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Quantitative phosphoproteomics reveals molecular pathway network alterations in human early-stage primary hepatic carcinomas: potential for 3P medical approach

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Abstract

Objective

Hepatic carcinoma is one of the most common types of malignant tumors in the digestive system, and its biological characteristics determine its high rate of metastasis and recurrence after radical resection, leading to a poor prognosis for patients. Increasing evidence demonstrates that phosphoproteins and phosphorylation-mediated molecular pathways influence the occurrence and development of hepatic carcinoma. It is urgent need to develop early-stage biomarkers for improving diagnosis, therapy, medical service, and prognostic assessment. We hypothesize that phosphoproteome and phosphorylation-mediated signaling pathway networks significantly differ in human early-stage primary hepatic carcinomas relative to control liver tissues, which will identify the key differentially phosphorylated proteins and phosphorylation-mediated signaling pathway network alterations in human early-stage primary hepatic carcinoma to innovate predictive diagnosis, prognostic assessment, and personalized medical services and progress beyond the state of the art in the framework of predictive, preventive, and personalized medicine (PPPM).

Methods

Tandem mass tag (TMT)-based quantitative proteomics coupled with TiO2 enrichment of phosphopeptides was used to identify phosphorylation profiling, and bioinformatics was used to analyze the pathways and biological functions of phosphorylation profiling between early-stage hepatic carcinoma tissues and tumor-adjacent normal control tissues. Furthermore, the integrative analysis with transcriptomic data from TCGA database obtained differently expressed genes (DEGs) corresponding to differentially phosphorylated proteins (DPPs) and overall survival (OS)-related DPPs.

Results

A total of 1326 phosphopeptides derived from 858 DPPs in human early-stage primary hepatic carcinoma were identified. KEGG pathway network analysis of 858 DPPs revealed 33 statistically significant signaling pathways, including spliceosome, glycolysis/gluconeogenesis, B-cell receptor signaling pathway, HIF-1 signaling pathway, and fatty acid degradation. Gene Ontology (GO) analysis of 858 DPPs revealed that protein phosphorylation was involved in 57 biological processes, 40 cellular components, and 37 molecular functions. Protein–protein interaction (PPI) network constructed multiple high-combined scores and co-expressed DPPs. Integrative analysis of transcriptomic data and DPP data identified 105 overlapped molecules (DPPs; DEGs) between hepatic carcinoma tissues and control tissues and 125 OS-related DPPs. Overlap** Venn plots showed 14 common molecules among datasets of DPPs, DEGs, and OS-related DDPs, including FTCD, NDRG2, CCT2, PECR, SLC23A2, PNPLA7, ANLN, HNRNPM, HJURP, MCM2, STMN1, TCOF1, TOP2A, and SSRP1. The drug sensitivities of OS-related DPPs were identified, including LMOD1, CAV2, UBE2E2, RAPH1, ANXA5, HDLBP, CUEDC1, APBB1IP, VCL, SRSF10, SLC23A2, EPB41L2, ESR1, PLEKHA4, SAFB2, SMARCAD1, VCAN, PSD4, RDH16, NOP56, MEF2C, BAIAP2L2, NAGS, SRSF2, FHOD3, and STMN1.

Conclusions

Identification and annotation of phosphoproteomes and phosphorylation-mediated signaling pathways in human early-stage primary hepatic carcinoma tissues provided new directions for tumor prevention and treatment, which (i) helps to enrich phosphorylation functional research and develop new biomarkers; (ii) enriches phosphorylation-mediated signaling pathways to gain a deeper understanding of the underlying mechanisms of early-stage primary hepatic carcinoma; and (iii) develops anti-tumor drugs that facilitate targeted phosphorylated sites. We recommend quantitative phosphoproteomics in early-stage primary hepatic carcinoma, which offers great promise for in-depth insight into the molecular mechanism of early-stage primary hepatic carcinoma, the discovery of effective therapeutic targets/drugs, and the construction of reliable phosphorylation-related biomarkers for patient stratification, predictive diagnosis, prognostic assessment, and personalized medical services in the framework of PPPM.

