Survival Of Lung Adenocarcinoma Patients Research Articles

TMEM173 is a biomarker of predicting prognosis, immune responses and therapeutic effect in human lung adenocarcinoma

The concerns on the function of Transmembrane protein 173 (TMEM173)-dependent innate immunity in prevention and management of cancers has recently been increased. The role of TMEM173 in predicting the prognosis and response to treatment in lung adenocarcinoma (LUAD) remain unclear. Our study revealed that TMEM173 expression was significantly differential in various tumors and the related prognosis was heterogeneous. Further investigation discovered that the expression level of TMEM173 in LUAD tissues was significantly decreased and high TMEM173 expression is associated with better overall survival in LUAD patients. TMEM173 was mainly enriched in immune response-regulating signaling pathway, T cell activation and cell cycle G2/M phase. Furthermore, it was found that TMEM173 expression was positively related to markers and infiltration levels of tumor-infiltrating immune cells. TMEM173 could predict response to targeted therapy, chemotherapy and immunotherapy in LUAD patients. In vitro TMEM173 knockdown decreased the percentage of G2 phase cells, contributing to the increased growth of lung cancer cells. These results implied that TMEM173 might be a prognostic biomarker and a potential target of precision therapy for LUAD patients.

Identification of an immune-related genes signature in lung adenocarcinoma to predict survival and response to immune checkpoint inhibitors

BackgroundAlthough advances in immune checkpoint inhibitor (ICI) research have provided a new treatment approach for lung adenocarcinoma (LUAD) patients, their survival is still unsatisfactory, and there are issues in the era of response prediction to immunotherapy.MethodsUsing bioinformatics methods, a prognostic signature was constructed, and its predictive ability was validated both in the internal and external datasets (GSE68465). We also explored the tumor-infiltrating immune cells, mutation profiles, and immunophenoscore (IPS) in the low-and high-risk groups.ResultsAs far as we are aware, this is the first study which introduces a novel prognostic signature model using BIRC5, CBLC, S100P, SHC3, ANOS1, VIPR1, LGR4, PGC, and IGKV4.1. According to multivariate analysis, the 9-immune-related genes (IRGs) signature provided an independent prognostic factor for the overall survival (OS). The low-risk group had better OS, and the tumor mutation burden (TMB) was significantly lower in this group. Moreover, the risk scores were negatively associated with the tumor-infiltrating immune cells, like CD8+ T cells, macrophages, dendritic cells, and NK cells. In addition, the IPS were significantly higher in the low-risk group as they had higher gene expression of immune checkpoints, suggesting that ICIs could be a promising treatment option for low-risk LUAD patients.ConclusionThe combination of these 9-IRGs not only could efficiently predict overall survival of LUAD patients but also show a powerful association with the expression of immune checkpoints and response to ICIs based on IPS; hoping this model paves the way for better stratification and management of patients in clinical practice.

A nomogram for cancer-specific survival of lung adenocarcinoma patients: A SEER based analysis

BackgroundNon-small cell lung cancer (NSCLC) accounts for 85 % of lung cancer cases. Among NSCLC subtypes, lung adenocarcinoma (LUAD) stands as the most prevalent. Regrettably, LUAD continues to exhibit a notably unfavorable overall prognosis. This study's primary aim was to develop and validate prognostic tools capable of predicting the likelihood of cancer-specific survival (CSS) in patients with LUAD. MethodsWe retrospectively collected 21,099 patients diagnosed with LUAD between 2010 and 2015, and 8290 patients diagnosed between 2004 and 2009 from SEER database. The cohort of 21,099 patients served as the prognostic group for the exploration of LUAD-related prognostic risk factors. The cohort of 8290 patients was designated for external validation. We created a training set and an internal validation set in the prognostic group for the development and internal validation of CSS nomograms. CSS predictors were identified through the least absolute shrinkage and selection operator (Lasso) regression analysis. Prognostic model was constructed via Cox hazard regression analysis, presented in the form of both static and dynamic network-based nomograms. ResultsSeveral independent prognostic factors were incorporated into the construction of nomogram. The nomogram accurately predicted CSS at 1, 3, and 5 years, with respective AUC values of 0.769, 0.761, and 0.748 for the training group, and 0.741, 0.752, and 0.740 for the testing group. The study demonstrated a strong agreement between anticipated and actual CSS values, supported by decision curve analysis (DCA) and time-dependent calibrated curves. High-risk patients based on the nomogram exhibiting significantly lower survival rates compared to their low-risk counterparts according to Kaplan-Meier (K-M) curves. The nomogram demonstrates excellent predictive power in the external validation cohort. ConclusionsA dependable and user-friendly nomogram has been developed, available in both static and online dynamic calculator formats, to facilitate healthcare professionals in accurately estimating the likelihood of CSS for patients diagnosed LUAD.

