Identification of Potential Prognostic Biomarkers for Sorafenib Efficacy in Hepatocellular Carcinoma Cells by Proteomic Approaches

• Main Authors: Ming Jiun Tsai, 蔡銘駿
• Other Authors: Lu-Ping Chow
• Format: Others
• Language: zh-TW
• Published: 2017
• Online Access: http://ndltd.ncl.edu.tw/handle/uxbqfs

碩士 === 國立臺灣大學 === 生物化學暨分子生物學研究所 === 105 === Hepatocellular carcinoma, HCC, is the most common liver cancer in the world. Clinically, there are many biomarkers which can be used to diagnose HCC and predict prognosis. According to the Barcelona-clinic liver cancer staging (BCLC staging), sorafenib is the only anticancer drug with proven prognostic efficacy for treatment of HCC. Sorafenib is a multi-kinase inhibitor and inhibits the MAPK pathway by inhibiting Raf. Because sorafenib is the only approved drug for advanced HCC and exhibits relatively mild adverse effect, biomarkers which can be used to predict sorafenib efficacy can assist in identifying the patients who are likely to benefit from the treatment. Many studies have attempted to investigate biomarkers of sorafenib efficacy by analyzing the associations between potential markers and patients’ outcomes. However, there are no appropriate biomarkers can be used to estimate prognosis. Therefore, it is necessary to find biomarkers which can be used to predict the prognosis of HCC patients after sorafenib treatment. We applied the quantitative proteomics method (Stable Isotope Labeling of Amino acids in Culture, SILAC) to analyze the differences of secretory and cytosolic proteins levels between HuH-7 and sorafenib-treated HuH-7 cells. We further used the LC MS/MS approach to identify the above proteins. The Ingenuity Pathway Analysis (IPA) was performed to analyze the difference of functions between secretory and cytosolic proteins of HuH-7 and sorafenib-treated HuH-7 cells. According to our results, we identified 2611 proteins in cell lysate and 1022 proteins in conditioned medium of sorafenib-treated HuH-7 cells. Of these proteins, there are 1091 and 145 proteins down-regulated in cell lysate and conditioned medium respectively after sorafenib treatment. Furthermore, we analyzed these two groups by bioinformatics software, TMHMM, SecretomeP and SignalP, and totally 103 proteins were classified as the secretory proteins. These proteins were found to be relating to apoptosis, proliferation, angiogenesis and cancer. In which, we selected four candidates, CTGF, Galectin-3, Glypican-3 and HMGB1, which may be potential biomarkers for predicting prognosis of HCC patients after sorafenib treatment. We validated these potential biomarkers by western blot in vitro and immunohistochemistry in vivo and found that the expressions of these four proteins are inhibited by sorafenib. In addition, the tumor volume was also decreased in vivo after sorafenib treatment. We further studied the involved cell signaling of these potential biomarkers with several inhibitors and found that these four proteins are regulated by MAPK/ERK pathway. Moreover, proliferation was also inhibited in GPC3-knowdown HuH-7 cells. In conclusion, we found that these four proteins are potential biomarkers for predicting prognosis of HCC patients after sorafenib treatment. It is expected to make these potential biomarkers be valuable in clinical use.