Advances in the radiogenomics of hepatocellular carcinoma

Share this content in WeChat

• Review •

LIU Yu LI Jie DONG Chunjiao PAN Xinyue SHANG Dandan

Cite this article as: LIU Y, LI J, DONG C J, et al. Advances in the radiogenomics of hepatocellular carcinoma[J]. Chin J Magn Reson Imaging, 2024, 15(9): 205-210. DOI:10.12015/issn.1674-8034.2024.09.036.

Abstract

[Abstract] Hepatocellular carcinoma (HCC) is a malignant tumor with high incidence and lethality, and its early diagnosis, precision treatment and prognosis evaluation have always been the focus of medical research. The prognosis of HCC diagnosis and treatment is closely related to the mutation status of the tumor gene, but the traditional detection of HCC gene mutation status is mainly based on invasive methods. In recent years, radiogenomics has developed rapidly, which can associate the gene mutation status with the imaging characteristics of tumor tissue, bringing hope for the non-invasive prediction of HCC gene mutation status. At present, there have been many radiogenomics studies on HCC related gene mutations, but still lacking systematic combing and summary of the research methods and results. This paper reviews the current research status of radiogenomics using machine learning and big data technology for non-invasive evaluation of HCC, discusses the existing challenges, and explores future directions to provide a reference for advancing research in this field, as well as for enhancing clinical decision-making and precision treatment for HCC patients.

[Keywords] liver cancer；hepatocellular carcinoma；radiomics；radiogenomics；magnetic resonance imaging

Contributor Information

LIU Yu¹ LI Jie² DONG Chunjiao² PAN Xinyue¹ SHANG Dandan^1*

¹ Department of Basic Medicine, Hebei Medical University, Shijiazhuang 050017, China

² Department of Medical Imaging, Hebei Medical University, Shijiazhuang 050017, China

Corresponding author: SHANG D D, E-mail: lily.dandan@163.com

Conflicts of interest None.

Publication Information

Received 2024-06-07

Accepted 2024-09-10

DOI: 10.12015/issn.1674-8034.2024.09.036

Text

References

[1]

PETRICK J L, FLORIO A A, ZNAOR A, et al. International trends in hepatocellular carcinoma incidence, 1978-2012[J]. Int J Cancer, 2020, 147(2): 317-330. DOI: 10.1002/ijc.32723.

[2]

JIANG D Z, MA X Y, ZHANG X, et al. New techniques: a roadmap for the development of HCC immunotherapy[J/OL]. Front Immunol, 2023, 14: 1121162 [2024-05-31]. https://pubmed.ncbi.nlm.nih.gov/37426674/. DOI: 10.3389/fimmu.2023.1121162.

[3]

WANG Y, DENG B C. Hepatocellular carcinoma: molecular mechanism, targeted therapy, and biomarkers[J]. Cancer Metastasis Rev, 2023, 42(3): 629-652. DOI: 10.1007/s10555-023-10084-4.

[4]

BRAY F, LAVERSANNE M, SUNG H, et al. Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries[J]. CA Cancer J Clin, 2024, 74(3): 229-263. DOI: 10.3322/caac.21834.

[5]

SUN X L. Research progress in the application of MRI imaging in liver cancer[J]. J Clin Radiol, 2023, 42(1): 141-144. DOI: 10.13437/j.cnki.jcr.2023.01.007.

[6]

WU J J, DAI H, ZHANG M M, et al. Radiomics analysis based on T2-fluid attenuated inversion recovery for evaluating the recurrence within 1 year after surgery in high-grade glioma[J]. Chin Comput Med Imag, 2024, 30(2): 134-140. DOI: 10.3969/j.issn.1006-5741.2024.02.003.

[7]

LAMBIN P, RIOS-VELAZQUEZ E, LEIJENAAR R, et al. Radiomics: extracting more information from medical images using advanced feature analysis[J]. Eur J Cancer, 2012, 48(4): 441-446. DOI: 10.1016/j.ejca.2011.11.036.

[8]

GUIOT J, VAIDYANATHAN A, DEPREZ L, et al. A review in radiomics: making personalized medicine a reality via routine imaging[J]. Med Res Rev, 2022, 42(1): 426-440. DOI: 10.1002/med.21846.

[9]

LEE I C, HUANG J Y, CHEN T C, et al. Evolutionary learning-derived clinical-radiomic models for predicting early recurrence of hepatocellular carcinoma after resection[J]. Liver Cancer, 2021, 10(6): 572-582. DOI: 10.1159/000518728.

