Identification of Transcriptional Markers and microRNA-mRNA Regulatory Networks in Colon Cancer by Integrative Analysis of mRNA and microRNA Expression Profiles in Colon Tumor Stroma

Particular exosomal micro-RNAs and gastrointestinal (GI) cancer cells' roles: Current theories

A diverse range of gastrointestinal tract disorders are called gastrointestinal (GI) malignancies. The transformation of normal cells into precursor cells, precursor cells into premalignant cells, and premalignant cells into cancerous cells is facilitated by the interaction of many modifiable and non-modifiable risk factors. Developing relevant therapy alternatives based on a better knowledge of the illness's aetiology is essential to enhance patient outcomes. The exosome is crucial in regulating intercellular interaction because it may send molecular signals to nearby or distant cells. Exosomes produced from cancer can introduce a variety of chemicals and vast concentrations of microRNA (miRNA) into the tumour microenvironment. These miRNAs significantly impact immunological evasion, metastasis, apoptosis resistance, and cell growth. Exosomal miRNAs, or exosomal miRNAs, are essential for controlling cancer resistance to apoptosis, according to mounting data. Exosomal miRNAs function as an interaction hub between cancerous cells and the milieu around them, regulating gene expression and various signalling pathways. Our research examines the regulatory function of exosomal miRNAs in mediating interactions between cancer cells and the stromal and immunological cells that make up the surrounding milieu.

Identifying the regulatory network of microRNAs and mRNAs to clarify molecular mechanisms in stroke by bioinformatics analysis

BACKGROUND

Stroke is one of the leading causes of disability and mortality worldwide.

OBJECTIVE

To identify the regulatory network of microRNAs (miRNAs) and mRNAs to clarify molecular mechanisms in stroke.

METHODS

Four miRNA datasets and two mRNA datasets of stroke were downloaded from the GEO database. R-Studio was utilized to analyze differentially expressed miRNAs (DEmiRNAs) and mRNAs (DEmRNAs) in the blood of stroke and control patients. FunRich software was utilized to conduct GO and biological pathway analysis on DEmiRNAs, and to search for transcription factors (TFs) of DEmiRNAs. Subsequently, we used miRDB, miRTarBase, and TargetScan to identify DEmiRNAs target genes and intersected with DEmRNAs to find common target genes. The miRNA-mRNA regulatory network of common target genes was constructed by using the Cytoscape. The biological and functional roles of target genes in the regulatory network were predicted using GO and KEGG pathway analyses.

RESULTS

464 DEmiRNAs and 329 DEmRNAs were screened. The top ten TFs (SP1, SP4, EGR1, TCF3, NKX6-1, ZFP161, RREB1, MEF2A, NFIC, POU2F1) were visualized. 16747 target genes of DEmiRNAs were predicted. Target genes were intersected with DEmRNAs, 107 common target genes and 162 DEmiRNAs regulating these common genes were obtained, and then a regulatory network was constructed. Target genes of the regulatory network were primarily enriched in VEGF signaling pathway, lipid and atherosclerosis, T cell receptor signaling pathway.

CONCLUSION

This study found that VEGF signaling pathway, lipid and atherosclerosis, T cell receptor signaling pathway are implicated in the biological process of stroke by constructing the regulatory network of miRNAs-mRNAs, which may have guide significance for the pathogenesis and treatment of stroke.

Improving targeted small molecule drugs to overcome chemotherapy resistance

BACKGROUND

Conventional cancer treatments face the challenge of therapeutic resistance, which causes poor treatment outcomes. The use of combination therapies can improve treatment results in patients and is one of the solutions to overcome this challenge. Chemotherapy is one of the conventional treatments that, due to the non-targeted and lack of specificity in targeting cancer cells, can cause serious complications in the short and long-term for patients by damaging healthy cells. Also, the employment of a wide range of strategies for chemotherapy resistance by cancer cells, metastasis, and cancer recurrence create serious problems to achieve the desired results of chemotherapy. Accordingly, targeted therapies can be used as a combination treatment with chemotherapy to both cause less damage to healthy cells, which as a result, they reduce the side effects of chemotherapy, and by targeting the factors that cause therapeutic challenges, can improve the results of chemotherapy in patients.

RECENT FINDINGS

Small molecules are one of the main targeted therapies that can be used for diverse targets in cancer treatment due to their penetration ability and characteristics. However, small molecules in cancer treatment are facing obstacles that a better understanding of cancer biology, as well as the mechanisms and factors involved in chemotherapy resistance, can lead to the improvement of this type of major targeted therapy.

CONCLUSION

In this review article, at first, the challenges that lead to not achieving the desired results in chemotherapy and how cancer cells can be resistant to chemotherapy are examined, and at the end, research areas are suggested that more focusing on them, can lead to the improvement of the results of using targeted small molecules as an adjunctive treatment for chemotherapy in the conditions of chemotherapy resistance and metastasis of cancer cells.

Exploration of Key Immune-Related Transcriptomes Associated with Doxorubicin-Induced Cardiotoxicity in Patients with Breast Cancer

