GDF10 inhibits cell proliferation and epithelial-mesenchymal transition in nasopharyngeal carcinoma by the transforming growth factor-β/Smad and NF-κB pathways

Inflammation accelerating intestinal fibrosis: from mechanism to clinic

Intestinal fibrosis is a prevalent complication of IBD that that can frequently be triggered by prolonged inflammation. Fibrosis in the gut can cause a number of issues, which continue as an ongoing challenge to healthcare systems worldwide. The primary causes of intestinal fibrosis are soluble molecules, G protein-coupled receptors, epithelial-to-mesenchymal or endothelial-to-mesenchymal transition, and the gut microbiota. Fresh perspectives coming from in vivo and in vitro experimental models demonstrate that fibrogenic pathways might be different, at least to some extent, independent of the ones that influence inflammation. Understanding the distinctive procedures of intestinal fibrogenesis should provide a realistic foundation for targeting and blocking specific fibrogenic pathways, estimating the risk of fibrotic consequences, detecting early fibrotic alterations, and eventually allowing therapy development. Here, we first summarize the inflammatory and non-inflammatory components of fibrosis, and then we elaborate on the underlying mechanism associated with multiple cytokines in fibrosis, providing the framework for future clinical practice. Following that, we discuss the relationship between modernization and disease, as well as the shortcomings of current studies. We outline fibrosis diagnosis and therapy, as well as our recommendations for the future treatment of intestinal fibrosis. We anticipate that the global review will provides a wealth of fresh knowledge and suggestions for future fibrosis clinical practice.

Identification and validation of immune-related methylated genes as diagnostic and prognostic biomarkers of nasopharyngeal carcinoma

BACKGROUND

Nasopharyngeal carcinoma (NPC) is a common malignancy occurring in the head and neck. Identification of immune-related methylated biomarkers might be helpful for NPC detection and prognostic evaluation.

METHODS

A co-methylation network based on WGCNA was constructed to identify modules associated with NPC and immune cells. In combination with differentially expressed genes (DEGs) and immune-related genes from ImmPort database, the candidate immune-related methylated genes (IRMGs) were obtained.

RESULTS

Our combined analysis identified 12 IRMGs. Among them, both the methylation and mRNA expression of CCL28, CSK, and PRKCB were correlated with the infiltration of B cells. CD1D, CR2, and GDF10 were favorable markers. Demethylation experiments validated that downregulation of GDF10, PRKCB, SLC40A1, and TGFBR3 in NPC resulted from promoter hypermethylation. Additionally, a diagnostic model was developed and exhibited high discriminative accuracy.

CONCLUSIONS

These results provided a group of immune-related methylated biomarkers that may help with the diagnosis and prognosis of NPC.

Characterizing intergenic transcription at RNA polymerase II binding sites in normal and cancer tissues

Intergenic transcription in normal and cancerous tissues is pervasive but incompletely understood. To investigate this, we constructed an atlas of over 180,000 consensus RNA polymerase II (RNAPII)-bound intergenic regions from 900 RNAPII chromatin immunoprecipitation sequencing (ChIP-seq) experiments in normal and cancer samples. Through unsupervised analysis, we identified 51 RNAPII consensus clusters, many of which mapped to specific biotypes and revealed tissue-specific regulatory signatures. We developed a meta-clustering methodology to integrate our RNAPII atlas with active transcription across 28,797 RNA sequencing (RNA-seq) samples from The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), and Encyclopedia of DNA Elements (ENCODE). This analysis revealed strong tissue- and disease-specific interconnections between RNAPII occupancy and transcriptional activity. We demonstrate that intergenic transcription at RNAPII-bound regions is a novel per-cancer and pan-cancer biomarker. This biomarker displays genomic and clinically relevant characteristics, distinguishing cancer subtypes and linking to overall survival. Our results demonstrate the effectiveness of coherent data integration to uncover intergenic transcriptional activity in normal and cancer tissues.

