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Development of a prognostic risk model for clear cell renal cell carcinoma by systematic evaluation of DNA methylation markers

BACKGROUND: Current risk models for renal cell carcinoma (RCC) based on clinicopathological factors are sub-optimal in accurately identifying high-risk patients. Here, we perform a head-to-head comparison of previously published DNA methylation markers and propose a potential prognostic model for cl...

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Autores principales: Joosten, S. C., Odeh, S. N. O., Koch, A., Buekers, N., Aarts, M. J. B., Baldewijns, M. M. L. L., Van Neste, L., van Kuijk, S., Schouten, L. J., van den Brandt, P. A., Tjan-Heijnen, V. C., van Engeland, M., Smits, K. M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8094610/
https://www.ncbi.nlm.nih.gov/pubmed/33947447
http://dx.doi.org/10.1186/s13148-021-01084-8
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author Joosten, S. C.
Odeh, S. N. O.
Koch, A.
Buekers, N.
Aarts, M. J. B.
Baldewijns, M. M. L. L.
Van Neste, L.
van Kuijk, S.
Schouten, L. J.
van den Brandt, P. A.
Tjan-Heijnen, V. C.
van Engeland, M.
Smits, K. M.
author_facet Joosten, S. C.
Odeh, S. N. O.
Koch, A.
Buekers, N.
Aarts, M. J. B.
Baldewijns, M. M. L. L.
Van Neste, L.
van Kuijk, S.
Schouten, L. J.
van den Brandt, P. A.
Tjan-Heijnen, V. C.
van Engeland, M.
Smits, K. M.
author_sort Joosten, S. C.
collection PubMed
description BACKGROUND: Current risk models for renal cell carcinoma (RCC) based on clinicopathological factors are sub-optimal in accurately identifying high-risk patients. Here, we perform a head-to-head comparison of previously published DNA methylation markers and propose a potential prognostic model for clear cell RCC (ccRCC). PATIENTS AND METHODS: Promoter methylation of PCDH8, BNC1, SCUBE3, GREM1, LAD1, NEFH, RASSF1A, GATA5, SFRP1, CDO1, and NEURL was determined by nested methylation-specific PCR. To identify clinically relevant methylated regions, The Cancer Genome Atlas (TCGA) was used to guide primer design. Formalin-fixed paraffin-embedded (FFPE) tissue samples from 336 non-metastatic ccRCC patients from the prospective Netherlands Cohort Study (NLCS) were used to develop a Cox proportional hazards model using stepwise backward elimination and bootstrapping to correct for optimism. For validation purposes, FFPE ccRCC tissue of 64 patients from the University Hospitals Leuven and a series of 232 cases from The Cancer Genome Atlas (TCGA) were used. RESULTS: Methylation of GREM1, GATA5, LAD1, NEFH, NEURL, and SFRP1 was associated with poor ccRCC-specific survival, independent of age, sex, tumor size, TNM stage or tumor grade. Moreover, the association between GREM1, NEFH, and NEURL methylation and outcome was shown to be dependent on the genomic region. A prognostic biomarker model containing GREM1, GATA5, LAD1, NEFH and NEURL methylation in combination with clinicopathological characteristics, performed better compared to the model with clinicopathological characteristics only (clinical model), in both the NLCS and the validation population with a c-statistic of 0.71 versus 0.65 and a c-statistic of 0.95 versus 0.86 consecutively. However, the biomarker model had limited added prognostic value in the TCGA series with a c-statistic of 0.76 versus 0.75 for the clinical model. CONCLUSION: In this study we performed a head-to-head comparison of potential prognostic methylation markers for ccRCC using a novel approach to guide primers design which utilizes the optimal location for measuring DNA methylation. Using this approach, we identified five methylation markers that potentially show prognostic value in addition to currently known clinicopathological factors. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13148-021-01084-8.
