Qiangqiang Ge, Zhong Lin, Xuequan Wang, Zhengli Jiang, Yan Hu
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We utilized expression data of LncRNAs and clinical information from 471 LUSC patients in The Cancer Genome Atlas (TCGA), randomly dividing them into a training set (n=236) and a testing set (n=235).</p><p><strong>Results: </strong>A prognostic signature model comprising seven LncRNAs was constructed using multivariate Cox regression analysis based on the training set. Using a risk score cutoff value of -0.12 (log2-transformed), patients were categorized into high-risk (n=101) and low-risk (n=370) groups. The high-risk group demonstrated significantly worse overall survival (OS) compared to the low-risk group (p<0.0001). The risk score showed strong prognostic predictive ability for LUSC patients, as evidenced by the area under the ROC curve (AUC: 0.66, 0.67, and 0.67) and nomogram analysis (C-index, calibration, and decision curve analysis) for 1-, 3-, and 5-year survival predictions. Independent prognostic factors for LUSC were identified, including risk group (HR=0.3, 95% CI: 0.22-0.4), stage (HR=1.78, 95% CI: 1.28-2.48), and age (HR=1.02, 95% CI: 1.00-1.04). KEGG enrichment analysis revealed that mRNAs influenced by the seven targeted LncRNAs, associated with immune evasion, were primarily linked to pathways such as chemical carcinogenesis, Th17 cell differentiation, NF-κB signaling, and proteoglycans in cancer. Expression levels of 14 target genes related to tumor immune tolerance were significantly suppressed, with eight confirmed via real-time PCR and western blot analysis. Additionally, CIBERSORT analysis of immune cell-related gene expression between normal and LUSC tissues indicated activation of the immune system in LUSC patients.</p><p><strong>Conclusion: </strong>In conclusion, our findings highlight the clinical significance of the seven LncRNA signature in predicting survival outcomes for LUSC patients.</p>","PeriodicalId":12482,"journal":{"name":"Frontiers in Oncology","volume":"15 ","pages":"1511564"},"PeriodicalIF":3.5000,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11973350/pdf/","citationCount":"0","resultStr":"{\"title\":\"A seven-LncRNA signature for prognosis prediction of patients with lung squamous cell carcinoma through tumor immune escape.\",\"authors\":\"Qiangqiang Ge, Zhong Lin, Xuequan Wang, Zhengli Jiang, Yan Hu\",\"doi\":\"10.3389/fonc.2025.1511564\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Lung squamous cell carcinoma (LUSC) is a malignant disease associated with poor therapeutic responses and prognosis. Preliminary studies have shown that the dysregulation of long non-coding RNAs (LncRNAs) is linked to cancer development and prognosis. However, research on the role of LncRNAs in LUSC remains limited.</p><p><strong>Methods: </strong>In this study, we aimed to develop a LncRNA signature for improved prognostic prediction in LUSC and to elucidate the underlying mechanisms. We utilized expression data of LncRNAs and clinical information from 471 LUSC patients in The Cancer Genome Atlas (TCGA), randomly dividing them into a training set (n=236) and a testing set (n=235).</p><p><strong>Results: </strong>A prognostic signature model comprising seven LncRNAs was constructed using multivariate Cox regression analysis based on the training set. Using a risk score cutoff value of -0.12 (log2-transformed), patients were categorized into high-risk (n=101) and low-risk (n=370) groups. The high-risk group demonstrated significantly worse overall survival (OS) compared to the low-risk group (p<0.0001). The risk score showed strong prognostic predictive ability for LUSC patients, as evidenced by the area under the ROC curve (AUC: 0.66, 0.67, and 0.67) and nomogram analysis (C-index, calibration, and decision curve analysis) for 1-, 3-, and 5-year survival predictions. Independent prognostic factors for LUSC were identified, including risk group (HR=0.3, 95% CI: 0.22-0.4), stage (HR=1.78, 95% CI: 1.28-2.48), and age (HR=1.02, 95% CI: 1.00-1.04). KEGG enrichment analysis revealed that mRNAs influenced by the seven targeted LncRNAs, associated with immune evasion, were primarily linked to pathways such as chemical carcinogenesis, Th17 cell differentiation, NF-κB signaling, and proteoglycans in cancer. Expression levels of 14 target genes related to tumor immune tolerance were significantly suppressed, with eight confirmed via real-time PCR and western blot analysis. 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引用次数: 0
