Prognostic model of lung adenocarcinoma constructed by the CENPA complex genes is closely related to immune infiltration

There is a known link between DNA methylation and cancer immunity/immunotherapy; however, the effect of DNA methylation on immunotherapy in lung adenocarcinoma (LUAD) remains to be elucidated. In the current study, we aimed to screen key markers for prognostic analysis of LUAD based on DNA methylation regulatory factor clustering. We classified LUAD using the NMF clustering method, and as a result, we obtained 20 DNA methylation regulatory genes. These 20 regulatory genes were used to determine the pattern of DNA methylation regulation, and patients were grouped for further analysis. The risk score model was analyzed in the TCGA dataset and an external validation set, and the correlation between the risk score and DNA methylation regulatory gene expression was explored. We analyzed the correlation between the prognostic model and immune infiltration and checkpoints. Finally, we analyzed the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes functions of the prognosis model and established the nomogram model and decision tree model. The survival analyses of ClusterA and ClusterB were significantly different. Survival analysis showed that patients with a high risk score had a poor prognosis. Survival models (tobacco, T, N, M, stage, sex, age, status, and risk score) were abnormally correlated with T cells and macrophages. The higher the risk score associated with smoking was and the higher the stage was, the more severe the LUAD and the more maladjusted the immune system were. Immune infiltration and abnormal expression of immune checkpoint genes in the prognostic model of LUAD were associated with the risk score. The prognostic models were mainly enriched in the cell cycle and DNA replication. Characterization of DNA methylation regulatory patterns is helpful to improve our understanding of the immune microenvironment in LUAD and to guide the development of a more personalized immunotherapy strategy in the future.

Download Full-text

A Six CT83-Related Genes Based Prognostic Signature for Lung Adenocarcinoma

Combinatorial Chemistry & High Throughput Screening ◽

10.2174/1871520621666210713112630 ◽

2021 ◽

Vol 24 ◽

Author(s):

Yongmei Wang ◽

Guimin Zhang ◽

Ruixian Wang

Keyword(s):

Regression Analysis ◽

Lung Adenocarcinoma ◽

Differential Expression ◽

Risk Score ◽

Prognostic Model ◽

Cox Regression ◽

Differential Expression Analysis ◽

Functional Enrichment ◽

Risk Scores ◽

Cox Regression Analysis

Background: This study aims to explore the prognostic values of CT83 and CT83-related genes in lung adenocarcinoma (LUAD). Methods: We downloaded the mRNA profiles of 513 LUAD patients (RNA sequencing data) and 246 NSCLC patients (Affymetrix Human Genome U133 Plus 2.0 Array) from TCGA and GEO databases. According to the median expression of CT83, the TCGA samples were divided into high and low expression groups, and differential expression analysis between them was performed. Functional enrichment analysis of differential expression genes (DEGs) was conducted. Univariate Cox regression analysis and LASSO Cox regression analysis were performed to screen the optimal prognostic DEGs. Then we established the prognostic model. A Nomogram model was constructed to predict the overall survival (OS) probability of LUAD patients. Results: CT83 expression was significantly correlated to the prognosis of LUAD patients. A total of 59 DEGs were identified, and a predictive model was constructed based on six optimal CT83-related DEGs, including CPS1, RHOV, TNNT1, FAM83A, IGF2BP1, and GRIN2A, could effectively predict the prognosis of LUAD patients. The nomogram could reliably predict the OS of LUAD patients. Moreover, the six important immune checkpoints (CTLA4, PD1, IDO1, TDO2, LAG3, and TIGIT) were closely correlated with the Risk Score, which was also differentially expressed between the LUAD samples with high and low-Risk Scores, suggesting that the poor prognosis of LUAD patients with high-Risk Score might be due to the immunosuppressive microenvironments. Conclusion: A prognostic model based on six optimal CT83 related genes could effectively predict the prognosis of LUAD patients.

Download Full-text

Exploration of Tumor Mutation Burden Combined with Immune Infiltrates in the Prognosis of Lung Adenocarcinoma

10.21203/rs.3.rs-219997/v1 ◽

2021 ◽

Author(s):

Zhenyu Zhao ◽

Boxue He ◽

Qidong Cai ◽

Pengfei Zhang ◽

Xiong Peng ◽

...

