Identification of a miRNA-mRNA network associated with lymph node metastasis in colorectal cancer

Patterns of Gene Expression Profiles Associated with Colorectal Cancer in Colorectal Mucosa by Using Machine Learning Methods

BACKGROUND

Colorectal cancer (CRC) has a very high incidence and lethality rate and is one of the most dangerous cancer types. Timely diagnosis can effectively reduce the incidence of colorectal cancer. Changes in para-cancerous tissues may serve as an early signal for tumorigenesis. Comparison of the differences in gene expression between para-cancerous and normal mucosa can help in the diagnosis of CRC and understanding the mechanisms of development.

OBJECTIVES

This study aimed to identify specific genes at the level of gene expression, which are expressed in normal mucosa and may be predictive of CRC risk.

METHODS

A machine learning approach was used to analyze transcriptomic data in 459 samples of normal colonic mucosal tissue from 322 CRC cases and 137 non-CRC, in which each sample contained 28,706 gene expression levels. The genes were ranked using four ranking methods based on importance estimation (LASSO, LightGBM, MCFS, and mRMR) and four classification algorithms (decision tree [DT], K-nearest neighbor [KNN], random forest [RF], and support vector machine [SVM]) were combined with incremental feature selection [IFS] methods to construct a prediction model with excellent performance.

RESULT

The top-ranked genes, namely, HOXD12, CDH1, and S100A12, were associated with tumorigenesis based on previous studies.

CONCLUSION

This study summarized four sets of quantitative classification rules based on the DT algorithm, providing clues for understanding the microenvironmental changes caused by CRC. According to the rules, the effect of CRC on normal mucosa can be determined.

Non-coding RNAs: a promising target for early metastasis intervention

ABSTRACT

Metastases account for the overwhelming majority of cancer-associated deaths. The dissemination of cancer cells from the primary tumor to distant organs involves a complex process known as the invasion-metastasis cascade. The underlying biological mechanisms of metastasis, however, remain largely elusive. Recently, the discovery and characterization of non-coding RNAs (ncRNAs) have revealed the diversity of their regulatory roles, especially as key contributors throughout the metastatic cascade. Here, we review recent progress in how three major types of ncRNAs (microRNAs, long non-coding RNAs, and circular RNAs) are involved in the multistep procedure of metastasis. We further examine interactions among the three ncRNAs as well as current progress in their regulatory mechanisms. We also propose the prevention of metastasis in the early stages of cancer progression and discuss current translational studies using ncRNAs as targets for metastasis diagnosis and treatments. These studies provide insights into developing more effective strategies to target metastatic relapse.

Sustainable and high-level microbial production of plant hemoglobin in Corynebacterium glutamicum

BACKGROUND

Plant hemoglobin shows great potential as a food additive to circumvent the controversy of using animal materials. Microbial fermentation with engineered microorganisms is considered as a promising strategy for sustainable production of hemoglobin. As an endotoxin-free and GRAS (generally regarded as safe) bacterium, Corynebacterium glutamicum is an attractive host for hemoglobin biosynthesis.

RESULTS

Herein, C. glutamicum was engineered to efficiently produce plant hemoglobin. Hemoglobin genes from different sources including soybean and maize were selected and subjected to codon optimization. Interestingly, some candidates optimized for the codon usage bias of Escherichia coli outperformed those for C. glutamicum regarding the heterologous expression in C. glutamicum. Then, saturated synonymous mutation of the N-terminal coding sequences of hemoglobin genes and fluorescence-based high-throughput screening produced variants with 1.66- to 3.45-fold increase in hemoglobin expression level. To avoid the use of toxic inducers, such as isopropyl-β-D-thiogalactopyranoside, two native inducible expression systems based on food additives propionate and gluconate were developed. Promoter engineering improved the hemoglobin expression level by 2.2- to 12.2-fold. Combination of these strategies and plasmid copy number modification allowed intracellular production of hemoglobin up to approximately 20% of total protein. Transcriptome and proteome analyses of the hemoglobin-producing strain revealed the cellular response to excess hemoglobin accumulation. Several genes were identified as potential targets for further enhancing hemoglobin production.

CONCLUSIONS

In this study, production of plant hemoglobin in C. glutamicum was systematically engineered by combining codon optimization, promoter engineering, plasmid copy number modification, and multi-omics-guided novel target discovery. This study offers useful design principles to genetically engineer C. glutamicum for the production of hemoglobin and other recombinant proteins.

