The novel circ_0028171/miR-218-5p/IKBKB axis promotes osteosarcoma cancer progression

LncRNA HOXA-AS3 promotes cell proliferation and invasion via targeting miR-218-5p/FOXP1 axis in osteosarcoma

Osteosarcoma is an aggressive form of bone cancer and affects the health in children and adolescents. Although conventional treatment improves the osteosarcoma survival, some patients have metastasis and drug resistance, leading to a worse prognosis. Therefore, it is necessary to explore the molecular mechanism of osteosarcoma occurrence and progression, which could discover the novel treatment for osteosarcoma. Long noncoding RNAs (lncRNAs) have been reported to regulate osteosarcoma occurrence and malignant progression. LncRNA HOXA-AS3 facilitates the tumorigenesis and progression in a variety of human cancers. However, the underlying mechanism of lncRNA HOXA-AS3-induced oncogenesis is poorly determined in osteosarcoma. To address this point, we utilized several cellular biological strategies and molecular approaches to explore the biological functions and mechanisms of lncRNA HOXA-AS3 in osteosarcoma cells. We found that lncRNA HOXA-AS3 facilitates cell proliferation and invasion via targeting miR-218-5p/FOXP1 axis in osteosarcoma. In conclusion, lncRNA HOXA-AS3 could be a promising target for osteosarcoma treatment.

Osteosarcoma in a ceRNET perspective

Osteosarcoma (OS) is the most prevalent and fatal type of bone tumor. It is characterized by great heterogeneity of genomic aberrations, mutated genes, and cell types contribution, making therapy and patients management particularly challenging. A unifying picture of molecular mechanisms underlying the disease could help to transform those challenges into opportunities.This review deeply explores the occurrence in OS of large-scale RNA regulatory networks, denominated "competing endogenous RNA network" (ceRNET), wherein different RNA biotypes, such as long non-coding RNAs, circular RNAs and mRNAs can functionally interact each other by competitively binding to shared microRNAs. Here, we discuss how the unbalancing of any network component can derail the entire circuit, driving OS onset and progression by impacting on cell proliferation, migration, invasion, tumor growth and metastasis, and even chemotherapeutic resistance, as distilled from many studies. Intriguingly, the aberrant expression of the networks components in OS cells can be triggered also by the surroundings, through cytokines and vesicles, with their bioactive cargo of proteins and non-coding RNAs, highlighting the relevance of tumor microenvironment. A comprehensive picture of RNA regulatory networks underlying OS could pave the way for the development of innovative RNA-targeted and RNA-based therapies and new diagnostic tools, also in the perspective of precision oncology.

Osteosarcoma neutrophil extracellular trap network-associated gene recurrence and metastasis model

Osteosarcoma (OS) is the most common malignancy in children and adolescents and has a high probability of recurrence and metastasis. A growing number of studies have shown that neutrophil extracellular traps (NETs) are strongly associated with cancer metastasis, but in osteosarcoma, genes associated with NETs that promote osteosarcoma recurrence and metastasis remain to be explored. We systematically investigated the gene expression patterns of NETs in OS samples from the GEO database. NETs molecular typing was evaluated based on NETs expression profiles, and the association between NETs molecular subtypes and immune microenvironment and metastatic features were explored. Ultimately, we constructed a signature model and column line graph associated with metastasis prediction and screened possible potential drugs for metastatic osteosarcoma. We established two different molecular subtypes of NETs, which showed significant differences in metastatic status, metastasis time, tumor immune microenvironment, and biological effects. We also constructed a NETs-related gene metastasis signature(NRGMS) to assess the expression pattern of NETs in patients to predict metastatic recurrence in osteosarcoma patients. We screened for TOMM40 and FH associated with metastatic recurrence in osteosarcoma patients. Overall, this study constructs a predictive model for osteosarcoma metastasis of NETs-related genes, which is expected to provide new insights into the metastasis of osteosarcoma.

CircECE1 promotes osteosarcoma progression through regulating RAB3D by sponging miR-588

BACKGROUND

Circular RNAs (circRNAs) have been confirmed to be involved in cancer pathogenesis. However, the underlying mechanism of circRNA endothelin converting enzyme 1 (circECE1) in osteosarcoma (OS) development is still not understood.

