Overexpression of FAM83A Is Associated with Poor Prognosis of Lung Adenocarcinoma

Diagnostic value of immune-related biomarker FAM83A in differentiating malignant from benign pleural effusion in lung adenocarcinoma

BACKGROUND

Malignant pleural effusion (MPE) is frequently observed in patients with advanced lung adenocarcinoma (LUAD). Pleural fluid cytology is a less invasive procedure compared to pleural biopsy. Therefore, it is crucial to identify novel effective biomarkers for LUAD-associated pleural fluid cytology.

METHODS

The RNA sequencing (RNA-Seq) and clinical data of LUAD cases were downloaded from TCGA and OncoSG databases. Differential gene expression analysis, survival analysis and immune cell infiltration analysis were performed on the LUAD datasets. The expression levels of FAM83A, TFF-1, and NapsinA in 94 paired LUAD and adjacent normal tissues, and in the pleural effusion specimens of 40 LUAD and 21 non-neoplastic patients were evaluated by immunohistochemistry.

RESULTS

FAM83A expression levels were significantly different between the LUAD and normal tissue datasets, and correlated with overall or disease-free survival, and histological grade of the tumors. Furthermore, the in-situ expression of FAM83A was higher in 89/94 LUAD tissues compared to the paired normal tissues. FAM83A expression was significantly correlated with immune cell infiltration, and showed a positive association with macrophage infiltration. In addition, FAM83A staining was positive in 37 LUAD pleural effusion samples, and negative in 20 non-neoplastic pleural effusion samples. The expression pattern of FAM83A in the pleural effusion of LUAD patients was relatively consistent with that of TFF-1 and NapsinA, and even stronger in some specimens that were weakly positive or negative for TTF1/NapsinA.

CONCLUSIONS

FAM83A is a promising immune-related biomarker in LUAD biopsy specimens and pleural fluid, and can distinguish between malignant and benign pleural effusion.

Sense and anti-sense: Role of FAM83A and FAM83A-AS1 in Wnt, EGFR, PI3K, EMT pathways and tumor progression

An increasing number of studies have shown that FAM83A, a member of the family with sequence similarity 83 (FAM83), which consists of eight members, is a key tumor therapeutic target involved in multiple signaling pathways. It has been reported that FAM83A plays essential roles in the regulation of Wnt/β-catenin, EGFR, MAPK, EMT, and other signaling pathways and physiological processes in models of pancreatic cancer, lung cancer, breast cancer, and other malignant tumors. Moreover, the expression of FAM83A could be significantly affected by multiple noncoding RNAs that are dysregulated in malignant tumors, the dysregulation of which is essential for the malignant process. Among these noncoding RNAs, the most noteworthy is the antisense long noncoding (Lnc) RNA of FAM83A itself (FAM83A-AS1), indicating an outstanding synergistic carcinogenic effect between FAM83A and FAM83A-AS1. In the present study, the specific mechanisms by which FAM83A and FAM83A-AS1 cofunction in the Wnt/β-catenin and EGFR signaling pathways were reviewed in detail, which will guide subsequent research. We also described the applications of FAM83A and FAM83A-AS1 in tumor therapy and provided a certain theoretical basis for subsequent drug target development and combination therapy strategies.

Identification of metabolism-related gene signature in lung adenocarcinoma

AIM

Lung cancer is one of the most common cancers in China and has a high mortality rate. Most patients who are diagnosed have lost the opportunity to undergo surgery. Aberrant metabolism is closely associated with tumorigenesis. We aimed to identify an effective metabolism-related prediction model for assessing prognosis based on the cancer genome atlas (TCGA) and GSE116959 databases.

METHODS

TCGA and GSE116959 datasets from Gene Expression Omnibus were used to obtain lung adenocarcinoma (LUAD) data. Additionally, we captured metabolism-related genes (MRGs) from the GeneCards database. First, we extracted differentially expressed genes using R to analyze the LUAD data. We then selected the same differentially expressed genes, including 168 downregulated and 77 upregulated genes. Finally, 218 differentially expressed MRGs (DEMRGs) were included to perform functional enrichment analysis and construct a protein-protein interaction network with the help of Cytoscape and Search Tool for the Retrieval of Interacting Genes database. Cytoscape was used to visualize the intensive intervals in the network. Then univariate and Least Absolute Shrinkage and Selection Operator Cox regression analyses, which assisted in identifying the overall survival (OS)-related DEMRGs and building a 10-DEMRG prognosis model, were performed. The prognostic values, tumor immunity relevance, and molecular mechanism were further investigated. A nomogram incorporating signature, age, gender, and TNM stage was established.

