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. 2016 Dec 5;6:38311. doi: 10.1038/srep38311

Biomarker MicroRNAs for Diagnosis, Prognosis and Treatment of Hepatocellular Carcinoma: A Functional Survey and Comparison

Sijia Shen 1,2,*, Yuxin Lin 2,*, Xuye Yuan 2, Li Shen 2,3, Jiajia Chen 2, Luonan Chen 4, Lei Qin 1,a, Bairong Shen 2,b
PMCID: PMC5137156  PMID: 27917899

Abstract

Hepatocellular Carcinoma (HCC) is one of the most common malignant tumors with high incidence and mortality rate. Precision and effective biomarkers are therefore urgently needed for the early diagnosis and prognostic estimation. MicroRNAs (miRNAs) are important regulators which play functions in various cellular processes and biological activities. Accumulating evidence indicated that the abnormal expression of miRNAs are closely associated with HCC initiation and progression. Recently, many biomarker miRNAs for HCC have been identified from blood or tissues samples, however, the universality and specificity on clinicopathological features of them are less investigated. In this review, we comprehensively surveyed and compared the diagnostic, prognostic, and therapeutic roles of HCC biomarker miRNAs in blood and tissues based on the cancer hallmarks, etiological factors as well as ethnic groups, which will be helpful to the understanding of the pathogenesis of biomarker miRNAs in HCC development and further provide accurate clinical decisions for HCC diagnosis and treatment.

Hepatocellular Carcinoma (HCC) is the sixth most common cancer worldwide in terms of number of cases and the second major contributor to cancer mortality in man. The survival rates in the United States and developed countries are only 3% to 5%1,2. There are still no effective biomarkers for the early diagnosis and prognosis of HCC. Currently, only about 30% to 40% patients with HCC can get effective treatment at the right time3. It is extremely necessary to discover new biomarkers for precision diagnosis, prognosis and treatment of HCC.

MicroRNAs (miRNAs) are small endogenous non-coding RNAs with 22–24 nucleotides in length. They play important roles in regulating human genes by inhibiting translation or cleavage. Recent studies showed that miRNAs were associated with a variety of important biological processes such as cell proliferation, development, and apoptosis4,5. Accumulating evidence indicated that miRNAs could be latent biomarkers in human cancers, including gastric cancer, lung cancer, prostate cancer, and breast cancer etc.6,7,8,9. Nowadays, extensive research efforts have demonstrated the biomarker role of miRNAs in HCC. For example, Jiang and his colleagues confirmed that miRNA panel assay (miR-10b, miR-106b and miR-181a) could be potential biomarkers for HCC preliminary screening10. He et al. focused on the applications of miRNAs from 13 studies and 21 sets of data and the association between the risk of HCC and miRNAs polymorphisms11. Another review summarized the function of circulating miRNAs12, and a meta-analysis included 14 studies involving 1,848 cases with HCC and 1187 controls concluded that the miRNA panels can be biomarkers for HCC with AUC = 0.99 (96% sensitivity and 96% specificity)13. Many comprehensive reviews recommend to pay attentions to the role and function of miRNAs in disease diagnosis, prognosis and therapy14,15,16,17,18,19,20,21,22. However, the differences in biological features of miRNAs between blood and tissues are still unclear, which limits the investigation on understanding clinical implications of miRNAs in different specimen.

In this review, we performed comprehensive functional analyses and comparisons of miRNA biomarkers in blood and tissues. The miRNA biomarkers in “tissues” were mainly extracted from liver tissues, adjacent noncancerous tissues or human HCC tissues whereas those in “blood” were collected from plasma, serum or whole blood samples. This review aims at comprehensively understanding the pathogenic mechanism and clinical value of HCC biomarker miRNAs, and providing insights into precision diagnosis and treatment of HCC.

Methods

Data collection

We systematically collected HCC biomarker miRNAs from citations in NCBI PubMed by retrieval formula “(liver cancer[tiab] OR intrahepatic bile duct[tiab] OR hepatocellular carcinoma[tiab] OR hepatoblastoma[tiab] OR cholangiocarcinoma[tiab]) AND (miRNA* OR microRNA*) AND (biomarker*[tiab] OR marker*[tiab] OR indicator*[tiab] OR predictor*[tiab])”. Here, studies in which miRNAs were exactly defined as markers or biomarkers were mainly considered, and those identified from body fluids such as saliva, urine and sweat were excluded as we only focused on miRNA biomarkers in blood and tissues. Besides, for further comparing the differentiation between HCC and cirrhosis and providing valuable strategies for the early detection of HCC, we also collected diagnostic miRNA biomarkers for liver cirrhosis using retrieval formula “cirrhosis[tiab] AND diagnos*[tiab] AND (miRNA* OR microRNA*) AND (biomarker*[tiab] OR marker*[tiab] OR indicator*[tiab] OR predictor*[tiab])”.

Target genes of miRNA biomarkers

The miRNA targets used in this study were integrated from both experimentally validated, i.e. miR2Disease23, TarBase (version 6.0)24, miRTarBase (version 4.5)25, miRecords (version 4.0)26 and computationally predicted, i.e. HOCTAR (version 2.0)27, ExprTargetDB28, and starBase (version 2.0)29 miRNA-target databases. To reduce false positives, we mainly selected miRNA-mRNA pairs validated by low-throughput experiments, i.e. real-time quantitative PCR, Western blot, etc. For computationally predicted pairs, they should reside in no fewer than two of the three prediction databases. Meanwhile, we unitized miRNA IDs according to the latest nomenclature in miRBase (release 21)30.

Functional survey of HCC biomarker miRNAs

The functions of HCC biomarker miRNAs are summarized based on the hallmarks of cancers31,32. Since some of the miRNAs are associated with liver injury and few of the miRNAs’ functions are unclear, we therefore grouped their functions into 12 categories as antigrowth signals, resisting cell death, avoiding immune destruction, tissue invasion and metastasis, tumor promotion inflammation, sustained angiogenesis, limitless replicative potential, genome instability and mutation, other clinicopathological features, liver injury, tumor suppressor/onco-miR, and unclear. Moreover, we compared the pathogenesis of HCC biomarker miRNAs based on etiological factors as well as ethnic groups, i.e. the effects of Hepatitis B Virus (HBV), Hepatitis C Virus (HCV) and ethnic variation on HCC development.

Pathway enrichment analyses

For better understanding the association between miRNAs and HCC pathogenesis, we mapped the targets of biomarker miRNAs onto signaling pathways using IPA (Ingenuity Pathway Analysis) program. The top 10 significantly enriched pathways (p-value < 0.01) were selected and further validated the correlation with HCC by PubMed literature exploration.

Results

Overview of the collected HCC biomarker miRNAs

After manually searching and checking in PubMed citations, a total of 50 and 18 diagnostic miRNA biomarkers in blood and tissues, respectively, were extracted from 44 articles (see Tables 1 and 2) and their clinicopathological features of HCC were further compared based on the hallmarks of cancer31, etiological factors and ethnic groups, respectively. As for prognostic and therapeutic biomarkers, respectively, 16 and 32 prognostic miRNAs in blood and tissues together with 8 therapeutic markers were collected according to records in 54 articles (see Tables 3, 4 and 5) and their clinicopathological features as well as functions were then explored.

Table 1. Diagnostic biomarkers in tissues for hepatocellular carcinoma.

