Retinoic Acid Metabolism-Related Enzyme Signature Identified Prognostic and Immune Characteristics in Sarcoma

• Published in: Frontiers in cell and developmental biology Vol. 9; p. 780951
• Main Authors: Xu, HuaiYuan, Hu, JinXin, Song, YiJiang, Chen, HongMin, Xu, YanYang, Deng, ChuangZhong, Wu, Hao, Song, GuoHui, Lu, JinChang, Tang, QinLian, Xia, LiangPing, Wang, Jin, Zhu, XiaoJun
• Format: Journal Article
• Language: English
• Published: Switzerland Frontiers Media S.A 03.02.2022
• Subjects: CD8+ T cell; Cell and Developmental Biology; immune; LASSO-penalized cox regression; retinoic acid metabolism; sarcoma; LASSO-penalized cox regression; immune; sarcoma; CD8+ T cell; retinoic acid metabolism
• ISSN: 2296-634X; 2296-634X
• DOI: 10.3389/fcell.2021.780951

Growing evidence indicates a link between retinoic acid (RA) metabolism and sarcoma progression or immunity in laboratory studies. However, a comprehensive analysis of RA abnormality in the sarcoma population is still lacking. Herein, we systematically analyzed the molecular features of 19 retinoic acid metabolism-related enzymes and sarcoma patients' clinical information based on TCGA/TARGET/GSE datasets. We identified two RA expression subtypes, which were related to distinct clinical survival outcomes and exhibited different biological features. Gene set enrichment analysis indicated a set of immune pathways were enriched in G1 while oncogenic pathways were enriched in G2. Immune cell infiltration analysis using the TIMER algorithm revealed more CD4 and CD8 T cell infiltration in G1 subgroups than in G2. Moreover, we generated a seven genes signature to predict the RA metabolism index based on the LASSO-penalized Cox regression model. Survival analysis demonstrated the significant prognostic differences between high- and low-risk groups among different bone and soft tissue datasets. A higher risk index was associated with less T cell CD8 infiltration. The predictive ability of the RA risk score was validated in 71 bone or soft tissue sarcoma clinical samples. These results indicated that RA-based classification could distinguish sarcoma patients with different clinical outcomes and immune statuses, which may help to explore better treatment decision-making for sarcoma patients.