A Transcriptome Sequencing Study on Genome-Wide Gene Expression Differences of Lung Cancer Cells Modulated by Fucoidan

Fucoidan has received increasing attention in anti-(lung) tumors. However, the effect of fucoidan on the gene changes of lung cancer cells (LCCs) has not been examined systematically. Herein, we investigate the effect of fucoidan on the phenotypes of LCCs and their gene expression by transcriptome sequencing analysis. The phenotypes of LCCs are significantly inhibited by fucoidan. Importantly, compared to LCCs, 1 mg/ml fucoidan has no effect on the phenotypes of normal cells. Further, 6,930 differentially expressed genes (DEGs) in the transcriptome of LCCs (3,501 up-regulated and 3,429 down-regulated genes) are detected via RNA-sequencing between the fucoidan and control groups. Gene Ontology analysis confirms that DEGs are reflected in DNA replication, cell-substrate junction, regulation of cell cycle phase transition, apoptosis, focal adhesion, cadherin binding, and cell adhesion molecule binding. Thus, our findings on the transcriptomic level highlight the therapeutic potential of fucoidan for lung cancer treatment.

Profiling and Integrated Analysis of Differentially Expressed MicroRNAs as Novel Biomarkers of Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is a heterogeneous disease that has multiple etiologies. It is the most common primary liver cancer, the sixth highest cause of cancer incidences, and the fourth highest cause of cancer-related deaths. The discovery of new biomarkers for the early detection, treatment, and prognosis of HCC would therefore be extremely useful. This study investigated differentially expressed ribonucleic acid (RNA) profiles by constructing a genome-wide profile of clinical samples. Differential expression analysis identified 1,280 differentially expressed messenger RNAs (dif-mRNAs), 99 differentially expressed microRNAs (dif-miRNAs), 181 differentially expressed long non-coding RNAs (dif-lncRNAs), and 31 differentially expressed circular RNAs (dif-circRNAs). Gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) path analysis were then conducted on these differentially expressed RNAs, revealing that they were clearly related to cell division, foreign body metabolism, and ribosome assembly. A competing endogenous RNA (ceRNA) network was then constructed based on the regulatory dif-miRNA-dif-mRNA and dif-miRNA-dif-lncRNA relationships. These results were also verified using HCC data from the Cancer Genome Atlas (TCGA); seven dif-miRNAs were verified in clinical samples by real-time quantitative polymerase chain reaction (RT-qPCR). Kaplan-Meier survival analysis revealed that the expression levels of Hsa-miR-1269a, Hsa-miR-421, and Hsa-miR-190b were correlated with overall survival. (P <0.05). Survival analysis of clinical samples showed that hsa-mir-1269a, hsa-mir-421 were associated with prognosis (p<0.05).This study revealed the general expression characteristics of specific differentially expressed miRNAs using a ceRNA network constructed from HCC samples. Hsa-mir-1269a, hsa-mir-421 may be promising candidates.

The bioinformatics and experimental analysis of AlkB family for prognosis and immune cell infiltration in hepatocellular carcinoma

BACKGROUND

Serving as N6-methyladenosine demethylases, the AlkB family is involved in the tumorigenesis of hepatocellular carcinoma (HCC). However, the molecular profiles and clinical values of the AlkB family in HCC are not well known.

METHODS

Several bioinformatics tools and in vitro experiments were used to identify the immune-related profiles and prognostic values of AlkB family in HCC.

RESULTS

In this study expression levels of ALKBH1/2/3/4/7 were all remarkably increased in HCC tissues when compared with normal tissues. Quantitative PCR (qPCR) and immunohistochemistry were used to validate the expression of AlkB family members in HCC tissues and normal liver tissues. In addition, high expression levels of ALKBH4 were negatively correlated with overall survival (OS) and disease-free survival (DFS) in patients with HCC. Increased ALKBH4 was also associated with pathological stage in HCC patients. The molecular profiles of AlkB family in HCC were mainly associated with peptidyl-serine modification, peptidyl-tyrosine modification, regulation of metal ion transport, etc. Furthermore, tumor-infiltrating immune cell analysis indicated that ALKBH1/2/3/4/5/6/7/8 and FTO were related to the infiltration of different immune cell, such as CD8+ T cells, macrophages, neutrophils, dendritic cells and CD4+ T cells. We also discovered that the methylation levels of ALKBH1/2/4/5/6/8 and FTO were remarkably reduced in HCC tissues.