Based on a few studies, heart failure patients with breast cancer were assessed to find potential biomarkers for doxorubicin-induced cardiotoxicity. However, key immune-related transcriptional markers linked to doxorubicin-induced cardiotoxicity in breast cancer patients have not been thoroughly investigated. We used GSE40447, GSE76314, and TCGA BRCA cohorts to perform this study. Then, we performed various bioinformatics approaches to identify the key immune-related transcriptional markers and their association with doxorubicin-induced cardiotoxicity in patients with breast cancer. We found 255 upregulated genes and 286 downregulated genes in patients with doxorubicin-induced heart failure in breast cancer. We discovered that in patients with breast cancer comorbidity doxorubicin-induced cardiotoxicity, the 58 immunological genes are elevated (such as CPA3, VSIG4, GATA2, RFX2, IL3RA, and LRP1), and the 60 genes are significantly suppressed (such as MS4A1, FCRL1, CD200, FCRLA, FCRL2, and CD79A). Furthermore, we revealed that the immune-related differentially expressed genes (DEGs) are substantially associated with the enrichment of KEGG pathways, including B-cell receptor signaling pathway, primary immunodeficiency, chemokine signaling pathway, hematopoietic cell lineage, cytokine-cytokine receptor interaction, Toll-like receptor signaling pathway, MAPK signaling pathway, focal adhesion, dilated cardiomyopathy, cell adhesion molecule, etc. Moreover, we discovered that the doxorubicin-induced immune-related genes are crucially involved in the protein-protein interaction and gene clusters. The immune-related genes, including IFIT5, XCL1, SPIB, BTLA, MS4A1, CD19, TCL1A, CD83, CD200, FCRLA, CD79A, BIRC3, and IGF2R are significantly associated with a poor survival prognosis of breast cancer patients and showed diagnostic efficacy in patients with breast cancer and heart failure. Molecular docking revealed that the survival-associated genes interact with the doxorubicin with appreciable binding affinity. Finally, we validated the expression level of immune-related genes in breast cancer patients-derived cardiomyocytes with doxorubicin-induced cardiotoxicity and found that the level of RAD9A, HSPA1B, GATA2, IGF2R, CD200, ERCC8, and BCL11A genes are consistently dysregulated. Our findings offered a basis for understanding the mechanism and pathogenesis of the cardiotoxicity caused by doxorubicin in breast cancer patients and predicted the interaction of immune-related potential biomarkers with doxorubicin.

A preliminary study of calcium channel-associated mRNA and miRNA networks in post-traumatic epileptic rats

The calcium channels are the main pathogenesis and therapeutic target for post-traumatic epilepsy (PTE). However, differentially expressed miRNAs (DEMs) and mRNAs associated with calcium channels in PTE and their interactions are poorly understood. We produced a PTE model in rats and conducted RNA-seq in PTE rats. Gene annotation was used to verify differentially expressed mRNAs related to calcium channels. RNAhybrid, PITA, and Miranda prediction were used to build the miRNA-mRNA pairs. Furthermore, Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were used for the functional enrichment analysis of DEMs. The quantification changes of mRNA and miRNA were verified by RT-qPCR. There were 431 identified differentially expressed genes (DEGs) in PTE rats compared with the sham group, of which five mRNAs and 7 miRNAs were related to calcium channels. The miRNA-mRNA network suggested a negative correlation between 11 pairs of miRNA-mRNA involved in the p53 signaling pathway, HIF-1 signaling pathway. RT-qPCR verified three upregulated mRNAs in PTE rats, associated with 7 DEMs negatively related to them, respectively. This study has revealed the changes in miRNA-mRNA pairs associated with calcium channels in PTE, which might contribute to the further interpretation of potential underlying molecular mechanisms of PTE and the discovery of promising diagnostics.

Immune function of colon cancer associated miRNA and target genes

Introduction

Colon cancer is a complex disease that involves intricate interactions between cancer cells and theimmune microenvironment. MicroRNAs (miRNAs) have recently emerged as critical regulators of gene expression in cancer, including colon cancer. There is increasing evidence suggesting that miRNA dysregulation plays a crucial role in modulating the immune microenvironment of intestinal cancer. In particular, miRNAs regulate immune cell activation, differentiation, and function, as well as cytokine and chemokine production in intestinal cancer. It is urgent to fully investigate the potential role of intestinal cancer-related miRNAs in shaping the immune microenvironment.

Methods

Therefore, this paper aims to identify miRNAs that are potentially associated with colon cancer and regulate a large number of genes related to immune function. We explored the role of these genes in colon cancer patient prognosis, immune infiltration, and tumor purity based on data of 174 colon cancer patients though convolutional neural network, survival analysis and multiple analysis tools.

Results

Our findings suggest that miRNA regulated genes play important roles in CD4 memory resting cells, macrophages.M2, and Mast cell activated cells, and they are concentrated in the cytokinecytokine receptor interaction pathway.

Discussion

Our study enhances our understanding of the underlying mechanisms of intestinal cancer and provides new insights into the development of effective therapies. Additionally, identification of miRNA biomarkers could aid in diagnosis and prognosis, as well as guide personalized treatment strategies for patients with intestinal cancer.

Identification of Hub Genes for Colorectal Cancer with Liver Metastasis Using miRNA-mRNA Network

Background

Liver metastasis is an important cause of death in patients with colorectal cancer (CRC). Increasing evidence indicates that microRNAs (miRNAs) are involved in the pathogenesis of colorectal cancer liver metastasis (CRLM). This study is aimed at exploring the potential miRNA-mRNA regulatory network.

Methods

From the GEO database, we downloaded the microarray datasets GSE56350 and GSE73178. GEO2R was used to conduct differentially expressed miRNAs (DEMs) between CRC and CRLM using the GEO2R tool. Then, GO and KEGG pathway analysis for differentially expressed genes (DEGs) performed via DAVID. A protein-protein interaction (PPI) network was constructed by the STRING and identified by Cytoscape. Hub genes were identified by miRNA-mRNA network. Finally, the expression of the hub gene expression was assessed in the GSE81558.

Results

The four DEMs (hsa-miR-204-5p, hsa-miR-122-5p, hsa-miR-95-3p, and hsa-miR-552-3p) were identified as common DEMs in GSE56350 and GSE73178 datasets. The SP1 was likely to adjust the upregulated DEMs; however, the YY1 could regulate both the upregulated and downregulated DEMs. A total of 3925 genes (3447 upregulated DEM genes and 478 downregulated DEM genes) were screened. These predicted genes were mainly linked to Platinum drug resistance, Cellular senescence, and ErbB signaling pathway. Through the gene network construction, most of the hub genes were found to be modulated by hsa-miR-204-5p, hsa-miR-122-5p, hsa-miR-95-3p, and hsa-miR-552-3p. Among the top 20 hub genes, the expression of CREB1, RHOA, and EGFR was significantly different in the GSE81558 dataset.

