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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">OL</journal-id>
<journal-title-group>
<journal-title>Oncology Letters</journal-title>
</journal-title-group>
<issn pub-type="ppub">1792-1074</issn>
<issn pub-type="epub">1792-1082</issn>
<publisher>
<publisher-name>D.A. Spandidos</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3892/ol.2018.7892</article-id>
<article-id pub-id-type="publisher-id">OL-0-0-7892</article-id>
<article-categories>
<subj-group>
<subject>Articles</subject>
</subj-group>
</article-categories>
<title-group>
<article-title>MicroRNA-33a downregulation is associated with tumorigenesis and poor prognosis in patients with hepatocellular carcinoma</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author"><name><surname>Xie</surname><given-names>Ru-Ting</given-names></name>
<xref rid="af1-ol-0-0-7892" ref-type="aff">1</xref>
<xref rid="af2-ol-0-0-7892" ref-type="aff">2</xref>
<xref rid="fn1-ol-0-0-7892" ref-type="author-notes">&#x002A;</xref></contrib>
<contrib contrib-type="author"><name><surname>Cong</surname><given-names>Xian-Ling</given-names></name>
<xref rid="af3-ol-0-0-7892" ref-type="aff">3</xref>
<xref rid="fn1-ol-0-0-7892" ref-type="author-notes">&#x002A;</xref></contrib>
<contrib contrib-type="author"><name><surname>Zhong</surname><given-names>Xiao-Ming</given-names></name>
<xref rid="af4-ol-0-0-7892" ref-type="aff">4</xref>
<xref rid="fn1-ol-0-0-7892" ref-type="author-notes">&#x002A;</xref></contrib>
<contrib contrib-type="author"><name><surname>Luo</surname><given-names>Ping</given-names></name>
<xref rid="af5-ol-0-0-7892" ref-type="aff">5</xref>
<xref rid="fn1-ol-0-0-7892" ref-type="author-notes">&#x002A;</xref></contrib>
<contrib contrib-type="author"><name><surname>Yang</surname><given-names>Hui-Qiong</given-names></name>
<xref rid="af2-ol-0-0-7892" ref-type="aff">2</xref></contrib>
<contrib contrib-type="author"><name><surname>Lu</surname><given-names>Gai-Xia</given-names></name>
<xref rid="af1-ol-0-0-7892" ref-type="aff">1</xref></contrib>
<contrib contrib-type="author"><name><surname>Luo</surname><given-names>Pei</given-names></name>
<xref rid="af1-ol-0-0-7892" ref-type="aff">1</xref></contrib>
<contrib contrib-type="author"><name><surname>Chang</surname><given-names>Zheng-Yan</given-names></name>
<xref rid="af2-ol-0-0-7892" ref-type="aff">2</xref></contrib>
<contrib contrib-type="author"><name><surname>Sun</surname><given-names>Ran</given-names></name>
<xref rid="af1-ol-0-0-7892" ref-type="aff">1</xref></contrib>
<contrib contrib-type="author"><name><surname>Wu</surname><given-names>Ting-Miao</given-names></name>
<xref rid="af1-ol-0-0-7892" ref-type="aff">1</xref></contrib>
<contrib contrib-type="author"><name><surname>Lv</surname><given-names>Zhong-Wei</given-names></name>
<xref rid="af1-ol-0-0-7892" ref-type="aff">1</xref></contrib>
<contrib contrib-type="author"><name><surname>Fu</surname><given-names>Da</given-names></name>
<xref rid="af1-ol-0-0-7892" ref-type="aff">1</xref>
<xref rid="c1-ol-0-0-7892" ref-type="corresp"/></contrib>
<contrib contrib-type="author"><name><surname>Ma</surname><given-names>Yu-Shui</given-names></name>
<xref rid="af1-ol-0-0-7892" ref-type="aff">1</xref>
<xref rid="af6-ol-0-0-7892" ref-type="aff">6</xref>
<xref rid="c1-ol-0-0-7892" ref-type="corresp"/></contrib>
</contrib-group>
<aff id="af1-ol-0-0-7892"><label>1</label>Department of Nuclear Medicine, Shanghai Tenth People&#x0027;s Hospital, Tongji University School of Medicine, Shanghai 200072, P.R. China</aff>
<aff id="af2-ol-0-0-7892"><label>2</label>Department of Pathology, Shanghai Tenth People&#x0027;s Hospital, Tongji University School of Medicine, Shanghai 200072, P.R. China</aff>
<aff id="af3-ol-0-0-7892"><label>3</label>Tissue Bank, China-Japan Union Hospital, Jilin University, Changchun, Jilin 130033, P.R. China</aff>
<aff id="af4-ol-0-0-7892"><label>4</label>Department of Radiology, Jiangxi Provincial Tumor Hospital, Nanchang, Jiangxi 330029, P.R. China</aff>
<aff id="af5-ol-0-0-7892"><label>5</label>Department of Breast Cancer, Nanchang Third Hospital, Nanchang, Jiangxi 330002, P.R. China</aff>
<aff id="af6-ol-0-0-7892"><label>6</label>Shanghai Engineering Research Center of Molecular Therapeutics and New Drug Development, College of Chemistry and Molecular Engineering, East China Normal University, Shanghai 200062, P.R. China</aff>
<author-notes>
<corresp id="c1-ol-0-0-7892"><italic>Correspondence to</italic>: Dr Da Fu or Dr Yu-Shui Ma, Department of Nuclear Medicine, Shanghai Tenth People&#x0027;s Hospital, Tongji University School of Medicine, Middle 301 Yanchang Road, Shanghai 200072, P.R. China, E-mail: <email>fu800da900@126.com</email>, E-mail: <email>mayushui2015@126.com</email></corresp>
