Integrated bioinformatics analysis identifies immune-related epithelial-mesenchymal transition prognostic biomarkers and immune infiltrates in patients with lung adenocarcinoma

Background:Lung cancer,particularly lung adenocarcinoma(LUAD),is highly lethal.Understanding the critical interaction between epithelial-mesenchymal transition(EMT)and the immune status of patients is imperative for clinical assessment.Methods:We conducted bioinformatics analysis to identify potential immune-related EMT(iEMT)prognostic genes and explored the immune status in LUAD.Using data from The CancerGenome Atlas andGSE68465,differentially expressed genes,were identified,and a risk modelwas constructed.Cluster analysis was conducted using the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathways.Results:Our findings revealed 69 differentially expressed iEMT genes,with risk values demonstrating independent prognostic significance for both The Cancer Genome Atlas and GSE68465 samples.The risk value was positively correlated with tumor stage.Immune cell infiltration analysis showed a significant decrease in resting dendritic cells and an increase in CD4 memory T cells in high-risk groups with poor survival prognoses.The immunotherapy analysis revealed weak immunotherapeutic effects in the high-risk group.Conclusions:This study provides insights into potential aberrant differential iEMT genes and risk models and explores immune landscapes that inform personalized immunotherapy in patients with LUAD.

Low-depth whole genome sequencing reveals copy number variations associated with higher pathologic grading and more aggressive subtypes of lung non-mucinous adenocarcinoma

Objective:Histology grade,subtypes and TNM stage of lung adenocarcinomas are useful predictors of prognosis and survival.The aim of the study was to investigate the relationship between chromosomal instability,morphological subtypes and the grading system used in lung non-mucinous adenocarcinoma(LNMA).Methods:We developed a whole genome copy number variation(WGCNV)scoring system and applied next generation sequencing to evaluate CNVs present in 91 LNMA tumor samples.Results:Higher histological grades,aggressive subtypes and more advanced TNM staging were associated with an increased WGCNV score,particularly in CNV regions enriched for tumor suppressor genes and oncogenes.In addition,we demonstrate that 24-chromosome CNV profiling can be performed reliably from specific cell types(<100 cells)isolated by sample laser capture microdissection.Conclusions:Our findings suggest that the WGCNV scoring system we developed may have potential value as an adjunct test for predicting the prognosis of patients diagnosed with LNMA.

Polo-like kinase 1 suppresses lung adenocarcinoma immunity throughnecroptosis

Polo-like kinase 1(PLK1)plays a crucial role in cell mitosis and has been associated with necroptosis.However,the role of PLK1 and necroptosis in lung adenocarcinoma(LA)remains unclear.In this study,we analyzed The Cancer Genome Atlas(TCGA)and Genotype-Tissue Expression databases to evaluate the prognostic value and mechanistic role of PLK1 in LA.PLK1 was found to be highly expressed in LA and was positively associated with advanced disease staging and poor survival outcomes.Functional enrichment analysis showed that PLK1 was involved in cell mitosis,neurotransmitter transmission,and drug metabolism.Further analysis using single-sample gene set enrichment analysis and ESTIMATE algorithm revealed a correlation between PLK1 expression and immune infiltration in LA.Silencing of PLK1 using miRNA transfection in LA cells reduced cell proliferation and increased apoptosis,as well as upregulating the expression of necroptosis-related proteins,such as RIPK1,RIPK3,and MLKL.Additionally,nude mouse transplantation tumor experiments demonstrated that silencing PLK1 reduced the growth capacity of LA cells.These findings suggest that PLK1 plays a critical role in LA progression by regulating necroptosis and immune infiltration,and may serve as a potential therapeutic target for immunotherapy.Furthermore,PLK1 expression can be used as a prognostic biomarker for LA patients.

Immunogenic cell death-related long noncoding RNA influences immunotherapy against lung adenocarcinoma

