Survival-Associated Metabolic Genes and Risk Scoring System in HER2-Positive Breast Cancer
Human epidermal growth factor receptor 2 (HER2)-positive breast cancer and triple-negative breast cancer have their own genetic, epigenetic, and protein expression profiles. In the present study, based on bioinformatics techniques, we explored the prognostic targets of HER2-positive breast cancer fr...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-05-01
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| Series: | Frontiers in Endocrinology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fendo.2022.813306/full |
| _version_ | 1818244947240812544 |
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| author | Chundi Gao Huayao Li Huayao Li Chao Zhou Cun Liu Jing Zhuang Lijuan Liu Changgang Sun Changgang Sun Changgang Sun |
| author_facet | Chundi Gao Huayao Li Huayao Li Chao Zhou Cun Liu Jing Zhuang Lijuan Liu Changgang Sun Changgang Sun Changgang Sun |
| author_sort | Chundi Gao |
| collection | DOAJ |
| description | Human epidermal growth factor receptor 2 (HER2)-positive breast cancer and triple-negative breast cancer have their own genetic, epigenetic, and protein expression profiles. In the present study, based on bioinformatics techniques, we explored the prognostic targets of HER2-positive breast cancer from metabonomics perspective and developed a new risk score system to evaluate the prognosis of patients. By identifying the differences between HER2 positive and normal control tissues, and between triple negative breast cancer and normal control tissues, we found a large number of differentially expressed metabolic genes in patients with HER2-positive breast cancer and triple-negative breast cancer. Importantly, in HER2-positive breast cancer, decreased expression of metabolism-related genes ATIC, HPRT1, ASNS, SULT1A2, and HAL was associated with increased survival. Interestingly, these five metabolism-related genes can be used to construct a risk score system to predict overall survival (OS) in HER2-positive patients. The time-dependent receiver operating characteristic (ROC) curve analysis showed that the predictive sensitivity of the risk scoring system was higher than that of other clinical factors, including age, stage, and tumor node metastasis (TNM) stage. This work shows that specific transcriptional changes in metabolic genes can be used as biomarkers to predict the prognosis of patients, which is helpful in implementing personalized treatment and evaluating patient prognosis. |
| first_indexed | 2024-12-12T14:25:07Z |
| format | Article |
| id | doaj.art-31ce356a31784cfcaf0650fec2c57d9c |
| institution | Directory Open Access Journal |
| issn | 1664-2392 |
| language | English |
| last_indexed | 2024-12-12T14:25:07Z |
| publishDate | 2022-05-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Endocrinology |
| spelling | doaj.art-31ce356a31784cfcaf0650fec2c57d9c2022-12-22T00:21:43ZengFrontiers Media S.A.Frontiers in Endocrinology1664-23922022-05-011310.3389/fendo.2022.813306813306Survival-Associated Metabolic Genes and Risk Scoring System in HER2-Positive Breast CancerChundi Gao0Huayao Li1Huayao Li2Chao Zhou3Cun Liu4Jing Zhuang5Lijuan Liu6Changgang Sun7Changgang Sun8Changgang Sun9College of First Clinical Medicine, Shandong University of Traditional Chinese Medicine, Jinan, ChinaCollege of Basic Medical, Shandong University of Traditional Chinese Medicine, Jinan, ChinaCollege of Traditional Chinese Medicine, Weifang Medical University, Weifang, ChinaDepartment of Oncology, Weifang Traditional Chinese Hospital, Weifang, ChinaCollege of First Clinical Medicine, Shandong University of Traditional Chinese Medicine, Jinan, ChinaDepartment of Oncology, Weifang Traditional Chinese Hospital, Weifang, ChinaDepartment of Oncology, Weifang Traditional Chinese Hospital, Weifang, ChinaDepartment of Oncology, Weifang Traditional Chinese Hospital, Weifang, ChinaAcademy of Chinese Medical Sciences, Shandong University of Traditional Chinese Medicine, Qingdao, ChinaCollege of Traditional Chinese Medicine, Weifang Medical University, Weifang, ChinaHuman epidermal growth factor receptor 2 (HER2)-positive breast cancer and triple-negative breast cancer have their own genetic, epigenetic, and protein expression profiles. In the present study, based on bioinformatics techniques, we explored the prognostic targets of HER2-positive breast cancer from metabonomics perspective and developed a new risk score system to evaluate the prognosis of patients. By identifying the differences between HER2 positive and normal control tissues, and between triple negative breast cancer and normal control tissues, we found a large number of differentially expressed metabolic genes in patients with HER2-positive breast cancer and triple-negative breast cancer. Importantly, in HER2-positive breast cancer, decreased expression of metabolism-related genes ATIC, HPRT1, ASNS, SULT1A2, and HAL was associated with increased survival. Interestingly, these five metabolism-related genes can be used to construct a risk score system to predict overall survival (OS) in HER2-positive patients. The time-dependent receiver operating characteristic (ROC) curve analysis showed that the predictive sensitivity of the risk scoring system was higher than that of other clinical factors, including age, stage, and tumor node metastasis (TNM) stage. This work shows that specific transcriptional changes in metabolic genes can be used as biomarkers to predict the prognosis of patients, which is helpful in implementing personalized treatment and evaluating patient prognosis.https://www.frontiersin.org/articles/10.3389/fendo.2022.813306/fullHER2-positive breast cancermetabonomicsprognostic risk scoring systemlasso cox regression analysissurvival prediction |
| spellingShingle | Chundi Gao Huayao Li Huayao Li Chao Zhou Cun Liu Jing Zhuang Lijuan Liu Changgang Sun Changgang Sun Changgang Sun Survival-Associated Metabolic Genes and Risk Scoring System in HER2-Positive Breast Cancer Frontiers in Endocrinology HER2-positive breast cancer metabonomics prognostic risk scoring system lasso cox regression analysis survival prediction |
| title | Survival-Associated Metabolic Genes and Risk Scoring System in HER2-Positive Breast Cancer |
| title_full | Survival-Associated Metabolic Genes and Risk Scoring System in HER2-Positive Breast Cancer |
| title_fullStr | Survival-Associated Metabolic Genes and Risk Scoring System in HER2-Positive Breast Cancer |
| title_full_unstemmed | Survival-Associated Metabolic Genes and Risk Scoring System in HER2-Positive Breast Cancer |
| title_short | Survival-Associated Metabolic Genes and Risk Scoring System in HER2-Positive Breast Cancer |
| title_sort | survival associated metabolic genes and risk scoring system in her2 positive breast cancer |
| topic | HER2-positive breast cancer metabonomics prognostic risk scoring system lasso cox regression analysis survival prediction |
| url | https://www.frontiersin.org/articles/10.3389/fendo.2022.813306/full |
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