Conclusion

In this study, miRNA-mRNA networks in CRLM were screened between CRC patients and CRLM patients to provide a new method to predict for the pathogenesis and development of CRC.

Transcriptomic data analysis coupled with copy number aberrations reveals a blood-based 17-gene signature for diagnosis and prognosis of patients with colorectal cancer

Background: Colorectal cancer (CRC) is the third most common cancer and third leading cause of cancer-associated deaths worldwide. Diagnosing CRC patients reliably at an early and curable stage is of utmost importance to reduce the risk of mortality. Methods: We identified global differentially expressed genes with copy number alterations in patients with CRC. We then identified genes that are also expressed in blood, which resulted in a blood-based gene signature. We validated the gene signature's diagnostic and prognostic potential using independent datasets of gene expression profiling from over 800 CRC patients with detailed clinical data. Functional enrichment, gene interaction networks and pathway analyses were also performed. Results: The analysis revealed a 17-gene signature that is expressed in blood and demonstrated that it has diagnostic potential. The 17-gene SVM classifier displayed 99 percent accuracy in predicting the patients with CRC. Moreover, we developed a prognostic model and defined a risk-score using 17-gene and validated that high risk score is strongly associated with poor disease outcome. The 17-gene signature predicted disease outcome independent of other clinical factors in the multivariate analysis (HR = 2.7, 95% CI = 1.3-5.3, p = 0.005). In addition, our gene network and pathway analyses revealed alterations in oxidative stress, STAT3, ERK/MAPK, interleukin and cytokine signaling pathways as well as potentially important hub genes, including BCL2, MS4A1, SLC7A11, AURKA, IL6R, TP53, NUPR1, DICER1, DUSP5, SMAD3, and CCND1. Conclusion: Our results revealed alterations in various genes and cancer-related pathways that may be essential for CRC transformation. Moreover, our study highlights diagnostic and prognostic value of our gene signature as well as its potential use as a blood biomarker as a non-invasive diagnostic method. Integrated analysis transcriptomic data coupled with copy number aberrations may provide a reliable method to identify key biological programs associated with CRC and lead to improved diagnosis and therapeutic options.

Hydroxytyrosol decreases EDNRA expression through epigenetic modification in colorectal cancer cells

The Mediterranean diet (MD) is one of the healthiest ones and is associated with a lower incidence of cardiovascular and cerebrovascular diseases as well as cancer. Extra virgin olive oil (EVOO) is probably the most idiosyncratic component of this diet. EVOO has been attributed with many healthful effects, which may be due to its phenolic components, e.g. including hydroxytyrosol (HT). Recent studies suggest that EVOO and HT have molecular targets in human tissues and modulate epigenetic mechanisms. DNA methylation is one of the most studied epigenetic mechanisms and consists of the addition of a methyl group to the cytosines of the DNA chain. Given the purported health effects of EVOO (poly)phenols, we analyzed the changes induced by HT in DNA methylation, in a colorectal cancer cell line. Caco-2 cells were treated with HT for one week or with the demethylating agent 5'-azacytidine for 48 h. Global DNA methylation was assessed by ELISA. DNA bisulfitation was performed and Infinium Methylation EPIC BeadChips were used to analyze the specific methylation of CpG sites. We show an increase in global DNA methylation in Caco-2 cells after HT treatment, with a total of 32,141 differentially methylated (CpGs DMCpGs). Interestingly, our analyses revealed the endothelin receptor type A gene (EDNRA) as a possible molecular target of HT. In summary, we demonstrate that cellular supplementation with HT results in a specific methylome map and propose a potential gene target for HT.

Endothelin-3 is epigenetically silenced in endometrioid endometrial cancer

Purpose

Changes in the activity of endothelins and their receptors may promote neoplastic processes. They can be caused by epigenetic modifications and modulators, but little is known about endothelin-3 (EDN3), particularly in endometrial cancer. The aim of the study was to determine the expression profile of endothelin family and their interactions with miRNAs, and to assess the degree of EDN3 methylation.

Methods

The study enrolled 45 patients with endometrioid endometrial cancer and 30 patients without neoplastic changes. The expression profile of endothelins and their receptors was determined with mRNA microarrays and RT-qPCR. The miRNA prediction was based on the miRNA microarray experiment and the mirDB tool. The degree of EDN3 methylation was assessed by MSP.

Results

EDN1 and EDNRA were overexpressed regardless of endometrial cancer grade, which may be due to the lack of regulatory effect of miR-130a-3p and miR-485-3p, respectively. In addition, EDN3 and EDNRB were significantly downregulated.

Conclusion

The endothelial axis is disturbed in endometrioid endometrial cancer. The observed silencing of EDN3 activity may be mainly due to DNA methylation.

Comprehensive analysis to identify pseudogenes/lncRNAs-hsa-miR-200b-3p-COL5A2 network as a prognostic biomarker in gastric cancer

OBJECTIVE

Gastric cancer is one of the most common and deadly types of cancer. The molecular mechanism of gastric cancer progression remains unclear.

MATERIALS AND METHODS

Four hub genes were identified through GEO and TCGA database screening and analysis. Prognostic analysis revealed that COL5A2 was the most likely to affect the prognosis of gastric cancer among the four hub genes. The relationships between COL5A2 and clinical variables and immune cell infiltration were analyzed. Then, COL5A2 was analyzed for single-gene differences and related functional enrichment. Using the starBase database for prediction and analysis, miRNAs and pseudogenes/lncRNAs that might combine with COL5A2 were identified; thus, the ceRNA network was constructed. Finally, the network was verified by Cox analysis and qPCR, and a nomogram was constructed.

