Integrated Analysis of ceRNA Network Reveals Prognostic and Metastasis Associated Biomarkers in Breast Cancer

Importance of LINC00852/miR-145-5p in breast cancer: a bioinformatics and experimental study

PURPOSE

We aimed to examine the importance of an lncRNA, namely LINC00852, in the pathogenesis of breast cancer.

MATERIALS AND METHODS

In the current study, we used several online tools to examine the importance of LINC00852 in breast cancer. Then, we examined these findings in 50 pairs of breast cancer tissues and adjacent non-cancerous ones. We also re-evaluated the data of miR-145-5p signature from our recent study.

RESULTS

While in silico tools revealed down-regulation of LINC00852 in breast cancer samples, expression assays showed significant up-regulation of this lncRNAs in breast cancer samples compared with matching control samples from Iranian patients. miR-145-5p was under-expressed in breast cancer samples compared with non-cancerous samples. LINC00852 could separate breast cancer tissues from adjacent non-malignant tissues with an AUC value of 0.7218 (P value < 0.001).

CONCLUSION

The current study potentiates LINC00852/miR-145-5p axis as a possible contributor to the pathogenesis of breast cancer.

Kinesin Family Member C1: Function in liver hepatocellular carcinoma and potential target for chemotherapeutic

MiR-105 exerts inhibitory effects on the development and progression of various cancers, including breast cancer, lung cancer, and gastric cancer. Through GEO data analysis, we observed decreased expression of miR-105 in liver cancer tissues compared to adjacent tissues. Furthermore, miR-105 downregulates KIFC1 expression levels by targeting its 3' UTR. KIFC1 (Kinesin Family Member C1), a Protein Coding gene, may play a role in mitotic metaphase plate polymerization and mitotic spindle assembly. However, our findings suggest that this gene could serve as a potential chemotherapeutic target for Liver hepatocellular carcinoma (LIHC). We obtained the LIHC dataset from the TCGA database and genotype Tissue Expression Project (GTEx) normal tissue data for differential analysis. Additionally, we utilized the cBioPortal database, tumor immune single-cell center (TISCH) database, gene set enrichment analysis (GSEA), and R software to investigate the possible functions and mechanisms of KIFC1. These findings were further validated through experiments such as immunohistochemistry and wound healing assays. Our results indicate that KIFC1 might be involved in DNA repair and cell cycle regulation in LIHC cells which subsequently impacts tumor cell proliferation; moreover, miR-105 influences hepatoma cell line proliferation via its interaction with KIFC1. Collectively, these results highlight the potential therapeutic significance of targeting KIFC1 for chemotherapy treatment in LIHC patients.

Coding, or non-coding, that is the question

The advent of high-throughput sequencing uncovered that our genome is pervasively transcribed into RNAs that are seemingly not translated into proteins. It was also found that non-coding RNA transcripts outnumber canonical protein-coding genes. This mindboggling discovery prompted a surge in non-coding RNA research that started unraveling the functional relevance of these new genetic units, shaking the classic definition of "gene". While the non-coding RNA revolution was still taking place, polysome/ribosome profiling and mass spectrometry analyses revealed that peptides can be translated from non-canonical open reading frames. Therefore, it is becoming evident that the coding vs non-coding dichotomy is way blurrier than anticipated. In this review, we focus on several examples in which the binary classification of coding vs non-coding genes is outdated, since the same bifunctional gene expresses both coding and non-coding products. We discuss the implications of this intricate usage of transcripts in terms of molecular mechanisms of gene expression and biological outputs, which are often concordant, but can also surprisingly be discordant. Finally, we discuss the methodological caveats that are associated with the study of bifunctional genes, and we highlight the opportunities and challenges of therapeutic exploitation of this intricacy towards the development of anticancer therapies.

