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Keywords:

  • liver;
  • hepatocellular carcinoma;
  • hepatitis C virus;
  • microRNA;
  • pathogenesis

Abstract

  1. Top of page
  2. Abstract
  3. Material and Methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References
  8. Supporting Information

Although several studies have investigated the association of miRNAs with hepatocellular carcinoma (HCC), the data published so far are not concordant. A reason for these discrepancies may be the fact that most studies used the nontumorous tissue surrounding the HCC lesion as a control, which is almost invariably affected by cirrhosis or chronic hepatitis, as well as other pathological conditions such as hepatitis B virus (HBV) or hepatitis C virus (HCV) infection. Moreover, HCC is often analyzed as a single group regardless of the different viral etiologies. The miRNAs differentially expressed in HCV-related HCC were investigated by comparing the tumorous tissues to a wide range of liver specimens, including healthy livers obtained from liver donors and patients who underwent liver resection for angioma, in addition to tissues from various acute and chronic liver diseases, including HCV-related cirrhosis not associated with HCC, HCV-related cirrhosis associated with HCC and HBV-associated acute liver failure. The whole set of 2,226 human miRNAs were examined, including 1,121 pre-miRNAs and 1,105 mature miRNAs, available in a microarray platform. Stringent statistical methods were applied to reduce the risk of false discoveries to less than 1%. These data identified 18 miRNAs exclusively expressed in HCV-associated HCC, characterized by high specificity and selectivity versus all other liver diseases and healthy conditions and connected into a regulatory network pivoting on p53, phosphatase and tensin homolog and all-trans retinoic acid signaling.

MicroRNAs (miRNAs) are small, about 22-nucleotide-long noncoding RNA molecules that bind to 6- to 7-nucleotide complementary sequences of mRNAs, usually resulting in post-transcriptional downregulation of gene expression. First discovered in C. elegans in 1993,[1] miRNAs were recognized as an essential, evolutionarily conserved class of genetic regulators only in 2003.[2] A single miRNA can target hundreds of mRNAs; however, at the same time, a single mRNA can be targeted by several miRNAs, thus forming a complex regulatory network that modulates basic functions such as cellular proliferation, differentiation, migration and apoptosis. Specific miRNA perturbations have been correlated with various diseases and in particular with the development of tumors. Over the last decade, the number of studies of miRNA in cancer has increased about ten times every 2 years.[3]

Murakami et al.[4] were the first to identify a set of miRNAs differentially expressed in hepatocellular carcinoma (HCC). Subsequently, a large number of studies have been performed to define the specific miRNA profile of HCC.[3, 5-8] However, no definite consensus has emerged on the miRNAs that are specifically associated with HCC. This may be in part attributed to the presence of different miRNA-related subclasses of HCC[9] but mainly to the fact that only few studies have compared HCC to bona fide normal liver tissue,[10-13] whereas the great majority evaluated the differential expression of miRNA in HCC versus the surrounding nontumor tissue used as control. However, tumor-adjacent tissues are typically affected by chronic hepatitis or cirrhosis of viral or nonviral etiology, including alcoholic liver disease, nonalcoholic steatohepatitis (NASH) or nonalcoholic fatty liver disease (NAFLD). In addition, a limitation of the current studies is that HCC cases are often analyzed as a single group regardless of the hepatitis virus involved. In fact, there is limited information on miRNAs specifically expressed in distinct groups of hepatitis C virus (HCV)- or hepatitis B virus (HBV)-related HCC.[11] All these facts may have considerably reduced the specificity and sensitivity for the identification of miRNA associated with HCC, thus limiting their usefulness as reliable biomarkers or potential therapeutic targets in HCC.

