Multifaceted p21 in carcinogenesis,stemness of tumor and tumor therapy

Cancer cells possess metabolic properties that are different from those of benign cells. p21, encoded by CDKN1A gene, also named p21^Cip1/WAF1, was first identified as a cyclin-dependent kinase regulator that suppresses cell cycle G1/S phase and retinoblastoma protein phosphorylation. CDKN1A (p21) acts as the downstream target gene of TP53 (p53), and its expression is induced by wild-type p53 and it is not associated with mutant p53. p21 has been characterized as a vital regulator that involves multiple cell functions, including G1/S cell cycle progression, cell growth, DNA damage, and cell stemness. In 1994, p21 was found as a tumor suppressor in brain, lung and colon cancer by targeting p53 and was associated with tumorigenesis and metastasis. Notably, p21 plays a significant role in tumor development through p53-dependent and p53-independent pathways. In addition, expression of p21 is closely related to the resting state or terminal differentiation of cells. p21 is also associated with cancer stem cells and acts as a biomarker for such cells. In cancer therapy, given the importance of p21 in regulating the G1/S and G2 check points, it is not surprising that p21 is implicated in response to many cancer treatments and p21 promotes the effect of oncolytic virotherapy.     

丝氨酸蛋白酶抑制剂(SERPIN)家族相关基因在结肠腺癌中预后模型的建立及应用

应用生物信息学方法,构建结肠腺癌(COAD)丝氨酸蛋白酶抑制剂(SERPIN)家族相关基因预后模型。从TCGA数据库和GEO数据库下载结肠腺癌(COAD)转录组和临床数据,根据数据中SERPINs家族基因的表达量对COAD患者进行一致性聚类分析;将数据随机均分为训练集(Train)组和验证集(Test)组,基于两个亚型的差异基因,利用Train组进行COX回归和Lasso回归构建预后模型,根据模型风险评分中位值将样本分为高、低风险两组,绘制高低风险组患者生存曲线;通过ROC曲线评价模型预测能力;利用Test组数据验证模型;构建列线图,评估患者生存率模型预测值与实际值的一致性;并利用利用ESTIMATE算法和CIBERSORT算法评估风险评分和肿瘤微环境(TME)以及免疫浸润的相关性。通过34个SERPIN基因确定了两个亚型,基于2个亚型筛选出了436个预后相关分型差异基因,通过Lasso回归确定出了11个预后相关基因参与风险模型的构建,根据模型评分区分的高低风险组具有明显的生存差异,列线图可以准确预测1、3和5年生存率。肿瘤微环境分析和免疫浸润分析显示高风险评分组患者免疫活性差。SERPIN家族相关基因构建的风险评分模型能够预测COAD的预后,有利于进一步指导临床对COAD的诊治,提高患者生存率。     

Profiles of immune infiltration in lung adenocarcinoma and their clinical significant: A gene-expression–based retrospective study

Lung cancer is one of the fatal tumors. The tumor microenvironment plays a key role in regulating tumor progression. To figure out the role of tumor microenvironment in lung adenocarcinoma (LUAD), ESTIMATE algorithm was used to evaluate the immune scores in LUAD. Patients with low immune scores had a worse overall survival (OS) compared with high immune scores. Using RNA-Seq data of 489 patients in The Cancer Genome Atlas (TCGA), differentially expressed genes (DEGs) were identified between high- and low-immune score groups. Based on the DEGs, nine-gene signature was constructed by the least absolute shrinkage and selection operator Cox regression model in TCGA set. The signature demonstrated significant prognostic value in both TCGA and Gene Expression Omnibus database. Multivariate Cox regression analyses indicated that nine-genes signature was an independent prognostic factor. Subgroup analysis also revealed a robust prognostic ability of nine-gene signature. A nomogram with a C-index of 0.722 had a favorable power for predicting 3-, 5-, and 10-year survival for clinical use by integrating nine-gene signature and other clinical features. Co-expression and functional enrichment analysis showed that nine-gene signature was significantly associated with immune response and provided potential profound molecules for revealing the mechanism of tumor initiation and progression. In conclusion, we revealed the significance of immune infiltration and built a novel nine-gene signature as a reliable prognostic factor for patients with LUAD.     

