DNTTIP2 Expression is Associated with Macrophage Infiltration and Malignant Characteristics in Low-Grade Glioma

Depletion of DNTTIP2 Induces Cell Cycle Arrest in Pancreatic Cancer Cells

BACKGROUND/AIM

Pancreatic cancer is one of the most lethal malignant cancers worldwide and the seventh most common cause of cancer-related death in both sexes. Herein, we analyzed open access data and discovered that expression of a gene called deoxynucleotidyltransferase terminal-interacting protein 2 (DNTTIP2) is linked to prognosis of pancreatic ductal adenocarcinoma (PDAC). We then elucidated the role of DNTTIP2 in the proliferation of pancreatic cancer cells in vitro.

MATERIALS AND METHODS

A WST-8 assay, cell cycle analysis, Annexin-V staining, quantitative reverse transcription-PCR, and western blot analysis were conducted to assess cell proliferation, cell cycle, apoptosis, and expression of DNTTIP2 mRNA and protein, respectively, in DNTTIP2-depleteted MIA-PaCa-2 and PK-1 cells.

RESULTS

Depletion of DNTTIP2 induced G1 arrest in MIA-PaCa-2 cells by decreasing expression of special AT-rich sequence binding protein 1 (SATB1) and cyclin-dependent kinase 6 (CDK6). In addition, depletion of DNTTIP2 induced G2 arrest in PK-1 cells by decreasing expression of CDK1. Depletion of DNTTIP2 did not induce apoptosis in MIA-PaCa-2 or PK-1 cells.

CONCLUSION

DNTTIP2 is involved in proliferation of pancreatic cancer cells. Thus, DNTTIP2 is a potential target for inhibiting progression of pancreatic cancers.

PLEKHA4 is a novel prognostic biomarker that reshapes the tumor microenvironment in lower-grade glioma

Background

Lower-grade glioma (LGG) is a primary intracranial tumor that carry a high risk of malignant transformation and limited therapeutic options. Emerging evidence indicates that the tumor microenvironment (TME) is a superior predictor for tumor progression and therapy response. PLEKHA4 has been demonstrated to be a biomarker for LGG that correlate with immune infiltration. However, the fundamental mechanism by which PLEKHA4 contributes to LGG is still poorly understood.

Methods

Multiple bioinformatic tools, including Tumor Immune Estimation Resource (TIMER), Gene Expression Profiling Interactive Analysis (GEPIA2), Shiny Methylation Analysis Resource Tool (SMART), etc., were incorporated to analyze the PLEKHA4. ESTIMATE, ssGSEA, CIBERSORT, TIDE and CellMiner algorithms were employed to determine the association of PLEKHA4 with TME, immunotherapy response and drug sensitivities. Immunohistochemistry (IHC)-based tissue microarrays and M2 macrophage infiltration assay were conducted to verify their associations.

Results

PLEKHA4 expression was found to be dramatically upregulated and strongly associated with unfavorable overall survival (OS) and disease-specific survival (DSS) in LGG patients, as well as their poor clinicopathological characteristics. Cox regression analysis identified that PLEKHA4 was an independent prognostic factor. Methylation analysis revealed that DNA methylation correlates with PLEKHA4 expression and indicates a better outcome in LGG. Moreover, PLEKHA4 was remarkably correlated with immune responses and TME remodeling, as evidenced by its positive correlation with particular immune marker subsets and the putative infiltration of immune cells. Surprisingly, the proportion of M2 macrophages in TME was strikingly higher than others, inferring that PLEKHA4 may regulate the infiltration and polarization of M2 macrophages. Evidence provided by IHC-based tissue microarrays and M2 macrophage infiltration assay further validated our findings. Moreover, PLEKHA4 expression was found to be significantly correlated with chemokines, interleukins, and their receptors, further supporting the critical role of PLEKHA4 in reshaping the TME. Additionally, we found that PLEKHA4 expression was closely associated with drug sensitivities and immunotherapy responses, indicating that PLEKHA4 expression also had potential clinical significance in guiding immunotherapy and chemotherapy in LGG.

Conclusion

PLEKHA4 plays a pivotal role in reshaping the TME of LGG patients, and may serve as a potential predictor for LGG prognosis and therapy.

M2 macrophage marker CHI3L2 could serve as a potential prognostic and immunological biomarker in glioma by integrated single-cell and bulk RNA-Seq analysis

BACKGROUND

CHI3L2 plays a crucial role in multiple cancers, but its importance in glioma remains unclear. Hence, we comprehensively integrated bulk RNA-sequencing (RNA-seq), proteomics and single-cell RNA-seq (scRNA-seq) to determine the roles of CHI3L2 in gliomas.

