Identification of pathogenesis-related microRNAs in hepatocellular carcinoma by expression profiling

  • Authors:
    • Yuki Katayama
    • Moegi Maeda
    • Ken Miyaguchi
    • Shota Nemoto
    • Mahmut Yasen
    • Shinji  Tanaka
    • Hiroshi Mizushima
    • Yutaka Fukuoka
    • Shigeki Arii
    • Hiroshi Tanaka
  • View Affiliations

  • Published online on: July 18, 2012     https://doi.org/10.3892/ol.2012.810
  • Pages: 817-823
Metrics: Total Views: 0 (Spandidos Publications: | PMC Statistics: )
Total PDF Downloads: 0 (Spandidos Publications: | PMC Statistics: )


Abstract

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors of the liver. Since postoperative recurrence and intrahepatic metastases occur frequently, the postoperative 5-year survival rate is low. To investigate the molecular mechanisms of HCC progression, mRNA as well as microRNA (miRNA) expression levels have been profiled in various studies. However, no previous study has comprehensively compared the expression of miRNAs in HCC patients with various clinical features using the tumor and surrounding non-tumor tissues and normal liver samples. In this study, we profiled the expression of miRNAs in tumor and non-tumor tissues from 40 HCC patients with heterogeneous pathogenesis and 6 surrounding non-tumor tissues from patients with metastatic liver cancer. To identify miRNAs specific to each disease state, we comprehensively compared the expression of miRNAs in various combinations. The results indicate that the expression of many known as well as novel miRNAs was altered in patients with the hepatitis C virus infection compared with those with the hepatitis B virus and without any virus infection. The following miRNAs were downregulated in the tumor and non-tumor tissues, and thus could serve as novel biomarkers for chronic liver diseases: miR-18b*, miR-296-5p, miR-557, miR-581, miR-625*, miR-1228, miR-1249 and miR-2116*. Similarly, miR-129*, miR-146b-3p and miR-448 are novel candidates for HCC biomarkers regardless of virus infection.

Introduction

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors of the liver and the third most common cause of mortality from cancer in eastern Asia. More than 85% of HCC is caused by the hepatitis B virus (HBV) or C virus (HCV) infection (13). Other causes are exposure to aflatoxin B1 (4), vinyl chloride (5) and tobacco (6), as well as chronic ethanol ingestion (7). Many of these factors are known causes of chronic hepatitis (CH) and liver cirrhosis, which represent a pre-neoplastic condition of HCC. HCC is often far advanced and may have multiple lesions at the time of diagnosis. Curative resection cannot be expected in cases with extrahepatic metastases. In cases without extrahepatic metastases, curative resection could potentially be performed; however, postoperative recurrence and intrahepatic metastases occur frequently, and the postoperative 5-year survival rate is reported to be 30–40% (2).

microRNAs (miRNAs) are short (19–25 nucleotides) noncoding single-stranded RNA molecules, which are cleaved from 70–100 nucleotide miRNA precursors. miRNAs regulate gene expression either at the transcriptional or translational level, based on specific binding to the complementary sequence in the coding or noncoding region of mRNA transcripts. Recent findings, based on microarray analysis of global miRNA expression profiles in cancer tissues, have revealed that miRNA profiles discriminate malignancies of the breast (8), lung (8,9), pancreas (8,10) and liver (1117) from their counterparts.

Expression profiling of miRNA in HCC was first reported by Murakami et al (11). They comprehensively analyzed miRNA expression in HCC and non-tumor tissues and compared expression patterns in tumor and non-tumor tissues, in three differentiation levels and also between chronic hepatitis and liver cirrhosis (11). Since then, various groups have profiled miRNA expression in HCC and surrounding non-tumor tissues (1217). Laderio et al performed miRNA profiling in HCC patients with various clinical features including normal liver samples (14). However, in their comparison, not all of the HCC samples were accompanied by their surrounding non-tumor tissues. Ura et al compared miRNA expression between HBV- and HCV-related HCC (16). Although they used normal liver tissue samples, all patients analyzed had the virus infection. In this way, there is no study which comprehensively compared the expression of miRNAs in HCC patients with various clinical features using tumor and surrounding non-tumor tissues. In this study, we profiled miRNA expressions in tumor and non-tumor tissues from 40 HCC patients with heterogeneous pathogenesis. We also investigated 6 surrounding non-tumor tissues from patients with metastatic liver cancer. These were used as normal liver samples. To identify miRNAs specific to each disease state, we compared the expression of miRNAs in various combinations.

