肺腺癌预后相关的炎症反应关键基因筛选及其预后预测模型建立

目的 筛选基于肺腺癌（LUAD）预后相关的炎症反应关键基因，并基于该基因构建预后预测模型。方法 在TCGA数据库中下载肺腺癌组织数据作为训练集，在GTEx数据库中下载正常肺组织数据作为训练集的正常对照，筛选差异表达基因（DEG）；在分子特征数据库中下载炎症反应相关基因列表，采用单变量COX回归分析其中与预后相关的炎症反应相关基因，与DEG取交集得到与LUAD预后相关的炎症反应相关基因，应用LASSO回归和随机生存森林（RSF）算法筛选与LUAD预后相关的炎症反应关键基因，并建立预后风险评分公式。使用训练集进行内部验证，从GEO数据库中下载LUAD数据作为验证集进行外部验证，绘制该预后风险评分预测患者1年、3年和5年生存率的受试者工作特征（ROC）曲线，根据cut-off值分为高、低风险组，比较其总生存期（OS）。单因素及多因素COX回归分析风险评分与训练集和验证集OS的关系，整合所有独立的预后相关因素，构建预测训练集患者1年、3年和5年生存率的列线图。结果 LUAD组织和正常肺组织的DEG共48个，与预后相关的炎症反应相关基因共50个，取交集后获得与LUAD预后相关的炎症反应相关基因共...     

肝细胞癌免疫相关基因与预后:基于TCGA生物信息学分析

目的探讨肝细胞癌(hepatocellular carcinoma,HCC)中免疫相关基因组表达与肿瘤预后的关系,寻找潜在的免疫治疗靶点。方法利用TCGA数据库中HCC转录组测序信息,借助生物信息学方法,寻找在癌组织中异常表达的免疫相关基因,同时筛选与患者总生存期密切相关的免疫基因,Cox回归构建可作为预后评估的风险评分模型并评价其预测能力。此外,利用Cytoscape软件绘制转录调控网络探讨潜在的作用机制。结果在HCC癌与癌旁组织中共发现2 068个基因存在差异表达,其中免疫相关基因有116个,单因素Cox分析显示22个免疫基因与预后相关,多变量Cox分析筛选出其中10个(FABP6、MAPT、BIRC5、CSPG5、FIGNL2、GAL、IL11、IL17D、SPP1、STC2)免疫相关基因作为预后的独立危险因子用于构建风险评分模型。患者风险评分与其临床分期密切相关(P0.001),而与患者年龄、性别、肿瘤细胞分化程度无相关性(P0.05)。此外,通过Pearson相关分析发现,患者风险评分能够在一定程度上反映淋巴细胞、树突状细胞、巨噬细胞、中性粒细胞在肿瘤微环境中的浸润程度。结论 HCC中多个免疫相关基因存在异常表达,且与患者预后密切相关,基于其构建的风险评分模型可有效预测患者预后,为HCC的免疫治疗提供新的潜在治疗靶点。     

皮层肌动蛋白表达水平与NSCLC患者MVD及术后预后的关系

目的 探讨皮层肌动蛋白(cortactin)表达水平与非小细胞肺癌(NSCLC)患者肿瘤微血管密度(MVD)及术后预后的关系。方法 选取行手术治疗的140例NSCLC患者，于术中获取癌组织及癌旁正常组织，采用免疫组化法检测cortactin表达情况，用CD34标记微血管计算MVD。比较癌组织及癌旁正常组织中表达水平，癌组织cortactin水平与MVD的相关性采用Pearson相关性分析，采用受试者工作特征(ROC)曲线分析cortactin对预后的预测效能。分析cortactin表达与临床病理特征的关系，采用COX比例风险模型分析NSCLC术后预后的影响因素。结果 癌组织cortactin表达量(1.09±0.27)明显高于癌旁组织(0.65±0.12;P<0.05)。癌组织中MVD计数为(38.09±7.27)个，Pearson相关性分析显示MVD与cortactin呈正相关(r=0.594,P<0.05)。随访3年，140例NSCLC患者中死亡58例(41.43%),存活82例(58.57%)。单因素、多因素Logistic回归分析显示，临床分级、淋巴结转移、MVD、...     

