Liao Yan, Chen Junkai, Yao Hao, Zheng Ting, Tu Jian, Chen Weidong, Guo ZeHao, Zou Yutong, Wen Lili, Xie Xianbiao
Department of Musculoskeletal Oncology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, 510080, China.
Guangdong Provincial Key Laboratory of Orthopedics and Traumatology, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, 510080, Guangdong, China.
J Transl Med. 2025 Jan 22;23(1):103. doi: 10.1186/s12967-025-06086-1.
Osteosarcoma is the most common malignant bone tumor in children and adolescents, characterized by high disability and mortality rates. Over the past three decades, therapeutic outcomes have plateaued, underscoring the critical need for innovative therapeutic targets. Solute carrier (SLC) family transporters have been implicated in the malignant progression of a variety of tumors, however, their specific role in osteosarcoma remains poorly understood.
The single-cell sequencing data from GSE152048 and GSE162454, along with RNA-seq from the TARGET and GSE21257 cohorts, were utilized for the analysis in this study. LASSO regression analysis was conducted to identify prognostic genes and construct an SLC-related prognostic signature. Survival analysis and ROC analysis evaluated the validity of the prognostic signature. The ESTIMATE and CIBERSORT Packages were utilized to assess the immune infiltration status. Pseudotime and CellChat analyses were performed to investigate the relationship between SLC7A1, malignant phenotypes, and the immune microenvironment. CCK8 assays, EdU staining, colony formation assays, Transwell assays, and co-culture systems were used to assess the effects of SLC7A1 on cell proliferation, metastasis, and macrophage polarization. Finally, virtual docking identified potential drugs targeting SLC7A1.
SLCs displayed distinct expression patterns across various cell types within the osteosarcoma microenvironment, with myeloid cells exhibiting a preference for amino acid uptake. A prognostic model comprising nine genes was constructed via LASSO regression, with SLC7A1 showing the highest hazard ratio. Multiple analytical algorithms indicated that SLCs were associated with immune cell infiltration and immune checkpoint gene expression. Single-cell analysis indicated that SLC7A1 was predominantly expressed in osteosarcoma cells and correlated with various malignant tumor characteristics. SLC7A1 also regulate interactions between tumor cells and macrophages, as well as modulate macrophage function through multiple pathways. In vitro assays and survival analysis demonstrated that inhibition of SLC7A1 suppressed the malignant phenotype of osteosarcoma cells, with SLC7A1 expression correlating with poor prognosis. Co-culture models confirmed the involvement of SLC7A1 in macrophage polarization. Finally, virtual screening and CETSA identified Cepharanthine as potential inhibitors of SLC7A1.
SLC-related prognostic signatures can be utilized for the prognostic evaluation of osteosarcoma. Pharmacological inhibition of SLC7A1 may be a feasible therapeutic approach for osteosarcoma.
骨肉瘤是儿童和青少年中最常见的恶性骨肿瘤,其特点是致残率和死亡率高。在过去三十年中,治疗效果已趋于平稳,这突出表明迫切需要创新的治疗靶点。溶质载体(SLC)家族转运蛋白与多种肿瘤的恶性进展有关,然而,它们在骨肉瘤中的具体作用仍知之甚少。
本研究利用来自GSE152048和GSE162454的单细胞测序数据,以及来自TARGET和GSE21257队列的RNA测序数据。进行LASSO回归分析以鉴定预后基因并构建与SLC相关的预后特征。生存分析和ROC分析评估了预后特征的有效性。利用ESTIMATE和CIBERSORT软件包评估免疫浸润状态。进行伪时间分析和CellChat分析以研究SLC7A1、恶性表型和免疫微环境之间的关系。使用CCK8测定、EdU染色、集落形成测定、Transwell测定和共培养系统来评估SLC7A1对细胞增殖、转移和巨噬细胞极化的影响。最后,虚拟对接确定了靶向SLC7A1的潜在药物。
SLC在骨肉瘤微环境中的各种细胞类型中表现出不同的表达模式,髓样细胞对氨基酸摄取表现出偏好。通过LASSO回归构建了一个包含九个基因的预后模型,其中SLC7A1显示出最高的风险比。多种分析算法表明,SLC与免疫细胞浸润和免疫检查点基因表达相关。单细胞分析表明,SLC7A1主要在骨肉瘤细胞中表达,并与各种恶性肿瘤特征相关。SLC7A1还调节肿瘤细胞与巨噬细胞之间的相互作用,并通过多种途径调节巨噬细胞功能。体外试验和生存分析表明,抑制SLC7A1可抑制骨肉瘤细胞的恶性表型,SLC7A1表达与不良预后相关。共培养模型证实了SLC7A参与巨噬细胞极化。最后,虚拟筛选和CETSA确定千金藤素为SLC7A1的潜在抑制剂。
与SLC相关的预后特征可用于骨肉瘤的预后评估。对SLC7A1的药理学抑制可能是骨肉瘤的一种可行治疗方法。