Materials and methods

Clinical specimens

Operative specimens of primary HCC and metastatic liver cancer tissues were obtained with informed consent from 40 and 6 patients, respectively, at the Department of Hepato-Biliary-Pancreatic Surgery at Tokyo Medical and Dental University Hospital between November 2005 and May 2008 (18). This research project was approved by the local ethics committee and all samples were obtained with the informed consent of the patients. The clinical findings were reviewed and analyzed from the patients’ medical records, and are shown in Table I. Of the 40 patients with HCC, 12 were infected with HBV, 12 with HCV, and 16 were not infected with HBV or HCV. In addition, 6 normal liver tissue samples obtained during surgery for metastatic liver cancer originating in the colon were used as control samples. All specimens were immediately frozen in liquid nitrogen and then stored at −80°C for RNA analysis.

Table I.

Clinical characteristics of 40 HCC patients and 6 patients with metastatic liver cancer.

Table I.

Clinical characteristics of 40 HCC patients and 6 patients with metastatic liver cancer.

PatientAgeGenderCancer typeVirus
L1870MHCCHBV
L2357MHCCHBV
L3457MHCCHBV
L6448FHCCHBV
L7670FHCCHBV
L8476FHCCHBV
L8551MHCCHBV
L8746MHCCHBV
L11668MHCCHBV
L12740MHCCHBV
L14478MHCCHBV
L15466FHCCHBV
L4266MHCCHCV
L5055FHCCHCV
L6368MHCCHCV
L7175MHCCHCV
L7253MHCCHCV
L7773MHCCHCV
L11963FHCCHCV
L12071FHCCHCV
L12443FHCCHCV
L13063MHCCHCV
L13267MHCCHCV
L15577MHCCHCV
L5758MHCC-
L5873MHCC-
L7385MHCC-
L8872MHCC-
L9065MHCC-
L9780MHCC-
L9875MHCC-
L10077MHCC-
L10269MHCC-
L10464FHCC-
L11278MHCC-
L11747MHCC-
L13176MHCC-
L13973MHCC-
L16056MHCC-
L16550FHCC-
C6256MMetastatic liver cancer
C8170MMetastatic liver cancer
C11454MMetastatic liver cancer
C12659MMetastatic liver cancer
C13265FMetastatic liver cancer
C14576MMetastatic liver cancer

[i] HCC, hepatocellular carcinoma; HBV, hepatitis B virus; HCV, hepatitis C virus.

RNA isolation

Small RNA with a miRNA-rich fraction was extracted from tissue specimens using the miRNeasy Mini kit (Qiagen, Valencia, CA, USA) according to the manufacturer’s instructions. RNAs were quantified with NanoDrop ND-1000. The integrity of the obtained RNA was assessed using Agilent Bioanalyzer RNA 6000 Nano Assay (Agilent Technologies, Palo Alto, CA, USA). All samples had an RNA integrity number (RIN) ≥4.0. The extracted RNAs were then analyzed by miRNA microarray using 3D-Gene (Toray Industries, Tokyo, Japan). The microarrays were scanned using GenePix 4000B.

Statistical analysis

The obtained microarray datasets were background corrected and used for statistical analyses using R statistical software. The Wilcoxon rank-sum test for paired data was performed to estimate the significance of miRNA gene expression differences between tumor and non-tumor tissues in 1) the 12 patients with HBV infection, 2) the 12 patients with HCV infection, 3) the 16 patients without virus infection, 4) the 24 patients with HBV or HCV infection, and 5) all 40 patients (see Fig. 1). In addition, an unpaired version of the Wilcoxon rank-sum test was used to compare the expression of miRNAs in the 6 normal liver samples with those in 6) the tumor and 7) non-tumor tissues in the 12 patients with HBV infection, 8) the tumor and 9) non-tumor tissues in the 12 patients with HCV infection, 10) the tumor and 11) non-tumor tissues in the 16 patients without virus infection, and 12) the tumor and 13) non-tumor tissues in all 40 patients (Figs. 2 and 3). MiRNAs with a fold change >1.5 and a p-value <0.05 were deemed as differentially expressed.

