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Your search keyword '"Zhao, Yanteng"' showing total 42 results
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42 results on '"Zhao, Yanteng"'

12. Direct Transition‐Metal‐Free Enantioselective Hydroxylation: Expeditious Access to 3‐Functionalized 3‐Hydroxy‐2‐oxindoles

Author

Zhao, Shouqin, primary, Yang, Wen, additional, Lan, Yunfei, additional, Zhao, Yanteng, additional, Xu, Yi, additional, Liu, Wanqing, additional, Wang, Linlin, additional, Zhou, Xin, additional, Yu, Changyan, additional, Guo, Ting, additional, Yuan, Lujiang, additional, Jia, Qianfa, additional, and Ren, Qiao, additional

Published
2024
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21. Genome-wide methylation profiling identify hypermethylated HOXL subclass genes as potential markers for esophageal squamous cell carcinoma detection

Author

Yu, Qiuning, primary, Xia, Namei, additional, Zhao, Yanteng, additional, Jin, Huifang, additional, Chen, Renyin, additional, Ye, Fanglei, additional, Chen, Liyinghui, additional, Xie, Ying, additional, Wan, Kangkang, additional, Zhou, Jun, additional, Zhou, Dihan, additional, and Lv, Xianping, additional

Published
2022
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22. Additional file 1 of A novel stemness-hypoxia-related signature for prognostic stratification and immunotherapy response in hepatocellular carcinoma

Author

Zhang, Genhao, Zhang, Kai, Zhao, Yanteng, Yang, Qiankun, and Lv, Xianping

Abstract

Additional file 1: Figure S1. Identify the weighted value β that meets the law of scale-free networks. Figure S2. (A) Heatmap of the expression levels of 61 SHRGs in normal and tumor tissues. (B) Protein-protein interaction (PPI) network construction. (C) The main enriched entries for these genes. Figure S3. NMF rank survey. Figure S4. The mutation rates of the top fifteen most significantly mutated genes were significantly different between the Cluster 1 and Cluster 2 subgroups. Figure S5. The prognostic model could further differentiate patients with different clinical characteristics. Figure S6. Identification of GO and KEGG enrichment between high- and low-risk scores subgroups. Figure S7. The mutation rates of the top fifteen most significantly mutated genes were significantly different between high- and low-risk scores subgroups. Figure S8. The predictive significance of the prognostic model was verified in the nomogram. Figure S9. Top 16 most important tumor-sensitive drugs. Table S1. Clinical characteristics of HCC patients involved in the study. Table S2. The sequences of the qRT-PCR primers used in this study. Table S3. Immune cells with differences in abundance between Cluster1 and Cluster 2 by the four algorithms. Table S4. Immune cells with differences in abundance between high- and low-risk score groups by the four algorithms. Table S5. 77 tumor-sensitive drugs targeting tumor cell stemness.

Published
2022
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31. Enhanced Peripheral Nerve Regeneration by a High Surface Area to Volume Ratio of Nerve Conduits Fabricated from Hydroxyethyl Cellulose/Soy Protein Composite Sponges

Author

Zhao, Yanteng, primary, Zhang, Qiang, additional, Zhao, Lei, additional, Gan, Li, additional, Yi, Li, additional, Zhao, Yanan, additional, Xue, Jingling, additional, Luo, Lihua, additional, Du, Qiaoyue, additional, Geng, Rongxin, additional, Sun, Zhihong, additional, Benkirane-Jessel, Nadia, additional, Chen, Pu, additional, Li, Yinping, additional, and Chen, Yun, additional

Published
2017
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41. A dual-gene panel of two fragments of methylated IRF4 and one of ZEB2 in plasma cell-free DNA for gastric cancer detection.

