Huang Yi, Gui Zhongxuan, Wu Muyun, Zhang Mengmeng, Jiang Yue, Ding Qiaoqiao, Yang Jinping, Ye Yingquan, Zhang Mei
Wuhu Hospital of Traditional Chinese Medicine, Wuhu, 241000, China.
Oncology Department of Integrated Traditional Chinese and Western Medicine, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022, China.
Heliyon. 2024 Oct 18;10(21):e39496. doi: 10.1016/j.heliyon.2024.e39496. eCollection 2024 Nov 15.
The tumor immune microenvironment (TIME) plays a pivotal role in determining ovarian cancer (OC) prognosis. Long non-coding RNAs (lncRNAs) are key regulators of immune response and tumor progression in OC. Among these, tumor-infiltrating B cells represent an emerging target in immune response pathways. However, the specific involvement of B cell-related lncRNAs (BCRLs) in OC remains unclarified.
Leveraging single-cell and bulk RNA-sequencing data, correlation analysis identified BCRLs in ovarian serous cystadenocarcinoma (OV) from the TCGA database. Subsequently, BCRLIs were filtered through COX survival analysis and the LASSO algorithm, leading to the development of a B cell-related lncRNA scoring system (BCRLss). The predictive accuracy of BCRLss for prognosis in TCGA-OV was assessed and externally validated in an independent cohort. Functional enrichment analyses were conducted to elucidate biological pathways associated with risk subgroups. Additionally, the relationship between BCRLss and TIME was investigated through multiple algorithms and consensus clustering, uncovering potential immune response targets. Drug sensitivity analyses further identified potential therapeutic options tailored to risk subgroups. The highest risk score lncRNA was selected for validation.
The BCRLss was constructed using six BCRLIs. Survival analysis revealed an improved prognosis in the low-risk group, with results corroborated by external validation in the ICGC-OV cohort. ROC analysis and nomogram construction confirmed the strong prognostic accuracy of BCRLss. Enrichment analysis highlighted associations between risk subgroups and tumor immune pathways, with the low-risk group demonstrating a more robust immune response and elevated expression of immune checkpoint-related genes. Drug sensitivity tests revealed notable differences across risk subgroups. experiments confirmed elevated LINC01150 expression in OC cells, and LINC01150 knockdown significantly inhibited the proliferation, invasion, and migration of SKOV3 cells.
In conclusion, BCRLss provides a reliable prognostic tool for predicting clinical outcomes and the immune landscape of patients with OC, offering valuable guidance for immunotherapy target selection and personalized treatment strategies.
肿瘤免疫微环境(TIME)在决定卵巢癌(OC)预后方面起着关键作用。长链非编码RNA(lncRNAs)是OC免疫反应和肿瘤进展的关键调节因子。其中,肿瘤浸润性B细胞是免疫反应途径中一个新兴的靶点。然而,B细胞相关lncRNAs(BCRLs)在OC中的具体作用仍不清楚。
利用单细胞和批量RNA测序数据,通过相关性分析从TCGA数据库中鉴定出卵巢浆液性囊腺癌(OV)中的BCRLs。随后,通过COX生存分析和LASSO算法筛选出BCRLIs,进而建立了B细胞相关lncRNA评分系统(BCRLss)。评估了BCRLss对TCGA-OV预后的预测准确性,并在一个独立队列中进行了外部验证。进行功能富集分析以阐明与风险亚组相关的生物学途径。此外,通过多种算法和一致性聚类研究了BCRLss与TIME之间的关系,发现了潜在的免疫反应靶点。药物敏感性分析进一步确定了针对风险亚组的潜在治疗方案。选择风险评分最高的lncRNA进行验证。
使用六个BCRLIs构建了BCRLss。生存分析显示低风险组预后改善,ICGC-OV队列的外部验证证实了这一结果。ROC分析和列线图构建证实了BCRLss具有很强的预后准确性。富集分析突出了风险亚组与肿瘤免疫途径之间的关联,低风险组表现出更强的免疫反应和免疫检查点相关基因的高表达。药物敏感性测试显示不同风险亚组之间存在显著差异。实验证实OC细胞中LINC01150表达升高,LINC01150基因敲低显著抑制SKOV3细胞的增殖、侵袭和迁移。
总之,BCRLss为预测OC患者的临床结局和免疫格局提供了一种可靠的预后工具,为免疫治疗靶点选择和个性化治疗策略提供了有价值的指导。