FOSL1 enhances growth and metastasis of human prostate cancer cells through epithelial mesenchymal transition pathway

MiR-33a targets FOSL1 and EN2 as a clinical prognostic marker for sarcopenia by glioma

To determine the relationship between glioma and muscle aging and to predict prognosis by screening for co-expressed genes, this study examined the relationship between glioma and sarcopenia. The study identified eight co-downregulated miRNAs, three co-upregulated miRNAs, and seven genes associated with overall glioma survival, namely, KRAS, IFNB1, ALCAM, ERBB2, STAT3, FOSL1, and EN2. With a multi-factor Cox regression model incorporating FOSL1 and EN2, we obtained ROC curves of 0.702 and 0.709, respectively, suggesting that glioma prognosis can be predicted by FOSL1 and EN2, which are differentially expressed in both cancer and aged muscle. FOSL1 and EN2 were analyzed using Gene Set Enrichment Analysis to identify possible functional pathways. RT-qPCR and a dual-luciferase reporter gene system verified that hsa-miR-33a targets FOSL1 and EN2. We found that hsa-mir-33a co-targeting FOSL1 and EN2 has a good predictive value for glioblastoma and skeletal muscle reduction.

Silencing of FOS-like antigen 1 represses restenosis via the ERK/AP-1 pathway in type 2 diabetic mice

Restenosis is a major limiting factor for a successful outcome in type 2 diabetes (T2D) patients undergoing percutaneous coronary intervention (PCI). The aim of this study is to explore the role and regulatory mechanism of FOS-like antigen 1 (FOSL1) in restenosis in T2D. A T2D with restenosis mouse model was established by the combination of high-fat diet and streptozotocin injection and by wire-injury. High glucose (HG)-treated vascular smooth muscle cells (VSMCs) were used to mimic T2D in vitro. The results of quantitative real time PCR and western blotting demonstrated that the expression of FOSL1 was increased not only in T2D mice or HG-induced VSMCs, but also in T2D mice that underwent wire-injury. HE staining revealed that FOSL1 knockdown significantly reduced the intimal/media ratio of T2D mice after wire-injury. Silencing of FOSL1 reversed the promoting effects of HG treatment on viability, migration and inflammation reactions, and the inhibiting effect on the apoptosis of VSMCs. Inhibition of ERK/AP-1 pathway obtained similar patterns in HG-induced VSMCs. The activation of ERK/AP-1 pathway reversed the influence of FOSL1 knockdown on HG-induced VSMCs. Our findings indicate that silencing of FOSL1 may suppress restenosis via regulation of the ERK/AP-1 pathway in T2D mice, pointing out a potential therapeutic target to prevent restenosis in T2D.

Signature identification of relapse-related overall survival of early lung adenocarcinoma after radical surgery

Background

The widespread use of low-dose chest CT screening has improved the detection of early lung adenocarcinoma. Radical surgery is the best treatment strategy for patients with early lung adenocarcinoma; however, some patients present with postoperative recurrence and poor prognosis. Through this study, we hope to establish a model that can identify patients that are prone to recurrence and have poor prognosis after surgery for early lung adenocarcinoma.

Materials and Methods

We screened prognostic and relapse-related genes using The Cancer Genome Atlas (TCGA) database and the GSE50081 dataset from the Gene Expression Omnibus (GEO) database. The GSE30219 dataset was used to further screen target genes and construct a risk prognosis signature. Time-dependent ROC analysis, calibration degree analysis, and DCA were used to evaluate the reliability of the model. We validated the TCGA dataset, GSE50081, and GSE30219 internally. External validation was conducted in the GSE31210 dataset.

Results

A novel four-gene signature (INPP5B, FOSL2, CDCA3, RASAL2) was established to predict relapse-related survival outcomes in patients with early lung adenocarcinoma after surgery. The discovery of these genes may reveal the molecular mechanism of recurrence and poor prognosis of early lung adenocarcinoma. In addition, ROC analysis, calibration analysis and DCA were used to verify the genetic signature internally and externally. Our results showed that our gene signature had a good predictive ability for recurrence and prognosis.

Conclusions

We established a four-gene signature and predictive model to predict the recurrence and corresponding survival rates in patients with early lung adenocarcinoma after surgery. These may be helpful for reforumulating post-operative consolidation treatment strategies.

SMAD4 represses FOSL1 expression and pancreatic cancer metastatic colonization

Metastasis is a complex and poorly understood process. In pancreatic cancer, loss of the transforming growth factor (TGF)-β/BMP effector SMAD4 is correlated with changes in altered histopathological transitions, metastatic disease, and poor prognosis. In this study, we use isogenic cancer cell lines to identify SMAD4 regulated genes that contribute to the development of metastatic colonization. We perform an in vivo screen identifying FOSL1 as both a SMAD4 target and sufficient to drive colonization to the lung. The targeting of these genes early in treatment may provide a therapeutic benefit.

Identification and Validation of a Six Immune-Related Genes Signature for Predicting Prognosis in Patients With Stage II Colorectal Cancer

Background

Immune-related genes (IRGs) play important roles in the tumor immune microenvironment and can affect the prognosis of cancer. This study aimed to construct a novel IRG signature for prognostic evaluation of stage II colorectal cancer (CRC).

