Survival Of Lung Adenocarcinoma Patients Research Articles

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.

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.

Prognostic value of tumor‑associated CD177+ neutrophils in lung adenocarcinoma.

The aim of the present study was to detect CD177+ neutrophils in tumor tissues and analyze their association with the clinical characteristics and prognosis of patients with lung adenocarcinoma (LUAD). Immunohistochemistry was used to detect CD177+ neutrophils in tumors and adjacent tissues of 16 patients with LUAD who underwent curative surgical resection. A total of 120 patients with LUAD were recruited, and their clinical data were collected; survival follow-up was performed. CD177+ neutrophils in tumor tissues were detected via immunohistochemistry, and the association between CD177+ neutrophils and clinical characteristics was analyzed. The density of CD177+ neutrophils in tumor tissues and adjacent tissues of patients with LUAD was analyzed using t-test, and the association between CD177+ neutrophils and clinical characteristics was analyzed through the Chi-square test. Survival was calculated using the Kaplan-Meier survival rate curve. Finally, the association between these indicators and the survival of LUAD patients was evaluated using Cox regression analysis. CD177+ neutrophil infiltration was significantly higher in LUAD tumor tissues, and the high density of CD177+ neutrophils was associated with the clinical characteristics of TNM stage, tumor differentiation and poor progression-free and overall survival in LUAD. In conclusion, tumor-associated CD177+ neutrophils associated with malignant progression and poor prognosis may be independent and unfavorable prognostic biomarkers for LUAD.

A Novel Methylation-based Model for Prognostic Prediction in Lung Adenocarcinoma.

Specific methylation sites have shown promise in the early diagnosis of lung adenocarcinoma (LUAD). However, their utility in predicting LUAD prognosis remains unclear. This study aimed to construct a reliable methylation-based predictor for accurately predicting the prognosis of LUAD patients. DNA methylation data and survival data from LUAD patients were obtained from the TCGA and a GEO series. A DNA methylation-based signature was developed using univariate least absolute shrinkage and selection operators and multivariate Cox regression models. Eight CpG sites were identified and validated as optimal prognostic signatures for the overall survival of LUAD patients. Receiver operating characteristic analysis demonstrated the high predictive ability of the eight-site methylation signature combined with clinical factors for overall survival. This research successfully identified a novel eight-site methylation signature for predicting the overall survival of LUAD patients through bioinformatic integrated analysis of gene methylation markers used in the early diagnosis of lung cancer.

Construction of a prognostic model of lung adenocarcinoma based on machine learning

In order to more accurately predict the prognosis and survival of lung adenocarcinoma patients, this paper used the gene expression and clinical information data of lung adenocarcinoma patients in the open database of TCGA to jointly construct a prognosis model of lung adenocarcinoma. Three difference analysis methods and univariate cox regression analysis were used as the preliminary screening method. By comparing the variable selection ability of lasso regression and random survival forest, comparing the performance of cox proportional risk regression model and random survival forest model, and integrating clinical data, a model that can more accurately predict the prognosis of lung adenocarcinoma patients was constructed. After comparison and selection, lasso regression was used to select variables and cox proportional risk model was used as the prediction model. The consistency index of the model reached 0.712. The AUC for 1-year, 3-year and 5-year survival of lung adenocarcinoma patients in the validation set were 0.808, 0.816 and 0.754, respectively. After the fusion of clinical data, the 1-year, 3-year and 5-year survival prediction AUC in the validation set were 0.840, 0.836 and 0.865, respectively, indicating that the model had good predictive performance.

