Integrated Proteomics and Bioinformatics to Identify Potential Prognostic Biomarkers in Hepatocellular Carcinoma

References

• Chen M, Cai X. Synthetic lethality is a novel and potential paradigm for precision medicine in advanced hepatocellular carcinoma. Liver Cancer. 2020;9(2):225–226. doi:10.1159/00050392732399437
   PubMed Web of Science ®Google Scholar
• Kudo M. Scientific rationale for combination immunotherapy of hepatocellular carcinoma with Anti-PD-1/PD-L1 and Anti-CTLA-4 antibodies. Liver Cancer. 2019;8(6):413–426. doi:10.1159/00050325432479569
   PubMed Web of Science ®Google Scholar
• Liu S, Yang Z, Li G, et al. Multi-omics analysis of primary cell culture models reveals genetic and epigenetic basis of intratumoral phenotypic diversity. Genomics Proteomics Bioinformatics. 2019;17(6):576–589. doi:10.1016/j.gpb.2018.07.00832205176
   PubMed Web of Science ®Google Scholar
• Bray F, Ferlay J, Soerjomataram I, Siegel R, Torre L, 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(6):394–424. doi:10.3322/caac.2149230207593
   PubMed Web of Science ®Google Scholar
• Zhang C, Wei S, Sun W, et al. Super-enhancer-driven AJUBA is activated by TCF4 and involved in epithelial-mesenchymal transition in the progression of hepatocellular carcinoma. Theranostics. 2020;10(20):9066–9082. doi:10.7150/thno.4534932802179
   PubMed Web of Science ®Google Scholar
• He T, Zheng K, Li G, Song B, Zhang Y. Identification of typical miRNAs and target genes in hepatocellular carcinoma by DNA microarray technique. Eur Rev Med Pharmacol Sci. 2014;18(1):108–116.24452951
   PubMed Web of Science ®Google Scholar
• Huang K, Maruyama T, Fan G. The naive state of human pluripotent stem cells: a synthesis of stem cell and preimplantation embryo transcriptome analyses. Cell Stem Cell. 2014;15(4):410–415. doi:10.1016/j.stem.2014.09.01425280217
   PubMed Web of Science ®Google Scholar
• Bao L, Guo T, Wang J, Zhang K, Bao M. Prognostic genes of triple-negative breast cancer identified by weighted gene co-expression network analysis. Oncol Lett. 2020;19(1):127–138. doi:10.3892/ol.2019.1107931897123
   PubMed Web of Science ®Google Scholar
• Mitra K, Carvunis A, Ramesh S, Ideker T. Integrative approaches for finding modular structure in biological networks. Nat Rev Genet. 2013;14(10):719–732. doi:10.1038/nrg355224045689
   PubMed Web of Science ®Google Scholar
• Malki K, Tosto MG, Jumabhoy I, et al. Integrative mouse and human mRNA studies using WGCNA nominates novel candidate genes involved in the pathogenesis of major depressive disorder. Pharmacogenomics. 2013;14(16):1979–1990. doi:10.2217/pgs.13.15424279853
   PubMed Web of Science ®Google Scholar
• Zuo Z, Shen JX, Pan Y, et al. Weighted Gene Correlation Network Analysis (WGCNA) detected loss of MAGI2 promotes Chronic Kidney Disease (CKD) by podocyte damage. Cell Physiol Biochem. 2018;51(1):244–261. doi:10.1159/00049520530448842
   PubMedGoogle Scholar
• Lau W, Lai PBS, Leung M, et al. Differential gene expression of hepatocellular carcinoma using cDNA microarray analysis. Oncol Res. 2000;12(2):59–69. doi:10.3727/09650400110874753011132925
   PubMed Web of Science ®Google Scholar
• Liwei Z, Yun W, Jiwu H, et al. A network biology approach to discover the molecular biomarker associated with hepatocellular carcinoma. Biomed Res Int. 2014;2014:278956.24949431
   PubMed Web of Science ®Google Scholar
• Chu A, Gordon R, Denise B, et al. Large-scale profiling of microRNAs for The Cancer Genome Atlas. Nucleic Acids Res. 2016;44(1):e3–e3. doi:10.1093/nar/gkv80826271990
   PubMed Web of Science ®Google Scholar
• Lausen B, Schumacher M. Maximally selected rank statistics. Biometrics. 1992;48:73. doi:10.2307/2532740
   Web of Science ®Google Scholar
• Matthew S. False discovery rates: a new deal. Biostatistics. 2016;(2):2.