INHA acts as a novel and potential biomarker in lung adenocarcinoma and shapes the immune-suppressive tumor microenvironment

BackgroundINHA expression has been correlated with the development, growth, and progression of multiple cancer types. However, the biological role of INHA has not been investigated in patients with lung adenocarcinoma (LUAD). Here, we performed a comprehensive bioinformatics analysis of the LUAD dataset to determine the mechanisms underlying the regulation of tumorigenesis by INHA.Materials and methodsINHA expression and clinical information of patients with LUAD were obtained from The Cancer Genome Atlas (TCGA) database. Protein levels in LUAD cell lines and human lung epithelial cells were examined by western blotting. Next, the prognostic value of INHA in LUAD was assessed using Cox regression analysis, while the potential biological functions and the impact on the immune microenvironment of INHA were investigated using gene set enrichment analysis (GSEA) and single sample GSEA (ssGSEA). Finally, the effect of INHA on LUAD cell proliferation and invasion was determined in vitro and in vivo.ResultsWe found significantly high mRNA and protein expression levels of INHA in LUAD tissues and cell lines. Additionally, a higher expression of INHA was linked to a shorter overall survival (OS) and a worse pathological stage, while INHA expression was associated with immune cell infiltration and immune-related markers in the LUAD tumor microenvironment. LUAD with high INHA expression tends to be a cold tumor. Furthermore, GO and KEGG enrichment analysis indicated that INHA-related genes were enriched in the cell adhesion and immune signaling pathways of LUAD. INHA promoted LUAD cell proliferation and invasion, in vitro and in vivo, by inducing the EGFR pathway.ConclusionOur findings revealed that INHA is overexpressed in LUAD and is linked to a poor prognosis. Our study demonstrates the potential of INHA as an immunotherapeutic and predictive biomarker in LUAD.     

Typical tumor immune microenvironment status determine prognosis in lung adenocarcinoma

BackgroundImmune cells, vital components of tumor microenvironment, regulate tumor survival and progression. Lung adenocarcinoma (LUAD), the tumor with the highest mortality rate worldwide, reconstitutes tumor immune microenvironment (TIME) to avoid immune destruction. Data have shown that TIME influences LUAD prognosis and predicts immunotherapeutic efficacy. The related information about the role of TIME's characteristics in LUAD is limited.MethodsWe performed unsupervised consensus clustering via machine-learning techniques to identify TIME clusters among 1906 patients and gathered survival data. The characteristics of TIME clusters of LUAD were visualized by multi-omics analysis, pseudo-time dynamic analysis, and enrichment analysis. TIME score model was constructed by principal component analysis. Comprehensive analysis and validation were conducted to test the prognostic efficacy and immunotherapeutic response of TIME score.ResultsTIME clusters (A, B and C) were constructed and exhibited different immune infiltration states. Multi-omics analyses included significant mutated genes (SMG), copy number variation (CNV) and cancer stemness that were significantly different among the three clusters. TIME cluster A had a lower SMG, lower CNV, and lower stemness but a higher immune infiltration level compared to TIME clusters B and C. TIME score showed that patients in low TIME score group had higher overall survival rates, higher immune infiltration level and high expression of immune checkpoints. In validation cohorts, low TIME score subgroup had better drug sensitivity and favorable immunotherapeutic response.ConclusionWe constructed a stable model of LUAD immune microenvironment characteristics that may improve the prognostic accuracy of patients, provide improved explanations of LUAD responses to immunotherapy, and provide new strategies for LUAD treatment.     

CYP1A1, GSTM1 and GSTT1 polymorphisms and lung cancer: a pooled analysis of gene-gene interactions

Gene-environment interactions have been extensively studied in lung cancer. It is likely that several genetic polymorphisms cooperate in increasing the individual risk. Therefore, the study of gene-gene interactions might be important to identify high-susceptibility subgroups. GSEC is an initiative aimed at collecting available data sets on metabolic polymorphisms and the risks of cancer at several sites and performing pooled analyses of the original data. Authors of published papers have provided original data sets. The present paper refers to gene-gene interactions in lung cancer and considers three polymorphisms in three metabolic genes: CYP1A1, GSTM1 and GSTT1. The present analyses compare the gene-gene interactions of the CYP1A1*2A, GSTM1 and GSTT1 polymorphisms from studies on lung cancer conducted in Europe and the USA between 1991 and 2000. Only Caucasians have been included. The data set includes 1466 cases and 1488 controls. The only clear-cut association was found with CYP1A1*2A. This association remained unchanged after stratification by polymorphisms in other genes (with an odds ratio [OR] of approximately 2.5), except when interaction with GSTM1 was considered. When the OR for CYP1A1*2A was stratified according to the GSTM1 genotype, the OR was increased only among the subjects who had the null (homozygous deletion) GSTM1 genotype (OR=2.8, 95% CI=0.9-8.4). The odds ratio for the interactive term (CYP1A1*2A by GSTM1) in logistic regression was 2.7 (95% CI=0.5-15.3). An association between lung cancer and the homozygous CYP1A1*2A genotype is confirmed. An apparent and biologically plausible interaction is suggested between this genotype and GSTM1.     