Keyword(s):

High Risk ◽

Lung Adenocarcinoma ◽

Clinical Application ◽

Risk Group ◽

High Risk Group ◽

Immune Microenvironment ◽

Tumor Mutation Burden ◽

Immune Signature ◽

Immune Infiltration ◽

Mutation Burden

Abstract Background: Lung adenocarcinoma (LUAD) accounts for a majority of cancer-related deaths worldwide annually. A recent study shows that immunotherapy is an effective method of LUAD treatment, and tumor mutation burden (TMB) was associated with the immune microenvironment and affected the immunotherapy. Exploration of the gene signature associated with tumor mutation burden and immune infiltrates in predicting prognosis in lung adenocarcinoma in this study, we explored the correlation of TMB with immune infiltration and prognosis in LUAD.Materials and Methods: In this study, we firstly got mutation data and LUAD RNA-Seq data of the LUAD from The Cancer Genome Atlas (TCGA), and according to the TMB we divided the patients into high/low-TMB levels groups. The gene ontology (GO) pathway enrichment analysis and KOBAS-Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways analysis were utilized to explore the molecular function of the differentially expressed genes (DEGs) between the two groups. The function enrichment analyses of DEGs were related to the immune pathways. Then, the ESTIMATE algorithm, CIBERSORT, and ssGSEA analysis were utilized to identify the relationship between TMB subgroups and immune infiltration. According to the results, Venn analysis was utilized to select the immune-related genes in DEGs. Univariate and Lasso Cox proportional hazards regression analyses were performed to construct the signature which positively associated with the immune infiltration and affected the survival. Finally, we verified the correlation between the signature and immune infiltration. Result: The exploration of the immune infiltration suggested that high-TMB subgroups positively associated with the high level of immune infiltration in LUAD patients. According to the TMB-related immune signature, the patients were divided into High/Low-risk groups, and the high-risk group was positively associated with poor prognostic. The results of the PCA analysis confirmed the validity of the signature. We also verified the effectiveness of the signature in GSE30219 and GSE72094 datasets. The ROC curves and C-index suggested the good clinical application of the TMB-related immune signature in LUAD prognosis. Another result suggested that the patients of the high-risk group were positively associated with higher TMB levels, PD-L1expression, and immune infiltration levels.Conclusion: In conclusion, our signature provides potential biomarkers for studying aspects of the TMB in LUAD such as TMB affected immune microenvironment and prognosis. This signature may provide some biomarkers which could improve the biomarkers of PD-L1 immunotherapy response and were inverted for the clinical application of the TMB in LUAD. LUAD male patients with higher TMB-levels and risk scores may benefit from immunotherapy. The high-risk patients along with higher PD-L1 expression of the signature may suitable for immunotherapy and improve their survival by detecting the TMB of LUAD.

Download Full-text

Identification and Validation of Immune-Related LncRNA Prognostic Signature for Lung Adenocarcinoma

Frontiers in Genetics ◽

10.3389/fgene.2021.681277 ◽

2021 ◽

Vol 12 ◽

Author(s):

Guomin Wu ◽

Qihao Wang ◽

Ting Zhu ◽

Linhai Fu ◽

Zhupeng Li ◽

...

Keyword(s):

Regression Analysis ◽

Lung Adenocarcinoma ◽

Clinical Features ◽

Cox Regression ◽

Differential Expression Analysis ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Prognostic Signature ◽

Cox Regression Analysis ◽

Immune Infiltration

This study aimed to establish a prognostic risk model for lung adenocarcinoma (LUAD). We firstly divided 535 LUAD samples in TCGA-LUAD into high-, medium-, and low-immune infiltration groups by consensus clustering analysis according to immunological competence assessment by single-sample gene set enrichment analysis (ssGSEA). Profile of long non-coding RNAs (lncRNAs) in normal samples and LUAD samples in TCGA was used for a differential expression analysis in the high- and low-immune infiltration groups. A total of 1,570 immune-related differential lncRNAs in LUAD were obtained by intersecting the above results. Afterward, univariate COX regression analysis and multivariate stepwise COX regression analysis were conducted to screen prognosis-related lncRNAs, and an eight-immune-related-lncRNA prognostic signature was finally acquired (AL365181.2, AC012213.4, DRAIC, MRGPRG-AS1, AP002478.1, AC092168.2, FAM30A, and LINC02412). Kaplan–Meier analysis and ROC analysis indicated that the eight-lncRNA-based model was accurate to predict the prognosis of LUAD patients. Simultaneously, univariate COX regression analysis and multivariate COX regression analysis were undertaken on clinical features and risk scores. It was illustrated that the risk score was a prognostic factor independent from clinical features. Moreover, immune data of LUAD in the TIMER database were analyzed. The eight-immune-related-lncRNA prognostic signature was related to the infiltration of B cells, CD4+ T cells, and dendritic cells. GSEA enrichment analysis revealed significant differences in high- and low-risk groups in pathways like pentose phosphate pathway, ubiquitin mediated proteolysis, and P53 signaling pathway. This study helps to treat LUAD patients and explore molecules related to LUAD immune infiltration to deeply understand the specific mechanism.

