Basement Membrane-Associated lncRNA Risk Model Predicts Prognosis and Guides Clinical Treatment in Clear Cell Renal Cell Carcinoma
The basement membrane (BM) affects the invasion and growth of malignant tumors. The role and mechanism of BM-associated lncRNAs in clear cell renal cell carcinoma (ccRCC) are unknown. In this study, we identified biomarkers of ccRCC and developed a risk model to assess patient prognosis. We download...
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| Format: | Article |
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MDPI AG
2023-09-01
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| Series: | Biomedicines |
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| Online Access: | https://www.mdpi.com/2227-9059/11/10/2635 |
| _version_ | 1797574691384197120 |
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| author | Xinxin Li Qihui Kuang Min Peng Kang Yang Pengcheng Luo |
| author_facet | Xinxin Li Qihui Kuang Min Peng Kang Yang Pengcheng Luo |
| author_sort | Xinxin Li |
| collection | DOAJ |
| description | The basement membrane (BM) affects the invasion and growth of malignant tumors. The role and mechanism of BM-associated lncRNAs in clear cell renal cell carcinoma (ccRCC) are unknown. In this study, we identified biomarkers of ccRCC and developed a risk model to assess patient prognosis. We downloaded transcripts and clinical data from the Cancer Genome Atlas (TCGA). Differential analysis, co-expression analysis, Cox regression analysis, and lasso regression were used to identify BM-associated prognostic lncRNAs and create a risk prediction model. We evaluated and validated the accuracy of the model using multiple methods and constructed a nomogram to predict the prognosis of ccRCC. GO, KEGG, and immunity analyses were used to explore differences in biological function. We constructed a risk model containing six BM-associated lncRNAs (LINC02154, IGFL2-AS1, NFE4, AC112715.1, AC092535.5, and AC105105.3). The risk model has higher diagnostic efficiency compared to clinical characteristics and can be used to forecast patient prognoses. We used renal cancer cells and tissue microarrays to verify the expression of lncRNAs in the risk model. We found that knocking down LINC02154 and AC112715.1 could inhibit the invasion ability of renal cancer cells. The risk model based on BM-associated lncRNAs can well predict ccRCC and guide clinical treatment. |
| first_indexed | 2024-03-10T21:25:54Z |
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| id | doaj.art-d6b85c81485c4fda9677b1eb181fb49f |
| institution | Directory Open Access Journal |
| issn | 2227-9059 |
| language | English |
| last_indexed | 2024-03-10T21:25:54Z |
| publishDate | 2023-09-01 |
| publisher | MDPI AG |
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| series | Biomedicines |
| spelling | doaj.art-d6b85c81485c4fda9677b1eb181fb49f2023-11-19T15:44:54ZengMDPI AGBiomedicines2227-90592023-09-011110263510.3390/biomedicines11102635Basement Membrane-Associated lncRNA Risk Model Predicts Prognosis and Guides Clinical Treatment in Clear Cell Renal Cell CarcinomaXinxin Li0Qihui Kuang1Min Peng2Kang Yang3Pengcheng Luo4Department of Urology, Wuhan Third Hospital (Tongren Hospital of Wuhan University), Wuhan 430060, ChinaDepartment of Urology, Wuhan Third Hospital (Tongren Hospital of Wuhan University), Wuhan 430060, ChinaDepartment of Oncology, Renmin Hospital of Wuhan University, Wuhan 430060, ChinaDepartment of Urology, Renmin Hospital of Wuhan University, Wuhan 430060, ChinaDepartment of Urology, Wuhan Third Hospital (Tongren Hospital of Wuhan University), Wuhan 430060, ChinaThe basement membrane (BM) affects the invasion and growth of malignant tumors. The role and mechanism of BM-associated lncRNAs in clear cell renal cell carcinoma (ccRCC) are unknown. In this study, we identified biomarkers of ccRCC and developed a risk model to assess patient prognosis. We downloaded transcripts and clinical data from the Cancer Genome Atlas (TCGA). Differential analysis, co-expression analysis, Cox regression analysis, and lasso regression were used to identify BM-associated prognostic lncRNAs and create a risk prediction model. We evaluated and validated the accuracy of the model using multiple methods and constructed a nomogram to predict the prognosis of ccRCC. GO, KEGG, and immunity analyses were used to explore differences in biological function. We constructed a risk model containing six BM-associated lncRNAs (LINC02154, IGFL2-AS1, NFE4, AC112715.1, AC092535.5, and AC105105.3). The risk model has higher diagnostic efficiency compared to clinical characteristics and can be used to forecast patient prognoses. We used renal cancer cells and tissue microarrays to verify the expression of lncRNAs in the risk model. We found that knocking down LINC02154 and AC112715.1 could inhibit the invasion ability of renal cancer cells. The risk model based on BM-associated lncRNAs can well predict ccRCC and guide clinical treatment.https://www.mdpi.com/2227-9059/11/10/2635basement membranediagnosticrenal cancerlncRNAprognostic modelbiomarker |
| spellingShingle | Xinxin Li Qihui Kuang Min Peng Kang Yang Pengcheng Luo Basement Membrane-Associated lncRNA Risk Model Predicts Prognosis and Guides Clinical Treatment in Clear Cell Renal Cell Carcinoma Biomedicines basement membrane diagnostic renal cancer lncRNA prognostic model biomarker |
| title | Basement Membrane-Associated lncRNA Risk Model Predicts Prognosis and Guides Clinical Treatment in Clear Cell Renal Cell Carcinoma |
| title_full | Basement Membrane-Associated lncRNA Risk Model Predicts Prognosis and Guides Clinical Treatment in Clear Cell Renal Cell Carcinoma |
| title_fullStr | Basement Membrane-Associated lncRNA Risk Model Predicts Prognosis and Guides Clinical Treatment in Clear Cell Renal Cell Carcinoma |
| title_full_unstemmed | Basement Membrane-Associated lncRNA Risk Model Predicts Prognosis and Guides Clinical Treatment in Clear Cell Renal Cell Carcinoma |
| title_short | Basement Membrane-Associated lncRNA Risk Model Predicts Prognosis and Guides Clinical Treatment in Clear Cell Renal Cell Carcinoma |
| title_sort | basement membrane associated lncrna risk model predicts prognosis and guides clinical treatment in clear cell renal cell carcinoma |
| topic | basement membrane diagnostic renal cancer lncRNA prognostic model biomarker |
| url | https://www.mdpi.com/2227-9059/11/10/2635 |
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