Significance of novel PANoptosis genes to predict prognosis and therapy effect in the lung adenocarcinoma

Lung adenocarcinoma (LUAD) is the dominant histotype of non-small cell lung cancer. Panoptosis, a comprehensive form of programmed cell death, is central to carcinogenesis. In this study, the expression of PANoptosis-related genes (PRGs) and their impact on the development, prognosis, tumor microenvironment, and treatment response of patients with lung adenocarcinoma (LUAD) were systematically evaluated. PRGs were selected from The Cancer Genome Atlas database and Genecards dataset using differential expression analysis. The signature of included PRGs was identified using univariate Cox regression analysis and LASSO regression analysis. Additionally, a nomogram was developed that includes signature and clinical information. Kaplan–Meier survival analysis and receiver operating characteristic curves were used to assess the predictive validity of these risk models. Finally, functional analysis of the selected PRGs in signature and analysis of immune landscape were also performed. Preliminary identification of 10 genes related to PANoptosis has significant implications for prognosis. Subsequently, seven related genes were integrated to classify LUAD patients into different survival risk groups. The prognostic risk score generated from the signature and the TNM stage were as independent prognostic factors and were utilized in creating a nomogram plot. Both the features and the nomogram plot showed accurate performance in predicting the overall survival of LUAD patients. The PRGs were enriched in several biological functions and pathways, and stratified studies were conducted on the differences in immune landscape between high-risk and low-risk groups based on their characteristics. Ultimately, our evaluation focused on the differences in drug treatment efficacy between the high-risk and low-risk groups, providing a foundation for future research directions. Potential associations between PRGs and patient prognosis in LUAD have been identified in this study. Potential biomarkers for clinical application could be considered for the prognostic predictors identified in this study.

1237P Association of LRRC15 protein expression with 5-year survival in lung adenocarcinoma patients

1237P Association of LRRC15 protein expression with 5-year survival in lung adenocarcinoma patients

Stratification of Lung Adenocarcinoma Patients Based on In Silico and Immunohistochemistry Analyses of Oxidative Stress-Related Genes.

Background: Lung adenocarcinoma (LUAD) remains heterogeneous in the prognosis of patients; oxidative stress (OS) has been widely linked to cancer progression. Therefore, it is necessary to explore the prognostic value of the OS-associated genes in LUAD. Methods: An OS-associated prognostic signature was developed using the Cox regression and random forest model in The Cancer Genome Atlas-LUAD dataset. Kaplan-Meier (K-M) survival curve and time-dependent receiver operating characteristic (tROC) curves were applied to evaluate and validate the predictive accuracy of this signature among the training and testing cohorts. A nomogram was constructed and also verified by the concordance index (C-index), calibration curves, and tROC curves, respectively. ESTIMATE algorithm and CIBERSORT algorithms were conducted to explore the signature's immune characteristics. Core target genes of the prognostic signature were identified in the protein-protein interaction network. Results: A six OS-associated prognostic gene signature (CDC25C, ERO1A, GRIA1, TERT, CAV1, BDNF) was developed. The tROC and K-M survival curves in the training and testing cohorts revealed that the signature had good and robust predictive capability to predict the overall survival of LUAD patients. Meanwhile, the risk score was an independent prognostic factor influencing patients' overall survival. The results of the C-index (0.714), calibration curves, and the 1-, 2-, and 3-year tROC curves (area under the curve = 0.703, 0.737, and 0.723, respectively) suggested that the nomogram had good predictive efficacy and prognostic value for LUAD. Then, the authors found that the high-risk group may be depletion or loss of antitumor function of immune cells. Finally, 10 core genes of the signature were predicted. Conclusion: Their study may provide a novel understanding for the identification of prognostic stratification in LUAD patients, as well as the regulation of OS-associated genes in LUAD progression.