Author

Bu C, Wang Z, Lv X, and Zhao Y

Subjects
Humans, Female, Male, Middle Aged, Aged, Adult, Stomach Neoplasms genetics, Stomach Neoplasms blood, Stomach Neoplasms diagnosis, DNA Methylation, Interferon Regulatory Factors genetics, Biomarkers, Tumor genetics, Biomarkers, Tumor blood, Zinc Finger E-box Binding Homeobox 2 genetics, Zinc Finger E-box Binding Homeobox 2 metabolism, Cell-Free Nucleic Acids genetics
Abstract

Early detection is crucial for increasing the survival rate of gastric cancer (GC). We aimed to identify a methylated cell-free DNA (cfDNA) marker panel for detecting GC. The differentially methylated CpGs (DMCs) were selected from datasets of The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. The selected DMCs were validated and further selected in tissue samples (40 gastric cancer and 36 healthy white blood cell samples) and in a quarter sample volume of plasma samples (37 gastric cancer, 12 benign gastric disease, and 43 healthy individuals). The marker combination selected was then evaluated in a normal sample volume of plasma samples (35 gastric cancer, 39 control diseases, and 40 healthy individuals) using real-time methylation-specific PCR (MSP). The analysis of the results compared methods based on 2 -ΔΔCt values and Ct values. In the results, 30 DMCs were selected through bioinformatics methods, and then 5 were selected for biological validation. The marker combination of two fragments of IRF4 (IRF4-1 and IRF4-2) and one of ZEB2 was selected due to its good performance. The Ct-based method was selected for its good results and practical advantages. The assay, IRF4-1 and IRF4-2 in one fluorescence channel and ZEB2 in another, obtained 74.3% sensitivity for the GC group at any stage, at 92.4% specificity. In conclusion, the panel of IRF4 and ZEB2 in plasma cfDNA demonstrates good diagnostic performance and application potential in clinical settings.

Published
2024
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42. Plasma methylated GNB4 and Riplet as a novel dual-marker panel for the detection of hepatocellular carcinoma.

Author

Zhao Y, Zhao L, Jin H, Xie Y, Chen L, Zhang W, Dong L, Zhang L, Huang Y, Wan K, Yang Q, and Wang S

Subjects
Humans, alpha-Fetoproteins analysis, alpha-Fetoproteins genetics, alpha-Fetoproteins metabolism, Biomarkers, Tumor metabolism, DNA Methylation, Carcinoma, Hepatocellular diagnosis, Carcinoma, Hepatocellular genetics, Liver Neoplasms diagnosis, Liver Neoplasms genetics, GTP-Binding Protein beta Subunits genetics, GTP-Binding Protein beta Subunits metabolism
Abstract

Early detection of hepatocellular carcinoma (HCC) can greatly improve the survival rate of patients. We aimed to develop a novel marker panel based on cell-free DNA (cfDNA) methylation for the detection of HCC. The differentially methylated CpG sites (DMCs) specific for HCC blood diagnosis were selected from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, then validated by the whole genome bisulphite sequencing (WGBS) of 12 paired HCC and paracancerous tissues. The clinical performance of the panel was evaluated using tissue samples [32 HCC, chronic liver disease (CLD), and healthy individuals] and plasma cohorts (173 HCC, 199 CLD, and 98 healthy individuals). The combination of G protein subunit beta 4 (GNB4) and Riplet had the optimal area under the curve (AUC) in seven candidates through TCGA, GEO, and WGBS analyses. In tissue validation, the GNB4 and Riplet showed an AUC of 100% with a sensitivity and specificity of 100% for detecting any-stage HCC. In plasma, it demonstrated a high sensitivity of 84.39% at 91.92% specificity, with an AUC of 92.51% for detecting any-stage HCC. The dual-marker panel had a higher sensitivity of 78.26% for stage I HCC than alpha-fetoprotein (AFP) of 47.83%, and a high sensitivity of 70.27% for detecting a single tumour (size ≤3 cm). In conclusion, we developed a novel dual-marker panel that demonstrates high accuracy in detecting HCC, surpassing the performance of AFP testing.

Published
2024
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