OMCD: OncomiR Cancer Database

BreVamiR3': A comprehensive database for breast cancer-associated genetic variations in miRNA and 3' UTR of their target genes

Breast cancer (BC) is a multifactorial disease where microRNA (miRNA)-mediated dysregulated gene expression plays a pivotal role in tumorigenesis, progression, and clinical outcomes. Genetic variation, particularly SNPs in miRNA sequences and the 3' untranslated regions (3'UTRs) of their target genes, can disrupt miRNA-mRNA interactions, leading to altered gene expression. Despite several existing databases providing insights into various aspects of miRNAs and their target genes in association with the development of the disease. Still, there remains a critical gap in a unified, BC-specific repository that integrates SNPs in miRNAs, their target genes, and associated molecular mechanisms. To address this, we developed BreVamiR3' (Breast cancer-associated genetic Variations in miRNA and 3'UTR of their target genes), a novel, freely accessible database (https://brevamir3.web.app/index.html). BreVamiR3' features comprehensive and curated data on 500 miRNAs and 828 target genes associated with BC, including experimentally validated SNPs, chromosomal loci, expression profiles, BC subtypes, signaling pathways, and classifications of genes i.e. oncogene, tumor suppressor, or both. Unique features of BreVamiR3' include detailed annotations of SNPs disrupting miRNA-target interactions, subtype-specific miRNA expression, visualization of miRNA-chromosomal distributions and their experimental validation. Chromosome 19 harbours the highest number of BC-associated miRNAs, while target genes such as CCND1, KRAS, and ERBB2 demonstrate extensive miRNA regulation. By integrating genetic variations with functional and clinical relevance, BreVamiR3' provides a single platform to explore miRNA-mediated regulatory networks, their genetic variation, and downstream signaling pathways in BC. This database serves as a powerful resource for researchers, enabling exploration of miRNA-gene interactions, genetic variation, and their role in pathogenesis of BC and diverse clinical outcomes.

miRNAs in the diagnosis and therapy of cardiac and mediastinal tumors: a new dawn for cardio-oncology?

Dysfunctions in miRNA production have been recently investigated as predictors of neoplasms and their therapeutic strategies. In this review, we summarize the available knowledge on miRNAs and cardiac tumors (such as myxoma) and mediastinal tumors (such as thymoma) and propose new avenues for future research. MiRNAs are crucial for cardiac development through the expression of cardiac transcription factors (miR-335-5p), hinder the cell cycle by modulating the activity of transcription factors (miR-126-3p, miR-320a), modulate the production of inflammatory factors such as interleukins (miR-217), and interfere with cell proliferation or apoptosis (miR-218, miR-634 and miR-122). Current and future research on miRNAs is essential, as a deep understanding could lead to a revolution in the field of diagnostics and prevention of neoplastic diseases.

Cancer pharmacoinformatics: Databases and analytical tools

Cancer is a subject of extensive investigation, and the utilization of omics technology has resulted in the generation of substantial volumes of big data in cancer research. Numerous databases are being developed to manage and organize this data effectively. These databases encompass various domains such as genomics, transcriptomics, proteomics, metabolomics, immunology, and drug discovery. The application of computational tools into various core components of pharmaceutical sciences constitutes "Pharmacoinformatics", an emerging paradigm in rational drug discovery. The three major features of pharmacoinformatics include (i) Structure modelling of putative drugs and targets, (ii) Compilation of databases and analysis using statistical approaches, and (iii) Employing artificial intelligence/machine learning algorithms for the discovery of novel therapeutic molecules. The development, updating, and analysis of databases using statistical approaches play a pivotal role in pharmacoinformatics. Multiple software tools are associated with oncoinformatics research. This review catalogs the databases and computational tools related to cancer drug discovery and highlights their potential implications in the pharmacoinformatics of cancer.

Decoding the Non-coding: Tools and Databases Unveiling the Hidden World of "Junk" RNAs for Innovative Therapeutic Exploration

Non-coding RNAs are pivotal regulators of gene and protein expression, exerting crucial influences on diverse biological processes. Their dysregulation is frequently implicated in the onset and progression of diseases, notably cancer. A profound comprehension of the intricate mechanisms governing ncRNAs is imperative for devising innovative therapeutic interventions against these debilitating conditions. Significantly, nearly 80% of our genome comprises ncRNAs, underscoring their centrality in cellular processes. The elucidation of ncRNA functions is pivotal for grasping the complexities of gene regulation and its implications for human health. Modern genome sequencing techniques yield vast datasets, stored in specialized databases. To harness this wealth of information and to understand the crosstalk of non-coding RNAs, knowledge of available databases is required, and many new sophisticated computational tools have emerged. These tools play a pivotal role in the identification, prediction, and annotation of ncRNAs, thereby facilitating their experimental validation. This Review succinctly outlines the current understanding of ncRNAs, emphasizing their involvement in disease development. It also highlights the databases and tools instrumental in classifying, annotating, and evaluating ncRNAs. By extracting meaningful biological insights from seemingly "junk" data, these tools empower scientists to unravel the intricate roles of ncRNAs in shaping human health.