Rab3B enhances the stabilization of DDX6 to promote lung adenocarcinoma aggressiveness

BackgroundLiver kinase B1 (LKB1) is frequently mutated in lung adenocarcinoma, and its loss contributes to tumor progression.MethodsTo identify LKB1 downstream genes that promote lung adenocarcinoma aggressiveness, we performed bioinformatical analysis using publicly available datasets.ResultsRab3B was upregulated in LKB1-depleted lung adenocarcinoma cells and suppressed by LKB1 overexpression. CREB protein was enriched at the promoter of Rab3B in lung cancer cells. Silencing of CREB abrogated the upregulation of Rab3B upon LKB1 loss. Immunohistochemistry revealed the elevated expression of Rab3B in lung adenocarcinomas relative to adjacent normal tissues. Upregulation of Rab3B was significantly associated with lymph node metastasis, advanced tumor stage, and reduced overall survival in lung adenocarcinoma patients. Knockdown of Rab3B suppressed and overexpression of Rab3B promoted the proliferation, colony formation, and migration of lung adenocarcinoma cells in vitro. In a mouse xenograft model, Rab3B depletion restrained and Rab3B overexpression augmented the growth of lung adenocarcinoma tumors. Mechanistically, Rab3B interacted with DDX6 and enhanced its protein stability. Ectopic expression of DDX6 significantly promoted the proliferation, colony formation, and migration of lung adenocarcinoma cells. DDX6 knockdown phenocopied the effects of Rab3B depletion on lung adenocarcinoma cells. Additionally, DDX6 overexpression partially rescued the aggressive phenotype of Rab3B-depleted lung adenocarcinoma cells.ConclusionLKB1 deficiency promotes Rab3B upregulation via a CREB-dependent manner. Rab3B interacts with and stabilizes DDX6 protein to accelerate lung adenocarcinoma progression. The Rab3B-DDX6 axis may be potential therapeutic target for lung adenocarcinoma.

Ferroptosis-related genes DUOX1 and HSD17B11 affect tumor microenvironment and predict overall survival of lung adenocarcinoma patients.

Recent studies have found that ferroptosis-related genes (FRGs) have broad applications in tumor therapy. However, the predictive potential of these genes in lung adenocarcinoma (LUAD) remains to be fully characterized. We aimed to investigate the FRGs that might be potential targets for LUAD. We screened the RNA sequencing samples from LUAD patients from the GEO database and analyzed the ferroptosis-related differentially expressed genes (DEGs). A functional analysis of DEGs was performed. The risk model was constructed to evaluation and validation FRGs. We explored the immune landscape of LUAD and controls. The value of FRGs in diagnosing LUAD was tested in the GSE30219, GSE37745, GSE0081 datasets, and qPCR was used to verify their diagnostic value in LUAD patients in our hospital. A total of 1327 DEGs in quantitative proteomics were obtained, of which ferroptosis-related DEGs were 259. Enrichment analysis showed significant enrichment in the absorption and metabolism of fatty acids and arachidonic acid. The upregulated genes (GCLC, RRM2, AURKA, SLC7A5, and SLC2A1) and downregulated genes (ANGPTL7, ALOX15, ALOX15B, HSD17B11, IL33, TSC22D3, and DUOX1) were selected as core genes in tissue samples from 62 patients by qPCR. DUOX1 and HSD17B11 were obtained by bioinformatics analysis, both of which showed similar expression trends at the RNA and protein levels. The Kaplan-Meier method showed that DUOX1 and HSD17B11 were closely related to the overall survival (OS) of LUAD patients. Ferroptosis-related genes DUOX1 and HSD17B11 are of considerable value in the diagnosis of LUAD patients. Their low expression suggests an increased recurrence rate and leads to a decrease in the patient quality of life.