The recent detection of miRNAs in serum[14] has opened new perspectives for the development of noninvasive tests that circumvent the difficulty in obtaining tissue samples from patients with severe/acute liver diseases. It has been shown that certain serum miRNAs are significantly associated with HCC, chronic hepatitis and other liver diseases, including drug-induced hepatic injuries.[15-17] However, serum miRNA does not seem to be correlated with the miRNA found in liver tissue. For example, miR-122, a liver-specific miRNA that is invariably decreased in all liver diseases investigated to date (NASH, NAFLD, HCC, liver fibrosis, hepatitis B and drug-induced liver injury),[8, 18] exhibits increased levels in the serum of HCC and chronic hepatitis patients.[17] Thus, although serum miRNAs may represent a valuable alternative to tissue miRNAs for the identification of disease biomarkers, they are unlikely to provide mechanistic insights into the development and progression of HCC.

To obtain a reliable profile of miRNAs specifically associated with HCC, we investigated the miRNAs expressed in six types of liver tissues: HCV-associated HCC (HCC), HCC-associated nontumorous cirrhosis (HCC-CIR), HCV-associated cirrhosis without HCC (CIR), HBV-associated acute liver failure (ALF), normal liver tissue surrounding angioma (NL) and normal liver from liver donors (LD). Characteristic features of our study were as follows: (i) the wide range of healthy and diseased liver tissues examined for which a histological diagnosis was available; (ii) the number of miRNAs investigated (1,105 pre-miRNAs and 1,105 mature miRNA); (iii) the stringent statistical methods used to reduce the risk of false discoveries to less than 1% and (iv) the homogeneous methods of tissue sampling (surgical liver specimens), RNA extraction, amplification and detection.

Of the 2,226 miRNA investigated, we identified only 18 miRNA specifically associated with HCC compared to the other five groups of liver tissues. These miRNAs are connected in a molecular network that includes p53, phosphatase and tensin homolog (PTEN) and all-trans retinoic acid (RA), suggesting a direct involvement of these cell growth regulators in the pathogenesis of HCC.

Material and Methods

  1. Top of page
  2. Abstract
  3. Material and Methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References
  8. Supporting Information

Patients

Liver specimens were obtained from 34 patients at the time of OLT (orthotopic liver transplantation), from two patients undergoing liver resection for HCV-associated HCC and from seven patients undergoing liver resection for liver angioma. The demographic features of the patients are shown in Table 1. We studied 26 liver specimens obtained from ten patients with HCV-associated HCC, including nine specimens from the tumor area (HCC) and 17 specimens from the surrounding nontumorous tissue affected by cirrhosis (HCC-CIR), because in one of the ten patients, miRNA expression profiling was performed only in the periphery but not in the tumor; 18 specimens from ten patients with HCV-associated cirrhosis without HCC (CIR) and 13 specimens from four patients with HBV-associated ALF. Among the patients with HCV-associated HCC, according to the grading by Edmondson and Steiner,[19] five patients had G2 and five had G3. As a control group, we studied individual liver specimens from 12 LD and from seven subjects who underwent hepatic resection for liver angioma (NL). Within the control group, none of the subjects had evidence of active infection with hepatitis viruses, as previously reported.[20] The results of liver enzymes were normal in all subjects, except one LD who showed very slightly elevated ALT (49 U/L, normal value <42 U/L). The liver histology was available at the time of this study in all patients. The majority (11/17, 65%) had completely normal liver histology, whereas the remaining six had minimal alterations, including mild steatosis in five (29%) and mild portal inflammation in one (6%). Up to five liver specimens were obtained for each patient. Each liver specimen was divided into two pieces: one was snap frozen and the other was fixed in formalin. Snap-frozen samples were stored at −80°C and were used for miRNA expression profiling by microarray; fixed liver tissues were used for liver histology. All liver specimens were analyzed histologically. Liver and serum specimens and clinical data were received under code to protect the identity of the study subjects. Written informed consent was obtained from each patient or from the next of kin. Our study was approved by the Review Board of the Hospital Brotzu, Cagliari, Italy, and by the NIH Office of Human Subjects Research, granted on the condition that all samples be made anonymous.

