Integrative analysis of efferocytosis- and invasion-related genes as potential biomarkers and therapeutic targets in breast cancer
Abstract Breast cancer remains a primary source of cancer-related mortality among females worldwide. This investigation sought to evaluate the distinctive expression patterns of genes linked to efferocytosis and invasion in breast cancer and their prognostic implications. Through bioinformatics anal...
Saved in:
| Main Authors: | , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Springer
2025-08-01
|
| Series: | Discover Oncology |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s12672-025-03346-w |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849226159624028160 |
|---|---|
| author | Jing Yang Rong Zhang Lamei Sun Cong Wang Ming Feng Bin Su Lixin Jiang |
| author_facet | Jing Yang Rong Zhang Lamei Sun Cong Wang Ming Feng Bin Su Lixin Jiang |
| author_sort | Jing Yang |
| collection | DOAJ |
| description | Abstract Breast cancer remains a primary source of cancer-related mortality among females worldwide. This investigation sought to evaluate the distinctive expression patterns of genes linked to efferocytosis and invasion in breast cancer and their prognostic implications. Through bioinformatics analyses, a robust prognostic risk modelwas developed. Breast cancer datasets were procured and processed from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and GeneCards databases. Differential expression analysis was executed utilizing DESeq2, identifying genes with|logFC| >1 and p-value < 0.05. Efferocytosis-related genes and invasion-related genes were curated from GeneCards and PubMed, resulting in 127 overlapping genes. A prognostic risk model was developed utilizing univariate Cox regression, Least Absolute Shrinkage and Selection Operator regression, and multivariate Cox regression analyses. A sum of 7860 differentially expressed genes was ascertained in the TCGA-BRCA dataset, comprising 4130 elevated and 11,990 reduced expressions. Among them, 32 efferocytosis- and invasion-related genes exhibited differential expression, including ANO6 and PLGRKT. Univariate Cox regression pinpointed ANO6 and PLGRKT as significant prognostic markers. The Least Absolute Shrinkage and Selection Operator regression yielded the risk score formula: Risk score = ANO6 × (0.328) + PLGRKT × (-0.277). Kaplan-Meier survival analysis suggested a notable difference in survival outcomes between high-risk and low-risk cohorts (p-value < 0.01). Multivariate Cox analysis confirmed risk score, age, NStage subgroups N1-N3, and TStage subgroup T4 as statistically significant prognostic predictors. Functional enrichment analysis suggested that ANO6 and PLGRKT were implicated in biological processes like bleb assembly and the positive regulation of phagocytosis. Gene Set Enrichment Analysis identified notable pathway associations, encompassing the KEAP1/NFE2L2 Pathway and TP53 Regulation of Metabolic Genes. In conclusion, the developed prognostic risk model effectively predicts survival outcomes in patients with breast cancer, with ANO6 and PLGRKT being pivotal in tumor progression. These observations provide essential knowledge for therapeutic intervention strategies and enhanced clinical care in breast cancer. |
| format | Article |
| id | doaj-art-b830d8794e904823bd96e7a7f2496b9e |
| institution | Kabale University |
| issn | 2730-6011 |
| language | English |
| publishDate | 2025-08-01 |
| publisher | Springer |
| record_format | Article |
| series | Discover Oncology |
| spelling | doaj-art-b830d8794e904823bd96e7a7f2496b9e2025-08-24T11:36:13ZengSpringerDiscover Oncology2730-60112025-08-0116112510.1007/s12672-025-03346-wIntegrative analysis of efferocytosis- and invasion-related genes as potential biomarkers and therapeutic targets in breast cancerJing Yang0Rong Zhang1Lamei Sun2Cong Wang3Ming Feng4Bin Su5Lixin Jiang6Department of General Surgery, Jiangyin Hospital Affiliated to Nanjing University of Chinese MedicineDepartment of General Surgery, Jiangyin Hospital Affiliated to Nanjing University of Chinese MedicineDepartment of Traditional Chinese Medicine, Jiangyin Nanzha Community Health Service CenterDepartment of Breast Surgery, Affiliated Hospital of Nanjing University of Chinese MedicineDepartment of Breast Surgery, Affiliated Hospital of Nanjing University of Chinese MedicineDepartment of General Surgery, Jiangyin Hospital Affiliated to Nanjing University of Chinese MedicineDepartment of General Surgery, Jiangyin Hospital Affiliated to Nanjing University of Chinese MedicineAbstract Breast cancer remains a primary source of cancer-related mortality among