Serum Biomarkers Study and the Establishment of Diagnostic Models for Hepatitids B-Related HCC

• Jing Bai

  Department of Medical Laboratory, Beijing Tongren Hospital, Capital Medical University, China

• Haishun Liu

  Department of Physics, Capital Normal University, China

• Hongfei Wan

  Department of Pathology, Beijing Tongren Hospital, Capital Medical University, China

• Xiangyi Liu

  Department of Medical Laboratory, Beijing Tongren Hospital, Capital Medical University, China

China's HCC accounts for 90% of HBV related HCC. Early detection, diagnosis and treatment are the key to effective control of HCC. By measuring the levels of expression of AFP, DCP and GP73 in the serum of HBV-related HCC patients, the diagnostic value of single and combined detection of the above indicators in HBV-related HCC shall be discussed, and the mathematical model of differential diagnosis by SVM shall be established to provide reference for the diagnosis of HBV-related HCC. A total of 301 patients and healthy persons from March 2016 to January 2018 from Beijing Tongren Hospital affiliated to Capital Medical University have been selected. These lection includes 57 cases of HBV-related HCC, 61 cases of non- HBV-related HCC, 52 cases of HBV-related cirrhosis, 57 cases of chronic HBV, and 74 healthy persons in the same period. The levels of serum DCP, AFP and GP73 in each group were measured. Combined diagnosis of three indexes is better than single diagnosis, P<0.001. Using SVM mathematical diagnosis model, the specificity and sensitivity of diagnosing HBV-related HCC and healthy controls reached 98.7% and 97.6%, while the specificity and sensitivity of diagnosing HBV-related HCC and HBV-related cirrhosis reached 90.91% and 96.3%, respectively. Serum DCP, AFP and GP73 can be used independently as a useful reference for diagnosing HBV-related HCC patients. Combined detection of the three indicators can improve the sensitivity of HBV-related HCC diagnostic test. The SVM model can be used to diagnose and identify liver diseases at different stages.

Torre LA, Bray F, Siegel RL, Ferlay, Lortet-Tieulent, Jemal A. Global cancer statistics 2012. J CA Cancer J Clin. 2015; 65(2): 87-108. https://doi.org/10.3322/caac.21262

Farazi PA, DePinho RA. Hepatocellular carcinoma pathogenesis: from genes to environment. J Nat Rev Cancer 2006; 6(9): 674-687. https://doi.org/10.1038/nrc1934

Xin Z, Liandi L, Fengzhu L, et al. Investigation and analysis of primary liver cancer mortality in China from 1990 to 1992. J Chinese Journal of Oncology 1999; 21(4): 245-249.

Boyle P, Levin B. World Cancer Report 2008

Maddrey W. Hepatitis B:an important public health issue. J Medi Virol 2000; 61(3): 362-366. https://doi.org/10.1002/1096-9071(200007)61:3<362::AID-JMV14>3.0.CO;2-I

Xiaoyong Z. Early diagnostic value of combined detection of serum AFP, TSGF, AFU, GGT and CEA for hepatitis B-related primary liver cancer J. China Health Engineering 2017; 16(4): 488-492.

Korean Liver Cancer Study Group (KLCSG), National Cancer Center, Korea (NCC). 2014. Korean Liver Cancer Study Group-National Cancer Center Korea Practice Guideline for the Management of Hepatocellular Carcinoma J. Korean Journal of Radiology 2015; 16(3): 465-522. https://doi.org/10.3348/kjr.2015.16.3.465

Sterling RK, Jeffers L, Gordon F, Venook AP, Reddy KR, Satomura S, Kanke F, Schmartz ME, Sheman M. Utility of Lens culinaris agglutinin-reactive fraction of alpha-fetoprotein and des-gamma-carboxy prothrombin, alone or in combination, as biomarkers for hepatocellular carcinoma, J. Clin Gastroenterol Hepatol 2009; 7(1): 104-113. https://doi.org/10.1016/j.cgh.2008.08.041

Ozkan H, Erdal H, Tutkak H, Karaeren Z,Yakut M, Yuksel O, Koklu S. Diagnostic and prognostic validity of Golgi protein73 in hepatocellular carcinoma. Digestion 2011; 83(1-2): 83-88. https://doi.org/10.1159/000320379

Guideline for diagnosis and treatment of primary liver cancer (2011 Edition), J. Journal of Clinical Oncology 2011; 10: 929-946.

Guidelines for the prevention and treatment of chronic hepatitis B (updated edition 2015), J. Journal of Hepatobiliary Diseases 2015; 31(12): 1941-1960.

Furey TS, Cristianini N, Duffy N, Bednarski DW, Schummer M, Haussler D. Support vector machine classification and validation of cancer tissue samples using microarray expression data, J. Bioinformatics 2000; 16(10): 906-914. https://doi.org/10.1093/bioinformatics/16.10.906

Tong S, Koller D. Support vector machine active learning with applications to text classification,J. Journal of Machine Learning Research 2002; 2(1): 45-66.

Liu H, Zhang Z, Zhang X, et al. Dimensionality Reduction for Identification of Hepatic Tumor Samples Based on Terahertz Time-Domain Spectroscopy, J. IEEE Transactions on Terahertz Science and Technology 2018; 8(3): 271-277. https://doi.org/10.1109/TTHZ.2018.2813085

Vapnik VN. The Nature of Statistical Learning Theory. New York, NY, USA: Springer-Verlag, 2000; pp. 988-999. https://doi.org/10.1109/72.788640

Chapelle O, Vapnik V, Bousquet O, et al. Choosing Multiple Parameters for Support Vector Machines, J. Machine Learning, 2002; 46(1-3): 131-159. https://doi.org/10.1023/A:1012450327387

Rajer-Kanduč K, Zupan J, Majcen N. Separation of data on the training and test set for modelling: a case study for modelling of five colour properties of a white pigment, J. Chemometrics and intelligent laboratory systems, 2003, 65(2): 221-229. https://doi.org/10.1016/S0169-7439(02)00110-7

Kennard RW, Stone LA. Computer aided design of experiments, J. Technometrics 1969; 11(1): 137-148. https://doi.org/10.1080/00401706.1969.10490666

Gao JJ, Song PP, Tamura S, Hasegawa K, Sugawara Y. Standardization of perioperative management on hepato-biliary-pancreatic surgery, J. Drug Discoveries & Therapeutics 2012; 6(2): 108-111. https://doi.org/10.5582/ddt.2012.v6.2.108

Song P, Tobe RG, Inagaki Y, Kokudo N, Hasegawa K. The management of hepatocellular carcinoma around the world: a comparison of guidelines from 2001 to 2011, J. Liver International Official Journal of the International Association for the Study of the Liver 2012; 32(32): 1053-1063. https://doi.org/10.1111/j.1478-3231.2012.02792.x

Bruix J, Sherman M. Management of hepatocellular carcinoma: an update. J Hepatology 2011; 53(3): 1020-1022. https://doi.org/10.1002/hep.24199

European Association for the Study of the liver, European Organisation for Research and Treatment of cancer. EASL-EORTC clinical practice guidlines: management of hepatocellular carcinoma, J. J Hepatol 2012; 56(4): 908-943. https://doi.org/10.1016/j.jhep.2011.12.001

Koike Y, Shiratori Y, Sato S, Obi S, Teratani T. Des-γ-carboxy prothrombin as a useful predisposing factor for the development of portal venous invasion in patients with hepatocellular carcinoma. J Cancer 2001; 91(3): 561-569. https://doi.org/10.1002/1097-0142(20010201)91:3<561::AID-CNCR1035>3.0.CO;2-N

• PDF