State Key Laboratory of Bioactive Substances and Function of Natural Medicine, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Clinical Laboratory, The Affiliated Hospital of Qingdao University, Qingdao, China.
Front Immunol. 2023 Oct 19;14:1279789. doi: 10.3389/fimmu.2023.1279789. eCollection 2023.
Coagulation is critically involved in the tumor microenvironment, cancer progression, and prognosis assessment. Nevertheless, the roles of coagulation-related long noncoding RNAs (CRLs) in colorectal cancer (CRC) remain unclear. In this study, an integrated computational framework was constructed to develop a novel coagulation-related lncRNA signature (CRLncSig) to stratify the prognosis of CRC patients, predict response to immunotherapy and chemotherapy in CRC, and explore the potential molecular mechanism.
CRC samples from The Cancer Genome Atlas (TCGA) were used as the training set, while the substantial bulk or single-cell RNA transcriptomics from Gene Expression Omnibus (GEO) datasets and real-time quantitative PCR (RT-qPCR) data from CRC cell lines and paired frozen tissues were used for validation. We performed unsupervised consensus clustering of CRLs to classify patients into distinct molecular subtypes. We then used stepwise regression to establish the CRLncSig risk model, which stratified patients into high- and low-risk groups. Subsequently, diversified bioinformatics algorithms were used to explore prognosis, biological pathway alteration, immune microenvironment, immunotherapy response, and drug sensitivity across patient subgroups. In addition, weighted gene coexpression network analysis was used to construct an lncRNA-miRNA-mRNA competitive endogenous network. Expression levels of CRLncSig, immune checkpoints, and immunosuppressors were determined using RT-qPCR.
We identified two coagulation subclusters and constructed a risk score model using CRLncSig in CRC, where the patients in cluster 2 and the low-risk group had a better prognosis. The cluster and CRLncSig were confirmed as the independent risk factors, and a CRLncSig-based nomogram exhibited a robust prognostic performance. Notably, the cluster and CRLncSig were identified as the indicators of immune cell infiltration, immunoreactivity phenotype, and immunotherapy efficiency. In addition, we identified a new endogenous network of competing CRLs with microRNA/mRNA, which will provide a foundation for future mechanistic studies of CRLs in the malignant progression of CRC. Moreover, CRLncSig strongly correlated with drug susceptibility.
We developed a reliable CRLncSig to predict the prognosis, immune landscape, immunotherapy response, and drug sensitivity in patients with CRC, which might facilitate optimizing risk stratification, guiding the applications of immunotherapy, and individualized treatments for CRC.
凝血在肿瘤微环境、癌症进展和预后评估中起着至关重要的作用。然而，凝血相关长非编码 RNA（CRLncRNA）在结直肠癌（CRC）中的作用仍不清楚。在本研究中，构建了一个集成的计算框架，以开发一种新的凝血相关 lncRNA 特征（CRLncSig），对 CRC 患者的预后进行分层，预测 CRC 患者对免疫治疗和化疗的反应，并探讨潜在的分子机制。
使用来自癌症基因组图谱（TCGA）的 CRC 样本作为训练集，同时使用来自基因表达综合数据库（GEO）数据集的大量或单细胞 RNA 转录组学以及来自 CRC 细胞系和配对冷冻组织的实时定量 PCR（RT-qPCR）数据进行验证。我们对 CRL 进行无监督共识聚类，将患者分为不同的分子亚型。然后，我们使用逐步回归建立 CRLncSig 风险模型，将患者分为高风险和低风险组。随后，使用多种生物信息学算法在患者亚组中探索预后、生物途径改变、免疫微环境、免疫治疗反应和药物敏感性。此外，使用加权基因共表达网络分析构建 lncRNA-miRNA-mRNA 竞争内源性网络。使用 RT-qPCR 测定 CRLncSig、免疫检查点和免疫抑制剂的表达水平。
我们鉴定了两个凝血亚群，并使用 CRC 中的 CRLncSig 构建了风险评分模型，其中亚群 2 和低风险组的患者预后更好。亚群和 CRLncSig 被确认为独立的危险因素，基于 CRLncSig 的列线图表现出强大的预后性能。值得注意的是，亚群和 CRLncSig 被鉴定为免疫细胞浸润、免疫反应表型和免疫治疗效率的指标。此外，我们鉴定了一个新的具有 microRNA/mRNA 的竞争 CRL 内源性网络，这将为未来 CRC 恶性进展中 CRL 的机制研究提供基础。此外，CRLncSig 与药物敏感性强烈相关。
我们开发了一种可靠的 CRLncSig，用于预测 CRC 患者的预后、免疫景观、免疫治疗反应和药物敏感性，这可能有助于优化风险分层、指导免疫治疗的应用和 CRC 的个体化治疗。
