中文English
ISSN 1001-5256 (Print)
ISSN 2097-3497 (Online)
CN 22-1108/R

Research advances in early screening and diagnosis of hepatocellular carcinoma

DOI: 10.3969/j.issn.1001-5256.2023.06.033
Research funding:

Tianjin Health Science and Technology Project Key Disciplines (TJWJ2022XK034);

Tianjin Key Medical Discipline (Specialty) Construction Project (TJYXZDXK-059B);

Key Scientific Research Project of Integrated Traditional Chinese and Western Medicine of Tianjin Health Commission (2021022)

More Information
  • Corresponding author: XU Liang, xuyangliang2004@sina.com (ORCID: 0000-0001-5441-1217)
  • Received Date: 2022-09-30
  • Accepted Date: 2022-10-24
  • Published Date: 2023-06-20
  • For the high-risk population, early screening and diagnosis are important measures to achieve good control of liver cancer and reduce the burden of liver cancer, and determining the high-risk population of liver cancer and formulating appropriate liver cancer screening strategies are the key to realizing the early screening and diagnosis of liver cancer. The risk assessment model for liver cancer is an important method for rapid and convenient identification of the high-risk population of liver cancer. Based on the risk stratification of liver cancer, the methods such as imaging technology, serological markers, liquid biopsy, metabolomics, and glycomics can be used for accurate early screening and diagnosis of liver cancer, so as to achieve the goal of early treatment.

     

  • [1]
    SUNG H, FERLAY J, SIEGEL RL, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries[J]. CA Cancer J Clin, 2021, 71(3): 209-249. DOI: 10.3322/caac.21660.
    [2]
    ZHOU M, WANG H, ZENG X, et al. Mortality, morbidity, and risk factors in China and its provinces, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017[J]. Lancet, 2019, 394(10204): 1145-1158. DOI: 10.1016/S0140-6736(19)30427-1.
    [3]
    General Office of National Health Commission. Standard for diagnosis and treatment of primary liver cancer (2022 edition)[J]. J Clin Hepatol, 2022, 38(2): 288-303. DOI: 10.3969/j.issn.1001-5256.2022.02.009.

    国家卫生健康委办公厅. 原发性肝癌诊疗指南(2022年版)[J]. 临床肝胆病杂志, 2022, 38(2): 288-303. DOI: 10.3969/j.issn.1001-5256.2022.02.009.
    [4]
    XIAO J, WANG F, WONG NK, et al. Global liver disease burdens and research trends: Analysis from a Chinese perspective[J]. J Hepatol, 2019, 71(1): 212-221. DOI: 10.1016/j.jhep.2019.03.004.
    [5]
    BRUIX J, CHAN SL, GALLE PR, et al. Systemic treatment of hepatocellular carcinoma: An EASL position paper[J]. J Hepatol, 2021, 75(4): 960-974. DOI: 10.1016/j.jhep.2021.07.004.
    [6]
    HEIMBACH JK, KULIK LM, FINN RS, et al. AASLD guidelines for the treatment of hepatocellular carcinoma[J]. Hepatology, 2018, 67(1): 358-380. DOI: 10.1002/hep.29086.
    [7]
    KUDO M, KAWAMURA Y, HASEGAWA K, et al. Management of hepatocellular carcinoma in Japan: JSH consensus statements and recommendations 2021 update[J]. Liver Cancer, 2021, 10(3): 181-223. DOI: 10.1159/000514174.
    [8]
    VOGEL A, CERVANTES A, CHAU I, et al. Correction to: "Hepatocellular carcinoma: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up"[J]. Ann Oncol, 2019, 30(5): 871-873. DOI: 10.1093/annonc/mdy510.
    [9]
    SHARMA SA, KOWGIER M, HANSEN BE, et al. Toronto HCC risk index: A validated scoring system to predict 10-year risk of HCC in patients with cirrhosis[J]. J Hepatol, 2018, 68(1): 92-99. DOI: 10.1016/j.jhep.2017.07.033.
    [10]
    ZHANG H, ZHU J, XI L, et al. Validation of the Toronto hepatocellular carcinoma risk index for patients with cirrhosis in China: a retrospective cohort study[J]. World J Surg Oncol, 2019, 17(1): 75. DOI: 10.1186/s12957-019-1619-3.
    [11]
    YANG HI, YUEN MF, CHAN HL, et al. Risk estimation for hepatocellular carcinoma in chronic hepatitis B (REACH-B): development and validation of a predictive score[J]. Lancet Oncol, 2011, 12(6): 568-574. DOI: 10.1016/S1470-2045(11)70077-8.
    [12]
    PAPATHEODORIDIS G, DALEKOS G, SYPSA V, et al. PAGE-B predicts the risk of developing hepatocellular carcinoma in Caucasians with chronic hepatitis B on 5-year antiviral therapy[J]. J Hepatol, 2016, 64(4): 800-806. DOI: 10.1016/j.jhep.2015.11.035.
    [13]
    LEE HW, KIM SU, PARK JY, et al. External validation of the modified PAGE-B score in Asian chronic hepatitis B patients receiving antiviral therapy[J]. Liver Int, 2019, 39(9): 1624-1630. DOI: 10.1111/liv.14129.
    [14]
    LAMBRECHT J, PORSCH-ÖZÇÜRÜMEZ M, BEST J, et al. The APAC score: a novel and highly performant serological tool for early diagnosis of hepatocellular carcinoma in patients with liver cirrhosis[J]. J Clin Med, 2021, 10(15): 3392. DOI: 10.3390/jcm10153392.
    [15]
    LI XH, HAO X, DENG YH, et al. The aMAP score was used to assess the risk of liver cancer among people with chronic liver disease in primary hospitals[J]. Chin J Hepatol, 2021, 29(4): 332-337. DOI: 10.3760/cma.j.cn501113-20210329-00144.