METHODS

The expression levels of circECE1, microRNA-588 (miR-588) and RAB3D, member RAS oncogene family (RAB3D) were gauged by quantitative real-time polymerase chain reaction (qRT-PCR) and western blot. OS cell proliferation was assessed by cell counting kit-8 (CCK-8) assay and 5-ethynyl-2'-deoxyuridine (EdU) assay. OS cell apoptosis rate and metastasis were identified by flow cytometry and transwell assay. Dual-luciferase reporter analysis and RNA immunoprecipitation (RIP) assay were performed to confirm the interactions among circECE1, miR-588 and RAB3D. Xenograft tumor models were established to explore circECE1 function in vivo. Immunohistochemistry (IHC) assay was applied to analyze RAB3D level after circECE1 knockdown.

RESULTS

In OS, circECE1 expression was higher than that in normal chondroma tissues. High levels of circECE1 were positively linked to OS cell viability, proliferation, migration and invasion, and negatively linked to OS cell apoptosis rate. It was found that circECE1 was a miR-588 sponge, and miR-588 inhibitor abrogated the influence of si-circECE1 on OS cells. MiR-588 targeted RAB3D to further regulate the pathological process of OS. Moreover, silencing circECE1 blocked OS tumor growth in vivo.

CONCLUSION

We elucidated the function of a novel circECE1/miR-588/RAB3D axis in OS progression.

Biological and therapeutic viewpoints towards role of miR-218 in human cancers: Revisiting molecular interactions and future clinical translations

Understanding the exact pathogenesis of cancer is difficult due to heterogenous nature of tumor cells and multiple factors that cause its initiation and development. Treatment of cancer is mainly based on surgical resection, chemotherapy, radiotherapy and their combination, while gene therapy has been emerged as a new kind of therapy for cancer. Post-transcriptional regulation of genes has been of interest in recent years and among various types of epigenetic factors that can modulate gene expression, short non-coding RNAs known as microRNAs (miRNAs) have obtained much attention. The stability of mRNA decreases by miRNAs to repress gene expression. miRNAs can regulate tumor malignancy and biological behavior of cancer cells and understanding their function in tumorigenesis can pave the way towards developing new therapeutics in future. One of the new emerging miRNAs in cancer therapy is miR-218 that increasing evidence highlights its anti-cancer activity, while a few studies demonstrate its oncogenic function. The miR-218 transfection is promising in reducing progression of tumor cells. miR-218 shows interactions with molecular mechanisms including apoptosis, autophagy, glycolysis and EMT, and the interaction is different. miR-218 induces apoptosis, while it suppresses glycolysis, cytoprotective autophagy and EMT. Low expression of miR-218 can result in development of chemoresistance and radio-resistance in tumor cells and direct targeting of miR-218 as a key player is promising in cancer therapy. LncRNAs and circRNAs are nonprotein coding transcripts that can regulate miR-218 expression in human cancers. Moreover, low expression level of miR-218 can be observed in human cancers such as brain, gastrointestinal and urological cancers that mediate poor prognosis and low survival rate.

Comprehensive analysis of a glycolysis and cholesterol synthesis-related genes signature for predicting prognosis and immune landscape in osteosarcoma

Background

Glycolysis and cholesterol synthesis are crucial in cancer metabolic reprogramming. The aim of this study was to identify a glycolysis and cholesterol synthesis-related genes (GCSRGs) signature for effective prognostic assessments of osteosarcoma patients.

Methods

Gene expression data and clinical information were obtained from GSE21257 and TARGET-OS datasets. Consistent clustering method was used to identify the GCSRGs-related subtypes. Univariate Cox regression and LASSO Cox regression analyses were used to construct the GCSRGs signature. The ssGSEA method was used to analyze the differences in immune cells infiltration. The pRRophetic R package was utilized to assess the drug sensitivity of different groups. Western blotting, cell viability assay, scratch assay and Transwell assay were used to perform cytological validation.

Results

Through bioinformatics analysis, patients diagnosed with osteosarcoma were classified into one of 4 subtypes (quiescent, glycolysis, cholesterol, and mixed subtypes), which differed significantly in terms of prognosis and tumor microenvironment. Weighted gene co-expression network analysis revealed that the modules strongly correlated with glycolysis and cholesterol synthesis were the midnight blue and the yellow modules, respectively. Both univariate and LASSO Cox regression analyses were conducted on screened module genes to identify 5 GCSRGs (RPS28, MCAM, EN1, TRAM2, and VEGFA) constituting a prognostic signature for osteosarcoma patients. The signature was an effective prognostic predictor, independent of clinical characteristics, as verified further via Kaplan-Meier analysis, ROC curve analysis, univariate and multivariate Cox regression analysis. Additionally, GCSRGs signature had strong correlation with drug sensitivity, immune checkpoints and immune cells infiltration. In cytological experiments, we selected TRAM2 as a representative gene to validate the validity of GCSRGs signature, which found that TRAM2 promoted the progression of osteosarcoma cells. Finally, at the pan-cancer level, TRAM2 had been correlated with overall survival, progression free survival, disease specific survival, tumor mutational burden, microsatellite instability, immune checkpoints and immune cells infiltration.

