TEAD4 Nuclear Localization and Regulation by miR-4269 and miR-1343-3p in Colorectal Carcinoma

Exosomal ssc-miR-1343 targets FAM131C to regulate porcine epidemic diarrhea virus infection in pigs

The porcine epidemic diarrhea virus (PEDV) causes diarrhea in piglets, thereby causing very significant economic losses for the global swine industry. In previous studies, it has been confirmed that microRNAs (miRNAs) play an important role in the infection caused by PEDV. However, the precise molecular mechanism of miRNAs in the regulation of PEDV infection is still not fully understood. In the present study, we utilized miRNA-seq analysis to identify ssc-miR-1343 with differential expression between PEDV-infected and normal piglets. The expression of ssc-miR-1343 was detected in isolated exosomes, and it was found to be significantly higher than that in the controls following PEDV infection. The ssc-miR-1343 mimic was found to decrease PEDV replication, whereas the ssc-miR-1343 inhibitor was observed to increase PEDV replication, and ssc-miR-1343 was delivered by exosomes during PEDV infection. Mechanistically, ssc-miR-1343 binds to the 3'UTR region of FAM131C, down-regulating its expression, and FAM131C has been shown to enhance PEDV replication through simultaneously suppressing pathways associated with innate immunity. The ssc-miR-1343/FAM131C axis was found to upregulate the host immune response against PEDV infection. In conclusion, our findings indicate that the transport of ssc-miR-1343 in exosomes is involved in PEDV infection. This discovery presents a new potential target for the development of drugs to treat PEDV.

TFAP2C exacerbates psoriasis-like inflammation by promoting Th17 and Th1 cells activation through regulating TEAD4 transcription

BACKGROUND

Psoriasis is one of the chronic and autoimmune skin diseases. It is important to uncover the mechanisms underlying the psoriasis. Transcription factor activator protein (TFAP-2) gamma, also known as AP2-gamma, is a protein encoded by the TFAP2C gene. Immune-mediated pathophysiological processes could be linked to psoriasis, but the mechanism is still unclear. Therefore, to date the cause of psoriasis has not been understood completely.

MATERIALS AND METHODS

Psoriasis is a complex disease triggered by genetic, immunological, and environmental stimuli. Keratinocytes play an important role in both initiation and maintenance phases of psoriasis. A psoriatic keratinocyte model was established by stimulating high sensitivity of human epidermal keratinocytes (HaCaT) to topoisomerase inhibitor cell lines using the accumulation of M5 cytokines comprising interleukin (IL)-17A, IL-22, oncostatin M, IL-1α, and tumor necrosis factor-α (TNF-α). The TFAP2C and transcriptional enhanced associate domain 4 (TEAD4) genes expression was evaluated by reverse transcription-quantitative polymerase chain reaction. Western blot analysis was used to examine protein expression. Cell viability (quantitative) of keratinocytes, including cytotoxicity, proliferation, and cell activation, was evaluated by the MTT assay. The relative percentage values of interleukin (IL)-17a, interferon gamma, and IL-4+ cells were measured by flow cytometry. Accordingly, chromatin immunoprecipitation and luciferase reporter assays were applied to evaluate the binding affinity of TFAP2C and TEAD4 promoter.

RESULTS

Level of the TFAP2C gene was elevated in the lesional skin of psoriasis patients. On the other hand, silencing of the TFAP2C gene suppressed the proliferation and inflammatory response in M5-induced keratinocytes. In addition, inhibition of TFAP2C alleviated imiquimod (IMQ)-induced skin injury in mice model. We also observed that suppression of TFAP2C inhibited the activation of T-helper 17 (Th17) and Th1 cells in IMQ-induced mice model. Mechanically, TFAP2C promoted TEAD4 transcriptional activation.

CONCLUSION

TFAP2C exacerbated psoriasis-like inflammation by increasing the activation of Th17 and Th1 cells by regulating TEAD4 transcription. This finding clearly indicated that TFAP2C could be considered a valuable biomarker for the prevention and treatment for psoriasis.

Comprehensive molecular analyses of an autoimmune-related gene predictive model and immune infiltrations using machine learning methods in moyamoya disease