Characterization of an endoplasmic reticulum stress-associated lncRNA prognostic signature and the tumor-suppressive role of RP11-295G20.2 knockdown in lung adenocarcinoma

Endoplasmic reticulum stress (ERS) is commonly induced by accumulating misfolded or unfolded proteins in tumor microenvironment. Long non-coding RNAs (lncRNAs) play important roles in ERS response and lung adenocarcinoma (LUAD) progression. However, the role of ERS-related lncRNAs in LUAD remains unknown. In this study, we aimed to identify ERS-associated lncRNAs with prognostic value in LUAD and characterize their clinical implications. Cox and least absolute shrinkage and selection operator regression analyses identified nine ERS-related lncRNAs with independent prognostic abilities, including five protective factors (CROCCP2, KIAA0125, LINC0996, RPARP-AS1 and TBX5-AS1) and four risk factors (LINC0857, LINC116, RP11-21L23.2 and RP11-295G20.2). We developed an ERS-related lncRNA risk prediction model in predicting overall survival of LUAD patients, which classified TCGA cohorts into high-risk (HS) and low-risk (LS) groups. Comprehensive bioinformatic analyses revealed HS patients featured with late-stage tumors, greater mutation burdens, weaker anti-tumor immunity/responses, and lower sensitivity to targeted drugs compared to LS patients, contributing to tumor progression and a poor prognosis. Functional enrichment analysis implicated these ERS-related lncRNAs in cell migration, cell death, and immunity. Furthermore, expression of the most significantly upregulated risk lncRNA, RP11-295G20.2, was validated at the mRNA level using clinical LUAD samples. Knockdown of RP11-295G20.2 obviously reduced ERS and suppressed proliferation, invasion, and migration of LUAD cells. This novel ERS-related lncRNA signature provides a new biomarker for prognostic prediction, and ERS-associated RP11-295G20.2 serves as a potential therapeutic target in LUAD.

Major Facilitator Superfamily Domain Containing 12 Is Overexpressed in Lung Cancer and Exhibits an Oncogenic Role in Lung Adenocarcinoma Cells.

Major facilitator superfamily domain containing 12 (MFSD12) regulates lysosomal cysteine import and promotes the proliferation and survival of melanoma cells. However, the expression and function of MFSD12 in other cancers, particularly in lung cancer, remain unclear. The expression of MFSD12 across various types of cancers and corresponding control tissues was examined using TIMER. MFSD12 expression in lung adenocarcinoma (LUAD) and its correlation with distinct clinicopathological features of LUAD patients were analyzed with UALCAN. The correlation between MFSD12 expression and survival of LUAD patients was assessed using the R package, survival, and the relationship between MFSD12 expression and immune infiltration status in LUAD was investigated using CIBERSORT. In addition, MFSD12 expression was knocked down in PC9 LUAD cells and their proliferation, capacity for expansion, cell cycle, apoptosis, and migration/invasion were evaluated through CCK-8 assays, colony formation assays, 7-AAD staining, Annexin V/PI staining, and Transwell assays, respectively. The stemness of these PC9 cells was determined through Western blotting, flow cytometry, and tumor sphere formation assays. MFSD12 mRNA levels were significantly elevated in multiple types of cancers, including LUAD. MFSD12 expression was also positively correlated with cancer stage, nodal metastasis, and infiltration of various immune cells in LUAD, and high MFSD12 levels predicted poor survival among LUAD patients. Knockdown of MFSD12 in PC9 cells resulted in decreased proliferation, attenuated colony formation capacity, cell cycle arrest, elevated apoptosis, impaired migration/invasion, and reduced stemness in PC9 cells. MFSD12 is an oncogene in LUAD.

