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Study of Clinical Predictive Value and Immune Characterization of SLFN11 in Clear Cell Renal Cell Carcinoma

BACKGROUND: SLFN11 has been found to regulate the development and progression of a variety of cancers and is associated with drug therapy, while its role in clear cell renal cell carcinoma (ccRCC) remains unclear; therefore, the aim of this study was to investigate SLFN11 expression in ccRCC patient...

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Autores principales: Liu, Yifu, Zhang, Zhicheng, Fu, Shengqiang, Wang, Siyuan, Cheng, Xiaofeng, Lei, Kunyang, Li, Zhilong, Sun, Ting, Ma, Ming
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8521339/
https://www.ncbi.nlm.nih.gov/pubmed/34675634
http://dx.doi.org/10.2147/IJGM.S336823
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author Liu, Yifu
Zhang, Zhicheng
Fu, Shengqiang
Wang, Siyuan
Cheng, Xiaofeng
Lei, Kunyang
Li, Zhilong
Sun, Ting
Ma, Ming
author_facet Liu, Yifu
Zhang, Zhicheng
Fu, Shengqiang
Wang, Siyuan
Cheng, Xiaofeng
Lei, Kunyang
Li, Zhilong
Sun, Ting
Ma, Ming
author_sort Liu, Yifu
collection PubMed
description BACKGROUND: SLFN11 has been found to regulate the development and progression of a variety of cancers and is associated with drug therapy, while its role in clear cell renal cell carcinoma (ccRCC) remains unclear; therefore, the aim of this study was to investigate SLFN11 expression in ccRCC patients and its correlations with clinicopathological and immunological features. METHODS: Gene profiles of ccRCC and the clinicopathological information of patients were downloaded from the TCGA database. Microarrays from the GEO database were used as a validation set for SLFN11 expression, which was experimentally verified in renal cancer cell lines by quantitative polymerase chain reaction (qPCR); protein expression and methylation levels were obtained from the HPA database and the UALCAN database. ROC curves, Kaplan–Meier survival analysis and Cox analysis were used to assess the diagnostic and predictive value of SLFN11 in ccRCC. Protein–protein interaction (PPI) networks for SLFN11 were obtained from the STRING website, and the TISIDB and TIMER 2.0 databases were used to study the relationship between SLFN11 and immune infiltration in the tumour microenvironment (TME). RESULTS: SLFN11 was significantly overexpressed in ccRCC tissues and renal cancer cell lines, which may be closely related to its hypermethylation status (P < 0.001). SLFN11 was positively correlated with a highly aggressive disease state, with the ROC curve showing an AUC value of 0.910 for SLFN11 in diagnosing ccRCC, and Kaplan–Meier and Cox analyses also revealed that upregulation of SLFN11 predicted a poor prognosis for ccRCC patients (P < 0.05). In addition, enrichment analysis showed that SLFN11 was closely associated with immune-related signalling pathways, and further exploration comprehensively demonstrated strong positive correlations with tumour immune lymphocytes, immune checkpoint genes, chemokines and chemokine receptors. CONCLUSION: Overall, our data analysis shows that SLFN11 is a strong diagnostic and prognostic biomarker for ccRCC and is also associated with immune infiltration in the TME.
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spelling pubmed-85213392021-10-20 Study of Clinical Predictive Value and Immune Characterization of SLFN11 in Clear Cell Renal Cell Carcinoma Liu, Yifu Zhang, Zhicheng Fu, Shengqiang Wang, Siyuan Cheng, Xiaofeng Lei, Kunyang Li, Zhilong Sun, Ting Ma, Ming Int J Gen Med Original Research BACKGROUND: SLFN11 has been found to regulate the development and progression of a variety of cancers and is associated with drug therapy, while its role in clear cell renal cell carcinoma (ccRCC) remains unclear; therefore, the aim of this study was to investigate SLFN11 expression in ccRCC patients and its correlations with clinicopathological and immunological features. METHODS: Gene profiles of ccRCC and the clinicopathological information of patients were downloaded from the TCGA database. Microarrays from the GEO database were used as a validation set for SLFN11 expression, which was experimentally verified in renal cancer cell lines by quantitative polymerase chain reaction (qPCR); protein expression and methylation levels were obtained from the HPA database and the UALCAN database. ROC curves, Kaplan–Meier survival analysis and Cox analysis were used to assess the diagnostic and predictive value of SLFN11 in ccRCC. Protein–protein interaction (PPI) networks for SLFN11 were obtained from the STRING website, and the TISIDB and TIMER 2.0 databases were used to study the relationship between SLFN11 and immune infiltration in the tumour microenvironment (TME). RESULTS: SLFN11 was significantly overexpressed in ccRCC tissues and renal cancer cell lines, which may be closely related to its hypermethylation status (P < 0.001). SLFN11 was positively correlated with a highly aggressive disease state, with the ROC curve showing an AUC value of 0.910 for SLFN11 in diagnosing ccRCC, and Kaplan–Meier and Cox analyses also revealed that upregulation of SLFN11 predicted a poor prognosis for ccRCC patients (P < 0.05). In addition, enrichment analysis showed that SLFN11 was closely associated with immune-related signalling pathways, and further exploration comprehensively demonstrated strong positive correlations with tumour immune lymphocytes, immune checkpoint genes, chemokines and chemokine receptors. CONCLUSION: Overall, our data analysis shows that SLFN11 is a strong diagnostic and prognostic biomarker for ccRCC and is also associated with immune infiltration in the TME. Dove 2021-10-13 /pmc/articles/PMC8521339/ /pubmed/34675634 http://dx.doi.org/10.2147/IJGM.S336823 Text en © 2021 Liu et al. https://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/ (https://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
Liu, Yifu
Zhang, Zhicheng
Fu, Shengqiang
Wang, Siyuan
Cheng, Xiaofeng
Lei, Kunyang
Li, Zhilong
Sun, Ting
Ma, Ming
Study of Clinical Predictive Value and Immune Characterization of SLFN11 in Clear Cell Renal Cell Carcinoma
title Study of Clinical Predictive Value and Immune Characterization of SLFN11 in Clear Cell Renal Cell Carcinoma
title_full Study of Clinical Predictive Value and Immune Characterization of SLFN11 in Clear Cell Renal Cell Carcinoma
title_fullStr Study of Clinical Predictive Value and Immune Characterization of SLFN11 in Clear Cell Renal Cell Carcinoma
title_full_unstemmed Study of Clinical Predictive Value and Immune Characterization of SLFN11 in Clear Cell Renal Cell Carcinoma
title_short Study of Clinical Predictive Value and Immune Characterization of SLFN11 in Clear Cell Renal Cell Carcinoma
title_sort study of clinical predictive value and immune characterization of slfn11 in clear cell renal cell carcinoma
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8521339/
https://www.ncbi.nlm.nih.gov/pubmed/34675634
http://dx.doi.org/10.2147/IJGM.S336823
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