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Data availability

All data and materials are provided in this article, and supplemental materials can be made publicly available.

Code availability

All protein and gene accession codes are available in the Swiss-Prot and Genbank databases.

Abbreviations

AFP:

Alpha-fetoprotein

ATO:

Arsenic trioxide

BP:

Biological processes

CC:

Cellular components

CTLA-4:

Cytotoxic T immune checkpoint suppressor lymphocyte-associated protein 4

DEG:

Differentially expressed genes

FAS:

Fatty acid synthase

GO:

Gene Ontology

HCD:

Higher-energy collisional dissociation

HIF-1:

Hypoxia-inducible factor 1

KEGG:

Kyoto Encyclopedia of Genes and Genomes

LC:

Liquid chromatography

MA:

Megestrol acetate

MF:

Molecular functions

MS/MS:

Tandem mass spectrometry

OS:

Overall survival

PD-1:

Programmed cell death protein 1

PPI:

Protein–protein interaction

PTM:

Post-translational modifications

ROS:

Reactive oxygen species

RS:

Arginine/serine

S:

Serine

SCX:

Strong cation exchange

STK4:

Serine and threonine kinases

T:

Threonine

TCGA:

The Cancer Genome Atlas

TMT:

Tandem mass tag

Y:

Tyrosine

References

  1. Anwanwan D, Singh SK, Singh S, Saikam V, Singh R. Challenges in liver cancer and possible treatment approaches. Biochim Biophys Acta Rev Cancer. 2020;1873:188314. https://doi.org/10.1016/j.bbcan.2019.188314.

    Article  CAS  PubMed  Google Scholar 

  2. Rimassa L, Finn RS, Sangro B. Combination immunotherapy for hepatocellular carcinoma. J Hepatol. 2023. https://doi.org/10.1016/j.jhep.2023.03.003.

    Article  PubMed  Google Scholar 

  3. Lebossé F, Zoulim F. Hepatitis B vaccine and liver cancer. Bull Cancer. 2021;108:90–101. https://doi.org/10.1016/j.bulcan.2020.10.014.

    Article  PubMed  Google Scholar 

  4. Llovet JM, De Baere T, Kulik L, Haber PK, Greten TF, Meyer T, et al. Locoregional therapies in the era of molecular and immune treatments for hepatocellular carcinoma. Nat Rev Gastroenterol Hepatol. 2021;18:293–313. https://doi.org/10.1038/s41575-020-00395-0.

    Article  CAS  PubMed  Google Scholar 

  5. Faivre S, Rimassa L, Finn RS. Molecular therapies for HCC: looking outside the box. J Hepatol. 2020;72:342–52. https://doi.org/10.1016/j.jhep.2019.09.010.

    Article  CAS  PubMed  Google Scholar 

  6. Shu F, **ao H, Li QN, Ren XS, Liu ZG, Hu BW, et al. Epigenetic and post-translational modifications in autophagy: biological functions and therapeutic targets. Signal Transduct Target Ther. 2023;8:32. https://doi.org/10.1038/s41392-022-01300-8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Jiang Y, Sun A, Zhao Y, Ying W, Sun H, Yang X, et al. Proteomics identifies new therapeutic targets of early-stage hepatocellular carcinoma. Nature. 2019;567:257–61. https://doi.org/10.1038/s41586-019-0987-8.

    Article  CAS  PubMed  Google Scholar 

  8. Pan S, Chen R. Pathological implication of protein post-translational modifications in cancer. Mol Aspects Med. 2022;86:101097. https://doi.org/10.1016/j.mam.2022.101097.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Harrington L, Fletcher JM, Heermann T, Woolfson DN, Schwille P. De novo design of a reversible phosphorylation-dependent switch for membrane targeting. Nat Commun. 2021;12:1472. https://doi.org/10.1038/s41467-021-21622-5.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Yang Y, Li S, Wang Y, Zhao Y, Li Q. Protein tyrosine kinase inhibitor resistance in malignant tumors: molecular mechanisms and future perspective. Signal Transduct Target Ther. 2022;7:329. https://doi.org/10.1038/s41392-022-01168-8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Dong Y, Hu H, Zhang X, Zhang Y, Sun X, Wang H, et al. Phosphorylation of PHF2 by AMPK releases the repressive H3K9me2 and inhibits cancer metastasis. Signal Transduct Target Ther. 2023;8:95. https://doi.org/10.1038/s41392-022-01302-6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Zhao J, Tian S, Guo Q, Bao K, Yu G, Wang X, et al. A PARylation-phosphorylation cascade promotes TOPBP1 loading and RPA-RAD51 exchange in homologous recombination. Mol Cell. 2022;82:2571-2587.e9. https://doi.org/10.1016/j.molcel.2022.04.031.

