Infiltration In Lung Adenocarcinoma Research Articles

DEP domain containing 1 as a biomarker for poor prognosis in lung adenocarcinoma

ObjectiveThe DEP domain-containing 1 (DEPDC1) gene is essential in the development and advancement of different types of cancer. This study is to examine the levels of DEPDC1 in lung adenocarcinoma (LUAD), and to determine its relationship with clinical results and immune response. The goal is to assess its potential as a biomarker and therapeutic target for LUAD. MethodsBy comprehensively utilizing the Cancer Genome Atlas (TCGA), gene Expression Synthesis (GEO), UALCAN, cBioPortal, TISIDB databases and online platforms, we conducted a bioinformatics analysis to investigate DEPDC1 gene survival analysis, prognostic diagnosis, prognostic survival, immune cell infiltration, DNA methylation, and the correlation of genetic mutations in LUAD. The results were validated through cell assay and immunohistochemical staining. ResultsDEPDC1 shows high levels of expression in the majority of tumors, with its expression being notably elevated in LUAD compablue to normal tissues. The expression of DEPDC1 varies based on the clinical characteristics of patients with LUAD. DEPDC1 expression affects the survival prognosis and prognostic model construction of LUAD patients. In addition, the presence of DEPDC1 is linked to immune infiltration. Various chemokines and chemokine receptors, immunoinhibitors and immune-stimulators in LUAD are significantly correlated with DEPDC1 methylation levels. Cell experiments confirmed through qPCR that the mRNA expression of DEPDC1 in LUAD was markedly elevated in comparison to the normal population, and immunohistochemistry showed positive DEPDC1 expression in LUAD pathological sections. ConclusionSystematic analysis and experiments have verified that DEPDC1 serves as a biomarker for detecting early, prediction of survival, and evaluation of immune cell infiltration in LUAD.

Low Expression MCEMP1 Promoting Lung Adenocarcinoma Progression by and its Clinical Value.

Lung cancer is a highly prevalent tumor with a lack of biological markers that reflect its progression. Mast cell surface membrane protein 1 (MCEMP1, also known as C19ORF59) has not been reported in lung adenocarcinoma (LUAD). We aimed to investigate the role of MCEMP1 in LUAD. MCEMP1 expression in LUAD was analyzed using The Cancer Genome Atlas (TCGA) data, and conducted univariate and multivariate Cox regression analyses to evaluate the prognostic significance of MCEMP1 expression in TCGA. Tumor Immune Estimation Resource (TIMER) was used for examining the correlation between MCEMP1 expression and immune cell infiltration in LUAD. Furthermore, proliferation, migration, invasion, and colony-forming ability were investigated using LUAD cell lines. MCEMP1 had low expression in LUAD patient tissues and was correlated with lymph node metastasis, differentiation level, and tumor status. The Area under Curve (AUC) value of MCEMP1 for the Receiver Operating Characteristic (ROC) curve analysis was 0.984. The immune infiltration analysis revealed a correlation between MCEMP1 expression and the extent of macrophages and neutrophil infiltration in LUAD. Additionally, MCEMP1 has low expression in clinical samples, MCEMP1 overexpressed in LUAD cells substantially reduced cell growth, migration, and invasion of malignant cells. Low expression MCEMP1 promotes LUAD progression, which provides new insights and a potential biological target for future LUAD therapies.

Prognostic effect of TCF1+ CD8+ T cell and TOX+ CD8+ T cell infiltration in lung adenocarcinoma.

Recent studies have highlighted the pivotal roles of T cell transcription factors TCF-1 and TOX in modulating the immune response in cancer, with TCF-1 maintaining CD8+ T cell stemness and TOX promoting T cell exhaustion. The prognostic significance of these factors in lung adenocarcinoma (LUAD) remains a critical area of investigation. The retrospective study included 191 patients with LUAD who underwent surgery, of whom 83% were in stages II and III. These patients were divided into exploratory (n = 135) and validation (n = 56) groups based on the time of diagnosis. Multiplex fluorescence immunohistochemistry was used to examine the infiltration levels of CD8+ T cells, TCF1+ CD8+ T cells, and TOX+ CD8+ T cells. The percentage of CD8+ T cells in tumor was markedly lower than that in stroma (p < 0.05). In tumor-draining lymph nodes (TDLNs) invaded by tumor, the proportion of stem-like TCF1+ CD8+ T cells was significantly decreased (p < 0.01). Importantly, higher infiltration levels of CD8+ T cells and TCF1+ CD8+ T cells were associated with improved disease-free survival (DFS) (p = 0.009 and p = 0.006, respectively) and overall survival (OS) (p = 0.018 and p = 0.010, respectively). This study underscores the potential of TCF1+ CD8+ T cells as prognostic biomarkers in LUAD, providing insights into the tumor immune microenvironment and guiding future therapeutic strategies.

