Genomic predictive model for recurrence and metastasis development in head and neck squamous cell carcinoma patients
| Autor(a) principal: | |
|---|---|
| Data de Publicação: | 2017 |
| Outros Autores: | , , , , , , , |
| Tipo de documento: | Artigo |
| Idioma: | eng |
| Título da fonte: | Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
| Texto Completo: | https://hdl.handle.net/10316/108378 https://doi.org/10.1038/s41598-017-14377-x |
Resumo: | The head and neck squamous cell carcinoma (HNSCC) population consists mainly of high-risk for recurrence and locally advanced stage patients. Increased knowledge of the HNSCC genomic profile can improve early diagnosis and treatment outcomes. The development of models to identify consistent genomic patterns that distinguish HNSCC patients that will recur and/or develop metastasis after treatment is of utmost importance to decrease mortality and improve survival rates. In this study, we used array comparative genomic hybridization data from HNSCC patients to implement a robust model to predict HNSCC recurrence/metastasis. This predictive model showed a good accuracy (>80%) and was validated in an independent population from TCGA data portal. This predictive genomic model comprises chromosomal regions from 5p, 6p, 8p, 9p, 11q, 12q, 15q and 17p, where several upstream and downstream members of signaling pathways that lead to an increase in cell proliferation and invasion are mapped. The introduction of genomic predictive models in clinical practice might contribute to a more individualized clinical management of the HNSCC patients, reducing recurrences and improving patients' quality of life. The power of this genomic model to predict the recurrence and metastases development should be evaluated in other HNSCC populations. |
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Genomic predictive model for recurrence and metastasis development in head and neck squamous cell carcinoma patientsAdultChromosomes, HumanCohort StudiesComparative Genomic HybridizationFemaleHumansMaleMiddle AgedNeoplasm MetastasisPrognosisRecurrenceSquamous Cell Carcinoma of Head and NeckGenomicsModels, StatisticalThe head and neck squamous cell carcinoma (HNSCC) population consists mainly of high-risk for recurrence and locally advanced stage patients. Increased knowledge of the HNSCC genomic profile can improve early diagnosis and treatment outcomes. The development of models to identify consistent genomic patterns that distinguish HNSCC patients that will recur and/or develop metastasis after treatment is of utmost importance to decrease mortality and improve survival rates. In this study, we used array comparative genomic hybridization data from HNSCC patients to implement a robust model to predict HNSCC recurrence/metastasis. This predictive model showed a good accuracy (>80%) and was validated in an independent population from TCGA data portal. This predictive genomic model comprises chromosomal regions from 5p, 6p, 8p, 9p, 11q, 12q, 15q and 17p, where several upstream and downstream members of signaling pathways that lead to an increase in cell proliferation and invasion are mapped. The introduction of genomic predictive models in clinical practice might contribute to a more individualized clinical management of the HNSCC patients, reducing recurrences and improving patients' quality of life. The power of this genomic model to predict the recurrence and metastases development should be evaluated in other HNSCC populations.Ribeiro I.P. is a recipient of a PhD fellowship (SFRH/BD/52290/2013) from the Portuguese Foundation for Science and Technology. Tis work was in part supported by CIMAGO (Center of Investigation on Environment Genetics and Oncobiology - Faculty of Medicine, University of Coimbra).Springer Nature2017-10-24info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttps://hdl.handle.net/10316/108378https://hdl.handle.net/10316/108378https://doi.org/10.1038/s41598-017-14377-xeng2045-2322Ribeiro, Ilda PatríciaCaramelo, FranciscoEsteves, LuísaMenoita, JoanaMarques, FranciscoBarroso, LeonorMiguéis, JorgeMelo, Joana BarbosaCarreira, Isabel Marquesinfo:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2025-02-25T16:21:15Zoai:estudogeral.uc.pt:10316/108378Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-29T05:59:45.461642Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse |
| dc.title.none.fl_str_mv |
Genomic predictive model for recurrence and metastasis development in head and neck squamous cell carcinoma patients |
| title |
Genomic predictive model for recurrence and metastasis development in head and neck squamous cell carcinoma patients |
| spellingShingle |