Silencing of GRHL2 induces epithelial‑to‑mesenchymal transition in lung cancer cell lines with different effects on proliferation and clonogenic growth

Grainyhead-like 2 (GRHL2) is a transcription factor that suppresses epithelial-to-mesenchymal transition (EMT). It has been previously shown that GRHL2 can confer both oncogenic and tumor-suppressive roles in human cancers, including breast, pancreatic and colorectal cancers. However, its role in lung cancer remains elusive. In the present study, a meta-analysis of multiple gene expression datasets with clinical data revealed that GRHL2 expression was increased in lung cancer compared with that in the normal tissues. Copy number analysis of GRHL2, performed using datasets of whole exome sequencing involving 151 lung cancer cell lines, revealed frequent amplifications, suggesting that the increased GRHL2 expression may have resulted from gene amplification. A survival meta-analysis of GRHL2 using The Cancer Genome Atlas (TCGA) dataset showed no association of GRHL2 expression with overall survival. GRHL2 expression was found to be associated with EMT status in lung cancer in TCGA dataset and lung cancer cell lines. GRHL2 knockdown induced partial EMT in the hTERT/Cdk4-immortalized normal lung epithelial cell line HBEC4KT without affecting proliferation measured by CCK-8 assays. In addition, GRHL2 silencing caused three lung cancer cell lines, H1975, H2009 and H441, to undergo partial EMT. However, the proliferative effects differed significantly. GRHL2 silencing promoted proliferation but not colony formation in H1975 cells whilst suppressing colony formation without affecting proliferation in H2009 cells, but it did not affect proliferation in H441 cells. These results suggest cell type-dependent effects of GRHL2 knockdown. Downstream, GRHL2 silencing enhanced the phosphorylation of AKT and ERK, assessed by western blotting with phospho-specific antibodies, in HBEC4KT, H1975 and H2009 cell lines but not in the H441 cell line. By contrast, transient GRHL2 overexpression did not affect A549 cell proliferation, which lack detectable endogenous expression of the GRHL2 protein. However, GRHL2 overexpression did suppress E-cadherin expression in A549 cells. These results suggested that GRHL2 does not only function as a tumor suppressor of EMT but can also behave as an oncogene depending on the lung cancer cell-type context.

Comprehensive Analysis of GDF10 Methylation Site-Associated Genes as Prognostic Markers for Endometrial Cancer

Growth differentiation factor-10 (GDF10) with its methylation trait has recently been found to play a crucial regulatory and communication role in cancers. This investigation aims to identify GDF10 methylation site-associated genes that are closely associated with endometrial cancer (EC) patients' survival based on normal and UCEC samples from the UCSC Xena database. Our study revealed for the first time that EC exhibited significantly higher levels of GDF10 promoter methylation in comparison with normal tissues. Multiple differentiated methylation sites, which have prognostic value due to their apparent survival differences, were found in the GDF10 promoter region. We performed weighted gene coexpression network analysis (WGCNA) on EC tissues and paraneoplastic tissues while using these differentially methylated sites as phenotypes for selecting the most correlated key modules and their internal genes. To obtain a gene set, the key module genes and differentially expressed genes (DEGs) of EC were intersected. The least absolute shrinkage and selection operator (LASSO) regression along with multivariate Cox regression were performed from the gene set and we screened out the key genes B4GALNT3, DNAJC22, and GREB1. Finally, a prognostic model was validated for effectiveness based on these genes. Additionally, Kaplan-Meier analysis and time-dependent receiver operating characteristics (ROC) were applied to assess and verify the model, and they showed good prognosis prediction. Moreover, the differences in risk scores were statistically significant with age, tumor stage, and grade. They may be related to the immune infiltration of tumors as well. In conclusion, based on the methylation-related genes associated with GDF10, we developed a prognosis model for EC patients. It might provide a fresh view for further research and treatment of EC.