The RNA world: from experimental laboratory to "in silico" approach. Part 1: User friendly RNA expression databases portals

Cellular information about "life instruction" is stored, transferred, and modified using different types of RNA molecules. During the last decades, a growing number of RNA data has been generated thanks to the development of microarray chips and next-generation sequencing (NGS) methods. Improvement of bioinformatics contributed to the discovery of many types of new non-coding RNAs (ncRNAs), mostly with regulatory functions that supplemented the knowledge about the world of RNA. All of it, as well as the Human Genome Project (HGP) and the Cancer Genome Atlas (TCGA) project, has resulted in the formation of data storage and analysis portals which are widely used in cancer research and moved science from in vitro to in silico research. In this review we presented and discussed the data storage and analysis portals used by us, such as cBioPortal, UALCAN, ENCORI, and others. During the revision of these sites, we paid attention to data integration, simplicity of analysis, and results visualization, which are important for users without bioinformatic or statistical skills. In our opinion, the RNA analysis online tools will rapidly develop during the next decade and it seems to be a way for personalization of cancer treatment.

Comprehensive analysis of differentially expressed miRNAs in hepatocellular carcinoma: Prognostic, predictive significance and pathway insights

Robust prognostic and predictive factors for hepatocellular carcinoma, a leading cause of cancer-related deaths worldwide, have not yet been identified. Previous studies have identified potential HCC determinants such as genetic mutations, epigenetic alterations, and pathway dysregulation. However, the clinical significance of these molecular alterations remains elusive. MicroRNAs are major regulators of protein expression. MiRNA functions are frequently altered in cancer. In this study, we aimed to explore the prognostic value of differentially expressed miRNAs in HCC, to elucidate their associated pathways and their impact on treatment response. To this aim, bioinformatics techniques and clinical dataset analyses were employed to identify differentially expressed miRNAs in HCC compared to normal hepatic tissue. We validated known associations and identified a novel miRNA signature with potential prognostic significance. Our comprehensive analysis identified new miRNA-targeted pathways and showed that some of these protein coding genes predict HCC patients' response to the tyrosine kinase inhibitor sorafenib.

Systematic Analysis to Identify the MIR99AHG-has-miR-21-5p-EHD1 CeRNA Regulatory Network as Potential Biomarkers in Lung Cancer

Lung cancer (LC) remains an extremely lethal disease worldwide, and effective prognostic biomarkers are at top priority. With the rapid development of high-throughput sequencing and bioinformatic analysis methods, the quest to characterize cancer transcriptomes continues to move forward. However, the integrated systematic analysis of lncRNA-miRNA-mRNA regulatory network in LC is lacking. In this study, we collected samples of cancer tissues and adjacent normal tissues from patients with lung cancer and conducted transcriptome and small RNA sequencing to identify differentially expressed genes (DEGs), miRNAs (DEMs), and lncRNAs (DELs). The regulatory roles of miRNAs in LC were explained by functional analysis on DEM-targeted genes. The lncRNA-miRNA pairs, miRNA-mRNA pairs, and lncRNA-mRNA pairs were identified and combined to construct the interplay of lncRNA-miRNA-mRNA. We evaluated the prognostic value of selected lncRNA-miRNA-mRNA by Kaplan-Meier analysis. Finally, we analyzed the expression levels of selected DEM, DELs, and DEGs in lung cancer patients and healthy people to verify our findings. A total of 1492 DEGs, 12 DEMs, and 604 DELs were identified in LC patients. Based on the bioinformatic analysis and the regulatory mechanism of ceRNAs, 3 lncRNAs (GATA2-AS1, LINC00632, MIR99AHG), 1 miRNA (hsa-miR-21-5p) and 5 targeted genes (RECK, TIMP3, EHD1, RASGRP1 and ERG) were figured out first. Through further Kaplan-Meier analysis screening the prognostic value, we finally found the hub subnetwork (MIR99AHG-hsa-miR-21-5p-EHD1) by collating lncRNA-miRNA pairs, miRNA-mRNA pairs and lncRNA-mRNA pairs. As the key of ceRNA regulatory network, the expression of miRNA-21-5p in lung cancer patients was significantly higher than that in healthy people (P < 0.01), and its high expression was significantly associated with poor prognosis (P = 0.0025). Our study successfully constructed a MIR99AHG-hsa-miR-21-5p-EHD1 mutually regulatory network, suggesting the potential efficient biomarkers in LC.