<fn id="fn1-ol-0-0-7892"><label>&#x002A;</label><p>Contributed equally</p></fn>
</author-notes>
<pub-date pub-type="ppub">
<month>04</month>
<year>2018</year></pub-date>
<pub-date pub-type="epub">
<day>29</day>
<month>01</month>
<year>2018</year></pub-date>
<volume>15</volume>
<issue>4</issue>
<fpage>4571</fpage>
<lpage>4577</lpage>
<history>
<date date-type="received"><day>11</day><month>12</month><year>2016</year></date>
<date date-type="accepted"><day>13</day><month>10</month><year>2017</year></date>
</history>
<permissions>
<copyright-statement>Copyright &#x00A9; 2018, Spandidos Publications</copyright-statement>
<copyright-year>2018</copyright-year>
</permissions>
<abstract>
<p>In order to examine the prognostic significance of miR-33a in patients with hepatocellular carcinoma (HCC), total RNA was extracted from 149 HCC biopsies, 36 of which were paired with para-carcinoma tissues, and miR-33a expression was measured by reverse transcription-quantitative polymerase chain reaction. The results demonstrated that miR-33a expression was decreased in HCC biopsies compared with normal liver tissue samples. It was also demonstrated that miR-33a expression was significantly associated with tumor foci number. Furthermore, overall and progression-free survival time was decreased in patients expressing low miR-33a with multiple tumor foci. Taken together, the low expression of miR-33a may be a potential risk factor for HCC.</p>
</abstract>
<kwd-group>
<kwd>microR-33a expression</kwd>
<kwd>hepatocellular carcinoma</kwd>
<kwd>overall survival</kwd>
<kwd>prognosis</kwd>
</kwd-group>
</article-meta>
</front>
<body>
<sec sec-type="intro">
<title>Introduction</title>
<p>Hepatocellular carcinoma (HCC) is the sixth most prevalent cancer worldwide, and is associated with an extremely poor prognosis (<xref rid="b1-ol-0-0-7892" ref-type="bibr">1</xref>&#x2013;<xref rid="b3-ol-0-0-7892" ref-type="bibr">3</xref>). A principal reason for the high mortality of this disease is the failure of early diagnosis for patients with HCC and the lack of effective therapies for patients with HCC in advanced stages. Despite a number of advances made in therapeutic strategies and surgery, the overall prognosis for patients with HCC remains poor due to the high rate of metastasis and recurrence (<xref rid="b4-ol-0-0-7892" ref-type="bibr">4</xref>&#x2013;<xref rid="b6-ol-0-0-7892" ref-type="bibr">6</xref>). Hence, the characterization of the molecular mechanisms in HCC is urgently required to allow the development of novel treatment methods for patients with HCC.</p>
<p>MicroRNAs (miRNAs/miRs) are small non-coding RNAs (21&#x2013;23 nucleotides) that are transcribed as precursors in the nucleus and are subsequently processed into mature miRNAs in the cytoplasm. Mature miRNAs primarily function by sequence specific interactions with the 3&#x2032;-untranslated regions of mRNAs, leading to the translational suppression or degradation of the mRNAs (<xref rid="b7-ol-0-0-7892" ref-type="bibr">7</xref>). An increasing number of studies have suggested that miRNAs serve an essential role as prognostic and predictive biomarkers in various types of cancer. For example, miR-1290 and miR-196b have been demonstrated to predict the chemotherapeutic response of patients with lung adenocarcinoma (<xref rid="b8-ol-0-0-7892" ref-type="bibr">8</xref>). miR-149, an anti-tumor miRNA, has been identified as dysregulated in a variety of types of cancer, including gastric (<xref rid="b9-ol-0-0-7892" ref-type="bibr">9</xref>), breast (<xref rid="b10-ol-0-0-7892" ref-type="bibr">10</xref>) and colorectal cancer (<xref rid="b11-ol-0-0-7892" ref-type="bibr">11</xref>,<xref rid="b12-ol-0-0-7892" ref-type="bibr">12</xref>).</p>
<p>It is also reported that a number of are associated with HCC carcinogenesis, progression and metastasis, including miR-15b (<xref rid="b13-ol-0-0-7892" ref-type="bibr">13</xref>), miR-122 (<xref rid="b14-ol-0-0-7892" ref-type="bibr">14</xref>) and miR-29 (<xref rid="b15-ol-0-0-7892" ref-type="bibr">15</xref>). Furthermore, the low expression of miR-124 is significantly associated with a more aggressive phenotype and a poorer prognosis (<xref rid="b16-ol-0-0-7892" ref-type="bibr">16</xref>), whereas a high expression of miR-182 has been associated with intrahepatic metastasis and poor prognosis in HCC (<xref rid="b17-ol-0-0-7892" ref-type="bibr">17</xref>). However, the mechanism of these miRNAs and their regulatory networks in HCC remain elusive, and a number of miRNAs that are associated with HCC have yet to be considered.</p>