肺癌组织中细胞角蛋白18的表达及与预后的相关性

目的 分析肺癌组织细胞角蛋白18(cytokeratin 18, CK18)的表达及与预后的相关性。方法 选取2019年1月至2020年12月我院收治的97例肺癌患者为对象,采用免疫组织化学染色法检测癌组织及配对癌旁组织中CK18表达;采用RT-PCR检测CK18 mRNA相对表达量。Kaplan-Meier曲线和COX比例风险回归分析肺癌预后情况。结果 癌组织CK18高表达51例(52.58%),高于癌旁组织15例(15.46%)(P<0.05)。癌组织CK18 mRNA相对表达量为(2.12±0.71),高于癌旁组织(0.67±0.21)(P<0.05)。COX多因素分析显示,TNM分期、远处转移、淋巴结转移、CK18高表达是肺癌低OS和低PFS的影响因素,化疗是保护因素(P<0.05)。97例中接受化疗41例、未接受化疗56例,CK18高表达者的总体生存期(OS)和无进展生存期(PFS)低于CK18低表达者(P<0.05)。结论 肺癌组织CK18表达水平升高,癌组织CK18高表达与肺癌患者不良生存预后有关,CK18可能成为肺癌的生物标志物。     

三阴性乳腺癌免疫相关LncRNA筛选及预后预测模型构建

目的 筛选出三阴性乳腺癌（TNBC）免疫相关LncRNA基因，构建TNBC预后预测模型。方法 (1)从癌症基因组图谱（TCGA）项目下载TNBC组织和癌旁组织的转录组RNA表达谱原始数据，结合Immport数据库，筛选TNBC免疫相关的LncRNA。进一步应用单因素及多因素Cox分析筛选TNBC与预后关系密切的免疫相关LncRNA，然后再根据最佳AIC值确定与预后关系密切的免疫相关LncRNA。(2)根据预后关系密切的免疫相关LncRNA，构建TNBC预后预测模型。(3)根据TNBC预后风险模型测算的风险评分值的中位值将TNBC患者样本分为高风险组和低风险组，比较高低风险组生存率。(4)采用ROC、主成分分析（PCA）评估构建的TNBC预后预测模型的预测效能。(5)采用多因素Cox分析TNBC预后预测模型预测效能的独立性。结果 共计65例份TNBC组织样本，得到369个免疫相关LncRNA，通过单因素和多因素Cox分析，共得到3个与预后关系密切的免疫相关LncRNA(AC090181.2、LINC01235、LINC01943)，并构建TNBC预后预测模型，该模型表达公式如下：风险评分...     

肺癌患者癌旁组织中上皮-间质转变相关蛋白表达对其预后的影响

目的探讨肺癌患者癌旁组织中上皮-间质转变(EMT)相关蛋白表达对其预后的影响。方法采用免疫组化法检测81例肺癌患者癌组织和配对癌旁组织中的EMT相关蛋白(E-cadherin、β-catenin和Vimentin),观察E-cadherin、β-catenin和Vimentin在癌组织和癌旁组织中表达差异,并比较癌旁组织中E-cadherin、β-catenin和Vimentin表达差异下患者的预后情况,以患者的病理资料和EMT相关蛋白表达差异纳入Cox回归模型,预后因子采用多因素分析。结果 (1)肺癌组织中E-cadherin和β-catenin阳性表达率(49.38%和14.81%)明显低于癌旁组织(72.84%和51.85%),而Vimentin阳性表达率(55.56%)明显高于癌旁组织(23.46%)(均P<0.05)。(2)癌旁组织中E-cadherin阳性、β-catenin阳性和Vimentin阴性患者预后较E-cadherin阴性、β-catenin阴性和Vimentin阳性患者预后好(P<0.05)。(3)Cox回归分析发现临床分期、肿瘤分期、EMT-L和肿瘤分化程度是独立的风险预后因子。结论 EMT相关蛋白在癌旁组织中的表达异常对肺癌患者的预后有一定的影响,在癌症早期阶段及癌旁组织未发生明显组织形态学异常时,EMT相关蛋白的检测对患者的预后情况分析具有一定的参考价值。     