Many miRNAs have been reported to be involved in cancer. In addition to the previously mentioned miRNA profiling studies (1117), numerous reviews and papers (1956) were found through a literature survey on miRNA and cancer. It should be noted that we deemed a miRNA to be previously reported only when the exact name of the miRNA was found in a study. In what follows, a miRNA whose association with cancer has been previously reported is called as a previously reported miRNA. Such miRNAs may be classified into two types depending on whether they show the same or opposite tendencies to the previous reports. For certain miRNAs, it is difficult to determine whether their expressions were reportedly up- or downregulated due to inconsistent reports and lack of available information on the change direction. In the latter case, such miRNAs were described simply as cancer markers.

Results

Table II indicates the differentially expressed miRNAs between the tumor tissues in all HCC patients and the 6 normal liver samples (Combination 12). Thirty miRNAs were downregulated in the tumor tissues while 18 were upregulated. The double-underlined miRNAs have been previously reported to be involved in HCC while the miRNAs with a single underline have a reported association with other types of cancer. Most of the 18 upregulated miRNAs were known to be involved in HCC and other types of cancer. The expression of miR-15b is reported to be upregulated in HCC (23). Overexpression of miR-18a contributes to HCC cell proliferation in females through the targeting of the estrogen receptor (21). miR-21 is known to be highly overexpressed in HCC, and its inhibition in cultured HCC cells increases the expression of PTEN, a direct target of miR-21, as well as tumor cell proliferation, migration and invasion (20). The overexpression of miR-96 is reported in HBV-related HCC (14,21). miR-222 is a HCC biomarker which is irrespective of viral association (21). miR-224 is overexpressed in HCC when compared to a benign hepatocellular tumor, hepatocellular adenoma (14), and is involved in the inhibition of apoptosis in HCC cells (21). In contrast to the upregulated miRNAs, only two downregulated miRNAs are previously reported. miR-101 is involved in the inhibition of apoptosis and its downregulation contributes to the spread of HCC (21).

Table II.

Differentially expressed miRNAs among the tumor tissues in all HCC patients and the 6 normal liver samples.

Table II.

Differentially expressed miRNAs among the tumor tissues in all HCC patients and the 6 normal liver samples.

miRNAFold changeP-value
m-2116*0.048<0.001
m-545*0.0770.012
m-5810.1010.004
m-21140.1040.012
m-129*0.1270.012
m-296-5p0.161<0.001
m-12670.1680.008
m-191*0.1780.001
m-222*0.1880.025
m-12490.197<0.001
m-18b*0.208<0.001
m-92a-2*0.2330.040
m-625*0.2330.001
m-9340.2370.002
m-1225-5p0.2390.026
m-19130.2840.001
m-12380.2860.002
m-5570.2880.001
m-9400.2920.003
m-12280.2930.002
m-133b0.3150.010
let-7f-1*0.3240.002
m-1225-3p0.3640.028
m-8020.3690.030
m-1224-3p0.3770.012
m-1440.3820.006
m-1010.4270.034
m-486-5p0.5510.038
m-29c0.5730.047
m-422a0.5760.004
m-19792.710.009
m-140-3p2.830.023
let-7i3.590.017
m-151-3p3.780.005
m-130b3.800.031
m-4254.860.033
m-256.55<0.001
m-217.440.005
m-18a9.050.024
m-22110.90.004
m-45211.00.017
m-22214.20.026
m-15b18.30.016
m-22482.40.006
m-34b*1340.032
m-374b1480.039
m-961810.032
m-216a2630.039

[i] miRNA, microRNA; HCC, hepatocellular carcinoma.

Figs. 13 summarize the results from all 13 combinations described in Materials and methods. The numbers 1–13 denote the aforementioned combinations. The numbers beside the upwards and downwards-pointing arrows indicate the numbers of up- and downregulated miRNAs, respectively. Three representative miRNAs in each combination are also shown. Here, ‘representative’ means the miRNAs with the first and second lowest p-values and the previously reported miRNA with the lowest p-value among the previously reported ones (underlined in the figures in the same way as in Table II). If the previously reported miRNA was the same as either of the first two, the miRNA with the third lowest p-value is shown in the figure. In all five combinations comparing tumor and non-tumor tissues, previously reported miRNAs demonstrated the lowest p-values (Fig. 1). Notably, the three representative miRNAs for HCC with HBV infection (Combination 1) and HCC without virus infection (Combination 3) do not include any miRNA with previous association with HCC. Conversely, many novel miRNAs as well as previously reported miRNAs were detected by the unpaired Wilcoxon rank-sum test (Figs. 2 and 3).

