Integrated Analysis of Multi-Omics Data to Establish a Hypoxia-Related Prognostic Model in Osteosarcoma
Background: Osteosarcoma (OS) is the most common malignant bone tumor in clinical practice, and currently, the ability to predict prognosis in the diagnosis of OS is limited. There is an urgent need to find new diagnostic methods and treatment strategies for OS. Material and methods: We downloaded t...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
SAGE Publishing
2022-10-01
|
| Series: | Evolutionary Bioinformatics |
| Online Access: | https://doi.org/10.1177/11769343221128537 |
| _version_ | 1797989930046062592 |
|---|---|
| author | Ye Tong Xiaoqing Zhang Ye Zhou |
| author_facet | Ye Tong Xiaoqing Zhang Ye Zhou |
| author_sort | Ye Tong |
| collection | DOAJ |
| description | Background: Osteosarcoma (OS) is the most common malignant bone tumor in clinical practice, and currently, the ability to predict prognosis in the diagnosis of OS is limited. There is an urgent need to find new diagnostic methods and treatment strategies for OS. Material and methods: We downloaded the multi-omics data for OS from the TARGET database. Prognosis-associated methylation sites were used to identify clustered subtypes of OS, and OS was classified into 3 subtypes (C1, C2, C3). Survival analysis showed significant differences between the C3 subtype and the other subtypes. Subsequently, differentially expressed genes (DEGs) across subtypes were screened and subjected to pathway enrichment analysis. Results: A total of 249 DEGs were screened from C3 subtype to other subtypes. Metabolic pathway enrichment analysis showed that DEGs were significantly enriched to the hypoxic pathway. Based on univariate and multivariate COX regression analysis, 12 genes from the hypoxia pathway were further screened and used to construct hypoxia-related prognostic model (HRPM). External validation of the HRPM was performed on the GSE21257 dataset. Finally, differences in survival and immune infiltration between high and low risk score groups were compared. Conclusion: In summary, we proposed a hypoxia-associated risk model based on a 12-gene expression signature, which is potentially valuable for prognostic diagnosis of patients with OS. |
| first_indexed | 2024-04-11T08:27:16Z |
| format | Article |
| id | doaj.art-d5de922bee6840c6bf1d8c9586b6fecc |
| institution | Directory Open Access Journal |
| issn | 1176-9343 |
| language | English |
| last_indexed | 2024-04-11T08:27:16Z |
| publishDate | 2022-10-01 |
| publisher | SAGE Publishing |
| record_format | Article |
| series | Evolutionary Bioinformatics |
| spelling | doaj.art-d5de922bee6840c6bf1d8c9586b6fecc2022-12-22T04:34:41ZengSAGE PublishingEvolutionary Bioinformatics1176-93432022-10-011810.1177/11769343221128537Integrated Analysis of Multi-Omics Data to Establish a Hypoxia-Related Prognostic Model in OsteosarcomaYe Tong0Xiaoqing Zhang1Ye Zhou2Department of Orthopaedics, Suzhou Hospital of Anhui Medical University, Suzhou, Anhui, ChinaDepartment of Laboratory, Bozhou People’s Hospital, Bozhou, Anhui, ChinaDepartment of Orthopaedics, Suzhou Hospital of Anhui Medical University, Suzhou, Anhui, ChinaBackground: Osteosarcoma (OS) is the most common malignant bone tumor in clinical practice, and currently, the ability to predict prognosis in the diagnosis of OS is limited. There is an urgent need to find new diagnostic methods and treatment strategies for OS. Material and methods: We downloaded the multi-omics data for OS from the TARGET database. Prognosis-associated methylation sites were used to identify clustered subtypes of OS, and OS was classified into 3 subtypes (C1, C2, C3). Survival analysis showed significant differences between the C3 subtype and the other subtypes. Subsequently, differentially expressed genes (DEGs) across subtypes were screened and subjected to pathway enrichment analysis. Results: A total of 249 DEGs were screened from C3 subtype to other subtypes. Metabolic pathway enrichment analysis showed that DEGs were significantly enriched to the hypoxic pathway. Based on univariate and multivariate COX regression analysis, 12 genes from the hypoxia pathway were further screened and used to construct hypoxia-related prognostic model (HRPM). External validation of the HRPM was performed on the GSE21257 dataset. Finally, differences in survival and immune infiltration between high and low risk score groups were compared. Conclusion: In summary, we proposed a hypoxia-associated risk model based on a 12-gene expression signature, which is potentially valuable for prognostic diagnosis of patients with OS.https://doi.org/10.1177/11769343221128537 |
| spellingShingle | Ye Tong Xiaoqing Zhang Ye Zhou Integrated Analysis of Multi-Omics Data to Establish a Hypoxia-Related Prognostic Model in Osteosarcoma Evolutionary Bioinformatics |
| title | Integrated Analysis of Multi-Omics Data to Establish a Hypoxia-Related Prognostic Model in Osteosarcoma |
| title_full | Integrated Analysis of Multi-Omics Data to Establish a Hypoxia-Related Prognostic Model in Osteosarcoma |
| title_fullStr | Integrated Analysis of Multi-Omics Data to Establish a Hypoxia-Related Prognostic Model in Osteosarcoma |
| title_full_unstemmed | Integrated Analysis of Multi-Omics Data to Establish a Hypoxia-Related Prognostic Model in Osteosarcoma |
| title_short | Integrated Analysis of Multi-Omics Data to Establish a Hypoxia-Related Prognostic Model in Osteosarcoma |
| title_sort | integrated analysis of multi omics data to establish a hypoxia related prognostic model in osteosarcoma |
| url | https://doi.org/10.1177/11769343221128537 |
| work_keys_str_mv | AT yetong integratedanalysisofmultiomicsdatatoestablishahypoxiarelatedprognosticmodelinosteosarcoma AT xiaoqingzhang integratedanalysisofmultiomicsdatatoestablishahypoxiarelatedprognosticmodelinosteosarcoma AT yezhou integratedanalysisofmultiomicsdatatoestablishahypoxiarelatedprognosticmodelinosteosarcoma |