最新的研究表明，TMEM251编码的溶酶体酶转运因子（LYSET）是氨基酸代谢重编程（AAMR）的关键调节因子，并且相关通路与某些肿瘤的进展显著相关。本研究的目的是探索TMEM251在透明细胞肾细胞癌（ccRCC）中的潜在通路，并基于这些通路中的中心基因建立相关的预测模型，用于预后和肿瘤免疫微环境（TIME）。我们从癌症基因组图谱（TCGA），E-MATE-1980和免疫治疗队列中获得了ccRCC样本的mRNA表达数据和临床信息。单细胞测序数据（GSE152938）从基因表达数据库（GEO）中下载。我们通过Gene Ontology（GO）和Kyoto Encyclopedia of Genes and Genomes（KEGG）分析TMEM251共表达基因的 Bi学通路进行了探索。通过Gene Set Variation Analysis（GSVA）和无监督聚类分析，研究了LYSET相关通路与预后的相关性。在饱和缩减选择运算符（LASSO）和Cox回归的指导下，鉴定了中心预后基因并构建了风险评分。通过CIBERSORTx和Tumor Immune Estimation Resource（TIMER）数据库进行了免疫浸润分析。通过肿瘤突变负荷（TMB）评分、免疫检查点表达和生存分析，分析了风险评分和中心预后基因对免疫治疗反应的预测价值。最后，通过免疫组化（IHC）验证了中心预后基因的表达。发现TMEM251与一些AAMR通路显著相关。最终确定了LYSET相关通路中的AAGAB、ENTR1、SCYL2和WDR72，用于构建风险评分模型。免疫浸润分析显示LYSET相关基因签名显著影响CD4+细胞、NK细胞、M2巨噬细胞等重要免疫细胞的浸润情况。此外，构建的风险评分与TMB和一些常见免疫检查点的表达呈正相关。在免疫治疗队列中，这些基因签名对Nibolumab治疗反应的预测价值也不同。最后，基于单细胞测序分析发现，TMEM251和中心基因签名在肿瘤细胞和一些免疫细胞中具有表达。有趣的是，IHC验证显示四个中心基因在ccRCC进展中具有潜在的双重作用。我们建立的新型预测性生物标志物可能有益于ccRCC的临床决策。我们的研究可能为LYSET相关基因签名成为治疗ccRCC和提高免疫治疗效果的新潜在靶点提供一些证据。我们的计算评分图可能对临床选择有益，但结果需要未来更多的实验验证。©2023年。作者（们）。

The latest research shows that the lysosomal enzyme trafficking factor (LYSET) encoded by TMEM251 is a key regulator of the amino acid metabolism reprogramming (AAMR) and related pathways significantly correlate with the progression of some tumors. The purpose of this study was to explore the potential pathways of the TMEM251 in clear cell renal cell carcinoma (ccRCC) and establish related predictive models based on the hub genes in these pathways for prognosis and tumor immune microenvironment (TIME).We obtained mRNA expression data and clinical information of ccRCC samples from The Cancer Genome Atlas (TCGA), E-MATE-1980, and immunotherapy cohorts. Single-cell sequencing data (GSE152938) were downloaded from the Gene Expression Omnibus (GEO) database. We explored biological pathways of the LYSET by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses of TMEM251-coexpression genes. The correlation of LYSET-related pathways with the prognosis was conducted by Gene Set Variation Analysis (GSVA) and unsupervised cluster analysis. The least absolute shrinkage and selection operator (LASSO) and Cox regression were used to identify hub prognostic genes and construct the risk score. Immune infiltration analysis was conducted by CIBERSORTx and Tumor Immune Estimation Resource (TIMER) databases. The predictive value of the risk score and hub prognostic genes on immunotherapy responsiveness was analyzed through the tumor mutation burden (TMB) score, immune checkpoint expression, and survival analysis. Immunohistochemistry (IHC) was finally used to verify the expressions of hub prognostic genes.The TMEM251 was found to be significantly correlated with some AAMR pathways. AAGAB, ENTR1, SCYL2, and WDR72 in LYSET-related pathways were finally identified to construct a risk score model. Immune infiltration analysis showed that LYSET-related gene signatures significantly influenced the infiltration of some vital immune cells such as CD4 + cells, NK cells, M2 macrophages, and so on. In addition, the constructed risk score was found to be positively correlated with TMB and some common immune checkpoint expressions. Different predictive values of these signatures for Nivolumab therapy responsiveness were also uncovered in immunotherapy cohorts. Finally, based on single-cell sequencing analysis, the TMEM251 and the hub gene signatures were found to be expressed in tumor cells and some immune cells. Interestingly, IHC verification showed a potential dual role of four hub genes in ccRCC progression.The novel predictive biomarkers we built may benefit clinical decision-making for ccRCC. Our study may provide some evidence that LYSET-related gene signatures could be novel potential targets for treating ccRCC and improving immunotherapy efficacy. Our nomogram might be beneficial to clinical choices, but the results need more experimental verifications in the future.© 2023. The Author(s).