RESULTS

First, we found that COL5A2, COL12A1, BGN and THBS2 were highly expressed in gastric cancer. COL5A2 had statistical significance in overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI) analysis. Immune infiltration analysis suggested that COL5A2 might influence the changes in the tumor immune microenvironment. The StarBase database was used to predict that 3 pseudogenes and 7 lncRNAs might inhibit the hsa-miR-200b-3p-COL5A2 axis in gastric cancer. The pseudogenes/lncRNA-hsa-miR-200b-3p-COL5A2 ceRNA network was identified and verified using Cox regression analysis and PCR. Finally, we constructed a nomogram.

CONCLUSIONS

We elucidated the regulatory role of the pseudogenes/lncRNA-hsa-miR-200b-3p-COL5A2 network in gastric cancer progression and constructed a nomogram. These studies may provide effective treatments and potential prognostic biomarkers for gastric cancer.

microRNA Bioinformatics

Firstly, I apologize for the delayed publication of this Special Issue in the form of a book title [...].

Cancer-Associated Stromal Fibroblast-Derived Transcriptomes Predict Poor Clinical Outcomes and Immunosuppression in Colon Cancer

Background: Previous studies revealed that colonic cancer-associated fibroblasts (CAFs) are associated with the modulation of the colon tumor microenvironment (TME). However, identification of key transcriptomes and their correlations with the survival prognosis, immunosuppression, tumor progression, and metastasis in colon cancer remains lacking. Methods: We used the GSE46824, GSE70468, GSE17536, GSE35602, and the cancer genome atlas (TCGA) colon adenocarcinoma (COAD) datasets for this study. We identified the differentially expressed genes (DEGs), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, hub genes, and survival-associated genes in colon cancer. Finally, we investigated the correlation of key genes with the survival prognosis, immunosuppression, and metastasis. Results: We identified 246 common DEGs between the GSE46824 and GSE70468 datasets of colonic CAFs, which included 72 upregulated and 174 downregulated genes. The upregulated pathways are mainly involved with cancers and cellular signaling, and downregulated pathways are involved with immune regulation and cellular metabolism. The search tool for the retrieval of interacting genes (STRING)-based analysis identified 15 hub genes and 9 significant clusters in colonic CAFs. The upregulation of CTHRC1, PDGFC, PDLIM3, NTM, and SLC16A3 and downregulation of FBN2 are correlated with a shorter survival time in colon cancer. The CTHRC1, PDGFC, PDLIM3, and NTM genes are positively correlated with the infiltration of tumor-associated macrophages (TAM), macrophages, M2 macrophages, the regulatory T cells (Tregs), T cell exhaustion, and myeloid-derived suppressor cells (MDSCs), indicating the immunosuppressive roles of these transcriptomes in colon cancer. Moreover, the CTHRC1, PDGFC, PDLIM3, NTM, and SLC16A3 genes are gradually increased from normal tissue to the tumor and tumor to the metastatic tumor, and FBN2 showed the reverse pattern. Furthermore, the CTHRC1, FBN2, PDGFC, PDLIM3, and NTM genes are positively correlated with the metastatic scores in colon cancer. Then, we revealed that the expression value of CTHRC1, FBN2, PDGFC, PDLIM3, NTM, and SLC16A3 showed the diagnostic efficacy in colonic CAFs. Finally, the expression level of CTHRC1, PDGFC, and NTM genes are consistently altered in colon tumor stroma as well as in the higher CAFs-group of TCGA COAD patients. Conclusion: The identified colonic CAFs-derived key genes are positively correlated with survival prognosis, immunosuppression, tumor progression, and metastasis.

Yiqi Jianpi Huayu Jiedu Decoction Inhibits Metastasis of Colon Adenocarcinoma by Reversing Hsa-miR-374a-3p/Wnt3/β-Catenin-Mediated Epithelial–Mesenchymal Transition and Cellular Plasticity

Colon adenocarcinoma (COAD) accounts for 95% of colon cancer cases, with the 5-year survival rate significantly affected by local or distant metastases. Yiqi Jianpi Huayu Jiedu decoction (YJHJD), based on the theory of “nourish qi, invigorate the spleen, remove blood stasis, and detoxify”, has long been applied and shown to be remarkable in the prevention and treatment of gastrointestinal tumors. However, the underlying therapeutic mechanisms of YJHJD have not been fully elucidated. Herein, we first confirmed hsa-miR-374a-3p as a tumor suppressor based on its lower expression in the plasma of patients with COAD with liver metastasis and association with more advanced local progression. We also verified WNT3 as a potential target of hsa-miR-374a-3p and observed its increased expression in COAD tissues. Furthermore, we showed that the hsa-miR-374a-3p/Wnt3/β-catenin axis was responsible for epithelial–mesenchymal transition (EMT) and cellular plasticity in COAD, as well as poorer patient prognosis. Our results showed that YJHJD inhibited motility and colony potential in vitro, as well as liver metastasis of COAD in vivo. Moreover, YJHJD induced a reversal of EMT and cellular plasticity-related molecular expression, increased hsa-miR-374a-3p, and decreased Wnt3 and β-catenin levels. In addition, silencing of hsa-miR-374a-3p weakened YJHJD inhibition, whereas the β-catenin inhibitor XAV939 partially repaired it. Taken together, these results demonstrated that YJHJD suppressed the EMT and cellular plasticity of COAD by regulating hsa-miR-374a-3p/Wnt3/β-catenin signaling.

Expression of specific microRNAs in tissue and plasma in colorectal cancer

BACKGROUND

MicroRNAs (miRNA/miR) play significant roles in the regulation of cell differentiation, cell cycle progression, and apoptosis. They become dysregulated during carcinogenesis and are eventually released into the circulation, enabling their detection in body fluids. Thus, this study compared the miRNA expression in tissue and plasma samples of colorectal cancer (CRC) patients and clinically healthy controls and determined miRNA expression as a potential CRC biomarker.