    Article  CAS  PubMed  Google Scholar 

  13. Wu W, Zhou Q, Masubuchi T, Shi X, Li H, Xu X, et al. Multiple signaling roles of CD3ε and its application in CAR-T cell therapy. Cell. 2020;182:855-871.e23. https://doi.org/10.1016/j.cell.2020.07.018.

    Article  CAS  PubMed  Google Scholar 

  14. Zhan X, Li J, Guo Y, Golubnitschaja O. Mass spectrometry analysis of human tear fluid biomarkers specific for ocular and systemic diseases in the context of 3P medicine. EPMA J. 2021;12:449–75. https://doi.org/10.1007/s13167-021-00265-y.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Wang Y, Cheng T, Lu M, Mu Y, Li B, Li X, et al. TMT-based quantitative proteomics revealed follicle-stimulating hormone (FSH)-related molecular characterizations for potentially prognostic assessment and personalized treatment of FSH-positive non-functional pituitary adenomas. EPMA J. 2019;10:395–414. https://doi.org/10.1007/s13167-019-00187-w.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Liu D, Li J, Li N, Lu M, Wen S, Zhan X. Integration of quantitative phosphoproteomics and transcriptomics revealed phosphorylation-mediated molecular events as useful tools for a potential patient stratification and personalized treatment of human nonfunctional pituitary adenomas. EPMA J. 2020;11:419–67. https://doi.org/10.1007/s13167-020-00215-0.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Li N, Zhan X. Integrated genomic analysis of proteasome alterations across 11,057 patients with 33 cancer types: clinically relevant outcomes in framework of 3P medicine. EPMA J. 2021;12:605–27. https://doi.org/10.1007/s13167-021-00256-z.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Yang WS, Zeng XF, Liu ZN, Zhao QH, Tan YT, Gao J, et al. Diet and liver cancer risk: a narrative review of epidemiological evidence. Br J Nutr. 2020;124:330–40. https://doi.org/10.1017/s0007114520001208.

    Article  CAS  PubMed  Google Scholar 

  19. Xue R, Zhang Q, Cao Q, Kong R, **ang X, Liu H, et al. Liver tumour immune microenvironment subtypes and neutrophil heterogeneity. Nature. 2022;612:141–7. https://doi.org/10.1038/s41586-022-05400-x.

    Article  CAS  PubMed  Google Scholar 

  20. Zhao MX, Chen Q, Li F, Fu S, Huang B, Zhao Y. Protein phosphorylation database and prediction tools. Brief Bioinform. 2023;24. https://doi.org/10.1093/bib/bbad090.

  21. Ng CKY, Dazert E, Boldanova T, Coto-Llerena M, Nuciforo S, Ercan C, et al. Integrative proteogenomic characterization of hepatocellular carcinoma across etiologies and stages. Nat Commun. 2022;13:2436. https://doi.org/10.1038/s41467-022-29960-8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Qin L, Cao X, Kaneko T, Voss C, Liu X, Wang G, et al. Dynamic interplay of two molecular switches enabled by the MEK1/2-ERK1/2 and IL-6-STAT3 signaling axes controls epithelial cell migration in response to growth factors. J Biol Chem. 2021;297:101161. https://doi.org/10.1016/j.jbc.2021.101161.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. **a Y, Liu X, Liu B, Zhang X, Tian G. Enhanced antitumor activity of combined megestrol acetate and arsenic trioxide treatment in liver cancer cells. Exp Ther Med. 2018;15:4047–55. https://doi.org/10.3892/etm.2018.5905.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Hall EH, Balsbaugh JL, Rose KL, Shabanowitz J, Hunt DF, Brautigan DL. Comprehensive analysis of phosphorylation sites in Tensin1 reveals regulation by p38MAPK. Mol Cell Proteomics. 2010;9:2853–63. https://doi.org/10.1074/mcp.M110.003665.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Yuan X, Zhang W, He Y, Yuan J, Song D, Chen H, et al. Proteomic analysis of cisplatin- and oxaliplatin-induced phosphorylation in proteins bound to Pt-DNA adducts. Metallomics. 2020;12:1834–40. https://doi.org/10.1039/d0mt00194e.