Lung adenocarcinoma(LUAD)is the leading cause of cancer-related deaths,accounting for over a million deaths worldwide annually.Immunogenic cell death(ICD)elicits an adaptive immune response.However,the role of ICD-related long noncoding RNAs(lncRNAs)in LUAD is unknown.In this study,we investigated the characteristics of the tumor microenvironment in LUAD,the prognostic significance of ICD-related lncRNAs,and the half-maximal inhibitory concentration(IC50)of possible chemotherapeutic drugs.We sorted prognostic lncRNAs using univariate Cox regression and constructed a risk signature based on them.We then confirmed the model’s accuracy and generated a nomogram.Additionally,we performed immune microenvironment analysis,somatic mutation calculation,Tumor Immune Dysfunction and Exclusion(TIDE)analysis,and anticancer pharmaceutical IC50 prediction.Least absolute shrinkage and selection operator Cox regression identified 27 prognostic lncRNAs related to ICD,and a unique risk signature using 10 ICD-related lncRNAs was constructed.The risk score was confirmed to be a reliable predictor of survival,with the highest c-index score.The signature had a remarkable predictive performance with clinical applicability and could accurately predict the overall survival in LUAD.Furthermore,the lncRNA signature was closely associated with immunocyte invasion.We also analyzed the correlation between the risk score,tumor-infiltrating immune cells,and prognosis and identified high immune and ESTIMATE scores in low-risk patients.Moreover,we observed elevated checkpoint gene expression and low TIDE scores in high-risk patients,indicating a good immunotherapy response.Finally,high-risk patients were shown to be susceptible to anticancer medications.Therefore,our unique risk signature comprising 10 ICD-related lncRNAs was demonstrated to indicate the characteristics of the tumor-immune microenvironment in LUAD,predict patients’overall survival,and guide individualized treatment.

Expression of PHF19 in lung adenocarcinoma and its effect on immune microenvironment

Objective:To investigate the expression level,clinical prognosis,genetic changes,methylation value,biological function and immunomodulatory effects of PHF19 in lung adenocarcinoma.Methods:Based on the RNA cohort data of lung adenocarcinoma in the Cancer Genome Atlas(TCGA)database,the expression difference of PHF19 between lung adenocarcinoma and normal tissues and the relationship between the expression level and the prognosis of patients were analyzed by using TIMER database and UALCAN database.The gene mutation of PHF19 in lung adenocarcinoma was analyzed in cBioPortal database and TIMER database.The promoter methylation level of PHF19 in lung adenocarcinoma was analyzed in UALCAN database.The enrichment of PHF19 co-expression gene was analyzed in LinkedOmics database and KEGG database.The correlation between the expression of PHF19 in lung adenocarcinoma and the level of immunoinfiltration was explored in the TIMER database.Results:The expression of PHF19 in lung adenocarcinoma tissues was up-regulated,and its high expression was significantly correlated with the pathological stage,lymph node metastasis and shortened overall survival of lung adenocarcinoma patients.Genetic variation was found in 0.9%of patients,amplification and missense mutation were the most common mutations,and TP53 mutation could lead to the high expression of PHF19.The promoter methylation level of PHF19 significantly decreased in lung adenocarcinoma.The function of PHF19 was focused on the process of cell mitosis and cell cycle.The expression level of PHF19 was significantly correlated with tumor immune cell infiltration and immune checkpoint expression.Conclusion:PHF19 can be used as a marker of poor prognosis of lung adenocarcinoma and plays an important role in the occurrence and development of lung adenocarcinoma.

Low expression of novel biomarker RCSD1 predicts poor prognosis of lung adenocarcinoma

Lung adenocarcinoma(LUAD)is a highly malignant lung tumor.In patients with acute lymphoblastic leukemia,the RCSD domain containing 1(RCSD1)gene is translocated and fused with the ABL1 gene to form the RCSD1-ABL1 fusion gene,resulting in high chromosome instability.However,the role of RCDS1 in lung adenocarcinoma remains unclear.This study aimed to evaluate the relationship between the expression of RCSD1 in lung adenocarcinoma,clinical prognosis,biological processes involved,and immune infiltration.The lung cancer explorer database was used to conduct a meta-analysis on the study of RCSD1 in lung adenocarcinoma.We downloaded the sequencing data of the RCSD1 gene in lung adenocarcinoma for prognostic analysis.A receiver operating characteristic(ROC)curve was drawn to assess the diagnostic value of RCSD1 expression in LUAD.Using R language,univariate and multivariate COX regression analysis of the clinical data of RCSD1 in lung adenocarcinoma was carried out.The molecular biological process of RCSD1 in lung adenocarcinoma and the relationship between RCSD1 expression level and immune infiltration were analyzed.Different from the normal lung tissue,the expression level of RCSD1 in lung adenocarcinoma is decreased.Low expression of RCSD1 is related to different clinicopathological characteristics.RCSD1 participates in multiple immune-related pathways and is positively correlated with tumor immune infiltrating cells,immune phenotypes,and immune checkpoint expression.We reveal for the first time the prognostic role of RCSD1 in lung adenocarcinoma.Its mechanism of action may be involved in regulating immune infiltration and can serve as a potential biomarker of lung adenocarcinoma.