RESULTS

A 10-DEMRG model was established to forecast the OS of LUAD through Least Absolute Shrinkage and Selection Operator regression analysis. This prognostic signature stratified LUAD patients into low-risk and high-risk groups. The receiver operating characteristic curve and K-M analysis indicated good performance of the DEMRGs signature at predicting OS in the TCGA dataset. Univariate and multivariate Cox regression also revealed that the DEMRGs signature was an independent prognosis factor in LUAD. We noticed that the risk score was substantially related to the clinical parameters of LUAD patients, covering age and stage. Immune analysis results showed that risk score was associated with some immune cells and immune checkpoints. Nomogram also verified the clinical value of the DEMRGs signature.

CONCLUSION

In this study, we constructed a DEMRGs signature and established a prognostic nomogram that is robust and reliable to predict OS in LUAD. Overall, the findings could help with therapeutic customization and personalized therapies.

Dipeptidase‑2 is a prognostic marker in lung adenocarcinoma that is correlated with its sensitivity to cisplatin

Lung cancer accounts for the highest percentage of cancer morbidity and mortality worldwide, and lung adenocarcinoma (LUAD) is the most prevalent subtype. Although numerous therapies have been developed for lung cancer, patient prognosis is limited by tumor metastasis and more effective treatment targets are urgently required. In the present study, gene expression profiles were extracted from the Gene Expression Omnibus database and mRNA expression data were downloaded from The Cancer Genome Atlas database. In addition, TIMER 2.0 database was used to analyze the expression of genes in normal and multiple tumor tissues. Protein expression was confirmed using the Human Protein Atlas database and LUAD cell lines, sphere formation assay, western blotting, and a xenograft mouse model were used to confirm the bioinformatics analysis. Dipeptidase‑2 (DPEP2) expression was significantly decreased in LUAD and was negatively associated with prognosis. DPEP2 overexpression substantially inhibited epithelial‑mesenchymal transition (EMT) as well as LUAD cell metastasis, and limited the expression of the cancer stem cell transformation markers, CD44 and CD133. In addition, DPEP2 improved LUAD sensitivity to cisplatin by inhibiting EMT; this was verified in vitro and in vivo. These data indicated that DPEP2 upregulates E‑cadherin, thereby regulating cell migration, cancer stem cell transformation, and cisplatin resistance, ultimately affecting the survival of patients with LUAD. Overall, the findings of the present suggest that DPEP2 is important in the development of LUAD and can be used both as a prognostic marker and a target for future therapeutic research.

Cuproptosis Depicts Immunophenotype and Predicts Immunotherapy Response in Lung Adenocarcinoma

BACKGROUND

Although significant progress has been made in immunotherapy for lung adenocarcinoma (LUAD), there is an urgent need to identify effective indicators to screen patients who are suitable for immunotherapy. Systematically investigating the cuproptosis-related genes (CRGs) in LUAD may provide new ideas for patients' immunotherapy stratification.

METHOD

We comprehensively analyzed the landscape of 12 CRGs in a merged TCGA and GEO LUAD cohort. We investigated the associations between tumor microenvironment and immunophenotypes. We utilized a risk score to predict the prognosis and immunotherapy response for an individual patient. Additionally, we conducted CCK-8 experiments to evaluate the impact of DLGAP5 knockdown on A549 cell proliferation.

RESULT

We utilized an integrative approach to analyze 12 CRGs and differentially expressed genes (DEGs) in LUAD samples, resulting in the identification of two distinct CRG clusters and two gene clusters. Based on these clusters, we generated immunophenotypes and observed that the inflamed phenotype had the most abundant immune infiltrations, while the desert phenotype showed the poorest immune infiltrations. We then developed a risk score model for individual patient prognosis and immunotherapy response prediction. Patients in the low-risk group had higher immune scores and ESTIMATE scores, indicating an active immune state with richer immune cell infiltrations and higher expression of immune checkpoint genes. Moreover, the low-risk group exhibited better immunotherapy response according to IPS, TIDE scores, and Imvigor210 cohort validation results. In addition, our in vitro wet experiments demonstrated that DLGAP5 knockdown could suppress the cell proliferation of A549.

CONCLUSION

Novel cuproptosis molecular patterns reflected the distinct immunophenotypes in LUAD patients. The risk model might pave the way to stratify patients suitable for immunotherapy and predict immunotherapy response.