ANLN promotes carcinogenesis in oral cancer by regulating the PI3K/mTOR signaling pathway

Hsa_circ_0079875 functions as a competitive endogenous RNA to promote hepatocellular carcinoma progression

Circular RNA (circRNA) can influence the development of hepatocellular carcinoma (HCC) as a competitive endogenous RNA (ceRNA). However, there are still many circRNAs whose functions are unknown. Our research explores the role of a novel circRNA, hsa_circ_0079875, in HCC. The expression of hsa_circ_0079875 in HCC was verified by next-generation sequencing, quantitative reverse transcription-polymerase chain reaction (qRT-PCR), and fluorescence in situ hybridization (FISH). The distribution of hsa_circ_0079875 in HCC cells was investigated by RNA subcellular isolation and FISH assays. The functional effects on HCC proliferation, invasion, migration, cell cycle, and apoptosis were verified by overexpression and knockdown of hsa_circ_0079875. Moreover, xenograft mouse models and immunohistochemistry experiments were used to assess the function of hsa_circ_0079875 in vivo. Hsa_circ_0079875 was up-regulated in HCC tissues and mainly distributed in the cytoplasm. Higher hsa_circ_0079875 leads to larger tumor tissue, more microvascular invasion(MVI) and higher AFP levels, which in turn leads to a poor prognosis. Overexpression of hsa_circ_0079875 can promote the proliferation, migration, and invasion of HCC cells and inhibit apoptosis in vitro and in vivo. Knocking down hsa_circ_0079875 has the opposite effect. Sequencing and biological information predicted the target miRNA and mRNA of hsa_circ_0079875. Further bioinformatics and clinical correlation analysis revealed that hsa_circ_0079875 promote the malignant biological behaviors of HCC through hsa_circ_0079875/miR-519d-59/NRAS ceRNA net. Therefore, hsa_circ_0079875 can be a potential prognostic marker and therapeutic target for HCC.

Dysregulated ANLN reveals immune cell landscape and promotes carcinogenesis by regulating the PI3K/Akt/mTOR pathway in clear cell renal cell carcinoma

Background

Abnormal anillin (ANLN) expression has been observed in multiple tumours and is closely associated with patient prognosis and clinical features. In this study, we systematically elucidated the clinical significance and biological roles of ANLN in patients with clear cell renal cell carcinoma (ccRCC).

Methods

We obtained transcriptome and clinical data of patients with ccRCC from public databases. Multi-omics data and clinical samples were combined to analyse the correlation between ANLN expression and the clinical characteristics of patients with renal cancer. Additionally, the immune cell landscape of ANLN expression was evaluated using different immune algorithms in the tumour microenvironment. The tumour-promoting potential of ANLN was confirmed using in vitro assays, including CCK8 and Transwell assays.

Results

Bioinformatics analysis showed that ANLN is over-expressed in patients with ccRCC, as validated by clinical samples. Publicly available clinical data suggest that high ANLN expression may indicate poor outcomes in patients with ccRCC. Moreover, biological function analysis revealed a marked enrichment of the cell cycle and PI3K-Akt pathways. The distribution of immune cells, particularly M2 macrophages, differed in patients with ccRCC. Furthermore, ANLN silencing inhibited the proliferation, migration, and invasion of renal cancer cells in vitro. After ANLN expression was knocked down in 786-O cells, the protein levels of important PI3K signalling pathway components, including PI3K, Akt, and mTOR, drastically decreased.

Conclusions

These findings suggest that ANLN is dysregulated in renal cancer tissues and promotes tumour progression by activating the PI3K/Akt/mTOR signalling pathway.

ANLN Serves as an Oncogene in Bladder Urothelial Carcinoma via Activating JNK Signaling Pathway

INTRODUCTION

To understand the significance of ANLN (anillin, actin-binding protein)-mediated c-Jun N-terminal kinase (JNK) signal pathway on the progression of bladder urothelial carcinoma (BLCA).

