MiRNA as a Diagnostic and Prognostic Biomarker of Hepatocellular Carcinoma

Background:

Hepatocellular carcinoma (HCC) is the sixth most common cancer and the third mortality rate of cancer in the world (Kamangar et al., 2006). Treatments of hepatocellular carcinoma include surgical resection, local therapies such as radiofrequency ablation (RFA) and percutaneous ethanol injection (PEI), transarterial chemoembolization (TACE), and best supportive care(Bruix and Sherman, 2005). For patients who are not candidates for surgical intervention or local therapies, sorafenib is recommended (Cheng et al., 2009; Llovet et al., 2008). However, even after successful treatment such as surgical resection, most patients suffered from recurrence or progression of the tumor (Bruix and Sherman, 2005; Llovet et al., 2002; Llovet et al., 2008). Though there are several staging systems of HCC have been developed, such as the Okuda staging system, AJCC system, BCLC staging system, and CLIP scoring system, the prognostic value of each staging systems are not consistent(Chen et al., 2009), and applicability of each staging system depends on the treatment methodology selected.

Because of the shortcoming of clinical staging systems in predicting the outcome of HCC, it is of great interest to search serum biomarkers to predict the prognosis HCC (Fujiyama et al., 2002; Marrero and Lok, 2004). Among them, alpha-fetoprotein (AFP) is the mostly well-studied. AFP has been used as a marker in diagnosing HCC (Bruix et al., 2001) and as a prognostic factor for newly diagnosed HCC(1998). AFP is also of value as a predictive factor for chemotherapy response (Chan et al., 2009). However, the applicability of AFP for HCC after surgical resection of tumor or after local therapy is still uncertain. For patients with HCC and normal serum level of AFP, APF could not be used a prognostic factor. Other biomarkers, such as glipecan-3, are still under development (Marrero and Lok, 2004).

MicroRNAs (miRNAs), 17- to 25-nucleotide non-coding RNAs, are frequently dysregulated in cancer and emerging as novel non-invasive biomarker for cancer screening, diagnosis, monitor therapy efficacy and predict prognosis (Wu et al., 2007). MiRNAs are stably expression in serum as their resistance to endogenous RNase and easily storage with high stability (Aref et al., 2014). Several studies have shown abnormal expression of human serum miRNAs in many cancers such as liver, colorectal, and pancreatic cancer (Huang et al., 2010; Liu et al., 2012; Qi et al., 2013). The sensitivity of miRNA as a diagnostic biomarker of HCC could be up to 80% (Yin et al., 2014). Using miRNA arrays can generate miRNA signatures and further improve the sensitivity and specificity of biomarker for tumor diagnosis and prognosis prediction.

Trial purpose：

1. To identify serum miRNA as a diagnosis or prediction biomarker for HCC.
2. To correlate with the expression level of miRNA between serum, HCC tumor tissue and adjacent non-tumor tissue.
3. To collect and store deoxyribonucleic acid (DNA) for future exploratory research into genes/genetic variation that may influence response to treatment in HCC.
4. To collect and store surplus plasma and tumor tissues for future exploratory research into proteins/genes/genetic variation that may influence response to treatment in HCCs.

Methods： Study design This is a prospective study. All patients need to provide informed consents. A total of 200 patients aged >20 year-old who are diagnosed HCC in the National Taiwan University and Far-Eastern Memorial Hospital will be enrolled. The diagnostic criteria of HCC are according to 2011 AASLD criteria (Bruix et al., 2011). In brief, nodules more than 1 cm found on ultrasound screening of a cirrhotic liver should be investigated further with one dynamic studies, either CT scan or contrast MRI. If the appearance is typical of HCC (i.e., hypervascular with washout in the portal/venous phase) in one technique, the lesion would be diagnosed as HCC. If the findings are not characteristic or the vascular profile is not coincidental among techniques the lesion should be biopsied. For clinical staging, two staging systems will be applied to these patients, including BCLC staging and clinical TNM system. The clinicopathological data will be collected prospectively. Clinical outcomes, including treatment toxicity, treatment response as defined by the revised RECIST criteria, disease-progression, and overall survival will be recorded.

Specimen and serum collection Blood samples will be collected at 3 time points-pre-treatment, 7 days after treatment and one month after treatment. Blood samples will be separated in plasma and mononuclear cells upon collection and will be stored in -20Ç before further use. The treatment methods include operation, TACE, RFA, PEI, or anti-angiogenesis agent including sorafenib use.

Tissue collection The HCC tissues (T) and the corresponding non-tumor liver tissues (NT) will be obtained. The surgical specimens will be frozen immediately after surgery and stored in -140°C.

Viral marker Hepatitis B surface antigen (HBsAg) and antibody to HCV (anti-HCV) will be checked using commercially available enzyme linked immunosorbant assay kits for every patient. For HBsAg positive patient, HBeAg and anti-HBe will be measured by enzyme linked immunosorbant assay. Serum level of HBV DNA will be measured by in house TaqMan real-time polymerase chain reaction (PCR). For anti-HCV positive patients, HCV RNA will be measured by in house TaqMan real-time PCR

RNA isolation, reverse transcription and miRNA array Blood samples drawn into EDTA containing tubes and centrifuged at 4,000x g for 15 min for plasma separation. Plasma transferred into a clean micro centrifuge tube and centrifuged again at 12,000x g for 5 min and 200 ul of plasma will be transferred to a new micro centrifuge tube and stored at -80 _C until analysis. RNA will isolated using High Pure miRNA Isolation Kit (Roche, Mannheim, Germany) according to the manufacturer's instructions and then stored at -80 _C until the experiment.

Reverse transcription reaction For miRNA analyses by quantitative real-time polymerase chain reaction (qRT-PCR), 100 ng of total RNA will be reverse-transcribed using the TaqMan miRNA Reverse Transcription Kit (Applied Biosystems, Carlsbad, CA, USA). All reactions will be performed as specified in the manufacturers protocol.

TaqMan low-density arrays TLDA will be analysed to identify the profile of differentially expressed miRNAs between the three sets of samples (pre-treatment, 7 days post-treatment, one month post treatment). In brief, total RNA will reverse-transcribed into cDNA by the TaqMan MicroRNA Reverse Transcription Kit and Megaplex RT set pool A and B version 3.0 (Applied Biosystems). The RT product will loaded into TaqMan Array Human MicroRNA A+B Cards Set v3.0 (Applied Biosystems), enabling simultaneous quantitation of 667 human miRNAs. TaqMan microRNA assays and analysis will be performed on the ABI 7900HT Instrument (Applied Biosystems). All reactions were performed according to the standard manufacturers' protocols. Quantitative miRNA expression data were acquired and normalized using ABI 7900HT SDS software (Applied Biosystems).

Quantitative Real-Time PCR (qRT-PCR) Expression of miRNA detected via TaqMan low-density arrays will also be studied as well in the HCC tumors and / or their paired normal liver tissue by qRT-PCR analysis as described previously (Lee et al., 2011). RNU6B snRNA was used as an endogenous control. Each microRNA assay was performed in triplicate. Expression of microRNAs was reported as delta Ct value (Ct value of RNU6B - Ct value of target microRNA). The investigators defined the groups of tumors or cells with high or low expression based on the median expression value of each microRNA.

Statistical analysis Overall survival and progression-free survival will be evaluated using Kaplan-Meier's method. Once a specific protein is identified by the proteomic study, patients will be divided into high expression group and low expression group, according to the median plasma expression level of the miRNA of all patients; survival difference between high expression group and low expression group will be analyzed using log-rank test. p-value less than 0.05 will be regarded as significant.