Table 1. Demographic features of the different groups of subjects studied
 HCV-associated HCC (HCC)[1]HCC-associated cirrhosis (HCC-CIR)HCV-associated cirrhosis (CIR)HBV-associated acute liver failure (ALF)Normal liver (NL)[2]Liver donors (LD)
  1. 1HCC: hepatocellular carcinoma.

  2. 2Obtained during liver resection for angioma.

Number of patients910104712
Number of liver specimens analyzed9171813712
Male gender (%)8990100501458
Age (mean ± SD)55 ± 1055 ± 1048 ± 742 ± 746 ± 1336 ± 21

miRNA analysis and nomenclature

We performed miRNA expression profiling of all liver specimens using Affymetrix GeneChip miRNA2.0 arrays (Affymetrix, Santa Clara, CA), which contain 1,121 pre-miRNA (mir-) and 1,105 mature miRNA (miR-) probe sets. Total RNA, including miRNA, was extracted from frozen liver specimens using the miRNeasy Mini Kit (Qiagen, Valencia, CA). The quality and integrity of RNA were assessed with the RNA 6000 Nano Assay on the Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA). Five hundred nanograms of total RNA, including miRNA, was poly(A) tailed and then directly ligated to a fluorescent dendrimer (a branched single and double-stranded DNA molecule conjugated to biotin) using the FlashTag Biotin HSR RNA Labeling Kit (Affymetrix). An ELISA was performed prior to hybridization and analysis of the arrays to verify that all miRNAs were correctly labeled with the biotin molecule at the 3′ end. Standard Affymetrix protocols were used for hybridization, staining, washing and scanning of the arrays (available at www.affymetrix.com). All samples passed the quality control (QC) assessment performed with the miRNA QCTool available through Affymetrix, using chip-specific QC probes. According to the changes incorporated in the miRBase 17 (miRBase.org), the “*” symbol (or the equivalent “-star” suffix of Affymetrix IDs) is replaced by the “-3p” nomenclature. In addition, the “-5p” nomenclature is considered equivalent to the short miRNA name (i.e., miR-199a-5p and miR-199a).

Statistical analysis

Raw microarray data (CEL files) were imported into BRB-ArrayTools v 4.2.1 (http://linus.nci.nih.gov/BRB-ArrayTools.html).[21] Probe set summaries were computed using RMA (Robust Multi-Array) algorithm. To adjust for differences in labeling intensities and hybridization, a global normalization was made by aligning signal intensities of data arrays across the medians. Data obtained from multiple specimens of the same patient were averaged; in patients with HCC, tumor and nontumor specimens were maintained as distinct groups. A multivariate permutation F-test[22] with a maximum proportion of false discovery of 1% with 80% confidence level was used to identify miRNA with different concentration levels among the six types of liver tissues examined. Pairwise t-test comparisons were then performed using this subset of miRNAs to identify the miRNAs that differed consistently (i.e., having the same direction of change, in all pairwise comparisons) and significantly (p ≤ 0.01, in all pairwise comparisons) in a specific group of livers compared to the other five groups. Hereafter, these miRNAs will be conventionally referred to as “exclusive” miRNAs. For each exclusive miRNA, we also calculated (i) the fold change (FC), (ii) the AUC (area under the receiver operator characteristic [ROC] curve) and (iii) the sensitivity and (iv) specificity based on the best cutoff value identified by the ROC curve. All these parameters were evaluated comparing the reference group expressing the exclusive miRNA to the other five groups pooled together. The relationship between the exclusive miRNAs and liver diseases were also visualized by the heat-map and principal component analysis (PCA). Data processing was performed using Statistica (StatSoft, www.statsoft.com), Multibase (v. 2012, Numerical Dynamics.com) and IPA (Ingenuity Pathway Analysis, release June 2012). miRNA microarray data are available at the Gene Expression Omnibus (http://www.ncbi.nlm.nih.gov/geo/, accession number GSE 40744).