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spelling pubmed-80946102021-05-05 Development of a prognostic risk model for clear cell renal cell carcinoma by systematic evaluation of DNA methylation markers Joosten, S. C. Odeh, S. N. O. Koch, A. Buekers, N. Aarts, M. J. B. Baldewijns, M. M. L. L. Van Neste, L. van Kuijk, S. Schouten, L. J. van den Brandt, P. A. Tjan-Heijnen, V. C. van Engeland, M. Smits, K. M. Clin Epigenetics Research BACKGROUND: Current risk models for renal cell carcinoma (RCC) based on clinicopathological factors are sub-optimal in accurately identifying high-risk patients. Here, we perform a head-to-head comparison of previously published DNA methylation markers and propose a potential prognostic model for clear cell RCC (ccRCC). PATIENTS AND METHODS: Promoter methylation of PCDH8, BNC1, SCUBE3, GREM1, LAD1, NEFH, RASSF1A, GATA5, SFRP1, CDO1, and NEURL was determined by nested methylation-specific PCR. To identify clinically relevant methylated regions, The Cancer Genome Atlas (TCGA) was used to guide primer design. Formalin-fixed paraffin-embedded (FFPE) tissue samples from 336 non-metastatic ccRCC patients from the prospective Netherlands Cohort Study (NLCS) were used to develop a Cox proportional hazards model using stepwise backward elimination and bootstrapping to correct for optimism. For validation purposes, FFPE ccRCC tissue of 64 patients from the University Hospitals Leuven and a series of 232 cases from The Cancer Genome Atlas (TCGA) were used. RESULTS: Methylation of GREM1, GATA5, LAD1, NEFH, NEURL, and SFRP1 was associated with poor ccRCC-specific survival, independent of age, sex, tumor size, TNM stage or tumor grade. Moreover, the association between GREM1, NEFH, and NEURL methylation and outcome was shown to be dependent on the genomic region. A prognostic biomarker model containing GREM1, GATA5, LAD1, NEFH and NEURL methylation in combination with clinicopathological characteristics, performed better compared to the model with clinicopathological characteristics only (clinical model), in both the NLCS and the validation population with a c-statistic of 0.71 versus 0.65 and a c-statistic of 0.95 versus 0.86 consecutively. However, the biomarker model had limited added prognostic value in the TCGA series with a c-statistic of 0.76 versus 0.75 for the clinical model. CONCLUSION: In this study we performed a head-to-head comparison of potential prognostic methylation markers for ccRCC using a novel approach to guide primers design which utilizes the optimal location for measuring DNA methylation. Using this approach, we identified five methylation markers that potentially show prognostic value in addition to currently known clinicopathological factors. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13148-021-01084-8. BioMed Central 2021-05-04 /pmc/articles/PMC8094610/ /pubmed/33947447 http://dx.doi.org/10.1186/s13148-021-01084-8 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Joosten, S. C.
Odeh, S. N. O.
Koch, A.
Buekers, N.
Aarts, M. J. B.
Baldewijns, M. M. L. L.
Van Neste, L.
van Kuijk, S.
Schouten, L. J.
van den Brandt, P. A.
Tjan-Heijnen, V. C.
van Engeland, M.
Smits, K. M.
Development of a prognostic risk model for clear cell renal cell carcinoma by systematic evaluation of DNA methylation markers
title Development of a prognostic risk model for clear cell renal cell carcinoma by systematic evaluation of DNA methylation markers
title_full Development of a prognostic risk model for clear cell renal cell carcinoma by systematic evaluation of DNA methylation markers
title_fullStr Development of a prognostic risk model for clear cell renal cell carcinoma by systematic evaluation of DNA methylation markers
title_full_unstemmed Development of a prognostic risk model for clear cell renal cell carcinoma by systematic evaluation of DNA methylation markers
title_short Development of a prognostic risk model for clear cell renal cell carcinoma by systematic evaluation of DNA methylation markers
title_sort development of a prognostic risk model for clear cell renal cell carcinoma by systematic evaluation of dna methylation markers
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8094610/
https://www.ncbi.nlm.nih.gov/pubmed/33947447
http://dx.doi.org/10.1186/s13148-021-01084-8
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