<p>miR-33a was originally demonstrated to regulate lipid and cholesterol metabolism (<xref rid="b18-ol-0-0-7892" ref-type="bibr">18</xref>), and is an intronic miRNA located within the sequence of the sterol regulatory element binding protein 2 (SREBP-2) gene. miR-33a has also been implicated as a tumor suppressor miRNA; Kuo <italic>et al</italic> (<xref rid="b19-ol-0-0-7892" ref-type="bibr">19</xref>) identified that miR-33a is downregulated in lung cancer cells and inhibits osteolytic bone metastasis by targeting parathyroid hormone. miR-33a has also been demonstrated to act as a tumor suppressor miRNA, and may downregulate the expression of the oncogenic kinase Pim-1 in K562 lymphoma cells and colon carcinoma (<xref rid="b20-ol-0-0-7892" ref-type="bibr">20</xref>,<xref rid="b21-ol-0-0-7892" ref-type="bibr">21</xref>). However, the role of miR-33a in HCC is not yet fully characterized. In the present study, the miR-33a expression was quantified, and its significance in the prediction of a prognosis was assessed in patients with HCC.</p>
</sec>
<sec sec-type="materials|methods">
<title>Materials and methods</title>
<sec>
<title/>
<sec>
<title>Patients and tissue samples</title>
<p>A total of 149 HCC biopsies with a median age of 65.4 years (range 45 to 81 years), 36 of which were pairs of tissue with para-carcinoma tissues, were extracted between July 2004 and October 2013 from Tissue Bank, China-Japan Union Hospital, Jilin University (Jilin, China). All tissues were snap-frozen immediately in liquid nitrogen and stored at &#x2212;80&#x00B0;C until the reverse transcription-quantitative polymerase chain reaction (RT-qPCR) assay. None of the participants had undergone chemotherapy or radiotherapy prior to surgery. Clinical features were recorded, including each participant&#x0027;s characteristics (age, sex,), tumor characteristics (foci number, diameter, tumor differentiation, and distant metastasis) and miR-33a expression status, as included in <xref rid="tI-ol-0-0-7892" ref-type="table">Table I</xref>. The HCC tissues were staged based on 7th edition of the American Joint Committee on Cancer Tumor-Node-Metastasis staging system for HCC (<xref rid="b22-ol-0-0-7892" ref-type="bibr">22</xref>). All patients were grouped as &#x2265;60 or &#x003C;60 years of age, and tumors were grouped as &#x2265;5 or &#x003C;5 cm according to the tumor diameter.</p>
<p>A 150-month follow-up was conducted. The information required in order to complete the follow-up was received via outpatient visits or telephone calls, and was updated at three-month intervals. OS (overall survival) was defined as the time period from diagnosis to the time of mortality, irrespective of the cause. PFS (progression free survival) was defined from the initial date of diagnosis to the time of tumor progression, as assessed by a computed tomography (CT) scan, or to the time of mortality due to HCC.</p>
</sec>
<sec>
<title>Ethics statement</title>
<p>The present study was approved by the Ethics Committee of Shanghai Tenth People&#x0027;s Hospital, Tongji University School of Medicine (Shanghai, China; approval no., SHSY-IEC-pap-15-18). Each participant provided written informed consent prior to participating in the study. All samples were handled anonymously, according to applicable ethical and legal standards.</p>
</sec>
<sec>
<title>RNA extraction</title>
<p>Total RNA was isolated from HCC and para-carcinoma tissue specimens using TRIzol reagent (Thermo Fisher Scientific, Inc., Waltham, MA, USA), according to the manufacturer&#x0027;s protocol. The RNA concentration was determined using a Nanodrop 1000 spectrophotometer (Nanodrop; Thermo Fisher Scientific, Inc.; Wilmington, DE, USA) and the purity was identified with 1.5&#x0025; denaturing agarose gel.</p>
</sec>
<sec>
<title>RT-qPCR</title>
<p>RT reactions were performed using AMV Reverse Transcriptase (Takara Biotechnology Co., Ltd., Dalian, China) and qPCR was performed on the Applied Biosystems 7900HT Sequence Detection System (Thermo Fisher Scientific, Inc.). TaqMan probe-based qPCR was carried out using TaqMan MicroRNA Reverse Transcription kit (cat. no. 4366597) and Universal Master Mix II (cat. no. 4440048; Applied Biosystems; Thermo Fisher Scientific, Inc.) according to the protocol of the manufacturer (<xref rid="b23-ol-0-0-7892" ref-type="bibr">23</xref>). Specific RT primers and TaqMan probes for hsa-miR-33a (cat. no. 000424) and U6 (cat. no. 4427975; (Applied Biosystems; Thermo Fisher Scientific, Inc.) were used to quantify the expression of hsa-miR-33a. The specific primers are as follows: hsa-miR-33a, forward, 5&#x2032;-GCACTTTCATGATACAAGCCG-3&#x2032; and reverse, 5&#x2032;-GACCACTCAGTTTAGAGCCA-3&#x2032;; U6, forward, 5&#x2032;-CTCGCTTCGGCAGCACATATACT-3&#x2032; and reverse, 5&#x2032;-ACGCTTCACGAATTTGCGTGTC-3&#x2032;. Thermocycling conditions were as follows: Initial denaturation at 94&#x00B0;C for 10 min, followed by 35 cycles of 94&#x00B0;C for 30 sec, 60&#x00B0;C for 30 sec and 72&#x00B0;C for 30 sec, with a final extension at 72&#x00B0;C for 10 min. Each reaction was independently tested a minimum of three times. U6 was used as the internal control and miR-33a levels were quantified using the 2<sup>&#x2212;&#x0394;&#x0394;Cq</sup> method (<xref rid="b24-ol-0-0-7892" ref-type="bibr">24</xref>). miR-33a level was summarized and recorded as high vs. low levels of expression based on the median value.</p>
</sec>
<sec>
<title>Statistical analysis</title>
<p>Statistical analysis was conducted using SPSS 20.0 (IBM Corp., Armonk, NY, USA) and the production of figures was performed with GraphPad 5.0 software (GraphPad Software, Inc., La Jolla, CA, USA). An independent t-test was used to evaluate differences between two groups, and a &#x03C7;<sup>2</sup> test was used to examine differences between multiple groups. OS and DFS curves were generated by GraphPad 5.0 software. Univariate and multivariate survival analyses were performed with Cox proportional hazard regression. P&#x003C;0.05 was considered to indicate a statistically significant difference.</p>
</sec>
</sec>
</sec>
<sec sec-type="results">
<title>Results</title>
<p>miR-33a expression in HCC and para-carcinoma tissue samples. In order to investigate the expression and prognostic significance of miR-33a in patients with HCC, the present study evaluated miR-33a expression levels via RT-qPCR in 36 biopsy pairs and 113 unpaired HCC biopsies. The miR-33a expression levels were classified as high or low compared with the median value. miR-33a expression levels were significantly lower in the 36 tumor biopsies than in the paired adjacent non-tumor tissues [fold change (FC), 0.11; P=0.004; <xref rid="f1-ol-0-0-7892" ref-type="fig">Fig. 1A and B</xref>]. It was also identified that the miR-33a expression was significantly downregulated in 149 HCC tissue samples relative to 36 non-tumor tissue samples (FC, 0.51, P=0.043; <xref rid="f1-ol-0-0-7892" ref-type="fig">Fig. 1C</xref>).</p>
<sec>
<title/>
<sec>
<title>Association of miR-33a expression with the clinical characteristics of HCC</title>
<p>The associations between miR-33a expression and individual clinical characteristics were investigated, and are listed in <xref rid="tI-ol-0-0-7892" ref-type="table">Table I</xref>. The results revealed that miR-33a expression levels were significantly correlated with sex (P=0.045) and tumor foci number (P=0.007) in HCC samples. However, there was no association of miR-33a expression with patient age, tumor diameter, tumor differentiation or distant metastasis (P&#x003E;0.05).</p>
<p>Association between clinical characteristics and prognosis in HCC. The association between the clinical characteristics and HCC prognosis were further investigated by univariate survival analyses based on a Cox proportional hazard regression model. In accord with our prior hypothesis, multiple tumor foci [hazard ratio (HR), 1.995; 95&#x0025; confidence interval (CI), 1.208&#x2013;3.293; P=0.007] increased tumor size (HR, 1.945; 95&#x0025; CI, 1.170&#x2013;3.246; P=0.011), poorly differentiated tumors (HR, 0.471; 95&#x0025; CI, 0.262&#x2013;0.842; P=0.011) and distant metastasis (HR, 3.468; 95&#x0025; CI, 1.130&#x2013;10.644; P=0.032) were positively associated with a poor prognosis (<xref rid="tII-ol-0-0-7892" ref-type="table">Table II</xref>).</p>
</sec>
<sec>
<title>Low expression of miR-33a is a prognostic marker for patients with HCC</title>
<p>As univariate survival (<xref rid="tII-ol-0-0-7892" ref-type="table">Table II</xref>) and Kaplan-Meier survival analyses (<xref rid="f2-ol-0-0-7892" ref-type="fig">Fig. 2A-D</xref>) demonstrated, the lower expression of miR-33a group exhibited a shorter OS (HR, 0.072; 95&#x0025; CI, 0.033&#x2013;0.159; P&#x003C;0.001) and PFS (HR, 0.194, 95&#x0025; CI, 0.118&#x2013;0.317; P&#x003C;0.001), which indicated that the low expression of miR-33a may be a negative factor for HCC prognosis.</p>