Reported ID Offical ID Sample Ethnicity Features Expression AUC PMID Validated Targets
miR-101 miR-101-3p 30 HC 67 CHB 61 HBV-LC 67 HBV-HCC China 1.inhibit HCC cell proliferation2.tumor suppressor3.promote apoptosis down CHB from HC 0.635 HBV-LC from HC 0.884 HBV-HCC from HC 0.788 2497195338 Mcl-1, SOX9
miR-126 miR-126-3p 19 HCV 6 HCC Germany tumor suppressor down NA 2550007595 NA
miR-127 miR-127-3p 33 HCC China tumor suppressor down NA 2485484296 NA
miR-130b miR-130b-3p 97 HCC China onco-miR up 0.914 2240334434 RUNX3
miR-139 miR-139-5p 31 CHB 31 HCC China 1.suppress metastasis and progression of cancer cells2.tumor suppressor down HCC from CH 0.761 (0.7701) 2454928251 Rho-kinase 2
miR-148a miR-148a-3p 19 HCC China onco-miR up NA 22496917106 NA
miR-150 miR-150-5p 15 HC 15 ICC China tumor suppressor up 0.764 2548232097 NA
miR-15b miR-15b-5p 96 HCC China preventing replicative stress in response to mitogenicsignalling up 0.982 2240334434 NA
miR-182 miR-182-5p HCC China proliferation up NA 2465362385 IGF1R and GSK3B
miR-18b miR-18b-5p 110 HCC Japan 1.proliferation2.loss of cell adhesion ability up NA 2349690152 TNRC6B
miR-199a miR-199a-5p 17 CH 23 HCC Egypt NA down 0.856 2630275154 Mitogen-activated protein kinase (MAPK)
miR-200a miR-200a-3p 29 HCC Germany suppress cancer cell migration up NA 2489532653 ZEB1/ZEB2
miR-200b miR-200b-3p 29 HCC Germany suppress cancer cell migration up NA 2489532653 ZEB1/ZEB2
miR-21 miR-21-5p 50 HC 30 LC 136 HCC Japan excessive secretion by primary cancer cells up CH from HC 0.773 HCC from HC 0.953 21749846110 NA
miR-21 miR-21-5p 17 CH 23 HCC Egypt 1.cell growth2.migration3.invasion up 0.943 2630275154 phosphatase and tensin homolog (PTEN)
miR-21 miR-21-5p 30 HC 97 HCC China 1.promote cell proliferation2.tumor invasion up NA 2597303255 PDCD4 and PTEN
miR-21 miR-21-5p 74 ICC China intrahepatic cholangiocarcinoma proliferation and growth up NA 2580322956 PTPN14 and PTEN
miR-214 miR-214-3p 9 HC 10 HCC China tumor suppressor down NA 2478942039 EZH2, CTNNB1 and CDH1
miR-224 miR-224-5p 9 HC 10 HCC China 1.cell proliferation2.migration3.invasion4.anti-apoptosis up NA 2478942039 CD40
miR-29a-5p miR-29a-5p 266 HCC China 1.tissue invasiveness and metastasis r2.tumor suppresso up 0.746 2328502257 NA
miR-483-5p miR-483-5p 69 HC 69 HCC America anti-apoptotic oncogene up HCC from HC 0.827 2412741340 NA
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Abbreviations and note: HC: healthy controls; CHB: patients with chronic type B hepatitis; CH: chronic hepatitis; HCV: hepatitis C virus; HCC: hepatocellular carcinoma; LC: liver cirrhosis; HBV: hepatitis B virus; ICC: Intrahepatic cholangiocarcinoma; NA: not available; 1: combination of plasma miRNA-139 with serum AFP; 2: combined miR-15b and miR-130b.

Table 2. Diagnostic biomarkers in blood for hepatocellular carcinoma.