If a miRNA is deemed to be upregulated in the tumor tissue when comparing tumor and non-tumor tissue, and also downregulated in the non-tumor tissues when comparing normal liver samples and non-tumor tissues, these results indicate that the miRNA was actually downregulated in the non-tumor tissue and thus it was detected as upregulated in the tumor when comparing the tumor and non-tumor tissues. To investigate such detailed changes, we compared lists of the differentially expressed miRNAs from the 13 combinations. Table III shows the results. For example, Normal↑ denotes that these miRNAs were downregulated in the tumor and non-tumor tissues compared with the normal liver. Similarly, Tumor↑ denotes that these miRNAs were upregulated in the tumor tissues only and their expression was not altered in the non-tumor tissues. HCV infection↑ indicates upregulation in the tumor and non-tumor tissues in patients with HCV infection while HCV↑ represents upregulation in the non-tumor tissue of the patients with HCV. V(−) denotes patients without virus infection. The expression levels of many miRNAs were altered in HCV-positive patients whereas a relatively small number of miRNAs were detected in patients with HBV and without virus infection.

Table III.

Differentially expressed miRNAs detected in various conditions.

Table III.

Differentially expressed miRNAs detected in various conditions.

Expression changeTotal detectedDetected miRNAs
Normal↑8miR-18b*, miR-296-5p, miR-557, miR-581, miR-625*, miR-1228, miR-1249, miR-2116*
Tumor↑1miR-183
Tumor↓5miR-29c, miR-129*, miR-146b-3p, miR-448, miR-486-5p
HCV infection↑125let-7a, let-7c, miR-22, miR-23a, miR-93, miR-100, miR-106b, miR-126, miR-135a, miR-210
HCV infection↓7miR-143, miR-548q, miR-670, miR-711, miR-718, miR-759, miR-762
HCC-C↑68miR-31, miR-96, miR-103-2*, miR-130b*, miR-132, miR-134, miR-138, miR-184, miR-301a, miR-372
HCC-C↑, V(-)_T↓24let-7a2, miR-21*, miR-25*, miR-33a*, miR-92b*, miR-127-3p, miR-149, miR-330-5p, miR-338-3p, miR-517*
HCV↑94miR-10a, miR-101, miR-130a, miR-146a, miR-155, miR-181b, miR-195, miR-197, miR-200a, miR-200b
HCV↑, V(-)_N↓10miR-30b*, miR-187*, miR-188-5p, miR-193b, miR-199a-5p, miR-542-5p, miR-574-5p, miR-658, miR-720, miR-1287
HCV↓7let-7b*, miR-139-3p, miR-220c, miR-616*, miR-708, miR-767-3p, miR-1911
HBV infection↑1miR-422a
HCC-B↑2miR-605, miR-1909
V(-)↑1miR-217
V(-)↓5miR-92a-2*, miR-361-3p, miR-513a-5p, miR-1234, miR-1914*
V(-)_T↑1miR-216a
V(-)_T↓10miR-133a, miR-199b-5p, miR-338-5p, miR-491-3p, miR-509-3-5p, miR-543, miR-627, miR-887, miR-921, miR-1247
V(-)_N↓6miR-664, miR-671-3p, miR-1246, miR-1268, miR-1280, miR-1978

[i] Normal↑ denotes downregulation in the tumor and non-tumor tissues when compared with normal liver. Tumor↑ denotes upregulation in the tumor tissues only and no alteration in the non-tumor tissues. HCV infection↑ denotes upregulation in the tumor and non-tumor tissues in patients with HCV infection while HCV↑ denotes upregulation in the non-tumor tissue of such patients. V(-) denotes patients without virus infection. HCC, hepatocellular carcinoma; HBV, hepatitis B virus; HCV, hepatitis C virus. The double-underlined miRNAs have been previously reported to be involved in HCC while the miRNAs with a single underline have a reported association with other types of cancer.

Discussion

In this study, miRNA expression was profiled in tumor and surrounding non-tumor tissues from 40 HCC patients with various clinical features. We first performed pairwise comparisons of miRNA expression between the tumor and non-tumor tissues. We also profiled miRNA expression in non-tumor tissue samples from 6 patients with metastatic liver cancer. These non-tumor samples were considered as normal liver and compared with the results from each of the tumor and non-tumor tissues in patients with HBV and HCV or without infection. These comprehensive comparisons provided valuable insight into the alteration of miRNAs in the tumor and non-tumor tissues. For example, when a ratio of 1.5 is obtained from a comparison of the miRNA expression level in tumor and non-tumor tissues, it cannot be proven whether the miRNA expression was increased in the tumor tissue or decreased in the non-tumor tissue, since both cases will produce the same results. Employing normal liver samples enables this distinction.