ABCA3作为非小细胞肺癌的预后生物标志物及其与免疫细胞浸润的相关性

目的 本研究旨在基于生物信息学分析探讨ABCA3在非小细胞肺癌——肺腺癌(lung adenocarcinoma,LUAD)中的临床意义和生物学功能。方法 基于癌症基因组图谱(the Cancer Genome Atlas,TCGA),提取LUAD中ABCA3表达和相应的临床信息。使用R4.2.2软件进行统计分析。采用Wilcoxon符号秩和检验比较TCGA LUAD队列中肿瘤组织与对照组之间ABCA3的表达,以及临床病理参数与ABCA3表达水平之间的关系。根据ABCA3表达的中位数,将TCGA LUAD患者分为高表达组和低表达组。使用survival包和survminer包分析ABCA3与LUAD患者总生存(overall survival,OS)期和无进展生存(progression free survival,PFS)期的关系,并进行单因素和多因素Cox回归分析确定与LUAD预后相关的危险因素。使用rms包构建预测LUAD患者1年、2年和3年OS率的列线图模型。使用DESeq2包对高表达组和低表达组患者进行差异表达基因(differential expressed genes,DEGs)分析,并使用cluster Profil er包对DEGs进行基因本体(Gene Ontology,GO)数据库和基因组京都百科全书(Kyoto Encyclopedia of Genes and Genomes,KEGG)富集分析。利用CIBERSORT算法预测LUAD肿瘤样本和正常样本中22种浸润性免疫细胞的丰度,并分析ABCA3表达与免疫浸润细胞和免疫检查点之间的相关性。结果 ABCA3基因在LUAD肿瘤组织中的表达均低于配对和非配对样本正常组织(P<0.05)。ABCA3高表达LUAD患者的OS (P=0.031)和PFS (P=0.044)明显高于低表达患者。T2分期(P=0.004)和T3分期(P=0.044)患者ABCA3的表达显著低于T1分期患者。多因素Cox回归分析显示,T分期、N分期和ABCA3表达是影响LUAD预后的独立影响因素(P<0.05)。基于ABCA3表达、T分期和N分期构建的列线图预测模型的C-index为0.86,提示模型与实际结果较为一致。校准曲线中的偏差修正线接近理想曲线,提示列线图模型的预测结果与观测结果较吻合。基因集富集分析显示ABCA3高表达组主要与花生四烯酸代谢、补体和凝血级联、肠道免疫网络免疫球蛋白A产生等有关。ABCA3的表达与NRP1、TRFRSF14、TNFSF15、CD40LG、HHLA2、CD28呈明显正相关,而与IDO1、CD70、TNFSF4、CD276和VTCN1呈明显负相关(P<0.05)。12种免疫浸润细胞在高表达组和低表达组存在明显差异(P<0.05)。此外,14种免疫浸润细胞与ABCA3表达呈现明显相关性(P<0.05),包括巨噬细胞、CD4+T细胞和树突细胞。结论 ABCA3的表达与LUAD患者预后和免疫细胞浸润有关,可能是预测非小细胞肺癌预后的有价值生物标志物。

基于失巢凋亡相关基因预测肺腺癌转移及预后模型的构建与验证

目的:失巢凋亡是一种特殊的程序性细胞死亡,在肿瘤转移中发挥重要的作用。肺腺癌常发生多器官扩散性转移,严重影响患者的预后。本研究旨在探索新的失巢凋亡相关标志物预测肺腺癌转移及预后。方法:从TCGA数据库和GEO数据库获取肺腺癌转移患者和未转移患者的基因表达谱和相应的临床数据,从GeneCard数据库下载293个失巢凋亡相关基因。通过无监督聚类分析,将肺腺癌转移患者分成两组肿瘤亚型,TIMER数据库和单样本基因集富集分析评估两组的免疫浸润和免疫细胞功能。接着,采用最小绝对收缩和选择算法和Cox回归模型构建失巢凋亡相关基因预后模型并进行外部数据集验证,ROC曲线和列线图进一步评估模型的预测能力。同时,评估了高风险组和低风险组的免疫治疗和药物治疗差异。最后,通过实时荧光定量PCR (qRTPCR)验证标记基因的表达以及多重免疫荧光组化验证标记基因的免疫细胞浸润。结果:两聚类分子亚型在临床病理特征、预后和免疫细胞浸润方面存在显著差异。Lasso及多因素Cox回归筛选得到了3个失巢凋亡相关预后基因(TLE1、EIF2AK3和BIRC3),构建3基因风险模型。根据风险评分中位值将患者分为高、低风险组,低风险组表现出更高的总生存期时间,免疫活性,肿瘤突变负担和PD1/PDL1表达,这与免疫检查点抑制剂的更好应答一致。列线图一步证明了模型的优越预测价值。qRTPCR显示,3个预后标志基因在肺腺癌细胞系和肺腺癌组织表达更高,多重免疫荧光组化验证其表达与免疫细胞浸润程度正相关。结论:综上所述,本研究建立了失巢凋亡相关基因为特征的预后风险模型,该模型在肺腺癌患者中有很好的预后预测价值,因而可作为评估肺腺癌患者预后的潜在诊断标志物和治疗靶点。

