Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/108482
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Department of Biomedical Engineering | - |
| dc.creator | Zhang, Z | - |
| dc.creator | Cao, C | - |
| dc.creator | Zhou, CL | - |
| dc.creator | Li, X | - |
| dc.creator | Miao, C | - |
| dc.creator | Shen, L | - |
| dc.creator | Singla, RK | - |
| dc.creator | Lu, X | - |
| dc.date.accessioned | 2024-08-19T01:58:41Z | - |
| dc.date.available | 2024-08-19T01:58:41Z | - |
| dc.identifier.issn | 1944-7124 | - |
| dc.identifier.uri | http://hdl.handle.net/10397/108482 | - |
| dc.language.iso | en | en_US |
| dc.publisher | Elsevier Inc. | en_US |
| dc.rights | © 2023 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). | en_US |
| dc.rights | The following publication Zhang, Z., Cao, C., Zhou, C.-L., Li, X., Miao, C., Shen, L., Singla, R. K., & Lu, X. (2023). Identification of a novel 5-methylcytosine-related signature for prognostic prediction of kidney renal papillary cell carcinoma and a Putative target for drug repurposing. Translational Oncology, 36, 101741 is available at https://doi.org/10.1016/j.tranon.2023.101741. | en_US |
| dc.subject | 5-methylcytosine | en_US |
| dc.subject | Kidney cancer | en_US |
| dc.subject | Kidney renal papillary cell carcinoma | en_US |
| dc.subject | Prognostic signature | en_US |
| dc.subject | Renal cell carcinoma | en_US |
| dc.subject | Tumor microenvironment | en_US |
| dc.subject | Tumor therapy | en_US |
| dc.title | Identification of a novel 5-methylcytosine-related signature for prognostic prediction of kidney renal papillary cell carcinoma and a Putative target for drug repurposing | en_US |
| dc.type | Journal/Magazine Article | en_US |
| dc.identifier.volume | 36 | - |
| dc.identifier.doi | 10.1016/j.tranon.2023.101741 | - |
| dcterms.abstract | Background: Many studies have demonstrated the crucial roles of 5-methylcytosine (m5C) RNA methylation in cancer pathogenesis. | - |
| dcterms.abstract | Methods: Two datasets, including TCGA-KIRP and ICGC, and related clinical information were downloaded, where the expression of 13 m5C regulators was examined. We applied LASSO regression to construct a multi-m5C-regulator-based signature in the TCGA cohort, which was further validated using the ICGC cohort. Univariate and multivariate Cox regressions were applied to evaluate the independent prognostic value of our model. The differences in biological functions and immune characterizations between high and low-risk groups divided based on the risk scores were also investigated via multiple approaches, such as enrichment analyses, mutation mining, and immune scoring. Finally, the sensitivities of commonly used targeted drugs were tested, and the connectivity MAP (cMAP) was utilized to screen potentially effective molecules for patients in the high-risk group. Experimental validation was done following qPCR tests in Caki-2 and HK-2 cell lines. | - |
| dcterms.abstract | Results: 3 m5C regulators, including ALYREF, DNMT3B and YBX1, were involved in our model. Survival analysis revealed a worse prognosis for patients in the high-risk group. Cox regression results indicated our model's superior predictive performance compared to single-factor prognostic evaluation. Functional enrichment analyses indicated a higher mutation frequency and poorer tumor microenvironment of patients in the high-risk group. qPCR-based results revealed that ALYREF, DNMT3B, and YBX1 were significantly up-regulated in Caki-2 cell lines compared with HK-2 cell lines. Molecules like BRD-K72451865, Levosimendan, and BRD-K03515135 were advised by cMAP for patients in the high-risk group. | - |
| dcterms.abstract | Conclusion: Our study presented a novel predictive model for KIRP prognosis. Furthermore, the results of our analysis provide new insights for investigating m5C events in KIRP pathogenesis. Graphical abstract: [Figure not available: see fulltext.] | - |
| dcterms.accessRights | open access | en_US |
| dcterms.bibliographicCitation | Translational oncology, Oct. 2023, v. 36, 101741 | - |
| dcterms.isPartOf | Translational oncology | - |
| dcterms.issued | 2023-10 | - |
| dc.identifier.scopus | 2-s2.0-85166518363 | - |
| dc.identifier.eissn | 1936-5233 | - |
| dc.identifier.artn | 101741 | - |
| dc.description.validate | 202408 bcch | - |
| dc.description.oa | Version of Record | en_US |
| dc.identifier.FolderNumber | OA_Scopus/WOS | en_US |
| dc.description.fundingSource | Others | en_US |
| dc.description.fundingText | Health Commission of Henan Province; 2020 Medical Science and Technology Research Plan of Henan Province | en_US |
| dc.description.pubStatus | Published | en_US |
| dc.description.oaCategory | CC | en_US |
| Appears in Collections: | Journal/Magazine Article | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 1-s2.0-S1936523323001274-main.pdf | 4.5 MB | Adobe PDF | View/Open |
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