Biosensors-Basel
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2022
·Vol. 12
·期 3
·162
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IF 5.743
Yitao Liang,Bin Zhang,Zexin Xue,Xuesong Ye,Bo Liang
Aberrations of genomic DNA methylation have been confirmed to be involved in the evolution of human cancer and have thus gained the potential to be depicted as biomarkers for cancer diagnostics and prognostic predictions, which implicates an urgent need for detection of total genomic DNA methylation. In this work, we suggested an assay for the quantification of global DNA methylation, utilizing methylation specific antibody (5mC) modified magnetic beads (MBs) for immunorecognition and affinity enrichment. Subsequently, the captured DNA on the surface of MBs interacted with the glucose oxidase-conjugated DNA antibody whose catalytic reaction product was engaged in electrochemical detection of the overall level of DNA methylation on a PB-doped screen-printed electrode. With 15 pg of input DNA, which, to our best knowledge, is the lowest required amount of DNA without sodium bisulfite treatment or amplification, this test strategy was able to perceive as low as 5% methylation level within 70 min including the preparation of anti-5mC-MBs. We believe this detection technique offers a promising option to detect global DNA methylation in both academic and clinical scenarios.Keywords:DNA methylation;magnetic beads;screen printed electrode;electrochemical
研究领域:
生物化学
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生物技术
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癌症研究
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分析化学
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DOI
PubMed
高影响因子
MedComm
·
2025
·Vol. 6
·期 8
·e70303
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IF 10.7
Jun Liu,Yi Yu,Qiqi Lu,Shan-Qiang Zhang,Ji-Cheng Li
Metabolic disorders play a crucial role in the occurrence of acute myocardial infarction (AMI). The objective of this research was to elucidate the characteristic metabolic profile of AMI and provide potential biomarkers for AMI. This study employed a targeted metabolomics approach utilizing the Ultra Performance Liquid Chromatography Tandem Mass Spectrometry (UPLC-MS/MS) system to identify both hydrophilic and hydrophobic metabolites present in plasma samples. Among 1498 detected metabolites, 78 were the most significantly expressed in the AMI group. Functional synergy analysis showed prominent enrichment in the pathways of steroid hormone biosynthesis, biosynthesis of unsaturated fatty acids, bile secretion, and ABC transporters. The metabolites 2-Hydroxy-6-Aminopurine, 17α-Hydroxyprogesterone, and S -(methyl) glutathione have been identified as potential metabolic biomarkers linked to the pathogenesis of AMI. The diagnostic model that integrates these three metabolites exhibited exceptional performance in both the discovery and validation cohorts, attaining an area under the curve (AUC) value greater than 0.9. In addition, based on the follow-up data, we also found that the three metabolites were potential predictive biomarkers for poor prognosis of AMI. This study delineated the characteristic metabolic profile of AMI and assessed the value of metabolic molecules in the diagnosis and prognosis of AMI. This may provide insights for understanding the AMI occurrence and progression.
研究领域:
心血管病学
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代谢组学
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分子医学
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临床生物化学
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转化医学
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疾病 biomarker 研究
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DOI
PubMed
高影响因子
JOURNAL OF NANOBIOTECHNOLOGY
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2024
·Vol. 22
·期 1
·1-21
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IF 10.6
Fei Yao,Cao Danping,Li Yanna,Wang Zhixiong,Dong Runyu,Zhu Menglin,Gao Peng,Wang Xiaoming,Cai Juan,Zuo Xueliang
Introduction Cisplatin-based chemotherapy is one of the fundamental therapeutic modalities for gastric cancer (GC). Chemoresistance to cisplatin is a great clinical challenge, and its underlying mechanisms remain poorly understood. Circular RNAs (circRNAs) are involved in the pathophysiology of multiple human malignancies. Methods High-throughput sequencing was performed to determine the differentially expressed profile of circRNA in GC tissues and cisplatin-resistant GC cells. Quantitative real-time polymerase chain reaction and Fluorescence in situ hybridization was utilized to confirm the dysregulation of circ_0008315 in GC tissues. To evaluate the prognostic significance of circ_0008315 in GC, we used Kaplan-Meier plot. The self-renewal ability of drug-resistant GC cell was verified through tumor sphere