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Defining incidence and complications of fibrolamellar liver cancer through tiered computational analysis of clinical data
The incidence and biochemical consequences of rare tumor subtypes are often hard to study. Fibrolamellar liver cancer (FLC) is a rare malignancy affecting adolescents and young adults. To better characterize the incidence and biochemical consequences of this disease, we combined a comprehensive anal...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10034241/ https://www.ncbi.nlm.nih.gov/pubmed/36959495 http://dx.doi.org/10.1038/s41698-023-00371-2 |
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author | Zack, Travis Losert, Kurt P. Maisel, Samantha M. Wild, Jennifer Yaqubie, Amin Herman, Michael Knox, Jennifer J. Mayer, Robert J. Venook, Alan P. Butte, Atul O’Neill, Allison F. Abou-Alfa, Ghassan K. Gordan, John D. |
author_facet | Zack, Travis Losert, Kurt P. Maisel, Samantha M. Wild, Jennifer Yaqubie, Amin Herman, Michael Knox, Jennifer J. Mayer, Robert J. Venook, Alan P. Butte, Atul O’Neill, Allison F. Abou-Alfa, Ghassan K. Gordan, John D. |
author_sort | Zack, Travis |
collection | PubMed |
description | The incidence and biochemical consequences of rare tumor subtypes are often hard to study. Fibrolamellar liver cancer (FLC) is a rare malignancy affecting adolescents and young adults. To better characterize the incidence and biochemical consequences of this disease, we combined a comprehensive analysis of the electronic medical record and national payer data and found that FLC incidence is likely five to eight times higher than previous estimates. By employing unsupervised learning on clinical laboratory data from patients with hyperammonemia, we find that FLC-associated hyperammonemia mirrors metabolic dysregulation in urea cycle disorders. Our findings demonstrate that advanced computational analysis of rich clinical datasets can provide key clinical and biochemical insights into rare cancers. |
format | Online Article Text |
id | pubmed-10034241 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-100342412023-03-23 Defining incidence and complications of fibrolamellar liver cancer through tiered computational analysis of clinical data Zack, Travis Losert, Kurt P. Maisel, Samantha M. Wild, Jennifer Yaqubie, Amin Herman, Michael Knox, Jennifer J. Mayer, Robert J. Venook, Alan P. Butte, Atul O’Neill, Allison F. Abou-Alfa, Ghassan K. Gordan, John D. NPJ Precis Oncol Brief Communication The incidence and biochemical consequences of rare tumor subtypes are often hard to study. Fibrolamellar liver cancer (FLC) is a rare malignancy affecting adolescents and young adults. To better characterize the incidence and biochemical consequences of this disease, we combined a comprehensive analysis of the electronic medical record and national payer data and found that FLC incidence is likely five to eight times higher than previous estimates. By employing unsupervised learning on clinical laboratory data from patients with hyperammonemia, we find that FLC-associated hyperammonemia mirrors metabolic dysregulation in urea cycle disorders. Our findings demonstrate that advanced computational analysis of rich clinical datasets can provide key clinical and biochemical insights into rare cancers. Nature Publishing Group UK 2023-03-23 /pmc/articles/PMC10034241/ /pubmed/36959495 http://dx.doi.org/10.1038/s41698-023-00371-2 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Brief Communication Zack, Travis Losert, Kurt P. Maisel, Samantha M. Wild, Jennifer Yaqubie, Amin Herman, Michael Knox, Jennifer J. Mayer, Robert J. Venook, Alan P. Butte, Atul O’Neill, Allison F. Abou-Alfa, Ghassan K. Gordan, John D. Defining incidence and complications of fibrolamellar liver cancer through tiered computational analysis of clinical data |
title | Defining incidence and complications of fibrolamellar liver cancer through tiered computational analysis of clinical data |
title_full | Defining incidence and complications of fibrolamellar liver cancer through tiered computational analysis of clinical data |
title_fullStr | Defining incidence and complications of fibrolamellar liver cancer through tiered computational analysis of clinical data |
title_full_unstemmed | Defining incidence and complications of fibrolamellar liver cancer through tiered computational analysis of clinical data |
title_short | Defining incidence and complications of fibrolamellar liver cancer through tiered computational analysis of clinical data |
title_sort | defining incidence and complications of fibrolamellar liver cancer through tiered computational analysis of clinical data |
topic | Brief Communication |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10034241/ https://www.ncbi.nlm.nih.gov/pubmed/36959495 http://dx.doi.org/10.1038/s41698-023-00371-2 |
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