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KIF11: A potential prognostic biomarker for predicting bone metastasis-free survival of prostate cancer
Most prostate cancer (PCa) cases remain indolent with a relatively good prognosis. However, bone metastasis of PCa can quickly worsen prognoses and lead to mortality. Metastasis-free survival (MFS), a strong surrogate for overall survival, is widely used in PCa prognosis research. The present study...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
D.A. Spandidos
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9353809/ https://www.ncbi.nlm.nih.gov/pubmed/35949593 http://dx.doi.org/10.3892/ol.2022.13432 |
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author | Wang, Haoyuan Li, Sijie Liu, Bin Wei, Shufei Wang, Tianyi Li, Tao Lin, Jiahu Ni, Xiaochen |
author_facet | Wang, Haoyuan Li, Sijie Liu, Bin Wei, Shufei Wang, Tianyi Li, Tao Lin, Jiahu Ni, Xiaochen |
author_sort | Wang, Haoyuan |
collection | PubMed |
description | Most prostate cancer (PCa) cases remain indolent with a relatively good prognosis. However, bone metastasis of PCa can quickly worsen prognoses and lead to mortality. Metastasis-free survival (MFS), a strong surrogate for overall survival, is widely used in PCa prognosis research. The present study identified molecules that affect bone MFS in PCa, with clinical validation. Three datasets (GSE32269, GSE74367 and GSE77930) were downloaded from the Gene Expression Omnibus database. Hub genes most relevant to clinical traits (bone metastasis-associated morbidity) were identified by weighted gene co-expression network analysis (WGCNA) and subjected to logistic regression analysis. Patient samples were obtained between January 2014 and December 2016, with a clinically annotated follow-up in December 2021. Clinical data and follow-up information for 60 patients with PCa were used in MFS analysis. Tumor samples were retrieved, and immunohistochemistry was performed to detect vascular endothelial growth factor (VEGF). The prognostic potential of the two molecules was assessed using Cox proportional hazards regression analysis. A total of 16 gene modules were obtained via WGCNA, and the tan module, containing 147 genes, was most closely linked to bone metastasis. In total, 877 differentially expressed genes (DEGs) were detected. The DEG-tan module intersection yielded seven hub genes [BUB1, kinesin family member (KIF)2C, RACGAP1, CENPE, KIF11, TTK and KIF20A]. Using univariate and multivariate logistic regression analyses for independent risk factors of bone metastasis, KIF11 and VEGF were found to be significantly associated with a higher T stage, prostate-specific antigen level and Gleason score. In addition, KIF11 and VEGF expression levels were positively correlated (P<0.001). Using univariate Cox analysis, KIF11 and VEGF were found to exhibit a significant association with poor MFS (P<0.05). However, only KIF11 was significantly associated with MFS upon multivariate analysis (P=0.007; hazard ratio, 2.776; 95% confidence interval, 1.315-5.859). Markers of bone metastasis in PCa were identified. Overall, KIF11 is an independent indicator that can predict bone metastasis for patients with PCa, which could be used to guide clinical practice. |
format | Online Article Text |
id | pubmed-9353809 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | D.A. Spandidos |
record_format | MEDLINE/PubMed |
spelling | pubmed-93538092022-08-09 KIF11: A potential prognostic biomarker for predicting bone metastasis-free survival of prostate cancer Wang, Haoyuan Li, Sijie Liu, Bin Wei, Shufei Wang, Tianyi Li, Tao Lin, Jiahu Ni, Xiaochen Oncol Lett Articles Most prostate cancer (PCa) cases remain indolent with a relatively good prognosis. However, bone metastasis of PCa can quickly worsen prognoses and lead to mortality. Metastasis-free survival (MFS), a strong surrogate for overall survival, is widely used in PCa prognosis research. The present study identified molecules that affect bone MFS in PCa, with clinical validation. Three datasets (GSE32269, GSE74367 and GSE77930) were downloaded from the Gene Expression Omnibus database. Hub genes most relevant to clinical traits (bone metastasis-associated morbidity) were identified by weighted gene co-expression network analysis (WGCNA) and subjected to logistic regression analysis. Patient samples were obtained between January 2014 and December 2016, with a clinically annotated follow-up in December 2021. Clinical data and follow-up information for 60 patients with PCa were used in MFS analysis. Tumor samples were retrieved, and immunohistochemistry was performed to detect vascular endothelial growth factor (VEGF). The prognostic potential of the two molecules was assessed using Cox proportional hazards regression analysis. A total of 16 gene modules were obtained via WGCNA, and the tan module, containing 147 genes, was most closely linked to bone metastasis. In total, 877 differentially expressed genes (DEGs) were detected. The DEG-tan module intersection yielded seven hub genes [BUB1, kinesin family member (KIF)2C, RACGAP1, CENPE, KIF11, TTK and KIF20A]. Using univariate and multivariate logistic regression analyses for independent risk factors of bone metastasis, KIF11 and VEGF were found to be significantly associated with a higher T stage, prostate-specific antigen level and Gleason score. In addition, KIF11 and VEGF expression levels were positively correlated (P<0.001). Using univariate Cox analysis, KIF11 and VEGF were found to exhibit a significant association with poor MFS (P<0.05). However, only KIF11 was significantly associated with MFS upon multivariate analysis (P=0.007; hazard ratio, 2.776; 95% confidence interval, 1.315-5.859). Markers of bone metastasis in PCa were identified. Overall, KIF11 is an independent indicator that can predict bone metastasis for patients with PCa, which could be used to guide clinical practice. D.A. Spandidos 2022-07-15 /pmc/articles/PMC9353809/ /pubmed/35949593 http://dx.doi.org/10.3892/ol.2022.13432 Text en Copyright: © Wang et al. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made. |
spellingShingle | Articles Wang, Haoyuan Li, Sijie Liu, Bin Wei, Shufei Wang, Tianyi Li, Tao Lin, Jiahu Ni, Xiaochen KIF11: A potential prognostic biomarker for predicting bone metastasis-free survival of prostate cancer |
title | KIF11: A potential prognostic biomarker for predicting bone metastasis-free survival of prostate cancer |
title_full | KIF11: A potential prognostic biomarker for predicting bone metastasis-free survival of prostate cancer |
title_fullStr | KIF11: A potential prognostic biomarker for predicting bone metastasis-free survival of prostate cancer |
title_full_unstemmed | KIF11: A potential prognostic biomarker for predicting bone metastasis-free survival of prostate cancer |
title_short | KIF11: A potential prognostic biomarker for predicting bone metastasis-free survival of prostate cancer |
title_sort | kif11: a potential prognostic biomarker for predicting bone metastasis-free survival of prostate cancer |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9353809/ https://www.ncbi.nlm.nih.gov/pubmed/35949593 http://dx.doi.org/10.3892/ol.2022.13432 |
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