Cargando…

Analysis of the Effect of SNAI Family in Breast Cancer and Immune Cell

SNAI family members are transcriptional repressors that induce epithelial-mesenchymal transition during biological development. SNAIs both have tumor-promoting and tumor-inhibiting effect. There are key regulatory effects on tumor onset and development, and patient prognosis in infiltrations of immu...

Descripción completa

Detalles Bibliográficos
Autores principales: Tu, Yifei, Fang, Pengfei, Zhang, Long, Sun, Kewang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9309217/
https://www.ncbi.nlm.nih.gov/pubmed/35898399
http://dx.doi.org/10.3389/fcell.2022.906885
_version_ 1784753108006469632
author Tu, Yifei
Fang, Pengfei
Zhang, Long
Sun, Kewang
author_facet Tu, Yifei
Fang, Pengfei
Zhang, Long
Sun, Kewang
author_sort Tu, Yifei
collection PubMed
description SNAI family members are transcriptional repressors that induce epithelial-mesenchymal transition during biological development. SNAIs both have tumor-promoting and tumor-inhibiting effect. There are key regulatory effects on tumor onset and development, and patient prognosis in infiltrations of immune cell and tumor microenvironmental changes. However, the relationships between SNAIs and immune cell infiltration remain unclear. We comprehensively analyzed the roles of SNAIs in cancer. We used Oncomine and TCGA data to analyze pan-cancer SNAI transcript levels. By analyzing UALCAN data, we found correlations between SNAI transcript levels and breast cancer patient characteristics. Kaplan–Meier plotter analysis revealed that SNAI1 and SNAI2 have a bad prognosis, whereas SNAI3 is the opposite. Analysis using the cBio Cancer Genomics Portal revealed alterations in SNAIs in breast cancer subtypes. Gene Ontology analysis and gene set enrichment analysis were used to analyze differentially expressed genes related to SNAI proteins in breast cancer. We used TIMER to analyze the effects of SNAI transcript levels, mutations, methylation levels, and gene copy number in the infiltration of immune cell. Further, we found the relationships between immune cell infiltration, SNAI expression levels, and patient outcomes. To explore how SNAI proteins affect immune cell, we further studied the correlations between immunomodulator expression, chemokine expression, and SNAI expression. The results showed that SNAI protein levels were correlated with the expression of several immunomodulators and chemokines. Through analysis of PharmacoDB data, we identified antitumor drugs related to SNAI family members and analyzed their IC50 effects on various breast cancer cell lines. In summary, our study revealed that SNAI family members regulate different immune cells infiltrations by gene copy number, mutation, methylation, and expression level. SNAI3 and SNIA1/2 have opposite regulatory effects. They all play a key role in tumor development and immune cell infiltration, and can provide a potential target for drug therapy.
format Online
Article
Text
id pubmed-9309217
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-93092172022-07-26 Analysis of the Effect of SNAI Family in Breast Cancer and Immune Cell Tu, Yifei Fang, Pengfei Zhang, Long Sun, Kewang Front Cell Dev Biol Cell and Developmental Biology SNAI family members are transcriptional repressors that induce epithelial-mesenchymal transition during biological development. SNAIs both have tumor-promoting and tumor-inhibiting effect. There are key regulatory effects on tumor onset and development, and patient prognosis in infiltrations of immune cell and tumor microenvironmental changes. However, the relationships between SNAIs and immune cell infiltration remain unclear. We comprehensively analyzed the roles of SNAIs in cancer. We used Oncomine and TCGA data to analyze pan-cancer SNAI transcript levels. By analyzing UALCAN data, we found correlations between SNAI transcript levels and breast cancer patient characteristics. Kaplan–Meier plotter analysis revealed that SNAI1 and SNAI2 have a bad prognosis, whereas SNAI3 is the opposite. Analysis using the cBio Cancer Genomics Portal revealed alterations in SNAIs in breast cancer subtypes. Gene Ontology analysis and gene set enrichment analysis were used to analyze differentially expressed genes related to SNAI proteins in breast cancer. We used TIMER to analyze the effects of SNAI transcript levels, mutations, methylation levels, and gene copy number in the infiltration of immune cell. Further, we found the relationships between immune cell infiltration, SNAI expression levels, and patient outcomes. To explore how SNAI proteins affect immune cell, we further studied the correlations between immunomodulator expression, chemokine expression, and SNAI expression. The results showed that SNAI protein levels were correlated with the expression of several immunomodulators and chemokines. Through analysis of PharmacoDB data, we identified antitumor drugs related to SNAI family members and analyzed their IC50 effects on various breast cancer cell lines. In summary, our study revealed that SNAI family members regulate different immune cells infiltrations by gene copy number, mutation, methylation, and expression level. SNAI3 and SNIA1/2 have opposite regulatory effects. They all play a key role in tumor development and immune cell infiltration, and can provide a potential target for drug therapy. Frontiers Media S.A. 2022-07-08 /pmc/articles/PMC9309217/ /pubmed/35898399 http://dx.doi.org/10.3389/fcell.2022.906885 Text en Copyright © 2022 Tu, Fang, Zhang and Sun. 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
Tu, Yifei
Fang, Pengfei
Zhang, Long
Sun, Kewang
Analysis of the Effect of SNAI Family in Breast Cancer and Immune Cell
title Analysis of the Effect of SNAI Family in Breast Cancer and Immune Cell
title_full Analysis of the Effect of SNAI Family in Breast Cancer and Immune Cell
title_fullStr Analysis of the Effect of SNAI Family in Breast Cancer and Immune Cell
title_full_unstemmed Analysis of the Effect of SNAI Family in Breast Cancer and Immune Cell
title_short Analysis of the Effect of SNAI Family in Breast Cancer and Immune Cell
title_sort analysis of the effect of snai family in breast cancer and immune cell
topic Cell and Developmental Biology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9309217/
https://www.ncbi.nlm.nih.gov/pubmed/35898399
http://dx.doi.org/10.3389/fcell.2022.906885
work_keys_str_mv AT tuyifei analysisoftheeffectofsnaifamilyinbreastcancerandimmunecell
AT fangpengfei analysisoftheeffectofsnaifamilyinbreastcancerandimmunecell
AT zhanglong analysisoftheeffectofsnaifamilyinbreastcancerandimmunecell
AT sunkewang analysisoftheeffectofsnaifamilyinbreastcancerandimmunecell