METHODS

Using quantitative reverse transcription polymerase chain reaction (RT-qPCR), miR-21-5p, miR-29a-3p, miR-92a-3p, miR-135b-5p, miR-196b-5p, and miR-197-3p, expression was analyzed and compared between the malignant (n = 41) and the adjacent neoplasm free mucosal tissues (n = 41) of CRC patients. The findings were validated in plasma samples (n = 36) collected from the same CRC patients prior to surgery or any form of treatment and compared to plasma from their age and sex-matched controls (n = 36).

RESULTS

MiR-21-5p, miR-29a-3p, miR-92a-3p, and miR- 196b-5p were upregulated and miR-135b-5p was downregulated in CRC malignant tissues compared to their expression in adjacent neoplasm-free tissue. This was further observed in the plasma of the same CRC cases compared to controls. MiR-92a-3p showed itself the most sensitive (0.93; p < .001) and most specific (0.95; p < .001) in detecting CRC in tissue. In plasma, miR-196b-5p was the most sensitive (0.97; p < .001) and specific (0.94; p < .001) in detecting CRC. Plasma miR-92a-3p and miR-196b-5p were the most sensitive (0.95; p < .001) and specific (0.94; p < .001) in the early detection of CRC.

CONCLUSIONS

Results show that specific miRNAs dysregulated in malignant tissues are released and can be detected in the circulation, supporting their potential as non-invasive biomarkers of CRC.

Autophagy Induced by BCL2-Related ceRNA Network Participates in the Occurrence of COPD

Purpose

Chronic obstructive pulmonary disease (COPD) is a predominant cause of mortality worldwide. Autophagy, which depends on a lysosomal degradation pathway, plays an essential role in the occurrence of COPD. The aim of our study was to identify the potential function of autophagy and construct a BCL2-related competing endogenous RNA (ceRNA) network that induces autophagy in COPD.

Methods

Blood sample data from GSE31568, GSE24709, and GSE61741 were collected from the Gene Expression Omnibus (GEO) database. Differentially expressed miRNAs in COPD and controls were identified via GEO2R. Transcription factors were obtained from FunRich. DIANA, miRDB, miRTarBase, and TargetScan were used to predict target genes of miRNAs. Autophagy genes were collected from the Human Autophagy Database (HADb). The GSE151052 dataset was used to identify autophagy-related differentially expressed genes in tissues. Functional enrichment and protein–protein interaction (PPI) network analyses were conducted via Metascape and the STRING network. Spearman correlation analysis was used to analyze the relationship between autophagy-related differentially expressed genes and lung function. The BCL2-related ceRNA network was modeled by Cytoscape.

Results

We obtained 41 differentially expressed miRNAs and 10 significantly different transcription factors. We identified 19 autophagy-related differentially expressed genes that were significantly different (P<0.05) in tissue samples. The most significant enrichment in Metascape was an autophagy item, which further confirmed autophagy participation in the occurrence of COPD. PPI network analysis found four genes (BCL2, BECN1, MAPK8, and ITPR1), among which BCL2 was correlated with both FEV1/FVC and FEV1 prediction. Finally, the BCL2-related ceRNA network was constructed to clarify the interaction of RNAs and occurrence of autophagy, including 18 miRNAs and 65 lncRNAs.

Conclusion

We identified 19 autophagy-related differentially expressed genes that participated in COPD; among them, BCL2 was correlated with lung function, and a BCL2-related ceRNA network was constructed, which further revealed the potential mechanism of autophagy involvement in COPD.

The role of Exosomal miRNAs in cancer

Exosomal miRNAs have attracted much attention due to their critical role in regulating genes and the altered expression of miRNAs in virtually all cancers affecting humans (Sun et al. in Mol Cancer 17(1):14, 2018). Exosomal miRNAs modulate processes that interfere with cancer immunity and microenvironment, and are significantly involved in tumor growth, invasion, metastasis, angiogenesis and drug resistance. Fully investigating the detailed mechanism of miRNAs in the occurrence and development of various cancers could help not only in the treatment of cancers but also in the prevention of malignant diseases. The current review highlighted recently published advances regarding cancer-derived exosomes, e.g., sorting and delivery mechanisms for RNAs. Exosomal miRNAs that modulate cancer cell-to-cell communication, impacting tumor growth, angiogenesis, metastasis and multiple biological features, were discussed. Finally, the potential role of exosomal miRNAs as diagnostic and prognostic molecular markers was summarized, as well as their usefulness in detecting cancer resistance to therapeutic agents.

Recognition of the Possible miRNA-mRNA Controlling Network in Stroke by Bioinformatics Examination

BACKGROUND

Based on the latest research of WHO, it has been revealed that more than 15 million people suffer from stroke every year worldwide. Of these 15 million people, 6 million succumb to death, and 5 million get permanently disabled. This is the prime reason for the substantial economic burden on all parts of the world.

METHODS

These data have been obtained from the GEO database, and the GEO2R tool was used to find out the differentially expressed miRNAs (DEMs) between the stroke and normal patients' blood. FunRich and miRNet were considered to find potential upstream transcription factors and downstream target genes of candidate EMRs. Next, we use GO annotation and KEGG pathway enrichment. Target genes were analyzed with the help of the R software. Then, the STRING database and Cytoscape software were used to conduct PPI and DEM-hub gene networks. Finally, GSE58294 was used to estimate the hub gene expressions.

RESULTS

Six DEMs in total were selected out from GSE95204 and GSE117064 datasets. 663 DEMs' target genes were predicted, and NRF1, EGR1, MYC, YY1, E2F1, SP4, and SP1 were predicted as an upstream transcription factor for DEMs' target genes. Target genes of DEMs were primarily augmented in the PI3K-Akt signaling pathway and p53 signaling pathway. The network construction of DEM hygiene is potentially modulated by hsa-miR-3591-5p, hsa-miR-548as-3p, hsa-miR-206, and hsa-miR-4503 hub genes which were found among the top 10 of the hub genes. Among the top 10 hub genes, justification of CTNNB1, PTEN, ESR1, CCND1, KRAS, AKT1, CCND2, CDKN1B, and MYCN was constant with that in the GSE58294 dataset.

