Cargando…
Deeper insights into transcriptional features of cancer-associated fibroblasts: An integrated meta-analysis of single-cell and bulk RNA-sequencing data
Cancer-associated fibroblasts (CAFs) have long been known as one of the most important players in tumor initiation and progression. Even so, there is an incomplete understanding of the identification of CAFs among tumor microenvironment cells as the list of CAF marker genes varies greatly in the lit...
Autores principales: | , , , , , , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9574913/ https://www.ncbi.nlm.nih.gov/pubmed/36263012 http://dx.doi.org/10.3389/fcell.2022.825014 |
_version_ | 1784811205290885120 |
---|---|
author | Kazakova, Anastasia N. Anufrieva, Ksenia S. Ivanova, Olga M. Shnaider, Polina V. Malyants, Irina K. Aleshikova, Olga I. Slonov, Andrey V. Ashrafyan, Lev A. Babaeva, Nataliya A. Eremeev, Artem V. Boichenko, Veronika S. Lukina, Maria M. Lagarkova, Maria A. Govorun, Vadim M. Shender, Victoria O. Arapidi, Georgij P. |
author_facet | Kazakova, Anastasia N. Anufrieva, Ksenia S. Ivanova, Olga M. Shnaider, Polina V. Malyants, Irina K. Aleshikova, Olga I. Slonov, Andrey V. Ashrafyan, Lev A. Babaeva, Nataliya A. Eremeev, Artem V. Boichenko, Veronika S. Lukina, Maria M. Lagarkova, Maria A. Govorun, Vadim M. Shender, Victoria O. Arapidi, Georgij P. |
author_sort | Kazakova, Anastasia N. |
collection | PubMed |
description | Cancer-associated fibroblasts (CAFs) have long been known as one of the most important players in tumor initiation and progression. Even so, there is an incomplete understanding of the identification of CAFs among tumor microenvironment cells as the list of CAF marker genes varies greatly in the literature, therefore it is imperative to find a better way to identify reliable markers of CAFs. To this end, we summarized a large number of single-cell RNA-sequencing data of multiple tumor types and corresponding normal tissues. As a result, for 9 different types of cancer, we identified CAF-specific gene expression signatures and found 10 protein markers that showed strongly positive staining of tumor stroma according to the analysis of IHC images from the Human Protein Atlas database. Our results give an insight into selecting the most appropriate combination of cancer-associated fibroblast markers. Furthermore, comparison of different approaches for studying differences between cancer-associated and normal fibroblasts (NFs) illustrates the superiority of transcriptome analysis of fibroblasts obtained from fresh tissue samples. Using single-cell RNA sequencing data, we identified common differences in gene expression patterns between normal and cancer-associated fibroblasts, which do not depend on the type of tumor. |
format | Online Article Text |
id | pubmed-9574913 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-95749132022-10-18 Deeper insights into transcriptional features of cancer-associated fibroblasts: An integrated meta-analysis of single-cell and bulk RNA-sequencing data Kazakova, Anastasia N. Anufrieva, Ksenia S. Ivanova, Olga M. Shnaider, Polina V. Malyants, Irina K. Aleshikova, Olga I. Slonov, Andrey V. Ashrafyan, Lev A. Babaeva, Nataliya A. Eremeev, Artem V. Boichenko, Veronika S. Lukina, Maria M. Lagarkova, Maria A. Govorun, Vadim M. Shender, Victoria O. Arapidi, Georgij P. Front Cell Dev Biol Cell and Developmental Biology Cancer-associated fibroblasts (CAFs) have long been known as one of the most important players in tumor initiation and progression. Even so, there is an incomplete understanding of the identification of CAFs among tumor microenvironment cells as the list of CAF marker genes varies greatly in the literature, therefore it is imperative to find a better way to identify reliable markers of CAFs. To this end, we summarized a large number of single-cell RNA-sequencing data of multiple tumor types and corresponding normal tissues. As a result, for 9 different types of cancer, we identified CAF-specific gene expression signatures and found 10 protein markers that showed strongly positive staining of tumor stroma according to the analysis of IHC images from the Human Protein Atlas database. Our results give an insight into selecting the most appropriate combination of cancer-associated fibroblast markers. Furthermore, comparison of different approaches for studying differences between cancer-associated and normal fibroblasts (NFs) illustrates the superiority of transcriptome analysis of fibroblasts obtained from fresh tissue samples. Using single-cell RNA sequencing data, we identified common differences in gene expression patterns between normal and cancer-associated fibroblasts, which do not depend on the type of tumor. Frontiers Media S.A. 2022-10-03 /pmc/articles/PMC9574913/ /pubmed/36263012 http://dx.doi.org/10.3389/fcell.2022.825014 Text en Copyright © 2022 Kazakova, Anufrieva, Ivanova, Shnaider, Malyants, Aleshikova, Slonov, Ashrafyan, Babaeva, Eremeev, Boichenko, Lukina, Lagarkova, Govorun, Shender and Arapidi. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Cell and Developmental Biology Kazakova, Anastasia N. Anufrieva, Ksenia S. Ivanova, Olga M. Shnaider, Polina V. Malyants, Irina K. Aleshikova, Olga I. Slonov, Andrey V. Ashrafyan, Lev A. Babaeva, Nataliya A. Eremeev, Artem V. Boichenko, Veronika S. Lukina, Maria M. Lagarkova, Maria A. Govorun, Vadim M. Shender, Victoria O. Arapidi, Georgij P. Deeper insights into transcriptional features of cancer-associated fibroblasts: An integrated meta-analysis of single-cell and bulk RNA-sequencing data |
title | Deeper insights into transcriptional features of cancer-associated fibroblasts: An integrated meta-analysis of single-cell and bulk RNA-sequencing data |
title_full | Deeper insights into transcriptional features of cancer-associated fibroblasts: An integrated meta-analysis of single-cell and bulk RNA-sequencing data |
title_fullStr | Deeper insights into transcriptional features of cancer-associated fibroblasts: An integrated meta-analysis of single-cell and bulk RNA-sequencing data |
title_full_unstemmed | Deeper insights into transcriptional features of cancer-associated fibroblasts: An integrated meta-analysis of single-cell and bulk RNA-sequencing data |
title_short | Deeper insights into transcriptional features of cancer-associated fibroblasts: An integrated meta-analysis of single-cell and bulk RNA-sequencing data |
title_sort | deeper insights into transcriptional features of cancer-associated fibroblasts: an integrated meta-analysis of single-cell and bulk rna-sequencing data |
topic | Cell and Developmental Biology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9574913/ https://www.ncbi.nlm.nih.gov/pubmed/36263012 http://dx.doi.org/10.3389/fcell.2022.825014 |
work_keys_str_mv | AT kazakovaanastasian deeperinsightsintotranscriptionalfeaturesofcancerassociatedfibroblastsanintegratedmetaanalysisofsinglecellandbulkrnasequencingdata AT anufrievaksenias deeperinsightsintotranscriptionalfeaturesofcancerassociatedfibroblastsanintegratedmetaanalysisofsinglecellandbulkrnasequencingdata AT ivanovaolgam deeperinsightsintotranscriptionalfeaturesofcancerassociatedfibroblastsanintegratedmetaanalysisofsinglecellandbulkrnasequencingdata AT shnaiderpolinav deeperinsightsintotranscriptionalfeaturesofcancerassociatedfibroblastsanintegratedmetaanalysisofsinglecellandbulkrnasequencingdata AT malyantsirinak deeperinsightsintotranscriptionalfeaturesofcancerassociatedfibroblastsanintegratedmetaanalysisofsinglecellandbulkrnasequencingdata AT aleshikovaolgai deeperinsightsintotranscriptionalfeaturesofcancerassociatedfibroblastsanintegratedmetaanalysisofsinglecellandbulkrnasequencingdata AT slonovandreyv deeperinsightsintotranscriptionalfeaturesofcancerassociatedfibroblastsanintegratedmetaanalysisofsinglecellandbulkrnasequencingdata AT ashrafyanleva deeperinsightsintotranscriptionalfeaturesofcancerassociatedfibroblastsanintegratedmetaanalysisofsinglecellandbulkrnasequencingdata AT babaevanataliyaa deeperinsightsintotranscriptionalfeaturesofcancerassociatedfibroblastsanintegratedmetaanalysisofsinglecellandbulkrnasequencingdata AT eremeevartemv deeperinsightsintotranscriptionalfeaturesofcancerassociatedfibroblastsanintegratedmetaanalysisofsinglecellandbulkrnasequencingdata AT boichenkoveronikas deeperinsightsintotranscriptionalfeaturesofcancerassociatedfibroblastsanintegratedmetaanalysisofsinglecellandbulkrnasequencingdata AT lukinamariam deeperinsightsintotranscriptionalfeaturesofcancerassociatedfibroblastsanintegratedmetaanalysisofsinglecellandbulkrnasequencingdata AT lagarkovamariaa deeperinsightsintotranscriptionalfeaturesofcancerassociatedfibroblastsanintegratedmetaanalysisofsinglecellandbulkrnasequencingdata AT govorunvadimm deeperinsightsintotranscriptionalfeaturesofcancerassociatedfibroblastsanintegratedmetaanalysisofsinglecellandbulkrnasequencingdata AT shendervictoriao deeperinsightsintotranscriptionalfeaturesofcancerassociatedfibroblastsanintegratedmetaanalysisofsinglecellandbulkrnasequencingdata AT arapidigeorgijp deeperinsightsintotranscriptionalfeaturesofcancerassociatedfibroblastsanintegratedmetaanalysisofsinglecellandbulkrnasequencingdata |