English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

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

Safrastyan, A., zu Siederdissen, C. H., & Wollny, D. (2023). Decoding cell-type contributions to the cfRNA transcriptomic landscape of liver cancer. Human Genomics, 17(1): 90. doi:10.1186/s40246-023-00537-w.

Item is

Files

show Files
hide Files
:
Safrastyan_Decoding_HumGen_2023.pdf (Publisher version), 3MB
Name:
Safrastyan_Decoding_HumGen_2023.pdf
Description:
-
OA-Status:
Gold
Visibility:
Public
MIME-Type / Checksum:
application/pdf / [MD5]
Technical Metadata:
Copyright Date:
2023
Copyright Info:
-

Locators

show

Creators

show
hide
 Creators:
Safrastyan, Aram, Author
zu Siederdissen, Christian Höner, Author
Wollny, Damian1, Author                 
Affiliations:
1Single Cell Genomics, Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology, Max Planck Society, ou_2173644              

Content

show
hide
Free keywords: Cell-free RNA; Cellular deconvolution; Liquid biopsy; Liver cancer; Modeling; Single-cell sequencing
 Abstract: 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. © 2023, BioMed Central Ltd., part of Springer Nature.

Details

show
hide
Language(s): eng - English
 Dates: 2023-10-052023-12
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1186/s40246-023-00537-w
 Degree: -

Event

show

Legal Case

show

Project information

show

Source 1

show
hide
Title: Human Genomics
Source Genre: Journal
 Creator(s):
Affiliations:
Publ. Info: -
Pages: - Volume / Issue: 17 (1) Sequence Number: 90 Start / End Page: - Identifier: ISSN: 1479-7364