Results

  1. Top of page
  2. Abstract
  3. Material and Methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References
  8. Supporting Information

A total of 182 miRNAs (8% of the whole set of 2,226 human miRNA probe sets present in the microarray chip) were found to be differentially expressed among the six types of liver tissues examined (i.e., HCC, HCC-CIR, CIR, ALF, NL and LD) using a multivariate permutation F-test with a false discovery rate ≤1% (Supporting Information Table S1). Thus, only two of the 182 miRNAs would be expected to be false positives. Pairwise t-test comparisons between single groups of livers were then performed on the 182 differentially expressed miRNAs using a significance threshold of p = 0.01. A subset of 55 exclusive miRNAs was identified, which were significantly and consistently expressed in the same direction of change in only a single group compared to all the other groups. Among these 55 unique miRNAs, 18 miRNA were exclusively expressed in HCC, 30 in ALF, four in LD, two in NL and one in CIR.

Using these exclusive miRNAs, we investigated the relationship among the six groups of liver specimens by PCA (Fig. 1). Strikingly, our analysis showed HCC and ALF orthogonally aligned at the ends of the PCA axes, a pattern indicative of strongly different and unrelated expression profiles. In addition, the relatively larger nearest-neighbor distance within HCC and ALF PCA clusters denoted a higher heterogeneity of miRNA expression within these groups than within the other groups. HCC was also well separated from HCC-CIR and CIR. By contrast, CIR and HCC-CIR clustered together, suggesting that these two cirrhotic tissues share a common miRNA profile. Consistent with the healthy condition of both LD and normal liver from patients who underwent partial hepatic resection for angioma (NL), the PCA showed a close association between these two groups.

image

Figure 1. Principal component analysis showing the relations among the six liver disease conditions resulting from 55 differentially expressed miRNAs. The map shows complete separation of HCV-associated hepatocellular carcinoma (HCC) and HBV-associated acute liver failure (ALF). A partial overlapping was seen between HCV-associated cirrhosis surrounding HCC (HCC-CIR) and HCV-associated cirrhosis without HCC (CIR), as well as between normal livers obtained from patients who underwent liver resection for angioma (NL) and liver donors (LD). The two principal components account for nearly 60% of the total variance expressed by the 55 miRNAs. [Color figure can be viewed in the online issue, which is available at wileyonlinelibrary.com.]

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The heat-map (Fig. 2) confirmed that the predominant deviations occurred in miRNAs exclusive for HCC (rightmost panel) and ALF (third panel). Healthy livers (LD and NL) showed a miRNA expression pattern opposite to that of HCC and ALF: exclusive miRNAs that were upregulated in HCC or ALF were downregulated in healthy livers and vice versa. The same relationship did not apply to cirrhotic livers (CIR and HCC-CIR), which exhibited a random color mosaic, irrespective of the upregulation or downregulation of HCC- and ALF-exclusive miRNAs. Figure 2 also shows the FC, the area under the ROC curve (AUC), sensitivity and specificity of the 55 exclusive miRNAs. In particular, HCC- and ALF-exclusive miRNAs reached high levels of sensitivity (91 ± 8 and 97 ± 4, respectively, mean ± standard deviation) and specificity (85 ± 6 and 100 ± 0, respectively), which are comparable to those of biomarkers of diagnostic grade. A plot of FCs of the 55 exclusive miRNAs is also shown in the Supporting Information Figure S1.

image

Figure 2. Heat-map of the 55 miRNAs (rows) differentially expressed in the six groups of livers analyzed. Each column represents a single patient (up to five liver specimens for each patient), and each row a single miRNA. miRNAs that are upregulated are shown in shades of red; those downregulated are shown in shades of green. The intensity of the color in each cell reflects the level of the corresponding miRNA in the corresponding patient expressed as normalized log 2 ratios. Within each group, miRNAs are ordered according to decreasing fold changes (FC). The columns on the right show the FC, area under the ROC curve (AUC), sensitivity (Sn) and specificity (Sp) of each miRNA, relative to the contrast between the group where it was differentially expressed and the remaining five groups. ROC curves of HCC miRNAs are also plotted in Figure 3. HCC, HCV-associated hepatocellular carcinoma; HCC-CIR, HCV-associated cirrhosis surrounding HCC; CIR, HCV-associated cirrhosis without HCC; ALF, HBV-associated acute liver failure; NL, normal liver from liver resection for angioma; LD, normal livers from liver donors. No data are shown for HCC-CIR as no differentially expressed miRNAs were found in this group of livers. [Color figure can be viewed in the online issue, which is available at wileyonlinelibrary.com.]