Reported ID Offical ID Sample Source Ethnicity Features Expression AUC PMID Validated Targets
miR-199a-3p miR-199a-3p 156 HC 78 HCC serum China invasion capability down 0.883 2561859958 phosphorylated-S6 protein
miR-223 miR-223-3p 167 HC 169 CHB 141 LC 457 HCC blood China NA down 0.864(training set) 0.888(validation set) 2210582259 Stathmin1
miR-101 miR-101-3p 30 HC 79 CHB 61 HBV-LC 67 HBV-HCC serum China 1.inhibit HCC cell proliferation2.tumor suppressor3.promote apoptosis down1 CHB from HC 0.635 HBV-LC from HC 0.884 HBV-HCC from HC 0.788 2497195338 Mcl-1, SOX9
miR-106b miR-106b-5p 50 HC 31 CLD 27 HCC blood China Proliferation up HCC from HC 0.89 HCC from CLD 0.81 CLD from HC 0.63 2576117910 p21/E2F5
miR-10b miR-10b-5p 50 HC 31 CLD 27 HCC blood China 1.onco-miR2.liver injury up HCC from HC 0.85 HCC from CLD 0.73 CLD from HC 0.66 2576117910 NA
miR-122 miR-122-5p 89 HC 48 CHB 101 HCC blood China liver injury up HCC from HC 0.79 CHB from HC 0.93 2122961092 NA
miR-122 miR-122-5p 167 HC 169 CHB 141 LC 457 HCC blood China 1.tumor size2.differentiation grade3.poor prognosis4.distance metastasis down 0.864(training set) 0.888(validation set) 2210582259 NA
miR-122 miR-122-5p 15 HC 30 DN 120 HCC serum China 1.induce apoptosis2.suppress proliferation up 0.629 2626455344 NA
miR-122 miR-122-5p 34 HC 70 HBV-HCC 48 CHB serum China liver injury up HCC from HC 0.869 HBV-HCC from CHB 0.630 2217481893 NA
miR-122-5p miR-122-5p 173 HC 233 LC 261 HCC serum China 1.regulating hepatocyte development and differentiation2.apoptosis and suppress proliferation down 0.887(training sets) 0.879(validation sets) 2523823886 HepG2 and Hep3B cells
miR-1228-5p miR-1228-5p 173 HC 233 LC 261 HCC serum China NA up 0.887(training sets) 0.879(validation sets) 2523823886 NA
miR-122a miR-122-5p 85 volunteers matched serum China tumor suppressor down 0.707(0.943)2 2372371398 NA
miR-125b-5p miR-125b-5p 28 HC 24 CHB 22 HBV-LC 20 HBV-HCC plasma Turkey suppress the cell growth up NA 2459545033 AKT
miR-130a miR-130a-3p 42 HC 125 HCV-CLD 112 HCV-HCC blood Egypt NA up HCV-HCC from HC 0.91 2635274042 NA
miR-130b miR-130b-3p 97 HCC serum China onco-miR up 0.914 22403344134 RUNX3
miR-139 miR-139-5p 31 CHB 31 HCC plasma China 1.suppress metastasis and progression of cancer cells2.tumor suppressor down HCC from CH 0.761 (0.770)3 2454928251 Rho-kinase 2
miR-141-3p miR-141-3p 173 HC 233 LC 261 HCC serum China NA up 0.887(training sets) 0.879(validation sets) 2523823886 NA
miR-143 miR-143-3p 127 HC 118 CH 95 HCC serum China differentiation up CH from HC 0.617 HCC from CH 0.795 2499365662 FNDC3B
miR-146a miR-146a-5p 42 HC 125 HCV-CLD 112 HCV-HCC blood Egypt 1.suppresses HCC invasion2.exerted negative effects on anti-tumor immune response up HCV-HCC from HC 0.787 HCV-HCC from HCV-CLD 0.85 26352740142 VEGF
miR-146a miR-146a-5p 313 HC 294 HCC serum China onco-miR NA NA 24816919107 NA
miR-150 miR-150-5p 120 HC 110 CHB 120 HCC serum China 1.tumor suppressor2.metastasis3.BCLC stage4.advanced TNM stages down 0.931 2621597060 NA
miR-150 miR-150-5p 15 HC 15 ICC plasma China tumor suppressor up 0.764 2548232097 NA
miR-15b miR-15b-5p 96 HCC serum China preventing replicative stress in response to mitogenicsignalling up 0.984 2240334434 NA
miR-16 miR-16-5p 107 CLD 105 HCC serum America 1.tumor suppressor2.apoptosis down NA 2127858341 BCL2, MCL1, CCND1, WNT3A
miR-17-5p miR-17-5p 28 HC 26 CHC 30 HCV-positive cirrhosis 8 HCC blood Turkey NA up NA 2539177181 NA
miR-181a miR-181a-5p 50 HC 31 CLD 27 HCC blood China tumor suppressor down HCC from HC 0.82 HCC from CLD 0.71 CLD from HC 0.64 2576117910 NA
miR-182 miR-182-5p 40 HC 95 BLD 103 HCC serum China 1.metastasis up 0.911 2590346661 TP53INP1
miR-18a miR-18a-5p 60 HC 30 HBV-CH 101 HBV-HCC serum China 1.liver injury2.onco-miR up NA 2286539994 NA
miR-192 miR-192-5p 167 HC 169 CHB 141 LC 457 HCC blood China NA up 0.864(training set) 0.888(validation set) 2210582259 NA
miR-192 miR-192-5p 42 HC 125 HCV-CLD 112 HCV-HCC blood Egypt liver injury up HCV-HCC from HC 0.878 HCV-HCC from HCV-CLD 0.69 2635274042 NA
miR-192-5p miR-192-5p 173 HC 233 LC 261 HCC serum China NA down 0.887(training sets) 0.879(validation sets) 2523823886 NA
miR-195 miR-195-5p 42 HC 125 HCV-CLD 112 HCV-HCC blood Egypt 1.onco-miR2.evading apoptosis3.tissue invasion and metastasis down HCV-HCC from HC 0.653 HCV-HCC from HCV-CLD 0.78 2635274042 FGF7 and GHR
miR-196a miR-196a-5p 313 HC 294 HCC serum China onco-miR NA NA 24816919107 NA
miR-199a-5p miR-199a-5p 173 HC 233 LC 261 HCC serum China tumor suppressor down 0.887(training sets) 0.879(validation sets) 2523823886 NA
miR-19a miR-19a-3p 42 HC 125 HCV-CLD 112 HCV-HCC blood Egypt 1.PV thrombosis2.invasion, satellite nodules and progression3.recurrence down HCV-HCC from HC 0.714 HCV-HCC from HCV-CLD 0.86 2635274042 NA
miR-206 miR-206 173 HC 233 LC 261 HCC serum China NA up 0.887(training sets) 0.879(validation sets) 2523823886 NA
miR-21 miR-21-5p 89 HC 48 CHB 101 HCC blood China liver injury up HCC from HC 0.87 CHB from HC 0.91 2122961092 NA
miR-21 miR-21-5p 167 HC 169 CHB 141 LC 457 HCC blood China tumor suppressor up 0.864(training set) 0.888(validation set) 2210582259 PTEN
miR-21 miR-21-5p 50 HC 30 LC 136 HCC serum Japan excessive secretion by primary cancer cells up CH from HC 0.773 HCC from HC 0.953 21749846110 NA
miR-21 miR-21-5p 30 HC 97 HCC blood China 1.promote cell proliferation2.tumor invasion up NA 2597303255 PDCD4 and PTEN
miR-21 miR-21-5p 74 ICC serum China intrahepatic cholangiocarcinoma proliferation and growth up NA 2580322956 PTPN14 and PTEN
miR-215 miR-215 127 HC 118 CH 95 HCC serum China metastasis up CH from HC 0.802 HCC from HC 0.816 2499365662 NA
miR-221 miR-221-3p 10 HC 30 HCV 30 HCV-LC 30 HCV-HCC serum Egypt anti-apoptotic down 0.655 2542932043 NA
miR-223 miR-223-3p 89 HC 48 CHB 101 HCC blood China liver injury up HCC from HC 0.86 CHB from HC 0.88 2122961092 NA
miR-223-3p miR-223-3p 28 HC 26 CHC 30 HCV-LC 8 HCC blood Turkey NA down NA 2539177181 NA
miR-223-3p miR-223-3p 28 HC 24 CHB 22 HBV-LC 20 HBV-HCC plasma Turkey NA down NA 2459545033 NA
miR-24-3p miR-24-3p 46 HC 31 CLD 84 HCC serum China 1.vascular invasion up HCC from CLD 0.636 (0.834)5 2512931263 NA
miR-26a miR-26a-5p 167 HC 169 CHB 141 LC 457 HCC blood China lower miR-26a expression experienced worse survival but better response to interferon therapy down 0.864(training set) 0.888(validation set) 2210582259 NA
miR-26a-5p miR-26a-5p 173 HC 233 LC 261 HCC serum China NA down 0.887(training sets) 0.879(validation sets) 2523823886 NA
miR-27a miR-27a-3p 167 HC 169 CHB 141 LC 457 HCC blood China onco-miR down 0.864(training set) 0.888(validation set) 2210582259 NA
miR-296 miR-296-5p 42 HC 125 HCV-CLD 112 HCV-HCC blood Egypt 1.metastasis2.tumor angiogenesis up HCV-HCC from HC 0.792 HCV-HCC from HCV-CLD 0.645 2635274042 NA
miR-302c-3p miR-302c-3p 28 HC 26 CHC 30 HCV-positive cirrhosis 8 HCC blood Turkey NA up NA 2539177181 NA
miR-30c-5p miR-30c-5p 28 HC 26 CHC 30 HCV-positive cirrhosis 8 HCC blood Turkey 1.HCV-positive cirrhosis2.interferon-beta therapy up NA 2539177181 NA
miR-331-3p miR-331-3p 40 HC 95 BLD 103 HCC serum China 1.proliferation2.metastasis up 0.89 2590346661 PH
miR-34a miR-34a-5p 42 HC 125 HCV-CLD 112 HCV-HCC blood Egypt child stage and BCLC score up HCV-HCC from HC 0.98 HCV-HCC from HCV-CLD 0.67 2635274042 NA
miR-375 miR-375 156 HC 78 HCC serum China tumor suppressor down 0.637 2561859958 NA
miR-375 miR-375 210 HC 135 HBV 48 HCV 120 HCC serum China NA up 0.96 21098710140 NA
miR-433-3p miR-433-3p 173 HC 233 LC 261 HCC serum China NA up 0.887(training sets) 0.879(validation sets) 2523823886 NA
miR-483-5p miR-483-5p 69 HC 69 HCC serum America anti-apoptotic oncogene up HCC from HC 0.827 2412741340 NA
miR-885-5p miR-885-5p 24 HC 23 CHB 26 LC 17 GC 9 ICC 6 FNH 46 HCC serum China cholesterol reverse transport up 0.904 20815808111 NA
let-7b let-7b-5p 15 HC 30 DN 120 HCC serum China tumor suppressor up 0.645 2626455344 NA
miR-203 miR-203a-3p 10 HC 30 non-cirrhotic HCV 25 HCV-related cirrhosis 23 HCV-HCC serum Egypt 1.tumor-suppressive2.angiogenesis down HCC from non-HCC 0.76 27268654141 NA
miR-885-5p miR-885-5p 192 HCC 96 LC 96 CHC 95 HC serum Egypt 1.onco-miR2.liver injury up HCC from HC 0.63 HCC from LC 0.775 27271989120 ISRE
miR-122 miR-122-5p 193 HCC 96 LC 96 CHC 95 HC serum Egypt 1.tumor suppressor2.regulate lipid and cholesterol metabolism up HCC from HC 0.617 HCC from LC 0.617 27271989120 ADAM17
miR-29b miR-29b-3p 194 HCC 96 LC 96 CHC 95 HC serum Egypt tumor suppressor down HCC from HC 0.766 27271989120 NA
miR-221 miR-221-3p 195 HCC 96 LC 96 CHC 95 HC serum Egypt 1.onco-miR2.apoptosis up HCC from LC 0.702 27271989120 CDKN1B/p27CDKN1C/p57
miR-181b miR-181b-5p 196 HCC 96 LC 96 CHC 95 HC serum Egypt 1.onco-miR2.migration and invasion up HCC from LC 0.679 27271989120 TIMP3
miR-22 miR-22-3p 197 HCC 96 LC 96 CHC 95 HC serum Egypt tumor suppressor down HCC from CHC 0.586 27271989120 HDAC4
miR-199a-3p miR-199a-3p 198 HCC 96 LC 96 CHC 95 HC serum Egypt tumor suppressor down HCC from CHC 0.7 27271989120 mTOR
miR-125b miR-125b-5p 56 HC 63 CHB 59 HBV-LC 64 HBV-HCC plasma China 1.tumor suppressor2.migration and invasion3.cellular proliferation and cell cycle progression down HBV-HCC from HC 0.891 27152955121 LIN28B
miR-96 miR-96-5p 104 HCC 100 CHB 90 LC 120 HC serum China 1.onco-miR2.migration and invasion up HCC from CHB 0.803 26770453142 NA
miR-126 miR-126-3p 28 HC 20 LC 59 HCC plasma India NA up low AFP HCC from non-HCC 0.765 low AFP HCC from LC 0.643 26756996143 APAF1, APC2, VEGFA, IRS1, CDKN2A
miR-224 miR-224-5p 26 HCC 22 LC 23 CHB 22 HC serum China 1.migration and invasion2.suppress apoptosis up 0.88 26724963144 NA
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Abbreviations and note: HC: healthy controls; CHB: patients with chronic type B hepatitis; CLD: chronic liver disease; HCV-CLD: non-malignant HCV-associated CLD patients; DN: chronic hepatitis B patients with pathologically proven DN; ICC: intrahepatic cholangiocellular carcinoma; LC: liver cirrhosis; HCV: hepatitis C virus HBV: hepatitis B virus; NA: not available; 1: upregulated in the HBV-LC group; 2: combined classifier (AFP and miRNA-122a); 3; combination of plasma miRNA-139 with serum AFP; 4: combined miR-15b and miR-130b; 5: Combined serum alpha-fetoprotein (AFP) and miR-24-3p.