Conclusion

Therefore, we constructed a GCSRGs signature that efficiently predicted osteosarcoma patient prognosis and guided therapy.

Multi-Omics Immune Interaction Networks in Lung Cancer Tumorigenesis, Proliferation, and Survival

There are currently no effective biomarkers for prognosis and optimal treatment selection to improve non-small cell lung cancer (NSCLC) survival outcomes. This study further validated a seven-gene panel for diagnosis and prognosis of NSCLC using RNA sequencing and proteomic profiles of patient tumors. Within the seven-gene panel, ZNF71 expression combined with dendritic cell activities defined NSCLC patient subgroups (n = 966) with distinct survival outcomes (p = 0.04, Kaplan-Meier analysis). ZNF71 expression was significantly associated with the activities of natural killer cells (p = 0.014) and natural killer T cells (p = 0.003) in NSCLC patient tumors (n = 1016) using Chi-squared tests. Overexpression of ZNF71 resulted in decreased expression of multiple components of the intracellular intrinsic and innate immune systems, including dsRNA and dsDNA sensors. Multi-omics networks of ZNF71 and the intracellular intrinsic and innate immune systems were computed as relevant to NSCLC tumorigenesis, proliferation, and survival using patient clinical information and in-vitro CRISPR-Cas9/RNAi screening data. From these networks, pan-sensitive and pan-resistant genes to 21 NCCN-recommended drugs for treating NSCLC were selected. Based on the gene associations with patient survival and in-vitro CRISPR-Cas9, RNAi, and drug screening data, MEK1/2 inhibitors PD-198306 and U-0126, VEGFR inhibitor ZM-306416, and IGF-1R inhibitor PQ-401 were discovered as potential targeted therapy that may also induce an immune response for treating NSCLC.

Apoptosis-Associated Gene Expression Profiling Is One New Prognosis Risk Predictor of Human Rectal Cancer

Background. Prior research has revealed the predictive significance of a series of genetic markers in the prognosis of rectal cancer (RC), but the roles of apoptosis-associated genes in RC are rarely studied. Methods. The RNA-seq data as well as clinical data about patients with rectum adenocarcinoma (READ) were downloaded from The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) project. Additionally, 87 apoptosis-associated genes were downloaded and acquired from Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Comprehensive bioinformatics analysis was carried out for deep exploration of the expression and prognostic significance of these genes. Least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analysis was performed for the establishment of a risk scoring equation for the prognosis model and construction of a survival prognosis model. ROC curves were drawn for evaluating the accuracy of the model. A real-time quantitative PCR assay was conducted for quantification of apoptosis-associated proteins related to prognosis. Results. Eight genes were identified as hub genes associated with the prognosis of PFS. A risk model of prognosis prediction based on four gene signatures (CYCS, IKBKB, NFKB1, and TRADD) was constructed. According to further analysis of this model, the high-risk group experienced worse overall survival than the other. The prognosis model demonstrated a favorable predictive ability, with areas under the receiver operating characteristic curves (AUC) of 0.720, 0.641, and 0.677 in forecasting the 1-, 2-, and 3-year prognosis, respectively. In addition, CYCS and NFKB1 presented low expression, while IKBKB and TRADD presented high expression in TCGA and clinical tumor samples. Conclusions. A four-gene signature risk model for prognosis forecasting of RC has been constructed, which possesses favorable predictive ability, which offers ideas and breakthrough points to the apoptosis-associated development of RC.

Identification of key serum biomarkers for the diagnosis and metastatic prediction of osteosarcoma by analysis of immune cell infiltration

Background

The role of circular RNAs (circRNAs) and microRNAs (miRNAs) in osteosarcoma (OS) development has not been fully elucidated. Further, the contribution of the immune response to OS progression is not well defined. However, it is known that circRNAs and miRNAs can serve as biomarkers for the diagnosis, prognosis, and therapy of many cancers. Thus, the aim of this study was to identify novel key serum biomarkers for the diagnosis and metastatic prediction of OS by analysis of immune cell infiltration and associated RNA molecules.