ExplORRNet: An interactive web tool to explore stage-wise miRNA expression profiles and their interactions with mRNA and lncRNA in human breast and gynecological cancers

Background

MicroRNAs (miRNAs) are key regulators of gene expression that have been implicated in gynecological and breast cancers. Understanding the cancer stage-wise expression patterns of miRNAs and their interactions with other RNA molecules in cancer is crucial to improve cancer diagnosis and treatment planning. Comprehensive web tools that integrate data on the transcriptome, circulating miRNAs, and their validated targets to derive beneficial conclusions in cancer research are lacking.

Methods

Using the Shiny R package, we developed a web tool called ExplORRNet that integrates transcriptomic profiles from The Cancer Genome Atlas and miRNA expression data derived from various sources, including tissues, cell lines, exosomes, serum, and plasma, available in the Gene Expression Omnibus database. Differential expression analyses between normal and tumor tissue samples as well as different stages of cancer, accompanied by gene enrichment and survival analyses, can be performed using specialized R packages. Additionally, a miRNA-messenger RNA (mRNA)-long non-coding RNA (lncRNA) networks are constructed to identify regulatory modules.

Results

Our tool identifies cancer stage-wise differentially regulated miRNAs, mRNAs, and lncRNAs in gynecological and breast cancers. Survival analysis identifies miRNAs associated with patient survival, and functional enrichment analysis provides insights into dysregulated miRNA-related biological processes and pathways. The miRNA-mRNA-lncRNA networks highlight interconnected regulatory molecular modules driving cancer progression. Case studies demonstrate the utility of the ExplORRNet for studying gynecological and breast cancers.

Conclusion

ExplORRNet is an intuitive and user-friendly web tool that provides a deeper understanding of dysregulated miRNAs and their functional implications in gynecological and breast cancers. We hope our ExplORRNet tool has potential utility among the clinical and basic researchers and will be beneficial to the entire cancer genomics community to encourage and facilitate mining the rapidly growing public databases to progress the field of precision oncology. The ExplORRNet is available at https://mirna.cs.ut.ee.

Current updates in sarcoma biomarker discovery: emphasis on next-generation sequencing-based methods

Soft tissue sarcomas comprise a heterogeneous group of neoplasms. Although soft tissue malignancies make up only 2% of adult cancers, classification based on histomorphology presents a diagnostic challenge. Characterisation of soft tissue sarcomas by molecular analysis is rapidly evolving to improve diagnostic accuracy and develop targeted therapies. This review highlights the advances in molecular techniques, including current next-generation sequencing-based assays (fusion detection by RNA sequencing, targeted/whole exome sequencing, microRNA profiling), as well as emerging methods (liquid biopsies, DNA methylation profiling, single-cell molecular profiling and next-generation immunohistochemistry) for future clinical applications.

CMC: Cancer miRNA Census - a list of cancer-related miRNA genes

A growing body of evidence indicates an important role of miRNAs in cancer; however, there is no definitive, convenient-to-use list of cancer-related miRNAs or miRNA genes that may serve as a reference for analyses of miRNAs in cancer. To this end, we created a list of 165 cancer-related miRNA genes called the Cancer miRNA Census (CMC). The list is based on a score, built on various types of functional and genetic evidence for the role of particular miRNAs in cancer, e.g. miRNA-cancer associations reported in databases, associations of miRNAs with cancer hallmarks, or signals of positive selection of genetic alterations in cancer. The presence of well-recognized cancer-related miRNA genes, such as MIR21, MIR155, MIR15A, MIR17 or MIRLET7s, at the top of the CMC ranking directly confirms the accuracy and robustness of the list. Additionally, to verify and indicate the reliability of CMC, we performed a validation of criteria used to build CMC, comparison of CMC with various cancer data (publications and databases), and enrichment analyses of biological pathways and processes such as Gene Ontology or DisGeNET. All validation steps showed a strong association of CMC with cancer/cancer-related processes confirming its usefulness as a reference list of miRNA genes associated with cancer.

MiR-150 and miR-155 expression predicts survival of cervical cancer patients: a translational approach to novel prognostic biomarkers

INTRODUCTION

High-risk human papillomavirus (HPV) is the aetiological agent of cervical cancer, which remains the fourth leading cause of cancer death in women worldwide. K14-HPV16 transgenic mice are a model for HPV-induced cancers, which undergo multistep squamous carcinogenesis at the skin, that is histologically and molecularly similar to carcinogenesis of the human cervix. Previous screens of differentially regulated microRNAs (miRs) using K14-HPV16 mice showed a role for miR-21, miR-155, miR-150, miR-146a, miR-125b and miR-223 during carcinogenesis.

