Long noncoding RNAs (lncRNAs) have been associated with cancer immunity regulation and the tumor microenvironment (TME). However, functions of lncRNAs of tumor-infiltrating B lymphocytes (TIL-Bs) and their clinical significance have not yet been fully elucidated. In the present study, a machine learning-based computational framework is presented for the identification of lncRNA signature of TIL-Bs (named 'TILBlncSig') through integrative analysis of immune, lncRNA and clinical profiles. The TILBlncSig comprising eight lncRNAs (TNRC6C-AS1, WASIR2, GUSBP11, OGFRP1, AC090515.2, PART1, MAFG-DT and LINC01184) was identified from the list of 141 B-cell-specific lncRNAs. The TILBlncSig was capable of distinguishing worse compared with improved survival outcomes across different independent patient datasets and was also independent of other clinical covariates. Functional characterization of TILBlncSig revealed it to be an indicator of infiltration of mononuclear immune cells (i.e. natural killer cells, B-cells and mast cells), and it was associated with hallmarks of cancer, as well as immunosuppressive phenotype. Furthermore, the TILBlncSig revealed predictive value for the survival outcome and immunotherapy response of patients with anti-programmed death-1 (PD-1) therapy and added significant predictive power to current immune checkpoint gene markers. The present study has highlighted the value of the TILBlncSig as an indicator of immune cell infiltration in the TME from a noncoding RNA perspective and strengthened the potential application of lncRNAs as predictive biomarkers of immunotherapy response, which warrants further investigation.

中文翻译：

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肿瘤浸润性 B 淋巴细胞 lncRNA 特征的计算识别对膀胱癌预后和免疫治疗的潜在影响。

长链非编码 RNA (lncRNA) 与癌症免疫调节和肿瘤微环境 (TME) 相关。然而，肿瘤浸润性 B 淋巴细胞 (TIL-B) 的 lncRNA 的功能及其临床意义尚未完全阐明。在本研究中，提出了一种基于机器学习的计算框架，用于通过对免疫、lncRNA 和临床特征的综合分析来识别 TIL-Bs 的 lncRNA 特征（命名为“TILBlncSig”）。从 141 个 B 细胞特异性 lncRNA 列表中鉴定出包含 8 个 lncRNA（TNRC6C-AS1、WASIR2、GUSBP11、OGFRP1、AC090515.2、PART1、MAFG-DT 和 LINC01184）的 TILBlncSig。TILBlncSig 能够区分不同独立患者数据集的生存结果与改善的生存结果相比更糟，并且也独立于其他临床协变量。TILBlncSig 的功能特征表明它是单核免疫细胞（即自然杀伤细胞、B 细胞和肥大细胞）浸润的指标，并且它与癌症的标志以及免疫抑制表型相关。此外，TILBlncSig 揭示了抗程序性死亡 1 (PD-1) 治疗患者的生存结果和免疫治疗反应的预测价值，并为当前的免疫检查点基因标记增加了显着的预测能力。