Identification of carcinogenesis and tumor progression processes in pancreatic ductal adenocarcinoma using high-throughput proteomics
Pancreatic ductal adenocarcinoma (PDAC) is an aggressive disease with an overall 5-year survival rate of just 5%. A better understanding of the carcinogenesis processes and the mechanisms of the progression of PDAC is mandatory. Fifty-two PDAC patients treated with surgery and adjuvant therapy, with...
| Autores: | , , , , , , , , , , , , , , , , |
|---|---|
| Tipo de recurso: | artículo |
| Fecha de publicación: | 2022 |
| País: | España |
| Institución: | Universidad Autónoma de Madrid |
| Repositorio: | Biblos-e Archivo. Repositorio Institucional de la UAM |
| Idioma: | inglés |
| OAI Identifier: | oai:repositorio.uam.es:10486/707566 |
| Acceso en línea: | http://hdl.handle.net/10486/707566 https://dx.doi.org/10.3390/cancers14102414 |
| Access Level: | acceso abierto |
| Palabra clave: | carcinogenesis high-throughput proteomics molecular profiles pancreatic ductal adenocarcinoma tumor progression Medicina |
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Identification of carcinogenesis and tumor progression processes in pancreatic ductal adenocarcinoma using high-throughput proteomicsTrilla Fuertes, LucíaGámez Pozo, AngeloLumbreras-Herrera, María IsabelLópez-Vacas, RocíoHeredia-Soto, VictoriaGhanem, IsmaelLópez-Camacho, ElenaZapater-Moros, AndreaMiguel, MaríaPena Burgos, Eva ManuelaPalacios, Elenade Uribe, MartaGuerra, LauraDittmann, AntjeMendiola, MartaVara, Juan Ángel FresnoFeliú Batlle, Jaimecarcinogenesishigh-throughput proteomicsmolecular profilespancreatic ductal adenocarcinomatumor progressionMedicinaPancreatic ductal adenocarcinoma (PDAC) is an aggressive disease with an overall 5-year survival rate of just 5%. A better understanding of the carcinogenesis processes and the mechanisms of the progression of PDAC is mandatory. Fifty-two PDAC patients treated with surgery and adjuvant therapy, with available primary tumors, normal tissue, preneoplastic lesions (PanIN), and/or lymph node metastases, were selected for the study. Proteins were extracted from small punches and analyzed by LC-MS/MS using data-independent acquisition. Proteomics data were analyzed using probabilistic graphical models, allowing functional characterization. Comparisons between groups were made using linear mixed models. Three proteomic tumor subtypes were defined. T1 (32% of patients) was related to adhesion, T2 (34%) had metabolic features, and T3 (34%) presented high splicing and nucleoplasm activity. These proteomics subtypes were validated in the PDAC TCGA cohort. Relevant biological processes related to carcinogenesis and tumor progression were studied in each subtype. Carcinogenesis in the T1 subtype seems to be related to an increase of adhesion and complement activation node activity, whereas tumor progression seems to be related to nucleoplasm and translation nodes. Regarding the T2 subtype, it seems that metabolism and, especially, mitochondria act as the motor of cancer development. T3 analyses point out that nucleoplasm, mitochondria and metabolism, and extracellular matrix nodes could be involved in T3 tumor carcinogenesis. The identified processes were different among proteomics subtypes, suggesting that the molecular motor of the disease is different in each subtype. These differences can have implications for the development of future tailored therapeutic approaches for each PDAC proteomics subtypeThis research was funded by EPIC-XS, project number 823839, the Horizon 2020 programme of the European Union, and ISCIII PI18/01604MDPIDepartamento de MedicinaFacultad de Medicina20222022-05-13research articlehttp://purl.org/coar/resource_type/c_2df8fbb1VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10486/707566https://dx.doi.org/10.3390/cancers14102414reponame:Biblos-e Archivo. Repositorio Institucional de la UAMinstname:Universidad Autónoma de MadridInglésengEuropean Commission http://dx.doi.org/10.13039/501100000780 Horizon 2020 Framework Programme 823839open accesshttp://purl.org/coar/access_right/c_abf2info:eu-repo/semantics/openAccessoai:repositorio.uam.es:10486/7075662026-06-23T12:46:27Z |
| dc.title.none.fl_str_mv |
Identification of carcinogenesis and tumor progression processes in pancreatic ductal adenocarcinoma using high-throughput proteomics |
| title |
Identification of carcinogenesis and tumor progression processes in pancreatic ductal adenocarcinoma using high-throughput proteomics |
| spellingShingle |
Identification of carcinogenesis and tumor progression processes in pancreatic ductal adenocarcinoma using high-throughput proteomics Trilla Fuertes, Lucía carcinogenesis high-throughput proteomics molecular profiles pancreatic ductal adenocarcinoma tumor progression Medicina |
| title_short |
Identification of carcinogenesis and tumor progression processes in pancreatic ductal adenocarcinoma using high-throughput proteomics |
| title_full |
Identification of carcinogenesis and tumor progression processes in pancreatic ductal adenocarcinoma using high-throughput proteomics |
| title_fullStr |
Identification of carcinogenesis and tumor progression processes in pancreatic ductal adenocarcinoma using high-throughput proteomics |
| title_full_unstemmed |
Identification of carcinogenesis and tumor progression processes in pancreatic ductal adenocarcinoma using high-throughput proteomics |