Identification of immune-associated biomarker for predicting lung adenocarcinoma: bioinformatics analysis and experiment verification of PTK6

BackgroundAbnormal expression of protein tyrosine kinase 6 (PTK6) has been proven to be involved in the development of gynecological tumors. However, its immune-related carcinogenic mechanism in other tumors remains unclear.ObjectiveThe aim of this study was to identify PTK6 as a novel prognostic biomarker in pan-cancer, especially in lung adenocarcinoma (LUAD), which is correlated with immune infiltration, and to clarify its clinicopathological and prognostic significance.MethodsThe prognostic value and immune relevance of PTK6 were investigated by using bio-informatics in this study. PTK6 expression was validated in vitro experiments (lung cancer cell lines PC9, NCI-H1975, and HCC827; human normal lung epithelial cells BEAS-2B). Western blot (WB) revealed the PTK6 protein expression in lung cancer cell lines. PTK6 expression was inhibited by Tilfrinib. Colony formation and the Cell Counting Kit-8 (CCK-8) assay were used to detect cell proliferation. The wound healing and trans-well were performed to analyze the cell migration capacity. Then flow cytometry was conducted to evaluate the cell apoptosis. Eventually, the relationship between PTK6 and immune checkpoints was examined. WB was used to estimate the PD-L1 expression at different Tilfrinib doses.ResultsPTK6 was an independent predictive factor for LUAD and was substantially expressed in LUAD. Pathological stage was significantly correlated with increased PTK6 expression. In accordance with survival analysis, poor survival rate in LUAD was associated with a high expression level of PTK6. Functional enrichment of the cell cycle and TGF-β signaling pathway was demonstrated by KEGG and GSEA analysis. Moreover, PTK6 expression considerably associated with immune infiltration in LUAD, as determined by immune analysis. Thus, the result of vitro experiments indicated that cell proliferation and migration were inhibited by the elimination of PTK6. Additionally, PTK6 suppression induced cell apoptosis. Obviously, PD-L1 protein expression level up-regulated while PTK6 was suppressed.ConclusionPTK6 has predictive value for LUAD prognosis, and could up regulated PD-L1.

Mitochondrial ribosomal protein S24 is associated with immunosuppressive microenvironment and cold tumor in lung adenocarcinoma

ObjectiveMRPS24 (Mitochondrial Ribosomal Protein S24) belongs to the mitochondrial ribosomal protein family, which participates in the protein synthesis of the mitochondrion. However, the relationship of MRPS24 with lung adenocarcinoma (LUAD) remained unknown. We aimed to identify its immunological and functional mechanisms in LUAD. MethodsThe analysis of MRPS24 expression, clinical features, diagnosis, prognosis, function analysis, genetic alteration, copy number variations, methylation, and tumor microenvironment was investigated by the TCGA, UCSC Xena, GEO, HPA, GEPIA, cBioPortal, MethSurv, TIMER, TIMER2.0, and TISIDB databases. ResultsMRPS24 was found to be more abundant in LUAD tumor tissue than in normal tissue. High levels of MRPS24 expression were found to be an independent prognostic factor by multivariate analysis. Functional analysis revealed that MRPS24 expression was associated with the immune, cell cycle and methylation. MRPS24 methylation level was inversely linked with its expression (p < 0.001). Patients with low MRPS24 methylation had a worse prognosis than those with high methylation (p < 0.05). In addition, the result revealed that the MRPS24 expression was inversely linked to the immune cell infiltration in LUAD. Finally, the validations of the expression level, prognosis, and immune cell infiltration of MRPS24 were in accordance with our previous results. ConclusionsThis study systematically explored that MRPS24 expression was significantly correlated with prognosis, tumorigenesis, genetic alteration, copy number variations, methylation, and immune cell infiltration in LUAD. MRPS24 might be a potential immune-related biomarker in the development and treatment of LUAD, thereby acting as a promising predictor of immunotherapy response in LUAD.

Accurate categorization and rapid pathological diagnosis correction with Micro-Raman technique in human lung adenocarcinoma infiltration level.