    Article  CAS  PubMed  Google Scholar 

  26. Meng SS, Gu HW, Zhang T, Li YS, Tang HB. Gradual deterioration of fatty liver disease to liver cancer via inhibition of AMPK signaling pathways involved in energy-dependent disorders, cellular aging, and chronic inflammation. Front Oncol. 2023;13:1099624. https://doi.org/10.3389/fonc.2023.1099624.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Kaihara T, Kawamata H, Imura J, Fujii S, Kitajima K, Omotehara F, et al. Redifferentiation and ZO-1 reexpression in liver-metastasized colorectal cancer: possible association with epidermal growth factor receptor-induced tyrosine phosphorylation of ZO-1. Cancer Sci. 2003;94:166–72. https://doi.org/10.1111/j.1349-7006.2003.tb01414.x.

    Article  CAS  PubMed  Google Scholar 

  28. French SW, Mayer RJ, Bardag-Gorce F, Ingelman-Sundberg M, Rouach H, Neve E, et al. The ubiquitin-proteasome 26s pathway in liver cell protein turnover: effect of ethanol and drugs. Alcohol Clin Exp Res. 2001;25:225s–9s. https://doi.org/10.1097/00000374-200105051-00036.

    Article  CAS  PubMed  Google Scholar 

  29. Stanley RF, Abdel-Wahab O. Dysregulation and therapeutic targeting of RNA splicing in cancer. Nat Cancer. 2022;3:536–46. https://doi.org/10.1038/s43018-022-00384-z.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Sciarrillo R, Wojtuszkiewicz A, Assaraf YG, Jansen G, Kaspers GJL, Giovannetti E, et al. The role of alternative splicing in cancer: From oncogenesis to drug resistance. Drug Resist Updat. 2020;53:100728. https://doi.org/10.1016/j.drup.2020.100728.

    Article  PubMed  Google Scholar 

  31. Zhou HZ, Li F, Cheng ST, Xu Y, Deng HJ, Gu DY, et al. DDX17-regulated alternative splicing that produced an oncogenic isoform of PXN-AS1 to promote HCC metastasis. Hepatology. 2022;75:847–65. https://doi.org/10.1002/hep.32195.

    Article  CAS  PubMed  Google Scholar 

  32. Ye Z, Bing A, Zhao S, Yi S, Zhan X. Comprehensive analysis of spliceosome genes and their mutants across 27 cancer types in 9070 patients: clinically relevant outcomes in the context of 3P medicine. EPMA J. 2022;13:335–50. https://doi.org/10.1007/s13167-022-00279-0.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Guo YE, Manteiga JC, Henninger JE, Sabari BR, Dall’Agnese A, Hannett NM, et al. Pol II phosphorylation regulates a switch between transcriptional and splicing condensates. Nature. 2019;572:543–8. https://doi.org/10.1038/s41586-019-1464-0.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Aubol BE, Adams JA. Recruiting a silent partner for activation of the protein kinase SRPK1. Biochemistry. 2014;53:4625–34. https://doi.org/10.1021/bi500483m.