摘要
背景:肺鳞状细胞癌(LUSC)是一种治疗效果和预后较差的恶性疾病。初步研究表明,长链非编码rna (LncRNAs)的失调与癌症的发展和预后有关。然而,关于lncrna在LUSC中的作用的研究仍然有限。方法:在本研究中,我们旨在开发一种用于改善LUSC预后预测的LncRNA特征,并阐明其潜在机制。我们利用The Cancer Genome Atlas (TCGA)中471例LUSC患者的lncrna表达数据和临床信息,将其随机分为训练集(n=236)和测试集(n=235)。结果:基于训练集,采用多变量Cox回归分析构建了包含7个lncrna的预后特征模型。采用风险评分截断值-0.12 (log2转化),将患者分为高危组(n=101)和低危组(n=370)。结论:总之,我们的研究结果强调了7个LncRNA特征在预测LUSC患者生存结局方面的临床意义。
A seven-LncRNA signature for prognosis prediction of patients with lung squamous cell carcinoma through tumor immune escape.
Background: Lung squamous cell carcinoma (LUSC) is a malignant disease associated with poor therapeutic responses and prognosis. Preliminary studies have shown that the dysregulation of long non-coding RNAs (LncRNAs) is linked to cancer development and prognosis. However, research on the role of LncRNAs in LUSC remains limited.
Methods: In this study, we aimed to develop a LncRNA signature for improved prognostic prediction in LUSC and to elucidate the underlying mechanisms. We utilized expression data of LncRNAs and clinical information from 471 LUSC patients in The Cancer Genome Atlas (TCGA), randomly dividing them into a training set (n=236) and a testing set (n=235).
Results: A prognostic signature model comprising seven LncRNAs was constructed using multivariate Cox regression analysis based on the training set. Using a risk score cutoff value of -0.12 (log2-transformed), patients were categorized into high-risk (n=101) and low-risk (n=370) groups. The high-risk group demonstrated significantly worse overall survival (OS) compared to the low-risk group (p<0.0001). The risk score showed strong prognostic predictive ability for LUSC patients, as evidenced by the area under the ROC curve (AUC: 0.66, 0.67, and 0.67) and nomogram analysis (C-index, calibration, and decision curve analysis) for 1-, 3-, and 5-year survival predictions. Independent prognostic factors for LUSC were identified, including risk group (HR=0.3, 95% CI: 0.22-0.4), stage (HR=1.78, 95% CI: 1.28-2.48), and age (HR=1.02, 95% CI: 1.00-1.04). KEGG enrichment analysis revealed that mRNAs influenced by the seven targeted LncRNAs, associated with immune evasion, were primarily linked to pathways such as chemical carcinogenesis, Th17 cell differentiation, NF-κB signaling, and proteoglycans in cancer. Expression levels of 14 target genes related to tumor immune tolerance were significantly suppressed, with eight confirmed via real-time PCR and western blot analysis. Additionally, CIBERSORT analysis of immune cell-related gene expression between normal and LUSC tissues indicated activation of the immune system in LUSC patients.
Conclusion: In conclusion, our findings highlight the clinical significance of the seven LncRNA signature in predicting survival outcomes for LUSC patients.
期刊介绍:
Cancer Imaging and Diagnosis is dedicated to the publication of results from clinical and research studies applied to cancer diagnosis and treatment. The section aims to publish studies from the entire field of cancer imaging: results from routine use of clinical imaging in both radiology and nuclear medicine, results from clinical trials, experimental molecular imaging in humans and small animals, research on new contrast agents in CT, MRI, ultrasound, publication of new technical applications and processing algorithms to improve the standardization of quantitative imaging and image guided interventions for the diagnosis and treatment of cancer.