In the context of surgical interventions for lung adenocarcinoma (LADC), precise determination of the extent of LADC infiltration plays a pivotal role in shaping the surgeon's strategic approach to the procedure. The prevailing diagnostic standard involves the expeditious intraoperative pathological diagnosis of areas infiltrated by LADC. Nevertheless, current methodologies rely on the visual interpretation of tissue images by proficient pathologists, introducing an error margin of up to 15.6%. In this study, we investigated the utilization of Micro-Raman technique on isolated specimens of human LADC with the objective of formulating and validating a workflow for the pathological diagnosis of LADC featuring diverse degrees of infiltration. Our strategy encompasses a thorough pathological characterization of LADC, spanning different tissue types and levels of infiltration. Through the integration of Raman spectroscopy with advanced deep learning models for simultaneous diagnosis, this approach offers a swift, precise, and clinically relevant means of analysis. The diagnostic performance of the convolutional neural network (CNN) model, coupled with the microscopic Raman technique, was found to be exceptional and consistent, surpassing the traditional support vector machine (SVM) model. The CNN model exhibited an area under the curve (AUC) value of 96.1% for effectively distinguishing normal tissue from LADC and an impressive 99.0% for discerning varying degrees of infiltration in LADCs. To comprehensively assess its clinical utility, Raman datasets from patients with intraoperative rapid pathologic diagnostic errors were utilized as test subjects and input into the established CNN model. The results underscored the substantial corrective capacity of the Micro-Raman technique, revealing a misdiagnosis correction rate exceeding 96% in all cases. Ultimately, our discoveries highlight the Micro-Raman technique's potential to augment the intraoperative diagnostic precision of LADC with varying levels of infiltration. And compared to the traditional SVM model, the CNN model has better generalization ability in diagnosing different infiltration levels. This method furnishes surgeons with an objective groundwork for making well-informed decisions concerning subsequent surgical plans.

Identification of CNKSR1 as a biomarker for “cold” tumor microenvironment in lung adenocarcinoma: An integrative analysis based on a novel workflow

BackgroundTherapies targeting PD1/PD-L1 pathway have revolutionized the treatment of lung cancer. However, anti-PD1/PD-L1 therapies have proven beneficial for only a select group of lung adenocarcinoma (LUAD) patients and generally do not work for immuno-cold tumors characterized by a lack of immune cell infiltration. Identifying novel biomarkers is vital to broad therapeutic options for LUAD patients with no response to anti-PD1/PD-L1 immunotherapies. MethodsOur study has developed a novel strategy to identify a promising biomarker that addresses the limitations of anti-PD1/PD-L1 immunotherapy in treating immunological cold tumors. We exacted LUAD RNA-seq data from the Cancer Genome Atlas database (TCGA). Using several machine learning methods, we identified the candidate biomarker. Based on the expression level of PD-L1 and the identified biomarker, samples were categorized into four groups. We further used ESTIMATE, ssGSEA, and CIBERSORT algorithms to calculate the immune infiltration level of each group. The results were validated in three independent bulk datasets and one scRNA-seq dataset. Immunohistochemistry (IHC) assessments were performed in clinical samples to further evaluate the coexpression of CNKSR1 and PD-L1, and to compare CD8 + T cell infiltration among groups. ResultsAfter comprehensive analyses, CNKSR1 was identified as a novel promising biomarker for immuno-cold LUAD. CNKSR1 mRNA expression levels exhibited a negative correlation with both PD-L1 mRNA expression and the extent of immune cell infiltration in LUAD. Besides, in contrast to the significant association between the expression of PD-L1 and the majority of other well-established or widely studied immune checkpoint molecules, a mutually exclusive expression pattern is observed between CNKSR1 and these molecules. The aforementioned results were consistent in validation datasets. The prognostic model built based on the CNKSR1 coexpression module also showed robust predictive performance. Additionally, IHC assessments have confirmed that the coexpression of CNKSR1 and PD-L1 is rare in LUAD samples. Notably, LUADs in the high-CNKSR1 group, characterized by high CNKSR1 but low PD- L1 expression, demonstrated reduced infiltration of CD8+ T cells. ConclusionsIn summary, CNKSR1 emerges as a promising biomarker for immune-cold LUADs, and the study into CNKSR1 modulating T-cell infiltration may lead to the identification of compensatory molecules to enhance the effectiveness of current immunotherapy for LUAD.

