Department of Thoracic Medical Oncology, Fudan University Shanghai Cancer Center, and Shanghai Key Laboratory of Medical Epigenetics, International Co-laboratory of Medical Epigenetics and Metabolism, Institutes of Biomedical Sciences, Shanghai Medical College, Fudan University, Shanghai, China.
Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.
Front Immunol. 2024 Aug 5;15:1421604. doi: 10.3389/fimmu.2024.1421604. eCollection 2024.
The introduction of Immune Checkpoint Inhibitors (ICIs) has marked a paradigm shift in treating Lung Squamous Cell Carcinoma (LUSC), emphasizing the urgent need for precise molecular biomarkers to reliably forecast therapeutic efficacy. This study aims to identify potential biomarkers for immunochemotherapy efficacy by focusing on plasma extracellular vesicle (EV)-derived long RNAs (exLRs).
We enrolled 78 advanced LUSC patients undergoing first-line immunochemotherapy. Plasma samples were collected, and exLR sequencing was conducted to establish baseline profiles. A retrospective analysis was performed on 42 patients to identify differentially expressed exLRs. Further validation of the top differentially expressed exLRs was conducted using quantitative reverse transcription PCR (qRT-PCR). Univariate Cox analysis was applied to determine the prognostic significance of these exLRs. Based on these findings, we developed a predictive signature (p-Signature).
In the retrospective analysis of 42 patients, we identified 460 differentially expressed exLRs, with pathways related to leukocyte migration notably enriched among non-responders. Univariate Cox analysis revealed 45 exLRs with prognostic significance. The top 6 protein-coding exLRs were validated using qRT-PCR, identifying CXCL8, SSH3, and SDHAF1 as differentially expressed between responders and non-responders. The p-Signature, comprising these three exLRs, demonstrated high accuracy in distinguishing responders from non-responders, with an Area Under the Curve (AUC) of 0.904 in the retrospective cohort and 0.812 in the prospective cohort.
This study highlighted the potential of plasma exLR profiles in predicting LUSC treatment efficacy. Intriguingly, lower p-Signature scores were associated with increased abundance of activated CD4+ and CD8+ T cells, indicating a more robust immune environment. These findings suggest that the p-Signature could serve as a valuable tool in guiding personalized and effective therapeutic strategies for LUSC.
免疫检查点抑制剂（ICIs）的引入标志着治疗肺鳞状细胞癌（LUSC）的范式转变，强调迫切需要精确的分子生物标志物来可靠地预测治疗效果。本研究旨在通过聚焦于血浆细胞外囊泡（EV）衍生的长 RNA（exLRs）来确定免疫化疗疗效的潜在生物标志物。
我们纳入了 78 例正在接受一线免疫化疗的晚期 LUSC 患者。采集了血浆样本，并进行了 exLR 测序以建立基线图谱。对 42 例患者进行了回顾性分析，以鉴定差异表达的 exLRs。使用定量逆转录 PCR（qRT-PCR）对 top 差异表达 exLRs 进行了进一步验证。应用单变量 Cox 分析确定这些 exLRs 的预后意义。基于这些发现，我们开发了一个预测签名（p-Signature）。
在对 42 例患者的回顾性分析中，我们鉴定了 460 个差异表达的 exLRs，其中非应答者中白细胞迁移相关途径显著富集。单变量 Cox 分析揭示了 45 个具有预后意义的 exLRs。使用 qRT-PCR 验证了 top 6 个蛋白编码 exLRs，发现 CXCL8、SSH3 和 SDHAF1 在应答者和非应答者之间表达差异。包含这三个 exLRs 的 p-Signature 在区分应答者和非应答者方面具有很高的准确性，在回顾性队列中的 AUC 为 0.904，前瞻性队列中为 0.812。
本研究强调了血浆 exLR 图谱在预测 LUSC 治疗效果方面的潜力。有趣的是，较低的 p-Signature 评分与更多活化的 CD4+和 CD8+T 细胞的丰度增加相关，表明更强大的免疫环境。这些发现表明，p-Signature 可作为指导 LUSC 个体化和有效治疗策略的有价值的工具。