Table 3. Prognostic biomarkers in tissues for hepatocellular carcinoma.

Reported ID Offical ID Sample Ethnicity Features Expression PMID Validated Targets
miR-101 miR-101-3p 20 HC 25 HBV-HCC China 1.HBsAg, HBV DNA level and tumor size up 24260081112 NA
miR-101 miR-101-3p 130 HCC China tumor suppressor down 2317871399 SOX9
miR-101 miR-101-3p 30 HC 79 CHB 61 HBV-LC 67 HBV-HCC China 1.inhibit HCC cell proliferation2.tumor suppressor up 2497195338 NA
miR-106b miR-106b-5p 104 HCC China 1.tumor size2. vascular invasion3. proliferation4. anchorage-independent growth of HCC cells5.metastasis up 2546644964 NA
miR-122 miR-122-5p 60 HCC China 1.tumor suppressor2.maintenance of normal physiological metabolism down 26252254100 PKM2
miR-125b miR-125b-5p 49 HCC China tumor suppressor down 24811246101 Eif5a2
miR-1269 miR-1269a 95 HCC China 1.tumor nodes2.portal vein tumor embolus3.vaso-invasion4.tumor capsular infiltration5.expression of MTDH6.onco-miR7.carcinogenesis, metastasis and invasion of HCC up 2578504872 AGAP1, AGK, BPTF, C16orf74, DACT1, LIX1L, RBMS3, ZNF706 and BMPER
miR-128-3p miR-128-3p 72 HCC China 1.suppress proliferation2.suppress metastasis down 2596236073 PIK3R1 PI3K/AKT
miR-130a miR-130a-3p 102 HCC China 1.gender, HBsAgstatus, tumor size, and TNM stage2.tumor suppressor down 25218269102 NA
miR-137 miR-137 136 HCC China 1.vein invasion2.distant metastasis3.inhibition promotes HCC cell growth down 2497080835 AKT2
miR-146a miR-146a-5p 85 HCC China tumor suppressor down 24172202103 ROCK1
miR-155 miR-155-5p 100 HCC China 1.metastasis2.inhibits apoptosis up 2386366945 NA
miR-155 miR-155-5p 216 HCC China onco-miR up 22629365108 NA
miR-17-5p miR-17-5p 120 HCC China regulating proliferation and migration up 2258301165 p38 MAPK-HSP27
miR-182 miR-182-5p 81 HCC China 1.onco-miR2.motility and invasiveness up 2581340366 FOXO1
miR-182 miR-182-5p 86 HCC China intrahepatic metastasis up 2268171767 MTSS1
miR-183 miR-183-5p 81 HCC China 1.onco-miR2.motility and invasiveness up 2581340366 FOXO1
miR-185 miR-185-5p 41 NTR 54 TR China 1.suppress the tumor cell growth2.suppress invasive down 2364805436 NA
miR-188-5p miR-188-5p 250 HCC China 1.suppress tumor cell proliferation2.suppress metastasis down 2599816374 FGF5
miR-18b miR-18b-5p 110 HCC Japan 1.proliferation2.loss of cell adhesion ability up 2349690152 TNRC6B
miR-199a-5p miR-199a-5p 120 HCC China 1.Negatively Associated With Malignancies2.Regulates Glycolysis3.Lactate Production down 26054020145 Hexokinase 2
miR-206 miR-206 147 HCC China 1.suppresses cell proliferation2.promotes apoptosis. down 2551308646 NA
miR-21 miR-21-5p 50 HC 30 CH 136 HCC Japan NA down 21749846110 NA
miR-21 miR-21-5p 112 HCC China 1.tumor differentiation2.TNM stage3.vein invasion up 2626162068 NA
miR-21 miR-21-5p 119 HCC China 1.tumorinvasion, metastasis and prognosis2.promote cell proliferation and invasion3.inhibits cell apoptosis up 2515037347 NA
miR-21 miR-21-5p 74 ICC China intrahepatic cholangiocarcinoma proliferation and growth up 2580322956 PTPN14 and PTEN
miR-212 miR-212-3p 86 HCC China 1.inhibited cell proliferation2.induced apoptosis down 2634732148 FOXA1
miR-214 miR-214-3p 65 HCC China tumor suppressor down 23962428104 FGFR-1
miR-25 miR-25-3p 96 HCC Iran 1.TNM stage2.suppress proliferation3.suppress migration up 2620929669 NA
miR-26a miR-26a-5p 120 HCC China 1.Cell Cycle2.angiogenesis up 2425942684 CDK6, cyclin D1
miR-26a miR-26a-5p 130 HCC China 1.suppress the tumor cell growth2.suppress invasive down 2338984837 interleukin-6-Stat3
miR-331-3p miR-331-3p 457 HCC China 1.Promotes Proliferation2.Metastasis up 2482530270 Leucine-Rich Repeat Protein Phosphatase
miR-34a miR-34a-5p 120 HCC China 1.tumor size2.higher serum AFP level down 25596083113 NA
miR-424 miR-424-5p 96 HCC China suppressed proliferation down 2631554187 pRb-E2F pathway, Akt3 and E2F3
miR-503 miR-503-5p 20 HCC China suppress metastasis down 2616326075 PRMT1
miR-744 miR-744-5p 96 HCC China 1.tumour suppressor2.tumor malignancy3.tumor cell proliferation4.invasion and migration5.HCC recurrence6.poor prognosis down 2554352176 NA
miR-9 miR-9-5p 200 HCC China 1.tumour suppressor2.tumor stage3.venous infiltration up 2555220471 NA
miR-96 miR-96-5p 81 HCC China 1.onco-miR2.motility and invasiveness up 2581340366 FOXO1
miR-125a miR-125a-5p 80 HCC China 1.Proliferation 2.Metastasis down 22768249146 MMP11 and VEGF
miR-99a miR-99a-5p 142 HCC China tumor suppressor down 21878637147 NA
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Abbreviations and note: HC: healthy controls; CHB: patients with chronic type B hepatitis; CLD: chronic liver disease; HCV-CLD: non-malignant HCV-associated CLD patients; DN: chronic hepatitis B patients with pathologically proven DN; ICC: intrahepatic cholangiocellular carcinoma; LC: liver cirrhosis; HCV: hepatitis C virus; HBV: hepatitis B virus; CH: chronic hepatitis; TR: treated recurrence group; NTR: none treated recurrence group; NA: not available.

Table 4. Prognostic biomarkers in blood for hepatocellular carcinoma.