METHODS

We now aim to translate these observations into the clinical setting, using data provided by The Cancer Genome Atlas (TCGA) to explore whether those microRNAs can influence the survival of cervical cancer patients.

RESULTS

Results showed that low miR-150, miR-155 and miR-146a expression levels in primary tumours were associated with poor overall survival. However, only miR-150 and miR-155 were found to be independent predictors, increasing the risk of death. When patients were stratified by clinical stage, low miR-150, miR-155, miR-146a and miR-125b were associated with poor survival for clinical stages I and II. Only low miR-150 expression increased the death risk.

CONCLUSION

We conclude that miR-150 and miR-155 may be potentially applied as prognostic biomarkers in cervical cancer patients. However, further investigation is required to determine their applicability.

Hepatitis B Virus Modulated Transcriptional Regulatory Map of Hepatic Cellular MicroRNAs

Hepatitis B virus (HBV) is an enveloped, hepatotropic, noncytopathic virus with a partially double-stranded DNA genome. It infects hepatocytes and is associated with progression to liver fibrosis and cirrhosis, culminating in hepatocellular carcinoma (HCC), accounting for 55% of total HCC cases. MicroRNAs (miRNAs) regulated by HBV play an important role in these pathologies. Mapping the miRNAs responsive to HBV and HBV-specific proteins, including HBV X protein (HBx) that harbor the majority of HBV-human protein interactions, could aid accelerate the diagnostics and therapeutics innovation against the infection and associated diseases. With this in mind, we used a unique annotation strategy whereby we first amassed 362 mature HBV responsive-human Differentially Expressed miRNAs (HBV-hDEmiRs). The core experimentally-validated messenger RNA targets of the HBV-hDEmiRs were mostly associated with viral infections and hepatic inflammation processes. Moreover, our annotation strategy enabled the characterization of HBx-dependent/independent HBV-hDEmiRs as a tool for evaluation of the impact of HBx as a therapeutic target. Bioinformatics analysis of the HBV-human protein-protein interactome revealed new insights into the transcriptional regulatory network of the HBV-hDEmiRs. We performed a comparative analysis of data on miRNAs gathered from HBV infected cell line studies and from tissue studies of fibrosis, cirrhosis, and HCC. Accordingly, we propose hsa-miR-15a-5p that is downregulated by multiple HBV proteins, including HBx, as a potential biomarker of HBV infection, and its progression to HCC. In all, this study underscores (1) the complexity of miRNA regulation in response to HBV infection and its progression into other liver pathologies and (2) provides a regulatory map of HBV-hDEmiRs and the underlying mechanisms modulating their expression through a cross talk between HBV viral proteins and human transcription factors.

Integrative Analysis of the Role of TP53 in Human Pan-Cancer

Tumor protein P53 (TP53) is an important tumor suppressor gene in humans. Under normal circumstances, TP53 can help repair mutated genes, or promote the death of cells with severe gene mutations (specifically, TP53 prevents cells from arrest in the G1/S phase when deoxyribonucleic acid (DNA) is damaged and promotes apoptosis if not repaired), and prevents normal cells from becoming malignant cells. TP53 mutations affect its tumor suppressor function, leading to the development of malignant tumors. In this study, using a public database, we explored the pan-cancer expression of TP53, its impact on patient survival and prognosis, the types of gene mutations, its correlation with immunity, and its regulation of other transcription factors and micro RNA (miRNA). The docking sites of therapeutic drugs and key amino acid sites of action provide a basis for future targeted therapies. TP53 has important biological functions in the human body. This study provides a theoretical basis for clinical TP53 gene therapy.

Machine-Learning-Based Single-Molecule Quantification of Circulating MicroRNA Mixtures

MicroRNAs (miRs) are small noncoding RNAs that regulate gene expression and are emerging as powerful indicators of diseases. MiRs are secreted in blood plasma and thus may report on systemic aberrations at an early stage via liquid biopsy analysis. We present a method for multiplexed single-molecule detection and quantification of a selected panel of miRs. The proposed assay does not depend on sequencing, requires less than 1 mL of blood, and provides fast results by direct analysis of native, unamplified miRs. This is enabled by a novel combination of compact spectral imaging and a machine learning-based detection scheme that allows simultaneous multiplexed classification of multiple miR targets per sample. The proposed end-to-end pipeline is extremely time efficient and cost-effective. We benchmark our method with synthetic mixtures of three target miRs, showcasing the ability to quantify and distinguish subtle ratio changes between miR targets.