低剂量CT影像组学列线图鉴别纯磨玻璃样微浸润性腺癌和浸润性腺癌

目的:探讨低剂量CT影像组学列线图鉴别纯磨玻璃样结节(pGGN)中肺微浸润性腺癌(MIA)和肺浸润腺癌(IAC)的价值。方法:回顾性分析2018年1月至2023年4月温州医科大学附属第五医院经手术病理证实且CT表现为pGGN的239例肺腺癌患者的临床和CT影像资料,包括MIA 93例和IAC 146例。采用完全随机法以7:3的比例将患者分为训练集(n=167)和验证集(n=72)。使用Radcloud平台提取低剂量CT图像中病灶的影像组学特征,通过降维保留纳入模型的最佳特征。随后,建立3种机器学习分类器包括逻辑回归(LR)、支持向量机(SVM)和随机森林(RF),以验证集中曲线下面积(AUC)最高的分类器作为最佳影像组学模型,并将其结果输出为影像组学评分(Rad-score)。将P<0.05的临床和CT形态学特征纳入到多因素Logistic回归分析中,筛选出鉴别MIA和IAC的独立危险因素,并建立临床模型。最终,基于Rad-score和临床危险因素构建联合模型,并绘制列线图。采用受试者工作特征(ROC)曲线的AUC、灵敏度、特异度和准确度评价模型的诊断性能。结果:通过降维得到15个与鉴别MIA和IAC显著相关的影像组学特征。在3种机器学习分类器中,RF具有最佳的诊断性能,其在训练集和验证集的AUC分别为0.837、0.788。多因素Logistic回归分析显示,最大径较大、形状不规则和毛刺征是鉴别MIA和IAC的独立危险因素,进一步结合Rad-score建立列线图。ROC曲线结果显示,该列线图呈现出良好的诊断性能,在训练集中的AUC、灵敏度、特异度、准确度分别为0.913、87.25%、81.54%、84.94%;在验证集中的AUC、灵敏度、特异度、准确度分别为0.862、88.63%、75.01%、82.78%。结论:低剂量CT影像组学列线图能够较好地鉴别表现为pGGN的MIA和IAC,可用于指导临床手术计划制定。

多组学分析LOXL2在肺腺癌诊断和预后评估中的作用

目的采用多数据库深入分析赖氨酰氧化酶样蛋白2(LOXL2)在肺腺癌中的表达、基因组改变、预后和免疫浸润,以探讨其在肺腺癌诊断和预后评估中的作用。方法采用TIMER、UALCAN、GEPIA和Kaplan-Meier数据库分析LOXL2表达并进行生存分析。采用cBioPortal数据库分析LOXL2在肺腺癌患者中的基因组变化。采用TIMER分析LOXL2和免疫细胞浸润及免疫检查点的相关性。采用HPA数据库描述LOXL2在正常肺组织和肺腺癌组织的蛋白表达。结果LOXL2在肺腺癌中的mRNA和蛋白水平表达均高于正常组织。LOXL2的高表达与肺腺癌较晚的分期和较差的预后相关。LOXL2的基因改变率为6%。LOXL2与肺腺癌中的部分免疫细胞浸润和免疫检查点[程序性细胞死亡蛋白-1(PD-1)和细胞毒性T淋巴细胞相关抗原4(CTLA-4)]密切相关。免疫组织化学实验表明LOXL2在肺腺癌中的蛋白表达高于正常肺组织。结论通过多组学数据挖掘表明,LOXL2在肺腺癌组织中呈高表达,且与免疫细胞浸润和患者预后不良相关,LOXL2可作为肺腺癌诊断和预后的新型生物标志物。

