Bioinformatics Tools for Bulk Gene Expression Deconvolution in Diabetic Retinopathy.

Retinal neovascularization is one of the leading causes of vision loss and a hallmark of proliferative diabetic retinopathy (PDR). The immune system is observed to be involved in the pathogenesis of diabetic retinopathy (DR). The specific immune cell type that contributes to retinal neovascularization can be identified via a bioinformatics analysis of RNA sequencing (RNA-seq) data, known as deconvolution analysis. Previous study has identified the infiltration of macrophages in the retina of rats with hypoxia-induced retinal neovascularization and patients with PDR through a deconvolution algorithm, known as CIBERSORTx. Here, we describe the protocols of using CIBERSORTx to perform the deconvolution analysis and downstream analysis of RNA-seq data.

FOXD3-induced miR-133a blocks progression and metastasis of colorectal cancer through regulating UBA2.

Background and Aim: Some studies have verified that miR-133a played an inhibitory role in several cancers. Whereas, the effect of miRNA-133a in colorectal cancer (CRC) has not been fully elucidated. Our study aims to confirm UBA2 as a direct target gene of miRNA-133a and explore the upstream modulatory molecules of miR-133a. In addition, their impacts on the biological characteristics of CRC cells were assessed. Methods: QRT-PCR analyzed miR-133a expression levels in colorectal cells including HCT116, SW48 cells and human normal colorectal cell line NCM460. A serial biological experiment assessed miR-133a effects on cell proliferation, migration, invasion and apoptosis capacities in HCT116 and SW48 cells. MiRNA targeting gene prediction and a dual luciferase assay were employed to confirm miR-133a-targeted UBA2. Transcription factors (TFs) FOXD3 was identified as an upstream regulator of miR-133a via JASPAR. The influence of miR-133a and FOXD3 on UBA2 expression was analyzed by qRT-PCR or western blot. Results: miR-133a was lowly expressed in CRC cells. High miRNA-133a expression suppressed the proliferation, migration, invasion and enhanced apoptosis capacities of CRC cells. MiR-133a targeted the UBA2 mRNA 3'UTR area and reduced UBA2 protein expression. We also unveiled that FOXD3 high-expression significantly raised miR-133a expression and diminished UBA2 expression. We also discovered that high miR-133a expression augmented the effects of elevated FOXD3 expression on CRC cell proliferation, migration and invasion, whereas, low miR-133a expression generated the opposite outcomes. Conclusion: FOXD3 induced miRNA-133a directly targeting UBA2 could affect the progression and growth of CRC.

ARGEOS: A New Bioinformatic Tool for Detailed Systematics Search in GEO and ArrayExpress.

Conduct a reanalysis of transcriptome data for studying intracellular signaling or solving other experimental problems is becoming increasingly popular. Gene expression data are archived as microarray or RNA-seq datasets mainly in two public databases: Gene Expression Omnibus (GEO) and ArrayExpress (AE). These databases were not initially intended to systematically search datasets, making it challenging to conduct a secondary study. Therefore, we have created the ARGEOS service, which has the following advantages that facilitate the search: (1) Users can simultaneously send several requests that are supposed to be used for systematic searches, and it is possible to correct the requests; (2) advanced analysis of information about the dataset is available. The service collects detailed protocols, information on the number of datasets, analyzes the availability of raw data, and provides other reference information. All this contributes to both rapid data analysis with the search for the most relevant datasets and to the systematic search with detailed analysis of the information of the datasets. The efficiency of the service is shown in the example of analyzing transcriptome data of activated (polarized) cells. We have performed a systematic search of studies of cell polarization (when cells are exposed to different immune stimuli). The web interface for ARGEOS is user-friendly and straightforward. It can be used by a person who is not familiar with database searching.

CircGSK3B promotes RORA expression and suppresses gastric cancer progression through the prevention of EZH2 trans-inhibition.

