免疫检查点抑制剂（ICIs）的引入标志着肺鳞状细胞癌（LUSC）治疗模式的转变，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。本研究旨在通过关注血浆细胞外囊泡 (EV) 衍生的长 RNA (exLR) 来确定免疫化疗疗效的潜在生物标志物。我们招募了 78 名接受一线免疫化疗的晚期 LUSC 患者。收集血浆样本，并进行 exLR 测序以建立基线概况。对 42 名患者进行回顾性分析，以确定差异表达的 exLR。使用定量逆转录 PCR (qRT-PCR) 对最高差异表达的 exLR 进行进一步验证。应用单变量 Cox 分析来确定这些 exLR 的预后意义。基于这些发现，我们开发了一个预测特征（p-Signature）。在对 42 名患者的回顾性分析中，我们鉴定了 460 个差异表达的 exLR，其中与白细胞迁移相关的通路在无应答者中显着丰富。单变量 Cox 分析揭示了 45 个具有预后意义的 exLR。使用 qRT-PCR 对排名前 6 的蛋白质编码 exLR 进行了验证，确定了 CXCL8、SSH3 和 SDHAF1 在应答者和非应答者之间的差异表达。由这三个 exLR 组成的 p 签名在区分应答者与无应答者方面表现出很高的准确性，回顾性队列中的曲线下面积 (AUC) 为 0.904，前瞻性队列中为 0.812。这项研究强调了血浆的潜力exLR 概况预测 LUSC 治疗效果。有趣的是，较低的 p-Signature 评分与激活的 CD4 和 CD8 T 细胞丰度增加相关，表明免疫环境更加稳健。这些研究结果表明，p-Signature 可以作为指导 LUSC 个性化和有效治疗策略的宝贵工具。版权所有 © 2024 张、廖、杨、李、王、于、吴、王、孙、赵、胡和王。

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.Copyright © 2024 Zhang, Liao, Yang, Li, Wang, Yu, Wu, Wang, Sun, Zhao, Hu and Wang.