Ectopic Expression of TIGIT in Lung Adenocarcinoma and Its Clinical Significance

This study aimed to investigate the T cell immunoreceptor with ITIM and Ig domains (TIGIT) expression in lung adenocarcinoma (LUAD). TIGIT expression was measured by western blot, reverse transcription quantitative polymerase chain reaction. Seventy-two paired surgical specimens were collected from patients with stage I-IV LUAD. The expression of TIGIT in surgical specimens was determined using immunohistochemistry. TIGIT was overexpressed in LUAD tissues. Moreover, overexpressed TIGIT was significantly associated with advanced clinical staging, lymph node metastasis, distant metastasis, and TP53 mutations in LUAD. Moreover, high expression of TIGIT was negatively correlated with purity of CD4&lt;sup&gt;&amp;#43;&lt;/sup&gt; T cells. High rations of TIGIT&lt;sup&gt;&amp;#43;&lt;/sup&gt;CD4&lt;sup&gt;&amp;#43;&lt;/sup&gt; T cells predicted poor overall survival of LUAD patients. Additionally, high ratios of TIGIT&lt;sup&gt;&amp;#43;&lt;/sup&gt;CD4&lt;sup&gt;&amp;#43;&lt;/sup&gt; T cells is closely related to CD4&lt;sup&gt;&amp;#43;&lt;/sup&gt; T cell depletion. Taken together, TIGIT was overexpressed in LUAD patients. High levels of TIGIT induced the alteration of CD4&lt;sup&gt;&amp;#43;&lt;/sup&gt; T cell based immunomodulation and predicted poor prognosis of LUAD patients. Therefore, TIGIT can be potential biomarker for LUAD.

DHEA down-regulates mitochondrial dynamics and promotes apoptosis of lung adenocarcinoma cells through FASTKD2.

Background: DHEA is a steroid hormone produced by the gonads, adrenal cortex, brain, and gastrointestinal tract. While the anti-obesity, anti-atherosclerosis, anti-cancer, and memory-enhancing effects of DHEA have been substantiated through cell experiments, animal studies, and human trials, the precise mechanisms underlying these effects remain unclear. Altered mitochondrial dynamics can lead to mitochondrial dysfunction, which is closely related to many human diseases, especially cancer and aging. This study was to investigate whether DHEA inhibits lung adenocarcinoma through the mitochondrial pathway and its molecular mechanism. Methods: Through animal experiments and cell experiments, the effect of DHEA on tumor inhibition was determined. The correlation between FASTKD2 expression and DHEA was analyzed by Western blot, Reverse transcription-quantitative PCR, Immunohistochemistry, and TCGA database. Results: In this study, DHEA supplementation in the diet can inhibit the tumor size of mice, and the effect of adding DHEA one week before the experiment is the best. DHEA limits the glycolysis process by inhibiting G6PDH activity, increases the accumulation of reactive oxygen species, and initiates apoptosis in the mitochondrial pathway of cancer cells. Conclusion: DHEA suppresses mitochondrial fission and promotes mitochondrial fusion by downregulating the expression of FASTKD2, thereby inhibiting tumor growth and prolonging the overall survival of lung adenocarcinoma patients, which also provides a new target for the prevention and treatment of lung adenocarcinoma.

Micropapillary or solid component predicts worse prognosis in pathological IA stage lung adenocarcinoma: A meta-analysis.

Micropapillary and solid patterns indicate worse survival in lung adenocarcinoma patients, even in pathological stage IB patients. However, whether the presence of micropapillary or solid components is related to worse prognosis in pathological IA stage lung adenocarcinoma remains unclear. Several databases were searched up to December 31, 2022 for relevant studies investigating the association between micropapillary and solid components and the survival of IA stage lung adenocarcinoma patients. Primary and secondary outcomes are disease-free survival (DFS) and overall survival (OS), respectively. Hazard ratios (HRs) and 95% confident intervals (CIs) were combined, and subgroup analysis stratified by the pathological subtype and proportion of components was further performed. A total of 19 studies with 12,562 cases were included. Pooled results indicated that micropapillary or solid components obviously predicted worse DFS (HR = 2.40, 95% CI: 1.96-2.94, P < .001) and OS (HR = 2.30, 95% CI: 1.68-3.15, P < .001). Subgroup analysis based on pathological subtype showed that both micropapillary and solid components were significantly associated with worse DFS (micropapillary: HR = 2.70, 95% CI: 1.70-4.28, P < .001; solid: HR = 3.98, 95% CI: 2.10-7.54, P < .001) and OS (micropapillary: HR = 2.29, 95% CI: 1.17-4.48, P = .015; solid: HR = 4.18, 95% CI: 1.72-10.17, P = .002). In addition, further subgroup analysis stratified by the proportion of micropapillary and solid components (>5%/1% or predominant) showed similar results. Micropapillary and solid patterns predicted a significantly worse prognosis in pathological IA stage lung adenocarcinoma patients.

