Browsing by Author "Chuang, Cheng-Hsun"

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A panel of eight microRNAs is a good predictive parameter for triple-negative breast cancer relapse
(2020-01-01)
Hong, Hsiao-Chin
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Chuang, Cheng-Hsun
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Huang, Wei-Chih
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Weng, Shun-Long
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Chen, Chia-Hung
Rationale: Triple-negative breast cancer (TNBC), which has the highest recurrence rate and shortest survival time of all breast cancers, is in urgent need of a risk assessment method to determine an accurate treatment course. Recently, miRNA expression patterns have been identified as potential biomarkers for diagnosis, prognosis, and personalized therapy. Here, we investigate a combination of candidate miRNAs as a clinically applicable signature that can precisely predict relapse in TNBC patients after surgery. Methods: Four total cohorts of training (TCGA_TNBC and GEOD-40525) and validation (GSE40049 and GSE19783) datasets were analyzed with logistic regression and Gaussian mixture analyses. We established a miRNA signature risk model and identified an 8-miRNA signature for the prediction of TNBC relapse. Results: The miRNA signature risk model identified ten candidate miRNAs in the training set. By combining 8 of the 10 miRNAs (miR-139-5p, miR-10b-5p, miR-486-5p, miR-455-3p, miR-107, miR-146b-5p, miR-324-5p and miR-20a-5p), an accurate predictive model of relapse in TNBC patients was established and was highly correlated with prognosis (AUC of 0.80). Subsequently, this 8-miRNA signature prognosticated relapse in the two validation sets with AUCs of 0.89 and 0.90. Conclusion: The 8-miRNA signature predictive model may help clinicians provide a prognosis for TNBC patients with a high risk of recurrence after surgery and provide further personalized treatment to decrease the chance of relapse.
Blockade of ITGA2 Induces Apoptosis and Inhibits Cell Migration in Gastric Cancer
(2018-05-01)
Chuang, Yu-Chang
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Wu, Hsin-Yi
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Lin, Yu-Ling
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Tzou, Shey-Cherng
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Chuang, Cheng-Hsun
Background: Gastric cancer is currently the fourth leading cause of cancer-related death worldwide. Gastric cancer is often diagnosed at advanced stages and the outcome of the treatment is often poor. Therefore, identifying new therapeutic targets for this cancer is urgently needed. Integrin alpha 2 (ITGA2) subunit and the beta 1 subunit form a heterodimer for a transmembrane receptor for extracellular matrix, is an important molecule involved in tumor cell proliferation, survival and migration. Integrin alpha 2 beta 1 is over-expressed on a variety of cancer cells, but is low or absent in most normal organs and resting endothelial cells. Results: In this report, we assessed the ITGA2 as the potential therapeutic target with the bioinformatics tools from the TCGA dataset in which composed of 375 gastric cancer tissues and 32 gastric normal tissues. According to the information from the Cancer Cell Line Encyclopedia (CCLE) database, the AGS cell line with ITGA2 high expression and the SUN-1 cell line with low expression were chosen for the further investigation. Interestingly, the anti-ITGA2 antibody (at 3 mu g/ml) inhibited approximately 50% survival of the AGS cells (over-expressed ITGA2), but had no effect in SNU-1 cells (ITGA2 negative). The extents of antibody-mediated cancer inhibition positively correlated with the expression levels of the ITGA2. We further showed that the anti-ITGA2 antibody induced apoptosis by upregulating the RhoA-p38 MAPK signaling to promote the expressions of Bim, Apaf-1 and Caspase-9, whereas the expressions of Ras and Bax/Bcl-2 were not affected. Moreover, blocking ITGA2 by the specific antibody at lower doses also inhibited cell migration of gastric cancer cells. Blockade of ITGA2 by a specific antibody down-regulated the expression of N-WASP, PAK and LIMK to impede actin organization and cell migration of gastric cancer cells. Conclusions: Here, we showed that the mRNA expression levels of ITGA2 comparing to normal tissues significantly increased. In addition, the results revealed that targeting integrin alpha 2 subunit by antibodies did not only inhibit cell migration, but also induce apoptosis effect on gastric cancer cells. Interestingly, higher expression level of ITGA2 led to significant effects on apoptosis progression during anti-ITGA2 antibody treatment, which indicated that ITGA2 expression levels directly correlate with their functionality. Our findings suggest that ITGA2 is a potential therapeutic target for gastric cancer.