Reported ID Offical ID Sample Source Ethnicity Features Expression PMID Validated Targets
miR-1 miR-1-3p 54 LC 195 HCC serum Germany 1.differentiation2.tumor suppressor up 2381024791 NA
miR-101 miR-101-3p 20 HC 25 HBV-HCC serum China 1.HBsAg, HBV DNA level and tumor size up 24260081112 NA
miR-101 miR-101-3p 30 HC 79 CHB 61 HBV-LC 67 HBV-HCC serum China 1.inhibit HCC cell proliferation2.tumor suppressor up 2497195338 NA
miR-122 miR-122-5p 122 HCC blood China 1.tumor suppressor2.proliferation3.differentiation4.regulation of cholesterol and lipid metabolisms5.stability and propagation of hepatitis C virus and hepatitis B infection up 2563644877 NA
miR-122 miR-122-5p 120 HCC plasma South Korea 1.hepatic necroinflammatory activity2.cell death3.tumor suppressor up 2612987849 NA
miR-122 miR-122-5p 54 LC 195 HCC serum Germany 1.liver transaminases2.MELD score down 2381024791 NA
miR-128-2 miR-128-2 20 HCC 20 HCC(PVTT) serum China onco-miR up 25642945109 NA
miR-150 miR-150-5p 120 HC 110 CHB 120 HCC serum China 1.tumor suppressor2. metastasis3.BCLC stage4.advanced TNM stages down 2621597060 NA
miR-16 miR-16-5p 60 HC 90 HCC serum China 1.tumor size2.liver dysfunction and coagulation defect down 24697119114 NA
miR-16 miR-16-5p 40 HCV 40 HCC serum Egypt 1.apoptosis2.bilirubin down 2613372550 NA
miR-17-5p miR-17-5p 96 HCC blood China 1.metastasis2.TNM stage up 2310808678 NA
miR-182 miR-182-5p 40 HC 95 BLD 103 HCC serum China metastasis up 2590346661 TP53INP1
miR-199a miR-199a-5p 40 HCV 40 HCC serum Egypt tumor size down 2613372550 NA
miR-203a miR-203a-3p 90 HCV 152 HCV-HCC serum China tumor suppressor down 26210453105 Snal2
miR-21 miR-21-5p 50 HC 30 CH 136 HCC serum Japan NA down 21749846110 NA
miR-21 miR-21-5p 74 ICC serum China intrahepatic cholangiocarcinoma proliferation and growth up 2580322956 PTPN14 and PTEN
miR-21 miR-21-5p 60 HC 90 HCC serum China liver injury down 24697119114 NA
miR-24-3p miR-24-3p 46 HC 31 CLD 84 HCC serum China vascular invasion up 2512931263 NA
miR-30c miR-30c-5p 90 HCV 152 HCV-HCC serum China tumor suppressor down 26210453105 EMT
miR-331-3p miR-331-3p 40 HC 95 BLD 103 HCC serum China 1.proliferation2.metastasis up 2590346661 PH
miR-335 miR-335-5p 125 HC 125 HCV/HBV 125 HCC serum China response to TACE and clinical outcome down 26305026148 NA
let-7f let-7f-5p 60 HC 90 HCC serum China 1.tumor size2.early recurrence down 24697119114 NA
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Abbreviations and note: PVTT: portal vein tumor thrombosis; LC: liver cirrhosis; HBV: Hepatitis B Virus; HCV: Hepatitis C Virus; HC: healthy controls; CHB: patients with chronic type B hepatitis; BLD: benign liver diseases; ICC: intrahepatic cholangiocellular carcinoma; CH: chronic hepatitis; NA: not available.

Table 5. Therapeutic biomarkers for hepatocellular carcinoma.

Reported ID Offical ID Sample Source Ethnicity Features Expression PMID Validated Targets
miR-335 miR-335-5p 62 HCC tissue China inhibit the proliferation and migration invasion down 25804796149 ROCK1
miR-192 miR-192-5p 59 HC 59 HCC tissue South Korea increase tumor cell migration and invasion down 25065598150 NA
miR-224 miR-224-5p 9 HC 10 HCC tissue China 1.cell proliferation s2. migration3.invasion4.anti-apoptosi up 2478942039 CD40
miR-214 miR-214-3p 9 HC 10 HCC tissue China tumor suppressor down 2478942039 EZH2, CTNNB1 and CDH1
miR-148a miR-148a-3p 19 HCC tissue China onco-miR up 22496917106 NA
miR-206 miR-206 147 HCC tissue China 1. suppress cell proliferation2.promote apoptosis. down 2551308646 NA
miR-331-3p miR-331-3p 457 HCC tissue China 1. promote proliferation2. metastasis up 2482530270 Leucine-Rich Repeat Protein Phosphatase
miR-26a miR-26a-5p 120 HCC tissue China 1. cell Cycle2. angiogenesis up 2425942684 CDK6, cyclin D1
miR-26a miR-26a-5p 130 HCC tissue China 1. suppress the tumor cell growth2. suppress invasive down 2338984837 interleukin-6-Stat3
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Abbreviations and note: HC: healthy controls; NA: not available.

Functional characterization of HCC biomarker miRNAs based on cancer hallmarks

The functional characterization of HCC biomarker miRNAs are summarized from the primary references and classified into 12 categories as shown in Fig. 1. It indicates that the biomarker miRNAs are associated with all aspects of hallmarks of cancers and all the hallmarks lead to the cancer. Therefore, the personalized biomarkers are needed to precision diagnosis, prognosis and treatment of the complex HCC. The functions of the biomarker miRNAs are summarized as follows.

Figure 1. The correlation among clinicopathological features and reported HCC miRNA biomarkers.

Figure 1

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Here, miRNAs in red and green, respectively, represent the up and down-regulated expression in tissues and blood. The miRNA in black means that its expression can be inconsistently up- or down- regulated in different reports. Sub-figure (a,b) represent clinicopathological features of diagnostic miRNA biomarkers in tissues and blood, respectively. Sub-figure (c,d) represent clinicopathological features of prognostic miRNA biomarkers in tissues and blood, respectively.

Insensitivity to Antigrowth Signals

Although it is unclear for the units and interconnections between the different kinds of antigrowth and differentiation-including signals and the core cell cycle machinery, an antigrowth signaling must be exist to circumvent developing HCC31. MiR-125b-5p and miR-15b-5p were the circulating diagnostic miRNA biomarkers associated with insensitivity to antigrowth signals and all of them were up-regulated and highly expressed in early-stage HCC cases33. Liu et al. combined miR-15b-5p and miR-130b-3p as a classifier for HCC detection, yielding a receiver operating characteristic curve area of 0.98 in their validation study, the same was found in tissue samples, miR-15-5p was also reported highly expressed34. As for prognostic biomarkers, three miRNAs related to insensitivity to antigrowth signals in the tissue samples were identified, including miR-137, miR-185-5p and miR-26a-5p. All of them were down-regulated in poor prognostic group which had a lower survival rate and shorter time to recurrence35,36,37.

Resisting Cell Death

Cancer cells evolve various ways to circumvent or restrict apoptosis. The diversity of apoptosis-avoiding machinery and program reflects the multiplicity of apoptosis-including signals that tumor cell populations experienced while their evolution to the malignant state32. In tissues, miR-101-3p, miR-224-5p and miR-483-5p were associated with resisting cell death. Among them, miR-101-3p was down-regulated whereas the remaining two were reported to be up-regulated38,39,40. Resisting cell death was significantly associated with lower expression of miR-101-3p, miR-16-5p, miR-195-5p, miR-203a-3p and miR-221-3p in blood samples38,41,42,43. Increased miR-221-3p, miR-224-5p, miR-483-5p and miR-122-5p expression were also detected in blood of HCC patients40,44. These above diagnostic biomarkers as classifiers for HCC detection, yielding a receiver operating characteristic curve area of 0.635 to 0.884 (see Tables 1 and 2). On the other hand, miR-155-5p, miR-206, miR-21-5p and miR-212-3p could be recognized as biomarkers for HCC prognosis in tissues. The expression levels of miR-155-5p and miR-21-5p were up-regulated whereas others were down-regulated45,46,47,48. Circulating miR-122-5p and miR-16-5p could be used as putative biomarkers for HCC. Among them, miR-122-5p and miR-16-5p were shown to be up and down-regulated, respectively49,50.