胃腺癌中免疫基因组表达及临床意义

目的探讨胃腺癌(gastric adenocarcinoma,GAC)中免疫相关基因的表达情况,寻找潜在的免疫治疗靶点。方法基于TCGA数据库中GAC全基因组测序,利用生物信息学方法,分析在肿瘤中异常表达的免疫相关基因,进一步筛选影响患者预后的免疫基因,Kaplan-Meier网站进行验证。通过Cytoscape软件预测可能的转录调控机制,Cox回归构建预测患者预后的风险模型并评价临床实用性。结果 6 685个基因在GAC癌组织与癌旁组织中有差异表达,其中366个为免疫相关基因,而与预后密切相关的免疫基因有33个。多因素Cox回归分析筛选出12个(TAP1、CXCL6、CTSG、CCL21、RNASE2、IGHD2-15、EDN2、PLAUR、GCG、RETN、RLN2、GLP2R)免疫基因构建风险模型。Kaplan-Meier网站验证TAP1、CTSG、RETN、GLP2R明显与患者预后相关。临床相关性上,该模型能反映肿瘤淋巴结转移情况,而与患者年龄、性别、肿瘤分期无相关性(P0.05)。通过Pearson相关分析,我们还发现该模型能够一定程度上反映树突状细胞、巨噬细胞、中性粒细胞在肿瘤微环境中的浸润情况。结论我们筛选出了与GAC患者预后密切相关的多个差异性表达的免疫基因,并在此基础上建立了一个能有效预测预后的风险评分模型,为将来的免疫治疗提供了新思路和潜在治疗靶点。     

基于生物信息学筛选胃癌失巢凋亡相关基因并构建预后模型

目的 采用生物信息学方法探讨失巢凋亡相关基因(Anoikis-related genes, ANRGs)在胃癌中的预后价值,并建立了基于ANRGs的预后风险评分模型。方法 从GeneCards数据库和Harmonizome数据库获得515个ANRGs。首先从TCGA数据库获得胃癌患者的基因表达数据和临床资料,并利用R4.2.2软件提取出差异表达的ANRGs,其次采用单因素COX回归筛选出与总生存期(OS)有关的ANRGs,再次采用LASSO回归和多因素COX回归构建ANRGs的预后风险评分模型。根据风险评分,将胃癌患者区分为高风险组和低风险组。最后计算ROC曲线下面积(AUC)和绘制Kaplan-Meier(K-M)生存曲线评估模型的预测性能,并使用GSE84437数据集进行验证。进一步评估风险评分与肿瘤免疫微环境之间的关系。将风险评分与临床病理特征相结合,建立基于ANRGs的列线图来预测总生存期。结果 筛选178个差异表达的ANRGs, 51个基因与预后相关,并从中选择10个基因来构建预后风险评分模型。该模型中,高风险组的总生存期显著低于低风险组(P<0.001),训练集(AU...     

CD105在肺癌组织中的表达及其与预后的关系

应用免疫组织化学SP法检测CD105在70份肺癌癌组织及40份癌旁组织标本中的表达,结果CD105在癌组织中的阳性表达率明显高于癌旁组织,其表达与肺癌临床分期有关;CD105不同表达的化疗患者中位生存时间明显长于非化疗者,以化疗CD105阴性者最长;COX回归分析显示,CD105与肺癌患者的预后有关.认为CD105与肺癌的发生、发展密切相关,可作为评价肺癌预后的指标.     