SHCBP1表达在肺腺癌预后及免疫细胞浸润中的临床价值

目的探讨纺锤体相关蛋白1(SHCBP1)在肺腺癌(LUAD)组织中的表达、预后及其对免疫细胞浸润的影响。方法从癌症基因组图谱(TCGA)数据库和基因表达综合(GEO)数据库下载LUAD组织的转录、临床及生存信息数据,比较LUAD和正常肺组织SHCBP1表达差异,分析LUAD中SHCBP1表达与临床参数、临床预后的相关性以及独立预后因素,评估SHCBP1高低表达组中免疫细胞浸润情况,预测SHCBP1相关信号通路。结果相比正常肺上皮组织,LUAD组织中的SHCBP1表达升高;SHCBP1表达水平与LUAD患者的年龄、T分期、N分期和临床分期均有关;SHCBP1高表达组的总生存期(OS)、疾病特异性生存期(DSS)、无进展生存期(PFS)预后较差;多因素COX回归分析表明SHCBP1是LUAD患者独立预后因素;基因富集分析(GSEA)结果提示SHCBP1高表达基因富集在有丝分裂姐妹染色单体分离、染色体分离及姐妹染色单体分离等基因集中;CIBERSORT和ssGSEA分析显示:SHCBP1高表达组CD4和CD8T细胞、自然杀伤T细胞、辅助T细胞、记忆B细胞等肿瘤浸润免疫细胞数量增加。结论SHCBP1在LUAD组织中上调,SHCBP1高表达与LUAD不良预后有关,SHCBP1可能成为LUAD的预后生物标志物及免疫治疗生物靶标。

肺腺癌中免疫治疗相关氧化应激基因表达的临床意义及其与免疫细胞浸润和药物敏感性的关系

目的:探究肺腺癌中与免疫治疗相关氧化应激基因(IROSG)及其与肿瘤组织免疫浸润和患者预后的关系。方法:从TCGA数据库和GEO数据库下载肺腺癌患者IROSG表达数据及相关临床信息。对非小细胞肺癌免疫治疗队列进行差异基因表达分析以获取免疫治疗相关基因,然后与从GeneCards数据库筛选的氧化应激相关基因取交集得到IROSG。基于得到的IROSG对肺腺癌患者进行分型,对亚型的差异表达基因进行单因素COX、LASSO和多因素COX回归分析以构建预后模型。使用模型公式计算每个患者的风险评分,并将患者划分为高、低风险组。从多个层面验证模型的预测效能,并进行肿瘤微环境(TME)分析、免疫治疗反应预测和药物敏感性分析。结果:通过数据库分析获取82个IROSG,IROSG高表达的肺腺癌患者预后较好(P<0.05)。基于IROSG表达水平分型和风险评分构建的肺腺癌患者预后模型预测能力好,基于风险评分和病例特征等预后因子构建的列线图和校正曲线能较好地预测肺腺癌患者的总生存率。低风险组主要富集于同种异体移植物排斥和自身免疫性疾病等通路,而高风险组主要富集在细胞周期和DNA复制等通路上,且低风险组肺腺癌组织中免疫细胞浸润水平较高。高、低风险评分结合肿瘤突变负荷(TMB)、TME、肿瘤免疫功能障碍和排斥(TIDE)评分和免疫检查点分子表达水平能较好地预测肺腺癌患者预后、免疫治疗反应和对化疗药物的敏感性。结论:本研究构建了一个可以预测肺腺癌患者预后和免疫治疗反应的模型,可为肺腺癌患者个体化治疗提供了理论依据。