Construction of an N6-methyladenosine lncRNA- and immune cell infiltration-related prognostic model in colorectal cancer

The present paper aims to shed light on the influence of N6-methyladenosine (m6A) long non-coding RNAs (lncRNAs) and immune cell infiltration on colorectal cancer (CRC). We downloaded workflow-type data and xml-format clinical data on CRC from The Cancer Genome Atlas project. The relationship between lncRNA and m6A was identified by using Perl and R software. Kyoto Encyclopedia of Genes and Genomes enrichment analysis was performed. Lasso regression was utilized to construct a prognostic model. Survival analysis was used to explore the relationship between clusters of m6A lncRNAs and clinical survival data. Differential analysis of the tumor microenvironment and an immune correlation analysis were used to determine immune cell infiltration levels in different clusters and their correlation with clinical prognosis. The expression of lncRNA was tightly associated with m6A. The univariate Cox regression analysis showed that lncRNA was a risk factor for the prognosis. Differential expression analysis demonstrated that m6A lncRNAs were partially highly expressed in tumor tissue. m6A lncRNA-related prognostic model could predict the prognosis of CRC independently. “ECM_RECEPTOR_INTERACTION” was the most significantly enriched gene set. PARP8 was overexpressed in tumor tissue and high-risk cluster. CD4 memory T cells, activated resting NK cells, and memory B cells were highly clustered in the high-risk cluster. All of the scores were higher in the low-risk group. m6A lncRNA is closely related to the occurrence and progression of CRC. The corresponding prognostic model can be utilized to evaluate the prognosis of CRC. m6A lncRNA and related immune cell infiltration in the tumor microenvironment can provide novel therapeutic targets for further research.

     

EDARV370A对新疆维吾尔族人群面部及耳朵形态的效应

外异蛋白受体基因(ectodysplasin A receptor,EDAR)是调控外胚层发育的重要基因。其关键错义突变EDARV370A的衍生等位基因370A在东亚和美洲原住民中具有很高的频率,但在非洲和欧洲罕见,该突变造成这些人群许多外胚层发育衍生表型的差异,包括东亚人特有的较直且厚的头发、较多的外泌汗腺、女性较小的乳房及铲形门齿等。目前,EDARV370A与同为外胚层衍生表型的人类头面部及耳部形态特征的关联尚不十分明确。本研究在715例新疆维吾尔族亚欧混合人群中,进行了EDARV370A与一系列系统的面部形态特征及耳朵形态表型的关联分析,以期更全面系统地理解EDARV370A对面部和耳朵形态的影响。研究表型包括利用本课题组近期发表的对三维面部照片自动化面部地标点标记方法获得的136个面部定量表型、1个下巴类型的定序分类表型以及6个耳朵形态的定序分类表型。研究发现EDARV370A与8个面部形态的定量表型、下巴类型以及3个耳朵形态定序分类表型显著相关(多重检验校正后P<0.05)。本研究结果进一步明确了EDARV370A的遗传多效性及其在亚欧混合人群中对面部和耳朵形态的影响。     