Identification of a prognosis-related gene signature and ceRNA regulatory networks in lung adenocarcinoma

The ceRNA network, consisting of both noncoding RNA and protein-coding RNA, governs the occurrence, progression, metastasis, and infiltration of lung adenocarcinoma. Signatures comprising multiple genes can effectively determine survival stratification and prognosis of patients with lung adenocarcinoma. To explore the mechanisms of lung adenocarcinoma progression and identify potential biological targets, we carried out systematic bioinformatics analyses of the genetic profiles of lung adenocarcinoma, such as weighted gene co-expression network analysis (WGCNA), differential expression (DE) assessment, univariate and multivariate Cox proportional hazard regression models, ceRNA modulatory networks generated using the ENCORI and miRcode databases, nomogram models, ROC curve assessment, and Kaplan-Meier survival curve analysis. The ceRNA network encompassed 37 nodes, comprising 12 mRNAs, 22 lncRNAs, and three miRNAs. Simultaneously, we performed integration analysis using the 12 genes from the ceRNA network. Our findings revealed that the signature established by these 12 genes serves as an adverse element in lung adenocarcinoma, contributing to unfavorable patient prognosis. To ensure the credibility of our results, we used in vitro experiments for further verification. In conclusion, our study delved into the potential mechanisms underlying lung adenocarcinoma via the ceRNA regulatory network, specifically focusing on the PIF1 and has-miR-125a-5p axis. Additionally, a signature comprising 12 genes was identified as a biomarker related to the prognosis of lung adenocarcinoma.

Identification and Verification of Metabolism-related Immunotherapy Features and Prognosis in Lung Adenocarcinoma.

Lung cancer is a frequent malignancy with a poor prognosis. Extensive metabolic alterations are involved in carcinogenesis and could, therefore, serve as a reliable prognostic phenotype. Our study aimed to develop a prognosis signature and explore the relationship between metabolic characteristic-related signature and immune infiltration in lung adenocarcinoma (LUAD). TCGA-LUAD and GSE31210 datasets were used as a training set and a validation set, respectively. A total of 513 LUAD samples collected from The Cancer Genome Atlas database (TCGA-LUAD) were used as a training dataset. Molecular subtypes were classified by consensus clustering, and prognostic genes related to metabolism were analyzed based on Differentially Expressed Genes (DEGs), Protein-Protein Interaction (PPI) network, the univariate/multivariate- and Lasso- Cox regression analysis. Two molecular subtypes with significant survival differences were divided by the metabolism gene sets. The DEGs between the two subtypes were identified by integrated analysis and then used to develop an 8-gene signature (TTK, TOP2A, KIF15, DLGAP5, PLK1, PTTG1, ECT2, and ANLN) for predicting LUAD prognosis. Overexpression of the 8 genes was significantly correlated with worse prognostic outcomes. RiskScore was an independent factor that could divide LUAD patients into low- and high-risk groups. Specifically, high-risk patients had poorer prognoses and higher immune escape. The Receiver Operating Characteristic (ROC) curve showed strong performance of the RiskScore model in estimating 1-, 3- and 5-year survival in both training and validation sets. Finally, an optimized nomogram model was developed and contributed the most to the prognostic prediction in LUAD. The current model could help effectively identify high-risk patients and suggest the most effective drug and treatment candidates for patients with LUAD.

Potential association of HSPD1 with dysregulations in ribosome biogenesis and immune cell infiltration in lung adenocarcinoma: An integrated bioinformatic approach.

Lung adenocarcinoma (LUAD) is a major histological subtype of lung cancer with a high mortality rate worldwide. Heat shock protein family D member 1 (HSPD1, also known as HSP60) is reported to be increased in tumor tissues of lung cancer patients compared with healthy control tissues. We aimed to investigate the roles of HSPD1 in prognosis, carcinogenesis, and immune infiltration in LUAD using an integrative bioinformatic analysis. HSPD1 expression in LUAD was investigated in several transcriptome-based and protein databases. Survival analysis was performed using the KM plotter and OSluca databases, while prognostic significance was independently confirmed through univariate and multivariate analyses. Integrative gene interaction network and enrichment analyses of HSPD1-correlated genes were performed to investigate the roles of HSPD1 in LUAD carcinogenesis. TIMER and TISIDB were used to analyze correlation between HSPD1 expression and immune cell infiltration. The mRNA and protein expressions of HSPD1 were higher in LUAD compared with normal tissues. High HSPD1 expression was associated with male gender and LUAD with advanced stages. High HSPD1 expression was an independent prognostic factor associated with poor survival in LUAD patients. HSPD1-correlated genes with prognostic impact were mainly involved in aberrant ribosome biogenesis, while LUAD patients with high HSPD1 expression had low tumor infiltrations of activated and immature B cells and CD4+ T cells. HSPD1 may play a role in the regulation of ribosome biogenesis and B cell-mediated immunity in LUAD. It could serve as a predictive biomarker for prognosis and immunotherapy response in LUAD.

CCND2 is a prognostic biomarker and correlates with immune infiltration in lung adenocarcinoma.

