A novel signature integrated endoplasmic reticulum stress and apoptosis related genes to predict prognosis for breast cancer
Background: Breast cancer (BC) is the primary cause of cancer mortality. Herein, we aimed to establish and verify a prognostic model consisting of endoplasmic reticulum stress and apoptosis related genes (ERAGs) to predict patient survival. Methods: The Cancer Genome Atlas (TCGA) database was used t...
| Main Authors: | , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2024-03-01
|
| Series: | Heliyon |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S240584402404310X |
| _version_ | 1797224112048832512 |
|---|---|
| author | Hao Fan Mingjie Dong Chaomin Ren Pengfei Shao Yu Gao Yushan Wang Yi Feng |
| author_facet | Hao Fan Mingjie Dong Chaomin Ren Pengfei Shao Yu Gao Yushan Wang Yi Feng |
| author_sort | Hao Fan |
| collection | DOAJ |
| description | Background: Breast cancer (BC) is the primary cause of cancer mortality. Herein, we aimed to establish and verify a prognostic model consisting of endoplasmic reticulum stress and apoptosis related genes (ERAGs) to predict patient survival. Methods: The Cancer Genome Atlas (TCGA) database was used to download gene expression and clinical data to identify the differentially expressed genes (DEGs). Using univariate Cox regression analysis and the Least Absolute Shrinkage and Selection Operator (LASSO)-penalized Cox proportional hazards regression analysis, the prognostic ERAGs were screened. The predictive performance was evaluated using Kaplan-Meier (KM) survival and receiver operating characteristic (ROC) curve analysis. Furthermore, a nomogram model incorporating clinical parameters and risk scores was constructed and subsequently evaluated using ROC and KM analysis. The correlation analysis, mutation analysis, functional enrichment analysis, and immune infiltration analysis were employed to investigate the specific mechanism of ERAGs. We also used Quantitative Real-Time PCR (RT-qPCR) to verify the differential expression of DE-ERAGs between the breast cancer cell line and mammary epithelial cell line. Results: We constructed a prognostic signature comprising 16 ERAGs. ROC, KM analysis and the nomogram model demonstrated high effectiveness in accurately predicting the overall survival (OS) of BRCA patients. The results of these analysis could provide reference for further mechanism exploration. Conclusion: We developed and assessed a novel molecular predictive model for breast cancer that focuses on endoplasmic reticulum stress and apoptosis in this study. It is a valuable complement to the existing prognostic prediction models for breast cancer. |
| first_indexed | 2024-04-24T13:47:56Z |
| format | Article |
| id | doaj.art-27810c04521246a0b4d725304b5fe545 |
| institution | Directory Open Access Journal |
| issn | 2405-8440 |
| language | English |
| last_indexed | 2024-04-24T13:47:56Z |
| publishDate | 2024-03-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Heliyon |
| spelling | doaj.art-27810c04521246a0b4d725304b5fe5452024-04-04T05:07:06ZengElsevierHeliyon2405-84402024-03-01106e28279A novel signature integrated endoplasmic reticulum stress and apoptosis related genes to predict prognosis for breast cancerHao Fan0Mingjie Dong1Chaomin Ren2Pengfei Shao3Yu Gao4Yushan Wang5Yi Feng6Department of Orthopedics, Second Hospital of Shanxi Medical University, Taiyuan, China; Shanxi Medical University, Taiyuan, ChinaDepartment of Orthopedics, Second Hospital of Shanxi Medical University, Taiyuan, China; Shanxi Medical University, Taiyuan, ChinaShanxi Medical University, Taiyuan, ChinaDepartment of Orthopedics, Second Hospital of Shanxi Medical University, Taiyuan, ChinaDepartment of Orthopedics, Second Hospital of Shanxi Medical University, Taiyuan, ChinaDepartment of Orthopedics, Second Hospital of Shanxi Medical University, Taiyuan, ChinaDepartment of Orthopedics, Second Hospital of Shanxi Medical University, Taiyuan, China; Corresponding author.Background: Breast cancer (BC) is the primary cause of cancer mortality. Herein, we aimed to establish and verify a prognostic model consisting of endoplasmic reticulum stress and apoptosis related genes (ERAGs) to predict patient survival. Methods: The Cancer Genome Atlas (TCGA) database was used to download gene expression and clinical data to identify the differentially expressed genes (DEGs). Using univariate Cox regression analysis and the Least Absolute Shrinkage and Selection