A promising prognostic signature for lung adenocarcinoma (LUAD) patients basing on 6 hypoxia-related genes

Background:Hypoxia signaling plays a critical role in the development of lung adenocarcinoma (LUAD). We herein aimed to explore the prognostic value of hypoxia-related genes and construct the hypoxia-related prognostic signature for LUAD patients.Methods:A total of 26 hypoxia-related genes were collected. Five hundred thirteen and 246 LUAD samples were obtained from the Cancer Genome Atlas and Gene Expression Omnibus databases, respectively. Univariate Cox regression and LASSO Cox regression analyses were conducted to screen the hypoxia-related genes associated with the prognosis of LUAD patients, which would be used for constructing prognosis predictive model for LUAD patients. Multivariate Cox regression analysis was done to determine the independent prognostic factors. The Nomogram model was constructed to predict the prognosis of LUAD patients.Results:Based on 26 hypoxia-related genes, LUAD samples could be divided into 4 clusters with different prognoses. Among which, 6 genes were included to construct the Risk Score and the LUAD patients with higher Risk Score had worse prognosis. Besides, the Nomogram based on all the independent risk factors could relatively reliably predict the survival probability. And 9 types of immune cells’ infiltration was significantly differential between high and low risk LUAD patients.Conclusion:The Risk Score model based on the 6 crucial hypoxia-related genes could relatively reliably predict the prognosis of LUAD patients.     

EGLN3在肺腺癌中表达的Meta分析

目的 分析EGLN3在肺腺癌(lung adenocarcinoma, LUAD)中的作用。方法 (1)通过癌症基因组图谱(the cancer genome atlas, TCGA)数据库下载535例肺腺癌样本和59例正常样本,分析EGLN3在肺腺癌和正常肺组织中的表达差异;(2)使用R语言分析EGLN3的表达水平及其在肺腺癌中的临床意义;(3)通过Kaplan-Meier方法、单因素和多因素COX回归分析和生存预测列线图确定EGLN3的表达水平与肺腺癌预后的关系;(4)通过基因集富集分析(GSEA)筛选EGLN3相关的生物学途径;(5)细胞实验：通过蛋白质印迹法(WB)验证EGLN3在肺腺癌细胞中是否存在差异表达;对EGLN3基因进行过表达和干扰表达,采用CCK-8增殖实验、划痕实验和Transwell侵袭实验,明确表达水平对肺腺癌细胞增殖、迁移和侵袭的影响。结果 (1)EGLN3在肺腺癌组织中表达水平高于正常肺组织细胞;(2)EGLN3表达水平与肺腺癌病理分期相关,病理分期越高,对应EGLN3表达水平越高;(3)EGLN3表达水平与肺腺癌总生存期(OS)独立预后相关,EGLN3高...     

Screening and evaluation of the role of immune genes of brain metastasis in lung adenocarcinoma progression based on the TCGA and GEO databases

BackgroundBrain metastasis was one of the factors leading to the poor long-term prognosis of patients with lung adenocarcinoma (LUAD).MethodsThe expression levels of immune genes in LUAD and LUAD brain metastases tissues were analyzed in {"type":"entrez-geo","attrs":{"text":"GSE161116","term_id":"161116"}}GSE161116 dataset using the GEO2R, and the levels of differential immune genes in normal lung and LUAD tissues were verified. The biological functions and signaling mechanisms of the differential immune genes were explored via Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis. Cox regression analysis was used to screen the prognostic factors of LUAD patients, and a risk model was constructed. The role of the model was checked in the development of LUAD via receiver operating characteristic analysis, gene set enrichment analysis, and Cox regression analysis.ResultsDifferentially expressed genes (DEGs) in brain metastasis were involved in the adaptive immune response, B cell differentiation, leukocyte migration, NF-kB signaling pathway, among others. The expression levels of TNFRSF11A, MS4A2, IL11, CAMP, MS4A1, and F2RL1 were independent factors affecting the poor prognosis of LUAD patients via Cox regression analysis and Akaike information criterion. In the constructed risk model, the overall survival of LUAD patients in the high-risk group was poor. The risk model was significantly related to the gender, clinical stage, T stage, lymph node metastasis, and survival status of LUAD patients. In addition, the risk model score was an independent risk factor that affected the poor prognosis of LUAD patients. TNFRSF11A, CAMP, F2RL1, IL11, MS4A1, and MS4A2 of the risk factors had diagnostic significance in LUAD brain metastasis and LUAD. The risk model participated in cytokinetic process, cell cycle, citrate cycle TCA cycle, etc. The risk model score was correlated with the levels of B cells memory, mast cells resting, macrophages M0, mast cells activated, neutrophils, eosinophils, T cells gamma delta, and immune cell markers.ConclusionsThe risk model based on the LUAD brain metastasis immune factors TNFRSF11A, MS4A2, IL11, CAMP, MS4A1, and F2RL1 was related to the diagnosis, poor prognosis, and immune infiltrating cells of LUAD patients, and is expected to provide a reference for the development of treatment strategies for LUAD patients.     