[10]

MENG X P, WANG Y C, JU S H, et al. Radiomics analysis on multiphase contrast-enhanced CT: a survival prediction tool in patients with hepatocellular carcinoma undergoing transarterial chemoembolization[J/OL]. Front Oncol, 2020, 10: 1196 [2024-06-01]. https://pubmed.ncbi.nlm.nih.gov/32850345/. DOI: 10.3389/fonc.2020.01196.

[11]

QI Y N, ZHAO T T, HAN M Y. The application of radiomics in predicting gene mutations in cancer[J]. Eur Radiol, 2022, 32(6): 4014-4024. DOI: 10.1007/s00330-021-08520-6.

[12]

PORCU M, SOLINAS C, MANNELLI L, et al. Radiomics and "radi-…omics" in cancer immunotherapy: a guide for clinicians[J/OL]. Crit Rev Oncol Hematol, 2020, 154: 103068 [2024-06-01]. https://pubmed.ncbi.nlm.nih.gov/32805498/. DOI: 10.1016/j.critrevonc.2020.103068.

[13]

WANG J, KANG B, SUN C, et al. CT-based radiomics nomogram for differentiating gastric hepatoid adenocarcinoma from gastric adenocarcinoma: a multicentre study[J]. Expert Rev Gastroenterol Hepatol, 2023, 17(2): 205-214. DOI: 10.1080/17474124.2023.2166490.

[14]

GULLO R L, DAIMIEL I, MORRIS E A, et al. Combining molecular and imaging metrics in cancer: radiogenomics[J/OL]. Insights Imaging, 2020, 11(1): 1 [2024-07-11]. https://pubmed.ncbi.nlm.nih.gov/31901171/. DOI: 10.1186/s13244-019-0795-6.

[15]

LIU Z Q, DUAN T, ZHANG Y Y, et al. Radiogenomics: a key component of precision cancer medicine[J]. Br J Cancer, 2023, 129(5): 741-753. DOI: 10.1038/s41416-023-02317-8.

[16]

BAI Y P, YANG Z, SHI A Y, et al. Clinical application of radiomics in hepatocellular carcinoma[J]. Chin J Surg Oncol, 2023, 15(2): 192-196. DOI: 10.3969/j.issn.1674-4136.2023.02.018.

[17]

BOEHM K M, KHOSRAVI P, VANGURI R, et al. Harnessing multimodal data integration to advance precision oncology[J]. Nat Rev Cancer, 2022, 22(2): 114-126. DOI: 10.1038/s41568-021-00408-3.

[18]

YUAN J L, XIE X T, ZHANG P N, et al. Research progress of machine learning model based on CT and MRI radiomics for predicting early recurrence of hepatocellular carcinoma[J]. Chin J Magn Reson Imag, 2022, 13(12): 154-158. DOI: 10.12015/issn.1674-8034.2022.12.029.

[19]

XIA T Y, ZHAO B, LI B R, et al. MRI-based radiomics and deep learning in biological characteristics and prognosis of hepatocellular carcinoma: opportunities and challenges[J]. J Magn Reson Imaging, 2024, 59(3): 767-783. DOI: 10.1002/jmri.28982.

[20]

SUN E J, WANKELL M, PALAMUTHUSINGAM P, et al. Targeting the PI3K/akt/mTOR pathway in hepatocellular carcinoma[J/OL]. Biomedicines, 2021, 9(11): 1639 [2024-05-10]. https://pubmed.ncbi.nlm.nih.gov/34829868/. DOI: 10.3390/biomedicines9111639.

[21]

TIAN L Y, SMIT D J, JÜCKER M. The role of PI3K/AKT/mTOR signaling in hepatocellular carcinoma metabolism[J/OL]. Int J Mol Sci, 2023, 24(3): 2652 [2024-05-11]. https://pubmed.ncbi.nlm.nih.gov/36768977/. DOI: 10.3390/ijms24032652.

[22]

LIAO H T, JIANG H Y, CHEN Y T, et al. Predicting genomic alterations of phosphatidylinositol-3 kinase signaling in hepatocellular carcinoma: a radiogenomics study based on next-generation sequencing and contrast-enhanced CT[J/OL]. Ann Surg Oncol, 2022 [2023-03-26]. https://pubmed.ncbi.nlm.nih.gov/35286532/. DOI: 10.1245/s10434-022-11505-4.

[23]

AN J, OH M, KIM S Y, et al. PET-based radiogenomics supports mTOR pathway targeting for hepatocellular carcinoma[J]. Clin Cancer Res, 2022, 28(9): 1821-1831. DOI: 10.1158/1078-0432.CCR-21-3208.