CCND2 expression influences the growth and proliferation of cancer cells and plays a crucial role in immune response of tumor. However, few studies focused on the correlation between CCND2 and lung adenocarcinoma (LUAD) in terms of prognosis and tumor immune infiltration. Original LUAD case data were screened from The Cancer Genome Atlas (TCGA) database. Using R software, we analyzed differently expressed CCND2 between LUAD and adjacent normal tissues. Kaplan-Meier analysis was conducted to determine the relationship between CCND2 expression and the overall survival of LUAD patients, and Cox regression analysis was performed to identify the independently prognostic risk factors for LUAD. Using TIMER (Tumor Immune Estimation Resource) and CIBERSORTx (Cell-type Identification by Estimating Relative Subsets of known RNA Transcripts) databases, the connection between CCND2 expression and LUAD immune infiltration was investigated. The level of CCND2 was significantly lower in LUAD than in adjacent normal tissues [adjusted P<0.05 and log2 fold change (FC) =-1.33]. LUAD patients who expressed lower CCND2 had a shorter overall survival (P=0.046) and CCND2 was an independently prognostic risk factor for LUAD [hazard ratio (HR): 0.77, P=0.049]. In LUAD patients, CCND2 expression was positively associated with the levels of B cells (r=0.159, P=4.00e-04), CD8+ T cells (r=0.287, P=7.88e-11), CD4+ T cells (r=0.301, P=8.14e-12), macrophages (r=0.128, P=4.57e-03), neutrophils (r=0.373, P=1.07e-17), and myeloid dendritic cells (r=0.284, P=1.43e-10). The levels of B cells and macrophages had significantly association with the overall survival of LUAD patients. CIBERSORTx showed that the proportions of naive B cells, resting dendritic cells, and macrophages M1 were higher in the low CCND2 expression group (P<0.05); whereas macrophages M1, activated natural killer (NK) cells, and resting CD4+ memory cells were lower (P<0.05). CCND2 can be exploited as a novel prognostic biomarker involved in immune infiltration of LUAD, hence providing new preventative and therapeutic options for LUAD.

PERP May Affect the Prognosis of Lung Adenocarcinoma by Inhibiting Apoptosis.

PERP, a member of the peripheral myelin protein gene family, is a new therapeutic target in cancer. The relationships between PERP and immune cell infiltration in lung cancer have not been studied. Therefore, the role of PERP in the tumour microenvironment (TME) of lung cancer needs to be further explored. In this study, we explored the association between PERP expression and clinical characteristics by analysing data from the TCGA database. Cox regression and Kaplan‒Meier methods were used to investigate the relationship between the expression of PERP and overall survival in patients with lung adenocarcinoma (LUAD). The relationship between PERP expression and the degree of infiltration of specific immune cell subsets in LUAD was evaluated using the TIMER database and GEPIA. We also performed GO enrichment analysis and KEGG enrichment analysis to reveal genes coexpressed with PERP using the Coexpedia database. Finally, we verified the expression and function of PERP in LUAD tissues and the A549 cell line by RT‒PCR, Western blot, CCK-8, IHC, and wound healing assays. The mouse model was used to study the in vivo effects of PERP. According to our results, PERP expression was significantly higher in LUAD tissues and associated with the clinical characteristics of the disease. Survival was independently associated with PERP in LUAD patients. We further verified that PERP might regulate B-cell infiltration in LUAD to affect the prognosis of LUAD. To identify PERP-related signalling pathways in LUAD, we performed a genome-aggregation analysis (GSEA) between low and high PERP expression datasets. LUAD cells express higher levels of PERP than paracarcinoma cells, and PERP inhibits the proliferation and metastasis of A549 cells through apoptosis. PERP may affect the prognosis of lung adenocarcinoma by inhibiting apoptosis and is associated with immune cell infiltration.

A novel disulfidptosis-related prognostic gene signature and experimental validation identify ACTN4 as a novel therapeutic target in lung adenocarcinoma.

