Insight of a lipid metabolism prognostic model to identify immune landscape and potential target for retroperitoneal liposarcoma
IntroductionThe exploration of lipid metabolism dysregulation may provide novel perspectives for retroperitoneal liposarcoma (RPLS). In our study, we aimed to investigate potential targets and facilitate further understanding of immune landscape in RPLS, through lipid metabolism-associated genes (LM...
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Frontiers Media S.A.
2023-07-01
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| Series: | Frontiers in Immunology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fimmu.2023.1209396/full |
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| author | Zhenyu Wang Ping Tao Peidang Fan Jiongyuan Wang Tao Rong Yingyong Hou Yuhong Zhou Weiqi Lu Liang Hong Lijie Ma Lijie Ma Yong Zhang Hanxing Tong |
| author_facet | Zhenyu Wang Ping Tao Peidang Fan Jiongyuan Wang Tao Rong Yingyong Hou Yuhong Zhou Weiqi Lu Liang Hong Lijie Ma Lijie Ma Yong Zhang Hanxing Tong |
| author_sort | Zhenyu Wang |
| collection | DOAJ |
| description | IntroductionThe exploration of lipid metabolism dysregulation may provide novel perspectives for retroperitoneal liposarcoma (RPLS). In our study, we aimed to investigate potential targets and facilitate further understanding of immune landscape in RPLS, through lipid metabolism-associated genes (LMAGs) based prognostic model.MethodsGene expression profiles and corresponding clinical information of 234 cases were enrolled from two public databases and the largest retroperitoneal tumor research center of East China, including cohort-TCGA (n=58), cohort-GSE30929 (n=92), cohort-FD (n=50), cohort-scRNA-seq (n=4) and cohort-validation (n=30). Consensus clustering analysis was performed to identify lipid metabolism-associated molecular subtypes (LMSs). A prognostic risk model containing 13 LMAGs was established using LASSO algorithm and multivariate Cox analysis in cohort-TCGA. ESTIMATE, CIBERSORT, XCELL and MCP analyses were performed to visualize the immune landscape. WGCNA was used to identify three hub genes among the 13 model LMAGs, and preliminarily validated in both cohort-GSE30929 and cohort-FD. Moreover, TIMER was used to visualize the correlation between antigen-presenting cells and potential targets. Finally, single-cell RNA-sequencing (scRNA-seq) analysis of four RPLS and multiplexed immunohistochemistry (mIHC) were performed in cohort-validation to validate the discoveries of bioinformatics analysis.ResultsLMS1 and LMS2 were characterized as immune-infiltrated and -excluded tumors, with significant differences in molecular features and clinical prognosis, respectively. Elongation of very long chain fatty acids protein 2 (ELOVL2), the enzyme that catalyzed the elongation of long chain fatty acids, involved in the maintenance of lipid metabolism and cellular homeostasis in normal cells, was identified and negatively correlated with antigen-presenting cells and identified as a potential target in RPLS. Furthermore, ELOVL2 was enriched in LMS2 with significantly lower immunoscore and unfavorable prognosis. Finally, a high-resolution dissection through scRNA-seq was performed in four RPLS, revealing the entire tumor ecosystem and validated previous findings.DiscussionThe LMS subgroups and risk model based on LMAGs proposed in our study were both promising prognostic classifications for RPLS. ELOVL2 is a potential target linking lipid metabolism to immune regulations against RPLS, specifically for patients with LMS2 tumors. |
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| language | English |
| last_indexed | 2024-03-13T00:56:54Z |
| publishDate | 2023-07-01 |
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| spelling | doaj.art-3ab64d71e3114eec8313f21d8bb5b9d72023-07-06T16:34:03ZengFrontiers Media S.A.Frontiers in Immunology1664-32242023-07-011410.3389/fimmu.2023.12093961209396Insight of a lipid metabolism prognostic model to identify immune landscape and potential target for retroperitoneal liposarcomaZhenyu Wang0Ping Tao1Peidang Fan2Jiongyuan Wang3Tao Rong4Yingyong Hou5Yuhong Zhou6Weiqi Lu7Liang Hong8Lijie Ma9Lijie Ma10Yong Zhang11Hanxing Tong12First Affiliated Hospital, Anhui University of Science and Technology, Huainan, ChinaDepartment of Laboratory Medicine, Shanghai Traditional Chinese Medicine-Integrated Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, ChinaFirst Affiliated Hospital, Anhui University of Science and Technology, Huainan, ChinaDepartment of General Surgery, Zhongshan Hospital, Fudan University, Shanghai, ChinaFirst Affiliated Hospital, Anhui University of Science and Technology, Huainan, ChinaDepartment of Pathology, Zhongshan