   Web of Science ®Google Scholar
• Szklarczyk D, Gable A, Lyon D, et al. STRING v11: protein-protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets. Nucleic Acids Res. 2019;47:D607–D613. doi:10.1093/nar/gky113130476243
   PubMed Web of Science ®Google Scholar
• 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(Suppl 4(S4)):S11. doi:10.1186/1752-0509-8-S4-S1125521941
   PubMed Web of Science ®Google Scholar
• Shannon P, Markiel A, Ozier O, et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 2003;13(11):2498–2504. doi:10.1101/gr.123930314597658
   PubMed Web of Science ®Google Scholar
• Mi H, Lazareva-Ulitsky B, Loo R, et al. The PANTHER database of protein families, subfamilies, functions and pathways. Nucleic Acids Res. 2005;33:D284–288. doi:10.1093/nar/gki07815608197
   PubMed Web of Science ®Google Scholar
• Huaiyu M, Xiaosong H, Anushya M, et al. PANTHER version 11: expanded annotation data from gene ontology and Reactome pathways, and data analysis tool enhancements. Nucleic Acids Res. 2017;(D1):D183–D189.27899595
   PubMed Web of Science ®Google Scholar
• Minoru K, Susumu G. KEGG: Kyoto Encyclopedia of Genes and Genomes. Nucleic Acids Res. 2000;(1):29–34.
   Web of Science ®Google Scholar
• Huang DW, Sherman BT, Lempicki RA. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc. 2009;4(1):44. doi:10.1038/nprot.2008.21119131956
   PubMed Web of Science ®Google Scholar
• Langfelder P, Horvath S. WGCNA: an R package for weighted correlation network analysis. BMC Bioinform. 2008;9:559. doi:10.1186/1471-2105-9-559
   PubMed Web of Science ®Google Scholar
• Subramanian A, Tamayo P, Mootha VK, et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. P Natl Acad Sci USA. 2005;102(43):15545–15550. doi:10.1073/pnas.0506580102
   PubMed Web of Science ®Google Scholar
• Benjamini Y, Hochberg Y. Controlling the false discovery rate - a practical and powerful approach to multiple testing. J R Stat Soc B. 1995;57(1):289–300.
   Google Scholar
• Knopp-Sihota JA, Newburn-Cook CV, Homik J, Cummings GG, Voaklander D. Calcitonin for treating acute and chronic pain of recent and remote osteoporotic vertebral compression fractures: a systematic review and meta-analysis. Osteoporosis Int. 2012;23(1):17–38. doi:10.1007/s00198-011-1676-0
   PubMed Web of Science ®Google Scholar
• Wallace MC, Preen D, Jeffrey GP, Adams LA. The evolving epidemiology of hepatocellular carcinoma: a global perspective. Expert Rev Gastroenterol Hepatol. 2015;9(6):765–779. doi:10.1586/17474124.2015.102836325827821
   PubMed Web of Science ®Google Scholar
• Siegel RL, Miller KD, Jemal A. Cancer statistics, 2017. CA Cancer J Clin. 2017;67(1).
   Web of Science ®Google Scholar
• Martínez-Chantar M, Avila M, Lu S. Hepatocellular carcinoma: updates in pathogenesis, detection and treatment. Cancers. 2020;12:10. doi:10.3390/cancers12102729
   Web of Science ®Google Scholar
• Buonaguro L, Tagliamonte M, Petrizzo A, Damiano E, Tornesello ML, Buonaguro FM. Cellular prognostic markers in hepatocellular carcinoma. Future Oncol. 2015;11(11):1591–1598. doi:10.2217/fon.15.3926043213
   PubMed Web of Science ®Google Scholar
• Lin J, Wu Y, Wu C, Shih P, Wang W, Chien Y. DNA methylation markers and serum α-fetoprotein level are prognostic factors in hepatocellular carcinoma. Ann Hepatol. 2015;14(4):494–504. doi:10.1016/S1665-2681(19)31171-826019036
   PubMed Web of Science ®Google Scholar
• Lee S, Rhim H, Kim YS, Kang TW, Song KD. Post-ablation des-gamma-carboxy prothrombin level predicts prognosis in hepatitis b-related hepatocellular carcinoma. Liver Int off J Int Assoc Study Liver. 2016;64(2):S342–S342.
