcinoma reveals three distinct tumor subtypes. Proc Natl Acad Sci USA 115(50):E11874–E11883

    CAS  PubMed  PubMed Central  Google Scholar 

  • Blake JA, Christie KR, Dolan ME, Drabkin HJ, Hill DP, Ni L, Sitnikov D, Burgess S, Buza T, Gresham C, McCarthy F, Pillai L, Wang H, Carbon S, Dietze H, Lewis SE, Mungall CJ, Munoz-Torres MC, Feuermann M, Gaudet P, Basu S, Chisholm RL, Dodson RJ, Fey P, Mi H, Thomas PD, Muruganujan A, Poudel S, Hu JC, Aleksander SA, McIntosh BK, Renfro DP, Siegele DA, Attrill H, Brown NH, Tweedie S, Lomax J, Osumi-Sutherland D, Parkinson H, Roncaglia P, Lovering RC, Talmud PJ, Humphries SE, Denny P, Campbell NH, Foulger RE, Chibucos MC, Giglio MG, Chang HY, Finn R, Fraser M, Mitchell A, Nuka G, Pesseat S, Sangrador A, Scheremetjew M, Young SY, Stephan R, Harris MA, Oliver SG, Rutherford K, Wood V, Bahler J, Lock A, Kersey PJ, McDowall MD, Staines DM, Dwinell M, Shimoyama M, Laulederkind S, Hayman GT, Wang SJ, Petri V, Deustachio P, Matthews L, Balakrishnan R, Binkley G, Cherry JM, Costanzo MC, Demeter J, Dwight SS, Engel SR, Hitz BC, Inglis DO, Lloyd P, Miyasato SR, Paskov K, Roe G, Simison M, Nash RS, Skrzypek MS, Weng S, Wong ED, Berardini TZ, Li D, Huala E, Argasinska J, Arighi C, Auchincloss A, Axelsen K, Argoud-Puy G, Bateman A, Bely B, Blatter MC, Bonilla C, Bougueleret L, Boutet E, Breuza L, Bridge A, Britto R, Casals C, Cibrian-Uhalte E, Coudert E, Cusin I, Duek-Roggli P, Estreicher A, Famiglietti L, Gane P, Garmiri P, Gos A, Gruaz-Gumowski N, Hatton-Ellis E, Hinz U, Hulo C, Huntley R, Jungo F, Keller G, Laiho K, Lemercier P, Lieberherr D, MacDougall A, Magrane M, Martin M, Masson P, Mutowo P, O'Donovan C, Pedruzzi I, Pichler K, Poggioli D, Poux S, Rivoire C, Roechert B, Sawford T, Schneider M, Shypitsyna A, Stutz A, Sundaram S, Tognolli M, Wu C, Xenarios I, Chan J, Kishore R, Sternberg PW, Van Auken K, Muller HM, Done J, Li Y, Howe D, Westerfield M (2015) Gene Ontology Consortium: going forward. Nucleic Acids Res 43(Database issue):D1049–D1056

    CAS  Google Scholar 

  • Chen H, Boutros PC (2011) VennDiagram: a package for the generation of highly-customizable Venn and Euler diagrams in R. BMC Bioinform 12:35

    Google Scholar 

  • Chin CH, Chen SH, Wu HH, Ho CW, Ko MT, Lin CY (2014) cytoHubba: identifying hub objects and sub-networks from complex interactome. BMC Syst Biol 8(Suppl 4):S11

    PubMed  PubMed Central  Google Scholar 

  • Cox DR (1972) Regression models and life-tables. J R Stat Soc Ser B (methodol) 34(2):187–202

    Google Scholar 

  • Fernando RI, Castillo MD, Litzinger M, Hamilton DH, Palena C (2011) IL-8 signaling plays a critical role in the epithelial–mesenchymal transition of human carcinoma cells IL-8 signaling in brachyury-induced tumor progression. Can Res 71(15):5296–5306

    CAS  Google Scholar 

  • Forner A, Llovet JM, Bruix J (2012) Hepatocellular carcinoma. Lancet (london, England) 379(9822):1245–1255

    PubMed  Google Scholar 

  • Forner A, Reig M, Bruix J (2018) Hepatocellular carcinoma. Lancet (london, England) 391(10127):1301–1314

    PubMed  Google Scholar 

  • Fu T, Dai LJ, Wu SY, Xiao Y, Ma D, Jiang YZ et al (2021) Spatial architecture of the immune microenvironment orchestrates tumor immunity and therapeutic response. J Hematol Oncol 14(1):98

    PubMed  PubMed Central  Google Scholar 

  • Gajewski TF, Schreiber H, Fu YX (2013) Innate and adaptive immune cells in the tumor microenvironment. Nat Immunol 14(10):1014–1022

    CAS  PubMed  PubMed Central  Google Scholar 

  • Giannelli G, Koudelkova P, Dituri F, Mikulits W (2016) Role of epithelial to mesenchymal transition in hepatocellular carcinoma. J Hepatol 65(4):798–808