Background: Growing evidence suggests the links between moyamoya disease (MMD) and autoimmune diseases. However, the molecular mechanism from genetic perspective remains unclear. This study aims to clarify the potential roles of autoimmune-related genes (ARGs) in the pathogenesis of MMD. Methods: Two transcription profiles (GSE157628 and GSE141025) of MMD were downloaded from GEO databases. ARGs were obtained from the Gene and Autoimmune Disease Association Database (GAAD) and DisGeNET databases. Differentially expressed ARGs (DEARGs) were identified using "limma" R packages. GO, KEGG, GSVA, and GSEA analyses were conducted to elucidate the underlying molecular function. There machine learning methods (LASSO logistic regression, random forest (RF), support vector machine-recursive feature elimination (SVM-RFE)) were used to screen out important genes. An artificial neural network was applied to construct an autoimmune-related signature predictive model of MMD. The immune characteristics, including immune cell infiltration, immune responses, and HLA gene expression in MMD, were explored using ssGSEA. The miRNA-gene regulatory network and the potential therapeutic drugs for hub genes were predicted. Results: A total of 260 DEARGs were identified in GSE157628 dataset. These genes were involved in immune-related pathways, infectious diseases, and autoimmune diseases. We identified six diagnostic genes by overlapping the three machine learning algorithms: CD38, PTPN11, NOTCH1, TLR7, KAT2B, and ISG15. A predictive neural network model was constructed based on the six genes and presented with great diagnostic ability with area under the curve (AUC) = 1 in the GSE157628 dataset and further validated by GSE141025 dataset. Immune infiltration analysis showed that the abundance of eosinophils, natural killer T (NKT) cells, Th2 cells were significant different between MMD and controls. The expression levels of HLA-A, HLA-B, HLA-C, HLA-DMA, HLA-DRB6, HLA-F, and HLA-G were significantly upregulated in MMD. Four miRNAs (mir-26a-5p, mir-1343-3p, mir-129-2-3p, and mir-124-3p) were identified because of their interaction at least with four hub DEARGs. Conclusion: Machine learning was used to develop a reliable predictive model for the diagnosis of MMD based on ARGs. The uncovered immune infiltration and gene-miRNA and gene-drugs regulatory network may provide new insight into the pathogenesis and treatment of MMD.

Somatic mutations in FAT cadherin family members constitute an underrecognized subtype of colorectal adenocarcinoma with unique clinicopathologic features

BACKGROUND

The FAT cadherin family members (FAT1, FAT2, FAT3 and FAT4) are conserved tumor suppressors that are recurrently mutated in several types of human cancers, including colorectal carcinoma (CRC).

AIM

To characterize the clinicopathologic features of CRC patients with somatic mutations in FAT cadherin family members.

METHODS

We analyzed 526 CRC cases from The Cancer Genome Atlas PanCancer Atlas dataset. CRC samples were subclassified into 2 groups based on the presence or absence of somatic mutations in FAT1, FAT2, FAT3 and FAT4. Individual clinicopathological data were collected after digital slide review. Statistical analysis was performed using t tests and chi-square tests.

RESULTS

This CRC study cohort had frequent mutations in the FAT1 (10.5%), FAT2 (11.2%), FAT3 (15.4%) and FAT4 (23.4%) genes. Two hundred CRC patients (38.0%) harbored somatic mutations in one or more of the FAT family genes and were grouped into the FAT mutated CRC subtype. The FAT-mutated CRC subtype was more commonly located on the right side of the colon (51.0%) than in the rest of the cohort (30.1%, P < 0.001). It showed favorable clinicopathologic features, including a lower rate of positive lymph nodes (pN1-2: 33.5% vs 46.4%, P = 0.005), a lower rate of metastasis to another site or organ (pM1: 7.5% vs 16.3%, P = 0.006), and a trend toward an early tumor stage (pT1-2: 25.0% vs 18.7%, P = 0.093). FAT somatic mutations were significantly enriched in microsatellite instability CRC (28.0% vs 2.1%, P < 0.001). However, FAT somatic mutations in microsatellite stable CRC demonstrated similar clinicopathologic behaviors, as well as a trend of a better disease-free survival rate (hazard ratio = 0.539; 95% confidence interval: 0.301-0.967; log-rank P = 0.073).

CONCLUSION

FAT cadherin family genes are frequently mutated in CRC, and their mutation profile defines a subtype of CRC with favorable clinicopathologic characteristics.

Transcriptional regulation of nuclear miRNAs in tumorigenesis (Review)

MicroRNAs (miRNAs/miRs) are a type of endogenous non‑coding small RNA that regulates gene expression. miRNAs regulate gene expression at the post‑transcriptional level by targeting the 3'‑untranslated region (3'UTR) of cytoplasmic messenger RNAs (mRNAs). Recent research has confirmed the presence of mature miRNAs in the nucleus, which bind nascent RNA transcripts, gene promoter or enhancer regions, and regulate gene expression via epigenetic pathways. Some miRNAs have been shown to function as oncogenes or tumor suppressor genes by modulating molecular pathways involved in human cancers. Notably, a novel molecular mechanism underlying the dysregulation of miRNA expression in cancer has recently been discovered, indicating that miRNAs may be involved in tumorigenesis via a nuclear function that influences gene transcription and epigenetic states, elucidating their potential therapeutic implications. The present review article discusses the import of nuclear miRNAs, nucleus‑cytoplasm transport mechanisms and the nuclear functions of miRNAs in cancer. In addition, some software tools for predicting miRNA binding sites are also discussed. Nuclear miRNAs supplement miRNA regulatory networks in cancer as a non‑canonical aspect of miRNA action. Further research into this aspect may be critical for understanding the role of nuclear miRNAs in the development of human cancers.