CONCLUSION

In summary, our research first constructs the miRNA-mRNA network in stroke, which probably renders an awakening purview into the pathogenesis and cure of stroke.

Bioinformatics Analysis of Hub Genes and Potential Therapeutic Agents Associated with Gastric Cancer

Purpose

The current treatment methods available for advanced gastric cancer are not very promising. Hence, it is important to explore novel biomarkers and potential therapeutic agents to treat gastric cancer (GC). This study aimed to identify hub genes associated with GC prognosis and explore potential drugs for its treatment.

Materials and Methods

Three gene expression data of GC and normal tissues were downloaded from the Gene Expression Omnibus (GEO) and processed to identify the differentially expressed genes (DEGs). We conducted a comprehensive analysis of DEGs, including functional enrichment analysis, construction of protein-protein interaction (PPI) network, identification of hub genes, survival analysis and expression verification of hub genes. Finally, we constructed the network of miRNA-mRNA, and predicted the drugs that might be effective for GC treatment.

Results

A total of 340 DEGs, including 94 up-regulated and 246 down-regulated genes, were identified. Among the up-regulated DEGs, the enrichment terms were primarily related to tumorigenesis and tumor progression, extracellular matrix organization, and collagen catabolic process. Additionally, 10 hub genes (FN1, COL3A1, COL1A2, BGN, THBS2, COL5A2, THBS1, COL5A1, SPARC, and COL4A1) were identified, out of which 7 genes were significantly associated with poor overall survival (OS) in GC. The expression levels of these 7 hub genes were verified using real-time PCR, immunohistochemistry, and the GEPIA2 (Gene Expression Profiling Interactive Analysis) server. A regulatory network of miRNA-mRNA was also constructed, and the top 4 interactive miRNAs (hsa-miR-29b-3p, hsa-miR-140-3p, hsa-miR-29a-3p, and hsa-miR-29c-3p) that targeted the most hub genes were identified. Finally, fourteen small molecules were predicted to be effective in treating GC.

Conclusion

The identification of the hub genes, miRNA-mRNA network, and potential candidate drugs associated with GC provides new insights into the molecular mechanisms and treatment of GC.

Identification of transcription factors and construction of a novel miRNA regulatory network in primary osteoarthritis by integrated analysis

Backgrounds

As osteoarthritis (OA) disease-modifying therapies are not available, novel therapeutic targets need to be discovered and prioritized. Here, we aim to identify miRNA signatures in patients to fully elucidate regulatory mechanism of OA pathogenesis and advance in basic understanding of the genetic etiology of OA.

Methods

Six participants (3 OA and 3 controls) were recruited and serum samples were assayed through RNA sequencing (RNA-seq). And, RNA-seq dataset was analysed to identify genes, pathways and regulatory networks dysregulated in OA. The overlapped differentially expressed microRNAs (DEMs) were further screened in combination with the microarray dataset GSE143514. The expression levels of candidate miRNAs were further validated by quantitative real-time PCR (qRT-PCR) based on the GEO dataset (GSE114007).

Results

Serum samples were sequenced interrogating 382 miRNAs. After screening of independent samples and GEO database, the two comparison datasets shared 19 overlapped candidate micRNAs. Of these, 9 up-regulated DEMs and 10 down-regulated DEMs were detected, respectively. There were 236 target genes for up-regulated DEMs and 400 target genes for those down-regulated DEMs. For up-regulated DEMs, the top 10 hub genes were KRAS, NRAS, CDC42, GDNF, SOS1, PIK3R3, GSK3B, IRS2, GNG12, and PRKCA; for down-regulated DEMs, the top 10 hub genes were NR3C1, PPARGC1A, SUMO1, MEF2C, FOXO3, PPP1CB, MAP2K1, RARA, RHOC, CDC23, and CREB3L2. Mir-584-5p-KRAS, mir-183-5p-NRAS, mir-4435-PIK3R3, and mir-4435-SOS1 were identified as four potential regulatory pathways by integrated analysis.

Conclusions

We have integrated differential expression data to reveal putative genes and detected four potential miRNA-target gene pathways through bioinformatics analysis that represent new mediators of abnormal gene expression and promising therapeutic targets in OA.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12891-021-04894-2.

A Network-Based Methodology to Identify Subnetwork Markers for Diagnosis and Prognosis of Colorectal Cancer

The development of reliable methods for identification of robust biomarkers for complex diseases is critical for disease diagnosis and prognosis efforts. Integrating multi-omics data with protein-protein interaction (PPI) networks to investigate diseases may help better understand disease characteristics at the molecular level. In this study, we developed and tested a novel network-based method to detect subnetwork markers for patients with colorectal cancer (CRC). We performed an integrated omics analysis using whole-genome gene expression profiling and copy number alterations (CNAs) datasets followed by building a gene interaction network for the significantly altered genes. We then clustered the constructed gene network into subnetworks and assigned a score for each significant subnetwork. We developed a support vector machine (SVM) classifier using these scores as feature values and tested the methodology in independent CRC transcriptomic datasets. The network analysis resulted in 15 subnetwork markers that revealed several hub genes that may play a significant role in colorectal cancer, including PTP4A3, FGFR2, PTX3, AURKA, FEN1, INHBA, and YES1. The 15-subnetwork classifier displayed over 98 percent accuracy in detecting patients with CRC. In comparison to individual gene biomarkers, subnetwork markers based on integrated multi-omics and network analyses may lead to better disease classification, diagnosis, and prognosis.

Contribution of endothelial cell-derived transcriptomes to the colon cancer based on bioinformatics analysis

Colon tumor endothelial cells (CTECs) plays substantial roles to induce immune invasion, angiogenesis and metastasis. Thus, identification of the CTECs-derived transcriptomes could be helpful for colon cancer diagnosis and potential therapy.