CONCLUSIONS

Collectively, our findings may deepen the understanding of specific molecular profiles of the AlkB family in HCC pathology. In particular, ALKBH4 could serve as a promising prognostic candidate for treating HCC, and these results might potentiate the development of more reliable therapeutic strategies for patients with HCC.

Predictive Value of Circulating miRNAs in Lymph Node Metastasis for Colon Cancer

(1) Background: Lymph node (LN) status is an indubitable prognostic factor for survival among colon cancer patients. MicroRNAs (miRNAs) have been implicated in the development and progression of many cancers and are potential biomarkers for cancer diagnosis and prognosis. Therefore, we validated candidate biomarkers using circulating miRNAs by analyzing the plasma miRNA concentrations from patients with colon cancer to predict LN metastasis. (2) Methods: This study included 79 blood samples from patients diagnosed with colon cancer. The NanoString assay was used for screening, and TaqMan miRNA assays for quantitative real-time polymerase chain reaction (RT-PCR) test was used for validation. In a discovery set, we compared the expression of 800 circulating miRNAs in 24 samples (stage 0/I/IIA versus IIIB/IIIC). For validation, a total 79 samples were tested using quantitative RT-PCR. (3) Results: In the discovery set, 10 candidate circulating miRNAs were detected (4 up-regulated miRNAs: miR-323a-3p, miR-382-5p, miR-29a-3p, and miR-376a-3p; 6 down-regulated miRNAs: miR-26a-5p, let-7g-5p, miR-15b-5p, miR-142-3p, miR-374a-5p, and let-7b-5p). In the validation set, higher expression of three circulating miRNAs (miR-323a-3p, miR-382-5p, and miR-376a-3p) was significantly associated with LN metastasis (p = 0.0063, 0.0107, and 0.0022). (4) Conclusions: High expression of circulating miR-323a-3p, miR-382-5p, and miR-376a-3p was significantly associated with LN metastasis in colon cancer patients. These miRNAs could be circulating biomarker candidates that predict the presence of LN metastasis.

Histone demethylase KDM5A promotes tumorigenesis of osteosarcoma tumor

Osteosarcoma is a primary bone malignancy with a high rate of recurrence and poorer prognosis. Therefore, it is of vital importance to explore novel prognostic molecular biomarkers and targets for more effective therapeutic approaches. Previous studies showed that histone demethylase KDM5A can increase the proliferation and metastasis of several cancers. However, the function of KDM5A in the carcinogenesis of osteosarcoma is not clear. In the current study, KDM5A was highly expressed in osteosarcoma than adjacent normal tissue. Knockdown of KDM5A suppressed osteosarcoma cell proliferation and induced apoptosis. Moreover, knockdown of KDM5A could increase the expression level of P27 (cell-cycle inhibitor) and decrease the expression of Cyclin D1. Furthermore, after knockout of KDM5A in osteosarcoma cells by CRISPR/Cas9 system, the tumor size and growth speed were inhibited in tumor-bearing nude mice. RNA-Seq of KDM5A-KO cells indicated that interferon, epithelial–mesenchymal transition (EMT), IL6/JAK/STAT3, and TNF-α/NF-κB pathway were likely involved in the regulation of osteosarcoma cell viability. Taken together, our research established a role of KDM5A in osteosarcoma tumorigenesis and progression.

Integrative expression network analysis of microRNA and gene isoforms in sacred lotus

Background

Gene expression is complex and regulated by multiple molecular mechanisms, such as miRNA-mediated gene inhibition and alternative-splicing of pre-mRNAs. However, the coordination of interaction between miRNAs with different splicing isoforms, and the change of splicing isoform in response to different cellular environments are largely unexplored in plants. In this study, we analyzed the miRNA and mRNA transcriptome from lotus (Nelumbo nucifera), an economically important flowering plant.

Results

Through RNA-seq analyses on miRNAs and their target genes (isoforms) among six lotus tissues, expression of most miRNAs seem to be negatively correlated with their targets and tend to be tissue-specific. Further, our results showed that preferential interactions between miRNAs and hub gene isoforms in one coexpression module which is highly correlated with leaf. Intriguingly, for many genes, their corresponding isoforms were assigned to different co-expressed modules, and they exhibited more divergent mRNA structures including presence and absence of miRNA binding sites, suggesting functional divergence for many isoforms is escalated by both structural and expression divergence. Further detailed functional enrichment analysis of miRNA targets revealed that miRNAs are involved in the regulation of lotus growth and development by regulating plant hormone-related pathway genes.