Knockdown of heat shock protein family D member 1 (HSPD1) in lung cancer cell altered secretome profile and cancer-associated fibroblast induction

The crosstalk between lung cancer cells and cancer-associated fibroblast (CAF) is pivotal in cancer progression. Heat shock protein family D member 1 (HSPD1) is a potential prognostic biomarker associated with the tumor microenvironment in lung adenocarcinoma (LUAD). However, the role of HSPD1 in CAF activation remains unclear. This study established stable HSPD1-knockdown A549 lung cancer cells using a lentivirus-mediated shRNA transduction. A targeted label-free proteomic analysis identified six significantly altered secretory proteins in the shHSPD1-A549 secretome compared to shControl-A549. Functional enrichment analysis highlighted their involvement in cell-to-cell communication and immune responses within the tumor microenvironment. Additionally, most altered proteins exhibited positive correlations and significant prognostic impacts on LUAD patient survival. Investigations on the effects of lung cancer secretomes on lung fibroblast WI-38 cells revealed that the shControl-A549 secretome stimulated fibroblast proliferation, migration, and CAF marker expression. These effects were reversed upon the knockdown of HSPD1 in A549 cells. Altogether, our findings illustrate the role of HSPD1 in mediating CAF induction through secretory proteins, potentially contributing to the progression and aggressiveness of lung cancer.

S100P facilitates LUAD progression via PKA/c-Jun-mediated tumor-associated macrophage recruitment and polarization

S100P, a member of the S100 calcium-binding protein family, is closely associated with abnormal proliferation, invasion, and metastasis of various cancers. However, its role in the lung adenocarcinoma (LUAD) tumor microenvironment (TME) remains unclear. In this study, we observed specific expression of S100P on tumor cells in LUAD patients through tissue immunofluorescence analysis. Furthermore, this expression was strongly correlated with the recruitment and polarization of tumor-associated macrophages (TAMs). Bioinformatics analysis revealed that high S100P expression is associated with poorer overall survival in LUAD patients. Subsequently, a subcutaneous mouse model demonstrated that S100P promotes recruitment and polarization of TAMs towards the M2 type. Finally, in vitro studies on LUAD cells revealed that S100P enhances the secretion of chemokines and polarizing factors by activating the PKA/c-Jun pathway, which is implicated in TAM recruitment and polarization towards the M2 phenotype. Moreover, inhibition of c-Jun expression impedes the ability of TAMs to infiltrate and polarize towards the M2 phenotype. In conclusion, our study demonstrates that S100P facilitates LUAD cells growth by recruiting M2 TAMs through PKA/c-Jun signaling, resulting in the production of various cytokines. Considering these findings, S100P holds promise as an important diagnostic marker and potential therapeutic target for LUAD.

Construction of a prognostic model based on memory CD4+ T cell-associated genes for lung adenocarcinoma and its applications in immunotherapy.

The association between memory CD4+ T cells and cancer prognosis is increasingly recognized, but their impact on lung adenocarcinoma (LUAD) prognosis remains unclear. In this study, using the cell-type identification by estimating relative subsets of RNA transcripts algorithm, we analyzed immune cell composition and patient survival in LUAD. Weighted gene coexpression network analysis helped identify memory CD4+ T cell-associated gene modules. Combined with module genes, a five-gene LUAD prognostic risk model (HOXB7, MELTF, ABCC2, GNPNAT1, and LDHA) was constructed by regression analysis. The model was validated using the GSE31210 data set. The validation results demonstrated excellent predictive performance of the risk scoring model. Correlation analysis was conducted between the clinical information and risk scores of LUAD samples, revealing that LUAD patients with disease progression exhibited higher risk scores. Furthermore, univariate and multivariate regression analyses demonstrated the model independent prognostic capability. The constructed nomogram results demonstrated that the predictive performance of the nomogram was superior to the prognostic model and outperformed individual clinical factors. Immune landscape assessment was performed to compare different risk score groups. The results revealed a better prognosis in the low-risk group with higher immune infiltration. The low-risk group also showed potential benefits from immunotherapy. Our study proposes a memory CD4+ T cell-associated gene risk model as a reliable prognostic biomarker for personalized treatment in LUAD patients.