<p>In order to explore whether the expression of miR-33a may unite with other clinical factors to influence HCC survival, a multivariate Cox proportional hazards regression analysis was performed. Associations between miR-33a expression and parameters (including age, sex, tumor foci number, tumor diameter, tumor differentiation and distant metastasis) that are predictive of HCC prognosis were initially analyzed by the model. As presented in <xref rid="tI-ol-0-0-7892" ref-type="table">Table I</xref>, the results demonstrated that the patient sex (P=0.045) and tumor foci number (P=0.007) were positively correlated with the miR-33a expression levels in the HCC tissue samples. A forward stepwise univariate survival analysis revealed that tumor foci number, tumor diameter, differentiation, distant metastasis and miR-33a expression were positively associated with HCC prognosis. The above results demonstrated that the number of tumor foci and the miR-33a expression level may jointly influence HCC prognosis.</p>
<p>The 149 HCC patients were subsequently divided into two groups. One group was comprised of patients with low miR-33 expression levels and multiple tumor foci (L&#x002B;M), whereas patients with high miR-33 expression levels and single tumor foci, comprised the other group (H&#x002B;S). The L&#x002B;M group experienced a significantly shorter OS (HR, 16.665; 95&#x0025; CI, 6.330&#x2013;43.873; P&#x003C;0.001) and PFS (HR, 5589; 95&#x0025; CI, 2.975&#x2013;10.503; P&#x003C;0.001) time compared with H&#x002B;S, as determined via multivariate Cox regression model and Kaplan-Meier survival analyses (<xref rid="tII-ol-0-0-7892" ref-type="table">Table II</xref>; <xref rid="f2-ol-0-0-7892" ref-type="fig">Fig. 2</xref>).</p>
<p>In summary, the data of the present study demonstrated that the expression of miR-33a may serve a significant role in HCC progression, and that miR-33a may have exhibited potential as a tumor biomarker in the determination of the prognosis of HCC.</p>
</sec>
</sec>
</sec>
<sec sec-type="discussion">
<title>Discussion</title>
<p>Molecular biomarkers have started to serve an important role in the selection of patient therapeutics; they may serve as indicators of a patient&#x0027;s individual likelihood of a chemotherapeutic response. The HCC mortality rate is the fastest growing among all types of cancer and it is the third most common cause of tumor-associated mortality (<xref rid="b25-ol-0-0-7892" ref-type="bibr">25</xref>&#x2013;<xref rid="b27-ol-0-0-7892" ref-type="bibr">27</xref>). Although there have been improvements in surgery and other therapeutic methods, the 5-year survival rate has remained &#x003C;15&#x0025; for a number of years (<xref rid="b28-ol-0-0-7892" ref-type="bibr">28</xref>&#x2013;<xref rid="b31-ol-0-0-7892" ref-type="bibr">31</xref>). In order to seek a more efficient and individualized treatment, it is essential for researchers to comprehensively understand the molecular mechanisms of HCC progression.</p>
<p>Accumulating studies have demonstrated that the expression of miRNA is dysregulated in various types of human cancer, and may be associated with oncogenesis. It has been reported that miRNAs can indirectly repress the expression of a number of cancer-associated genes, and directly work as tumor suppressors or oncogenes (<xref rid="b32-ol-0-0-7892" ref-type="bibr">32</xref>). A number of studies have described the role of miRNAs in cancer treatment and diagnosis as a prognostic indicator. For example, a seven-miRNA signature of could be a robust predictor for OS and relapse-free survival in gastric cancer (<xref rid="b33-ol-0-0-7892" ref-type="bibr">33</xref>), or the low expression of miR-26 in the diagnosis of HCC (<xref rid="b34-ol-0-0-7892" ref-type="bibr">34</xref>).</p>
<p>A number of miRNAs have a confirmed effect on the initiation and progression of HCC. For example, the overexpression of miR-149 suppressed the migration and invasion of HCC by targeting protein phosphatase, Mg<sup>2&#x002B;</sup>/Mn<sup>2&#x002B;</sup> dependent 1F directly (<xref rid="b35-ol-0-0-7892" ref-type="bibr">35</xref>). miR-148a induces hepatocytic differentiation by inhibiting the inhibitor of nuclear factor &#x03BA;&#x03B1;/NUMB/NOTCH pathway (<xref rid="b36-ol-0-0-7892" ref-type="bibr">36</xref>).</p>