基于生物信息学分析SGOL1在肺腺癌中的表达及预后价值

目的通过生物信息学方法分析Shugoshin-1(SGOL1)在肺腺癌中的表达及预后价值。方法从癌症基因组图谱数据库中下载肺腺癌组织和正常组织的表达谱数据和临床资料,并对SGOL1进行表达差异分析和临床相关性分析。使用R包“pROC”绘制受试者操作特征曲线(receiver operator characteristic curve,ROC曲线)评估SGOL1表达对肺腺癌患者临床诊断预测的准确性;利用R包“survival”“survminer”和单因素及多因素Cox回归分析评估SGOL1表达对肺腺癌患者预后的影响;通过检索肿瘤免疫单细胞中心和TIMER2.0数据库,分析肺腺癌中SGOL1的表达分布及与免疫细胞浸润的关系;利用LinkedOmics数据库对SGOL1及其共表达进行功能富集分析;利用交互作用基因/蛋白质检索工具构建SGOL1的蛋白质–蛋白质相互作用网络。结果与正常组织比较,肿瘤组织的SGOL1表达量显著上调(P<0.001);与癌旁组织比较,肿瘤组织的SGOL1表达量显著上调(P<0.001)。在肺腺癌的不同临床病理分期中,与Ⅰ期比较,Ⅱ期、Ⅲ期、Ⅳ期的SGOL1显著高表达(P<0.05)。ROC曲线显示,SGOL1对肺腺癌患者具有良好的诊断效能,曲线下面积为0.959(95%CI:0.942~0.975)。SGOL1高表达组患者的总生存期、疾病特异生存期、无病生存期和无瘤间期均较SGOL1低表达组显著缩短(P<0.05)。单因素及多因素Cox回归分析结果表明,临床分期(HR=1.629,P<0.001)和SGOL1表达水平(HR=1.447,P=0.002)与肺腺癌患者的预后较差相关,可作为肺腺癌患者预后的独立危险因素。SGOL1表达水平与B细胞、CD4^(+)T细胞和树突状细胞的浸润水平呈显著负相关(P<0.05),与巨噬细胞、CD8^(+)T细胞和中性粒细胞的浸润水平呈显著正相关(P<0.05)。富集分析显示,SGOL1可能在有丝分裂、细胞周期、p53信号通路和氨基酸代谢等途径中发挥作用。蛋白质-蛋白质相互作用网络分析提示SGOL1与CBX1、PPP2CA、PPP2R5C、CDCA8、ESPL1、PPP2R1A、BUB1、PPP2R5A、SGO2、CDC20等多个分子关系密切。结论SGOL1在肺腺癌组织中高表达,且与肺腺癌患者的预后较差相关。SGOL1可作为预测肺腺癌患者预后的生物标志物之一。

肿瘤微环境免疫细胞浸润在肺腺癌进展中的作用机制研究

目的通过生物信息学技术,筛选出与肺腺癌(LUAD)复发相关的关键基因和信号通路,为探讨LUAD复发的分子机制提供理论支持。方法从TCGA和GEO数据库中下载LUAD相关数据集,利用加权基因共表达网络分析(WGCNA)算法挑选关键基因模块,采用LASSO-Cox回归分析构建预后模型;Limma算法筛选差异表达基因;Estimate和MCP算法评估免疫细胞浸润。结果共筛选出29个相关基因模块。单因素Cox分析结果显示,仅有4个基因与患者预后显著相关。基于该基因集进行的LASSO-Cox预后模型显示,风险评分高的患者其预后差,提示该模型具有良好的预测能力。该模型筛选出4个关键基因,分别为丝氨酸-苏氨酸激酶受体相关蛋白(STRAP)、G蛋白亚基γ12(GNG 12)、线粒体甘油-3-磷酸酰基转移酶(GPAM)、锚蛋白重复和泛素结构域蛋白1(ANKUB 1)。本研究对STRAP进行了深入分析,结果显示,STRAP在泛癌中呈现广泛高表达,且与多种肿瘤的不良预后及临床病理特征显著相关。STRAP与免疫抑制分子的表达呈显著正相关。高表达STRAP的患者其微环境CD8+T细胞、NK细胞等多种免疫细胞浸润降低,抑癌基因的单核苷酸多态性(SNP)显著升高,呈现“冷肿瘤”表型。此外,免疫组织化学表明,STRAP在肿瘤组织中显著高表达。结论基因模型能够较好地预测患者复发风险,其中STRAP在LUAD发展中可能发挥重要作用。

胸部CT在预测周围型浸润性肺腺癌EGFR基因突变中的应用研究

目的分析胸部计算机断层扫描(CT)在预测周围型浸润性肺腺癌表皮生长因子受体(EGFR)基因突变中的应用价值。方法选取邓州市疾病预防控制中心2020年1月到2023年2月的462例周围型浸润性肺腺癌患者实施胸部CT检测,对比不同组织学亚型(贴壁为主型、腺泡为主型、乳头为主型、微乳头为主型、实体为主型)的EGFR基因突变状态、胸部CT图像特征(部位、形态、磨玻璃密度影、最大直径、磨玻璃密度影中瘤直径比、空泡征、支气管充气征、毛刺、肿瘤不伴有囊腔样改变),并应用Logistic回归分析胸部CT影像特征与EGFR基因突变的相关性。结果本组EGFR基因突变共计180例(突变组),野生型共计282例(野生组),通过分析组织学亚型与EGFR基因突变状态的相关性显示,突变组中贴壁为主型占比显著高于野生组,差异具有统计学意义(P<0.05),其它类型比较差异无统计学意义(P>0.05)。通过分析胸部CT检查结果显示,野生组具有磨玻璃密度影占比显著高于突变组,肿瘤不伴有囊腔样改变占比显著低于突变组,差异均有统计学意义(P<0.05)。Logistic回归分析结果表明,具有磨玻璃密度影、肿瘤不伴有囊腔样改变对于预测EGFR基因突变具有非常重要的临床价值。结论胸部CT可较为准确的预测周围型浸润性肺腺癌EGFR基因突变。