A robust six-gene prognostic signature based on two prognostic subtypes constructed by chromatin regulators is correlated with immunological features and therapeutic response in lung adenocarcinoma.

Accumulating evidence has demonstrated that chromatin regulators (CRs) regulate immune cell infiltration and are correlated with prognoses of patients in some cancers. However, the immunological and prognostic roles of CRs in lung adenocarcinoma (LUAD) are still unclear. Here, we systematically revealed the correlations of CRs with immunological features and the survival in LUAD patients based on a cohort of gene expression datasets from the public TCGA and GEO databases and real RNA-seq data by an integrative analysis using a comprehensive bioinformatics method. Totals of 160 differentially expressed CRs (DECRs) were identified between LUAD and normal lung tissues, and two molecular prognostic subtypes (MPSs) were constructed and evaluated based on 27 prognostic DECRs using five independent datasets (p =0.016, <0.0001, =0.008, =0.00038 and =0.00055, respectively). Six differentially expressed genes (DEGs) (CENPK, ANGPTL4, CCL20, CPS1, GJB3, TPSB2) between two MPSs had the most important prognostic feature and a six-gene prognostic model was established. LUAD patients in the low-risk subgroup showed a higher overall survival (OS) rate than those in the high-risk subgroup in nine independent datasets (p <0.0001, =0.021, =0.016, =0.0099, <0.0001, =0.0045, <0.0001, =0.0038 and =0.00013, respectively). Six-gene prognostic signature had the highest concordance index of 0.673 compared with 19 reported prognostic signatures. The risk score was significantly correlated with immunological features and activities of oncogenic signaling pathways. LUAD patients in the low-risk subgroup benefited more from immunotherapy and were less sensitive to conventional chemotherapy agents. This study provides novel insights into the prognostic and immunological roles of CRs in LUAD.

A novel anoikis-related gene signature predicts in lung adenocarcinoma

ObjectiveTo generate a prognostic model prognosis based on anoikis-related genes (ANRGs) expression for Lung adenocarcinoma (LUAD), an exploration of the prognostic value of ANRGs in LUAD was conducted. MethodsBased on the expression matrix of genes from the TCGA database, we built the co-expressed modules by weighted gene co-expression network analysis (WGCNA). Then we identified the differentially expressed ANRGs (DE-ANGs) between LUAD and normal samples by the WGCNA results, DEGs, and the 345 ANRGs. The biofunction of the DE-ANRGs was interpreted using the GO and KEGG databases. Univariate and multivariate regression models were used to verify whether the risk model could serve as an independent prognostic factor. A nomogram was utilized to predict overall survival (OS) in LUAD. ResultsThe expression of 56 DE-ANRGs was significantly different in tumor tissues. We established a 4-ANRG prognostic signature. In the TCGA cohort and the external GSE31210 validation cohort, the OS of the high-risk group was lower than that of the low-risk group significantly. Moreover, the prediction performance of the risk model was excellently verified by the ROC curve. In addition, both univariate COX and multivariate Cox analyses indicated that risk score could act as an independent prognostic factor for LUAD patients. The calibration curve and C-index demonstrated that the nomogram was satisfactory in predicting 1, 3- and 5-year survival in LUAD patients. ConclusionsOur study developed a novel prognostic signature of 4 ANRGs with Excellent prognostic performance for LUAD patients.