    Article  CAS  PubMed  Google Scholar 

  35. Chen D, Zhao Z, Chen L, Li Q, Zou J, Liu S. PPM1G promotes the progression of hepatocellular carcinoma via phosphorylation regulation of alternative splicing protein SRSF3. Cell Death Dis. 2021;12:722. https://doi.org/10.1038/s41419-021-04013-y.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Li N, Li H, Wang Y, Cao L, Zhan X. Quantitative proteomics revealed energy metabolism pathway alterations in human epithelial ovarian carcinoma and their regulation by the antiparasite drug ivermectin: data interpretation in the context of 3P medicine. EPMA J. 2020;11:661–94. https://doi.org/10.1007/s13167-020-00224-z.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Yang Z, Yan C, Ma J, Peng P, Ren X, Cai S, et al. Lactylome analysis suggests lactylation-dependent mechanisms of metabolic adaptation in hepatocellular carcinoma. Nat Metab. 2023;5:61–79. https://doi.org/10.1038/s42255-022-00710-w.

    Article  CAS  PubMed  Google Scholar 

  38. Jiang H, Greathouse RL, Tiche SJ, Zhao M, He B, Li Y, et al. Mitochondrial uncoupling induces epigenome remodeling and promotes differentiation in neuroblastoma. Cancer Res. 2023;83:181–94. https://doi.org/10.1158/0008-5472.Can-22-1029.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Mager CE, Mormol JM, Shelton ED, Murphy PR, Bowman BA, Barley TJ, et al. p38 MAPK and MKP-1 control the glycolytic program via the bifunctional glycolysis regulator PFKFB3 during sepsis. J Biol Chem. 2023;299:103043. https://doi.org/10.1016/j.jbc.2023.103043.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Kun S, Mathomes RT, Docsa T, Somsák L, Hayes JM. Design and synthesis of 3-(β-d-glucopyranosyl)-4-amino/4-guanidino pyrazole derivatives and analysis of their glycogen phosphorylase inhibitory potential. Molecules. 2023;28. https://doi.org/10.3390/molecules28073005.

  41. Inomata Y, Oh JW, Taniguchi K, Sugito N, Kawaguchi N, Hirokawa F, et al. Downregulation of miR-122–5p activates glycolysis via PKM2 in Kupffer cells of rat and mouse models of non-alcoholic steatohepatitis. Int J Mol Sci. 2022;23. https://doi.org/10.3390/ijms23095230.

  42. Barrea L, Caprio M, Tuccinardi D, Moriconi E, Di Renzo L, Muscogiuri G, et al. Could ketogenic diet “starve” cancer? Emerging evidence. Crit Rev Food Sci Nutr. 2022;62:1800–21. https://doi.org/10.1080/10408398.2020.1847030.

    Article  CAS  PubMed  Google Scholar 

  43. Roth KG, Mambetsariev I, Kulkarni P, Salgia R. The mitochondrion as an emerging therapeutic target in cancer. Trends Mol Med. 2020;26:119–34. https://doi.org/10.1016/j.molmed.2019.06.009.

    Article  CAS  PubMed  Google Scholar 

  44. ** H, He Y, Zhao P, Hu Y, Tao J, Chen J, et al. Targeting lipid metabolism to overcome EMT-associated drug resistance via integrin β3/FAK pathway and tumor-associated macrophage repolarization using legumain-activatable delivery. Theranostics. 2019;9:265–78. https://doi.org/10.7150/thno.27246.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Martínez-Montañés F, Casanovas A, Sprenger RR, Topolska M, Marshall DL, Moreno-Torres M, et al. Phosphoproteomic analysis across the yeast life cycle reveals control of fatty acyl chain length by phosphorylation of the fatty acid synthase complex. Cell Rep. 2020;32:108024. https://doi.org/10.1016/j.celrep.2020.108024.

    Article  CAS  PubMed  Google Scholar 

  46. ** Z, Chai YD, Hu S. Fatty acid metabolism and cancer. Adv Exp Med Biol. 2021;1280:231–41. https://doi.org/10.1007/978-3-030-51652-9_16.

    Article  CAS  PubMed  Google Scholar 

  47. Liu W, Hao J, Zhu L, Li F, Liu Q, Liu S, et al. Phospho-GSK-3β is involved in the high-glucose-mediated lipid deposition in renal tubular cells in diabetes. Int J Biochem Cell Biol. 2013;45:2066–75. https://doi.org/10.1016/j.biocel.2013.07.007.