Methods

Gene expression profiles and clinical data for stage II CRC patients were collected from the Cancer Genome Atlas and Gene Expression Omnibus database. Univariate, multivariate Cox regression, and least absolute shrinkage and selection operator regression were used to develop the IRG signature, namely IRGCRCII. A nomogram was constructed, and the “Cell Type Identification by Estimating Relative Subsets of RNA Transcripts” (CIBERSORT) method was used to estimate immune cell infiltration. The expression levels of genes and proteins were validated by qRT-PCR and immunohistochemistry in 30 pairs of primary stage II CRC and matched normal tissues.

Results

A total of 466 patients with stage II CRC were included, and 274 differentially expressed IRGs were identified. Six differentially expressed IRGs were detected and used to construct the IRGCRCII signature, which could significantly stratify patients into high-risk and low-risk groups in terms of disease-free survival in three cohorts: training, test, and external validation (GSE39582). Receiver operating characteristics analysis revealed that the area under the curves of the IRGCRCII signature were significantly greater than those of the OncotypeDX colon signature at 1 (0.759 vs. 0.623), 3 (0.875 vs. 0.629), and 5 years (0.906 vs. 0.698) disease-free survival, respectively. The nomogram performed well in the concordance index (0.779) and calibration curves. The high-risk group had a significantly higher percentage of infiltrated immune cells (e.g., M2 macrophages, plasma cells, resting mast cells) than the low-risk group. Finally, the results of qRT-PCR and immunohistochemistry experiments performed on 30 pairs of clinical specimens were consistent with bioinformatics analysis.

Conclusion

This study developed and validated a novel immune prognostic signature based on six differentially expressed IRGs for predicting disease-free survival and immune status in patients with stage II CRC, which may reflect immune dysregulation in the tumor immune microenvironment.

Preclinical analysis of novel prognostic transcription factors and immune-related gene signatures for bladder cancer via TCGA-based bioinformatic analysis

Bladder cancer (BLCA) is a common malignancy of human urinary tract, whose prognosis is influenced by complex gene interactions. Immune response activity can act as a potential prognostic factor in BLCA. The present study established a prognostic model, based on the identification of tumor transcription factors (TFs) and immune-related genes (IRGs), and further explored their therapeutic potential in BLCA. The enrichment scores of 29 IRG sets, identified in The Cancer Genome Atlas BLCA tumor samples, were quantified by single-sample Gene Set Enrichment Analysis. The abundance of infiltrated immune cells in tumor tissues was determined using the Estimating Relative algorithm. Tumor-related TFs and IRGs signatures were retrieved using Least Absolute Shrinkage and Selection Operator Cox regression analysis. A prognostic gene network was built using Pearson's correlation analysis as a means of predicting the regulatory relationship between prognostic TFs and IRGs. A nomogram was devised to also predict the overall survival (OS) rate of patients with BLCA. Based on the Genomics of Drug Sensitivity in Cancer data, potential therapeutic drugs were identified upon analyzing the relationship between the expression level of prognostic genes and respective IC₅₀ values. In vitro experiments were implemented for further validation. Respective TF binding profiles were acquired from the JASPAR 2020 database. The elevated infiltration of CD8⁺ T Cells was correlated with an improved OS of patients with BLCA. An innovative prognostic model for BLCA was then constructed that composed of nine putative gene markers: CXCL13, prepronociceptin, microtubule-associated protein tau, major histocompatibility class I polypeptide-related sequence B, prostaglandin E2 receptor EP3 subtype, IL20RA, proepiregulin, early growth response protein 1 and FOS-related antigen 1 (FOSL1). Furthermore, a theoretical basis for the correlation between the prognostic TFs and IRGs was reported. For this, 10 potentially effective drugs targeting the TFs in the present model for patients with BLCA were identified. It was then verified that downregulation of FOSL1 can lead to an enhanced sensitivity of the TW37 in T24 bladder cancer cells. Overall, the present prognostic model demonstrated a robust capability of predicting OS of patients with BLCA. Hence, the gene markers identified could be applied for targeted therapies against BLCA.

Expression and function of FRA1 protein in tumors

AP-1 is a dimeric complex that is composed of JUN, FOS, ATF and MAF protein families. FOS-related antigen 1 (FRA1) which encoded by FOSL1 gene, belongs to the FOS protein family, and mainly forms an AP-1 complex with the protein of the JUN family to exert an effect. Regulation of FRA1 occurs at levels of transcription and post-translational modification, and phosphorylation is the major post-translational modification. FRA1 is mainly regulated by the mitogen-activated protein kinases signaling pathway and is degraded by ubiquitin-independent proteasomes. FRA1 can affect biological functions, such as tumor proliferation, differentiation, invasion and apoptosis. Studies have demonstrated that FRA1 is abnormally expressed in many tumors and plays a relevant role, but the specific condition varies from the target organs. FRA1 is overexpressed in breast cancer, lung cancer, colorectal cancer, prostate cancer, nasopharyngeal cancer, thyroid cancer and other tumors. However, the expression of FRA1 is decreased in cervical cancer, and the expression of FRA1 in ovarian cancer and oral squamous cell carcinoma is still controversial. In this review, we present a detailed description of the regulatory factors and functions of FRA1, also, the expression of FRA1 in various tumors and its function in relative tumor.