唾液酸免疫球蛋白型凝集素-15促进结直肠癌细胞增殖和迁移并抑制肿瘤组织中CD4+与CD8+T细胞浸润

唾液酸免疫球蛋白型凝集素-15(sialic acid-binding immunoglobulin-type lectin-15,Siglec-15)属于Siglecs家族的一员,是一种新型免疫抑制分子。Siglec-15在多种人类肿瘤细胞和肿瘤相关巨噬细胞中高表达,但Siglec-15在结直肠癌(colorectal cancer,CRC)中的生物学功能及其对免疫微环境的影响尚不明确。本文旨在分析Siglec-15异常表达对CRC细胞功能及CD4⁺T细胞、CD8⁺T细胞浸润的影响。首先,分析TCGA数据库中结直肠癌与正常组织中Siglec-15 mRNA表达水平,并对52例人CRC与配对癌旁组织进行免疫组织化学染色(IHC),发现Siglec-15在CRC中的表达水平高于癌旁组织(P<0.01)。CCK8和划痕愈合结果显示,敲低Siglec-15能抑制人CRC细胞SW480增殖(P<0.01)和迁移(P<0.05)。磁珠分选小鼠脾的CD8⁺T细胞并与小鼠CRC细胞MC38共培养,发现MC38细胞过表达Siglec-15能抑制CD8⁺T细胞对其的杀伤以及IFN-γ和TNF-α的分泌(P<0.01)。小鼠荷瘤结果表明,过表达Siglec-15可以促进小鼠肿瘤生长(P<0.05)。单样本基因集富集分析、荷瘤小鼠肿瘤组织及人结直肠癌组织IHC分析均表明,Siglec-15高表达时,肿瘤微环境中CD4⁺T细胞、CD8⁺T细胞浸润减少(P<0.05)。综上所述,Siglec-15可能通过促进CRC细胞增殖迁移以及抑制CD4⁺T细胞、CD8⁺T细胞浸润促进结直肠癌进展。本文为探究Siglec-15在CRC中的免疫抑制作用提供了一些新的实验依据。     

TMK4 receptor kinase negatively modulates ABA signaling by phosphorylating ABI2 and enhancing its activity

In plants, clade A type 2C protein phosphatases (PP2CAs) have emerged as major players in abscisic acid (ABA)-regulated stress responses by inhibiting protein kinase activity. However, how different internal and external environmental signals modulate the activity of PP2CAs are not well known. The transmembrane kinase (TMK) protein 4 (TMK4), one member of a previously identified receptor kinase subfamily on the plasma membrane that plays vital roles in plant cell growth, directly interacts with PP2CAs member (ABA-Insensitive 2, ABI2). tmk4 mutant is hypersensitive to ABA in both ABA-inhibited seed germination and primary root growth, indicating that TMK4 is a negative regulator in ABA signaling pathway. Further analyses indicate that TMK4 phosphorylates ABI2 at three conserved Ser residues, thus enhancing the activity of ABI2. The phosphorylation-mimic ABI2^{S139DS140DS266D} can complement but non-phosphorylated form ABI2^{S139AS140AS266A} cannot complement ABA hypersensitive phenotype of the loss-of-function mutant abi1-2abi2-2. This study provides a previously unidentified mechanism for positively regulating ABI2 by a plasma membrane protein kinase.     

Trade-off relationship between vein density and vein diameter of Achnatherum splendens in response to habitat changes in Zhangye wetland

Aims The coevolution between vein traits has influences on water use strategies of plant and the formation of leaf economic spectrum, and therefore is important for understanding the trade-off between carbon input in leaf vein construction and the functional feedback from leaf veins. Our aim is to study the allometric relationship between vein density and vein diameter of Achnatherum splendens populations at three natural microhabitats (subcanopy, transitional and open areas) in Zhangye wetland. Methods According to the shade condition of the arbor canopy and the distance to arbor, the A. splendens community were divided into three microenvironments: subcanopy, transitional and open areas. We sampled 10 (4 m × 4 m) A. splendens plots from each microenvironment and investigate the biological characteristics of the plots and leaf traits of the plants within the plots. Then the soil physical and chemical properties, and community photosynthetically active radiation (PAR) were investigated at three gradients. Six individual of A. splendens were selected in each plot and the leaf length, leaf width, vein density and vein diameter of two or three healthy and complete leaves from four directions of each individual were measured in laboratory. The SMA estimation method and correlation analysis were then used to examine the allometric relationship between vein density and vein diameter. Important findings Along the gradient from subcanopy, transitional zone to open areas, soil moisture displayed a pattern of initial decrease of plant community, and soil electric conductivity displayed increase changing trends. Photosynthetically active radiation (PAR), vapor pressure deficit (VPD), vein density (1.28-1.59 mm·mm^-2), leaf width and water use efficiency (WUE) increase gradually, while the leaf length, vein diameter (0.21-0.16 mm) of A. splendens decrease. The average value of plasticity indexes of leaf characteristics was 0.19. Leaf net photosynthetic rate (P_n), transpiration rate (T_r) and bundle density increase first and them decrease. The vein density and vein diameter of A. splendens were negatively correlated with each other in subcanopy environment (p < 0.01), transitional and open areas (p < 0.05). The SMA (0.54-1.50) slope of regression equation in the scaling relationships between vein density and vein diameter decrease gradually from subcanopy to open areas.     