Development of a computational promoter with highly efficient expression in tumors
(2018-04-27)
Ho, Shu-Yi
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Chang, Bo-Hau
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Chung, Chen-Han
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Lin, Yu-Ling
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Chuang, Cheng-Hsun
Background: Gene therapy is a potent method to increase the therapeutic efficacy against cancer. However, a gene that is specifically expressed in the tumor area has not been identified. In addition, nonspecific expression of therapeutic genes in normal tissues may cause side effects that can harm the patients' health. Certain promoters have been reported to drive therapeutic gene expression specifically in cancer cells; however, low expression levels of the target gene are a problem for providing good therapeutic efficacy. Therefore, a specific and highly expressive promoter is needed for cancer gene therapy. Methods: Bioinformatics approaches were utilized to analyze transcription factors (TFs) from high-throughput data. Reverse transcription polymerase chain reaction, western blotting and cell transfection were applied for the measurement of mRNA, protein expression and activity. C57BL/6JNarl mice were injected with pD5-hrGFP to evaluate the expression of TFs. Results: We analyzed bioinformatics data and identified three TFs, nuclear factor kappa-light-chain-enhancer of activated B cells (NF-kappa B), cyclic AMP response element binding protein (CREB), and hypoxia-inducible factor-1 alpha (HIF-1 alpha), that are highly active in tumor cells. Here, we constructed a novel mini-promoter, D5, that is composed of the binding sites of the three TFs. The results show that the D5 promoter specifically drives therapeutic gene expression in tumor tissues and that the strength of the D5 promoter is directly proportional to tumor size. Conclusions: Our results show that bioinformatics may be a good tool for the selection of appropriate TFs and for the design of specific mini-promoters to improve cancer gene therapy.
Lipoplex-based targeted gene therapy for the suppression of tumours with VEGFR expression by producing anti-angiogenic molecules
(2020-04-09)
Ho, Shu-Yi
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Chen, Pin-Rong
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Chen, Chia-Hung
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Tsai, Nu-Man
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Lin, Yu-Hsin
Background The anti-angiogenic fusion protein RBDV-IgG1 Fc (RBDV), which comprises the receptor-binding domain of vascular endothelial growth factor-A (VEGF-A), has shown antitumour effects by reducing angiogenesis in vivo. This study used the cationic lipoplex lipo-PEG-PEI-complex (LPPC) to simultaneously encapsulate both the RBDV targeting protein and the RBDV plasmid (pRBDV) without covalent bonds to assess VEGFR targeting gene therapy in mice with melanoma in vivo. Results LPPC protected the therapeutic transgene from degradation by DNase, and the LPPC/RBDV complexes could specifically target VEGFR-positive B16-F10 cells both in vitro and in vivo. With or without RBDV protein-targeting direction, the pRBDV-expressing RBDV proteins were expressed and reached a maximal concentration on the 7th day in the sera after transfection in vivo and significantly elicited growth suppression against B16-F10 melanoma but not IgG1 control proteins. In particular, LPPC/pRBDV/RBDV treatment with the targeting molecules dramatically inhibited B16-F10 tumour growth in vivo to provide better therapeutic efficacy than the treatments with gene therapy with IgG1 protein targeting or administration of a protein drug with RBDV. Conclusions The simultaneous combination of the LPPC complex with pRBDV gene therapy and RBDV protein targeting might be a potential tool to conveniently administer targeted gene therapy for cancer therapy.
miRTarBase update 2018: a resource for experimentally validated microRNA-target interactions
(2018-01-04)
Chou, Chih-Hung
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Shrestha, Sirjana
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Yang, Chi-Dung
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Chang, Nai-Wen
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Lin, Yu-Ling
MicroRNAs (miRNAs) are small non-coding RNAs of similar to 22 nucleotides that are involved in negative regulation of mRNA at the post-transcriptional level. Previously, we developed miRTarBase which provides information about experimentally validated miRNA-target interactions (MTIs). Here, we describe an updated database containing 422 517 curated MTIs from 4076 miRNAs and 23 054 target genes collected from over 8500 articles. The number of MTIs curated by strong evidence has increased similar to 1.4-fold since the last update in 2016. In this updated version, target sites validated by reporter assay that are available in the literature can be downloaded. The target site sequence can extract new features for analysis via a machine learning approach which can help to evaluate the performance of miRNA-target prediction tools. Furthermore, different ways of browsing enhance user browsing specific MTIs. With these improvements, miRTarBase serves as more comprehensively annotated, experimentally validated miRNA-target interactions databases in the field of miRNA related research. miRTarBase is available at http://miRTarBase.mbc.nctu.edu.tw/.