BACKGROUND: Circular RNAs (circRNAs) are a class of non-coding RNA that play critical roles in the development and pathogenesis of various cancers. The circRNA circGSK3B (hsa_circ_0003763) has been shown to enhance cell proliferation, migration, and invasion in hepatocellular carcinoma. However, the specific functions and underlying mechanistic involvement of circGSK3B in gastric cancer (GC) have not yet been explored. Our study aimed to investigate the effect of circGSK3B on the progression of GC and to identify any potential mechanisms underlying this process. METHODS: CircRNA datasets associated with GC were obtained from the PubMed, GEO, and ArrayExpress databases, and circRNAs were validated via RT-qPCR and Sanger sequencing. Biotin-labeled RNA pull-down, mass spectrometry, RNA immunoprecipitation, and in vitro binding assays were employed to determine proteins demonstrating interactions with circGSK3B. Gene expression regulation was assessed through RT-qPCR, chromatin immunoprecipitation, and western blot assays. Gain- and loss-of-function assays were used to analyze any effects of circGSK3B and its partner regulatory molecule (EZH2) on the proliferation, invasion, and migration abilities of GC cells both in vitro and in vivo. RESULTS: CircGSK3B was mainly identified in the nucleus. This circRNA was present at a reduced concentration in GC tissues and cell lines. Overexpression of circGSK3B was shown to inhibit the growth, invasion, and metastasis of GC cells both in vitro and in vivo. Mechanistically, circGSK3B directly interacted with EZH2, acting to suppress the binding of EZH2 and H3K27me3 to the RORA promoter, and leading to an elevation in RORA expression and ultimately the suppression of GC progression. CONCLUSIONS: CircGSK3B acts as a tumor suppressor, reducing EZH2 trans-inhibition and GC progression. This demonstrates the potential use of this RNA as a therapeutic target for GC.

Transcription factor SP1-induced microRNA-146b-3p facilitates the progression and metastasis of colorectal cancer via regulating FAM107A.

BACKGROUND: Recent studies have provided compelling evidence regarding the association of microRNAs (miRNAs) with the progression and development of tumors. Among the miRNAs, the dysregulation of miR-146b-3p expression has been reported in several cancers, however, its effect on colorectal cancer (CRC) remains unexplored. Many studies have suggested a close correlation between the transcription factor (TF)-miRNA signal and cancer. The present study explored the effects of TF-miR-146b-3p axis on CRC and elucidated its downstream regulatory molecule. MATERIALS AND METHODS: The expression levels of miR-146b-3p in CRC tissues and cell lines were assessed via quantitative real-time polymerase chain reaction (qRT-PCR). The impact of miR-146b-3p on CRC cell proliferation, migration, and invasion were analyzed using the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide (MTT) cell proliferation assay and transwell migration and invasion assay. Additionally, the impact of miR-146b-3p on CRC cell cycle and apoptosis was investigated using flow cytometry. The targets of miR-146b-3p, predicted by miRWalk database, were verified using a dual-luciferase reporter system. The expression levels of TFs were detected using qRT-PCR. The effects of miR-146b-3p and SP1 on FAM107A expression were assessed by performing qRT-PCR and western blotting. Chromatin Immunoprecipitation (ChIP) Assay was performed and JASPAR database was utilized to explore the regulatory relationship between the SP1 and miR-146b-3p. RESULTS: Increased expression of miR-146b-3p in CRC tissues and cell lines correlated with poor overall survival (OS). Upregulation of miR-146b-3p expression remarkably promoted the proliferation, migration, and invasion of CRC cells and suppressed their apoptosis. Furthermore, SP1 overexpression significantly elevated the miR-146b-3p expression, decreased the FAM107A expression, and promoted the G1/S transition. The miR-146b-3p overexpression also enhanced the effects of SP1 overexpression on CRC cell proliferation, migration, and invasion, whereas miR-146b-3p knockdown led to the opposite results. CONCLUSION: Mechanistically, miR-146b-3p functions as an oncogene by directly targeting FAM107A. Our results highlight the critical regulatory role played by SP1-induced miR-146b-3p expression in CRC development. Our results suggest that SP1/miR-146b-3p/FAM107A axis may be a potential therapeutic target for CRC.

Identification of Mast Cell-Based Molecular Subtypes and a Predictive Signature in Clear Cell Renal Cell Carcinoma.

