Dataset Information

The comprehensive investigation of transcription factor AP-2 alpha in lung adenocarcinoma

ABSTRACT:

Background

Transcription factor AP-2 alpha (TFAP2A) has been reported to participate in various tumors. However, the transcriptional levels and prognostic values of TFAP2A remain elusive in lung adenocarcinoma (LUAD). The purpose of the present study was to investigate the impact of the TFAP2A in LUAD.

Methods

The transcriptional levels and prognostic effects of TFAP2A were explored in patients with LUAD using various online databases, including the GEPIA, Oncomine, and Kaplan-Meier plotter databases. Meanwhile, meta-analyses were performed to verify the expression levels and prognostic effects of TFAP2A in LUAD using the Lung Cancer Explorer (LCE) database. In addition, target genes of TFAP2A were identified in the Animal TFDB3.0 dataset.

Results

Our comprehensively study indicated the mRNA expression levels of TFAP2A in LUAD were significantly higher than that of normal controls. In the survival analyses, higher TFAP2A levels were related to the shortened survival time of patients with LUAD. Meanwhile, the meta-analyses based on the LCE database also suggested the overexpressed TFAP2A led to worsen prognosis of patients with LUAD. Finally, the cell division cycle 6 (CDC6) and aurora kinase A (AURKA) were regarded as two target genes of TFAP2A.

Conclusions

We have performed comprehensive analyses for TFAP2A in patients with LUAD. Patients with higher TFAP2A levels demonstrated worsen prognosis than those with lower TFAP2A levels. The CDC6 and AURKA might be two target genes of TFAP2A. Further molecular biological experiments were required to study the mechanisms of TFAP2A in LUAD.

SUBMITTER: Liao H

PROVIDER: S-EPMC8799082 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Lung cancer is the second most commonly diagnosed carcinoma and is the leading cause of cancer death. Although significant progress has been made towards its understanding and treatment, unraveling the complexities of lung cancer is still hampered by a lack of comprehensive knowledge on the mechanisms underlying the disease. High-throughput and multidimensional genomic data have shed new light on cancer biology. In this study, we developed a network-based approach integrating somatic mutations, the transcriptome, DNA methylation, and protein-DNA interactions to reveal the key regulators in lung adenocarcinoma (LUAD). By combining Bayesian network analysis with tissue-specific transcription factor (TF) and targeted gene interactions, we inferred 15 disease-related core regulatory networks in co-expression gene modules associated with LUAD. Through target gene set enrichment analysis, we identified a set of key TFs, including known cancer genes that potentially regulate the disease networks. These TFs were significantly enriched in multiple cancer-related pathways. Specifically, our results suggest that hepatitis viruses may contribute to lung carcinogenesis, highlighting the need for further investigations into the roles that viruses play in treating lung cancer. Additionally, 13 putative regulatory long non-coding RNAs (lncRNAs), including three that are known to be associated with lung cancer, and nine novel lncRNAs were revealed by our study. These lncRNAs and their target genes exhibited high interaction potentials and demonstrated significant expression correlations between normal lung and LUAD tissues. We further extended our study to include 16 solid-tissue tumor types and determined that the majority of these lncRNAs have putative regulatory roles in multiple cancers, with a few showing lung-cancer specific regulations. Our study provides a comprehensive investigation of transcription factor and lncRNA regulation in the context of LUAD regulatory networks and yields new insights into the regulatory mechanisms underlying LUAD. The novel key regulatory elements discovered by our research offer new targets for rational drug design and accompanying therapeutic strategies.

Project description:The discovery of bladder cancer transcriptional subtypes provides an opportunity to identify high risk patients, and tailor disease management. Recent studies suggest tumor heterogeneity contributes to regional differences in molecular subtype within the tumor, as well as during progression and following treatment. Nonetheless, the transcriptional drivers of the aggressive basal-squamous subtype remain unidentified. As PPARɣ has been repeatedly implicated in the luminal subtype of bladder cancer, we hypothesized inactivation of this transcriptional master regulator during progression results in increased expression of basal-squamous specific transcription factors (TFs) which act to drive aggressive behavior. We initiated a pharmacologic and RNA-seq-based screen to identify PPARɣ-repressed, basal-squamous specific TFs. Hierarchical clustering of RNA-seq data following treatment of three human bladder cancer cells with a PPARɣ agonist identified a number of TFs regulated by PPARɣ activation, several of which are implicated in urothelial and squamous differentiation. One PPARɣ-repressed TF implicated in squamous differentiation identified is Transcription Factor Activating Protein 2 alpha (TFAP2A). We show TFAP2A and its paralog TFAP2C are overexpressed in basal-squamous bladder cancer and in squamous areas of cystectomy samples, and that overexpression is associated with increased lymph node metastasis and distant recurrence, respectively. Biochemical analysis confirmed the ability of PPARɣ activation to repress TFAP2A, while PPARɣ antagonist and PPARɣ siRNA knockdown studies indicate the requirement of a functional receptor. In vivo tissue recombination studies show TFAP2A and TFAP2C promote tumor growth in line with the aggressive nature of basal-squamous bladder cancer. Our findings suggest PPARɣ inactivation, as well as TFAP2A and TFAP2C overexpression cooperate with other TFs to promote the basal-squamous transition during tumor progression.