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Implications of prognosis-associated genes in pancreatic tumor metastasis: lessons from global studies in bioinformatics
Pancreatic cancer (PC) is a highly lethal malignancy with a 5-year survival rate of 10%. The occurrence of metastasis, among other hallmarks, is the main contributor to its poor prognosis. Consequently, the elucidation of metastatic genes involved in the aggressive nature of the disease and its poor...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8556170/ https://www.ncbi.nlm.nih.gov/pubmed/34591244 http://dx.doi.org/10.1007/s10555-021-09991-1 |
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author | Kisling, Sophia G. Natarajan, Gopalakrishnan Pothuraju, Ramesh Shah, Ashu Batra, Surinder K. Kaur, Sukhwinder |
author_facet | Kisling, Sophia G. Natarajan, Gopalakrishnan Pothuraju, Ramesh Shah, Ashu Batra, Surinder K. Kaur, Sukhwinder |
author_sort | Kisling, Sophia G. |
collection | PubMed |
description | Pancreatic cancer (PC) is a highly lethal malignancy with a 5-year survival rate of 10%. The occurrence of metastasis, among other hallmarks, is the main contributor to its poor prognosis. Consequently, the elucidation of metastatic genes involved in the aggressive nature of the disease and its poor prognosis will result in the development of new treatment modalities for improved management of PC. There is a deep interest in understanding underlying disease pathology, identifying key prognostic genes, and genes associated with metastasis. Computational approaches, which have become increasingly relevant over the last decade, are commonly used to explore such interests. This review aims to address global studies that have employed global approaches to identify prognostic and metastatic genes, while highlighting their methods and limitations. A panel of 48 prognostic genes were identified across these studies, but only five, including ANLN, ARNTL2, PLAU, TOP2A, and VCAN, were validated in multiple studies and associated with metastasis. Their association with metastasis has been further explored here, and the implications of these genes in the metastatic cascade have been interpreted. |
format | Online Article Text |
id | pubmed-8556170 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-85561702021-11-04 Implications of prognosis-associated genes in pancreatic tumor metastasis: lessons from global studies in bioinformatics Kisling, Sophia G. Natarajan, Gopalakrishnan Pothuraju, Ramesh Shah, Ashu Batra, Surinder K. Kaur, Sukhwinder Cancer Metastasis Rev Article Pancreatic cancer (PC) is a highly lethal malignancy with a 5-year survival rate of 10%. The occurrence of metastasis, among other hallmarks, is the main contributor to its poor prognosis. Consequently, the elucidation of metastatic genes involved in the aggressive nature of the disease and its poor prognosis will result in the development of new treatment modalities for improved management of PC. There is a deep interest in understanding underlying disease pathology, identifying key prognostic genes, and genes associated with metastasis. Computational approaches, which have become increasingly relevant over the last decade, are commonly used to explore such interests. This review aims to address global studies that have employed global approaches to identify prognostic and metastatic genes, while highlighting their methods and limitations. A panel of 48 prognostic genes were identified across these studies, but only five, including ANLN, ARNTL2, PLAU, TOP2A, and VCAN, were validated in multiple studies and associated with metastasis. Their association with metastasis has been further explored here, and the implications of these genes in the metastatic cascade have been interpreted. Springer US 2021-09-30 2021 /pmc/articles/PMC8556170/ /pubmed/34591244 http://dx.doi.org/10.1007/s10555-021-09991-1 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/) . |
spellingShingle | Article Kisling, Sophia G. Natarajan, Gopalakrishnan Pothuraju, Ramesh Shah, Ashu Batra, Surinder K. Kaur, Sukhwinder Implications of prognosis-associated genes in pancreatic tumor metastasis: lessons from global studies in bioinformatics |
title | Implications of prognosis-associated genes in pancreatic tumor metastasis: lessons from global studies in bioinformatics |
title_full | Implications of prognosis-associated genes in pancreatic tumor metastasis: lessons from global studies in bioinformatics |
title_fullStr | Implications of prognosis-associated genes in pancreatic tumor metastasis: lessons from global studies in bioinformatics |
title_full_unstemmed | Implications of prognosis-associated genes in pancreatic tumor metastasis: lessons from global studies in bioinformatics |
title_short | Implications of prognosis-associated genes in pancreatic tumor metastasis: lessons from global studies in bioinformatics |
title_sort | implications of prognosis-associated genes in pancreatic tumor metastasis: lessons from global studies in bioinformatics |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8556170/ https://www.ncbi.nlm.nih.gov/pubmed/34591244 http://dx.doi.org/10.1007/s10555-021-09991-1 |
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