As shown in Fig. 2, miR-30d, miR-124, miR-200b and miR-378 demonstrated significant changes in expression in the non-tumor tissues in HCC patients compared with normal liver samples in Combinations 7, 9, 11 and 13. In all combinations except 9, only a few previously detected miRNAs were observed: let-7e, let-7f, miR-98 and miR-144. Notably, none of them demonstrated the same tendency observed in previous studies. In Combination 9, more than 80 of the 342 miRNAs detected were previously reported, and 21 and 24 of them demonstrated the same and opposite tendencies observed in previous reports, respectively. These results suggest that these miRNAs may play a role in the very early stages of carcinogenesis in HCC and some may have different roles in HCC and chronic liver diseases.

As shown in Table III, miR-2116* was significantly downregulated in HCC as well as the surrounding non-tumor tissues compared with the normal liver samples in all possible combinations; thus, miR-2116* may have some influence upon carcinogenesis of HCC. Although this miRNA has no previously reported correlation with cancer, its predicted target genes involve genes associated with cancer. The top four predicted targets with the strongest prediction scores (57) were ZDHHC11, MTCH2, DIRC2 and PEA15 (as of January 2012 according to www.microrna.org). The gene copy number of ZDHHC11 was altered in nearly half of the patients with non-small cell lung cancer (58) and bladder cancer (59). MTCH2 is a gene exhibiting highly restricted levels of gene expression variation in tumor tissues compared to non-malignant tissues (60). Bodmer et al identified DIRC2 as a familial renal cell carcinoma-associated gene (61). The expression level of PEA15 was used for grading the malignancy of astrocytic tumors (62). These facts indicate that the predicted targets play roles in cancer. The expression of miR-2116* was altered in the non-tumor tissues when compared to the normal liver samples, and accordingly, as discussed earlier, this miRNA may also play a role in the early stages of carcinogenesis. Other miRNAs which were consistently downregulated in the tumor and non-tumor tissues are miR-18b*, miR-296-5p, miR-557, miR-581, miR-625*, miR-1228 and miR-1249. Similar to miR-2116*, the predicted target genes of miR-1249 involved numerous genes whose association with cancer has been reported.

The results strongly suggest that the above miRNAs are novel biomarker candidates for chronic liver diseases. Some are novel biomarker candidates for HCC irrespective of virus infection and HCC with HCV, as shown in Table III. In this way, through miRNA expression profiling, we identified various pathogenesis-related miRNAs which may be used as biomarkers for a specific disease state, although further investigation is required.

Acknowledgements

This study was funded by the Scientific Research Grant (No. 20510184), Science and Technology Promotion Adjustment Expenses (No. 08005234), and the Integrated Database Project, from the Ministry of Education, Culture, Sports, Science and Technology of Japan.

References

1. 

HB El-SeragKL RudolphHepatocellular carcinoma: epidemiology and molecular carcinogenesisGastroenterology13225572576200710.1053/j.gastro.2007.04.06117570226

2. 

H BlumHepatocellular carcinoma: therapy and preventionWorld J Gastroenterol1173917400200516437707

3. 

M CrampHBV + HCV = HCC?Gut451681691999

4. 

Y SoiniSC ChiaWP BennettAn aflatoxin-associated mutational hotspot at codon 249 in the p53 tumor suppressor gene occurs in hepatocellular carcinomas from MexicoCarcinogenesis1710071012199610.1093/carcin/17.5.10078640905

5. 

P BoffettaL MatisaneKA MundtLD DellMeta-analysis of studies of occupational exposure to vinyl chloride in relation to cancer mortalityScand J Work Environ Health29220229200310.5271/sjweh.72512828392

6. 

H TsukumaT HiyamaA OshimaA case-control study of hepatocellular carcinoma in Osaka, JapanInt J Cancer45231236199510.1002/ijc.2910450205

7. 

F DonatoA TaggerU GelattiAlcohol and hepatocellular carcinoma: the effect of lifetime intake and hepatitis virus infections in men and womenAm J Epidemiol155323333200210.1093/aje/155.4.32311836196

8. 

