Immune-related glycosylation genes based classification predicts prognosis and therapy options of osteosarcoma.

Autor: Wang W; Zhejiang University, Hangzhou, Zhejiang 310058, China; Department of Orthopedics, Fenghua People's Hospital, 36 Gongyuan Road, Ningbo, Zhejiang 315502, China; Department of Orthopedics, Musculoskeletal Tumor Center, the Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang 310009, China., Jiao Y; Clinical Laboratory, Minhang Hospital, Fudan University, No. 170, Xinsong Road, Shanghai 201199, China., Du X; Shanghai East Hospital, Tongji University School of Medicine, Shanghai 200120, China. Electronic address: wzmudxj@163.com., Ye Z; Zhejiang University, Hangzhou, Zhejiang 310058, China; Department of Orthopedics, Musculoskeletal Tumor Center, the Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang 310009, China. Electronic address: yezhaoming@zju.edu.cn.
Jazyk: angličtina
Zdroj: Gene [Gene] 2024 Oct 05; Vol. 933, pp. 148985. Date of Electronic Publication: 2024 Oct 05.
DOI: 10.1016/j.gene.2024.148985
Abstrakt: Osteosarcoma is the most common primary bone malignancy, with a very poor prognosis. Aberrant glycosylation is close involvement in osteosarcoma. Accordingly, this study aimed at investigating the role of glycosylation genes in the prognosis and therapy options of osteosarcoma. The microenvironment of osteosarcoma was assessed using estimate algorithm. A total of 20 immune-related glycosylation genes (IRGGs) was identified using Pearson correlation analysis. Accordingly, osteosarcoma patients were divided into C1 and C2 type using consensus clustering. Multiple algorithms (Xcell, MCP-counter, ssGSEA, epic, quantiseq), cancer immune cycle analysis, and GSVA were applied to estimate the immune, molecule and metabolism characteristics of osteosarcoma, indicating that C1 type was featured with high immune infiltration, high glycosylation, enriched MEK signaling, and good prognosis, while C2 type was characterized by more metastasis, enriched immunotherapy-positive gene signatures, high tumor mutation burden, and poor prognosis. Results from TIDE algorithm and immunotherapy datasets suggested the C2 type's preference of immune checkpoint inhibitors (ICIs), while data of GDSC, CMap analysis and cell experiments indicated that C1 type was sensitivity to MEK inhibitor PD0325901. In addition, univariate Cox and Lasso analysis was combined to establish an IRGGs' risk score containing 6 genes (B3GNT8, FUT7, GAL3ST4, GALNT14, HS3ST2, and MFNG). The data of DCA and ROC indicated its well prediction of prognosis in osteosarcoma. Finally, cellular location analysis showed that the 6 genes not only distributed in tumor cells but also in immune cells. In summary, the classification and risk score based on IRGGs effectively predicted the prognosis and therapy options of osteosarcoma. Further studies on IRGGs may contribute to the understanding of cancer immunity in osteosarcoma.
Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
(Copyright © 2024. Published by Elsevier B.V.)
Databáze: MEDLINE
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