Download Full-text

EGFR DNA Methylation Correlates With EGFR Expression, Immune Cell Infiltration, and Overall Survival in Lung Adenocarcinoma

Frontiers in Oncology ◽

10.3389/fonc.2021.691915 ◽

2021 ◽

Vol 11 ◽

Author(s):

Zhanyu Xu ◽

Fanglu Qin ◽

Liqiang Yuan ◽

Jiangbo Wei ◽

Yu Sun ◽

...

Keyword(s):

Dna Methylation ◽

Protein Expression ◽

Lung Adenocarcinoma ◽

Methylation Level ◽

Promoter Region ◽

Body Region ◽

Gene Body ◽

Immune Infiltration ◽

Cpg Sites ◽

Gene Body Region

BackgroundThe epidermal growth factor receptor (EGFR) is a primary target of molecular targeted therapy for lung adenocarcinoma (LUAD). The mechanisms that lead to epigenetic abnormalities of EGFR in LUAD are still unclear. The purpose of our study was to evaluate the abnormal methylation of EGFR CpG sites as potential biomarkers for LUAD.MethodsTo assess the differentially methylation CpG sites of EGFR in LUAD, we used an integrative study of Illumina HumanMethylation450K and RNA-seq data from The Cancer Genome Atlas (TCGA). We evaluated and compared EGFR multiple-omics data to explore the role of CpG sites located in EGFR promoter regions and gene body regions and the association with transcripts, protein expression levels, mutations, and somatic copy number variation. We calculated the correlation coefficients between CpG sites of EGFR and immune infiltration fraction (by MCPcounter and ESTIMATE) and immune-related pathways in LUAD. Finally, we validated the differential methylation of clinically and prognostically relevant CpG sites using quantitative methylation-specific PCR (qMSP).ResultsWe found that the methylation level of many EGFR CpGs in the promoter region was negatively correlated with the transcription level, protein expression, and SCNV, while the methylation at the gene body region was positively correlated with these features. The methylation level of EGFR CpGs in the promoter region was positively correlated with the level of immune infiltration and IFN-γ signature, while the opposite was found for methylation of the gene body region. The qMSP results showed that cg02316066 had a high methylation level, while cg02166842 had a low methylation level in LUAD. There was a high degree of co-methylation between cg02316066 and cg03046247.ConclusionOur data indicate that EGFR is an epigenetic regulator in LUAD acting through DNA methylation. Our research provides a theoretical basis for the further detection of EGFR DNA methylation as a predictive biomarker for LUAD survival and immunotherapy.

Download Full-text

Identification of prognostic gene signature associated with microenvironment of lung adenocarcinoma

PeerJ ◽

10.7717/peerj.8128 ◽

2019 ◽

Vol 7 ◽

pp. e8128 ◽

Cited By ~ 12

Author(s):

Cheng Yue ◽

Hongtao Ma ◽

Yubai Zhou

Keyword(s):