Lung adenocarcinoma (LUAD) is a prevalent form of malignancy globally. Disulfidptosis is novel programmed cell death pathway based on disulfide proteins, may have a positive impact on the development of LUAD treatment strategies. To investigate the impact of disulfidptosis-related genes (DRGs) on the prognosis of LUAD, developed a risk model to facilitate the diagnosis and prognostication of patients. We also explored ACTN4 (DRGs) as a new therapeutic biomarker for LUAD. We investigated the expression patterns of DRGs in both LUAD and noncancerous tissues. To assess the prognostic value of the DRGs, we developed risk models through univariate Cox analysis and lasso regression. The expression and function of ACTN4 was evaluated by qRT-PCR, immunohistochemistry and in vitro experiments. The TIMER examined the association between ACTN4 expression and immune infiltration in LUAD. Ten differentially expressed DRGs were identified. And ACTN4 was identified as potential risk factors through univariate Cox regression analysis (P< 0.05). ACTN4 expression and riskscore were used to construct a risk model to predict overall survival in LUAD, and high-risk demonstrated a significantly higher mortality rate compared to the low-risk cohort. qRT-PCR and immunohistochemistry assays indicated ACTN4 was upregulated in LUAD, and the upregulation was associated with clinicopathologic features. In vitro experiments showed the knockdown of ACTN4 expression inhibited the proliferation in LUAD cells. The TIMER analysis demonstrated a correlation between the expression of ACTN4 and the infiltration of diverse immune cells. Elevated ACTN4 expression was associated with a reduction in memory B cell count. Additionally, the ACTN4 expression was associated with m6A modification genes. Our study introduced a prognostic model based on DRGs, which could forecast the prognosis of patients with LUAD. The biomarker ACTN4 exhibits promise for the diagnosis and management of LUAD, given its correlation with tumor immune infiltration and m6A modification.

Overexpression of SPP1 is a prognostic indicator of immune infiltration in lung adenocarcinoma.

The extracellular phosphoprotein, secreted phosphoprotein 1 (SPP1), plays a crucial role in various tumors and regulating the immune system. This study aimed to evaluate its prognostic value and relationship to immune infiltration in lung adenocarcinoma (LUAD). In the TCGA and GEO datasets, the information on clinic and transcriptome analysis of SPP1 in non-small-cell lung cancer (NSCLC) was examined accordingly. The association of SPP1 expression with overall survival and clinicopathologic characteristics was investigated by univariate and multivariate analysis. CancerSEA database was utilized to investigate the role of SPP1 at the cellular level by single-cell analysis. Additionally, the CIBERSORT algorithm was utilized to assess the correlation among the immune cells that infiltrated. NSCLC tissues exhibited a notable rise in SPP1 expression compared with that of normal tissues. Furthermore, the overexpression of SPP1 was substantially associated with clinicopathological features and unfavorable survival outcomes in individuals with LUAD, whereas no such correlation was observed in lung squamous cell carcinoma. Immune cells that infiltrate tumors and their corresponding genes were associated with SPP1 expression levels in LUAD. SPP1 is a reliable indicator for assessing LUAD immune infiltration status and prognosis. With this approach, SPP1 can help earlier LUAD diagnosis and act as a possible immunotherapy target.

SLC7A8 overexpression inhibits the growth and metastasis of lung adenocarcinoma and is correlated with a dismal prognosis.

Overexpression of solute carrier family 7 member 8 (SLC7A8) has been shown to relate to the survival time and tumor progression in cancer patients. However, the role of SLC7A8 in lung adenocarcinoma (LUAD) is still obscure. The relationships between SLC7A8 expression in LUAD tissues and clinical values as well as immune infiltration were explored through bioinformatics. The functions and pathways of SLC7A8 in LUAD were investigated using Kyoto Encyclopedia of Genes and Genomes enrichment analysis, Gene Set Enrichment Analysis, Western blotting, and other methods. We found that the expression of SLC7A8 was decreased significantly in LUAD tissues compared with normal tissues, which was related to the dismal survival time and disease progression. Moreover, it carried diagnostic value in LUAD and was a risk factor for dismal prognosis. Receiver operating characteristic curve analysis indicated that the expression level of SLC7A8 carried significant diagnostic value in LUAD. Overexpression of SLC7A8 inhibited the proliferation, invasion, and migration of LUAD cells, likely through a mechanism involving the cell cycle. SLC7A8 expression in LUAD was significantly correlated with the infiltration of immune cells, especially B cells, interstitial dendritic cells, mast cells, CD56 bright cells, natural killer cells, plasmacytoid dendritic cells, T follicular helper cells, T helper 2 and 17 cells, and immune factors. The downregulation of SLC7A8 was related to a dismal prognosis and immune cell infiltration in LUAD. Increasing the expression of SLC7A8 inhibited the growth and migration of LUAD cells, thereby improving the prognosis of patients.

G6PD is a prognostic biomarker correlated with immune infiltrates in lung adenocarcinoma and pulmonary arterial hypertension.