Single-cell sequencing analysis and transcriptome analysis constructed the macrophage related gene-related signature in lung adenocarcinoma and verified by an independent cohort

BackgroundRecent studies have emphasized the close relationship between macrophages and tumor immunity, and the prognosis of lung adenocarcinoma (LUAD) patients is intimately linked to this. Nonetheless, the prognostic signature and classification of different immune patterns in LUAD patients based on the macrophages is largely unexplored.MethodsTwo sc-RNAseq datasets of LUAD patients were collected and reprocessed. The differentially expressed genes (DEGs) related to macrophages between LUAD tissues and normal lung tissues were then identified. Based upon the above genes, three distinct immune patterns in the TCGA-LUAD cohort were identified. The ssGSEA and CIBERSORT were applied for immune profiling and characterization of different subtypes. A four-gene prognostic signature for LUAD patients was established based on the DEGs between the subtypes using stepwise multi-Cox regression. TCGA-LUAD cohort was used as training set. Five GEO-LUAD datasets and an independent cohort containing 112 LUAD samples were used for validation. TIDE (tumor immune dysfunction and exclusion) and drug sensitivity analyses were also performed.ResultsMacrophage-related differentially expressed genes were found out using the publicly available scRNA-seq data of LUAD. Three different immune patterns which were proved to have distinct immune infiltration characteristics in the TCGA-LUAD cohort were recognized based on the above macrophage-related genes. Thereafter, 174 DEGs among the above three different immune patterns were figured out; on the basis of this, a four-gene prognostic signature was constructed. This signature distinguished the prognosis of LUAD patients well in various GSE datasets as well as our independent cohort. Further analyses revealed that patients which had a higher risk score also accompanied with a lower immune infiltration level and a worse response to several immunotherapy biomarkers.ConclusionThis study highlighted that macrophage were significantly associated with TME diversity and complexity. The four-gene prognostic signature could be used for predicting outcomes and immune landscapes for patients with LUAD.     

A signature of immune-related gene pairs predicts oncologic outcomes and response to immunotherapy in lung adenocarcinoma

In this study, we established the predictive model for lung adenocarcinoma (LUAD) depending on immune-related gene pairs (IRGPs) signature, which could not consider the technical bias of different platforms. Furthermore, we explored the predictive model with regard to the immune microenvironment and response to immunotherapy and identified specific drugs targeting the IRGPs model. Twenty-three IRGPs were identified and comprised the predictive model. When compared with the high-risk group, the low-risk group displayed a distinctly favorable prognosis and was characterized by increased immune score and decreased tumor purity. In addition, the low-risk group exhibited higher expression of immune checkpoint molecules, lower tumor stemness index, and was much more sensitive to immunotherapy. Lastly, candidate drugs that aimed at LUAD subtype differentiation were identified. The derived IRGPs model is an adverse independent biomarker for estimating oncologic outcomes in LUAD patients, and may be helpful to formulate personalized immunotherapy strategy.     

Synthesis of 4-amino-6-(hetero)arylalkylamino-1,2,4-triazolo[4,3-a]quinoxalin-1-one derivatives as potent A(2A) adenosine receptor antagonists

In previous papers (Colotta, V. et al. Arch. Pharm. Pharm. Med. Chem. 1999, 332, 39. Colotta, V. et al. J. Med. Chem. 2000, 43, 1158) we reported the synthesis and binding affinity at bovine (b) A₁ and A_2A and human (h) A₃ adenosine receptors (ARs) of the 4-amino-6-benzylamino-2-phenyl-1,2,4-triazolo[4,3-a]quinoxalin-1-one (compound A) which resulted in a potent and selective A_2A AR antagonist. Compound A provided the lead compound of a series of 6- or 8-(hetero)arylalkylamino-4-amino-2-phenyl-1,2,4-triazolo[4,3-a]quinoxalin-1-one derivatives (compounds 1–20) which are the object of this paper. Most of the newly synthesized compounds are inactive at hA₃ ARs while they possess both nanomolar bA_2A affinities and different degrees of bA_2A versus bA₁ selectivity. The binding data show that hydrophilic substituents on the benzyl moiety are the most profitable for bA_2A receptor affinity. Furthermore, their steric hindrance seems to play an important role for the bA_2A AR interaction, thus suggesting that the 6-aralkylamino moiety of these ligands interacts with a size-limited binding pocket of this AR subtype. Thus, the SAR studies provided us some new insights about the structural requirements of the bA_2A AR recognition site.     