Prognostic analysis and risk assessment based on RNA editing in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality, and prognosis assessment is crucial for guiding treatment decisions. In this study, we aimed to develop a personalized prognostic model for HCC based on RNA editing. RNA editing is a post-transcriptional process that can affect gene expression and, in some cases, play a role in cancer development. By analyzing RNA editing sites in HCC, we sought to identify a set of sites associated with patient prognosis and use them to create a prognostic model. We gathered RNA editing data from the Synapse database, comprising 9990 RNA editing sites and 250 HCC samples. Additionally, we collected clinical data for 377 HCC patients from the Cancer Genome Atlas (TCGA) database. We employed a multi-step approach to identify prognosis-related RNA editing sites (PR-RNA-ESs). We assessed how patients in the high-risk and low-risk groups, as defined by the model, fared in terms of survival. A nomogram was developed to predict the precise survival prognosis of HCC patients and assessed the prognostic model's utility through a receiver operating characteristic (ROC) analysis and decision curve analysis (DCA). Our analysis identified 33 prognosis-related RNA editing sites (PR-RNA-ESs) associated with HCC patient prognosis. Using a combination of LASSO regression and cross-validation, we constructed a prognostic model based on 13 PR-RNA-ESs. Survival analysis demonstrated significant differences in the survival outcomes of patients in the high-risk and low-risk groups defined by this model. Additionally, the differential expression of the 13 PR-RNA-ESs played a role in shaping patient survival. Risk-prognostic investigations further distinguished patients based on their risk levels. The nomogram enabled precise survival prognosis prediction. Our study has successfully developed a highly personalized and accurate prognostic model for individuals with HCC, leveraging RNA editing data. This model has the potential to revolutionize clinical evaluation and medical management by providing individualized prognostic information. The identification of specific RNA editing sites associated with HCC prognosis and their incorporation into a predictive model holds promise for improving the precision of treatment strategies and ultimately enhancing patient outcomes in HCC.

Competing endogenous RNAs in head and neck squamous cell carcinoma: a review

Our understanding of RNA biology has evolved with recent advances in research from it being a non-functional product to molecules of the genome with specific regulatory functions. Competitive endogenous RNA (ceRNA), which has gained prominence over time as an essential part of post-transcriptional regulatory mechanism, is one such example. The ceRNA biology hypothesis states that coding RNA and non-coding RNA co-regulate each other using microRNA (miRNA) response elements. The ceRNA components include long non-coding RNAs, pseudogene and circular RNAs that exert their effect by interacting with miRNA and regulate the expression level of its target genes. Emerging evidence has revealed that the dysregulation of the ceRNA network is attributed to the pathogenesis of various cancers, including the head and neck squamous cell carcinoma (HNSCC). This is the most prevalent cancer developed from the mucosal epithelium in the lip, oral cavity, larynx and pharynx. Although many efforts have been made to comprehend the cause and subsequent treatment of HNSCC, the morbidity and mortality rate remains high. Hence, there is an urgent need to understand the holistic progression of HNSCC, mediated by ceRNA, that can have immense relevance in identifying novel biomarkers with a defined therapeutic intervention. In this review, we have made an effort to highlight the ceRNA biology hypothesis with a focus on its involvement in the progression of HNSCC. For the identification of such ceRNAs, we have additionally highlighted a number of databases and tools.

Construction of ceRNA network and identification of hub differentially expressed genes associated with breast cancer using reanalysis of microarray dataset: A systems biology approach

The interaction between long non-coding RNAs (lncRNAs), miRNAs and mRNAs has implications in the pathogenesis of different cancer, including breast cancer. In the current study, we developed an in-silico approach to ascertain the competing endogenous RNA (ceRNA) network in breast cancer. Our approach led to identification of 1816 differentially expressed (DE) mRNAs, including 1039 downregulated DEmRNAs (such as LEP and ADIPOQ) and 777 upregulated DEmRNAs (such as COL11A1 and COL10A1), 19 DElncRNAs, including 15 downregulated DElncRNAs (such as CARMN and COPG2IT1) and 4 upregulated DElncRNAs (such as MALAT1 and NRAV) and 27 DEmiRNAs, including 15 downregulated DEmiRNAs (such as MIR452 and MIR224) and 12 upregulated DEmiRNAs (such as MIR6787 and MIR21). Pathway analysis revealed down-regulation of PPAR, Fatty acid metabolism, Adipocytokine, Vascular smooth muscle contraction and Metabolism of xenobiotics by cytochrome P450, while up-regulation of Pyrimidine metabolism, p53 signaling pathway, Cell cycle, Oocyte meiosis and RNA transport pathways in breast cancer. Finally, we constructed an lncRNA/miRNA/mRNA ceRNA network consisted of 2 lncRNAs, 15 mRNAs, and 4 miRNAs. This network represents an appropriate target for design of anti-cancer modalities and documentation of novel markers for breast cancer.