PSMA4在肺腺癌预后、诊断和免疫浸润中的作用和机制研究

目的探究PSMA4在肺腺癌(lung adenocarcinoma,LUAD)预后、诊断和免疫浸润中的作用和机制。方法从癌症基因组图谱(the cancer genome atlas,TCGA)数据库中获取LUAD患者的表达谱和临床信息。通过Wilcoxon秩和检验比较LUAD组(n=539)与正常组(n=59)PSMA4基因的表达水平。通过在GEO数据库下载GSE40791和GSE10072 LUAD数据集,验证PSMA4在LUAD组与正常组中的表达水平。收集10对2023年1-12月在陆军军医大学第二附属医院呼吸科进行纤维支气管镜肺活检术的LUAD患者的肿瘤和癌旁组织样本。采用RT-qPCR技术验证PSMA4在10对LUAD和癌旁组织中的表达。体外培养肺癌细胞和正常肺上皮细胞,通过RT-qPCR检测PSMA4在各组细胞中的表达。并对PSMA4的高低表达组进行了功能富集分析和免疫细胞浸润分析,通过Cox回归分析和Kaplan-Meier(KM)法确定PSMA4对于LUAD的诊断和预后的价值,并构建列线图预测不同时间点的总生存率。结果TCGA数据集、GSE40791和GSE10072 LUAD数据集中的表达数据显示,PSMA4在LUAD组中的表达明显高于正常组(P<0.01)。RT-qPCR检测分析发现,PSMA4在LUAD和肺癌细胞中的表达显著高于癌旁组织和正常肺上皮细胞(P<0.01)。PSMA4高表达是诊断LUAD和预后不良的标志物,与肿瘤微环境中效应记忆性T细胞、滤泡辅助性T细胞、B淋巴细胞、自然杀伤细胞、中央记忆性T细胞、肥大细胞的水平的降低有关。结论PSMA4对LUAD有良好的诊断效能,并且与LUAD的预后和免疫浸润密切相关。

hsa-miR-1293正向调控双硫死亡基因SLC3A2促进肺腺癌发展

目的 通过生物信息学方法对肺腺癌患者的基因表达谱芯片进行分析,研究影响肺腺癌的发展机制,探索肺腺癌新的治疗靶点。方法 从癌症基因图谱数据库下载mRNA和miRNA表达数据,通过R语言和生存分析筛选关键基因并通过数据库生存模块进行验证,对预后相关基因进行高表达通路富集分析。最后进行关键基因与免疫细胞相关性分析。结果 经筛选确定关键双硫死亡基因SLC3A2和关键核激活miRNA(hsa-miR-1293),SLC3A2与hsa-miR-1293表达呈正相关,其表达越高,肺腺癌患者预后越差。与SLC3A2最显著相关的富集通路为氨酰基转移RNA生物合成。SLC3A2与4种差异免疫细胞呈正相关,与4种差异免疫细胞呈负相关。结论 hsa-miR-1293正向调控双硫死亡基因SLC3A2表达促进肺腺癌的发生发展,可为肺腺癌开发新的治疗靶点提供思路。