S VoliniaGA CalinCG LiuA microRNA expression signature of human solid tumors defines cancer gene targetsProc Natl Acad Sci USA10322572261200610.1073/pnas.051056510316461460

9. 

N YanaiharaN CaplenE BowmanUnique micro RNA molecular profiles in lung cancer diagnosis and prognosisCancer Cell9189198200610.1016/j.ccr.2006.01.02516530703

10. 

EJ LeeY GusevJ JiangExpression profiling identifies microRNA signature in pancreatic cancerInt J Cancer12010461054200710.1002/ijc.2239417149698

11. 

Y MurakamiT YasudaK SaigoComprehensive analysis of microRNA expression patterns in hepatocellular carcinoma and non-tumorous tissuesOncogene2525372545200610.1038/sj.onc.120928316331254

12. 

A BudhuHL JiaM ForguesIdentification of metastasis-related microRNAs in hepatocellular carcinomaHepatology47897907200810.1002/hep.2216018176954

13. 

H VarnhortU DrebberF SchulzeMicroRNA gene expression profile of hepatitis C virus-associated hepatocellular carcinomaHepatology4712231232200810.1002/hep.2215818307259

14. 

Y LaderioG CouchyC BalabaudMicroRNA profiling in hepatocellular tumor is associated with clinical features and oncogene/tumor suppressors gene mutationsHepatology4719551963200810.1002/hep.2225618433021

15. 

W LiL XieX HeDiagnostic and prognositic implications of microRNAs in human hepatocellular carcinomaInt J Cancer12316161622200810.1002/ijc.2369318649363

16. 

S UraM HondaT YamashitaDifferential microRNA expression between hapatitis B and hepatitis C leading disease progression to hepatocellular carcinomaHepatology4910981112200910.1002/hep.2274919173277

17. 

S ToffaninY HoshidaA LachenmayerMicroRNA-based classification of hepatocellular carcinoma and oncogenic role of miR-517aGastoenterology14016181628201110.1053/j.gastro.2011.02.00921324318

18. 

M YasenH MizushimaK MogushiExpression of Aurora B and alterative variant forms in hepatocellular carcinoma and adjacent tissueCancer Sci100472480200910.1111/j.1349-7006.2008.01068.x19134008

19. 

L GramantieriF FornariE CallegariMicroRNA involvement in hepatocellular carcinomaJ Cell Mol Med1221892204200810.1111/j.1582-4934.2008.00533.x19120703

20. 

RN AravalliCJ SteerNK CressmanMolecular mechanisms of hepatocellular carcinomaHepatology4820472063200810.1002/hep.22580

21. 

J JiXW WangNew kids on the blockCancer Biol Therapy816831690200910.4161/cbt.8.18.8898

22. 

L LiangCM WongQ YingMicroRNA-125b suppressed human liver cancer cell proliferation and metastasis by directly targeting oncogene LIN28BHepatology5217311740201010.1002/hep.2390420827722

23. 

M OsakiF TakeshitaT OchiyaMicroRNAs as biomarkers and therapeutic drugs in human cancerBiomarkers13658670200810.1080/1354750080264657219096960

24. 

J TakamizawaH KonishiK YanagisawaReduced expression of the let-7 micro RNAs in human lung cancers in association with shortened postoperative survivalCancer Res6437533756200410.1158/0008-5472.CAN-04-063715172979

25. 

M FabbriR GarzonA CimminoMicroRNA-29 family reverts aberrant methylation in lung cancer by targeting DNA methyltransferases 3A and 3BProc Natl Acad Sci USA1041580515810200710.1073/pnas.070762810417890317

26. 

GT BommerI GerinY Fengp53-mediated activation of miRNA34 candidate tumor-suppressor genesCurr Biol1712981307200710.1016/j.cub.2007.06.06817656095

27. 

M CrawfordE BrawnerK BattleMicroRNA-126 inhibits invasion in non-small cell lung carcinoma cell linesBiochem Biophys Res Commun373607612200810.1016/j.bbrc.2008.06.09018602365

28. 

Y HayashitaH OsadaY TatematsuA polycistronic microRNA cluster, miR-17-92, is overexpressed in human lung cancers and enhances cell proliferationCancer Res6596289632200510.1158/0008-5472.CAN-05-235216266980

29. 

S VoliniaGA CalinCG LiuA microRNA expression signature of human solid tumors defines cancer gene targetsProc Natl Acad Sci USA10322572261200610.1073/pnas.051056510316461460

30. 

