Probing the Potential of Defense Response-Associated Genes for Predicting the Progression, Prognosis, and Immune Microenvironment of Osteosarcoma
Background: The defense response is a type of self-protective response of the body that protects it from damage by pathogenic factors. Although these reactions make important contributions to the occurrence and development of tumors, the role they play in osteosarcoma (OS), particularly in the immun...
| Main Authors: | , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-04-01
|
| Series: | Cancers |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-6694/15/8/2405 |
| _version_ | 1797606008076369920 |
|---|---|
| author | Liangkun Huang Fei Sun Zilin Liu Wenyi Jin Yubiao Zhang Junwen Chen Changheng Zhong Wanting Liang Hao Peng |
| author_facet | Liangkun Huang Fei Sun Zilin Liu Wenyi Jin Yubiao Zhang Junwen Chen Changheng Zhong Wanting Liang Hao Peng |
| author_sort | Liangkun Huang |
| collection | DOAJ |
| description | Background: The defense response is a type of self-protective response of the body that protects it from damage by pathogenic factors. Although these reactions make important contributions to the occurrence and development of tumors, the role they play in osteosarcoma (OS), particularly in the immune microenvironment, remains unpredictable. Methods: This study included the clinical information and transcriptomic data of 84 osteosarcoma samples and the microarray data of 12 mesenchymal stem cell samples and 84 osteosarcoma samples. We obtained 129 differentially expressed genes related to the defense response (DRGs) by taking the intersection of differentially expressed genes with genes involved in the defense response pathway, and prognostic genes were screened using univariate Cox regression. Least absolute shrinkage and selection operator (LASSO) penalized Cox regression and multivariate Cox regression were then used to establish a DRG prognostic signature (DGPS) via the stepwise method. DGPS performance was examined using independent prognostic analysis, survival curves, and receiver operating characteristic (ROC) curves. In addition, the molecular and immune mechanisms of adverse prognosis in high-risk populations identified by DGPS were elucidated. The results were well verified by experiments. Result: BNIP3, PTGIS, and ZYX were identified as the most important DRGs for OS progression (hazard ratios of 2.044, 1.485, and 0.189, respectively). DGPS demonstrated outstanding performance in the prediction of OS prognosis (area under the curve (AUC) values of 0.842 and 0.787 in the training and test sets, respectively, adj-<i>p</i> < 0.05 in the survival curve). DGPS also performed better than a recent clinical prognostic approach with an AUC value of only 0.674 [metastasis], which was certified in the subsequent experimental results. These three genes regulate several key biological processes, including immune receptor activity and T cell activation, and they also reduce the infiltration of some immune cells, such as B cells, CD8+ T cells, and macrophages. Encouragingly, we found that DGPS was associated with sensitivity to chemotherapeutic drugs including JNK Inhibitor VIII, TGX221, MP470, and SB52334. Finally, we verified the effect of BNIP3 on apoptosis, proliferation, and migration of osteosarcoma cells through experiments. Conclusions: This study elucidated the role and mechanism of BNIP3, PTGIS, and ZYX in OS progression and was well verified by the experimental results, enabling reliable prognostic means and treatment strategies to be proposed for OS patients. |
| first_indexed | 2024-03-11T05:09:16Z |
| format | Article |
| id | doaj.art-9674262ae14e4388980da201728fe357 |
| institution | Directory Open Access Journal |
| issn | 2072-6694 |
| language | English |
| last_indexed | 2024-03-11T05:09:16Z |
| publishDate | 2023-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Cancers |
| spelling | doaj.art-9674262ae14e4388980da201728fe3572023-11-17T18:40:30ZengMDPI AGCancers2072-66942023-04-01158240510.3390/cancers15082405Probing the Potential of Defense Response-Associated Genes for Predicting the Progression, Prognosis, and Immune Microenvironment of OsteosarcomaLiangkun Huang0Fei Sun1Zilin Liu2Wenyi Jin3Yubiao Zhang4Junwen Chen5Changheng Zhong6Wanting Liang7Hao Peng8Department of Orthopedics Surgery, Renmin Hospital of Wuhan University, Wuhan 430060, ChinaDepartment of Orthopedics Surgery, Renmin Hospital of Wuhan University, Wuhan 430060, ChinaDepartment of Orthopedics Surgery, Renmin Hospital of Wuhan University, Wuhan 430060, ChinaDepartment of Biomedical Sciences, College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Kowloon Tong, Hong Kong SAR, ChinaDepartment of Orthopedics Surgery, Renmin Hospital of Wuhan University, Wuhan 430060, ChinaDepartment of Orthopedics Surgery, Renmin Hospital of Wuhan University, Wuhan 430060, ChinaDepartment of Orthopedics Surgery, Renmin Hospital of Wuhan University, Wuhan 430060, ChinaDepartment of Clinical Medicine, Xianyue Hospital of Xiamen Medical College, Xiamen 310058, ChinaDepartment of Orthopedics Surgery, Renmin Hospital of Wuhan University, Wuhan 430060, ChinaBackground: The defense response is a type of self-protective response of the body that protects it from damage by pathogenic factors. Although