Establishment of a CD8+T cells-related prognostic risk model for acral melanoma based on single-cell and bulk RNA sequencing

被引:0
|
作者
Wang, Wenwen [1 ,2 ]
Liu, Pu [3 ,4 ]
Ma, Jie [4 ]
Li, Jun [1 ]
Leng, Ling [2 ]
机构
[1] Peking Union Med Coll & Chinese Acad Med Sci, Peking Union Med Coll Hosp, Dept Dermatol, Beijing, Peoples R China
[2] Chinese Acad Med Sci & Peking Union Med Coll, Peking Union Med Coll Hosp, Ctr Translat Med, State Key Lab Complex Severe & Rare Dis,Stem Cell, Beijing, Peoples R China
[3] Chongqing Univ Posts & Telecommun, Chongqing Key Lab Big Data Bio Intelligence, Chongqing, Peoples R China
[4] Beijing Inst Life, Beijing Proteome Res Ctr, Natl Ctr Prot Sci Beijing, State Key Lab Med Prote, Beijing, Peoples R China
关键词
acral melanoma; CD8+T cells; prognostic model; single-cell RNA sequencing; CANCER-IMMUNOTHERAPY; ANTITUMOR RESPONSES; CUTANEOUS MELANOMA; UNITED-STATES; CHOP GADD153; EXPRESSION; ACTIVATION; SURVIVAL; RECEPTOR; APOPTOSIS;
D O I
10.1111/srt.13900
中图分类号
R75 [皮肤病学与性病学];
学科分类号
100206 ;
摘要
BackgroundCD8+ T cells have been recognized as crucial factors in the prognosis of melanoma. However, there is currently a lack of gene markers that accurately describe their characteristics and functions in acral melanoma (AM), which hinders the development of personalized medicine.MethodsFirstly, we explored the composition differences of immune cells in AM using single-cell RNA sequencing (scRNA-seq) data and comprehensively characterized the immune microenvironment of AM in terms of composition, developmental differentiation, function, and cell communication. Subsequently, we constructed and validated a prognostic risk scoring model based on differentially expressed genes (DEGs) of CD8+ T cells using the TCGA-SKCM cohort through Lasso-Cox method. Lastly, immunofluorescence staining was performed to validate the expression of four genes (ISG20, CCL4, LPAR6, DDIT3) in AM and healthy skin tissues as included in the prognostic model.ResultsThe scRNA-seq data revealed that memory CD8+ T cells accounted for the highest proportion in the immune microenvironment of AM, reaching 70.5%. Cell-cell communication analysis showed extensive communication relationships among effector CD8+ T cells. Subsequently, we constructed a prognostic scoring model based on DEGs derived from CD8+ T cell sources. Four CD8+ T cell-related genes were included in the construction and validation of the prognostic model. Additionally, immunofluorescence results demonstrated that ISG20 and CCL4 were downregulated, while LPAR6 and DDIT3 were upregulated in AM tissues compared to normal skin tissues.ConclusionIdentifying biomarkers based on the expression levels of CD8+ T cell-related genes may be an effective approach for establishing prognostic models in AM patients. The independently prognostic risk evaluation model we constructed provides new insights and theoretical support for immunotherapy in AM.
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页数:13
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