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Predictive value of an ICD-associated DAMP gene signature for survival and immunotherapy response in osteosarcoma
Hao Jin1, Xinyuan Zhang1, Haopeng Li1
1Department of Orthopedics, The First Affiliated Hospital of Harbin Medical University, China.
Background:
The tumor microenvironment (TME) in osteosarcoma, shaped by damage-associated molecular patterns (DAMPs) released during immunogenic cell death (ICD)-a process that elicits robust immune responses-critically modulates antitumor immunity, particularly in this aggressive malignancy. Despite the recognized importance of DAMPs in various cancers, including osteosarcoma, comprehensive research into their impact specifically within osteosarcoma remains limited. This study aims to elucidate the impact of DAMPs on immune cell infiltration and antitumor immunity in osteosarcoma by identifying and characterizing DAMP-associated gene expression profiles.
Methods:
This study analyzed a curated set of ICD-related DAMP genes from the TARGET-OS and GSE21257 datasets to investigate their prognostic significance in osteosarcoma patients. We applied unsupervised clustering to classify osteosarcoma patients into distinct DAMP-associated subtypes based on gene expression profiles. The gene expression profiles and their prognostic significance were evaluated using univariate and multivariate Cox regression analyses in the osteosarcoma cohort. Immune characteristics were assessed using the ESTIMATE and ssGSEA algorithms, with molecular differences compared between the subtypes. GO and KEGG enrichment analyses were performed to identify immune-related biological pathways underlying the DAMP-associated subtypes.
Results:
Two DAMP-associated subtypes with distinct prognostic profiles were identified; Cluster 1 exhibited poorer survival outcomes and elevated expression of immune checkpoint molecules, indicative of an immunosuppressive tumor microenvironment. A prognostic model, constructed using LASSO-selected genes (FPR1, TLR4), effectively stratified patients into high- and low-risk groups, with the low-risk group demonstrating superior survival and potential responsiveness to immunotherapy.
Conclusion:
Our findings underscore the critical role of DAMP-related genes in influencing the immune landscape of osteosarcoma, providing novel insights into the mechanisms that drive differential responses to treatment. By harnessing the prognostic potential of DAMP-related genes, this study advances personalized medicine in osteosarcoma, potentially improving the efficacy of immunotherapeutic interventions.
Insights
Damage-associated molecular patterns (DAMPs) significantly impact osteosarcoma immunity. Identifying DAMP-related gene profiles can predict patient outcomes and guide immunotherapy for better treatment efficacy.
Area of Science:
- Oncology
- Immunology
- Genomics
Background:
- The tumor microenvironment (TME) in osteosarcoma is influenced by damage-associated molecular patterns (DAMPs) released during immunogenic cell death (ICD).
- Limited research exists on the specific impact of DAMPs on osteosarcoma's immune landscape and antitumor immunity.
Purpose of the Study:
- To investigate the role of DAMPs in modulating immune cell infiltration and antitumor immunity in osteosarcoma.
- To identify DAMP-associated gene expression profiles and their prognostic significance.
Main Methods:
- Analysis of ICD-related DAMP genes from TARGET-OS and GSE21257 datasets.
- Unsupervised clustering to define DAMP-associated osteosarcoma subtypes.
- Prognostic evaluation using Cox regression, ESTIMATE, ssGSEA, GO, and KEGG enrichment analyses.
Main Results:
- Two distinct DAMP-associated subtypes were identified, with one showing poorer survival and an immunosuppressive TME.
- A prognostic model using FPR1 and TLR4 stratified patients into high- and low-risk groups.
- The low-risk group demonstrated better survival and potential immunotherapy response.
Conclusions:
- DAMP-related genes are critical in shaping the osteosarcoma immune landscape and treatment response.
- Harnessing DAMP gene prognostic potential advances personalized medicine and immunotherapy efficacy in osteosarcoma.
