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Co-Expression Network Analysis Identified LTF in Association with Metastasis Risk and Prognosis in Clear Cell Renal Cell Carcinoma
OBJECTIVE: Clear cell renal cell carcinoma (ccRCC) is the most common renal cancer in adults. The 5-year survival rate of patients with advanced ccRCC is less than 30%. Lack of potential biomarkers for treatment and prognosis is a limitation for early diagnosis and treatment of ccRCC. METHODS: We co...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Dove
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7381825/ https://www.ncbi.nlm.nih.gov/pubmed/32764988 http://dx.doi.org/10.2147/OTT.S251000 |
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author | Ni, Lihua Yuan, Cheng Zhang, Changjiang Xiang, Yuandi Wu, Juan Wang, Xiaolong Wu, Xiaoyan |
author_facet | Ni, Lihua Yuan, Cheng Zhang, Changjiang Xiang, Yuandi Wu, Juan Wang, Xiaolong Wu, Xiaoyan |
author_sort | Ni, Lihua |
collection | PubMed |
description | OBJECTIVE: Clear cell renal cell carcinoma (ccRCC) is the most common renal cancer in adults. The 5-year survival rate of patients with advanced ccRCC is less than 30%. Lack of potential biomarkers for treatment and prognosis is a limitation for early diagnosis and treatment of ccRCC. METHODS: We collected microarray profiles of 39 ccRCC and matched normal samples to identify differential expression genes (DEGs). Then, a weighted gene co-expression network analysis (WGCNA) was constructed to identify gene modules associated with the metastasis in ccRCC. The Cancer Genome Atlas (TCGA) database and the Human Protein Atlas (HPA, https://www.proteinatlas.org/) database were used for verification set. Finally, we used biological experiments to preliminary investigate the impact of LTF on the tumor biological behavior of ccRCC, including proliferation, migration, invasion, and apoptosis. RESULTS: A total of 15 genetic modules were identified, and the light-green module is considered the most relevant to tumor metastasis. (P = 0.02, R(2) = −0.4). Protein–protein interaction (PPI) network was performed to identify the hub nodes in the light-green module. Finally, combining the results of PPI, WGCNA and DEGs, lactotransferrin (LTF) gene was regarded as “real” hub genes for cancer metastasis risk. LTF was subsequently validated using the TCGA database. Immunohistochemistry confirmed that the expression of LTF in ccRCC tumor tissue was significantly lower than that in normal tissue based on the HPA database. Intriguingly, patients with low expression of LTF had lower survival rates (HR = 0.66, 95% CI: 0.49–0.89, P = 0.0067), the expression level of the sample was negatively correlated with tumor stage (P = 0.0385), and patients with low expression of LTF gene were more likely to have distant metastasis (P = 0.038). Overexpression of LTF inhibited the proliferation, migration, invasion and promoted apoptosis of human ccRCC cells in vitro. CONCLUSION: LTF might be a novel prognostic biomarker for ccRCC. |
format | Online Article Text |
id | pubmed-7381825 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Dove |
record_format | MEDLINE/PubMed |
spelling | pubmed-73818252020-08-05 Co-Expression Network Analysis Identified LTF in Association with Metastasis Risk and Prognosis in Clear Cell Renal Cell Carcinoma Ni, Lihua Yuan, Cheng Zhang, Changjiang Xiang, Yuandi Wu, Juan Wang, Xiaolong Wu, Xiaoyan Onco Targets Ther Original Research OBJECTIVE: Clear cell renal cell carcinoma (ccRCC) is the most common renal cancer in adults. The 5-year survival rate of patients with advanced ccRCC is less than 30%. Lack of potential biomarkers for treatment and prognosis is a limitation for early diagnosis and treatment of ccRCC. METHODS: We collected microarray profiles of 39 ccRCC and matched normal samples to identify differential expression genes (DEGs). Then, a weighted gene co-expression network analysis (WGCNA) was constructed to identify gene modules associated with the metastasis in ccRCC. The Cancer Genome Atlas (TCGA) database and the Human Protein Atlas (HPA, https://www.proteinatlas.org/) database were used for verification set. Finally, we used biological experiments to preliminary investigate the impact of LTF on the tumor biological behavior of ccRCC, including proliferation, migration, invasion, and apoptosis. RESULTS: A total of 15 genetic modules were identified, and the light-green module is considered the most relevant to tumor metastasis. (P = 0.02, R(2) = −0.4). Protein–protein interaction (PPI) network was performed to identify the hub nodes in the light-green module. Finally, combining the results of PPI, WGCNA and DEGs, lactotransferrin (LTF) gene was regarded as “real” hub genes for cancer metastasis risk. LTF was subsequently validated using the TCGA database. Immunohistochemistry confirmed that the expression of LTF in ccRCC tumor tissue was significantly lower than that in normal tissue based on the HPA database. Intriguingly, patients with low expression of LTF had lower survival rates (HR = 0.66, 95% CI: 0.49–0.89, P = 0.0067), the expression level of the sample was negatively correlated with tumor stage (P = 0.0385), and patients with low expression of LTF gene were more likely to have distant metastasis (P = 0.038). Overexpression of LTF inhibited the proliferation, migration, invasion and promoted apoptosis of human ccRCC cells in vitro. CONCLUSION: LTF might be a novel prognostic biomarker for ccRCC. Dove 2020-07-17 /pmc/articles/PMC7381825/ /pubmed/32764988 http://dx.doi.org/10.2147/OTT.S251000 Text en © 2020 Ni et al. http://creativecommons.org/licenses/by-nc/3.0/ This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php). |
spellingShingle | Original Research Ni, Lihua Yuan, Cheng Zhang, Changjiang Xiang, Yuandi Wu, Juan Wang, Xiaolong Wu, Xiaoyan Co-Expression Network Analysis Identified LTF in Association with Metastasis Risk and Prognosis in Clear Cell Renal Cell Carcinoma |
title | Co-Expression Network Analysis Identified LTF in Association with Metastasis Risk and Prognosis in Clear Cell Renal Cell Carcinoma |
title_full | Co-Expression Network Analysis Identified LTF in Association with Metastasis Risk and Prognosis in Clear Cell Renal Cell Carcinoma |
title_fullStr | Co-Expression Network Analysis Identified LTF in Association with Metastasis Risk and Prognosis in Clear Cell Renal Cell Carcinoma |
title_full_unstemmed | Co-Expression Network Analysis Identified LTF in Association with Metastasis Risk and Prognosis in Clear Cell Renal Cell Carcinoma |
title_short | Co-Expression Network Analysis Identified LTF in Association with Metastasis Risk and Prognosis in Clear Cell Renal Cell Carcinoma |
title_sort | co-expression network analysis identified ltf in association with metastasis risk and prognosis in clear cell renal cell carcinoma |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7381825/ https://www.ncbi.nlm.nih.gov/pubmed/32764988 http://dx.doi.org/10.2147/OTT.S251000 |
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