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Co-expression analysis of pancreatic cancer proteome reveals biology and prognostic biomarkers
PURPOSE: Despite extensive biological and clinical studies, including comprehensive genomic and transcriptomic profiling efforts, pancreatic ductal adenocarcinoma (PDAC) remains a devastating disease, with a poor survival and limited therapeutic options. The goal of this study was to assess co-expre...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Netherlands
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7716908/ https://www.ncbi.nlm.nih.gov/pubmed/32860207 http://dx.doi.org/10.1007/s13402-020-00548-y |
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author | Mantini, G. Vallés, A. M. Le Large, T. Y. S. Capula, M. Funel, N. Pham, T. V. Piersma, S. R. Kazemier, G. Bijlsma, M. F. Giovannetti, E. Jimenez, C. R. |
author_facet | Mantini, G. Vallés, A. M. Le Large, T. Y. S. Capula, M. Funel, N. Pham, T. V. Piersma, S. R. Kazemier, G. Bijlsma, M. F. Giovannetti, E. Jimenez, C. R. |
author_sort | Mantini, G. |
collection | PubMed |
description | PURPOSE: Despite extensive biological and clinical studies, including comprehensive genomic and transcriptomic profiling efforts, pancreatic ductal adenocarcinoma (PDAC) remains a devastating disease, with a poor survival and limited therapeutic options. The goal of this study was to assess co-expressed PDAC proteins and their associations with biological pathways and clinical parameters. METHODS: Correlation network analysis is emerging as a powerful approach to infer tumor biology from omics data and to prioritize candidate genes as biomarkers or drug targets. In this study, we applied a weighted gene co-expression network analysis (WGCNA) to the proteome of 20 surgically resected PDAC specimens (PXD015744) and confirmed its clinical value in 82 independent primary cases. RESULTS: Using WGCNA, we obtained twelve co-expressed clusters with a distinct biology. Notably, we found that one module enriched for metabolic processes and epithelial-mesenchymal-transition (EMT) was significantly associated with overall survival (p = 0.01) and disease-free survival (p = 0.03). The prognostic value of three proteins (SPTBN1, KHSRP and PYGL) belonging to this module was confirmed using immunohistochemistry in a cohort of 82 independent resected patients. Risk score evaluation of the prognostic signature confirmed its association with overall survival in multivariate analyses. Finally, immunofluorescence analysis confirmed co-expression of SPTBN1 and KHSRP in Hs766t PDAC cells. CONCLUSIONS: Our WGCNA analysis revealed a PDAC module enriched for metabolic and EMT-associated processes. In addition, we found that three of the proteins involved were associated with PDAC survival. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s13402-020-00548-y) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-7716908 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Springer Netherlands |
record_format | MEDLINE/PubMed |
spelling | pubmed-77169082020-12-04 Co-expression analysis of pancreatic cancer proteome reveals biology and prognostic biomarkers Mantini, G. Vallés, A. M. Le Large, T. Y. S. Capula, M. Funel, N. Pham, T. V. Piersma, S. R. Kazemier, G. Bijlsma, M. F. Giovannetti, E. Jimenez, C. R. Cell Oncol (Dordr) Original Paper PURPOSE: Despite extensive biological and clinical studies, including comprehensive genomic and transcriptomic profiling efforts, pancreatic ductal adenocarcinoma (PDAC) remains a devastating disease, with a poor survival and limited therapeutic options. The goal of this study was to assess co-expressed PDAC proteins and their associations with biological pathways and clinical parameters. METHODS: Correlation network analysis is emerging as a powerful approach to infer tumor biology from omics data and to prioritize candidate genes as biomarkers or drug targets. In this study, we applied a weighted gene co-expression network analysis (WGCNA) to the proteome of 20 surgically resected PDAC specimens (PXD015744) and confirmed its clinical value in 82 independent primary cases. RESULTS: Using WGCNA, we obtained twelve co-expressed clusters with a distinct biology. Notably, we found that one module enriched for metabolic processes and epithelial-mesenchymal-transition (EMT) was significantly associated with overall survival (p = 0.01) and disease-free survival (p = 0.03). The prognostic value of three proteins (SPTBN1, KHSRP and PYGL) belonging to this module was confirmed using immunohistochemistry in a cohort of 82 independent resected patients. Risk score evaluation of the prognostic signature confirmed its association with overall survival in multivariate analyses. Finally, immunofluorescence analysis confirmed co-expression of SPTBN1 and KHSRP in Hs766t PDAC cells. CONCLUSIONS: Our WGCNA analysis revealed a PDAC module enriched for metabolic and EMT-associated processes. In addition, we found that three of the proteins involved were associated with PDAC survival. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s13402-020-00548-y) contains supplementary material, which is available to authorized users. Springer Netherlands 2020-08-29 2020 /pmc/articles/PMC7716908/ /pubmed/32860207 http://dx.doi.org/10.1007/s13402-020-00548-y Text en © The Author(s) 2020 Open Access This 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/. |
spellingShingle | Original Paper Mantini, G. Vallés, A. M. Le Large, T. Y. S. Capula, M. Funel, N. Pham, T. V. Piersma, S. R. Kazemier, G. Bijlsma, M. F. Giovannetti, E. Jimenez, C. R. Co-expression analysis of pancreatic cancer proteome reveals biology and prognostic biomarkers |
title | Co-expression analysis of pancreatic cancer proteome reveals biology and prognostic biomarkers |
title_full | Co-expression analysis of pancreatic cancer proteome reveals biology and prognostic biomarkers |
title_fullStr | Co-expression analysis of pancreatic cancer proteome reveals biology and prognostic biomarkers |
title_full_unstemmed | Co-expression analysis of pancreatic cancer proteome reveals biology and prognostic biomarkers |
title_short | Co-expression analysis of pancreatic cancer proteome reveals biology and prognostic biomarkers |
title_sort | co-expression analysis of pancreatic cancer proteome reveals biology and prognostic biomarkers |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7716908/ https://www.ncbi.nlm.nih.gov/pubmed/32860207 http://dx.doi.org/10.1007/s13402-020-00548-y |
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