[Expression of ASPM in Lung Adenocarcinoma and Its Relationship with Development and Prognosis]

In lung adenocarcinoma, low expression of the cell surface extracellular nucleotidase CD39 is related to immune infiltration and a poor prognosis

Background

Extracellular nucleotidase on the cell surface CD39 plays a crucial role in the tumor microenvironment in the immunosuppressive adenosine pathway. However, the association between CD39 and lung adenocarcinoma has rarely been recorded. This study aimed to explore the involvement of CD39 in the biological processes of lung cancer.

Methods

First, a prediction model was established by analyzing the expression of CD39 in lung adenocarcinoma and its relationships with clinical evidence of lung adenocarcinoma using The Cancer Genome Atlas (TCGA) and Tumor IMmune Estimation Resource (TIMER) databases. In the TCGA and TIMER databases, the relationship between CD39 and immune cells and the relationship with immune-related expressed genes were studied. Subsequently, using gene set enrichment analysis (GSEA), the potential mechanism of action was investigated.

Results

Lung adenocarcinoma patients with elevated CD39 expression had improved overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI). CD39 expression was reduced in lung adenocarcinoma tumor tissue in the TCGA and TIMER databases. The nomogram's C-index was 0.688 (0.665-0.712), indicating some consistency in the prediction model. According to the TIMER and TCGA databases, CD39 expression was strongly connected with several immune cells invading and with immune checkpoint-related markers such as PDCD1, CD274, CTLA-4, and several functional T cells. GSEA revealed that CD39 influences the extracellular matrix, immunological microenvironment, programmed death 1 (PD-1) expression, glucose metabolism, PTEN stability, inflammatory response, and angiogenesis in lung cancer.

Conclusions

The current study's findings demonstrated that CD39 can be employed as a possible predictive biomarker for lung adenocarcinoma and may enhance the patients' poor prognosis by preventing the immunological escape of tumor cells from the lung adenocarcinoma tumor microenvironment.

Construction and Validation of a Tumor Microenvironment-Based Scoring System to Evaluate Prognosis and Response to Immune Checkpoint Inhibitor Therapy in Lung Adenocarcinoma Patients

Background: Lung cancer is among the most dangerous malignant tumors to human health. Lung adenocarcinoma (LUAD) accounts for about 40% of all lung cancers. Accumulating evidence suggests that the tumor microenvironment (TME) is a crucial regulator of carcinogenesis and therapeutic efficacy in LUAD. However, the impact of tumor microenvironment-related signatures (TMERSs) representing the TME characteristics on the prognosis and therapeutic outcome of LUAD patients remains to be further explored. Materials and methods: Gene expression files and clinical information of 1630 LUAD samples and 275 samples with immunotherapy information from different databases such as The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO) and Cancer Research Institute (CRI) iAtlas were downloaded and analyzed. Three hundred tumor microenvironment-related signatures (TMERS) based on a comprehensive collection of marker genes were quantified by single sample gene set enrichment analysis (ssGSEA), and then eight significant signatures were selected to construct the tumor microenvironment-related signature score (TMERSscore) by performing Least Absolute Shrinkage and Selection Operator (LASSO)-Cox analysis. Results: In this study, we constructed a TME-based prognostic stratification model for patients with LUAD and validated it in several external datasets. Furthermore, the TMERSscore was found to be positively correlated with tumor malignancy and a high TMERSscore predicted a poor prognosis. Moreover, the TMERSscore of responders treated with Immune Checkpoint Inhibitor (ICI) therapies was significantly lower than that of non-responders, and the TMERSscore was positively correlated with the tumor immune dysfunction and exclusion (TIDE) score, implying that a low TMERSscore predicts a better response to ICI treatment and may provide independent and incremental predictive value over current biomarkers. Conclusions: Overall, we constructed a TMERSscore that can be used for LUAD patient prognosis stratification as well as ICI therapeutic efficacy evaluation, supportive results from independent external validation sets showed its robustness and effectiveness.

Overexpression of abnormal spindle-like microcephaly-associated (ASPM) increases tumor aggressiveness and predicts poor outcome in patients with lung adenocarcinoma

Background

Cumulative evidence points to abnormal spindle-like microcephaly-associated (ASPM) protein being overexpressed in various cancers, and the aberrant expression of ASPM has been shown to promote cancer tumorigenicity and progression. However, its role and clinical significance in lung adenocarcinoma (LUAD) remains unclear. This study aimed to determine the expression patterns of ASPM and its clinical significance in LUAD.

Methods

In total, 4 original worldwide LUAD microarray mRNA expression datasets (N=1,116) with clinical and follow-up annotations were downloaded from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. The expression of ASPM protein in LUAD patients was detected by immunohistochemistry. Survival analysis and Cox regression analysis were used to examine the prognostic value of ASPM expression. Gene set enrichment analysis (GSEA) was performed to investigate the relationship between ASPM and LUAD.