   Google Scholar
• Berry D, O’Byrne S, Vreeland A, Blaner W, Noy N. Cross talk between signaling and vitamin A transport by the retinol-binding protein receptor STRA6. Mol Cell Biol. 2012;32(15):3164–3175. doi:10.1128/MCB.00505-1222665496
   PubMed Web of Science ®Google Scholar
• Zhong M, Kawaguchi R, Costabile B, et al. Regulatory mechanism for the transmembrane receptor that mediates bidirectional vitamin A transport. Proc Natl Acad Sci U S A. 2020;117(18):9857–9864. doi:10.1073/pnas.191854011732300017
   PubMed Web of Science ®Google Scholar
• Ashla A, Hoshikawa Y, Tsuchiya H, et al. Genetic analysis of expression profile involved in retinoid metabolism in non-alcoholic fatty liver disease. Hepatol Res. 2010;40(6):594–604. doi:10.1111/j.1872-034X.2010.00646.x20618457
   PubMed Web of Science ®Google Scholar
• Chen D, Feng X, Lv Z, et al. ACADS acts as a potential methylation biomarker associated with the proliferation and metastasis of hepatocellular carcinomas. Aging. 2019;11(20):8825–8844. doi:10.18632/aging.10229231652420
   PubMedGoogle Scholar
• Scheiner B, Stättermayer A, Schwabl P, et al. Impact of HSD17B13 rs72613567 genotype on hepatic decompensation and mortality in patients with portal hypertension. Liver Int. 2020;40(2):393–404. doi:10.1111/liv.1430431967400
   PubMed Web of Science ®Google Scholar
• Lu C, Fang S, Weng Q, et al. Integrated analysis reveals critical glycolytic regulators in hepatocellular carcinoma. CCS. 2020;18(1):97. doi:10.1186/s12964-020-00539-432576292
   PubMed Web of Science ®Google Scholar
• Cai J, Yuan S, Yang F, et al. Paraoxonase 3 inhibits cell proliferation and serves as a prognostic predictor in hepatocellular carcinoma. Oncotarget. 2016;7(43):70045–70057. doi:10.18632/oncotarget.1214527661119
   PubMedGoogle Scholar
• Song Y, Ahn J, Suh Y, Davis M, Lee K. Identification of novel tissue-specific genes by analysis of microarray databases: a human and mouse model. PLoS One. 2013;8(5):e64483. doi:10.1371/journal.pone.006448323741331
   PubMed Web of Science ®Google Scholar
• Dangi B, Davydova N, Vavilov N, Zgoda V, Davydov D. Nonadditivity in human microsomal drug metabolism revealed in a study with coumarin 152, a polyspecific cytochrome P450 substrate. Xenobiotica. 2020;1–13.
   Web of Science ®Google Scholar
• Gao H, Cao Y, Xia H, Zhu X, Jin Y. CYP4A11 is involved in the development of nonalcoholic fatty liver disease via ROS‑induced lipid peroxidation and inflammation. Int J Mol Med. 2020;45(4):1121–1129. doi:10.3892/ijmm.2020.447932124935
   PubMed Web of Science ®Google Scholar
• Ooeda K, Kubiura-Ichimaru M, Tsuji S, et al. A two-dimensional multiwell cell culture method for the production of CYP3A4-expressing hepatocyte-like cells from HepaRG cells. Pharmacol Res Perspect. 2020;8(5):e00652. doi:10.1002/prp2.65232955797
   PubMed Web of Science ®Google Scholar
• Eun H, Cho S, Lee B, et al. Cytochrome P450 4A11 expression in tumor cells: a favorable prognostic factor for hepatocellular carcinoma patients. J Gastroenterol Hepatol. 2019;34(1):224–233. doi:10.1111/jgh.1440630069903
   PubMed Web of Science ®Google Scholar
• Zhu L, Baker S, Liu W, et al. Lipid in the livers of adolescents with nonalcoholic steatohepatitis: combined effects of pathways on steatosis. Metabolism. 2011;60(7):1001–1011. doi:10.1016/j.metabol.2010.10.00321075404
   PubMed Web of Science ®Google Scholar
• Gao Q, Zhang G, Zheng Y, et al. SLC27A5 deficiency activates NRF2/TXNRD1 pathway by increased lipid peroxidation in HCC. Cell Death Differ. 2020;27(3):1086–1104. doi:10.1038/s41418-019-0399-131367013
   PubMed Web of Science ®Google Scholar
• Chen S. Identification of SARS-CoV-2 proteins binding human mRNAs as a novel signature predicting overall survival in hepatocellular carcinoma. DNA Cell Biol. 2020.
   Web of Science ®Google Scholar