揭示橙皮素和大黄素作为联合治疗抑制胰腺癌C-Met基因进展的潜在作用。

IF 1 4区 生物学 Q4 BIOCHEMISTRY & MOLECULAR BIOLOGY
Rangaraj Kaviyaprabha, Thandaserry Vasudevan Miji, Puthupparambil Shaji Sreelakshmi, Sridhar Muthusami, Palanisamy Arulselvan, Muruganantham Bharathi
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引用次数: 0

摘要

背景:胰腺腺癌(PAAD)是最常见的癌症之一,死亡率高。只有10%的PAAD患者能活到5年。因此,应进一步提高患者的生存率。目的:本研究采用计算方法鉴定PAAD中新的生物标志物和潜在有效的小药物样分子。目的:本研究旨在鉴定胰腺癌的差异表达基因(differential expression Genes, DEGs)和影响生存率的基因(survival - impact Genes, SDEGs),以筛选出胰腺癌的特异性基因,并预测与橙皮素和大黄素相互作用的疗效。此外,另一个目标是使用MTT试验验证预测的疗效。方法:采用GEPIA2数据库对TCGA-PAAD数据集进行分析,鉴定deg和sdeg。Venn确定了deg和sdeg之间常见的分散基因。使用Network Analyst v3.0、CytoScape v3.10.1和cytoHubba构建PPI网络,hub基因鉴定被描述为靶蛋白。利用PDB和PubChem以SDF格式获得目标蛋白和13种植物化合物的PDB结构。利用Autodock vina和Discovery Studio Visualizer v19.1.0.1828进行分子对接研究并进行可视化。用橙皮素和大黄素处理MiaPaCa-2细胞株,测定其细胞毒性。结果:从TCGA-PAAD数据集中共鉴定出9219个差异表达基因(DEGs)。其中上调8740个、下调479个基因,差异均有统计学意义(P≤0.05)。可能筛选出500个PAAD患者中最影响生存率的基因(sdeg), P≤0.05有统计学意义。在获得的deg和sdeg之间鉴定出共有137个基因。对预测的137个常见基因绘制了生存热图。96个基因被确定为最危险的基因(以红色突出显示)。然后利用蛋白-蛋白相互作用(protein-protein interaction, PPI)对96个最危险基因构建网络。从构建的PPI网络中,鉴定出相互作用较高的前10个基因。通过生存分析鉴定出最危险的基因,发现所有鉴定出的基因都显著降低了PAAD患者的生存率。从中选择影响高生存率的5个基因CDK1、CENPE、NCAPG、KIF20A、c-MET进行进一步分析。对鉴定出的前5个基因进行了分子对接研究,并与13种植物化合物进行了抗癌活性研究。分子对接分析表明,橙皮苷的结合亲和力(BA) = -8.0 kcal/mol;均方根偏差(RMSD) = 2.012 Å)和大黄素(BA = -8.6 kcal/mol;RMSD = 1.605 Å)根据氢键数和BA与c-MET相互作用良好。因此,在MiaPaCa-2细胞株上验证了橙皮素、大黄素、橙皮素:大黄素联合使用的协同作用,IC50值分别为171.3 μM、72.94 μM、92.36 μM。结论:大黄素能显著降低MiaPaCa-2胰腺细胞的增殖速率,与橙皮素无协同作用。然而,大黄素提高了橙皮素在胰腺细胞中的作用,这表明两种化合物通过药代动力学偶联进行结构修饰可能有助于未来发现治疗胰腺癌的新化合物。然而,需要进一步的胰腺细胞系,如Panc-1、Bx- PC-3等,以及包括CDX和PDX在内的体内模型来验证橙皮素和大黄素对胰腺细胞的联合作用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Unveiling the Potential Role of Hesperetin and Emodin as a Combination Therapy to Inhibit the Pancreatic Cancer Progression against the C-Met Gene.

Background: Pancreatic adenocarcinoma (PAAD) is one of the most prevalent cancers, and it has high death rates. Only 10% of PAAD patients can survive until 5 years. Hence, the improvement of survival rate of the patients should be improved.

Aim: The present study used a computational approach to identify novel biomarkers and potentially effective small drug-like molecules in PAAD.