METHODS

By analysis of CTECs-derived gene expression profiling dataset, we identified differentially expressed genes (DEGs) between CTECs and colon normal endothelial cells (CNECs). In addition, we identified the significant pathways and protein-protein interaction (PPI) network that was significantly associated with the DEGs. Furthermore, we identified hub genes whose expression was significantly associated with prognosis and immune cell infiltrations in colon cancer. Finally, we identified the significant correlations between the prognostic hub genes and immune-inhibitory markers in colon cancer.

RESULTS

We identified 362 DEGs in CTECs relative to the CNECs, including117 up-regulated genes and 245 down-regulated genes in the CTECs. In addition, we identified significantly up-regulated pathways in CTECs that were mainly involved in cancer and immune regulation. Furthermore, we identified hub genes (such as SPARC, COL1A1, COL1A2 and IGFBP3) that are associated with prognosis and immune cells infiltrations in colon cancer. Interestingly, we found that prognosis-associated hub genes (SPARC, COL1A1, COL1A2 and IGFBP3) are positively correlated with immune-inhibitory markers of various immunosuppressive cells, including TAM, M2 macrophage, Tregs and T cell exhaustion. Finally, our findings revealed that prognosis-associated upregulated hub genes are positively correlated with immune checkpoint markers, including PD-L1 and PD-L2 and the immunosuppressive markers including TGFB1 and TGFBR1.

CONCLUSIONS

The identification of CTECs-specific transcriptomes may provide crucial insights into the colon tumor microenvironment that mediates the development of colon cancer.

Infiltrative tumour growth pattern correlates with poor outcome in oesophageal cancer

Objective

Oesophageal cancer (OEC) is an aggressive disease with a poor survival rate. Prognostic markers are thus urgently needed. Due to the demonstrated prognostic value of histopathological growth pattern (HGP) in other cancers, we performed a retrospective assessment of HGP in patients suffering from invasive OEC.

Design

A first cohort composed of 89 treatment-naïve operated patients with OEC from The Cancer Genome Atlas (TCGA) public database was constituted, from which H&E images and RNA-sequencing data were retrieved. Next, a second cohort composed of 99 patients with OEC treated and operated in a Belgian hospital was established. H&E-stained sections and extracted tumorous RNA were obtained from the samples. HGP were assessed on H&E slides as infiltrative (IGP) or expansive (EGP). TCGA RNA-sequencing data were analysed through the gene set enrichment analysis and Cytoscape softwares. Real-time quantitative PCR (qPCR) experiments were performed to assess gene expression in the Belgian cohort.

Results

IGP patients displayed a grim prognosis compared with EGP patients, while IGP was found as associated with numerous lymphovascular emboli and perinervous infiltrations. Analyses of the TCGA expression data showed that angiogenesis, epithelial-to-mesenchymal transition (EMT) and inflammation were significantly upregulated in IGP compared with EGP samples. qPCR experiments of three genes appearing as highly upregulated in each pathway showed no difference in expression according to the HGP.

Conclusion

The current study demonstrates the poor prognostic value carried by IGP in OC and suggests angiogenesis, EMT and inflammation as key carcinogenetic pathways upregulated in this pattern.

Deciphering microRNA-mRNA regulatory network in adult T-cell leukemia/lymphoma; the battle between oncogenes and anti-oncogenes

Adult T-cell leukemia/lymphoma (ATLL) is virus-caused cancer that originates from the infection by human T-cell leukemia virus type 1. ATLL dysregulates various biological pathways related to the viral infection and cancer progression through the dysexpression of miRNAs and mRNAs. In this study, the potential regulatory subnetworks were constructed aiming to shed light on the pathogenesis mechanism of ATLL. For this purpose, two mRNA and one miRNA expression datasets were firstly downloaded from the GEO database. Next, the differentially expressed genes and miRNAs (DEGs and DE-miRNAs, respectively), as well as differentially co-expressed gene pairs (DCGs), were determined. Afterward, common DEGs and DCGs targeted by experimentally validated DE-miRNAs were explored. The oncogenic and anti-oncogenic miRNA-mRNA regulatory subnetworks were then generated. The expression levels of four genes and two miRNAs were examined in the blood samples by qRT-PCR. The members of three oncogenic/anti-oncogenic subnetworks were generally enriched in immune, virus, and cancer-related pathways. Among them, FZD6, THBS4, SIRT1, CPNE3, miR-142-3p, and miR-451a were further validated by real-time PCR. The significant up-regulation of FZD6, THBS4, and miR-451a as well as down-regulation of CPNE3, SIRT1, and miR-142-3p were found in ATLL samples than normal samples. The identified oncogenic/anti-oncogenic subnetworks are pieces of the pathogenesis puzzle of ATLL. The ultimate winner is probably an oncogenic network that determines the final fate of the disease. The identified genes and miRNAs are proposed as novel prognostic biomarkers for ATLL.

COL5A2 as a potential clinical biomarker for gastric cancer and renal metastasis

BACKGROUND

Gastric cancer, characterized by insidious onset and multiple metastasis, is almost incurable and has poor prognosis, and also one of the leading causes of treatment failure and death in patients with gastric cancer (GC). However, the prognosis of collagen type V alpha2 chain (COL5A2) in GC and renal metastasis is unknown.

METHODS

Recruited 148 patients who underwent GC. The diagnosis of GC was confirmed by ultrasound imaging and pathological examination. Immunohistochemistry and RT-qPCR were performed to exam the expression level of COL5A2. The statistical methods included Pearson chi-square test, Spearman-rho correlation test, univariate and multivariate cox regression analysis. Finally, this research constructed receiver operating characteristic (ROC) curves and applied the area under the curve (AUC).

RESULTS

Based on Pearson's chi-square test, Spearman-rho test, and univariate/multivariate cox regression, pathologic grade (P < .001), renal metastasis (P < .001) and staging (P < .001) were significantly related to COL5A2. And COL5A2 expression (hazard ratio [HR]: 18.834, P < .001) is an independent risk factor of GC. The AUC was used as the degree of confidence in judging each factor: COL5A2 (AUC = 0.878, P < .001), COL1A1 (AUC = 0.636, P = .006), COL1A2 (AUC = 0.545, P = .368), and COL3A1 (AUC = 0.617, P = .019). Through the ROC result, COL5A2 had more advantage as a biomarker for GC than other collagens.