Results

Dataset analyses and immunohistochemistry revealed that ASPM expression was significantly higher in the LUAD tissues compared with normal lung tissues, especially in the advanced tumor stage. Additionally, overexpression of ASPM was significantly correlated with shorter overall survival (OS) and relapse-free survival (RFS) in LUAD. Univariate and multivariate Cox regression analyses revealed that the overexpression of ASPM was a potential independent predictor of poor OS and RFS. However, ASPM overexpression was not significantly associated with predicting OS in lung squamous cell carcinoma. GSEA analysis demonstrated that ASPM was significantly enriched in the cell cycle, DNA replication, homologous recombination, RNA degradation, mismatch repair, and p53 signaling pathways.

Conclusions

These findings demonstrate the important role of ASPM in the tumorigenesis and progression of LUAD.

Exploration of Prognostic Biomarkers for Lung Adenocarcinoma Through Bioinformatics Analysis

With the development of computer technology, screening cancer biomarkers based on public databases has become a common research method. Here, an eight-gene prognostic model, which could be used to judge the prognosis of patients with lung adenocarcinoma (LUAD), was developed through bioinformatics methods. This study firstly used several gene datasets from GEO database to mine differentially expressed genes (DEGs) in LUAD tissue and healthy tissue via joint analysis. Later, enrichment analysis for the DEGs was performed, and it was found that the DEGs were mainly activated in pathways involved in extracellular matrix, cell adhesion, and leukocyte migration. Afterward, a TCGA cohort was used to perform univariate Cox, least absolute shrinkage and selection operator method, and multivariate Cox regression analyses for the DEGs, and a prognostic model consisting of eight genes (GPX3, TCN1, ASPM, PCP4, CAV2, S100P, COL1A1, and SPOK2) was established. Receiver operation characteristic (ROC) curve was then used to substantiate the diagnostic efficacy of the prognostic model. The survival significance of signature genes was verified through the GEPIA database, and the results exhibited that the risk coefficients of the eight genes were basically congruous with the effects of these genes on the prognosis in the GEPIA database, which suggested that the results were accurate. Finally, combined with clinical characteristics of patients, the diagnostic independence of the prognostic model was further validated through univariate and multivariate regression, and the results indicated that the model had independent prognostic value. The overall finding of the study manifested that the eight-gene prognostic model is closely related to the prognosis of LUAD patients, and can be used as an independent prognostic indicator. Additionally, the prognostic model in this study can help doctors make a better diagnosis in treatment and ultimately benefit LUAD patients.

Abnormal spindle-like microcephaly-associated protein enhances cell invasion through Wnt/β-catenin-dependent regulation of epithelial-mesenchymal transition in non-small cell lung cancer cells

Background

Lung cancer is one of the most common cancer worldwide, invasion and metastasis are still the bottleneck in the clinical setting. More diagnostic markers and drug targets need to be clarified. Therefore, we screened abnormal spindle-like microcephaly-associated protein (ASPM) as our candidate gene, which is associated with the poor prognosis. The aim of the present study was to understand the roles of ASPM in cell invasion in non-small cell lung cancer (NSCLC).

Methods

Gene Expression Omnibus (GEO) datamining was used to identify ASPM. Transwell invasion assay, quantitative reverse transcription polymerase chain reaction (qRT-PCR), and Western blot analysis were performed to discover the molecular functions of ASPM. Overexpression and small interfering mediated knockdown techniques have been used to study the cell invasion hallmarks of cancer.

Results

ASPM stood out among all the candidate genes from GEO datamining. ASPM in lung cancer tissues has been associated with poor overall survival rate. The protein levels of ASPM has been validated using lung cancer patients’ tissues, which upregulation of ASPM expression has been found in lung cancer patients. Silencing of ASPM decreased the cell invasion reflected by epithelial-mesenchymal transition (EMT) biomarkers: downregulation of vimentin and upregulation of E-cadherin. Matrix metalloproteinase (MMP) 2/9 protein levels were also affected upon transient knockdown of ASPM. Furthermore, the suppression of ASPM markedly inhibited the Wnt/β-catenin signaling pathway in vitro. The ectopic expression of ASPM had the opposite effect. The inhibition of β-catenin in ASPM-overexpressing lung cancer cells reduced the expression of EMT markers. The inhibitory effects on the Wnt/β-catenin signaling pathway were attenuated in cancer cells when ASPM was silenced. These findings demonstrated that the silencing of ASPM strongly reduced cell invasion in lung cancer.

Conclusions

ASPM promoted NSCLC invasion through EMT and by affecting the MMP family of proteins. The Wnt/β-catenin signaling pathway played an indispensable role in the ASPM-mediated NSCLC EMT-invasion cascade.