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The ROC curves of the 18 HCC-exclusive miRNAs are plotted in Figure 3. Four of these miRNAs (miR-224, miR-224-3p, miR-221 and miR-130a) showed AUC values of 97. Interestingly, among the 18 HCC-exclusive miRNAs, there were three pairs of mature miRNAs: miR-224 and miR-224-3p (both upregulated); miR-139-5p and miR-139-3p (downregulated) and miR-199a-5 and miR-199a-3p (downregulated). The detection of the miRNA-224 pair is supported by the presence of the precursor (mir-224) among the 18 HCC-exclusive miRNAs.

image

Figure 3. Receiver operating characteristic curve analysis of the 18 miRNA differentially expressed in HCC. The average area under the curve (AUC) of all 18 miRNAs is 91.9 ± 4.1 (mean ± SD). Sensitivity and specificity values are shown in Figure 2. [Color figure can be viewed in the online issue, which is available at wileyonlinelibrary.com.]

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A set of 4,195 mRNAs potentially targeted by the HCC-exclusive mature miRNAs was obtained from TarBase, TargetScan, miRecords and Ingenuity Expert/Assistant Findings databases, using data validated by experimental observations or high-confidence predictions. The screening was done for 14 of the 16 mature miRNAs, as data of miR-199a-3p and miR-199a-5p were not available. The analysis made it possible to identify the different miRNAs targeting the same mRNA (miRNA convergency) as well as the different mRNAs targeted by the same miRNA (miRNA divergency; Fig. 4a).

image

Figure 4. Relationship between 14 HCC-exclusive mature miRNAs and their putative target mRNAs obtained from TarBase, TargetScan, miRecords and Ingenuity Expert/Assistant Findings, using data validated by experimental observations or high-confidence predictions. (a) Two-way table showing miRNAs that share the same target mRNA (miRNA convergency) in the rows, and mRNAs targeted by the same miRNA (miRNA divergency) in the columns. The table shows only the first 16 mRNAs with the highest miRNA convergency. Mir-195 and miR-497 are in the same column as they have the same seed sequence. The maximum convergency is shown by seven miRNAs (54%) that target QKI. The maximum divergency is shown by miR-195/miR-497, which target 1,440 mRNAs (34% of the 4,195 mRNAs identified). Data of miR-199a-3p and miR-199a-5p were not available. The red color indicates miRNAs that are upregulated in HCC, and green indicates miRNAs downregulated. (b) Relationship between the number of targeting miRNAs and the number of targeted mRNAs. Most of mRNAs are targeted by one or two miRNAs. The line shows the exponential fitting. [Color figure can be viewed in the online issue, which is available at wileyonlinelibrary.com.]

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The maximum convergency is represented by eight miRNAs (miR-195, miR-497, miR-214, miR-224, miR-139-5p, miR-125a-5p, miR-130a and miR-221), all potentially able to bind to QKI (quaking homolog) mRNA. QKI is a member of the signal transduction and activation of RNA family of RNA-binding proteins, which has recently been identified as a tumor suppressor in various cancers (glioblastoma multiforme, gastric cancer and colon cancer)[23-25]; however, its role in HCC remains to be established.