[24]

ZHUANG W T, YE T, WANG W, et al. CTNNB1 in neurodevelopmental disorders[J/OL]. Front Psychiatry, 2023, 14: 1143328 [2024-05-01]. https://pubmed.ncbi.nlm.nih.gov/37009120/. DOI: 10.3389/fpsyt.2023.1143328.

[25]

HUO J Y, WU L Q, ZANG Y J. Development and validation of a CTNNB1-associated metabolic prognostic model for hepatocellular carcinoma[J]. J Cell Mol Med, 2021, 25(2): 1151-1165. DOI: 10.1111/jcmm.16181.

[26]

TÜMEN D, HEUMANN P, GÜLOW K, et al. Pathogenesis and current treatment strategies of hepatocellular carcinoma[J/OL]. Biomedicines, 2022, 10(12): 3202 [2024-05-10]. https://pubmed.ncbi.nlm.nih.gov/36551958/. DOI: 10.3390/biomedicines10123202.

[27]

YONEDA N, MATSUI O, KOBAYASHI S, et al. Current status of imaging biomarkers predicting the biological nature of hepatocellular carcinoma[J]. Jpn J Radiol, 2019, 37(3): 191-208. DOI: 10.1007/s11604-019-00817-3.

[28]

UENO A, MASUGI Y, YAMAZAKI K, et al. OATP1B3 expression is strongly associated with Wnt/β-catenin signalling and represents the transporter of gadoxetic acid in hepatocellular carcinoma[J]. J Hepatol, 2014, 61(5): 1080-1087. DOI: 10.1016/j.jhep.2014.06.008.

[29]

AREFAN D, D'ARDENNE N M, IRANPOUR N, et al. Quantitative radiomics and qualitative LI-RADS imaging descriptors for non-invasive assessment of β-catenin mutation status in hepatocellular carcinoma[J]. Abdom Radiol (NY), 2024, 49(7): 2220-2230. DOI: 10.1007/s00261-024-04344-2.

[30]

LIU Y K, YANG Q. The roles of EZH2 in cancer and its inhibitors[J/OL]. Med Oncol, 2023, 40(6): 167 [2024-05-19]. https://pubmed.ncbi.nlm.nih.gov/37148376/. DOI: 10.1007/s12032-023-02025-6.

[31]

YANG D, WANG S H, CHEN S H, et al. Analysis of EZH2 gene expression level in hepatocellular carcinoma tissues and its clinical significance by bioinformatics method[J]. Int J Lab Med, 2023, 44(2): 147-153. DOI: 10.3969/j.issn.1673-4130.2023.02.004.

[32]

BAE A N, JUNG S J, LEE J H, et al. Clinical value of EZH2 in hepatocellular carcinoma and its potential for target therapy[J/OL]. Medicina, 2022, 58(2): 155 [2024-06-13]. https://pubmed.ncbi.nlm.nih.gov/35208478/. DOI: 10.3390/medicina58020155.

[33]

KULLMANN M K, PODMIRSEG S R, ROILO M, et al. The CDK inhibitor p57Kip2 enhances the activity of the transcriptional coactivator FHL2[J/OL]. Sci Rep, 2020, 10(1): 7140 [2024-06-10]. https://pubmed.ncbi.nlm.nih.gov/32346031/. DOI: 10.1038/s41598-020-62641-4.

[34]

MA X A, WU T, GUO H, et al. The expression and prognostic significance of p57, CKS1 and SKP2 mRNA in hepatocellular carcinoma utilizing Oncomine and TCGA Datasets[J]. Clin Res Pract, 2016, 1(25): 1-4. DOI: 10.3969/j.issn.2096-1413.2016.25.001.

[35]

WANG Q, CHAI X Q. Construction and validation of a preoperative nomogram prediction model for microvascular invasion in small hepatocellular carcinoma[J]. J Hepatopancreatobiliary Surg, 2024, 36(3): 136-143. DOI: 10.11952/j.issn.1007-1954.2024.03.002.

[36]

ZHANG Y M, CUI J, WAN W, et al. Multimodal imaging under artificial intelligence algorithm for the diagnosis of liver cancer and its relationship with expressions of EZH2 and p57[J/OL]. Comput Intell Neurosci, 2022, 2022: 4081654 [2024-05-21]. https://pubmed.ncbi.nlm.nih.gov/35321452/. DOI: 10.1155/2022/4081654.

[37]

YE G B, LING B. Research progress of Golgi body membrane protein 1 gene in tumor[J]. J Youjiang Med Univ Natl, 2023, 45(5): 812-815. DOI: 10.3969/j.issn.1001-5817.2023.05.022.

[38]

CAO L M, WANG M, XU K. Research progress of role and mechanism of SETD7 in tumor occurrence and progression[J]. Chin J Lung Cancer, 2023, 26(1): 38-45. DOI: 10.3779/j.issn.1009-3419.2023.106.02.