| title_sort |
Identification of carcinogenesis and tumor progression processes in pancreatic ductal adenocarcinoma using high-throughput proteomics |
| dc.creator.none.fl_str_mv |
Trilla Fuertes, Lucía Gámez Pozo, Angelo Lumbreras-Herrera, María Isabel López-Vacas, Rocío Heredia-Soto, Victoria Ghanem, Ismael López-Camacho, Elena Zapater-Moros, Andrea Miguel, María Pena Burgos, Eva Manuela Palacios, Elena de Uribe, Marta Guerra, Laura Dittmann, Antje Mendiola, Marta Vara, Juan Ángel Fresno Feliú Batlle, Jaime |
| author |
Trilla Fuertes, Lucía |
| author_facet |
Trilla Fuertes, Lucía Gámez Pozo, Angelo Lumbreras-Herrera, María Isabel López-Vacas, Rocío Heredia-Soto, Victoria Ghanem, Ismael López-Camacho, Elena Zapater-Moros, Andrea Miguel, María Pena Burgos, Eva Manuela Palacios, Elena de Uribe, Marta Guerra, Laura Dittmann, Antje Mendiola, Marta Vara, Juan Ángel Fresno Feliú Batlle, Jaime |
| author_role |
author |
| author2 |
Gámez Pozo, Angelo Lumbreras-Herrera, María Isabel López-Vacas, Rocío Heredia-Soto, Victoria Ghanem, Ismael López-Camacho, Elena Zapater-Moros, Andrea Miguel, María Pena Burgos, Eva Manuela Palacios, Elena de Uribe, Marta Guerra, Laura Dittmann, Antje Mendiola, Marta Vara, Juan Ángel Fresno Feliú Batlle, Jaime |
| author2_role |
author author author author author author author author author author author author author author author author |
| dc.contributor.none.fl_str_mv |
Departamento de Medicina Facultad de Medicina |
| dc.subject.none.fl_str_mv |
carcinogenesis high-throughput proteomics molecular profiles pancreatic ductal adenocarcinoma tumor progression Medicina |
| topic |
carcinogenesis high-throughput proteomics molecular profiles pancreatic ductal adenocarcinoma tumor progression Medicina |
| description |
Pancreatic ductal adenocarcinoma (PDAC) is an aggressive disease with an overall 5-year survival rate of just 5%. A better understanding of the carcinogenesis processes and the mechanisms of the progression of PDAC is mandatory. Fifty-two PDAC patients treated with surgery and adjuvant therapy, with available primary tumors, normal tissue, preneoplastic lesions (PanIN), and/or lymph node metastases, were selected for the study. Proteins were extracted from small punches and analyzed by LC-MS/MS using data-independent acquisition. Proteomics data were analyzed using probabilistic graphical models, allowing functional characterization. Comparisons between groups were made using linear mixed models. Three proteomic tumor subtypes were defined. T1 (32% of patients) was related to adhesion, T2 (34%) had metabolic features, and T3 (34%) presented high splicing and nucleoplasm activity. These proteomics subtypes were validated in the PDAC TCGA cohort. Relevant biological processes related to carcinogenesis and tumor progression were studied in each subtype. Carcinogenesis in the T1 subtype seems to be related to an increase of adhesion and complement activation node activity, whereas tumor progression seems to be related to nucleoplasm and translation nodes. Regarding the T2 subtype, it seems that metabolism and, especially, mitochondria act as the motor of cancer development. T3 analyses point out that nucleoplasm, mitochondria and metabolism, and extracellular matrix nodes could be involved in T3 tumor carcinogenesis. The identified processes were different among proteomics subtypes, suggesting that the molecular motor of the disease is different in each subtype. These differences can have implications for the development of future tailored therapeutic approaches for each PDAC proteomics subtype |
| publishDate |
2022 |
| dc.date.none.fl_str_mv |
2022 2022-05-13 |
| dc.type.none.fl_str_mv |
research article http://purl.org/coar/resource_type/c_2df8fbb1 VoR http://purl.org/coar/version/c_970fb48d4fbd8a85 |
| dc.type.openaire.fl_str_mv |
info:eu-repo/semantics/article |
| format |
article |
| dc.identifier.none.fl_str_mv |
http://hdl.handle.net/10486/707566 https://dx.doi.org/10.3390/cancers14102414 |
| url |
http://hdl.handle.net/10486/707566 https://dx.doi.org/10.3390/cancers14102414 |
| dc.language.none.fl_str_mv |
Inglés eng |
| language_invalid_str_mv |
Inglés |
| language |
eng |
| dc.relation.none.fl_str_mv |
European Commission http://dx.doi.org/10.13039/501100000780 Horizon 2020 Framework Programme 823839 |
| dc.rights.none.fl_str_mv |
open access http://purl.org/coar/access_right/c_abf2 |
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info:eu-repo/semantics/openAccess |
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open access http://purl.org/coar/access_right/c_abf2 |
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openAccess |
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application/pdf |
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MDPI |
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MDPI |
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reponame:Biblos-e Archivo. Repositorio Institucional de la UAM instname:Universidad Autónoma de Madrid |
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Universidad Autónoma de Madrid |
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Biblos-e Archivo. Repositorio Institucional de la UAM |
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Biblos-e Archivo. Repositorio Institucional de la UAM |
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