Anoikis-related gene signatures predict prognosis of lung adenocarcinoma patients and reveal immune infiltration.

Lung adenocarcinoma (LUAD), a type of lung cancer, is one of the most aggressive and deadly malignancies worldwide. Malignant tumor cells exhibit strong anti-anoikis properties to achieve distant metastasis through the circulatory system. However, more research is needed to understand how anoikis is involved in the progression, metastasis and especially the prognosis of LUAD. We obtained anoikis-related genes (ARGs) from two websites, Harmonizome and Genecards, and integrated them to select and model the genes associated with LUAD prognosis. In addition, we investigated differences in the immune cell microenvironment and pathways of enrichment analysis between subtypes. We finally constructed a nomogram based on ARGs and used decision curve analysis (DCA) to demonstrate that this model could help clinicians make clinical decisions. Sixty-four differentially expressed genes (DEGs) were found to be associated with survival, and of these, six were chosen to build a prognostic model. The time-dependent receiver operating characteristic (ROC) curves showed that the model had a satisfactory predictive ability. Enrichment analysis and immune microenvironment analysis revealed that the immune status and drug sensitivity of populations at high and low risk were different. We integrated the clinicopathological features of LUAD with the risk score to build the nomogram. The nomogram was shown to be a good predictor of short- and long-term survival in LUAD patients through DCA analysis. This new model based on six ARGs and nomograms in our study could help patients with LUAD develop personalized treatment plans.

Abstract 668: Enhancing chemosensitivity of lung adenocarcinoma via Y-box binding protein 1 (YB-1) inhibition

Abstract Background: Y-box binding protein 1 (YB-1, YBX1) is a multifunctional nucleic acid binding protein that regulates the expression of various genes by binding to their mRNA and stabilizing them. In over 20 cancer types, including lung adenocarcinoma (LUAD), YBX1 expression is significantly elevated in tumor samples compared to normal tissue. Within cancer cells, YB-1 promotes the expression of genes involved in tumorigenesis and chemoresistance. Consequently, elevated YBX1 expression in tumor is associated with poor clinical outcomes and significantly reduced overall survival in LUAD patients. Therefore, YB-1 emerges as a promising therapeutic target for LUAD treatment. Utilizing a small molecule YB-1 inhibitor, CET056, we performed a series of in vitro and in vivo analyses to assess the therapeutic efficacy of YB-1 inhibition and unravel YB-1’s role in tumorigenesis and disease progression in LUAD. Methods: Four human and one mouse LUAD cell lines were treated with CET056 and/or chemotherapeutic drugs and analyzed for the in vitro therapeutic activity of CET056. Using xenograft and syngeneic LUAD mouse models, the preclinical therapeutic efficacy of CET056 on disease progression of LUAD was also tested. Results: CET056 was shown to effectively decrease YB-1 expression in both human and mouse LUAD cell lines and exert inhibitory effects on LUAD in vitro and in vivo. This treatment delayed tumor progression and metastasis in CMT-64 syngeneic mouse model. Proteomics analysis revealed that translational machinery-associated pathways were down-regulated in LUAD cells after CET056 treatment whereas apoptosis and cell death-associated pathways were up-regulated. In alignment with this finding, CET056 treatment in combination with cisplatin showed chemo-sensitizing effect on LUAD in vitro and in vivo. Conclusion: Our studies suggest that YB-1 could be a promising target for combating chemoresistance in LUAD. Inhibition of YB-1 with a small molecule drug as a monotherapy or combination therapy could an effective strategy to treat LUAD. Citation Format: Jee Min Lee, Dhanir Tailor, Fernando J. Garcia-Marques, Abel Bermudez, Sharon Pitteri, Sanjay V. Malhotra. Enhancing chemosensitivity of lung adenocarcinoma via Y-box binding protein 1 (YB-1) inhibition [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 668.