<p>miR-33a serves a significant role in fatty acid metabolism and cholesterol synthesis (<xref rid="b37-ol-0-0-7892" ref-type="bibr">37</xref>,<xref rid="b38-ol-0-0-7892" ref-type="bibr">38</xref>), and inhibiting miR-33a has been considered as a method to reduce the risk of cardiovascular disease (<xref rid="b39-ol-0-0-7892" ref-type="bibr">39</xref>). It is suggested that miR-33 may function as a tumor-associated molecule, as miR-33b can inhibit cell growth and induce apoptosis through suppressing the activity of WNT/&#x03B2;-catenin signaling in lung adenocarcinoma cells (<xref rid="b40-ol-0-0-7892" ref-type="bibr">40</xref>), and also inhibit the proliferation and migration of osteosarcoma cells by targeting hypoxia-inducible factor-1&#x03B1; (<xref rid="b41-ol-0-0-7892" ref-type="bibr">41</xref>). With further in-depth study of miR-33a, it was identified that mir-33a can also affect cell proliferation and cell cycle progression in tumors by regulating cyclin-dependent kinase 5, cyclin D1 and Pim-1 (<xref rid="b42-ol-0-0-7892" ref-type="bibr">42</xref>,<xref rid="b43-ol-0-0-7892" ref-type="bibr">43</xref>), inhibit bone metastasis by targeting parathyroid hormone-related protein (<xref rid="b19-ol-0-0-7892" ref-type="bibr">19</xref>), and inhibit cancer cell growth, invasion and metastasis by regulating the expression of high mobility group AT-hook 2 (<xref rid="b44-ol-0-0-7892" ref-type="bibr">44</xref>) and &#x03B2;-catenin (<xref rid="b45-ol-0-0-7892" ref-type="bibr">45</xref>). However, to the best of our knowledge, no report previously existed regarding the role of miR-33a in HCC.</p>
<p>In the present study, HCC and para-carcinoma tissues were examined to determine the prognostic significance of miR-33a expression. Kaplan-Meier survival curve analysis indicated that patients with lower miR-33a expression exhibited significantly poorer survival. miR-33a expression was significantly associated with the number of tumor foci, which is an important clinical determinant of the prognosis of patients with HCC. In a univariate Cox model, it was identified that low miR-33a expression was an independent predictive factor for the OS time of HCC patients. In a multivariate Cox model, it was identified that the presence of multiple foci was associated with the low expression of miR-33a, and the decreased OS and PFS time of patients with HCC.</p>
<p>In summary, the data of the present study revealed that the miR-33a expression level was significantly associated with the number of tumor foci, and the combination of low miR-33a expression with multiple foci number was associated with significantly decreased OS and PFS time. miR-33a may, therefore, promote regional metastasis and serve as a potential prognostic biomarker for HCC in clinical practice. However, further study with a larger cohort is required in order to validate this view.</p>
</sec>
</body>
<back>
<ack>
<title>Acknowledgements</title>
<p>The present study was supported in part by grants from the National Natural Science Foundation of China (81201535, 81302065, 81472202, 81772932, 81472209 and 81702243), Jilin Provincial Science and Technology Department (20140414061GH), Shanghai Natural Science Foundation (12ZR1436000 and 16ZR1428900) and Shanghai Municipal Commission of Health and Family Planning (201440398 and 201540228).</p>
</ack>
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<fig id="f1-ol-0-0-7892" position="float">
<label>Figure 1.</label>
<caption><p>miR-33a expression in normal liver and HCC tissues. (A) miR-33a expression levels in cancer vs. adjacent non-tumor tissue samples (n=36). (B) miR-33a expression levels in paired HCC and adjacent non-tumor tissue samples (n=36). (C) miR-33a expression in tumor samples (n=149) and paired adjacent non-tumor tissue (n=36). miR-33a, microRNA-33a; HCC, hepatocellular carcinoma.</p></caption>
<graphic xlink:href="ol-15-04-4571-g00.tif"/>
</fig>
<fig id="f2-ol-0-0-7892" position="float">
<label>Figure 2.</label>
<caption><p>Analysis of the effect of miR-33a expression and clinical parameters on the survival of patients with HCC. Univariate survival analysis of (A) OS and (B) PFS in HCC, as determined by Kaplan-Meier plots stratified by miRNA-33a expression. Univariate survival analysis of (C) OS and (D) PFS in HCC, as determined by Kaplan-Meier plots stratified by the number of foci. Multivariate analysis of (E) OS and (F) PFS by Kaplan-Meier survival analysis stratified by the number of foci and miRNA-33a expression. miR-33a, microRNA-33a; HCC, hepatocellular carcinoma; OS, overall survival; PFS, progression free survival.</p></caption>
<graphic xlink:href="ol-15-04-4571-g01.tif"/>
</fig>
<table-wrap id="tI-ol-0-0-7892" position="float">
<label>Table I.</label>
<caption><p>The association between miR-33a expression and clinicopathological characteristics in patients with hepatocellular carcinoma.</p></caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th/>
<th/>
<th align="center" valign="bottom" colspan="2">miR-33a expression, n (&#x0025;)</th>
<th/>
</tr>
<tr>
<th/>
<th/>
<th align="center" valign="bottom" colspan="2"><hr/></th>
<th/>
</tr>
<tr>
<th align="left" valign="bottom">Parameters</th>
<th align="center" valign="bottom">Cases, n (&#x0025;)</th>
<th align="center" valign="bottom">Low</th>