Lung adenocarcinoma (LUAD) with Pulmonary arterial hypertension (PAH) shows a poor prognosis. Detecting related genes is imperative for prognosis prediction. The gene expression profiles of LUAD and PAH were acquired from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) database, respectively. The co-expression modules associated with LUAD and PAH were evaluated using the Weighted Gene Co-Expression Network Analysis (WGCNA). The relationship between key gene expression with immune-cell infiltration and the tumor immune microenvironment (TIME) was evaluated. We confirmed the mRNA and protein levels in vivo and vitro. G6PD knockdown was used to conduct the colony formation assay, transwell invasion assay, and scratch wound assay of A549 cells. EDU staining and CCK8 assay were performed on G6PD knockdown HPASMCs. We identified therapeutic drug molecules and performed molecular docking between the key gene and small drug molecules. Three major modules and 52 overlapped genes were recognized in LUAD and PAH. We identified the key gene G6PD, which was significantly upregulated in LUAD and PAH. In addition, we discovered a significant difference in infiltration for most immune cells between high- and low-G6PD expression groups. The mRNA and protein expressions of G6PD were significantly upregulated in LUAD and PAH. G6PD knockdown decreased proliferation, cloning, and migration of A549 cells and cell proliferation in HPASMCs. We screened five potential drug molecules against G6PD and targeted glutaraldehyde by molecular docking. This study reveals that G6PD is an immune-related biomarker and a possible therapeutic target for LUAD and PAH patients.

FSTL3 is associated with prognosis and immune cell infiltration in lung adenocarcinoma

PurposeFSTL3 expression is altered in various types of cancer. However, the role and mechanism of action of FSTL3 in lung adenocarcinoma development and tumor immunity are unknown. We investigated the association between FSTL3 expression and clinical characteristics and immune cell infiltration in lung adenocarcinoma samples from The Cancer Genome Atlas (TCGA) and a separate validation set from our hospital.MethodsData on immune system infiltration, gene expression, and relevant clinical information were obtained by analyzing lung adenocarcinoma sample data from TCGA database. Using online tools like GEPIA, the correlations between FSTL3 expression and prognosis, clinical stage, survival status, and tumor-infiltrating immune cells were examined. In a validation dataset, immunohistochemistry was performed to analyze FSTL3 expression and its related clinical characteristics.ResultsFSTL3 expression was markedly reduced in patients with lung adenocarcinoma. N stage, pathological stage, and overall survival were significantly correlated with FSTL3 expression. According to GSEA, FSTL3 is strongly linked to signaling pathways such as DNA replication and those involved in cell cycle regulation. Examination of TCGA database and TIMER online revealed a correlation between FSTL3 and B cell, T cell, NK cell, and neutrophil levels. The prognosis of patients with lung adenocarcinoma was significantly affected by six genes (KRT6A, VEGFC, KRT14, KRT17, SNORA12, and KRT81) related to FSTL3.ConclusionFSTL3 is significantly associated with the prognosis and progression of lung adenocarcinoma and the infiltration of immune cells. Thus, targeting FSTL3 and its associated genes in immunotherapy could be potentially beneficial for the treatment of lung adenocarcinoma.

Identification and validation of a 4-extracellular matrix gene signature associated with prognosis and immune infiltration in lung adenocarcinoma

BackgroundThe extracellular matrix (ECM) plays a crucial role in the development and tumor microenvironment of lung adenocarcinoma (LUAD). This study aimed to establish a risk score of ECM-related genes in LUAD and explore the association between the risk score and patient survival as well as immune cell infiltration, somatic mutations, and therapy response. MethodsGene expression data from The Cancer Genome Atlas (TGCA) and eight Gene Expression Omnibus (GEO) databases were used to analyze and identify differentially expressed genes (DEGs). Prognostic ECM-related genes were identified and utilized to formulate a prognostic signature. A nomogram was constructed using TCGA dataset and validated in two GEO datasets. Differences between high- and low-risk patients were analyzed for function enrichment, immune cell infiltration, somatic mutations, and therapy response. Finally, Quantitative real-time PCR (qRT-PCR) was used to detect the mRNA expression of DEGs in LUAD. ResultsA risk score based on four ECM-related genes, ANOS1, CD36, COL11A1, and HMMR, was identified as an independent prognostic factor for overall survival (OS) compared to other clinical variables. Subsequently, a nomogram incorporating the risk score and TNM staging was developed using the TCGA dataset. Internal and external validation of the nomogram, conducted through calibration plots, C-index, time-dependent receiver operating characteristics (ROC), integrated discrimination improvement (IDI), and decision curve analyses (DCA), demonstrated the excellent discriminatory ability and clinical practicability of this nomogram. The risk score correlated with the distribution of function enrichment, immune cell infiltration, and immune checkpoint expression. More somatic mutations occurred in the high-risk group. The risk score also demonstrated a favorable ability to predict immunotherapy response and drug sensitivity. ConclusionA novel signature based on four ECM-related genes is developed to help predict LUAD prognosis. This signature correlates with tumor immune microenvironment and can predict the response to different therapies in LUAD patients.