Machine learning framework develops neutrophil extracellular traps model for clinical outcome and immunotherapy response in lung adenocarcinoma.

Neutrophil extracellular traps (NETs) are novel inflammatory cell death in neutrophils. Emerging studies demonstrated NETs contributed to cancer progression and metastases in multiple ways. This study intends to provide a prognostic NETs signature and therapeutic target for lung adenocarcinoma (LUAD) patients. Consensus cluster analysis performed by 38 reported NET-related genes in TCGA-LUAD cohorts. Then, WGCNA network was conducted to investigate characteristics genes in clusters. Seven machine learning algorithms were assessed for training of the model, the optimal model was picked by C-index and 1-, 3-, 5-year ROC value. Then, we constructed a NETs signature to predict the overall survival of LUAD patients. Moreover, multi-omics validation was performed based on NETs signature. Finally, we constructed stable knockdown critical gene LUAD cell lines to verify biological functions of Phospholipid Scramblase 1 (PLSCR1) in vitro and in vivo. Two NETs-related clusters were identified in LUAD patients. Among them, C2 cluster was provided as "hot" tumor phenotype and exhibited a better prognosis. Then, WGCNA network identified 643 characteristic genes in C2 cluster. Then, Coxboost algorithm proved its optimal performance and provided a prognostic NETs signature. Multi-omics revealed that NETs signature was involved in an immunosuppressive microenvironment and predicted immunotherapy efficacy. In vitro and in vivo experiments demonstrated that knockdown of PLSCR1 inhibited tumor growth and EMT ability. Besides, cocultural assay indicated that the knockdown of PLSCR1 impaired the ability of neutrophils to generate NETs. Finally, tissue microarray (TMA) for LUAD patients verified the prognostic value of PLSCR1 expression. In this study, we focus on emerging hot topic NETs in LUAD. We provide a prognostic NETs signature and identify PLSCR1 with multiple roles in LUAD. This work can contribute to risk stratification and screen novel therapeutic targets for LUAD patients.

G2 and S phase-expressed protein 1 is a biomarker for poor prognosis in lung adenocarcinoma.

Studying the regulatory mechanism and clinical application of G2 and S phase-expressed protein 1 (GTSE1) genes in lung adenocarcinoma (LUAD). LUAD data was obtained from The Cancer Genome Atlas (TCGA) database, and differentially expressed genes (DEGs) were derived by analyzing expression data using R software. Survival analysis was performed to identify genes associated with LUAD, and among them, a target gene for LUAD was identified. Further analysis of the gene expression profiling interactive analysis database revealed differences in gene expression between normal and tumor tissues of LUAD patients. Disease free survival (DFS) and overall survival (OS) of the GTSE1 genes in LUAD were compared. The study conducted a GSEA analysis of GTSE1 expression and further investigated the relationships between GTSE1 expression and the survival time of LUAD patients at different pathological stages. The correlations between OS and GTSE1 gene expression were explored based on different treatments. Additionally, the correlation between the GTSE1 gene and immune infiltration was analyzed. The results indicated that the expression of GTSE1 was significantly higher in tumor tissues of LUAD compared to normal tissues. Furthermore, patients with high GTSE1 expression had significantly lower survival rates for OS and DFS compared to patients with low expression of GTSE1. The GSEA analysis of GTSE1 revealed its involvement in LUAD through the Reactome unwinding of DNA and Biocarta ranms pathway. In patients with LUAD at the pathological T2 stage, low expression of GTSE1 was associated with longer survival time. Furthermore, LUAD patients with low GTSE1 expression who underwent surgery without chemotherapy exhibited a longer survival time. The GTST1 gene, identified as a target gene of LUAD, was validated through cell experiments and pathological sections. GTSE1 can be used as a marker and therapeutic target for LUAD. The survival of LUAD patients can be improved by reducing the expression of GTSE1.