M GarofaloC QuintavalleG Di LevaMicroRNA signatures of TRAIL resistance in human non-small cell lung cancerOncogene2738453855200810.1038/onc.2008.618246122

31. 

N YanaiharaN CaplenE BowmanUnique microRNA molecular profiles in lung cancer diagnosis and prognosisCancer Cell9189198200610.1016/j.ccr.2006.01.02516530703

32. 

Z HuJ ChenT TianGenetic variants of miRNA sequences and non-small cell lung cancer survivalJ Clin Invest11826002608200818521189

33. 

SL YuHY ChenGC ChangMicroRNA signature predicts survival and relapse in lung cancerCancer Cell134857200810.1016/j.ccr.2007.12.00818167339

34. 

A MarkouEG TsarouchaL KaklamanisM FotinouV GeogouliasES LianidouPrognostic value of mature microRNA-21 and microRNA-205 overexpression in non-small cell lung cancer by quantitative real-time RT-PCRClin Chem5416961704200810.1373/clinchem.2007.10174118719201

35. 

LX YanXF HuangQ ShaoMicroRNA miR-21 overexpression in human breast cancer is associated with advanced clinical stage, lymph node metastasis and patient poor prognosisRNA1423482360200810.1261/rna.103480818812439

36. 

SH ChanCW WuAF LiCW ChiWC LinmiR-21 microRNA expression in human gastric carcinomas and its clinical associationAnticancer Res28907911200818507035

37. 

T SchepelerJT ReinertMS OstenfeldDiagnostic and prognostic microRNAs in stage II colon cancerCancer Res6864166424200810.1158/0008-5472.CAN-07-611018676867

38. 

G ChildsM FazzariG KungLow-level expression of microRNAs let-7d and miR-205 are prognostic markers of head and neck squamous cell carcinomaAm J Pathol174736745200910.2353/ajpath.2009.08073119179615

39. 

C RoldoE MissiagliaJP HaganMicroRNA expression abnormalities in pancreatic endocrine and acinar tumors are associated with distinctive pathologic features and clinical behaviorJ Clin Oncol2446774684200610.1200/JCO.2005.05.5194

40. 

G MarcucciMD RadmacherK MaharryMicroRNA expression in cytogenetically normal acute myeloid leukemiaN Engl J Med35819191928200810.1056/NEJMoa07425618450603

41. 

GA CalinM FerracinA CimminoA microRNA signature associated with prognosis and progression in chronic lymphocytic leukemiaN Engl J Med35317931801200510.1056/NEJMoa05099516251535

42. 

L LuD KatsarosIA de la LongraisO SochircaH YuHypermethylation of let-7a-3 in epithelial ovarian cancer is associated with low insulin-like growth factor-II expression and favorable prognosisCancer Res671011710122200710.1158/0008-5472.CAN-07-254417974952

43. 

Y GuoZ ChenL ZhangDistinctive microRNA profiles relating to patient survival in esophageal squamous cell carcinomaCancer Res682633200810.1158/0008-5472.CAN-06-441818172293

44. 

SS ChimTK ShingEC HungDetection and characterization of placental microRNAs in material plasmaClin Chem54482490200810.1373/clinchem.2007.09797218218722

45. 

S GiladE MeiriY YogevSerum microRNAs are promising biomarkersPLoS One3e3148200810.1371/journal.pone.000314818773077

46. 

PS MitchelRA ParkinEM KrohCirculating microRNAs as stable blood-based markers for cancer detectionProc Natl Acad Sci USA1051051310518200810.1073/pnas.080454910518663219

47. 

CH LawrieCd CooperE BallabioJ ChiD TramontiCS HattonAberrant expression of microRNA biosynthetic pathways components is a common feature of haematological malignancyBr J Hematol141672675200819298586

48. 

R DiazJ SilvaJM GarciaDeregulated expression of miR-106a predicts survival in human colon cancer patientsGenes Chromosomes Cancer47794802200810.1002/gcc.2058018521848

49. 

K ScheeO FodstadK FlatmarkMicroRNAs as biomarkers in colorectal cancerAm J Patho17715921599201010.2353/ajpath.2010.10002420829435

50. 

WKK WuCW LeeCH ChoD FanK WuJ YuJJY SungMicroRNA dysregulation in gastric cancer: a new player enters the gameOncogene2957615671201010.1038/onc.2010.35220802530

51. 