Avoiding Immune Destruction

According to the long-standing theory of immune surveillance proposes, most of solid tumors such as HCC appeared to have somehow controlled to avoid detection by the different kinds of arms of the immune system or could limit the extent of immunological killing, thus they could evade eradication by immune system32. Motawi and his colleagues overviewed that serum miR-146p-5p was up-regulated in HCC and showed the clinical value for HCV-related HCC diagnosis. This circulatory biomarker miRNA was reported to exerted negative effects on anti-tumor immune response42.

Tissue Invasion and Metastasis

Invasion and metastasis, complex and multi-step processes, are elementary factors that affects HCC patients survival rate and their genetic and biochemical mechanisms remain poorly understood31. In tissues, high expression of miR-18b-5p, miR-200a-3p, miR-200b-3p, miR-21-5p, miR-224-5p and miR-29-5p were most frequently to be detected in HCC, and miR-139-5p was down-regulated. Therefore, they were valuable for diagnosis of HCC39,51,52,53,54,55,56,57. Several circulating miRNA biomarkers also displayed signally correlation with tissue invasion and metastasis, including highly expressed miR-146a-5p, miR-181b-5p, miR-182-5p, miR-21-5p, miR-215, miR-24-3p, miR-224-5p, miR-296-5p, miR-331-3p and miR-96-5p and low expressed miR-125b-5p, miR-199a-3p, miR-122-5p, miR-139-5p, miR-150-5p, miR-195-5p and miR-19a-3p. The above diagnostic biomarkers could be used as classifiers for HCC detection, yielding a receiver operating characteristic curve area of 0.645 to 0.94342,51,55,56,58,59,60,61,62,63.

In tissues, with regard to up-regulated microRNAs in HCC tissues, highly expression of miR-106b-5p, miR-155-5p, miR-17-5p, miR-182-5p, miR-183-5p, miR-18b-5p, miR-21-5p, miR-25-3p, miR-331-3p, miR-9-5p and miR-96-5p were significantly correlated with invasion and metastasis45,47,52,56,64,65,66,67,68,69,70,71. The expression level of miR-1269a in HCC patients without portal vein tumor embolus was reduced72. In addition, the low expression of miR-125a-5p, miR-128-3p, miR-137, miR-185-5p, miR-188-5p, miR-26a-5p, miR-503-5p and miR-744-5p were detected in HCC tissues compared with their non-tumor livers and were involved in the multi-step processes35,36,37,73,74,75,76. There were six circulating prognostic biomarker miRNAs reported to be associated with tissue invasion and metastasis, including miR-122-5p, miR-17-5p, miR-182-5p, miR-21-5p, miR-24-3p and miR-331-3p, all of them were up-regulated in the group with low survival rate56,61,63,77,78. Meanwhile, the serum miR-150-5p was shown highly expressed in HCC patients after surgical operation and then low expressed after tumor relapsed60.

Tumor Promoted Inflammation

Inflammation has been proved to be existed at the earliest stage of tumor processes and to be capable of fostering the progression of incipient neoplasia into advanced tumors79. Besides chemicals, particularly reactive oxygen species were positively mutagenic for adjacent cancer cells, accelerating their genetic evolution towards the high malignant carcinoma80. In blood, the increased expression of miR-30c-5p could be used as a new classifier for HCV-positive HCC in early-stage81. In addition, hepatic necroinflammatory activity was associated with the high expression of miR-122-5p in plasma. The over expression of circulating miR-122-5p was a prognostic biomarker predicting the poor survival rate of patients underwent radio frequency ablation49.

Sustained Angiogenesis

Both oxygen and nutrients transported by vasculature are essential for cell survival and function. All cells in tissues obligate to live within 100 μm of a capillary blood vessel. The evidence showed that cells with aberrant proliferative lesions tended to lack angiogenic ability at first, and led to hinder the capability for expansion31. The development of angiogenic ability is vital for incipient neoplasia growth82,83. The over expression of circulating miR-296-5p was significantly associated with tumor angiogenesis42. In tissues, high expression of miR-26a-5p could suppress tumor angiogenesis in HCC by targeting HGF-cMet signaling, and it was a novel prognostic biomarker for HCC84.

Limitless Replicative Potential

There are three factors can lead to an uncoupling of the growth of a cell process from signals in their microenvironment, including insensitivity to antigrowth signals, resistance to apoptosis, and growth signal autonomy. Senescence, just like apoptosis, is as a protective system that could be activated by opposite growth signals or shortened telomeres that drives abnormal cells irreversibly into a G0-like state, and it could prevent further proliferation31. High expression of miR-182-5p, miR-18b-5p, miR-21-5p and miR-224-5p, together with the down-regulated expression of miR-101-3p and miR-139-5p not only played important roles in the regulation of cell proliferation and limitless replicative potential, but also were diagnostic signals for HCC38,39,51,52,54,55,56,85. High expression of miR-106b-5p, miR-21-5p, miR-331-3p and low expression of miR-101-3p, miR-125b-5p, miR-139-5p had great potential to be noninvasive and accurate circulating biomarkers for HCC preliminary screening10,38,51,55,56,61. Moreover, some opposite results about the expression levels of miR-122-5p were discussed44,86. In tissues, high expression of eight miRNAs (i.e. miR-101-3p, miR-106-5p, miR-17-5p, miR-18b-5p, miR-21-5p, miR-25-3p and miR-331-3p) and low expression of seven miRNAs (i.e. miR-125a-5p, miR-128-3p, miR-188-5p, miR-206, miR-212-3p, miR-424-5p and miR-744-5p) were outstandingly correlated with limitless replicative potential and could provide positive prognostic values for HCC38,46,47,48,52,56,64,65,69,70,73,74,76,87. Four prognostic circulating miRNAs associated with proliferation and limitless replicative potential, including miR-101-3p, miR-122-5p, miR-21-5p and miR-331-3p, were reported up-regulated in HCC patients38,56,61,77.

Genome Instability and Mutation

Multi-step cancer progression could be described as a series of genic clonal expansions. Acquiring the chance of an enabling mutant gene triggered these clonal expansions88,89,90. The widespread destabilization of genome is inherent to the vast majority of HCC cells32. The high expression of miR-122-5p and low expression of miR-143-3p in blood were prominently correlated with differentiation and genome instability. They could be used as noninvasive circulating biomarkers for diagnosis of HCC59,62,86. Up-regulated expression of miR-21-5p has been observed to be associated with genome instability and mutation, and it was a novel prognostic biomarker for HCC68. Patients with high serum concentrations of miR-1-3p and miR-122-5p showed a long overall survival time and these miRNAs could be used to assess the HCC staging scores77,91.

Liver injury

Biochemical molecules including miRNAs can be released into the circulation system due to the hypoxia and damage of liver cells. Accumulating reports indicated that serum miR-10b-5p, miR-122-5p, miR-18-5p, miR-192-5p, miR-21-5p, miR-223-3p and miR-885-5p were went up in patients with chronic hepatitis or HCC and they could serve as diagnostic biomarkers for liver injury but not specific for HCC10,42,92,93,94.

Tumor suppressor/onco-miR

Genetic suppressor and carcinogenicity interpreted the function of miRNAs from another perspective. In tissues, high expression of miR-150-5p and miR-29a-5p and low expression of miR-101-3p, miR-126-3p, miR-127-3p, miR-139-5p and miR-214-3p played tumor-suppressor roles and could be used as diagnostic biomarkers for HCC38,39,51,57,95,96,97. The circulating miR-101-3p, miR-122-5p, miR-125b-5p, miR-139-5p, miR-150-5p, miR-16-5p, miR-181a-5p, miR-199a-3p, miR-199a-5p, miR-203a-3p, miR-21-5p, miR-22-3p, miR-29b-3p, miR-375, let-7b-5p correlated with tumor suppressor and could be potential biomarkers to differentiate HCC from healthy controls10,38,41,44,51,58,59,60,86,97,98. On the other hand, miR-101-3p, miR-122-5p, miR-125b-5p, miR-130a-3p, miR-146a-5p, miR-214-3p and miR-99a-5p were considered as tumor suppressors in HCC and served as prognostic indicators for HCC38,99,100,101,102,103,104. Serum miR-1-3p, miR-101-3p, miR-122-5p, miR-150-5p, miR-203a-3p and miR-30c-5p were associated with suppressing tumorigenicity and new independent parameters of overall survival in HCC38,49,60,77,91,105.

