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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...

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Autores principales: Lv, Wenchang, Yu, Honghao, Han, Mei, Tan, Yufang, Wu, Min, Zhang, Jun, Wu, Yiping, Zhang, Qi
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
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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.
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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
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