    李秀华, 郝新, 邓永红, 等. 应用aMAP评分评估基层医院慢性肝病人群的肝癌发生风险[J]. 中华肝脏病杂志, 2021, 29(4): 332-337. DOI: 10.3760/cma.j.cn501113-20210329-00144.
    [16]
    KIM HY, LAMPERTICO P, NAM JY, et al. An artificial intelligence model to predict hepatocellular carcinoma risk in Korean and Caucasian patients with chronic hepatitis B[J]. J Hepatol, 2022, 76(2): 311-318. DOI: 10.1016/j.jhep.2021.09.025.
    [17]
    HARRIS PS, HANSEN RM, GRAY ME, et al. Hepatocellular carcinoma surveillance: An evidence-based approach[J]. World J Gastroenterol, 2019, 25(13): 1550-1559. DOI: 10.3748/wjg.v25.i13.1550.
    [18]
    CHOI J, KIM GA, HAN S, et al. Longitudinal assessment of three serum biomarkers to detect very early-stage hepatocellular carcinoma[J]. Hepatology, 2019, 69(5): 1983-1994. DOI: 10.1002/hep.30233.
    [19]
    HUGHES DM, BERHANE S, EMILY DE GROOT CA, et al. Serum levels of α-fetoprotein increased more than 10 years before detection of hepatocellular carcinoma[J]. Clin Gastroenterol Hepatol, 2021, 19(1): 162-170. e4. DOI: 10.1016/j.cgh.2020.04.084.
    [20]
    YAN YF, WANG YT, ZHU C, et al. Meta analysis of the accuracy of liver cancer screening technology[J]. Chin J Evid-Based Med, 2018, 18(5): 418-427. DOI: 10.7507/1672-2531.201802055.