J ZavadilH YeZ LiuProfiling and functional analyses of microRNAs and their target gene products in human uterine leiomyomasPLoS One5e12362201010.1371/journal.pone.001236220808773

52. 

MV IorioC PiovanCM CroceInterplay between microRNAs and the epigenetic machinery: an intricate networkBoichim Biophys Acta1799694701201010.1016/j.bbagrm.2010.05.00520493980

53. 

N ValeriI VanniniF FaniniF CaloreB AdairM FabbriEpigenetics, miRNAs, and human cancer: a new chapter in human gene regulationMamm Genome20573580200910.1007/s00335-009-9206-519697081

54. 

A SchaeferM JungG KristiansenMicroRNAs and cancer: current state and future perspectives in urologic oncologyUrologic Oncol28413201010.1016/j.urolonc.2008.10.02119117772

55. 

R GarzonG MarcucciCM CroceTargeting microRNAs in cancer: rationale, strategies and challengesNat Rev Drug Discov9775789201010.1038/nrd317920885409

56. 

GA CalinCG LiuC SevignaniMicroRNA profiling reveals distinct signatures in B cell chronic lymphocytic leukemiasProc Natl Acad Sci USA1011175511760200410.1073/pnas.040443210115284443

57. 

D BetelA KoppalP AngiusC SanderC LeslieComprehensive modeling of microRNA targets predicts functional non-conserved and non-canonical sitesGenome Biol11R90201010.1186/gb-2010-11-8-r9020799968

58. 

JU KangSH KooKC KwonJW ParkJM KimGain at chromosomal region 5p15.33, containing TERT, is the most frequent genetic event in early stages of non-small cell lung cancerCancer Genet Cytogenet82111200810.1016/j.cancergencyto.2007.12.00418328944

59. 

Y YamamotoY ChochiH MatuyamaGain of 5p15.33 is associated with progression of bladder cancerOncology72132138200710.1159/000111132

60. 

K YuK GanesanLK TanA precisely regulated gene expression cassette potentially modulates metastasis and survival in multiple solid cancersPLoS Genet4e1000129200810.1371/journal.pgen.100012918636107

61. 

D BodmerM EleveldE Kater-BaatsDisruption of a novel MFS transporter gene, DIRC2, by a familial renal cell carcinoma-associated t(2;3)(q35;q21)Hum Mol Genet11641649200210.1093/hmg/11.6.64111912179

62. 

Y WatanabeF YamasakiY KajiwaraExpression of phosphoprotein enriched in astrocytes 15 kDa (PEA-15) in astrocytic tumors: a novel approach of correlating malignancy grade and prognosisJ Neurooncol100449457201010.1007/s11060-010-0201-120455002

Related Articles

Journal Cover

October 2012
Volume 4 Issue 4

Print ISSN: 1792-1074
Online ISSN:1792-1082

Sign up for eToc alerts

Recommend to Library

Copy and paste a formatted citation
x
Spandidos Publications style
Katayama Y, Maeda M, Miyaguchi K, Nemoto S, Yasen M, Tanaka S, Mizushima H, Fukuoka Y, Arii S, Tanaka H, Tanaka H, et al: Identification of pathogenesis-related microRNAs in hepatocellular carcinoma by expression profiling. Oncol Lett 4: 817-823, 2012
APA
Katayama, Y., Maeda, M., Miyaguchi, K., Nemoto, S., Yasen, M., Tanaka, S. ... Tanaka, H. (2012). Identification of pathogenesis-related microRNAs in hepatocellular carcinoma by expression profiling. Oncology Letters, 4, 817-823. https://doi.org/10.3892/ol.2012.810
MLA
Katayama, Y., Maeda, M., Miyaguchi, K., Nemoto, S., Yasen, M., Tanaka, S., Mizushima, H., Fukuoka, Y., Arii, S., Tanaka, H."Identification of pathogenesis-related microRNAs in hepatocellular carcinoma by expression profiling". Oncology Letters 4.4 (2012): 817-823.
Chicago
Katayama, Y., Maeda, M., Miyaguchi, K., Nemoto, S., Yasen, M., Tanaka, S., Mizushima, H., Fukuoka, Y., Arii, S., Tanaka, H."Identification of pathogenesis-related microRNAs in hepatocellular carcinoma by expression profiling". Oncology Letters 4, no. 4 (2012): 817-823. https://doi.org/10.3892/ol.2012.810