Hospital, Fudan University, Shanghai, ChinaDepartment of Medical Oncology, Zhongshan Hospital, Fudan University, Shanghai, ChinaDepartment of General Surgery, Zhongshan Hospital, Fudan University, Shanghai, ChinaDepartment of General Surgery, Shanghai Fifth People’s Hospital, Fudan University, Shanghai, ChinaDepartment of General Surgery, Shanghai Fifth People’s Hospital, Fudan University, Shanghai, ChinaDepartment of Liver Surgery, Renji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, ChinaDepartment of General Surgery, Zhongshan Hospital, Fudan University, Shanghai, ChinaDepartment of General Surgery, Zhongshan Hospital, Fudan University, Shanghai, ChinaIntroductionThe exploration of lipid metabolism dysregulation may provide novel perspectives for retroperitoneal liposarcoma (RPLS). In our study, we aimed to investigate potential targets and facilitate further understanding of immune landscape in RPLS, through lipid metabolism-associated genes (LMAGs) based prognostic model.MethodsGene expression profiles and corresponding clinical information of 234 cases were enrolled from two public databases and the largest retroperitoneal tumor research center of East China, including cohort-TCGA (n=58), cohort-GSE30929 (n=92), cohort-FD (n=50), cohort-scRNA-seq (n=4) and cohort-validation (n=30). Consensus clustering analysis was performed to identify lipid metabolism-associated molecular subtypes (LMSs). A prognostic risk model containing 13 LMAGs was established using LASSO algorithm and multivariate Cox analysis in cohort-TCGA. ESTIMATE, CIBERSORT, XCELL and MCP analyses were performed to visualize the immune landscape. WGCNA was used to identify three hub genes among the 13 model LMAGs, and preliminarily validated in both cohort-GSE30929 and cohort-FD. Moreover, TIMER was used to visualize the correlation between antigen-presenting cells and potential targets. Finally, single-cell RNA-sequencing (scRNA-seq) analysis of four RPLS and multiplexed immunohistochemistry (mIHC) were performed in cohort-validation to validate the discoveries of bioinformatics analysis.ResultsLMS1 and LMS2 were characterized as immune-infiltrated and -excluded tumors, with significant differences in molecular features and clinical prognosis, respectively. Elongation of very long chain fatty acids protein 2 (ELOVL2), the enzyme that catalyzed the elongation of long chain fatty acids, involved in the maintenance of lipid metabolism and cellular homeostasis in normal cells, was identified and negatively correlated with antigen-presenting cells and identified as a potential target in RPLS. Furthermore, ELOVL2 was enriched in LMS2 with significantly lower immunoscore and unfavorable prognosis. Finally, a high-resolution dissection through scRNA-seq was performed in four RPLS, revealing the entire tumor ecosystem and validated previous findings.DiscussionThe LMS subgroups and risk model based on LMAGs proposed in our study were both promising prognostic classifications for RPLS. ELOVL2 is a potential target linking lipid metabolism to immune regulations against RPLS, specifically for patients with LMS2 tumors.https://www.frontiersin.org/articles/10.3389/fimmu.2023.1209396/fullELOVL2retroperitoneal liposarcomaTCGAlipid metabolismimmune landscape |
| spellingShingle | Zhenyu Wang Ping Tao Peidang Fan Jiongyuan Wang Tao Rong Yingyong Hou Yuhong Zhou Weiqi Lu Liang Hong Lijie Ma Lijie Ma Yong Zhang Hanxing Tong Insight of a lipid metabolism prognostic model to identify immune landscape and potential target for retroperitoneal liposarcoma Frontiers in Immunology ELOVL2 retroperitoneal liposarcoma TCGA lipid metabolism immune landscape |
| title | Insight of a lipid metabolism prognostic model to identify immune landscape and potential target for retroperitoneal liposarcoma |
| title_full | Insight of a lipid metabolism prognostic model to identify immune landscape and potential target for retroperitoneal liposarcoma |
| title_fullStr | Insight of a lipid metabolism prognostic model to identify immune landscape and potential target for retroperitoneal liposarcoma |
| title_full_unstemmed | Insight of a lipid metabolism prognostic model to identify immune landscape and potential target for retroperitoneal liposarcoma |
| title_short | Insight of a lipid metabolism prognostic model to identify immune landscape and potential target for retroperitoneal liposarcoma |
| title_sort | insight of a lipid metabolism prognostic model to identify immune landscape and potential target for retroperitoneal liposarcoma |
| topic | ELOVL2 retroperitoneal liposarcoma TCGA lipid metabolism immune landscape |
| url | https://www.frontiersin.org/articles/10.3389/fimmu.2023.1209396/full |
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