METHODS

The Cancer Genome Atlas (TCGA) database was utilized to perform the clinical significance of ANLN in BLCA. Then, ANLN expression was determined in human normal primary bladder epithelial cells (BdEC) and BLCA cells. Later, ANLN knockdown was performed in BLCA cells, where the expression of MAPK8, MAPK9, and p-JNK/JNK was detected. BLCA cells were divided into the Mock, siNC, siANLN, SP600125 (a selective JNK inhibitor), and ANLN + SP600125 group, followed by measurements of real-time quantitative polymerase chain reaction, 3-4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide, Annexin V-FITC/PI, Wound-healing, Transwell, and immunofluorescence assays.

RESULTS

ANLN was upregulated in the BLCA tissues, which showed a relation with the stage of patients. Besides, BLCA patients with high expression of ANLN had a worse prognosis than those with low expression of ANLN. Besides, the expression of ANLN in the BLCA tissues was positively correlated with MAPK8 and MAPK9. SP600125 suppressed the JNK signal pathway, reduced the proliferation, and increased BLCA cell apoptosis, with the reductions in the invasion and migration and the upregulation of phospho-histone H3 Ser-10 (pHH3), which was abolished by the overexpression of ANLN.

CONCLUSION

ANLN, as an oncogene of BLCA, may associate with the activation of JNK signal pathway. Inhibiting ANLN could deactivate the JNK signal pathway, thereby suppressing the proliferation, invasion, and migration while promoting the apoptosis of BLCA cells.

A network-based dynamic criterion for identifying prediction and early diagnosis biomarkers of complex diseases

Lung adenocarcinoma (LUAD) seriously threatens human health and generally results from dysfunction of relevant module molecules, which dynamically change with time and conditions, rather than that of an individual molecule. In this study, a novel network construction algorithm for identifying early warning network signals (IEWNS) is proposed for improving the performance of LUAD early diagnosis. To this end, we theoretically derived a dynamic criterion, namely, the relationship of variation (RV), to construct dynamic networks. RV infers correlation [Formula: see text] statistics to measure dynamic changes in molecular relationships during the process of disease development. Based on the dynamic networks constructed by IEWNS, network warning signals used to represent the occurrence of LUAD deterioration can be defined without human intervention. IEWNS was employed to perform a comprehensive analysis of gene expression profiles of LUAD from The Cancer Genome Atlas (TCGA) database and the Gene Expression Omnibus (GEO) database. The experimental results suggest that the potential biomarkers selected by IEWNS can facilitate a better understanding of pathogenetic mechanisms and help to achieve effective early diagnosis of LUAD. In conclusion, IEWNS provides novel insight into the initiation and progression of LUAD and helps to define prospective biomarkers for assessing disease deterioration.

Comprehensive bioinformatics analysis reveals the prognostic value, predictive value, and immunological roles of ANLN in human cancers

Anillin (ANLN) is a unique scaffolding, actin-binding protein, which is essential for the integrity and ingression of the cleavage furrow. It is mainly involved in the cytokinesis process, while its role in various tumors has not been fully addressed and remains largely elusive. To provide a thorough perspective of ANLN’s roles among diverse malignancies, we conducted a comprehensive, pan-cancer analysis about ANLN, including but not limited to gene expression levels, prognostic value, biological functions, interacting proteins, immune-related analysis, and predictive value. As a result, when compared to normal tissues, ANLN expression is elevated in most cancers, and its expression also differs in different immune subtypes and molecular subtypes in diverse cancers. In addition, in 17 types of cancer, ANLN expression is increased in early tumor stages, and higher ANLN expression predicts worse survival outcomes in more than ten cancers. Furthermore, ANLN shows close correlations with the infiltration levels of most immune cells, and enrichment analysis using ANLN co-expressed genes reveals that ANLN plays essential roles in cell cycle, mitosis, cellular senescence, and p53 signaling pathways. In the final, ANLN exhibits high accuracy in predicting many cancers, and subsequent multivariate analysis suggests ANLN could be an independent prognostic factor in specific cancer types. Taken together, ANLN is proved to be a novel and promising biomarker for its excellent predictive utility, promising prognostic value, and potential immunological roles in pan-cancer. Targeting ANLN might be an attractive approach to tumor treatment.