Background: Kidney renal clear cell carcinoma (KIRC) is a common malignant tumor of the urinary system. Surgery is the preferred treatment option; however, the rate of distant metastasis is high. Mast cells in the tumor microenvironment promote or inhibit tumorigenesis depending on the cancer type; however, their role in KIRC is not well-established. Here, we used a bioinformatics approach to evaluate the roles of mast cells in KIRC. Methods: To quantify mast cell abundance based on gene sets, a single-sample gene set enrichment analysis (ssGSEA) was utilized to analyze three datasets. Weighted correlation network analysis (WGCNA) was used to identify the genes most closely related to mast cells. To identify new molecular subtypes, the nonnegative matrix factorization algorithm was used. GSEA and least absolute shrinkage and selection operator (LASSO) Cox regression were used to identify genes with high prognostic value. A multivariate Cox regression analysis was performed to establish a prognostic model based on mast cell-related genes. Promoter methylation levels of mast cell-related genes and relationships between gene expression and survival were evaluated using the UALCAN and GEPIA databases. Results: A prolonged survival in KIRC was associated with a high mast cell abundance. KIRC was divided into two molecular subtypes (cluster 1 and cluster 2) based on mast cell-related genes. Genes in Cluster 1 were enriched for various functions related to cancer development, such as the TGFß signaling pathway, renal cell carcinoma, and mTOR signaling pathway. Based on drug sensitivity predictions, sensitivity to doxorubicin was higher for cluster 2 than for cluster 1. By a multivariate Cox analysis, we established a clinical prognostic model based on eight mast cell-related genes. Conclusion: We identified eight mast cell-related genes and constructed a clinical prognostic model. These results improve our understanding of the roles of mast cells in KIRC and may contribute to personalized medicine.

A united risk model of 11 immune­related gene pairs and clinical stage for prediction of overall survival in clear cell renal cell carcinoma patients.

Clear cell renal cell carcinoma (ccRCC) is the most common subtype of renal cancer. Currently, we lack effective risk models for the prognosis of ccRCC patients. Given the significant role of cancer immunity in ccRCC, we aimed to establish a novel united risk model including clinical stage and immune-related gene pairs (IRGPs) to assess the prognosis. The gene expression profile and clinical data of ccRCC patients from The Cancer Genome Atlas and Arrayexpress were divided into training cohort (n = 381), validation cohort 1 (n = 156), and validation cohort 2 (n = 101). Through univariate Cox regression analysis and Least Absolute Shrinkage and Selection Operator analysis, 11 IRGPs were obtained. After further analysis, it was found that clinical stage could be an independent prognostic factor; hence, we used it to construct a united prognostic model with 11 IRGPs. Based on this model, patients were divided into high-risk and low-risk groups. In Kaplan-Meier analysis, a significant difference was observed in overall survival (OS) among all three cohorts (p < 0.001). The calibration curve revealed that the signature model is in high accordance with the observed values of each data cohort. The 1-year, 3-year, and 5-year receiver operating characteristic curves of each data cohort showed better performance than only IRGP signatures. The results of immune infiltration analysis revealed significantly (p < 0.05) higher abundance of macrophages M0, T follicular helper cells, and other tumor infiltrating cells. In summary, we successfully established a united prognostic risk model, which can effectively assess the OS of ccRCC patients.

Cancer markers: integratively annotated classification.

Translational cancer genomics research aims to ensure that experimental knowledge is subject to computational analysis, and integrated with a variety of records from omics and clinical sources. The data retrieval from such sources is not trivial, due to their redundancy and heterogeneity, and the presence of false evidence. In silico marker identification, therefore, remains a complex task that is mainly motivated by the impact that target identification from the elucidation of gene co-expression dynamics and regulation mechanisms, combined with the discovery of genotype-phenotype associations, may have for clinical validation. Based on the reuse of publicly available gene expression data, our aim is to propose cancer marker classification by integrating the prediction power of multiple annotation sources. In particular, with reference to the functional annotation for colorectal markers, we indicate a classification of markers into diagnostic and prognostic classes combined with susceptibility and risk factors.