The diagnostic potential of a circRNA-miRNA network in non-small cell lung cancer

Increasing studies demonstrate the significant contributions of circRNA-related competitive endogenous RNA (ceRNA) regulatory networks to tumorigenesis and cancer progression. Here, we aimed to construct a non-small cell lung cancer (NSCLC)-specific circRNA-miRNA network and evaluate its diagnostic potential in NSCLC. MiRNA deep sequencing was performed to screen differentially-expressed serum miRNAs in NSCLC. Four bioinformatics databases (TargetScan, miRanda, starBase, and RNAhybrid) were used to analyze the integrated circRNA-miRNA interaction network. The circRNA-miRNA network, including hsa-miR-4482-3p, hsa-miR-146a-3p, hsa_circ_0008167 and hsa_circ_0003317 was constructed based on their interactions and preliminary testing in NSCLC cells. The relative levels of the selected non-coding RNAs (ncRNAs) were quantified using quantitative real-time polymerase chain reaction (qRT-PCR) in the healthy, pneumonia, benign lung tumor and NSCLC cohorts. The diagnostic power of the circRNA-miRNA network was evaluated using receiver operating characteristic (ROC) analyses. The serum levels of hsa-miR-4482-3p, hsa-miR-146a-3p, hsa_circ_0008167, and hsa_circ_0003317 were dysregulated in NSCLC. The combination of the four ncRNAs showed the highest diagnostic value to discriminate between benign lung tumors and NSCLC. Additionally, the upregulated levels of hsa_circ_0008167 were correlated to more aggressive features of NSCLC, such as lymph node metastasis, distant metastasis, and higher stage. Furthermore, the combination of hsa_circ_0008167 + hsa-miR-4482-3p, and hsa_circ_0008167 + hsa-miR-4482-3p + hsa-miR-146a-3p had the greatest diagnostic power to differentiate between lymph node +/- metastases and higher/lower stages, respectively, compared to circRNAs or miRNAs alone, and traditional tumor markers. In conclusion, we identified a specific circRNA-miRNA network with higher sensitivity and specificity to diagnose NSCLC, thereby providing a new strategy for further development of ceRNA-related tumor markers in other cancers. KEY MESSAGES: Serum miR-4482-3p, miR-146a-3p, circ_0008167 and circ_0003317 are dysregulated in NSCLC. Higher levels of serum circ_0008167 are associated with more malignant NSCLC. Multiple combinations of circRNAs and miRNAs show higher value to diagnose NSCLC.

ncRNA-mediated ceRNA regulatory network: Transcriptomic insights into breast cancer progression and treatment strategies

With the rapid development of next-generation sequencing technology, several studies have shown that ncRNAs can act as competitive endogenous RNAs (ceRNAs) and are involved in various biological processes, such as proliferation, differentiation, apoptosis, and migration of breast cancer (BC) cells, and plays an important role in BC progression as a molecular target for its diagnosis, treatment, prognosis, and differentiation of subtypes and age groups of BC patients. Based on the description of ceRNA-related biological functions, this study screened and sorted the sequencing analysis and experimental verification conclusions of BC-related ceRNAs and found that the ncRNAs mediated ceRNA networks can promote the development of BC by promoting the expression of genes related to BC proliferation, drug resistance, and apoptosis, inducing the production of epithelial-mesenchymal transition (EMT) to promote metastasis and activating cancer-related signaling pathways.

The prognostic value and response to immunotherapy of immunogenic cell death-associated genes in breast cancer

Breast cancer (BRCA) remains the most prevalent cancer worldwide and the tumor microenvironment (TME) has been discovered to exert a wide influence on the overall survival and therapeutic response. Numerous lines of evidence reported that the effects of immunotherapy of BRCA were manipulated by TME. Immunogenic cell death (ICD) is a form of regulated cell death (RCD) that is capable of fueling adaptive immune responses and aberrant expression of ICD-related genes (ICDRGs) can govern the TME system by emitting danger signals or damage-associated molecular patterns (DAMPs). In the current study, we obtained 34 key ICDRGs in BRCA. Subsequently, using the transcriptome data of BRCA from the TCGA database, we constructed a risk signature based on 6 vital ICDRGs, which had a good performance in predicting the overall survival of BRCA patients. We also examined the efficacy of our risk signature in the validation dataset (GSE20711) in the GEO database and it performed excellently. According to the risk model, patients with BRCA were divided into high-risk and low-risk groups. Also, the unique immune characteristics and TME between the two subgroups and 10 promising small molecule drugs targeting BRCA patients with different ICDRGs risk have been investigated. The low-risk group had good immunity indicated by T cell infiltration and high immune checkpoint expression. Moreover, the BRCA samples could be divided into three immune subtypes according to immune response severity (ISA, ISB, and ISC). ISA and ISB predominated in the low-risk group and patients in the low-risk group exhibited a more vigorous immune response. In conclusion, we developed an ICDRGs-based risk signature that can predict the prognosis of BRCA patients and offer a novel therapeutic strategy for immunotherapy, which would be of great significance in the BRCA clinical setting.