Objective: The objective of this study was to identify the Differentially Expressed Genes (DEGs) and survival rate affecting genes (SDEGs) to single out the specific gene responsible for pancreatic cancer and predict the efficacy of interactions with hesperetin and emodin. Further, another objective was to validate the predicted efficacies using an MTT assay.

Methods: The GEPIA2 database was used to analyze the TCGA-PAAD dataset and identify DEGs and SDEGs. Venn identified the commonly scattered genes between the DEGs and SDEGs. Network Analyst v3.0, CytoScape v3.10.1, and cytoHubba were used for PPI network construction and hub genes identification was described as target proteins. The PDB and PubChem were utilized to obtain the PDB structure of the target proteins and 13 phytocompounds in SDF format. Molecular docking studies were carried out and visualized by utilizing Autodock vina and Discovery Studio Visualizer v19.1.0.1828. The cytotoxicity was measured in the MiaPaCa-2 cell line after being treated with hesperetin and emodin.

Results: A total of 9219 Differentially Expressed Genes (DEGs) from the TCGA-PAAD dataset were identified. Among them, 8740 and 479 genes were up and down-regulated with the statistical significance of P ≤ 0.05, respectively. Likely, 500 most survival rate affecting genes (SDEGs) in PAAD patients with a statistical significance of P ≤ 0.05 were identified. The common 137 genes were identified between these obtained DEGs and SDEGs. The survival heat map was delineated for the predicted 137 common genes. Ninety-six genes were identified as the most hazardous genes (highlighted in red). After that, the network was constructed by using protein-protein interaction (PPI) for the most hazardous 96 genes. From the constructed PPI network, the highly interacted top 10 genes were identified. The survival analysis was carried out to identify the most hazardous genes and revealed that all the identified genes significantly reduced the survival rate of the patients affected by PAAD. From that, high survival affecting 5 genes, such as CDK1, CENPE, NCAPG, KIF20A, and c-MET, were selected for further analysis. The molecular docking studies were carried out for the identified top 5 genes, with the 13 phytocompounds reviewed previously for anti-cancer activity. The molecular docking analysis revealed that the hesperetin (binding affinity (BA) = -8.0 kcal/mol; Root mean square deviation (RMSD) = 2.012 Å) and emodin (BA = -8.6 kcal/mol; RMSD = 1.605 Å) interacted well with the c-MET based on the number of hydrogen bonds and BA. Hence, the synergistic efficacy was validated in the cell line MiaPaCa-2 with the hesperetin, emodin, and hesperetin: emodin in combination and obtained the IC50 values of 171.3 μM, 72.94 μM, and 92.36 μM respectively.

Conclusion: The results stated that emodin significantly reduced the cell proliferation rate of the MiaPaCa-2 pancreatic cells, and no synergistic effects were observed in this context with hesperetin. However, emodin improved the hesperetin efficacy in pancreatic cells, indicating that structural modification through pharmacokinetics by coupling these two compounds may help to identify novel compounds to treat pancreatic cancer in the future. However, further pancreatic cell lines, such as Panc-1, Bx- PC-3, etc., and in vivo models that include CDX and PDX are needed to verify the combination effect of hespertin and emodin on pancreatic cells.

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来源期刊
Protein and Peptide Letters
Protein and Peptide Letters 生物-生化与分子生物学
CiteScore
2.90
自引率
0.00%
发文量
98
审稿时长
2 months
期刊介绍: Protein & Peptide Letters publishes letters, original research papers, mini-reviews and guest edited issues in all important aspects of protein and peptide research, including structural studies, advances in recombinant expression, function, synthesis, enzymology, immunology, molecular modeling, and drug design. Manuscripts must have a significant element of novelty, timeliness and urgency that merit rapid publication. Reports of crystallization and preliminary structure determination of biologically important proteins are considered only if they include significant new approaches or deal with proteins of immediate importance, and preliminary structure determinations of biologically important proteins. Purely theoretical/review papers should provide new insight into the principles of protein/peptide structure and function. Manuscripts describing computational work should include some experimental data to provide confirmation of the results of calculations. Protein & Peptide Letters focuses on: Structure Studies Advances in Recombinant Expression Drug Design Chemical Synthesis Function Pharmacology Enzymology Conformational Analysis Immunology Biotechnology Protein Engineering Protein Folding Sequencing Molecular Recognition Purification and Analysis
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