High Risk ◽

Lung Adenocarcinoma ◽

Prognostic Model ◽

Cox Regression ◽

Risk Group ◽

Expression Profiles ◽

Gene Signature ◽

Low Risk ◽

Differentially Expressed ◽

Lasso Regression

Background Lung cancer has the highest morbidity and mortality worldwide, and lung adenocarcinoma (LADC) is the most common pathological subtype. Accumulating evidence suggests the tumor microenvironment (TME) is correlated with the tumor progress and the patient’s outcome. As the major components of TME, the tumor-infiltrated immune cells and stromal cells have attracted more and more attention. In this study, differentially expressed immune and stromal signature genes were used to construct a TME-related prognostic model for predicting the outcomes of LADC patients. Methods The expression profiles of LADC samples with clinical information were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). The differentially expressed genes (DEGs) related to the TME of LADC were identified using TCGA dataset by Wilcoxon rank sum test. The prognostic effects of TME-related DEGs were analyzed using univariate Cox regression. Then, the least absolute shrinkage and selection operator (LASSO) regression was performed to reduce the overfit and the number of genes for further analysis. Next, the prognostic model was constructed by step multivariate Cox regression and risk score of each sample was calculated. Then, survival and Receiver Operating Characteristic (ROC) analyses were conducted to validate the model using TCGA and GEO datasets, respectively. The Kyoto Encyclopedia of Genes and Genomes analysis of gene signature was performed using Gene Set Enrichment Analysis (GSEA). Finally, the overall immune status, tumor purity and the expression profiles of HLA genes of high- and low-risk samples was further analyzed to reveal the potential mechanisms of prognostic effects of the model. Results A total of 93 TME-related DEGs were identified, of which 23 DEGs were up-regulated and 70 DEGs were down-regulated. The univariate cox analysis indicated that 23 DEGs has the prognostic effects, the hazard ratio ranged from 0.65 to 1.25 (p < 0.05). Then, seven genes were screened out from the 23 DEGs by LASSO regression method and were further analyzed by step multivariate Cox regression. Finally, a three-gene (ADAM12, Bruton Tyrosine Kinase (BTK), ERG) signature was constructed, and ADAM12, BTK can be used as independent prognostic factors. The three-gene signature well stratified the LADC patients in both training (TCGA) and testing (GEO) datasets as high-risk and low-risk groups, the 3-year area under curve (AUC) of ROC curves of three GEO sets were 0.718 (GSE3141), 0.646 (GSE30219) and 0.643 (GSE50081). The GSEA analysis indicated that highly expressed ADAM12, BTK, ERG mainly correlated with the activation of pathways involving in focal adhesion, immune regulation. The immune analysis indicated that the low-risk group has more immune activities and higher expression of HLA genes than that of the high-risk group. In sum, we identified and constructed a three TME-related DEGs signature, which could be used to predict the prognosis of LADC patients.

Download Full-text

CDKN2A or CDKN2B homozygous deletion with high-immune infiltration as a favorable prognostic factor for lung adenocarcinoma.

Journal of Clinical Oncology ◽

10.1200/jco.2021.39.15_suppl.e20543 ◽

2021 ◽

Vol 39 (15_suppl) ◽

pp. e20543-e20543

Author(s):

Benxu Tan ◽

Yonghong Chen ◽

Lei Xia ◽

Xian Yu ◽

Yusheng Huang ◽

...

Keyword(s):

Prognostic Factor ◽

Lung Adenocarcinoma ◽

Homozygous Deletion ◽

Hazard Ratio ◽

Gene Set Enrichment Analysis ◽

Rank Test ◽

Immune Infiltration ◽

Log Rank Test ◽

Significant Difference ◽

Wild Group

e20543 Background: CDKN2A and CDKN2B both acted as tumor suppressor genes by regulating the cell cycle, which in humans were located at chromosome 9, band p21.3. The frequencies of homozygous deletion (HomDel) in CDKN2A and CDKN2B in lung adenocarcinoma (LUAD) were 12.5% and 12.1%, respectively. However, the genomic, immunogenomic features and impact on the prognosis of LUAD patients with CDKN2A/B HomDel were still unclear. Methods: The cohort of this study was from The Cancer Genome Atlas (TCGA). A total of 508 LUAD patients, including 99 CDKN2A/B HomDel (homdel) and 509 CDKN2A/B wild (wild). This study explored the difference of genomic and immunogenomic landscape between homdel and wild by analysis of whole-exome sequencing (WES) and RNA sequencing data. Results: The most frequently mutated genes were TP53, TTN, MUC16, and CSMD3. Their frequencies in homdel and wild are 46% and 48%, 43% and 46%, 35% and 41%, 33% and 38%, respectively. There was no significant difference of tumor mutational burden (TMB) between homdel and wild (median TMB, 133 in homdel vs 177 in wild; Wilcoxon test, p = 0.11), and clinical characteristics including age, gender, smoking history, and tumor stage were not significantly different between homdel and wild. Homdel had a shorter overall survival (OS) than wild (Log-rank test, p = 0.04, Hazard Ratio: 0.7, 95% CI: 0.49-1.02), but there was no significant difference in progression-free survival (PFS) (Log-rank test, p = 0.05, Hazard Ratio: 0.73, 95% CI: 0.51-1.04). We used single sample gene set enrichment analysis (ssGSEA) to calculate the enrichment score (ES) of 25 immune-related pathways such as antigen presentation and T cell-mediated immunity, and then used the consensus clustering algorithm (ConsensusClusterPlus) to cluster homdel and wild respectively, and both clustered into low and high immune infiltration groups. For the high immune infiltration and low immune infiltration in homdel and wild, high immune infiltration had a longer OS (Log-rank test, p = 0.009, Hazard Ratio: 2.19, 95% CI: 1.22-3.94) and PFS (Log-rank test, p = 0.044, Hazard Ratio: 1.8, 95% CI: 1.01-3.2) than low immune infiltration in homdel. However, there was no significant heterogeneity between high and immune infiltration in terms of PFS (Log-rank test, p = 0.28, Hazard Ratio: 1.21, 95% CI: 0.87-1.68) and OS (Log-rank test, p = 0.96, Hazard Ratio: 1.01, 95% CI: 0.71-1.44) in the wild group, the wild group had longer OS than homdel group with low immune infiltration (Log-rank test, p = 0.003, Hazard Ratio: 0.5, 95% CI: 0.29-0.88), while had the same OS with homdel with high immune infiltration, irrespective of immune infiltration. And so was PFS (Log-rank test, p = 0.005, Hazard Ratio: 0.48, 95% CI: 0.27-0.82). Conclusions: CDKN2A/B homdel was an unfavorable prognostic factor for LUAD, but which with high immune infiltration might improve patient survival time.