IQGAP1 and RNA Splicing in the Context of Head and Neck via Phosphoproteomics

IQGAP1 (IQ motif-containing GTPase-activating protein 1) scaffolds several signaling pathways in mammalian cells that are implicated in carcinogenesis, including the RAS and PI3K pathways that involve multiple protein kinases. IQGAP1 has been shown to promote head and neck squamous cell carcinoma (HNSCC); however, the underlying mechanism(s) remains unclear. Here, we report a mass spectrometry-based analysis identifying differences in phosphorylation of cellular proteins in vivo and in vitro in the presence or absence of IQGAP1. By comparing the esophageal phosphoproteome profiles between Iqgap1+/+ and Iqgap1-/- mice, we identified RNA splicing as one of the most altered cellular processes. Serine/arginine-rich splicing factor 6 (SRSF6) was the protein with the most downregulated levels of phosphorylation in Iqgap1-/- tissue. We confirmed that the absence of IQGAP1 reduced SRSF6 phosphorylation both in vivo and in vitro. We then expanded our analysis to human normal oral keratinocytes. Again, we found factors involved in RNA splicing to be highly altered in the phosphoproteome profile upon genetic disruption of IQGAP1. Both the Clinical Proteomic Tumor Analysis Consortium (CPTAC) and the Cancer Genome Atlas (TCGA) data sets indicate that phosphorylation of splicing-related proteins is important in HNSCC prognosis. The Biological General Repository for Interaction Datasets (BioGRID) repository also suggested multiple interactions between IQGAP1 and splicing-related proteins. Based on these collective observations, we propose that IQGAP1 regulates the phosphorylation of splicing proteins, which potentially affects their splicing activities and, therefore, contributes to HNSCC. Raw data are available from the MassIVE database with identifier MSV000087770.

A Four-Gene Prognostic Signature Based on the TEAD4 Differential Expression Predicts Overall Survival and Immune Microenvironment Estimation in Lung Adenocarcinoma

Background: TEA domain transcription factor 4 (TEAD4) is a member of the transcriptional enhancer factor (TEF) family of transcription factors, which is studied to be linked to the tumorigenesis and progression of various forms of cancers, including lung adenocarcinoma (LUAD). However, the specific function of this gene in the progression of LUAD remains to be explored.

Method: A total of 19 genes related to the Hippo pathway were analyzed to identify the significant genes involved in LUAD progression. The TCGA-LUAD data (n = 585) from public databases were mined, and the differentially expressed genes (DEGs) in patients with the differential level of TEAD4 were identified. The univariate Cox regression, zero LASSO regression coefficients, and multivariate Cox regression were performed to identify the independent prognostic signatures. The immune microenvironment estimation in the two subgroups, including immune cell infiltration, HLA family genes, and immune checkpoint genes, was assessed. The Gene Set Enrichment Analysis (GSEA) and GO were conducted to analyze the functional enrichment of DEGs between the two risk groups. The potential drugs for the high-risk subtypes were forecasted via the mode of action (moa) module of the connectivity map (CMap) database.

Results:TEAD4 was found to be significantly correlated with poor prognosis in LUAD-patients. A total of 102 DEGs in TEAD4-high vs. TEAD4-low groups were identified. Among these DEGs, four genes (CPS1, ANLN, RHOV, and KRT6A) were identified as the independent prognostic signature to conduct the Cox risk model. The immune microenvironment estimation indicated a strong relationship between the high TEAD4 expression and immunotherapeutic resistance. The GSEA and GO showed that pathways, including cell cycle regulation, were enriched in the high-risk group, while immune response-related and metabolism biological processes were enriched in the low-risk group. Several small molecular perturbagens targeting CFTR or PLA2G1B, by the mode of action (moa) modules of the glucocorticoid receptor agonist, cyclooxygenase inhibitor, and NFkB pathway inhibitor, were predicted to be suited for the high-risk subtypes based on the high TEAD4 expression.

Conclusion: The current study revealed TEAD4 is an immune regulation–related predictor of prognosis and a novel therapeutic target for LUAD.