METHODS

Bulk RNA-seq, proteomics and scRNA-seq data of CHI3L2 in glioma were obtained from online databases. The quantitative real-time polymerase chain reaction (qRT-PCR) and immunohistochemistry (IHC) were conducted to verify the CHI3L2 expression. Then, univariate and multivariate Cox regression analyses, Norman charts and gene set enrichment analysis (GSEA) were performed. Finally, the associations between CHI3L2 and tumor immunity were explored.

RESULTS

The expression of CHI3L2 was markedly higher in glioma cancers compared with normal tissues from analysis of the data of the Cancer Genome Atlas and Chinese Glioma Genome Atlas datasets and as verified by GSE4290, GSE50161, qRT-PCR and IHC results (p < 0.05). High expression of CHI3L2 suggested poor overall survival (OS) prognosis in gliomas (p < 0.05). CHI3L2 might also serve as an independent predictor of OS for gliomas (p < 0.05) and we also constructed a Norman chart to predict these patients' survival prognosis with good performance. GSEA analysis showed that CHI3L2 might be involved with eight pathways in gliomas. Regarding tumor immunity, CHI3L2 was found to be significantly involved with immune cell infiltration levels of low-grade glioma, the tumor immune microenvironment, immune checkpoints and immune cells in both low-grade glioma and glioblastoma (p < 0.05). Additionally, scRNA-seq data for CHI3L2 in glioma from the TISCH2 website showed that CHI3L2 is mainly expressed in astrocytes, endothelial cells, CD8+ T cells, mono/macrophage cells, etc. CONCLUSIONS: CHI3L2 presents prognostic and immunological values in glioma, providing novel therapeutic targets for glioma patients.

High Expression of DNTTIP1 Predicts Poor Prognosis in Clear Cell Renal Cell Carcinoma

Background

Invasion and metastasis led to poor prognosis and death of clear cell renal cell carcinoma (ccRCC) patients. The deoxynucleotidyl transferase terminal interacting protein 1 (DNTTIP1) was reported to promote multiple tumor progression. However, there is no research about DNTTIP1 in ccRCC.

Methods

Kaplan-Meier survival analysis, multivariate analysis demonstrated the prognostic indicator in overall survival (OS) and disease-free survival (DFS) of ccRCC with DNTTIP1 expression in the Cancer Genome Atlas Kidney Clear Cell Carcinoma (TCGA-KIRC). Receiver operator characteristic (ROC) curve analyzed diagnostic ability of DNTTIP1 in TCGA-KIRC and validation dataset. The quantitative real-time polymerase chain reaction (qRT-PCR) detected the DNTTIP1 expression in renal cancer tissues, and the Office of Cancer Clinical Proteomics Research (CPTAC) verified the protein expression of DNTTIP1. Moreover, nomogram predicted the role of DNTTIP1 in ccRCC patient. Single-sample Gene Set Enrichment Analysis (SsGSEA) and GSEA evaluated the pathogenesis role of DNTTIP1 in TCGA-KIRC.

Results

DNTTIP1 expression was higher in ccRCC tumor tissues. High expression of DNTTIP1 was associated with poor OS (HR = 1.618, P < 0.0001), and poor DFS (HR = 1.789, P < 0.0001). SsGSEA and GSEA showed DNTTIP1 was associated with hypoxia, epithelial-mesenchymal transition (EMT), angiogenesis, G2M checkpoint. DNTTIP1 had a positive correlation with EMT biomarkers in ccRCC, and might be an effective target for ccRCC.

Conclusion

This study provided that higher expression of DNTTIP1 predicted poor prognosis in ccRCC, and DNTTIP1 might be a novel detection biomarker and therapeutic target of tumor malignant in the future.

Advances in the role of STAT3 in macrophage polarization

The physiological processes of cell growth, proliferation, differentiation, and apoptosis are closely related to STAT3, and it has been demonstrated that aberrant STAT3 expression has an impact on the onset and progression of a number of inflammatory immunological disorders, fibrotic diseases, and malignancies. In order to produce the necessary biological effects, macrophages (M0) can be polarized into pro-inflammatory (M1) and anti-inflammatory (M2) types in response to various microenvironmental stimuli. STAT3 signaling is involved in macrophage polarization, and the research of the effect of STAT3 on macrophage polarization has gained attention in recent years. In order to provide references for the treatment and investigation of disorders related to macrophage polarization, this review compiles the pertinent signaling pathways associated with STAT3 and macrophage polarization from many fundamental studies.