Yidan Sun, Qianqian Ma, Yixun Chen, Dongying Liao, Fanming Kong
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Based on the overall survival time and survival status of LUAD patients, a 10-gene prognostic model composed of ABL1, BAK1, IKBKB, PPP2R3C, CCNB2, CORO1A, FADD, P2RX7, TNFSF14, and ZC3H8 was subsequently identified as prognostic markers from The Cancer Genome Atlas (TCGA)-LUAD to develop a prognostic signature. This study constructed a gene prognosis model based on gene expression profiles and corresponding survival information through survival analysis, as well as 1-year, 3-year, and 5-year ROC curve analysis. Enrichment analysis attempted to reveal the potential mechanism of action and molecular pathway of prognostic genes. The CIBERSORT algorithm calculated the infiltration degree of 22 immune cells in each sample and compared the difference of immune cell infiltration between high-risk group and low-risk group. At the cellular level, PCR and CKK8 experiments were used to verify the differences in the expression of the constructed 10-gene model and its effects on cell viability, respectively. The experimental results supported the significant biological significance and potential application value of the molecular model in the prognosis of lung cancer. Enrichment analyses showed that these genes were mainly related to lymphocyte homeostasis.</p>\n </section>\n \n <section>\n \n <h3> Conclusion</h3>\n \n <p>We identified a novel immune cell homeostasis prognostic signature. Targeting these immune cell homeostasis prognostic genes may be an alternative for LUAD treatment. 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Maintaining the homeostasis of immune cells is an important way for anti-tumor immunotherapy. However, the biological significance of maintaining immune homeostasis and immune therapeutic effect has not been well studied.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Methods</h3>\\n \\n <p>We constructed a diagnostic and prognostic model for LUAD based on B and T cells homeostasis-related genes. Minimum absolute contraction and selection operator (LASSO) analysis and multivariate Cox regression are used to identify the prognostic gene signatures. Based on the overall survival time and survival status of LUAD patients, a 10-gene prognostic model composed of ABL1, BAK1, IKBKB, PPP2R3C, CCNB2, CORO1A, FADD, P2RX7, TNFSF14, and ZC3H8 was subsequently identified as prognostic markers from The Cancer Genome Atlas (TCGA)-LUAD to develop a prognostic signature. 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引用次数: 0
摘要
背景 肺腺癌(LUAD)是呼吸系统中侵袭性最强的恶性肿瘤之一。它也是导致肺腺癌患者死亡的常见病理类型。维持免疫细胞的平衡是抗肿瘤免疫疗法的重要途径。然而,维持免疫平衡的生物学意义和免疫治疗效果尚未得到很好的研究。 方法 我们根据 B 细胞和 T 细胞平衡相关基因构建了一个 LUAD 诊断和预后模型。采用最小绝对收缩和选择算子(LASSO)分析和多变量 Cox 回归确定预后基因特征。根据LUAD患者的总生存时间和生存状态,随后从The Cancer Genome Atlas (TCGA)-LUAD中确定了由ABL1、BAK1、IKBKB、PPP2R3C、CCNB2、CORO1A、FADD、P2RX7、TNFSF14和ZC3H8组成的10个基因预后模型作为预后标志物,从而建立了预后特征。本研究根据基因表达谱构建了基因预后模型,并通过生存分析以及1年、3年和5年ROC曲线分析获得了相应的生存信息。富集分析试图揭示预后基因的潜在作用机制和分子途径。CIBERSORT 算法计算了每个样本中 22 个免疫细胞的浸润程度,并比较了高危组和低危组免疫细胞浸润的差异。在细胞层面,利用 PCR 和 CKK8 实验分别验证了所构建的 10 基因模型的表达差异及其对细胞活力的影响。实验结果支持了该分子模型在肺癌预后中的重要生物学意义和潜在应用价值。富集分析表明,这些基因主要与淋巴细胞稳态有关。 结论 我们发现了一种新的免疫细胞稳态预后特征。以这些免疫细胞平衡预后基因为靶点可能是治疗肺癌的一种选择。预测模型的可靠性在生物信息学水平、细胞水平和基因水平上都得到了证实。
Identification and analysis of prognostic immune cell homeostasis characteristics in lung adenocarcinoma
Background
Lung adenocarcinoma (LUAD) is one of the most invasive malignant tumor of the respiratory system. It is also the common pathological type leading to the death of LUAD. Maintaining the homeostasis of immune cells is an important way for anti-tumor immunotherapy. However, the biological significance of maintaining immune homeostasis and immune therapeutic effect has not been well studied.
Methods
We constructed a diagnostic and prognostic model for LUAD based on B and T cells homeostasis-related genes. Minimum absolute contraction and selection operator (LASSO) analysis and multivariate Cox regression are used to identify the prognostic gene signatures. Based on the overall survival time and survival status of LUAD patients, a 10-gene prognostic model composed of ABL1, BAK1, IKBKB, PPP2R3C, CCNB2, CORO1A, FADD, P2RX7, TNFSF14, and ZC3H8 was subsequently identified as prognostic markers from The Cancer Genome Atlas (TCGA)-LUAD to develop a prognostic signature. This study constructed a gene prognosis model based on gene expression profiles and corresponding survival information through survival analysis, as well as 1-year, 3-year, and 5-year ROC curve analysis. Enrichment analysis attempted to reveal the potential mechanism of action and molecular pathway of prognostic genes. The CIBERSORT algorithm calculated the infiltration degree of 22 immune cells in each sample and compared the difference of immune cell infiltration between high-risk group and low-risk group. At the cellular level, PCR and CKK8 experiments were used to verify the differences in the expression of the constructed 10-gene model and its effects on cell viability, respectively. The experimental results supported the significant biological significance and potential application value of the molecular model in the prognosis of lung cancer. Enrichment analyses showed that these genes were mainly related to lymphocyte homeostasis.
Conclusion
We identified a novel immune cell homeostasis prognostic signature. Targeting these immune cell homeostasis prognostic genes may be an alternative for LUAD treatment. The reliability of the prediction model was confirmed at bioinformatics level, cellular level, and gene level.
期刊介绍:
Overview
Effective with the 2016 volume, this journal will be published in an online-only format.
Aims and Scope
The Clinical Respiratory Journal (CRJ) provides a forum for clinical research in all areas of respiratory medicine from clinical lung disease to basic research relevant to the clinic.
We publish original research, review articles, case studies, editorials and book reviews in all areas of clinical lung disease including:
Asthma
Allergy
COPD
Non-invasive ventilation
Sleep related breathing disorders
Interstitial lung diseases
Lung cancer
Clinical genetics
Rhinitis
Airway and lung infection
Epidemiology
Pediatrics
CRJ provides a fast-track service for selected Phase II and Phase III trial studies.
Keywords
Clinical Respiratory Journal, respiratory, pulmonary, medicine, clinical, lung disease,
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