Characterization of glucose metabolism in breast cancer to guide clinical therapy
BackgroundBreast cancer (BRCA) ranks as a leading cause of cancer death in women worldwide. Glucose metabolism is a noticeable characteristic of the occurrence of malignant tumors. In this study, we aimed to construct a novel glycometabolism-related gene (GRG) signature to predict overall survival (...
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Frontiers Media S.A.
2022-09-01
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Series: | Frontiers in Surgery |
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Online Access: | https://www.frontiersin.org/articles/10.3389/fsurg.2022.973410/full |
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author | Yingying Mei Lantao Zhao Man Jiang Fangfang Yang Xiaochun Zhang Yizhen Jia Na Zhou |
author_facet | Yingying Mei Lantao Zhao Man Jiang Fangfang Yang Xiaochun Zhang Yizhen Jia Na Zhou |
author_sort | Yingying Mei |
collection | DOAJ |
description | BackgroundBreast cancer (BRCA) ranks as a leading cause of cancer death in women worldwide. Glucose metabolism is a noticeable characteristic of the occurrence of malignant tumors. In this study, we aimed to construct a novel glycometabolism-related gene (GRG) signature to predict overall survival (OS), immune infiltration and therapeutic response in BRCA patients.Materials and methodsThe mRNA sequencing and corresponding clinical data of BRCA patients were obtained from public cohorts. Lasso regression was applied to establish a GRG signature. The immune infiltration was evaluated with the ESTIMATE and CIBERSORT algorithms. The drug sensitivity was estimated using the value of IC50, and further forecasted the therapeutic response of each patient. The candidate target was selected in Cytoscape. A nomogram was constructed via the R package of “rms”.ResultsWe constructed a six-GRG signature based on CACNA1H, CHPF, IRS2, NT5E, SDC1 and ATP6AP1, and the high-risk patients were correlated with poorer OS (P = 2.515 × 10−7). M2 macrophage infiltration was considerably superior in high-risk patients, and CD8+ T cell infiltration was significantly higher in low-risk patients. Additionally, the high-risk group was more sensitive to Lapatinib. Fortunately, SDC1 was recognized as candidate target and patients had a better OS in the low-SDC1 group. A nomogram integrating the GRG signature was developed, and calibration curves were consistent between the actual and predicted OS.ConclusionsWe identified a novel GRG signature complementing the present understanding of the targeted therapy and immune biomarker in breast cancer. The GRGs may provide fresh insights for individualized management of BRCA patients. |
first_indexed | 2024-04-11T10:31:11Z |
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id | doaj.art-4011ae574e1e4d3fafc6ffe506fcaeb8 |
institution | Directory Open Access Journal |
issn | 2296-875X |
language | English |
last_indexed | 2024-04-11T10:31:11Z |
publishDate | 2022-09-01 |
publisher | Frontiers Media S.A. |
record_format | Article |
series | Frontiers in Surgery |
spelling | doaj.art-4011ae574e1e4d3fafc6ffe506fcaeb82022-12-22T04:29:25ZengFrontiers Media S.A.Frontiers in Surgery2296-875X2022-09-01910.3389/fsurg.2022.973410973410Characterization of glucose metabolism in breast cancer to guide clinical therapyYingying Mei0Lantao Zhao1Man Jiang2Fangfang Yang3Xiaochun Zhang4Yizhen Jia5Na Zhou6Precision Medicine Center of Oncology, The Affiliated Hospital of Qingdao University, Qingdao University, Qingdao, ChinaDepartment of Anesthesiology, The Affiliated Hospital of Qingdao University, Qingdao, ChinaPrecision Medicine Center of Oncology, The Affiliated Hospital of Qingdao University, Qingdao University, Qingdao, ChinaPrecision Medicine Center of Oncology, The Affiliated Hospital of Qingdao University, Qingdao University, Qingdao, ChinaPrecision Medicine Center of Oncology, The Affiliated Hospital of Qingdao University, Qingdao University, Qingdao, ChinaCore Laboratory, The University of Hong Kong-Shenzhen Hospital, Shenzhen, ChinaPrecision Medicine Center of Oncology, The Affiliated Hospital of Qingdao University, Qingdao University, Qingdao, ChinaBackgroundBreast cancer (BRCA) ranks as a leading cause of cancer death in women worldwide. Glucose metabolism is a noticeable characteristic of the occurrence of malignant tumors. In this study, we aimed to construct a novel glycometabolism-related gene (GRG) signature to predict overall survival (OS), immune infiltration and therapeutic response in BRCA patients.Materials and methodsThe mRNA sequencing and corresponding clinical data of BRCA patients were obtained from public cohorts. Lasso regression was applied to establish a GRG signature. The immune infiltration was evaluated with the ESTIMATE and CIBERSORT algorithms. The drug sensitivity was estimated using the value of IC50, and further forecasted the therapeutic response of each patient. The candidate target was selected in Cytoscape. A nomogram was constructed via the R package of “rms”.ResultsWe constructed a six-GRG signature based on CACNA1H, CHPF, IRS2, NT5E, SDC1 and ATP6AP1, and the high-risk patients were correlated with poorer OS (P = 2.515 × 10−7). M2 macrophage infiltration was considerably superior in high-risk patients, and CD8+ T cell infiltration was significantly higher in low-risk patients. Additionally, the high-risk group was more sensitive to Lapatinib. Fortunately, SDC1 was recognized as candidate target and patients had a better OS in the low-SDC1 group. A nomogram integrating the GRG signature was developed, and calibration curves were consistent between the actual and predicted OS.ConclusionsWe identified a novel GRG signature complementing the present understanding of the targeted therapy and immune biomarker in breast cancer. The GRGs may provide fresh insights for individualized management of BRCA patients.https://www.frontiersin.org/articles/10.3389/fsurg.2022.973410/fullbreast cancerglucose metabolismprognosisimmune infiltrationdrug sensitivity |
spellingShingle | Yingying Mei Lantao Zhao Man Jiang Fangfang Yang Xiaochun Zhang Yizhen Jia Na Zhou Characterization of glucose metabolism in breast cancer to guide clinical therapy Frontiers in Surgery breast cancer glucose metabolism prognosis immune infiltration drug sensitivity |
title | Characterization of glucose metabolism in breast cancer to guide clinical therapy |
title_full | Characterization of glucose metabolism in breast cancer to guide clinical therapy |
title_fullStr | Characterization of glucose metabolism in breast cancer to guide clinical therapy |
title_full_unstemmed | Characterization of glucose metabolism in breast cancer to guide clinical therapy |
title_short | Characterization of glucose metabolism in breast cancer to guide clinical therapy |
title_sort | characterization of glucose metabolism in breast cancer to guide clinical therapy |
topic | breast cancer glucose metabolism prognosis immune infiltration drug sensitivity |
url | https://www.frontiersin.org/articles/10.3389/fsurg.2022.973410/full |
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