Identification of circRNA-lncRNA-miRNA-mRNA competitive endogenous RNA networks as prognostic bio-markers in head and neck squamous cell carcinoma

BACKGROUND

Head and neck squamous cell carcinoma (HNSCC) is one of the most prevalent neoplasms of malignancy. The pathogenesis of HNSCC is involved in the change of gene expression and the abnormal interaction between genes.

OBJECTIVE

The purpose of our research is to find genes that affect the survival time of patients and construct circRNA-lncRNA-miRNA-mRNA network. This paper aims to reveal the development mechanism of HNSCC and provide new ideas for clinical prognosis prediction.

METHODS

Transcriptome data were obtained from TCGA and GEO databases. A total of 556 samples were included. We screened the differentially expressed lncRNAs, circRNAs and mRNAs to predict interactions between lncRNA-miRNA, circRNA-miRNA and miRNA-mRNA. Then, we selected the hub mRNAs to predict the prognosis of patients.

RESULTS

We identified 8 hub prognostic mRNAs (FAM111A, IFIT2, CAV1, KLF9, OCIAD2, SLCO3A1, S100A16 and APOL3) by a series of bioinformatics analyses and established the prognostic ceRNA network of 8 mRNAs, 3 miRNAs, 2 circRNAs and 1 lncRNAs according to the targeting relationship by using databases.

CONCLUSION

We established the circRNA-lncRNA-miRNA-mRNA gene interaction network in HNSCC. We illuminated the molecular mechanism underlying the gene regulation associated with the pathogenesis of HNSCC and predicted the biomarkers related to prognosis.

Expression of connexins and pannexins in diseased human liver

Connexin proteins can form hexameric hemichannels and gap junctions that mediate paracrine and direct intercellular communication, respectively. Gap junction activity is crucial for the maintenance of hepatic homeostasis, while connexin hemichannels become particularly active in liver disease, such as hepatitis, fibrosis, cholestasis or even hepatocellular carcinoma. Channels consisting of connexin-like proteins named pannexins have been directly linked to liver inflammation and cell death. The goal of the present study was to characterize the expression and subcellular localization of connexins and pannexins in liver of patients suffering from various chronic and neoplastic liver diseases. Specifically, real-time quantitative reverse transcription polymerase chain reaction, immunoblotting and immunohistochemistry analyses were performed on human liver biopsies. It was found that pannexin1 and pannexin2 gene expression are correlated to a certain degree, as is pannexin1 protein expression with connexin32 and connexin43 protein expression. Furthermore, this study is the first to detect pannexin3 in human patient liver biopsies via both immunoblot and immunohistochemistry.

The emerging potentials of lncRNA DRAIC in human cancers

Long non-coding RNA (lncRNA) is a subtype of noncoding RNA that has more than 200 nucleotides. Numerous studies have confirmed that lncRNA is relevant during multiple biological processes through the regulation of various genes, thus affecting disease progression. The lncRNA DRAIC, a newly discovered lncRNA, has been found to be abnormally expressed in a variety of diseases, particularly cancer. Indeed, the dysregulation of DRAIC expression is closely related to clinicopathological features. It was also reported that DRAIC is key to biological functions such as cell proliferation, autophagy, migration, and invasion. Furthermore, DRAIC is of great clinical significance in human disease. In this review, we discuss the expression signature, clinical characteristics, biological functions, relevant mechanisms, and potential clinical applications of DRAIC in several human diseases.

A novel prognostic signature of metastasis-associated genes and personalized therapeutic strategy for lung adenocarcinoma patients

Lung adenocarcinoma (LUAD) is a highly invasive and metastatic malignant tumor with high morbidity and mortality. This study aimed to construct a prognostic signature for LUAD patients based on metastasis-associated genes (MAGs). RNA expression profiles were downloaded from the Cancer Genome Atlas (TCGA) database. RRA method was applied to identify differentially expressed MAGs. A total of 192 significantly robust MAGs were determined among seven GEO datasets. MAGs were initially selected through the Lasso Cox regression analysis and 6 MAGs were included to construct a prognostic signature model. Transcriptome profile, patient prognosis, correlation between the risk score and clinicopathological features, immune cell infiltration characteristics, immunotherapy sensitivity and chemotherapy sensitivity differed between low- and high-risk groups after grouping according to median risk score. The reliability and applicability of the signature were further validated in the GSE31210, GSE50081 and GSE68465 cohort. CMap predicted 62 small molecule drugs on the base of the prognostic MAGs. Targeted drug staurosporine had hydrogen bonding with Gln-172 of SLC2A1, which is one of MAGs. Staurosporine could inhibit cell migration in A549 and H1299. We further verified mRNA and protein expression of 6 MAGs in A549 and H1299. The signature can serve as a promising prognostic tool and may provide a novel personalized therapeutic strategy for LUAD patients.