The highest divergency is shown by miR-195 and miR-497, two miRNAs with the same seed sequence, potentially able to bind to 1,440 mRNAs, equivalent to 34% of all mRNAs targeted by the set of HCC-exclusive miRNAs. Figure 4a also shows that the clusters of miRNAs targeting the same mRNA include both downregulated and upregulated miRNAs, a fact that denotes the extreme complexity of the post-transcriptional regulation played by miRNAs. However, the correlation between the number of converging miRNAs and the number of targeted mRNAs shows that most of mRNAs are targeted by a single miRNA (Fig. 4b). Interestingly, the data fit perfectly to an exponential function, suggesting that the relationship between targeting miRNA and targeted mRNA follows a precise, although not yet parametrically defined, statistical distribution.

IPA core analysis attributed the 18 HCC-exclusive miRNAs to the HCC category (p = 5.42 × 10−11) yielding a single network that included 16 of the 18 miRNAs, with the only exclusion of miR-452 and miR-1269. However, miRNA-452 was added manually to the network as this miRNA was recently shown to be coordinately regulated with its neighboring miRNA-224 in HCC through epigenetic mechanisms.[26] The IPA network with this update is shown in Figure 5. Interestingly, the network pivots on p53, PTEN and RA, three important modulators of cell growth, differentiation, apoptosis and cell cycle, which also play an important role in the development of HCC.[27, 28] Our data depict ALF as an extreme condition, totally different from all the other liver conditions investigated. All 30 ALF-exclusive miRNAs showed very high sensitivity and specificity values. The role of these miRNAs in ALF is currently being investigated in a separate study. According to the definition of exclusive miRNAs used in our study, the presence of groups with similar characteristics would reduce the probability of detecting exclusive miRNAs in these groups. This may explain why only a single exclusive miRNA was detected in CIR and none in HCC-CIR livers. However, four (miR-4298, miR-575, miR-33b-3p and mir-610_x) and two (mir-517a_x, miR-21-3p) miRNAs were found to be exclusively expressed by LD and NL, respectively.

image

Figure 5. Network showing the relationship among 17 HCC-exclusive miRNAs detected in our study (asterisks) obtained using IPA. Sixteen miRNAs were automatically mapped by IPA. MiR-452 was added manually on the basis of data found in the literature. Only miRNA-1269, so far reported only in a case of breast tumor, is not represented in the network. When more than one miRNAs are associated with the same icon, the first one is that nominally shown in the pathway; the others (with the exception of miR-452) are indicated by IPA as synonyms. Mature miRNAs are represented by trapezoids. Pre-miRNAs are Ω-shaped (hairpin-like). The green and red colors represent negative-fold and positive-fold changes, respectively. The intensity of the color is indicative of the magnitude of the FC. Note that miRNAs with asterisks associated with the same icon have approximately the same FC, as shown in Figure 2. Most of the miRNAs pivot on p53, PTEN and all-trans retinoic acid (visualized in yellow). [Color figure can be viewed in the online issue, which is available at wileyonlinelibrary.com.]

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Discussion

  1. Top of page
  2. Abstract
  3. Material and Methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References
  8. Supporting Information

The expression of miRNAs associated with HCC was first investigated in 2006 by Murakami et al.[4] who identified eight miRNAs differentially expressed in HCC by comparing samples of HCC with paired samples of adjacent nontumorous tissue. Some of these miRNAs were confirmed in subsequent studies.[11-13, 29, 30] However, in recent years, the number of miRNAs associated with HCC has exponentially grown, and a recent review produced a list of 112 miRNAs associated to HCC identified in 17 studies.[5] The most consistently detected was miR-199a, reported by seven of 17 studies. On the other hand, a total of 74 miRNAs (66% of the entire set) were reported only in individual studies, demonstrating a substantial lack of consensus among the different reports. These discrepancies have been attributed to the differences among miRNA probes, staging and grade of malignancy of the tumor and etiological factors. The latter in particular are difficult to control due to the coexistence of infections by hepatitis viruses, metabolic disorders and liver fibrosis underlying HCC. The robustness of the association with HCC, irrespective of the etiologic factors, is evident in the case of miRNA 199a/b-3p, the third most highly expressed miRNA in the liver,[11] which was found to be consistently decreased in HCC in patients with HBV infection,[11] HCV infection (data from our study) and alcohol consumption.[29] The demonstration of a causative relationship between miR-199a/b-3p and HCC was further confirmed by the correlation of this miRNA with poor survival, shorter time to tumor recurrence and inhibition of HCC growth both in vivo and in vitro after miRNA 199a/b-3p administration, along with downregulation of growth- and tumor-promoting pathways (mTOR, c-MET and PAK4/Raf/MERK/ERK).[10, 11, 31] However, it is possible that certain miRNAs are selectively expressed according to the different HCC etiology. Consistent with this hypothesis, we found only a small fraction (20%) of miRNAs in common between HCV-related HCC and virus-negative, alcohol-related HCC (data of our study and Ref. [29], respectively), suggesting that alcohol-related and HCV-related HCCs are regulated, at least in part, by different miRNA profiles. These observations underscore the need for an accurate etiological diagnosis to link differential miRNA expression to specific liver conditions.

