CDA gene silencing regulated the proliferation and apoptosis of chronic myeloid leukemia K562 cells

Circadian Genes MBOAT2/CDA/LPCAT2/B4GALT5 in the Metabolic Pathway Serve as New Biomarkers of PACA Prognosis and Immune Infiltration

Pancreatic cancer (PACA) is a highly malignant tumor with a poor prognosis. Recent studies have discovered substantial differences in the expression levels of several circadian genes in PACA samples compared to normal samples. The goal of this research was to find differentially expressed rhythm genes (DERGs) in PACA samples and determine their role in the development of PACA. A total of 299 DERGs were identified in PACA, including 134 downregulated genes and 165 upregulated genes. DERGs were significantly abundant in the metabolic pathway and immune response pathways, according to GO and KEGG analyses. Survival analyses showed that PACA patients who had higher expression levels of MBOAT2/CDA/LPCAT2/B4GALT5 had shorter overall survival times. Using cell assay verification, the mRNA levels of MBOAT2/CDA/LPCAT2/B4GALT5 in Patu-8988 and PNAC-1 cells were found to be significantly higher than those in HPDE6-C7 cells, which was in line with previous studies on PACA patient data. Through conducting univariate Cox analysis, it was determined that MBOAT2/CDA/LPCAT2/B4GALT5 expression, age and grade were all high-risk factors. The MBOAT2/CDA/LPCAT2/B4GALT5 genes were independently correlated with overall survival, according to the multivariate Cox analysis. The proportion of immune cells in PACA and normal samples significantly changed, according to the immune infiltration analysis. Furthermore, MBOAT2/CDA/LPCAT2/B4GALT5 expression levels were significantly related to the level of immune cell infiltration. The protein-protein interaction network of the MBOAT2/CDA/LPCAT2/B4GALT5 genes included 54 biological nodes and 368 interacting genes. In conclusion, the finding of these DERGs adds to the investigation of the molecular processes underlying the onset and progression of PACA. In the future, DERGs may serve as prognostic and diagnostic biomarkers as well as drug targets for chronotherapy in PACA patients.

Transcriptome profiling of osteoclast subsets associated with arthritis: A pathogenic role of CCR2hi osteoclast progenitors

Introduction

The existence of different osteoclast progenitor (OCP) subsets has been confirmed by numerous studies. However, pathological inflammation-induced osteoclastogenesis remains incompletely understood. Detailed characterization of OCP subsets may elucidate the pathophysiology of increased osteoclast activity causing periarticular and systemic bone resorption in arthritis. In our study, we rely on previously defined OCP subsets categorized by the level of CCR2 expression as circulatory-like committed CCR2^hi OCPs, which are substantially expanded in arthritis, and marrow-resident CCR2^lo OCPs of immature phenotype and behavior.

Methods

In order to perform transcriptome characterization of those subsets in the context of collagen-induced arthritis (CIA), we sorted CCR2^hi and CCR2^lo periarticular bone marrow OCPs of control and arthritic mice, and performed next-generation RNA sequencing (n=4 for each group) to evaluate the differential gene expression profile using gene set enrichment analysis with further validation.

Results

A disparity between CCR2^hi and CCR2^lo subset transcriptomes (863 genes) was detected, with the enrichment of pathways for osteoclast differentiation, chemokine and NOD-like receptor signaling in the CCR2^hi OCP subset, and ribosome biogenesis in eukaryotes and ribosome pathways in the CCR2^lo OCP subset. The effect of intervention (CIA) within each subset was greater in CCR2^hi (92 genes) than in CCR2^lo (43 genes) OCPs. Genes associated with the osteoclastogenic pathway (Fcgr1, Socs3), and several genes involved in cell adhesion and migration (F11r, Cd38, Lrg1) identified the CCR2^hi subset and distinguish CIA from control group, as validated by qPCR (n=6 for control mice, n=9 for CIA mice). The latter gene set showed a significant positive correlation with arthritis clinical score and frequency of CCR2^hi OCPs. Protein-level validation by flow cytometry showed increased proportion of OCPs expressing F11r/CD321, CD38 and Lrg1 in CIA, indicating that they could be used as disease markers. Moreover, osteoclast pathway-identifying genes remained similarly expressed (Fcgr1) or even induced by several fold (Socs3) in preosteoclasts differentiated in vitro from CIA mice compared to pre-cultured levels, suggesting their importance for enhanced osteoclastogenesis of the CCR2^hi OCPs in arthritis.

Conclusion

Our approach detected differentially expressed genes that could identify distinct subset of OCPs associated with arthritis as well as indicate possible therapeutic targets aimed to modulate osteoclast activity.

Metabolic syndrome related gene signature predicts the prognosis of patients with pancreatic ductal carcinoma. A novel link between metabolic dysregulation and pancreatic ductal carcinoma

Background

Pancreatic cancer is one of the most common malignancies worldwide. In recent years, specific metabolic activities, which involves the development of tumor, caused wide public concern. In this study, we wish to explore the correlation between metabolism and progression of tumor.

Methods

A retrospective analysis including 95 patients with pancreatic ductal adenocarcinoma (PDAC) and PDAC patients from The Cancer Genome Atlas (TCGA), the International Cancer Genome Consortium (ICGC), and The Gene Expression Omnibus (GEO) database were involved in our study. Multivariate Cox regression analysis was used to construct the prognosis model. The potential connection between metabolism and immunity of PDAC was investigated through a weighted gene co-expression network analysis (WGCNA). 22 types of Tumor-infiltrating immune cells (TIICs) between high-risk and low-risk groups were estimated through CIBERSORT. Moreover, the potential immune-related signaling pathways between high-risk and low-risk groups were explored through the gene set enrichment analysis (GSEA). The role of key gene GMPS in developing pancreatic tumor was further investigated through CCK-8, colony-information, and Transwell.

Results

The prognostic value of the MetS factors was analyzed using the Cox regression model, and a clinical MetS-based nomogram was established. Then, we established a metabolism-related signature to predict the prognosis of PDAC patients based on the TCGA databases and was validated in the ICGC database and the GEO database to find the distinct molecular mechanism of MetS genes in PDAC. The result of WGCNA showed that the blue module was associated with risk score, and genes in the blue module were found to be enriched in the immune-related signaling pathway. Furthermore, the result of CIBERSORT demonstrated that proportions of T cells CD8, T cells Regulatory, Tregs NK cells Activated, Dendritic cells Activated, and Mast cells Resting were different between high-risk and low-risk groups. These differences are potential causes of different prognoses of PDAC patients. GSEA and the protein–protein interaction network (PPI) further revealed that our metabolism-related signature was significantly enriched in immune‐related biological processes. Moreover, knockdown of GMPS in PDAC cells suppressed proliferation, migration, and invasion of tumor cells, whereas overexpression of GMPS performed oppositely.

Conclusion

The results shine light on fundamental mechanisms of metabolic genes on PDAC and establish a reliable and referable signature to evaluate the prognosis of PDAC. GMPS was identified as a potential candidate oncogene with in PDAC, which can be a novel biomarker and therapeutic target for PDAC treatment.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-02378-w.