[39]

CHEN Y Y, YANG S S, HU J W, et al. Increased expression of SETD7 promotes cell proliferation by regulating cell cycle and indicates poor prognosis in hepatocellular carcinoma[J/OL]. PLoS One, 2016, 11(5): e0154939 [2024-06-10]. https://pubmed.ncbi.nlm.nih.gov/27183310/. DOI: 10.1371/journal.pone.0154939.

[40]

MASRI R E, DELON J. RHO GTPases: from new partners to complex immune syndromes[J]. Nat Rev Immunol, 2021, 21(8): 499-513. DOI: 10.1038/s41577-021-00500-7.

[41]

QIN C D, MA D N, ZHANG S Z, et al. The Rho GTPase Rnd1 inhibits epithelial-mesenchymal transition in hepatocellular carcinoma and is a favorable anti-metastasis target[J/OL]. Cell Death Dis, 2018, 9(5): 486 [2024-07-10]. https://pubmed.ncbi.nlm.nih.gov/29706627/. DOI: 10.1038/s41419-018-0517-x.

[42]

LI X M, CHENG L, LI C M, et al. Associating Preoperative MRI Features and Gene Expression Signatures of Early-stage Hepatocellular Carcinoma Patients using Machine Learning[J]. J Clin Transl Hepatol, 2022, 10(1): 63-71. DOI: 10.14218/JCTH.2021.00023.

[43]

SEGAL E, SIRLIN C B, OOI C, et al. Decoding global gene expression programs in liver cancer by noninvasive imaging[J]. Nat Biotechnol, 2007, 25(6): 675-680. DOI: 10.1038/nbt1306.

[44]

TAOULI B, HOSHIDA Y, KAKITE S, et al. Imaging-based surrogate markers of transcriptome subclasses and signatures in hepatocellular carcinoma: preliminary results[J]. Eur Radiol, 2017, 27(11): 4472-4481. DOI: 10.1007/s00330-017-4844-6.

[45]

XIA W, CHEN Y, ZHANG R, et al. Radiogenomics of hepatocellular carcinoma: multiregion analysis-based identification of prognostic imaging biomarkers by integrating gene data-a preliminary study[J/OL]. Phys Med Biol, 2018, 63(3): 035044 [2024-05-22]. https://pubmed.ncbi.nlm.nih.gov/29311419/. DOI: 10.1088/1361-6560/aaa609.

[46]

WANG D D, ZHANG L H, SUN Z Q, et al. A radiomics signature associated with underlying gene expression pattern for the prediction of prognosis and treatment response in hepatocellular carcinoma[J/OL]. Eur J Radiol, 2023, 167: 111086 [2024-06-14]. https://pubmed.ncbi.nlm.nih.gov/37708675/. DOI: 10.1016/j.ejrad.2023.111086.

[47]

WANG Y J, WENG W X, LIANG R M, et al. Predicting T cell-inflamed gene expression profile in hepatocellular carcinoma based on dynamic contrast-enhanced ultrasound radiomics[J]. J Hepatocell Carcinoma, 2023, 10: 2291-2303. DOI: 10.2147/JHC.S437415.

[48]

FENTON S E, BURNS M C, KALYAN A. Epidemiology, mutational landscape and staging of hepatocellular carcinoma[J/OL]. Chin Clin Oncol, 2021, 10(1): 2 [2024-07-14]. https://pubmed.ncbi.nlm.nih.gov/33541087/. DOI: 10.21037/cco-20-162.

[49]

PINYOL R, TORRECILLA S, WANG H, et al. Molecular characterisation of hepatocellular carcinoma in patients with non-alcoholic steatohepatitis[J]. J Hepatol, 2021, 75(4): 865-878. DOI: 10.1016/j.jhep.2021.04.049.

[50]

ZHOU W, XU D M, ZHANG H, et al. Discussion on the relationship between medical imaging technology and medical imaging diagnosis[J]. Chinese Community Doctors, 2021, 37(22): 106-107. DOI: 10.3969/j.issn.1007-614x.2021.22.051.

[51]

YUAN E Y, SONG B. Clinical application of liver cancer imaging: present situation and prospect[J]. Radiol Pract, 2023, 38(9): 1084-1088. DOI: 10.13609/j.cnki.1000-0313.2023.09.001.

PREV Progress in MRI evaluation of nonalcoholic fatty liver disease

NEXT Current status and prospects of radiomics in the diagnosis of colorectal cancer

LINK

Tel & Fax: +8610-67113815 E-mail: editor@cjmri.cn