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BACKGROUND

Bladder cancer, a highly fatal disease, poses a significant threat to patients. Positioned at 19q13.2-13.3, LIG1, one of the four DNA ligases in mammalian cells, is frequently deleted in tumour cells of diverse origins. Despite this, the precise involvement of LIG1 in BLCA remains elusive. This pioneering investigation delves into the uncharted territory of LIG1's impact on BLCA. Our primary objective is to elucidate the intricate interplay between LIG1 and BLCA, alongside exploring its correlation with various clinicopathological factors.

METHODS

We retrieved gene expression data of para-carcinoma tissues and bladder cancer (BLCA) from the GEO repository. Single-cell sequencing data were processed using the "Seurat" package. Differential expression analysis was then performed with the "Limma" package. The construction of scale-free gene co-expression networks was achieved using the "WGCNA" package. Subsequently, a Venn diagram was utilized to extract genes from the positively correlated modules identified by WGCNA and intersect them with differentially expressed genes (DEGs), isolating the overlapping genes. The "STRINGdb" package was employed to establish the protein-protein interaction (PPI) network.Hub genes were identified through the PPI network using the Betweenness Centrality (BC) algorithm. We conducted KEGG and GO enrichment analyses to uncover the regulatory mechanisms and biological functions associated with the hub genes. A machine-learning diagnostic model was established using the R package "mlr3verse." Mutation profiles between the LIG1^high and LIG1^low groups were visualized using the BEST website. Survival analyses within the LIG1^high and LIG1^low groups were performed using the BEST website and the GENT2 website. Finally, a series of functional experiments were executed to validate the functional role of LIG1 in BLCA.

RESULTS

Our investigation revealed an upregulation of LIG1 in BLCA specimens, with heightened LIG1 levels correlating with unfavorable overall survival outcomes. Functional enrichment analysis of hub genes, as evidenced by GO and KEGG enrichment analyses, highlighted LIG1's involvement in critical function such as the DNA replication, cellular senescence, cell cycle and the p53 signalling pathway. Notably, the mutational landscape of BLCA varied significantly between LIG1 and LIG1 groups.Immune infiltrating analyses suggested a pivotal role for LIG1 in immune cell recruitment and immune regulation within the BLCA microenvironment, thereby impacting prognosis. Subsequent experimental validations further underscored the significance of LIG1 in BLCA pathogenesis, consolidating its functional relevance in BLCA samples.

CONCLUSIONS

Our research demonstrates that LIG1 plays a crucial role in promoting bladder cancer malignant progression by heightening proliferation, invasion, EMT, and other key functions, thereby serving as a potential risk biomarker.

BACKGROUND

METHODS

RESULTS

CONCLUSIONS

背景

膀胱癌是一种致命性很高的疾病，对患者构成重大威胁。位于 19q13.2-13.3 的 LIG1 是哺乳动物细胞中的四种 DNA 连接酶之一，在不同来源的肿瘤细胞中经常缺失。尽管如此，LIG1 在膀胱癌中的确切作用仍不清楚。这项开创性的研究深入探讨了 LIG1 对膀胱癌的影响。我们的主要目标是阐明 LIG1 与膀胱癌之间错综复杂的相互作用，并探讨其与各种临床病理因素的相关性。

方法

我们从 GEO 数据库中检索了癌旁组织和膀胱癌 (BLCA) 的基因表达数据。使用“Seurat”软件包处理单细胞测序数据。使用“Limma”软件包进行差异表达分析。使用“WGCNA”软件包构建无标度基因共表达网络。随后，使用 Venn 图从 WGCNA 鉴定的正相关模块中提取基因，并与差异表达基因 (DEGs) 进行交集，分离重叠基因。使用“STRINGdb”软件包建立蛋白质-蛋白质相互作用 (PPI) 网络。使用节点之间的中间中心度 (BC) 算法从 PPI 网络中识别枢纽基因。我们进行了 KEGG 和 GO 富集分析，以揭示与枢纽基因相关的调控机制和生物学功能。使用 R 包“mlr3verse”建立机器学习诊断模型。使用 BEST 网站可视化 LIG1^high 和 LIG1^low 组之间的突变谱。使用 BEST 网站和 GENT2 网站在 LIG1^high 和 LIG1^low 组内进行生存分析。最后，进行了一系列功能实验来验证 LIG1 在 BLCA 中的功能作用。

结果

我们的研究表明，LIG1 在 BLCA 标本中上调，LIG1 水平升高与总生存期不良相关。通过 GO 和 KEGG 富集分析，对枢纽基因进行功能富集分析，突出了 LIG1 在 DNA 复制、细胞衰老、细胞周期和 p53 信号通路等关键功能中的作用。值得注意的是，LIG1 和 LIG1 组之间的膀胱癌突变图谱差异显著。免疫浸润分析表明，LIG1 在膀胱癌微环境中的免疫细胞募集和免疫调节中发挥关键作用，从而影响预后。随后的实验验证进一步强调了 LIG1 在 BLCA 发病机制中的重要性，巩固了其在 BLCA 样本中的功能相关性。