Methods

Human OS differentially expressed circRNAs (DEcircRNAs), differentially expressed miRNAs (DEmiRNAs), and differentially expressed mRNAs (DEmRNAs) were identified by analysis of microarray data downloaded from Gene Expression Omnibus (GEO) datasets. Further, characteristic patterns of OS-infiltrating immune cells were analyzed. On this basis, we identified statistically significant transcription factors. Moreover we performed pathway enrichment analysis, constructed protein–protein interaction networks, and devised competitive endogenous RNA (ceRNA) networks. Biological targets of the ceRNA networks were evaluated and potential OS biomarkers confirmed by RT-qPCR analysis of the patients’ serum.

Results

Seven differentially expressed circRNAs, 166 differentially expressed miRNAs, and 175 differentially expressed mRNAs were identified. An evaluation of cellular OS infiltration identified the highest level of infiltration by M0 macrophages, M2 macrophages, and CD8+ T cells, with M0 macrophages and CD8+ T cells as the most prominent. Significant patterns of tumor-infiltrating immune cells were identified by principal component analysis. Moreover, 185 statistically significant transcription factors were associated with OS. Further, in association with immune cell infiltration, hsa-circ-0010220, hsa-miR-326, hsa-miR-338-3p, and FAM98A were identified as potential novel biomarkers for OS diagnosis. Of these, FAM98A had the most promise as a diagnostic marker for OS and OS metastasis. Most importantly, a novel diagnostic model consisting of these four biomarkers (hsa-circ-0010220, hsa-miR-326, hsa-miR-338-3p, and FAM98A) was established with a 0.928 AUC value.

Conclusions

In summary, potential serum biomarkers for OS diagnosis and metastatic prediction were identified based on an analysis of immune cell infiltration. A novel diagnostic model consisting of these four promising serum biomarkers was established. Taken together, the results of this study provide a new perspective by which to understand immunotherapy of OS.

Hsa_circ_0050102 regulates the pancreatic cancer development via miR‐218‐5p/PPME1 axis

Background

Pancreatic cancer (PC) is a malignancy worldwide. Circular RNAs (circRNAs) affects the growth of PC, nonetheless the mechanism is blurry. Here, we reconnoitered the parts of hsa_circ_0050102 in PC.

Methods

Hsa_circ_0050102, microRNA‐218‐5p (miR‐218‐5p) and protein phosphatase methylesterase 1 (PPME1) abundances were indicated by quantitative RT‐PCR or Western blot. Moreover, the cell functions were uncovered. Additionally, the relation of miR‐218‐5p and hsa_circ_0050102 or PPME1 was identified by dual‐luciferase reporter assay. Ultimately, the mice teats were utilized to quantity the part of hsa_circ_0050102.

Results

Hsa_circ_0050102 and PPME1 contents were increased, and the miR‐218‐5p was dwindled in PC. Hsa_circ_0050102 lack subdued cell vitality, colony formation, cell migration and invasion, and angiogenesis, but endorsed cell apoptosis in PC cells. Furthermore, miR‐218‐5p was established to block the development of PC cells via PPME1. Hsa_circ_0050102 bound to miR‐218‐5p to adjust the content of PPME1.

Conclusion

Hsa_circ_0050102 expedited the expansion of PC through growing PPME1 abundance by adjusting miR‐218‐5p.

MicroRNA-376b-3p targets RGS1 mRNA to inhibit proliferation, metastasis, and apoptosis in osteosarcoma

Background

To investigate the role of microRNA-376b-3p (miR-376b-3p) and regulator of G protein signaling 1 (RGS1) in the proliferation, metastasis, and apoptosis of osteosarcoma.

Methods

Differentially expressed genes (DEGs) between tumor and normal tissues from GSE14359 and GSE33382 in the cancer genome atlas (TCGA) dataset were analyzed with GEO2R online. Similarly, differentially expressed miRNAs from GSE70367 were also analyzed with GEO2R. The interaction between the differentially expressed miRNAs and the shared distal metastasis-related DEGs from the two datasets were analyzed using miRWalk and Cytoscape. RGS1 and miR-376-3p were chosen to verify the prediction. RGS1 stably expressing and silencing cells were established based on the MG63 and U2OS cell lines. The targeting of RGS1 with miR-376b-3p was confirmed with Starbase prediction and luciferase reporter assay. Cell proliferation, metastasis, and apoptosis were characterized in vitro and in xenograft mice.