Operator (LASSO)-penalized Cox proportional hazards regression analysis, the prognostic ERAGs were screened. The predictive performance was evaluated using Kaplan-Meier (KM) survival and receiver operating characteristic (ROC) curve analysis. Furthermore, a nomogram model incorporating clinical parameters and risk scores was constructed and subsequently evaluated using ROC and KM analysis. The correlation analysis, mutation analysis, functional enrichment analysis, and immune infiltration analysis were employed to investigate the specific mechanism of ERAGs. We also used Quantitative Real-Time PCR (RT-qPCR) to verify the differential expression of DE-ERAGs between the breast cancer cell line and mammary epithelial cell line. Results: We constructed a prognostic signature comprising 16 ERAGs. ROC, KM analysis and the nomogram model demonstrated high effectiveness in accurately predicting the overall survival (OS) of BRCA patients. The results of these analysis could provide reference for further mechanism exploration. Conclusion: We developed and assessed a novel molecular predictive model for breast cancer that focuses on endoplasmic reticulum stress and apoptosis in this study. It is a valuable complement to the existing prognostic prediction models for breast cancer.http://www.sciencedirect.com/science/article/pii/S240584402404310XBreast cancerEndoplasmic reticulum stressApoptosisBioinformaticsPrognosis |
| spellingShingle | Hao Fan Mingjie Dong Chaomin Ren Pengfei Shao Yu Gao Yushan Wang Yi Feng A novel signature integrated endoplasmic reticulum stress and apoptosis related genes to predict prognosis for breast cancer Heliyon Breast cancer Endoplasmic reticulum stress Apoptosis Bioinformatics Prognosis |
| title | A novel signature integrated endoplasmic reticulum stress and apoptosis related genes to predict prognosis for breast cancer |
| title_full | A novel signature integrated endoplasmic reticulum stress and apoptosis related genes to predict prognosis for breast cancer |
| title_fullStr | A novel signature integrated endoplasmic reticulum stress and apoptosis related genes to predict prognosis for breast cancer |
| title_full_unstemmed | A novel signature integrated endoplasmic reticulum stress and apoptosis related genes to predict prognosis for breast cancer |
| title_short | A novel signature integrated endoplasmic reticulum stress and apoptosis related genes to predict prognosis for breast cancer |
| title_sort | novel signature integrated endoplasmic reticulum stress and apoptosis related genes to predict prognosis for breast cancer |
| topic | Breast cancer Endoplasmic reticulum stress Apoptosis Bioinformatics Prognosis |
| url | http://www.sciencedirect.com/science/article/pii/S240584402404310X |
| work_keys_str_mv | AT haofan anovelsignatureintegratedendoplasmicreticulumstressandapoptosisrelatedgenestopredictprognosisforbreastcancer AT mingjiedong anovelsignatureintegratedendoplasmicreticulumstressandapoptosisrelatedgenestopredictprognosisforbreastcancer AT chaominren anovelsignatureintegratedendoplasmicreticulumstressandapoptosisrelatedgenestopredictprognosisforbreastcancer AT pengfeishao anovelsignatureintegratedendoplasmicreticulumstressandapoptosisrelatedgenestopredictprognosisforbreastcancer AT yugao anovelsignatureintegratedendoplasmicreticulumstressandapoptosisrelatedgenestopredictprognosisforbreastcancer AT yushanwang anovelsignatureintegratedendoplasmicreticulumstressandapoptosisrelatedgenestopredictprognosisforbreastcancer AT yifeng anovelsignatureintegratedendoplasmicreticulumstressandapoptosisrelatedgenestopredictprognosisforbreastcancer AT haofan novelsignatureintegratedendoplasmicreticulumstressandapoptosisrelatedgenestopredictprognosisforbreastcancer AT mingjiedong novelsignatureintegratedendoplasmicreticulumstressandapoptosisrelatedgenestopredictprognosisforbreastcancer AT chaominren novelsignatureintegratedendoplasmicreticulumstressandapoptosisrelatedgenestopredictprognosisforbreastcancer AT pengfeishao novelsignatureintegratedendoplasmicreticulumstressandapoptosisrelatedgenestopredictprognosisforbreastcancer AT yugao novelsignatureintegratedendoplasmicreticulumstressandapoptosisrelatedgenestopredictprognosisforbreastcancer AT yushanwang novelsignatureintegratedendoplasmicreticulumstressandapoptosisrelatedgenestopredictprognosisforbreastcancer AT yifeng novelsignatureintegratedendoplasmicreticulumstressandapoptosisrelatedgenestopredictprognosisforbreastcancer |