OncoUroMiR: Circulating miRNAs for Detection and Discrimination of the Main Urological Cancers Using a ddPCR-Based Approach

The three most common genitourinary malignancies (prostate/kidney/bladder cancers) constitute a substantial proportion of all cancer cases, mainly in the elderly population. Early detection is key to maximizing the patients' survival, but the lack of highly accurate biomarkers that might be used through non-/minimally invasive methods has impaired progress in this domain. Herein, we sought to develop a minimally invasive test to detect and discriminate among those urological cancers based on miRNAs assessment through ddPCR. Plasma samples from 268 patients with renal cell (RCC; n = 119), bladder (BlCa; n = 73), and prostate (PCa; n = 76) carcinomas (UroCancer group), and 74 healthy donors were selected. Hsa-miR-126-3p, hsa-miR-141-3p, hsa-miR-153-5p, hsa-miR-155-5p, hsa-miR-182-5p, hsa-miR-205-5p, and hsa-miR-375-3p levels were assessed. UroCancer cases displayed significantly different circulating hsa-miR-182-5p/hsa-miR-375-3p levels compared to healthy donors. Importantly, the hsa-miR-155-5p/hsa-miR-375-3p panel detected RCC with a high specificity (80.54%) and accuracy (66.04%). Furthermore, the hsa-miR-126-3p/hsa-miR-375-3p panel identified BlCa with a 94.87% specificity and 76.45% NPV whereas higher hsa-miR-126-3p levels were found in PCa patients. We concluded that plasma-derived miRNAs can identify and discriminate among the main genitourinary cancers, with high analytical performance. Although validation in a larger cohort is mandatory, these findings demonstrate that circulating miRNA assessment by ddPCR might provide a new approach for early detection and risk stratification of the most common urological cancers.

An Updated Overview of Existing Cancer Databases and Identified Needs

Our search of existing cancer databases aimed to assess the current landscape and identify key needs. We analyzed 71 databases, focusing on genomics, proteomics, lipidomics, and glycomics. We found a lack of cancer-related lipidomic and glycomic databases, indicating a need for further development in these areas. Proteomic databases dedicated to cancer research were also limited. To assess overall progress, we included human non-cancer databases in proteomics, lipidomics, and glycomics for comparison. This provided insights into advancements in these fields over the past eight years. We also analyzed other types of cancer databases, such as clinical trial databases and web servers. Evaluating user-friendliness, we used the FAIRness principle to assess findability, accessibility, interoperability, and reusability. This ensured databases were easily accessible and usable. Our search summary highlights significant growth in cancer databases while identifying gaps and needs. These insights are valuable for researchers, clinicians, and database developers, guiding efforts to enhance accessibility, integration, and usability. Addressing these needs will support advancements in cancer research and benefit the wider cancer community.

SOX9 is a target of miR-134-3p and miR-224-3p in breast cancer cell lines

The transcription factor SOX9 represents an important mediator of breast cancer progression. miRNAs are small non-coding RNAs inhibiting translation of target genes upon interaction with the 3'-UTR region of respective mRNA molecules. Deregulated miRNA expression is involved in hallmarks of cancer like sustained proliferation and inhibition of apoptosis. Here, we investigated the miRNA-mediated regulation of SOX9 expression in two breast cancer cell lines, thereby providing further insights into cellular mechanisms driving breast cancer progression. The modulating effects of miR-134-3p, miR-224-3p, and miR-6859-3p on SOX9 expression were analyzed by qPCR and Western blot in human MDA-MB-231 breast cancer cells. Direct binding of the above-mentioned miRNAs to the SOX9 3'-UTR was assessed by luciferase reporter assays and site-directed mutagenesis. Expression levels of the investigated miRNAs in tumor samples versus healthy tissues were analyzed in silico using publicly available databases. Transfection of miR-134-3p, miR-224-3p, or miR-6859-3p reduced SOX9 expression on mRNA and protein level. Reporter assays proved direct binding of miR-134-3p and miR-224-3p to the SOX9 3'-UTR in MDA-MB-231 and MCF-7 cells. Expression analysis performed in silico revealed reduced expression of both miRNAs in breast cancer tissues. We describe three novel miRNAs targeting SOX9 in human breast cancer cell lines. Among them miR-134-2p and miR-224-3p might act as tumor suppressors, whose down-regulation induces elevated SOX9 levels thereby promoting breast cancer progression.