<th align="center" valign="bottom">High</th>
<th align="center" valign="bottom">P-value</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="top">Age, years</td>
<td/>
<td/>
<td/>
<td align="center" valign="top">0.211</td>
</tr>
<tr>
<td align="left" valign="top">&#x00A0;&#x00A0;&#x003C;60</td>
<td align="center" valign="top">66 (44.9)</td>
<td align="center" valign="top">29 (19.7)</td>
<td align="center" valign="top">37 (25.2)</td>
<td/>
</tr>
<tr>
<td align="left" valign="top">&#x00A0;&#x00A0;&#x2265;60</td>
<td align="center" valign="top">81 (55.1)</td>
<td align="center" valign="top">44 (29.9)</td>
<td align="center" valign="top">37 (25.2)</td>
<td/>
</tr>
<tr>
<td align="left" valign="top">&#x00A0;&#x00A0;Unknown</td>
<td align="center" valign="top">2</td>
<td/>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="top">Sex</td>
<td/>
<td/>
<td/>
<td align="center" valign="top">0.045</td>
</tr>
<tr>
<td align="left" valign="top">&#x00A0;&#x00A0;Male</td>
<td align="center" valign="top">117 (79.6)</td>
<td align="center" valign="top">63 (42.9)</td>
<td align="center" valign="top">54 (36.7)</td>
<td/>
</tr>
<tr>
<td align="left" valign="top">&#x00A0;&#x00A0;Female</td>
<td align="center" valign="top">30 (20.4)</td>
<td align="center" valign="top">10 (6.8)</td>
<td align="center" valign="top">20 (13.6)</td>
<td/>
</tr>
<tr>
<td align="left" valign="top">&#x00A0;&#x00A0;Unknown</td>
<td align="center" valign="top">2</td>
<td/>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="top">Number of foci</td>
<td/>
<td/>
<td/>
<td align="center" valign="top">0.007</td>
</tr>
<tr>
<td align="left" valign="top">&#x00A0;&#x00A0;Single</td>
<td align="center" valign="top">97 (68.3)</td>
<td align="center" valign="top">39 (27.5)</td>
<td align="center" valign="top">58 (40.8)</td>
<td/>
</tr>
<tr>
<td align="left" valign="top">&#x00A0;&#x00A0;Multiple</td>
<td align="center" valign="top">45 (31.7)</td>
<td align="center" valign="top">29 (20.4)</td>
<td align="center" valign="top">16 (11.3)</td>
<td/>
</tr>
<tr>
<td align="left" valign="top">&#x00A0;&#x00A0;Unknown</td>
<td align="center" valign="top">7</td>
<td/>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="top">Diameter</td>
<td/>
<td/>
<td/>
<td align="center" valign="top">0.078</td>
</tr>
<tr>
<td align="left" valign="top">&#x00A0;&#x00A0;&#x003C;5 cm</td>
<td align="center" valign="top">91 (68.3)</td>
<td align="center" valign="top">40 (27.2)</td>
<td align="center" valign="top">51 (34.7)</td>
<td/>
</tr>
<tr>
<td align="left" valign="top">&#x00A0;&#x00A0;&#x2265;5 cm</td>
<td align="center" valign="top">56 (31.7)</td>
<td align="center" valign="top">33 (22.4)</td>
<td align="center" valign="top">23 (15.6)</td>
<td/>
</tr>
<tr>
<td align="left" valign="top">&#x00A0;&#x00A0;Unknown</td>
<td align="center" valign="top">2</td>
<td/>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="top">Tumor differentiation</td>
<td/>
<td/>
<td/>
<td align="center" valign="top">0.105</td>
</tr>
<tr>
<td align="left" valign="top">&#x00A0;&#x00A0;Poor</td>
<td align="center" valign="top">10 (7.7)</td>
<td align="center" valign="top">7 (5.4)</td>
<td align="center" valign="top">3 (2.3)</td>
<td/>
</tr>
<tr>
<td align="left" valign="top">&#x00A0;&#x00A0;Moderate</td>
<td align="center" valign="top">96 (73.8)</td>
<td align="center" valign="top">51 (39.2)</td>
<td align="center" valign="top">45 (34.6)</td>
<td/>
</tr>
<tr>
<td align="left" valign="top">&#x00A0;&#x00A0;Well</td>
<td align="center" valign="top">24 (18.5)</td>
<td align="center" valign="top">8 (6.2)</td>
<td align="center" valign="top">16 (12.3)</td>
<td/>
</tr>
<tr>
<td align="left" valign="top">&#x00A0;&#x00A0;Unknown</td>
<td align="center" valign="top">19</td>
<td/>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="top">Distant metastasis</td>
<td/>
<td/>
<td/>
<td align="center" valign="top">0.223</td>
</tr>
<tr>
<td align="left" valign="top">&#x00A0;&#x00A0;Absence</td>
<td align="center" valign="top">89 (91.8)</td>
<td align="center" valign="top">26 (26.8)</td>
<td align="center" valign="top">63 (64.9)</td>
<td/>
</tr>
<tr>
<td align="left" valign="top">&#x00A0;&#x00A0;Presence</td>
<td align="center" valign="top">8 (8.2)</td>
<td align="center" valign="top">4 (4.1)</td>
<td align="center" valign="top">4 (4.1)</td>
<td/>
</tr>
<tr>
<td align="left" valign="top">&#x00A0;&#x00A0;Unknown</td>
<td align="center" valign="top">52</td>
<td/>
<td/>
<td/>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn id="tfn1-ol-0-0-7892"><p>miR-33a, microRNA-33a.</p></fn>
</table-wrap-foot>
</table-wrap>
<table-wrap id="tII-ol-0-0-7892" position="float">
<label>Table II.</label>