    CAS  PubMed  Google Scholar 

  • Hammond ME, Lapointe GR, Feucht PH, Hilt S, Gallegos CA, Gordon CA et al (1995) IL-8 induces neutrophil chemotaxis predominantly via type I IL-8 receptors. J Immunol (baltimore, Md: 1950). 155(3):1428–1433

    CAS  Google Scholar 

  • Han Y, Wang Y, Dong X, Sun D, Liu Z, Yue J et al (2023) TISCH2: expanded datasets and new tools for single-cell transcriptome analyses of the tumor microenvironment. Nucleic Acids Res 51(D1):D1425–D1431

    PubMed  Google Scholar 

  • Iasonos A, Schrag D, Raj GV, Panageas KS (2008) How to build and interpret a nomogram for cancer prognosis. J Clin Oncol off J Am Soc Clin Oncol 26(8):1364–1370

    Google Scholar 

  • Ito K, Murphy D (2013) Application of ggplot2 to pharmacometric graphics. CPT Pharmacomet Syst Pharmacol 2(10):e79

    CAS  Google Scholar 

  • Kamarudin AN, Cox T, Kolamunnage-Dona R (2017) Time-dependent ROC curve analysis in medical research: current methods and applications. BMC Med Res Methodol 17(1):53

    PubMed  PubMed Central  Google Scholar 

  • La Vecchia C, Negri E, Cavalieri d’Oro L, Franceschi S (1998) Liver cirrhosis and the risk of primary liver cancer. Eur J Cancer Prev off J Eur Cancer Prev Organ (ECP) 7(4):315–320

    Google Scholar 

  • Lamouille S, Xu J, Derynck R (2014) Molecular mechanisms of epithelial-mesenchymal transition. Nat Rev Mol Cell Biol 15(3):178–196

    CAS  PubMed  PubMed Central  Google Scholar 

  • Lánczky A, Győrffy B (2021) Web-based survival analysis tool tailored for medical research (KMplot): development and implementation. J Med Internet Res 23(7):e27633

    PubMed  PubMed Central  Google Scholar 

  • Lei X, Lei Y, Li JK, Du WX, Li RG, Yang J et al (2020) Immune cells within the tumor microenvironment: Biological functions and roles in cancer immunotherapy. Cancer Lett 470:126–133

    CAS  PubMed  Google Scholar 

  • Li X, Huang L, Leng X (2018) Analysis of prognostic factors of more/equal to10 years of survival for liver cancer patients after liver transplantation. J Cancer Res Clin Oncol 144(12):2465–2474

    CAS  PubMed  PubMed Central  Google Scholar 

  • Li B, Cheng J, Wang H, Zhao S, Zhu H, Li C et al (2019) CCNB1 affects cavernous sinus invasion in pituitary adenomas through the epithelial-mesenchymal transition. J Transl Med 17(1):336

    PubMed  PubMed Central  Google Scholar 

  • Maeser D, Gruener RF, Huang RS (2021) oncoPredict: an R package for predicting in vivo or cancer patient drug response and biomarkers from cell line screening data. Brief Bioinform. https://doi.org/10.1093/bib/bbab260

    Article  PubMed  PubMed Central  Google Scholar 

  • Malumbres M, Barbacid M (2005) Mammalian cyclin-dependent kinases. Trends Biochem Sci 30(11):630–641

    CAS  PubMed  Google Scholar 

  • Marrero JA (2006) Hepatocellular carcinoma. Curr Opin Gastroenterol 22(3):248–253

    PubMed  Google Scholar 

  • Maxwell PJ, Gallagher R, Seaton A, Wilson C, Scullin P, Pettigrew J et al (2007) HIF-1 and NF-kappaB-mediated upregulation of CXCR1 and CXCR2 expression promotes cell survival in hypoxic prostate cancer cells. Oncogene 26(52):7333–7345

    CAS  PubMed  Google Scholar 

  • Newman AM, Liu CL, Green MR, Gentles AJ, Feng W, Xu Y et al (2015) Robust enumeration of cell subsets from tissue expression profiles. Nat Methods 12(5):453–457

    CAS  PubMed  PubMed Central  Google Scholar 

  • Pardoll DM (2012) The blockade of immune checkpoints in cancer immunotherapy. Nat Rev Cancer 12(4):252–264

    CAS  PubMed  PubMed Central  Google Scholar 

  • Powell DR, Huttenlocher A (2016) Neutrophils in the tumor microenvironment. Trends Immunol 37(1):41–52

    CAS  PubMed  Google Scholar 

  • Qian BZ, Pollard JW (2010) Macrophage diversity enhances tumor progression and metastasis. Cell 141(1):39–51

    CAS  PubMed  PubMed Central  Google Scholar 

  • Ritchie ME, Phipson B, Wu D, Hu Y, Law CW, Shi W et al (2015) limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res 43(7):e47

    PubMed  PubMed Central  Google Scholar 

  • Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D et al (2003) Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res 13(11):2498–2504