formation assay. GC organoids were constructed to simulate the tumor microenvironment and verified the function of circ_0008315 in cisplatin resistance of gastric cancer. In vivo evaluation was conducted using patient-derived xenograft models. Dual-luciferase reporter gene, RNA immunoprecipitation and miRNA pull-down assays were employed to investigate the molecular mechanisms of circ_0008315 in GC. Results We revealed that a novel circRNA hsa_circ_0008315 was upregulated in GC and cisplatin-resistant GC cells. Elevated circ_0008315 was also observed in cisplatin-resistant GC organoid model. High circ_0008315 expression predicted unfavorable survival outcome in GC patients. Downregulation of circ_0008315 expression inhibited proliferation, mobility, and epithelial-mesenchymal transition of GC cells in vitro and in vivo. Reducing circ_0008315 expression in cisplatin-resistant GC organoid model reversed cisplatin resistance. Mechanistically, circ_0008315 modulated the stem cell properties of GC through the miR-3666/CPEB4 signaling pathway, thereby promoting cisplatin resistance and GC malignant progression. Furthermore, we developed PLGA-PEG nanoparticles targeting circ_0008315, and the nanoparticles could effectively inhibit GC proliferation and cisplatin resistance. Conclusion Circ_0008315 exacerbates GC progression and cisplatin resistance, and can be used as a prognostic predictor. Circ_0008315 may function as a promising nanotherapeutic target for GC treatment. Graphical Abstract
研究领域:
肿瘤学
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分子生物学
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药理学
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纳米技术
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DOI
PubMed
高影响因子
Frontiers in Oncology
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2021
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IF 6.244
Xu Guoqiang,Yang Mei,Wang Qiaoli,Zhao Liufang,Zhu Sijin,Zhu Lixiu,Xu Tianrui,Cao Ruixue,Li Cheng,Liu Qiuyan,Xiong Wei,Su Yan,Dong Jian
Introduction: Colorectal cancer (CRC) is the most common gastrointestinal cancer and has a low overall survival rate. Tumor–node–metastasis staging alone is insufficient to predict patient prognosis. Autophagy and long noncoding RNAs play important roles in regulating the biological behavior of CRC. Therefore, establishing an autophagy-related lncRNA (ARlncRNA)-based bioinformatics model is important for predicting survival and facilitating clinical treatment.Methods: CRC data were retrieved from The Cancer Genome Atlas. The database was randomly divided into train set and validation set; then, univariate and multivariate Cox regression analyses were performed to screen prognosis-related ARlncRNAs for prediction model construction. Interactive network and Sankey diagrams of ARlncRNAs and messenger RNAs were plotted. We analyzed the survival rate of high- and low-risk patients and plotted survival curves and determined whether the risk score was an independent predictor of CRC. Receiver operating characteristic curves were used to evaluate model sensitivity and specificity. Then, the expression level of lncRNA was detected by quantitative real-time polymerase chain reaction, and the location of lncRNA was observed by fluorescence in situ hybridization. Additionally, the protein expression was detected by Western blot.Results: A prognostic prediction model of CRC was built based on nine ARlncRNAs (NKILA, LINC00174, AC008760.1, LINC02041, PCAT6, AC156455.1, LINC01503, LINC00957, and CD27-AS1). The 5-year overall survival rate was significantly lower in the high-risk group than in the low-risk group among train set, validation set, and all patients (all p < 0.001). The model had high sensitivity and accuracy in predicting the 1-year overall survival rate (area under the curve = 0.717). The prediction model risk score was an independent predictor of CRC. LINC00174 and NKILA were expressed in the nucleus and cytoplasm of normal colonic epithelial cell line NCM460 and colorectal cancer cell lines HT29. Additionally, LINC00174 and NKILA were overexpressed in HT29 compared with NCM460. After autophagy activation, LINCC00174 expression was significantly downregulated both in NCM460 and HT29, while NKILA expression was significantly increased.Conclusion: The new ARlncRNA-based model predicts CRC patient prognosis and provides new research ideas regarding potential mechanisms regulating the biological behavior of CRC. ARlncRNAs may play important roles in personalized cancer treatment.
研究领域:
肿瘤学
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分子生物学
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生物信息学
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临床研究
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产品关联
DOI
PubMed
高影响因子
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