<caption><p>Cox regression model analysis for OS and PFS based on various clinical characteristics in patients with hepatocellular carcinoma.</p></caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th/>
<th align="center" valign="bottom" colspan="3">Univariate analysis for OS</th>
<th align="center" valign="bottom" colspan="3">Multivariate analysis for OS</th>
<th align="center" valign="bottom" colspan="3">Univariate analysis for PFS</th>
<th align="center" valign="bottom" colspan="3">Multivariate analysis for PFS</th>
</tr>
<tr>
<th/>
<th align="center" valign="bottom" colspan="3"><hr/></th>
<th align="center" valign="bottom" colspan="3"><hr/></th>
<th align="center" valign="bottom" colspan="3"><hr/></th>
<th align="center" valign="bottom" colspan="3"><hr/></th>
</tr>
<tr>
<th align="left" valign="bottom">Factor</th>
<th align="center" valign="bottom">HR</th>
<th align="center" valign="bottom">95&#x0025; CI</th>
<th align="center" valign="bottom">P-value</th>
<th align="center" valign="bottom">HR</th>
<th align="center" valign="bottom">95&#x0025; CI</th>
<th align="center" valign="bottom">P-value</th>
<th align="center" valign="bottom">HR</th>
<th align="center" valign="bottom">95&#x0025; CI</th>
<th align="center" valign="bottom">P-value</th>
<th align="center" valign="bottom">HR</th>
<th align="center" valign="bottom">95&#x0025; CI</th>
<th align="center" valign="bottom">P-value</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="top">Age</td>
<td align="center" valign="top">1.193</td>
<td align="center" valign="top">0.709&#x2013;2.009</td>
<td align="center" valign="top">0.507</td>
<td/>
<td/>
<td/>
<td align="center" valign="top">1.062</td>
<td align="center" valign="top">0.692&#x2013;1.655</td>
<td align="center" valign="top">0.979</td>
<td/>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="top">Sex</td>
<td align="center" valign="top">0.493</td>
<td align="center" valign="top">0.225&#x2013;1.084</td>
<td align="center" valign="top">0.079</td>
<td/>
<td/>
<td/>
<td align="center" valign="top">0.609</td>
<td align="center" valign="top">0.330&#x2013;1.124</td>
<td align="center" valign="top">0.113</td>
<td/>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="top">Number of foci</td>
<td align="center" valign="top">1.995</td>
<td align="center" valign="top">1.208&#x2013;3.293</td>
<td align="center" valign="top">0.007</td>
<td align="center" valign="top">16.665</td>
<td align="center" valign="top">6.330&#x2013;43.873</td>
<td align="center" valign="top">&#x003C;0.001</td>
<td align="center" valign="top">1.634</td>
<td align="center" valign="top">1.040&#x2013;2.569</td>
<td align="center" valign="top">0.033</td>
<td align="center" valign="top">5.589</td>
<td align="center" valign="top">2.975&#x2013;10.503</td>
<td align="center" valign="top">&#x003C;0.001</td>
</tr>
<tr>
<td align="left" valign="top">Diameter</td>
<td align="center" valign="top">1.945</td>
<td align="center" valign="top">1.170&#x2013;3.246</td>
<td align="center" valign="top">0.011</td>
<td/>
<td/>
<td/>
<td align="center" valign="top">1.549</td>
<td align="center" valign="top">0.991&#x2013;2.419</td>
<td align="center" valign="top">0.055</td>
<td/>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="top">Tumor differentiation</td>
<td align="center" valign="top">0.471</td>
<td align="center" valign="top">0.262&#x2013;0.842</td>
<td align="center" valign="top">0.011</td>
<td/>
<td/>
<td/>
<td align="center" valign="top">0.512</td>
<td align="center" valign="top">0.308&#x2013;0.851</td>
<td align="center" valign="top">0.011</td>
<td/>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="top">Distant metastasis</td>
<td align="center" valign="top">3.468</td>
<td align="center" valign="top">1.130&#x2013;10.644</td>
<td align="center" valign="top">0.032</td>
<td/>
<td/>
<td/>
<td align="center" valign="top">4.879</td>
<td align="center" valign="top">2.199&#x2013;10.825</td>
<td align="center" valign="top">&#x003C;0.001</td>
<td/>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="top">miR-33a expression</td>
<td align="center" valign="top">0.072</td>
<td align="center" valign="top">0.033&#x2013;0.159</td>
<td align="center" valign="top">&#x003C;0.001</td>
<td/>
<td/>
<td/>
<td align="center" valign="top">0.194</td>
<td align="center" valign="top">0.118&#x2013;0.317</td>
<td align="center" valign="top">&#x003C;0.001</td>
<td/>
<td/>
<td/>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn id="tfn2-ol-0-0-7892"><p>OS, overall survival; PFS, progression free survival; HR, hazard regression; CI, confidence interval.</p></fn>
</table-wrap-foot>
</table-wrap>
</floats-group>
</article>