Comprehensive analysis of prognostic value and immune infiltration of Regulator of Chromosome Condensation 2 in lung adenocarcinoma.

Background: Lung adenocarcinoma (LUAD) incidence and mortality take the leading place of most malignancies. Previous studies have revealed the regulator of chromosome condensation 1 (RCC1) family members played an essential role during tumorigenesis. However, its biological functions in LUAD still need further investigation. Methods: Several databases were applied to explore potential effects of RCC1 family members on LUAD, such as Oncomine, GEPIA, and cBioPortal. Real-time PCR and immunohistochemistry were used to verify the expression of RCC2 in stage I LUAD. H1975 and A549 were selected to explore the biological function of RCC2 in cellular malignant phenotype. Results: The expressions of RCC1 and RCC2 showed marked differences in malignant tissue compared to lung tissue. The higher the expression levels of RCC1 or RCC2 in LUAD patients, the shorter their overall survival (OS). In normal lung tissues, RCC1 expression was highly enriched in alveolar cells and endothelial cells. Compare with RCC1, RCC2 expression in normal lung tissue was significantly enriched in macrophages, B cells and granulocytes. Additionally, RCC2 expression level was correlated with multiple immune cell infiltration in LUAD. Moreover, the mutation or different sCNA status of RCC2 exerted influence on multiple immune cell infiltration distribution. We found that the upregulation of RCC1 and RCC2 were obviously related to TP53 mutation. GSEA analysis revealed that RCC2 was involved in the process of DNA replication, nucleotide excision repair and cell cycle, which might affect tumor progression through P53 signaling pathway. We further elucidated that downregulation of RCC2 could dramatically repress the migration and invasion of LUAD cells. Conclusions: The study demonstrated that RCC1 and RCC2 expression were markedly increased in early-stage of LUAD. Patients with high expression of RCC1 or RCC2 had a worse prognosis. Based on our analysis, RCC1 and RCC2 might exert influence on LUAD process through DNA replication, nucleotide excision repair and cell cycle, as well as cells migration and invasion. Different from RCC1, RCC2 also involved in immune infiltration. These analyses provided a novel insight into the identification of diagnostic biomarker.

Neutrophil infiltration associated genes on the prognosis and tumor immune microenvironment of lung adenocarcinoma.

The neutrophils exhibit both anti-tumor and pro-tumor effects in cancers. The correlation between neutrophils and tumor development in lung adenocarcinoma (LUAD) is still uncertain, possibly due to a lack of specific neutrophil infiltration evaluation methods. In this study, we identified 30 hub genes that were significantly associated with neutrophil infiltration in LUAD through data mining, survival analysis, and multiple tumor-infiltrating immune cells (TICs) analysis, including TIMER, CIBERSORT, QUANTISEQ, XCELL, and MCPCOUNTER. Consensus clustering analysis showed that these 30 hub genes were correlated with clinical features in LUAD. We further developed a neutrophil scoring system based on these hub genes. The neutrophil score was significantly correlated with prognosis and tumor immune microenvironment (TIME) in LUAD. It was also positively associated with PD-L1 expression and negatively associated with tumor mutational burden (TMB). When combined with the neutrophil score, the predictive capacity of PD-L1 and TMB for prognosis was significantly improved. Thus, the 30 hub genes might play an essential role in the interaction of neutrophils and LUAD, and the neutrophil scoring system might effectually assess the infiltration of neutrophils. Furthermore, we verified the expression of these 30 genes in the LUAD tumor tissues collected from our department. We further found that overexpressed TNFAIP6 and TLR6 and downregulated P2RY13, SCARF1, DPEP2, PRAM1, CYP27A1, CFP, GPX3, and NCF1 in LUAD tissue might be potentially associated with neutrophils pro-tumor effects. The following in vitro experiments demonstrated that TNFAIP6 and TLR6 were significantly overexpressed, and P2RY13 and CYP27A1 were significantly downregulated in LUAD cell lines, compared to BEAS-2B cells. Knocking down TNFAIP6 in A549 and PC9 resulted in the upregulation of FAS, CCL3, and ICAM-1, and the downregulation of CCL2, CXCR4, and VEGF-A in neutrophils when co-culturing with the conditioned medium (CM) from LUAD cells. Knocking down TNFAIP6 in LUAD also led to an elevated early apoptosis rate of neutrophils. Therefore, overexpressed TNFAIP6 in LUAD cancer cells might lead to neutrophils "N2" polarization, which exhibited pro-tumor effects. Further research based on the genes identified in this pilot study might shed light on neutrophils' effects on LUAD in the future.