these reactions make important contributions to the occurrence and development of tumors, the role they play in osteosarcoma (OS), particularly in the immune microenvironment, remains unpredictable. Methods: This study included the clinical information and transcriptomic data of 84 osteosarcoma samples and the microarray data of 12 mesenchymal stem cell samples and 84 osteosarcoma samples. We obtained 129 differentially expressed genes related to the defense response (DRGs) by taking the intersection of differentially expressed genes with genes involved in the defense response pathway, and prognostic genes were screened using univariate Cox regression. Least absolute shrinkage and selection operator (LASSO) penalized Cox regression and multivariate Cox regression were then used to establish a DRG prognostic signature (DGPS) via the stepwise method. DGPS performance was examined using independent prognostic analysis, survival curves, and receiver operating characteristic (ROC) curves. In addition, the molecular and immune mechanisms of adverse prognosis in high-risk populations identified by DGPS were elucidated. The results were well verified by experiments. Result: BNIP3, PTGIS, and ZYX were identified as the most important DRGs for OS progression (hazard ratios of 2.044, 1.485, and 0.189, respectively). DGPS demonstrated outstanding performance in the prediction of OS prognosis (area under the curve (AUC) values of 0.842 and 0.787 in the training and test sets, respectively, adj-<i>p</i> < 0.05 in the survival curve). DGPS also performed better than a recent clinical prognostic approach with an AUC value of only 0.674 [metastasis], which was certified in the subsequent experimental results. These three genes regulate several key biological processes, including immune receptor activity and T cell activation, and they also reduce the infiltration of some immune cells, such as B cells, CD8+ T cells, and macrophages. Encouragingly, we found that DGPS was associated with sensitivity to chemotherapeutic drugs including JNK Inhibitor VIII, TGX221, MP470, and SB52334. Finally, we verified the effect of BNIP3 on apoptosis, proliferation, and migration of osteosarcoma cells through experiments. Conclusions: This study elucidated the role and mechanism of BNIP3, PTGIS, and ZYX in OS progression and was well verified by the experimental results, enabling reliable prognostic means and treatment strategies to be proposed for OS patients.https://www.mdpi.com/2072-6694/15/8/2405defense responseosteosarcomaprognosismetastasisimmunetherapy |
| spellingShingle | Liangkun Huang Fei Sun Zilin Liu Wenyi Jin Yubiao Zhang Junwen Chen Changheng Zhong Wanting Liang Hao Peng Probing the Potential of Defense Response-Associated Genes for Predicting the Progression, Prognosis, and Immune Microenvironment of Osteosarcoma Cancers defense response osteosarcoma prognosis metastasis immune therapy |
| title | Probing the Potential of Defense Response-Associated Genes for Predicting the Progression, Prognosis, and Immune Microenvironment of Osteosarcoma |
| title_full | Probing the Potential of Defense Response-Associated Genes for Predicting the Progression, Prognosis, and Immune Microenvironment of Osteosarcoma |
| title_fullStr | Probing the Potential of Defense Response-Associated Genes for Predicting the Progression, Prognosis, and Immune Microenvironment of Osteosarcoma |
| title_full_unstemmed | Probing the Potential of Defense Response-Associated Genes for Predicting the Progression, Prognosis, and Immune Microenvironment of Osteosarcoma |
| title_short | Probing the Potential of Defense Response-Associated Genes for Predicting the Progression, Prognosis, and Immune Microenvironment of Osteosarcoma |
| title_sort | probing the potential of defense response associated genes for predicting the progression prognosis and immune microenvironment of osteosarcoma |
| topic | defense response osteosarcoma prognosis metastasis immune therapy |
| url | https://www.mdpi.com/2072-6694/15/8/2405 |
| work_keys_str_mv | AT liangkunhuang probingthepotentialofdefenseresponseassociatedgenesforpredictingtheprogressionprognosisandimmunemicroenvironmentofosteosarcoma AT feisun probingthepotentialofdefenseresponseassociatedgenesforpredictingtheprogressionprognosisandimmunemicroenvironmentofosteosarcoma AT zilinliu probingthepotentialofdefenseresponseassociatedgenesforpredictingtheprogressionprognosisandimmunemicroenvironmentofosteosarcoma AT wenyijin probingthepotentialofdefenseresponseassociatedgenesforpredictingtheprogressionprognosisandimmunemicroenvironmentofosteosarcoma AT yubiaozhang probingthepotentialofdefenseresponseassociatedgenesforpredictingtheprogressionprognosisandimmunemicroenvironmentofosteosarcoma AT junwenchen probingthepotentialofdefenseresponseassociatedgenesforpredictingtheprogressionprognosisandimmunemicroenvironmentofosteosarcoma AT changhengzhong probingthepotentialofdefenseresponseassociatedgenesforpredictingtheprogressionprognosisandimmunemicroenvironmentofosteosarcoma AT wantingliang probingthepotentialofdefenseresponseassociatedgenesforpredictingtheprogressionprognosisandimmunemicroenvironmentofosteosarcoma AT haopeng probingthepotentialofdefenseresponseassociatedgenesforpredictingtheprogressionprognosisandimmunemicroenvironmentofosteosarcoma |