手术切除肺腺癌患者免疫细胞浸润分析及预后关系

目的探究肺腺癌手术患者免疫细胞浸润模式及预后关系。方法基于GSE68465数据集,利用CIBERSORT软件包,对442例样本中22种免疫细胞进行定量分析,利用Survival包,Kaplan-Meier法分析22种免疫细胞含量与总生存率关系,利用Cox多变量回归分析构建肺腺癌手术患者免疫细胞预后风险模型,根据风险评分中位数,分为高风险组和低风险组,绘制Kaplan-Meier生存曲线和ROC曲线,评估模型的预测效果。结果肺腺癌组织浸润的免疫细胞主要有浆细胞、M2巨噬细胞和M0巨噬细胞,肺腺癌组织与正常组织免疫浸润存在显著差异。静息NK细胞与预后关系显著(P<0.05)。基于5种免疫细胞构建预后风险模型(Risk Score=8.156×静息NK细胞+9.059×活化CD4+记忆T细胞+3.899×活化肥大细胞+2.452×M0巨噬细胞+5.575×活化树突状细胞),高风险组较低风险组预后显著较差(P<0.0001),ROC曲线提示该风险模型具有较好的预后预测效果。结论免疫细胞浸润风险评分模型可以有效预测肺腺癌手术患者预后。     

Model establishment of prognostic-related immune genes in laryngeal squamous cell carcinoma

Background:Laryngeal squamous cell carcinoma (LSCC) is one of the most common malignant tumors of the head and neck in the world. At present, the treatment methods include surgery, radiotherapy, and chemotherapy, but the 5-year survival rate is still not ideal and the quality of life of the patients is low. Due to the relative lack of immunotherapy methods, this study aims to build a risk prediction model of related immune genes, which can be used to effectively predict the prognosis of laryngeal cancer patients, and provide targets for subsequent immunotherapy.Methods:We collected the 111 cases of laryngeal squamous cell carcinoma and 12 matched normal samples in the The Cancer Genome Atlas Database (TCGA) gene expression quantification database. The differentially expressed related immune genes were screened by R software version 3.5.2. The COX regression model of immune related genes was constructed, and the sensitivity and specificity of the model were evaluated. The risk value was calculated according to the model, and the risk curve was drawn to verify the correlation between related immune genes, risk score, and clinical traits.Results:We selected 8 immune-related genes that can predict the prognosis of LSCC in a COX regression model and plotted the Kaplan–Meier survival curve. The 5-year survival rate of the high-risk group was 16.5% (95% CI: 0.059–0.459), and that of the low-risk group was 72.9% (95% CI: 0.555–0.956). The area under the receiver operating characteristic (ROC) curve was used to confirm the accuracy of the model (AUG = 0.887). After univariate and multivariate regression analysis, the risk score can be used as an independent risk factor for predicting prognosis. The risk score (P = .021) was positively correlated with the clinical Stage classification.Conclusion:We screened out 8 immune genes related to prognosis: RBP1, TLR2, AQP9, BTC, EPO, STC2, ZAP70, and PLCG1 to construct risk value models, which can be used to speculate the prognosis of the disease and provide new targets for future immunotherapy.     

人肺腺癌组织S100 A6蛋白表达及其临床意义

目的：探讨S100A6蛋白表达对肺腺癌患者的临床特征及其转移预后的影响。方法收集手术切除、经病理证实的肺腺癌及配对癌旁正常肺组织标本各98例,通过 Western blot 检测S100A6蛋白表达。结果肺腺癌组织 S100A6蛋白表达量显著高于癌旁正常肺组织(t=19.884,P<0.05);S100A6蛋白表达与肺腺癌患者性别、年龄无相关性(P 值均>0.05),与患者吸烟指数、肿瘤细胞分化、淋巴结转移、远处转移、临床分期均有显著相关(P 值均<0.05);Kaplan-Meier 法比较低表达组和高表达组患者的生存期,差异有统计学意义(P <0.05);COX比例风险多因素回归分析发现,肿瘤分化、TNM分期和 S100A6蛋白表达是影响肺腺癌患者预后的独立因素。结论 S100A6在肺腺癌组织显著高表达,可以作为与肿瘤发生、发展密切相关的一种标志蛋白。     