The high expression of miR-130b-3p, miR-148a-3p, miR-181b-5p, miR-221-3p, miR-885-5p and miR-96-5p were functional in tumorigenicity and could be served as early diagnostic biomarkers for different tumor type34,106. Meanwhile, miR-10b-5p, miR-130b-3p, miR-146a-5p, miR-18-5p, miR-195-5p, miR-196a-5p and miR-27a-3p were related to carcinogenicity and played vital roles in HCC detection10,34,42,59,94,107. There were six miRNAs associated with oncogenicity and could be potential biomarkers for the overall survival of patients with HCC, including miR-1269a, miR-155-5p, miR-182-5p, miR-183-5p, miR-96-5p and miR-128-266,72,108,109.

Other clinicopathological features

Besides the above ten clinicopathological features and the hallmarks of cancer, biomarker miRNAs were also correlated with other clinicopathological features, such as secretion by primary cancer cells, child stage, cholesterol reverse transport, tumor size and recurrence, etc. Tomimaru et al. found that miR-21-5p was excessively secreted by primary cancer cells and could be a potential diagnostic biomarker for HCC110. Motawi and his colleagues identified that serum miR-34a-5p was correlated with child stage and BCLC score and could be used as an early biomarkers for HCC in high-risk group42. The miR-885-5p and miR-122-5p in serum was reported related to cholesterol reverse transport and assessment of liver pathologies111. In addition, miR-101-3p, miR-106b-5p, miR-130a-3p, miR-16-5p, miR-199a-5p, let-7f-5p and miR-34a-5p were found to have a significant correlation with tumor size in the tissue and serum of HCC patients50,64,102,112,113,114. The present literature also provided evidence that miR-130a-3p, miR-21-5p, miR-25-3p, miR-17-5p were independent prognostic factors and were associated with the TNM classification which is a universally accepted cancer staging system based on extension and size of the primary tumor (T), the adjacent lymph node (N), and the distant metastasis (M)68,69,78,102. The down-regulated expression of miR-774-5p and let-7f-5p can be considered as noninvasive biomarkers for predicting of the recurrence of HCC76,114.

Comparison of HCC biomarker miRNAs based on etiological factors and ethnic groups

Recently, accumulating evidence indicated that the occurrence and development of HCC are closely associated with etiological factors as well as ethnic groups. The differentiation between HCC and liver cirrhosis, for instance, is one of the main problems for the early detection of HCC. Moreover, different etiological factors such as HBV (Hepatitis B Virus) and HCV (Hepatitis C Virus) can also contribute to the HCC carcinogenesis. On the other hand, the incidence and mortality of HCC often showed different patterns among different ethnic groups. Hence it is necessary to compare HCC biomarker miRNAs based on etiological factors and ethnic groups.

Biomarker miRNAs for classifying of HCC and liver cirrhosis

After manually searching for citations in PubMed, a total of 13 miRNA biomarkers for liver cirrhosis diagnosis were collected (see Table S1). We then compared them with HCC diagnostic miRNA biomarkers in order to screen key signatures for HCC early detection. As shown in Fig. 2, eight miRNAs, i.e. miR-106b-5p, miR-122-5p, miR-141-3p, miR-146a-5p, miR-181b-5p, miR-18a-5p, miR-19a-3p and miR-21-5p, were shared by cirrhosis and HCC. Interestingly, three of them (miR-106b-5p, miR-18a-5p and miR-21-5p) showed inverse expression patterns in cirrhosis and HCC groups. For example, the expression of miR-106b-5p (miR-106b) was down in cirrhosis samples115 whereas it turned out to be up-regulated in the blood of HCC patients10. In addition, miR-19a-3p (miR-19a) was reported as a useful molecular marker for monitoring the progression of liver fibrosis to cirrhosis and finally, to HCC42.

Figure 2. The Venn diagram of miRNA biomarkers for liver cirrhosis and HCC.

Figure 2

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Here circles in blue and red, respectively, represent miRNAs for cirrhosis and HCC. The miRNAs in red and green represent the up- and down-regulated expression, respectively. The miRNAs in purple means they showed inverse expression patterns in cirrhosis and HCC samples and those in black means their expressions were inconsistently up- or down- regulated according to different literature reports.

The remaining 5 and 49 miRNAs, respectively, were specific to cirrhosis and HCC, which could be served as independent factors for classifying of cirrhosis and HCC. For example, miR-29c-3p showed significant positive correlations with the level of serum cholinesterase (CHE) and albumin (ALB) in liver cirrhosis patients, suggesting that the miRNA played functional roles in the establishment of liver cirrhosis116. Han et al. found that two miRNAs, i.e. miR-224 (miR-224-5p) and miR-214 (miR-214-3p), were significantly up- and down-regulated in HCC tissue samples respectively, which provided novel biomarker signatures for HCC diagnosis and treatment39.

It can be concluded that biomarker miRNAs revealed the pathogenesis of cirrhosis and HCC at the post-transcriptional level and could help deeply understand the differentiation between cirrhosis and HCC. From the perspective of precision medicine, HCC miRNA biomarkers, especially those specific to HCC, were indicators for capturing the early diagnostic signatures at the time of HCC initiation.

Biomarker miRNAs for monitoring the development of HBV/HCV-related HCC

It has been widely acknowledged that the progression of HCC is closely affected by the infection of etiological factors, such as HBV, HCV, etc. On the other hand, miRNAs are reported to play crucial roles in HBV/HCV replication and pathogenesis117,118,119, i.e. they regulated HBV by directly binding to HBV transcripts or changing HBV gene expression at the transcriptional level118. For better investigating the influence of HBV/HCV on HCC development, miRNA biomarkers for HBV/HCV-related HCC were extracted from our collected dataset. As illustrated in Fig. 3, several miRNAs, i.e. miR-122-5p, miR-126-3p, miR-143-3p, miR-192-5p, etc., were functional in both HBV- and HCV-related HCC evolutionary progression. For example, Tan et al. found that serum miR-122-5p could be used as the diagnostic biomarker for detecting HBV-related HCC. Both the area under the receiver operating characteristic curve (AUC) and logistic regression model convinced the predictive power86. Meanwhile, the miRNA was also turned out to be effective for early detection of HCC on top HCV infection. Using the miRNA panel where miR-122-5p included, HCC patients could be classified from healthy controls and liver cirrhosis patients with high diagnostic accuracy120.

Figure 3. The Venn diagram of miRNA biomarkers for HBV/HCV-related HCC.

Figure 3

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Here miRNA biomarkers for HBV/HCV-related HCC were extracted from our collected dataset. Circles in blue and red, respectively, represent miRNAs for HBV-related HCC and HCV-related HCC. The miRNAs in orange and dark green represent the diagnostic and prognostic markers, respectively. The miRNAs in brown means they had both diagnostic and prognostic role according to different literature reports.

There is still a large number of biomarker miRNAs that could be specifically used for monitoring the development of HBV/HCV-related HCC. Chen et al. analyzed the plasma samples from 242 individuals and uncovered that the expression of miR-125b-5p (miR-125b) was significantly down-regulated in HBV-induced HCC (HBV-HCC) patients compared to healthy controls as well as HBV groups without HCC121. Moreover, the low plasma level of miR-125b-5p also reflected the higher possibility of metastasis. Therefore, the miRNA held promise as a valuable diagnostic biomarker for HBV-HCC and HBV-infected patients with high HCC risks could be early detected by dynamically monitoring the changes of this miRNA. Liu et al. demonstrated that the expression levels of miR-30c-5p (miR-30c) and miR-203a-3p (miR-203a) were crucial indicators for predicting the poor prognosis of HCV-related HCC because the core protein of HCV could down-regulate the expression of miR-30c-5p and miR-203a-3p, resulting in the activation of epithelial-mesenchymal transition in normal hepatocytes as well as HCC tumor cells. As reported before, the activation process may contribute to the carcinogenesis of HCC105.

Understanding the pathogenesis of miRNA biomarkers in HBV/HCV-related HCC provided insights to evaluate the potential effects of HBV/HCV on HCC development, which will be helpful to the early and personalized detection of HCC.