Download Full-text

ERO1L shapes the immune-suppressive tumor microenvironment and is a potential biomarker for immunotherapy response in lung adenocarcinoma.

Journal of Clinical Oncology ◽

10.1200/jco.2021.39.15_suppl.e21006 ◽

2021 ◽

Vol 39 (15_suppl) ◽

pp. e21006-e21006

Author(s):

Lihui Liu ◽

Chao Wang ◽

Sini Li ◽

Pei Xue ◽

Hua Bai ◽

...

Keyword(s):

T Cells ◽

Endoplasmic Reticulum ◽

Lung Adenocarcinoma ◽

Signaling Pathways ◽

Survival Data ◽

Checkpoint Inhibitors ◽

Q Value ◽

Immune Infiltration ◽

Potential Biomarker

e21006 Background: Recently, immune checkpoint inhibitors have led to a paradigm shift in treatment for patients with lung adenocarcinoma (LUAD), however, the identification of biomarkers to enable patient selection is urgently required. The endoplasmic reticulum oxidoreductin-1-like ( ERO1L) gene encodes an endoplasmic reticulum luminal localized glycoprotein known to associated with hypoxia. The role of ERO1L in the crafting of the tumor immune microenvironment (TIME) is yet to be elucidated. Methods: In this study, raw datasets (including RNA-seq, methylation, sgRNA-seq, phenotype, and survival data) were obtained from public databases. This data was analyzed and used to explore the biological landscape of ERO1L in immune infiltration. Expression data was used to characterize samples. Using gene signatures and cell quantification, stromal and immune infiltration was determined. These findings were used to predict sensitivity to immunotherapy. Results: We identified ERO1L to be an oncogene, the mRNA expression of which is significantly higher in LUAD compared with normal tissues. High expression levels of ERO1L were associated with poor prognoses in terms of overall survival (HR: 1.52, 95% CI: 1.27-1.82) and progression-free survival (HR: 1.93, 95% CI: 1.47-2.53). This overexpression was found to be a result of hypomethylation of the ERO1L promoter. Overexpression of ERO1L resulted in an immune-suppressive TIME via the recruitment of immune-suppressive cells including regulatory T cells (Spearman’s ρ = 0.199, p < 0.001) cancer associated fibroblasts (ρ = 0.286, p < 0.001), and myeloid-derived suppressor cells (ρ = 0.423, p < 0.001), and also indicated the polarization of M1-type to M2-type macrophage. On the contrary, overexpression of ERO1L was closely associated with deficiency of immune-active cells including B cells (ρ = -0.250, p < 0.001), CD8+ T cells (ρ = -0.299, p < 0.001), and NK cells (ρ = -0.258, p < 0.001). Using the Tumor Immune Dysfunction and Exclusion (TIDE) framework, it was identified that patients in the ERO1Lhigh group possessed a significantly lower response rate (31.0%) to immunotherapy compared with the ERO1Llow group (86.0%). Mechanistic analysis revealed that overexpression of ERO1L was associated with the upregulation of JAK-STAT (NES = 1.65, FDR q-value = 0.0) and NF-κB (NES = 2.03, FDR q-value = 0.0) signaling pathways, thus affecting chemokine and cytokine patterns in the TIME. Conclusions: Our study provides clear insight into the potential role of ERO1L in tumor immunology. Overexpression of ERO1L was indicative of a hypoxia-induced immune-suppressive TIME, which was shown to confer resistance to immunotherapy in patients with LUAD. ERO1L was shown to mediate cytokine and chemokine patterns in the TIME, which were resulted from activations of JAK-STAT and NF-κB signaling pathways.

Download Full-text