MicroRNAs in Cancer and Cardiovascular Disease

Although cardiac tumor formation is rare, accumulating evidence suggests that the two leading causes of deaths, cancers, and cardiovascular diseases are similar in terms of pathogenesis, including angiogenesis, immune responses, and fibrosis. These similarities have led to the creation of new exciting field of study called cardio-oncology. Here, we review the similarities between cancer and cardiovascular disease from the perspective of microRNAs (miRNAs). As miRNAs are well-known regulators of translation by binding to the 3'-untranslated regions (UTRs) of messenger RNAs (mRNAs), we carefully dissect how a specific set of miRNAs are both oncomiRs (miRNAs in cancer) and myomiRs (muscle-related miRNAs). Furthermore, from the standpoint of similar pathogenesis, miRNAs categories related to the similar pathogenesis are discussed; namely, angiomiRs, Immune-miRs, and fibromiRs.

Decreased expression of miR-23b is associated with poor survival of endometrial cancer patients

Endometrial cancer (EC) is one of the most common types of cancer of the female reproductive system. EC is classified into two types (EC1 and EC2). MiRNAs are single-stranded RNA molecules that regulate gene expression posttranscriptionally. They have aberrant expression profiles in cancer, including EC. This study aimed to assess the level of expression of a panel of 16 miRNAs in both types of EC and healthy endometrium (HE). A total of 45 patients were enrolled into the study, 18 patients diagnosed with EC1, 12 diagnosed with EC2, and 15 HE controls. Tumor tissues or healthy endometrial tissues were dissected from archival formalin-fixed paraffin-embedded (FFPE) using laser capture microdissection (LCM). RNA was isolated from collected material and the expression of selected miRNAs was determined using the real-time qPCR. We found that miR-23b, miR-125b-5p, miR-199a-3p, miR-221-3p, and miR-451a were downregulated in EC in comparison to HE. Moreover, the expression of miR-34a-5p and miR-146-5p was higher in EC1 compared to EC2. Analysis of The Cancer Genome Atlas (TCGA) database confirmed decreased levels of miR-23b, miR-125b-5p, and miR-199a-3p in EC. Decreased miR-23b expression was associated with worse survival of EC patients.

The Role of MicroRNAs in HER2-Positive Breast Cancer: Where We Are and Future Prospective

Simple Summary

Breast cancer is the most diagnosed malignancy in woman worldwide and, despite the availability of new innovative therapies, it remains the first cause of death for tumor in woman. 20% of all breast cancer cases are HER2 positive, meaning that they are characterized by an aberrant expression of the growth factor receptor HER2. This receptor is involved in survival and proliferation mechanisms, conferring to this breast cancer subtype a particular aggressiveness. The introduction of anti-HER2 agents, such as trastuzumab, in the clinical practice, significantly improved the prognosis. However, a great portion of patients is not responsive to this therapy. Thus, cancer research is working to provide new tools to better manage HER2 positive breast cancers, such as biomarkers and therapeutic approaches. MicroRNAs could be used for these purposes. They are small molecules involved in almost all biological processes, including cancer promoting pathways. Researchers consider microRNAs as promising clinical tools because they are easily detectable and stable in both tissues and blood samples, and an increasing body of evidence supports their potential use as targets of therapy, prognostic and predictive biomarkers, or therapeutic agents. This review sums up the most recent scientific publications about microRNAs in HER2 positive breast cancer.

Abstract

Breast cancer that highly expresses human epidermal growth factor receptor 2 (HER2+) represents one of the major breast cancer subtypes, and was associated with a poor prognosis until the introduction of HER2-targeted therapies such as trastuzumab. Unfortunately, up to 30% of patients with HER2+ localized breast cancer continue to relapse, despite treatment. MicroRNAs (miRNAs) are small (approximately 20 nucleotides long) non-coding regulatory oligonucleotides. They function as post-transcriptional regulators of gene expression, binding complementarily to a target mRNA and leading to the arrest of translation or mRNA degradation. In the last two decades, translational research has focused on these small molecules because of their highly differentiated expression patterns in blood and tumor tissue, as well as their potential biological function. In cancer research, they have become pivotal for the thorough understanding of oncogenic biological processes. They might also provide an efficient approach to early monitoring of tumor progression or response to therapy. Indeed, changes in their expression patterns can represent a flag for deeper biological changes. In this review, we sum up the recent literature regarding miRNAs in HER2+ breast cancer, taking into account their potential as powerful prognostic and predictive biomarkers, as well as therapeutic tools.