    Article  CAS  PubMed  Google Scholar 

  48. Llovet JM, Castet F, Heikenwalder M, Maini MK, Mazzaferro V, Pinato DJ, et al. Immunotherapies for hepatocellular carcinoma. Nat Rev Clin Oncol. 2022;19:151–72. https://doi.org/10.1038/s41571-021-00573-2.

    Article  CAS  PubMed  Google Scholar 

  49. Sangro B, Sarobe P, Hervás-Stubbs S, Melero I. Advances in immunotherapy for hepatocellular carcinoma. Nat Rev Gastroenterol Hepatol. 2021;18:525–43. https://doi.org/10.1038/s41575-021-00438-0.

    Article  PubMed  PubMed Central  Google Scholar 

  50. Heinrich S, Craig AJ, Ma L, Heinrich B, Greten TF, Wang XW. Understanding tumour cell heterogeneity and its implication for immunotherapy in liver cancer using single-cell analysis. J Hepatol. 2021;74:700–15. https://doi.org/10.1016/j.jhep.2020.11.036.

    Article  CAS  PubMed  Google Scholar 

  51. Ho TTB, Nasti A, Seki A, Komura T, Inui H, Kozaka T, et al. Combination of gemcitabine and anti-PD-1 antibody enhances the anticancer effect of M1 macrophages and the Th1 response in a murine model of pancreatic cancer liver metastasis. J Immunother Cancer. 2020;8. https://doi.org/10.1136/jitc-2020-001367.

  52. Wei CY, Zhu MX, Zhang PF, Huang XY, Wan JK, Yao XZ, et al. PKCα/ZFP64/CSF1 axis resets the tumor microenvironment and fuels anti-PD1 resistance in hepatocellular carcinoma. J Hepatol. 2022;77:163–76. https://doi.org/10.1016/j.jhep.2022.02.019.

    Article  CAS  PubMed  Google Scholar 

  53. Li W, **ao J, Zhou X, Xu M, Hu C, Xu X, et al. STK4 regulates TLR pathways and protects against chronic inflammation-related hepatocellular carcinoma. J Clin Invest. 2015;125:4239–54. https://doi.org/10.1172/jci81203.

    Article  PubMed  PubMed Central  Google Scholar 

  54. Bao MH, Wong CC. Hypoxia, metabolic reprogramming, and drug resistance in liver cancer. Cells. 2021;10. https://doi.org/10.3390/cells10071715.

  55. Wicks EE, Semenza GL. Hypoxia-inducible factors: cancer progression and clinical translation. J Clin Invest. 2022;132. https://doi.org/10.1172/jci159839.

  56. Kuchnio A, Moens S, Bruning U, Kuchnio K, Cruys B, Thienpont B, et al. The cancer cell oxygen sensor PHD2 promotes metastasis via activation of cancer-associated fibroblasts. Cell Rep. 2015;12:992–1005. https://doi.org/10.1016/j.celrep.2015.07.010.

    Article  CAS  PubMed  Google Scholar 

  57. **g X, Yang F, Shao C, Wei K, **e M, Shen H, et al. Role of hypoxia in cancer therapy by regulating the tumor microenvironment. Mol Cancer. 2019;18:157. https://doi.org/10.1186/s12943-019-1089-9.

    Article  PubMed  PubMed Central  Google Scholar 

  58. Yang G, Shi R, Zhang Q. Hypoxia and oxygen-sensing signaling in gene regulation and cancer progression. Int J Mol Sci. 2020;21. https://doi.org/10.3390/ijms21218162.

  59. Wei J, Hu M, Du H. Improving cancer immunotherapy: exploring and targeting metabolism in hypoxia microenvironment. Front Immunol. 2022;13:845923. https://doi.org/10.3389/fimmu.2022.845923.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Li X, Yang Y, Zhang B, Lin X, Fu X, An Y, et al. Lactate metabolism in human health and disease. Signal Transduct Target Ther. 2022;7:305. https://doi.org/10.1038/s41392-022-01151-3.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Li M, Ning J, Wang J, Yan Q, Zhao K, Jia X. SETD7 regulates chondrocyte differentiation and glycolysis via the Hippo signaling pathway and HIF‑1α. Int J Mol Med. 2021;48. https://doi.org/10.3892/ijmm.2021.5043.

