Candidate Gene and MicroRNA Biomarkers of Metastatic Renal Cell Carcinoma (MRCC) Response to Sunitinib
Abstract Backgrounds: The incidence of renal cancer is relatively insidious, and some patients have been metastatic renal cancer at the initial visit. Sunitinib is the first-line systemic therapy for patients with metastatic renal cell carcinoma, however, there is scant analysis of its effect on genes and microRNAs.Methods: In this study, 8 differentially expressed microRNAs and 112 differentially expressed genes were designated by analyzing mRNA and microRNA data sets and weighted correlation network analysis (WGCNA).Results: NIPSNAP1 gene showed the most co-expression with other genes. Through the intersection of the microRNA target gene with our differentially expressed genes, we got 26 genes. KEGG and GO analysis showed that these genes were predominantly concentrated in Pathways in cancer, Sphingolipid metabolism and Glycosaminoglycan degradation. After we set the 26 genes and gene of WGCNA do intersection, received six genes, respectively is NIPSNAP1, SDC4, TBC1D9, NEU1, STK40 and PLAUR. Conclusion: Through subsequent cell, molecular and flow cytometry experiments, we found the PLAUR would play a crucial role in renal cell carcinoma (RCC) resistant to sunitinib, which will be available for new ideas to forecast sunitinib resistance and reverse sunitinib resistance..
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Preprint| Erscheinungsjahr: |
2022 |
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| Erschienen: |
2022 |
| Enthalten in: |
ResearchSquare.com - (2022) vom: 12. Jan. Zur Gesamtaufnahme - year:2022 |
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| Sprache: |
Englisch |
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| Beteiligte Personen: |
yang, qiwei [VerfasserIn] |
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| Links: |
Volltext [kostenfrei] |
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| doi: |
10.21203/rs.3.rs-1228653/v1 |
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| 520 | |a Abstract Backgrounds: The incidence of renal cancer is relatively insidious, and some patients have been metastatic renal cancer at the initial visit. Sunitinib is the first-line systemic therapy for patients with metastatic renal cell carcinoma, however, there is scant analysis of its effect on genes and microRNAs.Methods: In this study, 8 differentially expressed microRNAs and 112 differentially expressed genes were designated by analyzing mRNA and microRNA data sets and weighted correlation network analysis (WGCNA).Results: NIPSNAP1 gene showed the most co-expression with other genes. Through the intersection of the microRNA target gene with our differentially expressed genes, we got 26 genes. KEGG and GO analysis showed that these genes were predominantly concentrated in Pathways in cancer, Sphingolipid metabolism and Glycosaminoglycan degradation. After we set the 26 genes and gene of WGCNA do intersection, received six genes, respectively is NIPSNAP1, SDC4, TBC1D9, NEU1, STK40 and PLAUR. Conclusion: Through subsequent cell, molecular and flow cytometry experiments, we found the PLAUR would play a crucial role in renal cell carcinoma (RCC) resistant to sunitinib, which will be available for new ideas to forecast sunitinib resistance and reverse sunitinib resistance. | ||
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