Results

A total of 10 up-regulated and 8 down-regulated DEGs were characterized as shared metastasis-related DEGs for GSE14359 and GSE33382. Among these DEGs, RGS1 was targeted with miR-376b-3p, a predicted down-regulated miRNA in GSE70367. High expression of RGS1 predicted proliferation, invasion, metastases, and poor prognosis in osteosarcoma. Overexpression of RGS1 promoted proliferation, invasion, mobility, and stemness in MG63 and U2OS cells, while silencing of RGS1 had the opposite effect in both cell lines. High expression of RGS1 promoted tumor growth in xenograft nude mice. RGS1 was targeted with miR-376b-3p; the addition of miR-376b-3p down-regulated RGS1, and suppressed cell proliferation, invasion, and metastasis. Meanwhile, sponging of miR-376b-3p had the opposite effect. The suppressive effects of miR-376b-3p could be abolished with RGS1, as cell proliferation, stemness, metastasis, and invasion were all promoted with RGS1 co-transfection in both cell lines.

Conclusions

Our study indicated that RGS1 is a tumor-promoting gene in osteosarcoma, which could be inhibited with miR-376b-3p.

Network propagation-based prioritization of long tail genes in 17 cancer types

BACKGROUND

The diversity of genomic alterations in cancer poses challenges to fully understanding the etiologies of the disease. Recent interest in infrequent mutations, in genes that reside in the "long tail" of the mutational distribution, uncovered new genes with significant implications in cancer development. The study of cancer-relevant genes often requires integrative approaches pooling together multiple types of biological data. Network propagation methods demonstrate high efficacy in achieving this integration. Yet, the majority of these methods focus their assessment on detecting known cancer genes or identifying altered subnetworks. In this paper, we introduce a network propagation approach that entirely focuses on prioritizing long tail genes with potential functional impact on cancer development.

RESULTS

We identify sets of often overlooked, rarely to moderately mutated genes whose biological interactions significantly propel their mutation-frequency-based rank upwards during propagation in 17 cancer types. We call these sets "upward mobility genes" and hypothesize that their significant rank improvement indicates functional importance. We report new cancer-pathway associations based on upward mobility genes that are not previously identified using driver genes alone, validate their role in cancer cell survival in vitro using extensive genome-wide RNAi and CRISPR data repositories, and further conduct in vitro functional screenings resulting in the validation of 18 previously unreported genes.

CONCLUSION

Our analysis extends the spectrum of cancer-relevant genes and identifies novel potential therapeutic targets.

circUSP34 accelerates osteosarcoma malignant progression by sponging miR-16-5p

Osteosarcoma (OS) is a primary and highly malignant mesenchymal tissue tumor. The specific pathological mechanism underlying disease initiation or progression remains unclear. Circular RNAs (circRNAs) are a type of covalently circular RNA with a head-to-tail junction site. In this study, we aimed to investigate the sponging mechanism between circRNAs and microRNAs (miRNAs) in OS. Based on the inhibited effect of miR-16-5p reported on OS, circUSP34 was analyzed as a sponge of miR-16-5p via Starbase. We found that circUSP34 promoted the proliferation, migration, and invasion of OS in vitro and in vivo. circUSP34 increased but miR-16-5p decreased in OS by qRT-PCR. Function assays showed that the malignancy of OS cells, including proliferation, migration, and invasion, was inhibited after knocking out circUSP34. Western blotting results showed that the expression level of vimentin and Ki-67 decreased. Similarly, miR-16-5p mimic compromised the proliferation, migration, and invasion of OS cells. FISH assay results indicated that circUSP34 and miR-16-5p were colocalized in the cytoplasm. The sponging mechanism of circUSP34 and miR-16-5p was verified by dual-luciferase reporter assay, RNA immunoprecipitation (RIP), and RNA pull down assays. Interestingly, the miR-16-5p inhibitor partly reversed the inhibitory effect of sh-circUSP34 on the malignancy of OS cells. Further, mice tumors for IHC indicated that vimentin, N-cadherin, and Ki-67 protein expression decreased, but E-cadherin protein expression increased. Collectively, circUSP34 promoted OS malignancy, including proliferation, migration, and invasion, by sponging miR-16-5p. It can serve as a potential therapeutic target and biomarker.