    严永锋, 王宇婷, 朱陈, 等. 肝癌筛查技术准确性的Meta分析[J]. 中国循证医学杂志, 2018, 18(5): 418-427. DOI: 10.7507/1672-2531.201802055.
    [21]
    ROBERTS LR, SIRLIN CB, ZAIEM F, et al. Imaging for the diagnosis of hepatocellular carcinoma: A systematic review and meta-analysis[J]. Hepatology, 2018, 67(1): 401-421. DOI: 10.1002/hep.29487.
    [22]
    NADAREVIC T, COLLI A, GILJACA V, et al. Magnetic resonance imaging for the diagnosis of hepatocellular carcinoma in adults with chronic liver disease[J]. Cochrane Database Syst Rev, 2022, 5(5): CD014798. DOI: 10.1002/14651858.CD014798.pub2.
    [23]
    GAO F, WEI Y, ZHANG T, et al. New liver MR imaging hallmarks for small hepatocellular carcinoma screening and diagnosing in high-risk patients[J]. Front Oncol, 2022, 12: 812832. DOI: 10.3389/fonc.2022.812832.
    [24]
    LV K, ZHAI H, JIANG Y, et al. Prospective assessment of diagnostic efficacy and safety of SonazoidTM and SonoVue® ultrasound contrast agents in patients with focal liver lesions[J]. Abdom Radiol (NY), 2021, 46(10): 4647-4659. DOI: 10.1007/s00261-021-03010-1.
    [25]
    FRAQUELLI M, NADAREVIC T, COLLI A, et al. Contrast- enhanced ultrasound for the diagnosis of hepatocellular carcinoma in adults with chronic liver disease[J]. Cochrane Database Syst Rev, 2022, 9(9): CD013483. DOI: 10.1002/14651858.CD013483.pub2.
    [26]
    ZHANG L, GU J, LI Y, et al. Clinical value study on contrast-enhanced ultrasound combined with enhanced CT in early diagnosis of primary hepatic carcinoma[J]. Contrast Media Mol Imaging, 2022, 2022: 7130533. DOI: 10.1155/2022/7130533.
    [27]
    LIU D, LIU F, XIE X, et al. Accurate prediction of responses to transarterial chemoembolization for patients with hepatocellular carcinoma by using artificial intelligence in contrast-enhanced ultrasound[J]. Eur Radiol, 2020, 30(4): 2365-2376. DOI: 10.1007/s00330-019-06553-6.
    [28]
    YASAKA K, AKAI H, ABE O, et al. Deep learning with convolutional neural network for differentiation of liver masses at dynamic contrast-enhanced CT: a preliminary study[J]. Radiology, 2018, 286(3): 887-896. DOI: 10.1148/radiol.2017170706.
    [29]
    HU HT, WANG W, CHEN LD, et al. Artificial intelligence assists identifying malignant versus benign liver lesions using contrast-enhanced ultrasound[J]. J Gastroenterol Hepatol, 2021, 36(10): 2875-2883. DOI: 10.1111/jgh.15522.
    [30]
    ZHOU JM, WANG T, ZHANG KH. AFP-L3 for the diagnosis of early hepatocellular carcinoma: A meta-analysis[J]. Medicine (Baltimore), 2021, 100(43): e27673. DOI: 10.1097/MD.0000000000027673.
    [31]
    CHOI J, KIM GA, HAN S, et al. Longitudinal assessment of three serum biomarkers to detect very early-stage hepatocellular carcinoma[J]. Hepatology, 2019, 69(5): 1983-1994. DOI: 10.1002/hep.30233.
    [32]
    BEST J, BECHMANN LP, SOWA JP, et al. GALAD score detects early hepatocellular carcinoma in an international cohort of patients with nonalcoholic steatohepatitis[J]. Clin Gastroenterol Hepatol, 2020, 18(3): 728-735. e4. DOI: 10.1016/j.cgh.2019.11.012.
    [33]
    CAVIGLIA GP, CIRUOLO M, ABATE ML, et al. Alpha-fetoprotein, protein induced by vitamin K absence or antagonist ii and glypican-3 for the detection and prediction of hepatocellular carcinoma in patients with cirrhosis of viral Etiology[J]. Cancers (Basel), 2020, 12(11): 3218. DOI: 10.3390/cancers12113218.
    [34]
    SAMMAN BS, HUSSEIN A, SAMMAN RS, et al. Common sensitive diagnostic and prognostic markers in hepatocellular carcinoma and their clinical significance: a Review[J]. Cureus, 2022, 14(4): e23952. DOI: 10.7759/cureus.23952.
    [35]
    SHAKER MK, ATTIA FM, HASSAN AA, et al. Evaluation of golgi protein 73 (GP73) as a potential biomarkers for hepatocellular carcinoma[J]. Clin Lab, 2020, 66(8): 190911. DOI: 10.7754/Clin.Lab.2020.190911.
    [36]
    YAMASHITA T, KOSHIKAWA N, SHIMAKAMI T, et al. Serum laminin γ2 monomer as a diagnostic and predictive biomarker for hepatocellular carcinoma[J]. Hepatology, 2021, 74(2): 760-775. DOI: 10.1002/hep.31758.
    [37]
    CHEN L, ZHANG H, JIANG B. Diagnostic value of combined detection of serum AFP, GGTI Ⅱ, AFU and DCP in liver cancer[J]. J Mol Diagn Ther, 2022, 14 (8): 1283-1286, 1291. DOI: 10.3969/j.issn.1674-6929.2022.08.006.

