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Decoding cell-type contributions to the cfRNA transcriptomic landscape of liver cancer

BACKGROUND: Liquid biopsy, particularly cell-free RNA (cfRNA), has emerged as a promising non-invasive diagnostic tool for various diseases, including cancer, due to its accessibility and the wealth of information it provides. A key area of interest is the composition and cellular origin of cfRNA in...

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Autores principales: Safrastyan, Aram, zu Siederdissen, Christian Höner, Wollny, Damian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10552294/
https://www.ncbi.nlm.nih.gov/pubmed/37798661
http://dx.doi.org/10.1186/s40246-023-00537-w
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author Safrastyan, Aram
zu Siederdissen, Christian Höner
Wollny, Damian
author_facet Safrastyan, Aram
zu Siederdissen, Christian Höner
Wollny, Damian
author_sort Safrastyan, Aram
collection PubMed
description BACKGROUND: Liquid biopsy, particularly cell-free RNA (cfRNA), has emerged as a promising non-invasive diagnostic tool for various diseases, including cancer, due to its accessibility and the wealth of information it provides. A key area of interest is the composition and cellular origin of cfRNA in the blood and the alterations in the cfRNA transcriptomic landscape during carcinogenesis. Investigating these changes can offer insights into the manifestations of tissue alterations in the blood, potentially leading to more effective diagnostic strategies. However, the consistency of these findings across different studies and their clinical utility remains to be fully elucidated, highlighting the need for further research in this area. RESULTS: In this study, we analyzed over 350 blood samples from four distinct studies, investigating the cell type contributions to the cfRNA transcriptomic landscape in liver cancer. We found that an increase in hepatocyte proportions in the blood is a consistent feature across most studies and can be effectively utilized for classifying cancer and healthy samples. Moreover, our analysis revealed that in addition to hepatocytes, liver endothelial cell signatures are also prominent in the observed changes. By comparing the classification performance of cellular proportions to established markers, we demonstrated that cellular proportions could distinguish cancer from healthy samples as effectively as existing markers and can even enhance classification when used in combination with these markers. CONCLUSIONS: Our comprehensive analysis of liver cell-type composition changes in blood revealed robust effects that help classify cancer from healthy samples. This is especially noteworthy, considering the heterogeneous nature of datasets and the etiological distinctions of samples. Furthermore, the observed differences in results across studies underscore the importance of integrative and comparative approaches in the future research to determine the consistency and robustness of findings. This study contributes to the understanding of cfRNA composition in liver cancer and highlights the potential of cellular deconvolution in liquid biopsy. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40246-023-00537-w.
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spelling pubmed-105522942023-10-06 Decoding cell-type contributions to the cfRNA transcriptomic landscape of liver cancer Safrastyan, Aram zu Siederdissen, Christian Höner Wollny, Damian Hum Genomics Research BACKGROUND: Liquid biopsy, particularly cell-free RNA (cfRNA), has emerged as a promising non-invasive diagnostic tool for various diseases, including cancer, due to its accessibility and the wealth of information it provides. A key area of interest is the composition and cellular origin of cfRNA in the blood and the alterations in the cfRNA transcriptomic landscape during carcinogenesis. Investigating these changes can offer insights into the manifestations of tissue alterations in the blood, potentially leading to more effective diagnostic strategies. However, the consistency of these findings across different studies and their clinical utility remains to be fully elucidated, highlighting the need for further research in this area. RESULTS: In this study, we analyzed over 350 blood samples from four distinct studies, investigating the cell type contributions to the cfRNA transcriptomic landscape in liver cancer. We found that an increase in hepatocyte proportions in the blood is a consistent feature across most studies and can be effectively utilized for classifying cancer and healthy samples. Moreover, our analysis revealed that in addition to hepatocytes, liver endothelial cell signatures are also prominent in the observed changes. By comparing the classification performance of cellular proportions to established markers, we demonstrated that cellular proportions could distinguish cancer from healthy samples as effectively as existing markers and can even enhance classification when used in combination with these markers. CONCLUSIONS: Our comprehensive analysis of liver cell-type composition changes in blood revealed robust effects that help classify cancer from healthy samples. This is especially noteworthy, considering the heterogeneous nature of datasets and the etiological distinctions of samples. Furthermore, the observed differences in results across studies underscore the importance of integrative and comparative approaches in the future research to determine the consistency and robustness of findings. This study contributes to the understanding of cfRNA composition in liver cancer and highlights the potential of cellular deconvolution in liquid biopsy. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40246-023-00537-w. BioMed Central 2023-10-05 /pmc/articles/PMC10552294/ /pubmed/37798661 http://dx.doi.org/10.1186/s40246-023-00537-w 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 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/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Safrastyan, Aram
zu Siederdissen, Christian Höner
Wollny, Damian
Decoding cell-type contributions to the cfRNA transcriptomic landscape of liver cancer
title Decoding cell-type contributions to the cfRNA transcriptomic landscape of liver cancer
title_full Decoding cell-type contributions to the cfRNA transcriptomic landscape of liver cancer
title_fullStr Decoding cell-type contributions to the cfRNA transcriptomic landscape of liver cancer
title_full_unstemmed Decoding cell-type contributions to the cfRNA transcriptomic landscape of liver cancer
title_short Decoding cell-type contributions to the cfRNA transcriptomic landscape of liver cancer
title_sort decoding cell-type contributions to the cfrna transcriptomic landscape of liver cancer
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10552294/
https://www.ncbi.nlm.nih.gov/pubmed/37798661
http://dx.doi.org/10.1186/s40246-023-00537-w
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