Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
State Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Cancer Sci. 2022 Dec;113(12):4289-4299. doi: 10.1111/cas.15553. Epub 2022 Sep 15.
Small cell lung cancer (SCLC) is the most devastating subtype of lung cancer with no clinically available prognostic biomarkers. N -methyladenosine (m A) and noncoding RNAs play critical roles in cancer development and treatment response. However, little is known about m A-related long noncoding RNAs (lncRNAs) in SCLC. We used 206 limited-stage SCLC (LS-SCLC) samples from two cohorts to undertake the first and most comprehensive exploration of the m A-related lncRNA profile in SCLC and constructed a relevant prognostic signature. In total, 289 m A-related lncRNAs were screened out. We then built a seven-lncRNA-based signature in the training cohort with 48 RNA sequencing data using univariate and multivariate Cox regression models. The signature was well validated in an independent cohort containing 158 cases with quantitative PCR data. In both cohorts, the signature divided patients into high- and low-risk groups with significantly different survival rates (both p < 0.001). Our signature predicted chemotherapy survival benefit in patients with LS-SCLC. Receiver operating characteristic and C-index analyses indicated that the signature was better at predicting prognosis and chemotherapy benefit than other clinicopathologic features. Moreover, the signature was identified as an independent predictor of prognosis and chemotherapy response in different cohorts. Furthermore, functional analysis showed that multiple activated immune-related pathways were enriched in the low-risk group. Additionally, the signature was also closely related to various immune checkpoints and inflammatory responses. We generated the first clinically available m A-related lncRNA signature to predict prognosis and chemotherapy benefit in patients with LS-SCLC. Our findings could help optimize the clinical management of patients with LS-SCLC and inform future therapeutic targets for SCLC.
小细胞肺癌（SCLC）是最具破坏性的肺癌亚型，目前临床上尚无可用的预后生物标志物。N6-甲基腺苷（m A）和非编码 RNA 在癌症的发生和治疗反应中起着关键作用。然而，人们对 SCLC 中 m A 相关的长非编码 RNA（lncRNA）知之甚少。我们使用来自两个队列的 206 例局限期 SCLC（LS-SCLC）样本，首次对 SCLC 中 m A 相关 lncRNA 谱进行了最全面的探索，并构建了相关的预后特征。总共筛选出 289 个 m A 相关的 lncRNA。然后，我们使用单变量和多变量 Cox 回归模型，在包含 48 个 RNA 测序数据的训练队列中构建了一个基于七个 lncRNA 的特征。该特征在包含 158 例定量 PCR 数据的独立队列中得到了很好的验证。在两个队列中，该特征将患者分为具有显著不同生存率的高风险和低风险组（均 p < 0.001）。我们的特征预测了 LS-SCLC 患者化疗的生存获益。接收者操作特征和 C 指数分析表明，该特征在预测预后和化疗获益方面优于其他临床病理特征。此外，该特征在不同队列中被确定为预后和化疗反应的独立预测因子。此外，功能分析表明，在低风险组中富集了多个激活的免疫相关途径。此外，该特征还与各种免疫检查点和炎症反应密切相关。我们生成了第一个临床上可用的 m A 相关 lncRNA 特征，以预测 LS-SCLC 患者的预后和化疗获益。我们的研究结果有助于优化 LS-SCLC 患者的临床管理，并为 SCLC 的未来治疗靶点提供信息。