    CAS  PubMed  PubMed Central  Google Scholar 

  • Shen H, Wu H, Sun F, Qi J, Zhu Q (2021) A novel four-gene of iron metabolism-related and methylated for prognosis prediction of hepatocellular carcinoma. Bioengineered 12(1):240–251

    CAS  PubMed  Google Scholar 

  • Si T, Huang Z, Jiang Y, Walker-Jacobs A, Gill S, Hegarty R et al (2021) Expression levels of three key genes CCNB1, CDC20, and CENPF in HCC are associated with antitumor immunity. Front Oncol 11:738841

    CAS  PubMed  PubMed Central  Google Scholar 

  • Subramanian A, Tamayo P, Mootha VK, Mukherjee S, Ebert BL, Gillette MA et al (2005) Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci USA 102(43):15545–15550

    CAS  PubMed  PubMed Central  Google Scholar 

  • Tang Z, Li C, Kang B, Gao G, Li C, Zhang Z (2017) GEPIA: a web server for cancer and normal gene expression profiling and interactive analyses. Nucleic Acids Res 45(W1):W98-w102

    CAS  PubMed  PubMed Central  Google Scholar 

  • Van Calster B, Wynants L, Verbeek JFM, Verbakel JY, Christodoulou E, Vickers AJ et al (2018) Reporting and interpreting decision curve analysis: a guide for investigators. Eur Urol 74(6):796–804

    PubMed  PubMed Central  Google Scholar 

  • Van Calster B, McLernon DJ, van Smeden M, Wynants L, Steyerberg EW (2019) Calibration: the Achilles heel of predictive analytics. BMC Med 17(1):230

    PubMed  PubMed Central  Google Scholar 

  • Villanueva A (2019) Hepatocellular carcinoma. N Engl J Med 380(15):1450–1462

    CAS  PubMed  Google Scholar 

  • Waugh DJ, Wilson C (2008) The interleukin-8 pathway in cancer. Clin Cancer Res off J Am Assoc Cancer Res 14(21):6735–6741

    CAS  Google Scholar 

  • Wilkerson MD, Hayes DN (2010) ConsensusClusterPlus: a class discovery tool with confidence assessments and item tracking. Bioinformatics (oxford, England) 26(12):1572–1573

    CAS  PubMed  Google Scholar 

  • Yu G, Wang LG, Han Y, He QY (2012) clusterProfiler: an R package for comparing biological themes among gene clusters. OMICS 16(5):284–287

    CAS  PubMed  PubMed Central  Google Scholar 

  • Zhang EL, Liang BY, Chen XP, Huang ZY (2015) Severity of liver cirrhosis: a key role in the selection of surgical modality for Child-Pugh A hepatocellular carcinoma. World J Surg Oncol 13:148

    PubMed  PubMed Central  Google Scholar 

  • Zinkernagel AS, Timmer AM, Pence MA, Locke JB, Buchanan JT, Turner CE et al (2008) The IL-8 protease SpyCEP/ScpC of group A Streptococcus promotes resistance to neutrophil killing. Cell Host Microbe 4(2):170–178

    CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgement

We would like to express our gratitude to the patients who generously donated their tissue samples and our sincere appreciation to the GEO database for providing the valuable data used in this study. We would also like to thank Qingyuan Sun’s parents for their unwavering support and encouragement throughout the duration of this project.

Funding

This work is supported by Young Scientists Fund of the National Natural Science Foundation of China (82201383), Project funded by China Postdoctoral Science Foundation (2022M711319), and Natural Science Foundation of Shandong Province China (ZR2021MH037).

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Authors and Affiliations

  1. Department of Physiology, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, 250012, Shandong, China

    Qingyuan Sun, Ran An, Jingxin Li, Chuanyong Liu, Menggeer Wang & Yanqing Wang

  2. Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, USA

    Yanqing Wang

  3. Department of Rehabilitation, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, 250021, Shandong, China

    Chao Wang

  4. Science and Technology Innovation Center, Shandong First Medical University, Jinan, 250021, Shandong, China

    Chuanyong Liu

Authors
  1. Qingyuan Sun
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  2. Ran An
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  3. Jingxin Li
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  4. Chuanyong Liu
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  6. Chao Wang
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Contributions

Conceptualization, YW; data curation, QS; funding acquisition, CW and YW; investigation, RA and MW; methodology, QS and RA; project administration, YW; resources, JL, CL, and YW; software, QS; supervision, JL, CL, and YW; validation, RA; visualization, QS, JL, and YW; writing—original draft, QS; writing—review & editing, CW and YW.

Corresponding authors

Correspondence to Chao Wang or Yanqing Wang.

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Sun, Q., An, R., Li, J. et al. The role of CXCL8 and CCNB1 in predicting hepatocellular carcinoma in the context of cirrhosis: implications for early detection and immune-based therapies. J Cancer Res Clin Oncol 149, 11471–11489 (2023). https://doi.org/10.1007/s00432-023-05004-6

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