females worldwide. This investigation sought to evaluate the distinctive expression patterns of genes linked to efferocytosis and invasion in breast cancer and their prognostic implications. Through bioinformatics analyses, a robust prognostic risk modelwas developed. Breast cancer datasets were procured and processed from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and GeneCards databases. Differential expression analysis was executed utilizing DESeq2, identifying genes with|logFC| >1 and p-value < 0.05. Efferocytosis-related genes and invasion-related genes were curated from GeneCards and PubMed, resulting in 127 overlapping genes. A prognostic risk model was developed utilizing univariate Cox regression, Least Absolute Shrinkage and Selection Operator regression, and multivariate Cox regression analyses. A sum of 7860 differentially expressed genes was ascertained in the TCGA-BRCA dataset, comprising 4130 elevated and 11,990 reduced expressions. Among them, 32 efferocytosis- and invasion-related genes exhibited differential expression, including ANO6 and PLGRKT. Univariate Cox regression pinpointed ANO6 and PLGRKT as significant prognostic markers. The Least Absolute Shrinkage and Selection Operator regression yielded the risk score formula: Risk score = ANO6 × (0.328) + PLGRKT × (-0.277). Kaplan-Meier survival analysis suggested a notable difference in survival outcomes between high-risk and low-risk cohorts (p-value < 0.01). Multivariate Cox analysis confirmed risk score, age, NStage subgroups N1-N3, and TStage subgroup T4 as statistically significant prognostic predictors. Functional enrichment analysis suggested that ANO6 and PLGRKT were implicated in biological processes like bleb assembly and the positive regulation of phagocytosis. Gene Set Enrichment Analysis identified notable pathway associations, encompassing the KEAP1/NFE2L2 Pathway and TP53 Regulation of Metabolic Genes. In conclusion, the developed prognostic risk model effectively predicts survival outcomes in patients with breast cancer, with ANO6 and PLGRKT being pivotal in tumor progression. These observations provide essential knowledge for therapeutic intervention strategies and enhanced clinical care in breast cancer.https://doi.org/10.1007/s12672-025-03346-wBreast cancerBioinformaticsEfferocytosisInvasionBiomarkerDifferentially expressed genes |
| spellingShingle | Jing Yang Rong Zhang Lamei Sun Cong Wang Ming Feng Bin Su Lixin Jiang Integrative analysis of efferocytosis- and invasion-related genes as potential biomarkers and therapeutic targets in breast cancer Discover Oncology Breast cancer Bioinformatics Efferocytosis Invasion Biomarker Differentially expressed genes |
| title | Integrative analysis of efferocytosis- and invasion-related genes as potential biomarkers and therapeutic targets in breast cancer |
| title_full | Integrative analysis of efferocytosis- and invasion-related genes as potential biomarkers and therapeutic targets in breast cancer |
| title_fullStr | Integrative analysis of efferocytosis- and invasion-related genes as potential biomarkers and therapeutic targets in breast cancer |
| title_full_unstemmed | Integrative analysis of efferocytosis- and invasion-related genes as potential biomarkers and therapeutic targets in breast cancer |
| title_short | Integrative analysis of efferocytosis- and invasion-related genes as potential biomarkers and therapeutic targets in breast cancer |
| title_sort | integrative analysis of efferocytosis and invasion related genes as potential biomarkers and therapeutic targets in breast cancer |
| topic | Breast cancer Bioinformatics Efferocytosis Invasion Biomarker Differentially expressed genes |
| url | https://doi.org/10.1007/s12672-025-03346-w |
| work_keys_str_mv | AT jingyang integrativeanalysisofefferocytosisandinvasionrelatedgenesaspotentialbiomarkersandtherapeutictargetsinbreastcancer AT rongzhang integrativeanalysisofefferocytosisandinvasionrelatedgenesaspotentialbiomarkersandtherapeutictargetsinbreastcancer AT lameisun integrativeanalysisofefferocytosisandinvasionrelatedgenesaspotentialbiomarkersandtherapeutictargetsinbreastcancer AT congwang integrativeanalysisofefferocytosisandinvasionrelatedgenesaspotentialbiomarkersandtherapeutictargetsinbreastcancer AT mingfeng integrativeanalysisofefferocytosisandinvasionrelatedgenesaspotentialbiomarkersandtherapeutictargetsinbreastcancer AT binsu integrativeanalysisofefferocytosisandinvasionrelatedgenesaspotentialbiomarkersandtherapeutictargetsinbreastcancer AT lixinjiang integrativeanalysisofefferocytosisandinvasionrelatedgenesaspotentialbiomarkersandtherapeutictargetsinbreastcancer |