PDP1 related ferroptosis risk signature indicates distinct immune microenvironment and prognosis of breast cancer patients
ObjectiveWe aim to construct a RiskScore model to aid in the early prognosis of breast cancer (BC).MethodsBC mRNA expression profiles were obtained from TCGA and GEO databases. Differential gene expression analysis identifies PDP1-ferroptosis-related genes. LASSO Cox regression was utilized to scree...
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Frontiers Media S.A.
2025-04-01
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| Series: | Frontiers in Pharmacology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fphar.2025.1551325/full |
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| author | Yufeng Wang Huifen Dang Gongjian Zhu Yingxia Tian |
| author_facet | Yufeng Wang Huifen Dang Gongjian Zhu Yingxia Tian |
| author_sort | Yufeng Wang |
| collection | DOAJ |
| description | ObjectiveWe aim to construct a RiskScore model to aid in the early prognosis of breast cancer (BC).MethodsBC mRNA expression profiles were obtained from TCGA and GEO databases. Differential gene expression analysis identifies PDP1-ferroptosis-related genes. LASSO Cox regression was utilized to screen genes to build a RiskScore model, and survival analysis were performed to investigate the reliability in BC prognosis. Immune cell infiltration proportions were calculated using CIBERSORT and xCell algorithms. Single-cell data processing and analysis were conducted using “Seurat”, “monocle”, and “iTALK” packages. PDP1 was silenced to validate its influence on the target genes.ResultsData from public databases revealed significant upregulation of PDP1 in BC samples compared to normal tissues. A RiskScore model based on PDP1-related differential ferroptosis-related genes (FRGs) ACSL1, BNIP3, and EMC2 was developed, which effectively predicted BC patient prognosis. High-risk BC samples exhibited poorer overall survival and were associated with immune microenvironment. The model remained significant in multivariate Cox regression analysis, indicating that it could independently predict the survival of BC patients. ACSL1, BNIP3, and EMC2 were downregulated after knockdown of PDP1.ConclusionRiskScore model constructed by PDP1-ferroptosis-related genes ACSL1, BNIP3, and EMC2 is able to help predict the prognosis of BC patients. |
| format | Article |
| id | doaj-art-ccc3d346956245639be0f6f6bc2cd80d |
| institution | OA Journals |
| issn | 1663-9812 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Frontiers Media S.A. |
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| series | Frontiers in Pharmacology |
| spelling | doaj-art-ccc3d346956245639be0f6f6bc2cd80d2025-08-20T02:12:06ZengFrontiers Media S.A.Frontiers in Pharmacology1663-98122025-04-011610.3389/fphar.2025.15513251551325PDP1 related ferroptosis risk signature indicates distinct immune microenvironment and prognosis of breast cancer patientsYufeng Wang0Huifen Dang1Gongjian Zhu2Yingxia Tian3Department of Breast Medical Oncology, Affiliated Cancer Hospital of Sun Yat-sen University, Gansu Hospital, Lanzhou, Gansu, ChinaDepartment of Breast Medical Oncology, Affiliated Cancer Hospital of Sun Yat-sen University, Gansu Hospital, Lanzhou, Gansu, ChinaDepartment of Science and Education Section, Affiliated Cancer Hospital of Sun Yat-sen University, Gansu Hospital, Lanzhou, Gansu, ChinaDepartment of Breast Medical Oncology, Affiliated Cancer Hospital of Sun Yat-sen University, Gansu Hospital, Lanzhou, Gansu, ChinaObjectiveWe aim to construct a RiskScore model to aid in the early prognosis of breast cancer (BC).MethodsBC mRNA expression profiles were obtained from TCGA and GEO databases. Differential gene expression analysis identifies PDP1-ferroptosis-related genes. LASSO Cox regression was utilized to screen genes to build a RiskScore model, and survival analysis were performed to investigate the reliability in BC prognosis. Immune cell infiltration proportions were calculated using CIBERSORT and xCell algorithms. Single-cell data processing and analysis were conducted using “Seurat”, “monocle”, and “iTALK” packages. PDP1 was silenced to validate its influence on the target genes.ResultsData from public databases revealed significant upregulation of PDP1 in BC samples compared to normal tissues. A RiskScore model based on PDP1-related differential ferroptosis-related genes (FRGs) ACSL1, BNIP3, and EMC2 was developed, which effectively predicted BC patient prognosis. High-risk BC samples exhibited poorer overall survival and were associated with immune microenvironment. The model remained significant in multivariate Cox regression analysis, indicating that it could independently predict the survival of BC patients. ACSL1, BNIP3, and EMC2 were downregulated after knockdown of PDP1.ConclusionRiskScore model constructed by PDP1-ferroptosis-related genes ACSL1, BNIP3, and EMC2 is able to help predict the prognosis of BC patients.https://www.frontiersin.org/articles/10.3389/fphar.2025.1551325/fullbreast cancerLASSO-cox regression analysisprognosisPDP1ACSL1BNIP3 |
| spellingShingle | Yufeng Wang Huifen Dang Gongjian Zhu Yingxia Tian PDP1 related ferroptosis risk signature indicates distinct immune microenvironment and prognosis of breast cancer patients Frontiers in Pharmacology breast cancer LASSO-cox regression analysis prognosis PDP1 ACSL1 BNIP3 |
| title | PDP1 related ferroptosis risk signature indicates distinct immune microenvironment and prognosis of breast cancer patients |
| title_full | PDP1 related ferroptosis risk signature indicates distinct immune microenvironment and prognosis of breast cancer patients |
| title_fullStr | PDP1 related ferroptosis risk signature indicates distinct immune microenvironment and prognosis of breast cancer patients |
| title_full_unstemmed | PDP1 related ferroptosis risk signature indicates distinct immune microenvironment and prognosis of breast cancer patients |
| title_short | PDP1 related ferroptosis risk signature indicates distinct immune microenvironment and prognosis of breast cancer patients |
| title_sort | pdp1 related ferroptosis risk signature indicates distinct immune microenvironment and prognosis of breast cancer patients |
| topic | breast cancer LASSO-cox regression analysis prognosis PDP1 ACSL1 BNIP3 |
| url | https://www.frontiersin.org/articles/10.3389/fphar.2025.1551325/full |
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