  62. Cheng SC, Quintin J, Cramer RA, Shepardson KM, Saeed S, Kumar V, et al. mTOR- and HIF-1α-mediated aerobic glycolysis as metabolic basis for trained immunity. Science. 2014;345:1250684. https://doi.org/10.1126/science.1250684.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Cheng J, Zhang R, Xu Z, Ke Y, Sun R, Yang H, et al. Early glycolytic reprogramming controls microglial inflammatory activation. J Neuroinflammation. 2021;18:129. https://doi.org/10.1186/s12974-021-02187-y.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Yuen VW, Wong CC. Hypoxia-inducible factors and innate immunity in liver cancer. J Clin Invest. 2020;130:5052–62. https://doi.org/10.1172/jci137553.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Reig M, Forner A, Rimola J, Ferrer-Fàbrega J, Burrel M, Garcia-Criado Á, Kelley RK, Galle PR, Mazzaferro V, Salem R, Sangro B, Singal AG, Vogel A, Fuster J, Ayuso C, Bruix J. BCLC strategy for prognosis prediction and treatment recommendation: the 2022 update. J Hepatol. 2022;76(3):b681-693. https://doi.org/10.1016/j.jhep.2021.11.018.

    Article  Google Scholar 

  66. Bureau of Medical Administration, National Health Commission of the People's Republic of China. Standardization for diagnosis and treatment of hepatocellular carcinoma (2022 edition). Chin J Dig Surg. 2022;21(2):143–167. https://doi.org/10.3760/cma.j.cn115610-20220124-00053.

  67. Fan L, Xu L, Tian S, Zheng X. Identification of a novel histone phosphorylation prognostic signature in hepatocellular carcinoma based on bulk and single-cell RNA sequencing. Front Endocrinol. 2022;13:965445. https://doi.org/10.3389/fendo.2022.965445.

    Article  Google Scholar 

  68. Tan CSH. Databases and computational tools for evolutionary analysis of protein phosphorylation. Methods Mol Biol. 2017;1636:475–84. https://doi.org/10.1007/978-1-4939-7154-1_29.

    Article  CAS  PubMed  Google Scholar 

  69. Yu Y, Peng XD, Qian XJ, Zhang KM, Huang X, Chen YH, Li YT, Feng GK, Zhang HL, Xu XL, Li S, Li X, Mai J, Li ZL, Huang Y, Yang D, Zhou LH, Zhong ZY, Li JD, Deng R, Zhu XF. Fis1 phosphorylation by Met promotes mitochondrial fission and hepatocellular carcinoma metastasis. Signal Transduct Target Ther. 2021;6(1):401. https://doi.org/10.1038/s41392-021-00790-2.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. da Silva EFG, Lima KG, Krause GC, Haute GV, Pedrazza L, Catarina AV, Gassen RB, Basso BDS, Dias HB, Luft C, Garcia MCR, Costa BP, Antunes GL, Basso LA, Donadio MVF, Machado P, de Oliveira JR. CPBMF65, a synthetic human uridine phosphorylase-1 inhibitor, reduces HepG2 cell proliferation through cell cycle arrest and senescence. Invest New Drugs. 2020;38(6):1653–63. https://doi.org/10.1007/s10637-020-00941-2.

    Article  CAS  PubMed  Google Scholar 

  71. Solimando AG, Susca N, Argentiero A, Brunetti O, Leone P, Re VD, Fasano R, Krebs M, Petracci E, Azzali I, Nanni O, Silvestris N, Vacca A, Racanelli V. Second-line treatments for advanced hepatocellular carcinoma: a systematic review and Bayesian Network meta-analysis. Clin Exp Med. 2022;22(1):65–74. https://doi.org/10.1007/s10238-021-00727-7.

    Article  CAS  PubMed  Google Scholar 

  72. Zhao Z, Zhang D, Wu F, Tu J, Song J, Xu M, Ji J. Sophoridine suppresses lenvatinib-resistant hepatocellular carcinoma growth by inhibiting RAS/MEK/ERK axis via decreasing VEGFR2 expression. J Cell Mol Med. 2021;25(1):549–60. https://doi.org/10.1111/jcmm.16108.