    陈琳, 张恒, 江斌. 血清AFP、GGTIⅡ、AFU和DCP联合检测对肝癌的诊断价值[J]. 分子诊断与治疗杂志, 2022, 14(8): 1283-1286, 1291. DOI: 10.3969/j.issn.1674-6929.2022.08.006.
    [38]
    EUN JW, JANG JW, YANG HD, et al. Serum proteins, HMMR, NXPH4, PITX1 and THBS4; a panel of biomarkers for early diagnosis of hepatocellular carcinoma[J]. J Clin Med, 2022, 11(8): 2128. DOI: 10.3390/jcm11082128.
    [39]
    CHEN L, ABOU-ALFA GK, ZHENG B, et al. Genome-scale profiling of circulating cell-free DNA signatures for early detection of hepatocellular carcinoma in cirrhotic patients[J]. Cell Res, 2021, 31(5): 589-592. DOI: 10.1038/s41422-020-00457-7.
    [40]
    CHALASANI NP, RAMASUBRAMANIAN TS, BHATTACHARYA A, et al. A novel blood-based panel of methylated dna and protein markers for detection of early-stage hepatocellular carcinoma[J]. Clin Gastroenterol Hepatol, 2021, 19(12): 2597-2605. e4. DOI: 10.1016/j.cgh.2020.08.065.
    [41]
    ZHOU J, YU L, GAO X, et al. Plasma microRNA panel to diagnose hepatitis B virus-related hepatocellular carcinoma[J]. J Clin Oncol, 2011, 29(36): 4781-4788. DOI: 10.1200/JCO.2011.38.2697.
    [42]
    LI YS, YANG ZG, CHEN Y, et al. Differential expression profile of cyclic RNA in serum exocrine bodies of hepatocellular carcinoma and its clinical significance[J]. J Hepatopancreatobiliary Surg, 2022, 34(5): 283-287. DOI: 10.11952/j.issn.1007-1954.2022.05.006.

    李叶晟, 杨宗国, 陈晹, 等. 肝癌血清外泌体环状RNA表达谱差异及其临床意义[J]. 肝胆胰外科杂志, 2022, 34(5): 283-287. DOI: 10.11952/j.issn.1007-1954.2022.05.006.
    [43]
    Large scale prospective cohort study data of early screening liquid biopsy for liver cancer[EB/OL]. [2021-09-01]. https://www.genetronhealth.com/product_detail.html.

    肝癌早筛液体活检大规模前瞻性队列研究数据[EB/OL]. [2021-09-01]. https://www.genetronhealth.com/product_detail.html.
    [44]
    LIN N, LIN Y, XU J, et al. A multi-analyte cell-free DNA-based blood test for early detection of hepatocellular carcinoma[J]. Hepatol Commun, 2022, 6(7): 1753-1763. DOI: 10.1002/hep4.1918.
    [45]
    ZHAN S, YANG P, ZHOU S, et al. Serum mitochondrial tsRNA serves as a novel biomarker for hepatocarcinoma diagnosis[J]. Front Med, 2022, 16(2): 216-226. DOI: 10.1007/s11684-022-0920-7.
    [46]
    LI Y, LI R, CHENG D, et al. The potential of CircRNA1002 as a biomarker in hepatitis B virus-related hepatocellular carcinoma[J]. Peer J, 2022, 10: e13640. DOI: 10.7717/peerj.13640.
    [47]
    STEPIEN M, KESKI-RAHKONEN P, KISS A, et al. Metabolic perturbations prior to hepatocellular carcinoma diagnosis: Findings from a prospective observational cohort study[J]. Int J Cancer, 2021, 148(3): 609-625. DOI: 10.1002/ijc.33236.
    [48]
    WANG SF, BAI ZF, YANG X, et al. Determination of serum metabolic group in patients with hepatocellular carcinoma by UPLC-QTOF-MS/MS technique[J]. Chin J Pharmacol Toxicol, 2020, 34(12): 918-929. DOI: 10.3867/j.issn.1000-3002.2020.12.004.

    王淑凤, 柏兆方, 杨馨, 等. 应用UPLC-QTOF-MS/MS技术测定肝细胞癌患者血清代谢组[J]. 中国药理学与毒理学杂志, 2020, 34(12): 918-929. DOI: 10.3867/j.issn.1000-3002.2020.12.004.
    [49]
    LIU J, GENG W, SUN H, et al. Integrative metabolomic characterisation identifies altered portal vein serum metabolome contributing to human hepatocellular carcinoma[J]. Gut, 2022, 71(6): 1203-1213. DOI: 10.1136/gutjnl-2021-325189.
    [50]
    YANG T, WANG Y, DAI W, et al. Increased B3GALNT2 in hepatocellular carcinoma promotes macrophage recruitment via reducing acetoacetate secretion and elevating MIF activity[J]. J Hematol Oncol, 2018, 11(1): 50. DOI: 10.1186/s13045-018-0595-3.v
    [51]
    CONG M, OU X, HUANG J, et al. A predictive model using n-glycan biosignatures for clinical diagnosis of early hepatocellular carcinoma related to hepatitis B virus[J]. OMICS, 2020, 24(7): 415-423. DOI: 10.1089/omi.2020.0055.
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