Identification and Validation of Immune-Related Gene Signature for Predicting Lymph Node Metastasis and Prognosis in Lung Adenocarcinoma

Lung cancer is a serious malignancy, and lung adenocarcinoma (LUAD) is the most common pathological subtype. Immune-related factors play an important role in lymph node metastasis. In this study, we obtained gene expression profile data for LUAD and normal tissues from the TCGA database and analyzed their immune-related genes (IRGs), and observed that 459 IRGs were differentially expressed. Further analysis of the correlation between differentially expressed IRGs and lymph node metastasis revealed 18 lymph node metastasis-associated IRGs. In addition, we analyzed the mutations status, function and pathway enrichment of these IRGs, and regulatory networks established through TF genes. We then identified eight IRGs (IKBKB, LTBR, MIF, PPARD, PPIA, PSME3, S100A6, SEMA4B) as the best predictors by LASSO Logistic analysis and used these IRGs to construct a model to predict lymph node metastasis in patients with LUAD (AUC 0.75; 95% CI: 0.7064-0.7978), and survival analysis showed that the risk score independently affected patient survival. We validated the predictive effect of risk scores on lymph node metastasis and survival using the GEO database as a validation cohort and the results showed good agreement. In addition, the risk score was highly correlated with infiltration of immune cells (mast cells activated, macrophages M2, macrophages M0 and B cells naïve), immune and stromal scores, and immune checkpoint genes (LTBR, CD40LG, EDA2R, and TNFRSF19). We identified key IRGs associated with lymph node metastasis in LUAD and constructed a reliable risk score model, which may provide valuable biomarkers for LUAD patients and further reveal the mechanism of its occurrence.

YY1-modulated long non-coding RNA SNHG12 promotes gastric cancer metastasis by activating the miR-218-5p/YWHAZ axis

Long non-coding RNA (lncRNA) small nucleolar RNA host gene 12 (SNHG12) plays important roles in the pathogenesis and progression of cancers. However, the role of SNHG12 in the metastasis of gastric cancer (GC) has not yet been thoroughly investigated. In the present study, we demonstrated that SNHG12 was upregulated in GC tissues and cell lines. In addition, the expression level of SNHG12 in GC samples was significantly related to tumor invasion depth, TNM stage and lymph node metastasis and was associated with disease-free survival (DFS) and overall survival (OS) in GC patients. In vivo and in vitro assays indicated that SNHG12 promotes GC metastasis and epithelial-mesenchymal transition (EMT). Bioinformatics and mechanistic analyses revealed that SNHG12 can directly target miR-218-5p to regulate YWHAZ mRNA, forming an SNHG12/miR-218-5p/YWHAZ axis and decreasing the ubiquitination of β-catenin. In addition, SNHG12 stabilizes CTNNB1 mRNA by binding with HuR, thus activating the β-catenin signaling pathway. Further analysis also revealed that the transcription factor YY1 negatively modulates SNHG12 transcription. In conclusion, SNHG12 is a potential prognostic marker and therapeutic target for GC. Negatively modulated by YY1, SNHG12 promotes GC metastasis and EMT by regulating the miR-218-5p/YWHAZ axis and stabilizing CTNNB1 via activation of the β-catenin signaling pathway.

Identification and Validation of Immune-Related Gene Signature for Predicting Lymph Node Metastasis and Prognosis in Lung Adenocarcinoma

Lung cancer is a serious malignancy, and lung adenocarcinoma (LUAD) is the most common pathological subtype. Immune-related factors play an important role in lymph node metastasis. In this study, we obtained gene expression profile data for LUAD and normal tissues from the TCGA database and analyzed their immune-related genes (IRGs), and observed that 459 IRGs were differentially expressed. Further analysis of the correlation between differentially expressed IRGs and lymph node metastasis revealed 18 lymph node metastasis-associated IRGs. In addition, we analyzed the mutations status, function and pathway enrichment of these IRGs, and regulatory networks established through TF genes. We then identified eight IRGs (IKBKB, LTBR, MIF, PPARD, PPIA, PSME3, S100A6, SEMA4B) as the best predictors by LASSO Logistic analysis and used these IRGs to construct a model to predict lymph node metastasis in patients with LUAD (AUC 0.75; 95% CI: 0.7064-0.7978), and survival analysis showed that the risk score independently affected patient survival. We validated the predictive effect of risk scores on lymph node metastasis and survival using the GEO database as a validation cohort and the results showed good agreement. In addition, the risk score was highly correlated with infiltration of immune cells (mast cells activated, macrophages M2, macrophages M0 and B cells naïve), immune and stromal scores, and immune checkpoint genes (LTBR, CD40LG, EDA2R, and TNFRSF19). We identified key IRGs associated with lymph node metastasis in LUAD and constructed a reliable risk score model, which may provide valuable biomarkers for LUAD patients and further reveal the mechanism of its occurrence.