Exploring the Diagnostic and Prognostic Predictive Values of Ferroptosis- Related Markers in Lung Adenocarcinoma.

Lung Adenocarcinoma (LUAD), a common and aggressive form of lung cancer, poses significant treatment challenges due to its low survival rates. To better understand the role of ferroptosis driver genes in LUAD, this study aimed to explore their diagnostic and prognostic significance, as well as their impact on treatment approaches and tumor immune function in LUAD. To accomplish the defined goals, a comprehensive methodology incorporating both in silico and wet lab experiments was employed. A comprehensive analysis was conducted on a total of 233 ferroptosis driver genes obtained from the FerrDB database. Utilizing various TCGA databases and the RT-qPCR technique, the expression profiles of 233 genes were examined. Among them, TP53, KRAS, PTEN, and HRAS were identified as hub genes with significant differential expression. Notably, TP53, KRAS, and HRAS exhibited substantial up-regulation, while PTEN demonstrated significant down-regulation at both the mRNA and protein levels in LUAD samples. The dysregulation of hub genes was further associated with poor overall survival in LUAD patients. Additionally, targeted bisulfite-sequencing (bisulfite-seq) analysis revealed aberrant promoter methylation patterns linked to the dysregulation of hub genes. Furthermore, hub genes were found to participate in diverse oncogenic pathways, highlighting their involvement in LUAD tumorigenesis. By leveraging the diagnostic and prognostic potential of ferroptosis driver hub genes (TP53, KRAS, PTEN, and HRAS), significant advancements can be made in the understanding and management of LUAD pathogenesis. Therapeutic targeting of these genes using specific drugs holds great promise for revolutionizing drug discovery and improving the overall survival of LUAD patients.

Over-Expression of EFNA2 in Lung Adenocarcinoma: EFNA2 Gene Expression Correlates with Shortened Survival

Background: The incidence of lung adenocarcinoma (LUAD) is increasing worldwide with different prognosis. Ephrin-A2（EFNA2), a member of the Eph/ephrin family, is associated with tumor progression. However, the correlations of EFNA2 with prognosis in LUAD remain unclear. The purpose of this article is to analyze the impact of EFNA2 on the prognosis of LUAD patients through TCGA, Oncomine, and GEPIA databases, and to explore its possible mechanisms. Methods: This article found a significant correlation between EFNA2 and shortened survival in LUAD patients through TCGA, Oncomine, and GEPIA database analysis. Therefore, we further invested the relationship between the expression and prognostic value of the EFNA2 gene in LUAD patients. Sequential data filtering (survival analysis, independent prognostic analysis, and clinicalcorrelation analysis) was performed. EFNA2 expression was analyzed by the Oncomine database and Tumor Immune Estimation Resource (TIMER). We evaluated the influence of EFNA2 on clinical prognosis using Kaplan-Meier plotter, the PrognoScan database and Gene Expression Profiling Interactive Analysis (GEPIA). The correlation between EFNA2 and cancer immune infiltrates was investigated by TIMER. In addition, correlations between EFNA2 expression and gene marker sets of immune infiltrates were analyzed by TIMER and GEPIA. In addition, gene enrichment analysis was performed by Metascape. Finally, a co-expression analysis was performed by the Oncomine database. Results: A cohort of LUAD patients showed that high EFNA2 expression was associated with poorer overall survival (OS), disease-free survival (DFS) by TCGA, and EFNA2 was significantly associated with stage in LUAD. In addition, EFNA2 expression was positively correlated with infiltrating levels of B cells and CD8+ T cells. Moreover, the differential expression of EFNA2 was significantly higher in lung adenocarcinoma compared with that in normal controls. Specifically, EFNA2 was positively associated with ADAMTSL5, REEP6, PCSK4, C19orf25, and ANAPC2. Conclusions: Our data indicate that EFNA2 is a potential diagnostic and prognostic biomarker and a promising molecular therapeutic target to attenuate LUAD progression.

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.