Genomic predictive model for recurrence and metastasis development in head and neck squamous cell carcinoma patients Ribeiro, Ilda Patrícia Adult Chromosomes, Human Cohort Studies Comparative Genomic Hybridization Female Humans Male Middle Aged Neoplasm Metastasis Prognosis Recurrence Squamous Cell Carcinoma of Head and Neck Genomics Models, Statistical |
| title_short |
Genomic predictive model for recurrence and metastasis development in head and neck squamous cell carcinoma patients |
| title_full |
Genomic predictive model for recurrence and metastasis development in head and neck squamous cell carcinoma patients |
| title_fullStr |
Genomic predictive model for recurrence and metastasis development in head and neck squamous cell carcinoma patients |
| title_full_unstemmed |
Genomic predictive model for recurrence and metastasis development in head and neck squamous cell carcinoma patients |
| title_sort |
Genomic predictive model for recurrence and metastasis development in head and neck squamous cell carcinoma patients |
| author |
Ribeiro, Ilda Patrícia |
| author_facet |
Ribeiro, Ilda Patrícia Caramelo, Francisco Esteves, Luísa Menoita, Joana Marques, Francisco Barroso, Leonor Miguéis, Jorge Melo, Joana Barbosa Carreira, Isabel Marques |
| author_role |
author |
| author2 |
Caramelo, Francisco Esteves, Luísa Menoita, Joana Marques, Francisco Barroso, Leonor Miguéis, Jorge Melo, Joana Barbosa Carreira, Isabel Marques |
| author2_role |
author author author author author author author author |
| dc.contributor.author.fl_str_mv |
Ribeiro, Ilda Patrícia Caramelo, Francisco Esteves, Luísa Menoita, Joana Marques, Francisco Barroso, Leonor Miguéis, Jorge Melo, Joana Barbosa Carreira, Isabel Marques |
| dc.subject.por.fl_str_mv |
Adult Chromosomes, Human Cohort Studies Comparative Genomic Hybridization Female Humans Male Middle Aged Neoplasm Metastasis Prognosis Recurrence Squamous Cell Carcinoma of Head and Neck Genomics Models, Statistical |
| topic |
Adult Chromosomes, Human Cohort Studies Comparative Genomic Hybridization Female Humans Male Middle Aged Neoplasm Metastasis Prognosis Recurrence Squamous Cell Carcinoma of Head and Neck Genomics Models, Statistical |
| description |
The head and neck squamous cell carcinoma (HNSCC) population consists mainly of high-risk for recurrence and locally advanced stage patients. Increased knowledge of the HNSCC genomic profile can improve early diagnosis and treatment outcomes. The development of models to identify consistent genomic patterns that distinguish HNSCC patients that will recur and/or develop metastasis after treatment is of utmost importance to decrease mortality and improve survival rates. In this study, we used array comparative genomic hybridization data from HNSCC patients to implement a robust model to predict HNSCC recurrence/metastasis. This predictive model showed a good accuracy (>80%) and was validated in an independent population from TCGA data portal. This predictive genomic model comprises chromosomal regions from 5p, 6p, 8p, 9p, 11q, 12q, 15q and 17p, where several upstream and downstream members of signaling pathways that lead to an increase in cell proliferation and invasion are mapped. The introduction of genomic predictive models in clinical practice might contribute to a more individualized clinical management of the HNSCC patients, reducing recurrences and improving patients' quality of life. The power of this genomic model to predict the recurrence and metastases development should be evaluated in other HNSCC populations. |
| publishDate |
2017 |
| dc.date.none.fl_str_mv |
2017-10-24 |
| dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
| dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
| format |
article |
| status_str |
publishedVersion |
| dc.identifier.uri.fl_str_mv |
https://hdl.handle.net/10316/108378 https://hdl.handle.net/10316/108378 https://doi.org/10.1038/s41598-017-14377-x |
| url |
https://hdl.handle.net/10316/108378 https://doi.org/10.1038/s41598-017-14377-x |
| dc.language.iso.fl_str_mv |
eng |
| language |
eng |
| dc.relation.none.fl_str_mv |
2045-2322 |
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info:eu-repo/semantics/openAccess |
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openAccess |
| dc.publisher.none.fl_str_mv |
Springer Nature |
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Springer Nature |
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reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia instacron:RCAAP |
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Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
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Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia |
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