miR2Trait: an integrated resource for investigating miRNA-disease associations

MicroRNAs are key components of cellular regulatory networks, and breakdown in miRNA function causes cascading effects leading to pathophenotypes. A better understanding of the role of miRNAs in diseases is essential for human health. Here, we have devised a method for comprehensively mapping the associations between miRNAs and diseases by merging on a common key between two curated omics databases. The resulting bidirectional resource, miR2Trait, is more detailed than earlier catalogs, uncovers new relationships, and includes analytical utilities to interrogate and extract knowledge from these datasets. miR2Trait provides resources to compute the disease enrichment of a user-given set of miRNAs and analyze the miRNA profile of a specified diseasome. Reproducible examples demonstrating use-cases for each of these resource components are illustrated. Furthermore we used these tools to construct pairwise miRNA-miRNA and disease-disease enrichment networks, and identified 23 central miRNAs that could underlie major regulatory functions in the human genome. miR2Trait is available as an open-source command-line interface in Python3 (URL: https://github.com/miR2Trait) with a companion wiki documenting the scripts and data resources developed, under MIT license for commercial and non-commercial use. A minimal web-based implementation has been made available at https://sas.sastra.edu/pymir18. Supplementary information is available at: https://doi.org/10.6084/m9.figshare.8288825.v3.

Innovative targets of the lncRNA-miR-mRNA network in response to low-dose aspirin in breast cancer patients

This study aimed to investigate innovative targets in breast cancer patients by considering the interaction of the lncRNA-miR-mRNA network in response to low-dose aspirin. The candidate miRs were first taken from the GEO and TCGA databases. Then, the candidate network was constructed using the high-throughput sequencing data. The expression levels of candidate targets were finally measured using Real-Time PCR in luminal A breast cancer patients undergoing aspirin (80 mg daily for three months) and non-aspirin groups during chemotherapy after surgery. The expression levels of TGFβ, IL-17, IFNγ, and IL-β proteins were measured using the ELISA technique. 5 lncRNAs, 12 miRs, and 10 genes were obtained in the bioinformatic phase. A significant expression increase of the candidate tumor suppressor lncRNAs, miRs, and genes and a substantial expression decrease of the candidate onco-lncRNAs, oncomiRs, and oncogenes were achieved after the aspirin consumption. Unlike the non-aspirin group, the expression levels of TGFβ, IL-17, IFNγ, and IL-β proteins were significantly decreased following aspirin consumption. The Kaplan-Meier analysis indicated a longer overall survival rate in the patients after aspirin consumption. Our results showed that the lncRNA-miR-mRNA network might be a significant target for aspirin; their expression changes may be a new strategy with potential efficacy for cancer therapy or prevention.

Novel targets in rectal cancer by considering lncRNA-miRNA-mRNA network in response to Lactobacillus acidophilus consumption: a randomized clinical trial

We aimed to explore the lncRNA-miR-mRNA network in response to Lactobacillus acidophilus (L. acidophilus) consumption in rectal cancer patients. The candidate miRs were first taken from the GEO and TCGA databases. We constructed the lncRNA-miR-mRNA network using the high-throughput sequencing data. At last, we created a heatmap based on the experimental data to show the possible correlation of the selected targets. The expression levels of selected targets were measured in the samples of 107 rectal cancer patients undergoing placebo and probiotic consumption and 10 noncancerous subjects using Real-Time PCR. Our analysis revealed a group of differentially expressed 12 miRs and 11 lncRNAs, and 12 genes in rectal cancer patients. A significant expression increase of the selected tumor suppressor miRs, lncRNAs, and genes and a substantial expression decrease of the selected oncomiRs, onco-lncRNAs, and oncogenes were obtained after the probiotic consumption compared to the placebo group. There is a strong correlation between some network components, including miR-133b and IGF1 gene, miR-548ac and MSH2 gene, and miR-21 and SMAD4 gene. In rectal cancer patients, L. acidophilus consumption was associated with improved expression of the lncRNA-miR-mRNA network, which may provide novel monitoring and therapeutic approaches.

Multi-Omic Data Improve Prediction of Personalized Tumor Suppressors and Oncogenes

