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Retinoic acid metabolism-related enzyme signature identified prognostic and immunotherapeutic efficiency in sarcoma

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Abstract Background: Dynamic balance of retinoic acid metabolism plays a major role in a variety of biological functions including cell proliferation and differentiation, while its dysregulation often leads to cancer progression and disordered immunity. Targeting retinoic acid signaling has shown effectivity in re-educates tumor microenvironment so that they could enhance the efficacy of immunotherapies and received better outcome. However, a comprehensive analysis of retinoic acid metabolism abnormality in sarcoma is still lacking, which limits the development and application of related targeted drugs.Methods: The RA metabolism related enzymes data set was collected from several database. Then we systematically analyzed the molecular features of 19 retinoic acid metabolism-related enzymes based on TCGA/TARGET/GSE datasets and revealed two subtypes with distinct metabolic status and prognostic value. And we further generated a 7 genes signature to predict retinoic acid metabolism index based on LASSO-penalized Cox regression model.Results: Gene set enrichment analysis indicated a set of immune and oncogenic pathways were enriched in poor-prognosis group. Connectivity Map screened 56 potential small molecules specific to different sub-groups. Survival analysis demonstrated significant prognostic difference between high- and low-risk groups among all datasets. Several immune cells including CD8+ T cells, Treg cells, Monocytes, and Macrophages showed different abundance between these groups, and immune checkpoint blockade therapy response prediction indicated potential immunotherapeutic efficiency of poor-prognosis group.Conclusions: Taken together, our study elaborated two different retinoic acid metabolism status of sarcoma, which revealed the metabolic heterogeneity of sarcoma. Robust and powerful metabolic index risk model could provide insightful suggestions to explore the molecular functions and mechanisms of retinoic acid metabolism.
Title: Retinoic acid metabolism-related enzyme signature identified prognostic and immunotherapeutic efficiency in sarcoma
Description:
Abstract Background: Dynamic balance of retinoic acid metabolism plays a major role in a variety of biological functions including cell proliferation and differentiation, while its dysregulation often leads to cancer progression and disordered immunity.
Targeting retinoic acid signaling has shown effectivity in re-educates tumor microenvironment so that they could enhance the efficacy of immunotherapies and received better outcome.
However, a comprehensive analysis of retinoic acid metabolism abnormality in sarcoma is still lacking, which limits the development and application of related targeted drugs.
Methods: The RA metabolism related enzymes data set was collected from several database.
Then we systematically analyzed the molecular features of 19 retinoic acid metabolism-related enzymes based on TCGA/TARGET/GSE datasets and revealed two subtypes with distinct metabolic status and prognostic value.
And we further generated a 7 genes signature to predict retinoic acid metabolism index based on LASSO-penalized Cox regression model.
Results: Gene set enrichment analysis indicated a set of immune and oncogenic pathways were enriched in poor-prognosis group.
Connectivity Map screened 56 potential small molecules specific to different sub-groups.
Survival analysis demonstrated significant prognostic difference between high- and low-risk groups among all datasets.
Several immune cells including CD8+ T cells, Treg cells, Monocytes, and Macrophages showed different abundance between these groups, and immune checkpoint blockade therapy response prediction indicated potential immunotherapeutic efficiency of poor-prognosis group.
Conclusions: Taken together, our study elaborated two different retinoic acid metabolism status of sarcoma, which revealed the metabolic heterogeneity of sarcoma.
Robust and powerful metabolic index risk model could provide insightful suggestions to explore the molecular functions and mechanisms of retinoic acid metabolism.

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