Conclusions

Taken together, our comprehensive analyses of miRNA and mRNA transcriptome elucidate the coordination of interaction between miRNAs and different splicing isoforms, and highlight the functional divergence of many transcript isoforms from the same locus in lotus.

Genome-wide analysis of prognostic-related lncRNAs, miRNAs and mRNAs forming a competing endogenous RNA network in lung squamous cell carcinoma

PURPOSE

As a type of cancer with the highest morbidity and mortality, lung squamous cell carcinoma (LUSC) has a very poor prognosis. Long-non-coding RNA (lncRNA) has recently attracted attentions because it can play the role of competing endogenous RNA (ceRNA) to inhibit microRNA (miRNA) functions. In this study, we aimed to find prognosis-related lncRNAs, miRNAs and mRNAs and construct a prognosis-related ceRNA network.

METHODS

The original LUSC RNA-sequencing data and miRNA profiles data were downloaded from the cancer genome atlas (TCGA) database. Differentially expressed lncRNAs, miRNAs and mRNAs were then identified between patients with lymph node metastasis and no lymph node metastasis. Univariate Cox regression analysis was performed to find the survival-associated lncRNAs, miRNAs and mRNAs. Subsequently, prognostic-related ceRNA network was established. By multivariate Cox regression analysis, three lncRNA signatures and three mRNA signatures were developed and used for predicting LUSC patients' survival.

RESULTS

A total of 224 lncRNAs, 160 miRNAs, 913 mRNAs were identified between samples with lymph node metastasis and no lymph node metastasis. Univariate Cox regression analysis showed that, among them, 28 lncRNAs, 8 miRNAs, 105 mRNAs were significantly associated with patients' overall survival time. Further pathway and enrichment analysis suggested that these mRNAs were associated with the regulation of transmembrane transport, regulation of blood circulation, plasma lipoprotein particle organization. Then we constructed a survival-related ceRNA network including 9 lncRNAs, 8 miRNAs and 23 mRNAs. Additionally, a multivariate Cox regression analysis demonstrated that three lncRNAs (AL161431.1, LINC02389, APCDD1L.DT) and three mRNAs (KLK6, SLITRK5, CCDC177) had a significant prognostic value. Risk score indicated that lncRNA signature and mRNA signature could independently predict overall survival in LUSC patients.

CONCLUSION

The current study provided a better understanding of the ceRNA network in the progression of LUSC and laid a theoretical foundation for LUSC prognosis.

A Circulating miRNA-Based Scoring System Established by WGCNA to Predict Colon Cancer

Introduction

Circulation microRNAs (miRNAs) perform as potential diagnostic biomarkers of many kinds of cancers. This study is aimed at identifying circulation miRNAs as diagnostic biomarkers in colon cancer.

Methods

We conducted a weighted gene coexpression network analysis (WGCNA) in miRNAs to find out the expression pattern among circulation miRNAs by using a “WGCNA” package in R. Correlation analysis was performed to find cancer-related modules. Differentially expressed miRNAs (DEmiRs) in colon cancer were identified by a “limma” package in R. Hub gene analysis was conducted for these DEmiRs in the cancer-related modules by the “closeness” method in cytoscape software. Then, logistic regression was performed to identify the independent risk factors, and a scoring system was constructed based on these independent risk factors. Then, we use data from the GEO database to confirm the reliability of this scoring system.

Results

A total of 9 independent coexpression modules were constructed based on the expression levels of 848 miRNAs by WGCNA. After correlation analysis, green (cor = 0.77, p = 3 × 10^‐25) and yellow (cor = 0.65, p = 6 × 10^‐16) modules were strongly correlated with cancer development. 20 hub genes were found after hub gene analysis in these DEmiRs by cytoscape. Among all these hub genes, hsa-miR-23a-3p (OR = 2.6391, p = 6.23 × 10^‐5) and hsa-miR-663a (OR = 1.4220, p = 0.0069) were identified as an independent risk factor of colon cancer by multivariate regression. Furthermore, a scoring system was built to predict the probability of colon cancer based on both of these miRNAs, the area under the curve (AUC) of which was 0.828. Data from GSE106817 and GSE112264 was used to confirm this scoring system. And the AUC of them was 0.980 and 0.917, respectively.

Conclusion

We built a scoring system based on circulation hub miRNAs found by WGCNA to predict the development of colon cancer.