Exploration of genes and tumor infiltrating lymphocytes in female lung adenocarcinoma microenvironment that predicted prognosis

The tumor microenvironment has an important impact on tumor growth, invasion, metastasis, anti-tumor immune tolerance, and prognosis. The present study aimed to explore female lung adenocarcinoma microenvironment-associated tumor infiltrating lymphocytes (TILs) and genes that predict prognosis in The Cancer Genome Atlas (TCGA) database. Gene expression profiles of female patients with lung adenocarcinoma were downloaded from TCGA. Base on the CIBERSORT algorithm, we determined the fractions of TILs. By applying the ESTIMATE algorithm, immune scores and stromal scores were derived. According to the immune and stromal scores, we categorized the female patients with lung adenocarcinoma into high and low score groups. We also identified the fractions of TILs and differentially expressed genes (DEGs) that were significantly related with prognosis. The proportion of M1 macrophages was significantly negatively related to overall survival in female patients with lung adenocarcinoma. There were 269 upregulated genes and 35 downregulated genes both in immune scores and stromal scores. PTPRC (protein tyrosine phosphatase receptor type C) and GIMAP6 (GTPase, IMAP family member 6) were not only hub genes, but also were significantly related to overall survival in the Kaplan–Meier Plotter online and TCGA databases. In summary, our study provided new insight into the tumor microenvironment-related cellular and molecular mechanisms of women with lung adenocarcinoma. The results will be useful for future clinical studies.     

Identification and validation of an autophagy-related long non-coding RNA signature as a prognostic biomarker for patients with lung adenocarcinoma

BackgroundLung adenocarcinoma (LUAD) is the most predominant pathological subtype of lung cancer, accounting for 40–70% of all lung cancer cases. Although significant improvements have been made in the screening, diagnosis, and precise management in recent years, the prognosis of LUAD remains bleak. This study aimed to investigate the prognostic significance of autophagy-related long non-coding RNAs (lncRNAs) and construct an autophagy-related lncRNA prognostic model in LUAD.MethodsThe gene expression data of LUAD patients were obtained from The Cancer Genome Atlas (TCGA) database. All autophagy-related genes were downloaded from the Human Autophagy Database (HADb). Spearman’s correlation test was exploited to identify potential autophagy-related lncRNAs. The multivariate Cox regression analysis was used to construct the prognostic signature, which divided LUAD patients into high-risk and low-risk groups. Subsequently, the receiver operating characteristic (ROC) curves were generated to assess the predictive ability of this prognostic model for overall survival (OS) in these individuals. Then, the Gene set enrichment analysis (GSEA) was conducted to execute pathway enrichment analysis. Finally, a multidimensional validation was exploited to verify our findings.ResultsA total of 1,144 autophagy-related lncRNAs were identified to construct the co-expression network via Spearman’s correlation test (|R²| >0.4 and P≤0.001). Ultimately, a 16 autophagy-related lncRNAs prognostic model was constructed, and the area under the ROC curve (AUC) was 0.775. The results of GSEA enrichment analysis showed that the genes in the high-risk group were mainly enriched in cell cycle and p53 signaling pathways. The results of the multidimensional database validation indicated that the expression level of BIRC5 was significantly correlated with the expression level of TMPO-AS1. Furthermore, both TMPO-AS1 and BIRC5 had a higher expression level in LUAD samples. LUAD patients with high expression levels of TMPO-AS1 and BIRC5 were correlated with advanced disease stage and poor OS.ConclusionsIn summary, our results suggested that the prognostic signature of the 16 autophagy-related lncRNAs has significant prognostic value for LUAD patients. Furthermore, TMPO-AS1 and BIRC5 are potential predictors and therapeutic targets in these individuals.