Identification of cuproptosis‐related lncRNAs for prognosis and immunotherapy in glioma

Glioma is a highly invasive primary brain tumour, making it challenging to accurately predict prognosis for glioma patients. Cuproptosis is a recently discovered cell death attracting significant attention in the tumour field. Whether cuproptosis‐related genes have prognostic predictive value has not been clarified. In this study, uni‐/multi‐variate Cox and Lasso regression analyses were applied to construct a risk model based on cuproptosis‐related lncRNAs using TCGA and CGGA cohorts. A nomogram was constructed to quantify individual risk, including clinical and genic characteristics and risk. GO and KEGG analyses were used to define functional enrichment of DEGs. Tumour mutation burden (TMB) and immune checkpoint analyses were performed to evaluate potential responses to ICI therapy. Ten prognostic lncRNAs were obtained from Cox regression. Based on the median risk score, patients were divided into high‐ and low‐risk groups. Either for grade 2–3 or for grade 4, glioma patients with high‐risk exhibited significant poorer prognoses. The risk was an independent risk factor associated with overall survival. The high‐risk group was functionally associated with immune responses and cancer‐related pathways. The high‐risk group was associated with higher TMB scores. The expression levels of many immune checkpoints in the high‐risk group were significantly higher than those in the low‐risk group. Differentiated immune pathways were primarily enriched in the IFN response, immune checkpoint and T‐cell co‐stimulation pathways. In conclusion, we established a risk model based on cuproptosis‐related lncRNAs showing excellent prognostic prediction ability but also indicating the immuno‐microenvironment status of glioma.     

Identification of a novel glycolysis-related gene signature that can predict the survival of patients with lung adenocarcinoma

Lung cancer is one of the most malignant cancers worldwide, and lung adenocarcinoma (LUAD) is the most common histologic subtype. Thousands of biomarkers related to the survival and prognosis of patients with this cancer type have been investigated through database mining; however, the prediction effect of a single gene biomarker is not satisfactorily specific or sensitive. Thus, the present study aimed to develop a novel gene signature of prognostic values for patients with LUAD. Using a data-mining method, we performed expression profiling of 1145 mRNAs in large cohorts with LUAD (n = 511) from The Cancer Genome Atlas database. Using the Gene Set Enrichment Analysis, we selected 198 genes related to GLYCOLYSIS, which is the most important enrichment gene set. Moreover, these genes were identified using Cox proportional regression modeling. We established a risk score staging system to predict the outcome of patients with LUAD and subsequently identified four genes (AGRN, AKR1A1, DDIT4, and HMMR) that were closely related to the prognosis of patients with LUAD. The identified genes allowed us to classify patients into the high-risk group (with poor outcome) and low-risk group (with better outcome). Compared with other clinical factors, the risk score has a better performance in predicting the outcome of patients with LUAD, particularly in the early stage of LUAD. In conclusion, we developed a four-gene signature related to glycolysis by utilizing the Cox regression model and a risk staging model for LUAD, which might prove valuable for the clinical management of patients with LUAD.     

基于在线数据库和真实世界样本探讨肺腺癌患者POLE/POLD1突变的临床意义

摘要 目的：POLE和POLD1突变导致DNA聚合酶校对功能丧失可能会影响基因组稳定性并导致突变增加和肿瘤形成。本文结合在线数据库和真实世界样本进一步分析肺腺癌（LUAD）患者POLE和/或 POLD1 突变的临床意义。方法：纳入2021年1月～2021年8月徐州医科大学附属医院肺癌术后组织标本115例,利用二代测序技术（NGS）检测基因突变;从癌症基因组图谱（TCGA）数据库收集肺腺癌数据集,通过Cbioportal在线数据库获得肿瘤突变分布图,通过Cibersort法计算获得样本的免疫相关细胞浸润情况。结果：真实世界样本中POLE/ POLD1突变的比例为7.83%（9/115）。TCGA数据显示POLE/POLD1突变的LUAD患者总生存期（OS）减少（P=0.0359）。然而,携带该突变的患者并发其他基因改变的频率明显增加,尤其是与TP53突变存在正相关;同时,POLE/POLD1突变与LUAD组织浸润性免疫杀伤细胞呈正相关,与免疫抑制细胞呈负相关,提示这部分患者对免疫检查点抑制剂（ICI）敏感。结论：LUAD患者POLE/POLD1突变预示较高的肿瘤突变负荷和免疫微环境改变,可作为ICI疗效预测的潜在生物标志物,值得临床关注。