CONCLUSIONS

COL5A2 gene expression level might be a risk factor for GC. COL5A2 has a strong correlation with the prognosis of the disease.

MiR-1254 and MEGF6 regulates oxaliplatin resistance in human colorectal cancer cells

Colorectal cancer (CRC) remains one of the deadliest diseases in the whole world. Cancer recurrence and chemotherapeutic drug resistance limit the overall survival rate of patients with CRC. This study aimed to discover the latent miRNAs and genes associated with oxaliplatin resistance in CRC cells. The study found that miR-1254 is upregulated in oxaliplatin-resistant CRC cell line HCT116-R compared with its parental cell line HCT116 by transcriptome sequencing and small RNA sequencing. Meanwhile, MEGF6 (multiple EGF-like domains 6) was downregulated in HCT116-R cells. Transient transfection of miR-1254 mimics significantly reduced cell apoptosis, increased HCT116 tolerance to oxaliplatin, and enhanced MEGF6 expression. Furthermore, transfection of miR-1254 inhibitor increased apoptosis, decreased HCT116-R tolerance to oxaliplatin, and reduced MEGF6 expression. In addition, transient transfection of SiMEGF6 enhanced HCT116 cell resistance to oxaliplatin and reduced cell apoptosis. In summary, MEGF6 is a latent functional target of miR-1254 in regulating oxaliplatin resistance and apoptosis in human CRC cells, suggesting a potential therapeutic target for CRC.

The landscape of long non-coding RNAs in tumor stroma

AIMS

Long non-coding RNAs (lncRNAs) are associated with cancer development, while their relationship with the cancer-associated stromal components remains poorly understood. In this review, we performed a broad description of the functional landscape of stroma-associated lncRNAs in various cancers and their roles in regulating the tumor-stroma crosstalk.

MATERIALS AND METHODS

We carried out a systematic literature review of PubMed, Scopus, Medline, Bentham, and EMBASE (Elsevier) databases by using the keywords "LncRNAs in cancer," "LncRNAs in tumor stroma," "stroma," "cancer-associated stroma," "stroma in the tumor microenvironment," "tumor-stroma crosstalk," "drug resistance of stroma," and "stroma in immunosuppression" till July 2020. We collected the latest articles addressing the biological functions of stroma-associated lncRNAs in cancer.

KEY FINDINGS

These articles reported that dysregulated stroma-associated lncRNAs play significant roles in modulating the tumor microenvironment (TME) by the regulation of tumor-stroma crosstalk, epithelial to mesenchymal transition (EMT), endothelial to mesenchymal transition (EndMT), extracellular matrix (ECM) turnover, and tumor immunity.

SIGNIFICANCE

The tumor stroma is a substantial portion of the TME, and the dysregulation of tumor stroma-associated lncRNAs significantly contributes to cancer initiation, progression, angiogenesis, immune evasion, metastasis, and drug resistance. Thus, stroma-associated lncRNAs could be potentially useful targets for cancer therapy.

Construction of Potential miRNA-mRNA Regulatory Network in COPD Plasma by Bioinformatics Analysis

Background

Chronic obstructive pulmonary disease (COPD) has become a major cause of morbidity and mortality worldwide. Increasing evidence indicates that aberrantly expressed microRNAs (miRNAs) are involved in the pathogenesis of COPD. However, an integrative exploration of miRNA–mRNA regulatory network in COPD plasma remains lacking.

Methods

The microarray datasets GSE24709, GSE61741, and GSE31568 were downloaded from the GEO database and analyzed using GEO2R tool to identify differentially expressed miRNAs (DEMs) between COPD and normal plasma. The consistently changing miRNAs in the three datasets were screened out as candidate DEMs. Potential upstream transcription factors and downstream target genes of candidate DEMs were predicted by FunRich and miRNet, respectively. Next, GO annotation and KEGG pathway enrichment analysis for target genes were performed using DAVID. Then, PPI and DEM-hub gene network were constructed using the STRING database and Cytoscape software. Finally, GSE56768 was used to evaluate the hub gene expressions.

Results

A total of nine (six upregulated and three downregulated) DEMs were screened out in the above three datasets. SP1 was predicted to potentially regulate most of the downregulated DEMs, while YY1 and E2F1 could regulate both upregulated and downregulated DEMs. 1139 target genes were then predicted, including 596 upregulated DEM target genes and 543 downregulated DEM target genes. Target genes of DEMs were mainly enriched in PI3K/Akt signaling pathway, mTOR signaling pathway, and autophagy. Through the DEM-hub gene network construction, most of the hub genes were found to be potentially modulated by miR-497-5p, miR-130b-5p, and miR-126-5p. Among the top 12 hub genes, MYC and FOXO1 expressions were consistent with that in the GSE56768 dataset.

Conclusion

In the study, potential miRNA–mRNA regulatory network was firstly constructed in COPD plasma, which may provide a new insight into the pathogenesis and treatment of COPD.

Exosomal miRNAs in tumor microenvironment

Tumor microenvironment (TME) is the internal environment in which tumor cells survive, consisting of tumor cells, fibroblasts, endothelial cells, and immune cells, as well as non-cellular components, such as exosomes and cytokines. Exosomes are tiny extracellular vesicles (40-160nm) containing active substances, such as proteins, lipids and nucleic acids. Exosomes carry biologically active miRNAs to shuttle between tumor cells and TME, thereby affecting tumor development. Tumor-derived exosomal miRNAs induce matrix reprogramming in TME, creating a microenvironment that is conducive to tumor growth, metastasis, immune escape and chemotherapy resistance. In this review, we updated the role of exosomal miRNAs in the process of TME reshaping.