BRCA1基因与肺腺癌免疫细胞浸润和预后的关系

目的探讨乳腺癌易感基因(BRCA1)与肺腺癌免疫细胞浸润和预后的关系。方法收集68例手术切除新鲜肺腺癌组织与癌旁肺组织(>癌组织边缘10 cm)标本,qRT-PCR检测BRCA1mRNA水平与免疫组化BRCA1基因表达;采用Oncomine数据库、Kaplan-meier Plotter数据库、TIMER数据库分析BRCA1基因与肺腺癌免疫细胞浸润和预后的关系。结果采用Oncomine数据库分析显示肺腺癌(LUAD)中BRCA1基因水平高于癌旁组织(P<0.05),qRT-PCR检测结果显示肺腺癌组织中BRCA1 mRNA表达水平高于癌旁组织,差异有统计学意义(P<0.05);TIMER数据库分析,BRCA1表达与中心粒细胞(γ=0.147,P=1.28×10-3)浸润水平具有强相关性,但与B细胞(γ=-0.09,P=4.73×10^(-2))、CD8+T细胞(γ=0.047,P=3.00×10^(-1))、CD4+T细胞(γ=0.039,P=3.91×10^(-1))、巨噬细胞(γ=-0.038,P=4.05×10^(-1))、及树突状细胞(γ=0.039,P=3.85×10^(-1))无相关性;Kaplan-meier Plotter数据库分析,BRCA1基因高表达肺腺癌患者总生存期、无病生存率低于低表达肺腺癌患者,差异有统计学意义(P<0.05)。结论BRCA1基因及mRNA在肺腺癌组织中呈高表达;BRCA1基因与患者不良预后及中性粒细胞免疫浸润密切相关。

肺腺癌中端粒相关lncRNA的表达及免疫相关分析

目的:本研究致力于开发一种基于端粒相关长链非编码RNA(lncRNA)的肺腺癌(LUAD)预后模型,以填补当前在高活性端粒酶作为肿瘤治疗靶点研究中的空白。通过综合分析端粒相关lncRNA的表达模式和临床数据,旨在构建可靠模型,预测LUAD患者的生存率和疾病进展,从而为个性化治疗提供精准指导。方法:通过癌症基因组图谱(TCGA)数据库提取肺腺癌(LUAD)样本数据,包括长链非编码RNA(lncRNA)表达谱和临床信息。采用共表达分析识别与端粒相关lncRNA,再通过Cox回归和LASSO回归分析构建LUAD患者生存期风险模型。模型预测效力通过Log-rank检验和Kaplan-Meier分析评估。并使用GO和KEGG分析进行端粒相关lncRNA功能富集可视化。免疫浸润评估采用CIBERSORT算法,分析肿瘤组织中免疫细胞的分布。结果:本研究构建了一个基于端粒相关lncRNA的预测模型,该模型包括6个预后相关lncRNA,它们在肺腺癌中的表达水平在不同风险组和临床模型中存在显著差异。高风险组的患者总生存(OS)时间显著缩短,且风险评分被验证为肺腺癌OS的独立预后因素。通过GSEA分析,揭示了与高表达基因相关的关键生物学通路,包括细胞周期、DNA复制和有丝分裂中的微管细胞骨架组织。免疫检查点分析表明PD-1、CTLA-4等基因在高风险组中表达水平显著不同,这一发现暗示针对肺腺癌患者,通过评估这些基因的表达情况,可以为实施个性化的免疫检查点阻断疗法提供依据。这表明,基于患者特定的基因表达模式,可以定制化免疫治疗方案,从而提高治疗的针对性和效果。结论:端粒相关lncRNAs风险模型具有准确预测LUAD患者预后的潜力,可作为未来潜在的治疗靶点。

肺腺癌中糖酵解代谢特征预测预后及指导治疗

目的:有氧糖酵解作为肿瘤独特的代谢特征,其作用机制仍未被完全阐明。本研究探索糖酵解代谢在肺腺癌(lung adenocarcinoma,LUAD)及其免疫微环境中的作用,以寻求糖酵解代谢与LUAD预后和免疫治疗效果的关系。方法:从癌症基因组图谱(The Cancer Genome Atlas,TCGA)和基因表达综合(Gene Expression Omnibus,GEO)数据库下载LUAD患者的基因表达数据和临床信息,采用单变量、最小绝对收缩和选择算子(least absolute shrinkage and selection operator,LASSO)Cox回归分析构建糖酵解代谢相关基因的LUAD预后评估模型。结果:在TCGA队列中,高危评分患者的预后更差,在GEO队列中也证实了此模型的可靠性。利用统计学工具获得的由糖酵解相关基因组成的预后模型和列线图模型为预测预后提供了一种新方法,并在15对LUAD和正常组织中验证了风险标签中的15个基因,它们在LUAD组织中表达异常。此外,风险评分与LUAD免疫微环境相关,经模型评估发现高危评分患者更适合接受免疫治疗。结论:本研究构建了与糖酵解代谢相关的15个基因组成的预后模型,该模型可预测患者对免疫治疗的敏感性,可用来指导临床实践,促进肿瘤的个体化治疗。