The identification of HCC-exclusive miRNAs is important in the perspective of identifying new diagnostic tools and potential therapeutic targets with high sensitivity (low false-negative error) and specificity (low false-positive error) for this highly lethal form of human cancer. In this respect, our study was aimed at extending the comparison of miRNA expression in HCV-related HCC to a wider range of liver diseases and healthy conditions, not included in earlier studies, to provide more reliable sensitivity and specificity data. Among the 18 HCC-exclusive miRNAs identified in our study, several were already reported in previous studies, including miR-221 and miR-224 (found in 52% of the previous reports), miR-199a-5p, miR-195, miR-214, miR-199a-3p, miR-125a-5p, miR-139-5p, miR-130a, miR-199b-3p, miR-139-3p, miR-224-3p and miR-452. The exceptions are represented by three of the 18 HCC-exclusive miRNAs (miR-497, miRNA-1269 and miR-424-3p), which were not previously reported in HCC studies. They include miR-497, which has been found in various tumors but not in HCC,[32-34] miRNA-1269, which has been found only in a case of breast tumor,[35] and miR-424-3p, which has never been associated with cancer. Conversely, several miRNAs indicated in previous studies as differentially expressed in HCC were not found to be exclusive for HCV-related HCC in our study. For instance, we found that let-7a and miR-200b, two miRNAs often reported as downregulated in HCC,[36-39] are downregulated in HCC compared to other diseases (CIR, HCC-CIR and ALF), but not compared to healthy livers (NL and LD), which were not commonly used for comparison in previous studies. In addition, miR-21, usually indicated as upregulated in HCC,[36, 40-42] was even more expressed in ALF.

The presence of all but one of the 18 HCC-exclusive miRNAs in a network that includes p53, PTEN and RA[43, 44] is consistent with the fact that these growth modulators are directly involved in the pathogenesis of HCC.[27, 28] p53, PTEN and RA are prominent tumor suppressors whose inactivation has been found to be responsible for the development of the majority of human cancers. This suggests that their molecular pathways play an essential, although not specific, role in the development of HCV-related HCC. These considerations corroborate the importance of identifying HCC-exclusive miRNAs for the development of new diagnostic tools and therapeutic strategies for HCC.

Acknowledgements

  1. Top of page
  2. Abstract
  3. Material and Methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References
  8. Supporting Information

Giacomo Diaz was the recipient of a grant from Fondazione Banco di Sardegna, Sassari, Italy (739/2011.1045).

References

  1. Top of page
  2. Abstract
  3. Material and Methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References
  8. Supporting Information

Supporting Information

  1. Top of page
  2. Abstract
  3. Material and Methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References
  8. Supporting Information

Additional Supporting Information may be found in the online version of this article.

FilenameFormatSizeDescription
ijc28075-sup-0001-suppinfo01.doc333KSupplementary Table
ijc28075-sup-0002-suppinfo02.tif84KSupplementary Figure

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