    Article  CAS  PubMed  Google Scholar 

  73. **ng X, Yuan H, Sun Y, Ke K, Dong X, Chen H, Liu X, Zhao B, Huang A. ANXA2Tyr23 and FLNASer2152 phosphorylation associate with poor prognosis in hepatic carcinoma revealed by quantitative phosphoproteomics analysis. J Proteomics. 2019;200:111–22. https://doi.org/10.1016/j.jprot.2019.03.017.

    Article  CAS  PubMed  Google Scholar 

  74. Borradaile NM, de Dreu LE, Huff MW. Inhibition of net HepG2 cell apolipoprotein B secretion by the citrus flavonoid naringenin involves activation of phosphatidylinositol 3-kinase, independent of insulin receptor substrate-1 phosphorylation. Diabetes. 2003;52(10):2554–61. https://doi.org/10.2337/diabetes.52.10.2554.

    Article  CAS  PubMed  Google Scholar 

  75. Zheng L, Yang W, Wu F, Wang C, Yu L, Tang L, Qiu B, Li Y, Guo L, Wu M, Feng G, Zou D, Wang H. Prognostic significance of AMPK activation and therapeutic effects of metformin in hepatocellular carcinoma. Clin Cancer Res. 2013;19(19):5372–80. https://doi.org/10.1158/1078-0432.CCR-13-0203.

    Article  CAS  PubMed  Google Scholar 

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Acknowledgements

The authors acknowledge The Cancer Genome Atlas (TCGA) project organizers as well as all study participants for providing the publicly available TCGA RNA-seq data and clinical data.

Funding

This work was supported by the Shandong Provincial Taishan Scholar Engineering Project Special Funds (to X.Z.), SCIBP Supported Projects (NO.SCIBP2021070018), the Shandong Provincial Natural Science Foundation (ZR2021MH156; ZR2022QH112), the Shandong First Medical University Talent Introduction Funds (to X.Z.), the Shandong First Medical University High-level Scientific Research Achievement Cultivation Funding Program (to X.Z.), and China National Nature Scientific Funds (82203592).

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Authors and Affiliations

  1. Department of General Surgery, The Third ** Zhang

  2. Medical Science and Technology Innovation Center, Shandong Key Laboratory of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University & Shandong Academy of Medical Sciences, 440 Jiyan Road, **an, Shandong, 250117, People’s Republic of China

    Na Li, Lamei Yang, Wenshuang Jia, Zhijun Li, Qianwen Shao & **-Zhang-Aff1">Yu** Zhang

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  3. Na Li
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  5. Wenshuang Jia
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  6. Zhijun Li
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  7. Qianwen Shao
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  8. **anquan Zhan
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Contributions

Y.Z. and N.L. analyzed data, prepared figures and tables, and designed and wrote the manuscript. Y.Z. and W.J. collected and processed clinical tissue samples, sample diagnoses, and clinical explanations. L.Y., Q.S., and Z. L. participated in partial data analysis. X.Z. conceived the concept, obtained phosphoproteomics original data, supervised results, designed, wrote, and critically revised the manuscript, and was responsible for its financial support and the corresponding works. All authors approved the final manuscript.

Corresponding author

Correspondence to **anquan Zhan.

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Ethical approval

All the patients were informed about the purposes of the study and consequently signed their “consent of the patient.” All investigations conformed to the principles outlined in the Declaration of Helsinki and were performed with permission by the Third **angya Hospital Medical Ethics Committee of Central South University and the Medical Ethics Committee of Shandong First Medical University, China.

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The authors declare no competing interests.

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Zhang, Y., Li, N., Yang, L. et al. Quantitative phosphoproteomics reveals molecular pathway network alterations in human early-stage primary hepatic carcinomas: potential for 3P medical approach. EPMA Journal 14, 477–502 (2023). https://doi.org/10.1007/s13167-023-00335-3

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  • DOI: https://doi.org/10.1007/s13167-023-00335-3

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