HCC miRNA biomarkers within different ethnic groups

Genomic profiling of HCC tumors showed that HCC patients in different geographic regions tended to have specific recurrent molecular aberrations122. Asians, on the whole, achieved the highest HCC incidence according to the report by Wong et al.123. In terms of prognosis, the overall survival rate was also disparate among different ethnic groups124. Here we reorganized HCC miRNA biomarkers based on the ethnicity of patients described in each citation. As illustrated in Fig. 4a, most of the reported HCC miRNA biomarkers were related to Chinese population, which indirectly indicated the high risk or high incidence of HCC in China. For further exploring the ethnic specificity of HCC miRNA biomarkers, we then partitioned miRNAs into two categories based on the patient race, i.e. Asian-related (Chinese, Japanese, South Korean, Indian and Iranian) and non-Asian-related (Egyptian, American, Turk and German) HCC miRNA biomarkers. As shown in Fig. 4b, the number of Asian-specific HCC miRNA biomarkers is far more than that of non-Asian. We noticed that some miRNAs were reported to be functional in both Asian and non-Asian group. However, the expression pattern of them was sometimes quite different when they were involved in different pathogenic processes or belonged to different ethnic groups. For example, miR-125b-5p was associated with the biological behavior of HCC and had the diagnostic value of HCC for both Turks and Chinese. As in plasma samples of Chinese patients, it was found to be down-regulated121 whereas in Turks samples, its expression level was up33. For comparison of Egyptian and Chinese, the down-regulation of miR-146a-5p was correlated with HCC carcinogenesis and deterioration in Chinese population103, but in samples of Egyptian patients, it was inverse42.

Figure 4. HCC miRNA biomarkers in different ethnic groups.

Figure 4

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Here miRNA biomarkers were classified based on the race/nation of patients described in each citation. Sub-figure (a) represents the distribution of reported HCC miRNA biomarkers in different national cohorts. Bars in blue, red and green mean the number of total, diagnostic and prognostic miRNA biomarkers, respectively. Sub-figure (b) is the Venn diagram of HCC miRNA biomarkers for Asian and non-Asian respectively. Circles in blue and red, respectively, represent Asian-related and non-Asian-related miRNA biomarkers. The miRNAs in orange and dark green represent the diagnostic and prognostic markers, respectively. The miRNAs in brown means they had both diagnostic and prognostic role according to different literature reports.

This ethnic difference may be caused by the heterogeneous pathogenesis, lifestyles and various factors including the diet, environmental exposures, etc. Moreover, the incidence of HBV/HCV infection in different countries is also inconsistent. Therefore, more in-depth researches on ethnically specific miRNA biomarkers is of clinical significance, which would provide personalized strategies for HCC diagnosis and treatment in the era of precision medicine.

Pathway enrichment analysis for targets of HCC miRNA biomarkers

We performed the pathway enrichment analysis for targets of different types of reported miRNA biomarkers using IPA program. Here the targets of miRNA biomarkers originated from seven publicly available miRNA-target databases, including four experimentally validated databases and three computationally predicted databases (see Methods). For the three categories, i.e. the diagnostic, prognostic and therapeutic biomarker miRNAs, the top 10 significantly enriched pathways (p-value < 0.01) were chosen and shown in Fig. 5. The common enriched pathways among them were Molecular Mechanisms of Cancer, Glucocorticoid Receptor Signaling, HGF Signaling, NGF Signaling, p53 Signaling etc. Most of them are well-studied cancer associated pathways. Das et al. reported that the pathway Molecular Mechanisms of Cancer was potentially associated with recurrent HCC secondary to HCV following liver transplantation125. Glucocorticoids are involved in controlling many essential biological processes that are related to energy supply and growth control. The Glucocorticoid Receptor often functions as a cofactor of transcription factor STAT5 for growth hormone induced genes and Glucocorticoid Receptor Signaling has been turned out to be important in body growth, steatosis and metabolic liver cancer development126. The experimental result in mouse model demonstrated that the metabolic dysfunction and impairment of Glucocorticoid Receptor Signaling could cause steatosis and HCC in mice127. Wu et al. revealed that the HGF signaling could be activated by over expression of gene C1GALT1 in HCC via modulation of MET O-glycosylation and dimerization, which offered new insights into O-glycosylation and HCC pathogenesis128. Jin et al. indicated that p53 Signaling pathway was significantly dysregulated in HCC and it could reflect the development and progression of HCC129. Moreover, a number of genes participated in regulating human HCC by interacting with p53 Signaling pathway. For instance, the key gene RASSF10, which is located on chromosome 11p15.2, could suppress the growth of HCC via activating p53 Signaling pathway130. EGR1 is one of the key components in p53 Signaling, the re-expression of gene BCL6B in HCC cells could increase its expression and finally contribute to the activation of p53 Signaling131.

Figure 5. Top 10 pathways significantly enriched with targets of different biomarker miRNAs from HCC tissue and blood.

Figure 5

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Sub-figure (a), (b), and (c) represent pathways enriched by targets of diagnostic, prognostic and therapeutic biomarker miRNAs, respectively. The statistical significance level (p-value) was negative 10-based log transformed.

Discussion

In this review, we made comprehensive functional survey and comparison of HCC diagnostic, prognostic and therapeutic miRNAs in blood and tissues. The number of diagnostic miRNA biomarkers in blood is approximately twice as much as those in tissues and meanwhile, the number of prognostic miRNA biomarkers in tissues is twice as much as those in blood. The reason for the statistical difference may be that many studies are inclined to investigate the noninvasive diagnostic miRNA biomarkers and researchers tend to use relatively stable hepatogenic biomarkers as prognostic indicators because miRNAs may be released into the blood selectively132,133. Most of the diagnostic, prognostic and therapeutic miRNA biomarkers are associated with one or two clinic pathological features in blood and tissues. A great number of prognostic biomarkers with high expression levels were detected in patients with shorter overall survival. Since the etiological factors as well as ethnic groups are closely associated with HCC carcinogenesis, we analyzed miRNA biomarkers by taking the HBV/HCV infection as well as regional variations into account in order to provide better clues for HCC pathogenic research. We mainly selected miRNAs which were explicitly reported as HCC markers/biomarkers in our current study. Besides, several miRNAs are still common and important during HCC development. For example, miR-142-3p was functional in HCC tumorigenesis and played a key role in regulating human RAC1 gene. The upregulation of miR-142-3p inhibited the expression level of RAC1 mRNA, suppressing the migration and invasion of HCC cells134. Interferon regulatory factor-1 (IRF-1) is a tumor-suppressor in HCC and its down-expression would help HCC tumors evade death. Yan et al. found that miR-23a was a negative regulator of IRF-1in HCC, which highlighted its importance in HCC initiation and progression135. Zhang et al. demonstrated that miR-99a could directly regulate AGO2 and control tumor growth in HCC, indicating the potential strategies for HCC treatment136.

HCC is a complex disease which is difficult for early diagnosis and treatment. The death rate of HCC remains high due to its poor prognosis. To some extent, miRNAs are effective biomarkers for HCC because of the noninvasive detection, good specificity and sensitivity. More systematic investigations and clinical experiments need to be done for better understanding the role and function of miRNA biomarkers in HCC pathogenesis137,138,139.

Additional Information

How to cite this article: Shen, S. et al. Biomarker MicroRNAs for Diagnosis, Prognosis and Treatment of Hepatocellular Carcinoma: A Functional Survey and Comparison. Sci. Rep. 6, 38311; doi: 10.1038/srep38311 (2016).

Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Material

Supplementary Table
srep38311-s1.xls (39KB, xls)

Acknowledgments

The work was supported by National Natural Science Foundation of China (NSFC) (grant Nos 91530320, 31670851, 31470821, 31400712).

Footnotes

Author Contributions S.S. and Y.L. contributed equally to the work. S.S. and Y.L. collected and analyzed the data; X.Y., L.S. and L.C. performed the computational analyses; S.S., Y.L., J.C. and B.S. wrote the manuscript; B.S. and L.Q. conceived and supervised the work jointly.

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