Cargando…
Analysis of Tumor Glycosylation Characteristics and Implications for Immune Checkpoint Inhibitor’s Efficacy for Breast Cancer
The alterations of glycosylation, which is a common post-translational modification of proteins, have been acknowledged as key events in breast cancer (BC) oncogenesis and progression. The aberrant expression of glycosyltransferases leads to aberrant glycosylation patterns, posing the diagnostic pot...
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/PMC9013822/ https://www.ncbi.nlm.nih.gov/pubmed/35444644 http://dx.doi.org/10.3389/fimmu.2022.830158 |
_version_ | 1784688079400861696 |
---|---|
author | Lv, Wenchang Yu, Honghao Han, Mei Tan, Yufang Wu, Min Zhang, Jun Wu, Yiping Zhang, Qi |
author_facet | Lv, Wenchang Yu, Honghao Han, Mei Tan, Yufang Wu, Min Zhang, Jun Wu, Yiping Zhang, Qi |
author_sort | Lv, Wenchang |
collection | PubMed |
description | The alterations of glycosylation, which is a common post-translational modification of proteins, have been acknowledged as key events in breast cancer (BC) oncogenesis and progression. The aberrant expression of glycosyltransferases leads to aberrant glycosylation patterns, posing the diagnostic potential in BC outcomes. The present study aims to establish a glycosyltransferase-based signature to predict BC prognosis and response to immune checkpoint inhibitors. We firstly screened 9 glycosyltransferase genes from The Cancer Genome Atlas (TCGA) database and accordingly established a glyco-signature for predicting the prognosis in BC patients. Patients with BC were successfully divided into high-risk and low-risk groups based on the median cutoff point for risk scores in this signature. Next, the combinational analyses of univariate and multivariate Cox regression, Kaplan–Meier, and receiver operating characteristic (ROC) curves were used to prove that this glyco-signature possessed excellent predictive performance for prognosis of BC patients, as the high-risk group possessed worse outcomes, in comparison to the low-risk group. Additionally, the Gene Set Enrichment Analysis (GSEA) and immunologic infiltration analysis were adopted and indicated that there was a more immunosuppressive state in the high-risk group than that in the low-risk group. The clinical sample validation verified that glycosyltransferase genes were differentially expressed in patients in the low- and high-risk groups, while the biomarkers of antitumor M1 macrophages were increased and N-glycosyltransferase STT3A decreased in the low-risk group. The final in vitro assay showed that the silencing of STT3A suppressed the proliferation and migration of BC cells. Collectively, our well-constructed glyco-signature is able to distinguish the high- and low-risk groups and accordingly predict BC prognosis, which will synergistically promote the prognosis evaluation and provide new immunotherapeutic targets for combating BC. |
format | Online Article Text |
id | pubmed-9013822 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-90138222022-04-19 Analysis of Tumor Glycosylation Characteristics and Implications for Immune Checkpoint Inhibitor’s Efficacy for Breast Cancer Lv, Wenchang Yu, Honghao Han, Mei Tan, Yufang Wu, Min Zhang, Jun Wu, Yiping Zhang, Qi Front Immunol Immunology The alterations of glycosylation, which is a common post-translational modification of proteins, have been acknowledged as key events in breast cancer (BC) oncogenesis and progression. The aberrant expression of glycosyltransferases leads to aberrant glycosylation patterns, posing the diagnostic potential in BC outcomes. The present study aims to establish a glycosyltransferase-based signature to predict BC prognosis and response to immune checkpoint inhibitors. We firstly screened 9 glycosyltransferase genes from The Cancer Genome Atlas (TCGA) database and accordingly established a glyco-signature for predicting the prognosis in BC patients. Patients with BC were successfully divided into high-risk and low-risk groups based on the median cutoff point for risk scores in this signature. Next, the combinational analyses of univariate and multivariate Cox regression, Kaplan–Meier, and receiver operating characteristic (ROC) curves were used to prove that this glyco-signature possessed excellent predictive performance for prognosis of BC patients, as the high-risk group possessed worse outcomes, in comparison to the low-risk group. Additionally, the Gene Set Enrichment Analysis (GSEA) and immunologic infiltration analysis were adopted and indicated that there was a more immunosuppressive state in the high-risk group than that in the low-risk group. The clinical sample validation verified that glycosyltransferase genes were differentially expressed in patients in the low- and high-risk groups, while the biomarkers of antitumor M1 macrophages were increased and N-glycosyltransferase STT3A decreased in the low-risk group. The final in vitro assay showed that the silencing of STT3A suppressed the proliferation and migration of BC cells. Collectively, our well-constructed glyco-signature is able to distinguish the high- and low-risk groups and accordingly predict BC prognosis, which will synergistically promote the prognosis evaluation and provide new immunotherapeutic targets for combating BC. Frontiers Media S.A. 2022-04-04 /pmc/articles/PMC9013822/ /pubmed/35444644 http://dx.doi.org/10.3389/fimmu.2022.830158 Text en Copyright © 2022 Lv, Yu, Han, Tan, Wu, Zhang, Wu and Zhang 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 | Immunology Lv, Wenchang Yu, Honghao Han, Mei Tan, Yufang Wu, Min Zhang, Jun Wu, Yiping Zhang, Qi Analysis of Tumor Glycosylation Characteristics and Implications for Immune Checkpoint Inhibitor’s Efficacy for Breast Cancer |
title | Analysis of Tumor Glycosylation Characteristics and Implications for Immune Checkpoint Inhibitor’s Efficacy for Breast Cancer |
title_full | Analysis of Tumor Glycosylation Characteristics and Implications for Immune Checkpoint Inhibitor’s Efficacy for Breast Cancer |
title_fullStr | Analysis of Tumor Glycosylation Characteristics and Implications for Immune Checkpoint Inhibitor’s Efficacy for Breast Cancer |
title_full_unstemmed | Analysis of Tumor Glycosylation Characteristics and Implications for Immune Checkpoint Inhibitor’s Efficacy for Breast Cancer |
title_short | Analysis of Tumor Glycosylation Characteristics and Implications for Immune Checkpoint Inhibitor’s Efficacy for Breast Cancer |
title_sort | analysis of tumor glycosylation characteristics and implications for immune checkpoint inhibitor’s efficacy for breast cancer |
topic | Immunology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9013822/ https://www.ncbi.nlm.nih.gov/pubmed/35444644 http://dx.doi.org/10.3389/fimmu.2022.830158 |
work_keys_str_mv | AT lvwenchang analysisoftumorglycosylationcharacteristicsandimplicationsforimmunecheckpointinhibitorsefficacyforbreastcancer AT yuhonghao analysisoftumorglycosylationcharacteristicsandimplicationsforimmunecheckpointinhibitorsefficacyforbreastcancer AT hanmei analysisoftumorglycosylationcharacteristicsandimplicationsforimmunecheckpointinhibitorsefficacyforbreastcancer AT tanyufang analysisoftumorglycosylationcharacteristicsandimplicationsforimmunecheckpointinhibitorsefficacyforbreastcancer AT wumin analysisoftumorglycosylationcharacteristicsandimplicationsforimmunecheckpointinhibitorsefficacyforbreastcancer AT zhangjun analysisoftumorglycosylationcharacteristicsandimplicationsforimmunecheckpointinhibitorsefficacyforbreastcancer AT wuyiping analysisoftumorglycosylationcharacteristicsandimplicationsforimmunecheckpointinhibitorsefficacyforbreastcancer AT zhangqi analysisoftumorglycosylationcharacteristicsandimplicationsforimmunecheckpointinhibitorsefficacyforbreastcancer |