The progression of tumorigenesis starts with a few mutational and structural driver events in the cell. Various cohort-based computational tools exist to identify driver genes but require multiple samples to identify less frequently mutated driver genes. Many studies use different methods to identify driver mutations/genes from mutations that have no impact on tumor progression; however, a small fraction of patients show no mutational events in any known driver genes. Current unsupervised methods map somatic and expression data onto a network to identify personalized driver genes based on changes in expression. Our method is the first machine learning model to classify genes as tumor suppressor gene (TSG), oncogene (OG), or neutral, thus assigning the functional impact of the gene in the patient. In this study, we develop a multi-omic approach, PIVOT (Personalized Identification of driVer OGs and TSGs), to train on experimentally or computationally validated mutational and structural driver events. Given the lack of any gold standards for the identification of personalized driver genes, we label the data using four strategies and, based on classification metrics, show gene-based labeling strategies perform best. We build different models using SNV, RNA, and multi-omic features to be used based on the data available. Our models trained on multi-omic data improved predictions compared with mutation and expression data, achieving an accuracy ≥0.99 for BRCA, LUAD, and COAD datasets. We show network and expression-based features contribute the most to PIVOT. Our predictions on BRCA, COAD, and LUAD cancer types reveal commonly altered genes such as TP53 and PIK3CA, which are predicted drivers for multiple cancer types. Along with known driver genes, our models also identify new driver genes such as PRKCA, SOX9, and PSMD4. Our multi-omic model labels both CNV and mutations with a more considerable contribution by CNV alterations. While predicting labels for genes mutated in multiple samples, we also label rare driver events occurring in as few as one sample. We also identify genes with dual roles within the same cancer type. Overall, PIVOT labels personalized driver genes as TSGs and OGs and also identified rare driver genes.

An innovative systematic approach introduced the involved lncRNA-miR-mRNA network in cell cycle and proliferation after conventional treatments in breast cancer patients

INTRODUCTION

The present study aimed to explore the involved lncRNA-miRNA-mRNA network in the cell cycle and proliferation after conventional treatments in Luminal A breast cancer patients.

METHODS

The candidate miRNAs (miRs), lncRNAs, and mRNAs were first taken from the Gene Expression Omnibus and TCGA databases. The lncRNA-miR-mRNA network was then constructed using the high-throughput sequencing data. The expression levels of selected targets were measured in the breast cancer and healthy samples by the Real-Time PCR technique and compared with the clinical outcomes by the Kaplan-Meier method.

RESULTS

Our analysis revealed a group of differentially expressed 3 lncRNAs, 9 miRs, and 14 mRNAs in breast cancer patients. A significant expression decrease of the selected tumor suppressor lncRNAs, miRs, and genes and a substantial expression increase of the selected onco-lncRNAs, oncomiRs, and oncogenes were obtained in the patients compared to the healthy group. The plasma levels of the lncRNAs, miRs, and mRNAs were more significant after the operation, chemotherapy, and radiotherapy than the pre-treatment. The Kaplan-Meier analysis indicated that the patients with a high expression of miR-21, miR-20b, IGF1R, and E2F2 and a low expression of miR-125a, PDCD4, and PTEN had exhibited a shorter overall survival rate.

CONCLUSION

Our results suggested that the underlying mechanisms of the lncRNA, miRs, and mRNAs and relevant signaling pathways may be considered predictive and therapeutic targets for breast cancer.

Prostanoid Signaling in Cancers: Expression and Regulation Patterns of Enzymes and Receptors

Cancer-associated disturbance of prostanoid signaling provides an aberrant accumulation of prostanoids. This signaling consists of 19 target genes, encoding metabolic enzymes and G-protein-coupled receptors, and prostanoids (prostacyclin, thromboxane, and prostaglandins E2, F2α, D2, H2). The study addresses the systems biology analysis of target genes in 24 solid tumors using a data mining pipeline. We analyzed differential expression patterns of genes and proteins, promoter methylation status as well as tissue-specific master regulators and microRNAs. Tumor types were clustered into several groups according to gene expression patterns. Target genes were characterized as low mutated in tumors, with the exception of melanoma. We found at least six ubiquitin ligases and eight protein kinases that post-translationally modified the most connected proteins PTGES3 and PTGIS. Models of regulation of PTGIS and PTGIR gene expression in lung and uterine cancers were suggested. For the first time, we found associations between the patient’s overall survival rates with nine multigene transcriptomics signatures in eight tumors. Expression patterns of each of the six target genes have predictive value with respect to cytostatic therapy response. One of the consequences of the study is an assumption of prostanoid-dependent (or independent) tumor phenotypes. Thus, pharmacologic targeting the prostanoid signaling could be a probable additional anticancer strategy.

Investigation and confirmation of differentially expressed miRNAs, as well as target gene prediction in papillary thyroid cancer, with a special emphasis on the autophagy signaling pathway

Papillary thyroid carcinoma (PTC) is the most common endocrine cancer. However, the role of biomechanics in the development and progression of PTC is obscure. The microarray dataset GSE104005 was examined to identify important microRNAs (miRNAs or miRs) and their probable roles in the carcinogenesis of PTC. The gene expression omnibus (GEO) database was used to obtain the data. R was used to access the differentially expressed miRNAs (DEMs) and genes (DEGs). The multiMiR software was used to predict DEM targets. To validate the top DEMs and DEGs, thirty tissue samples were obtained from PTC patients who had their thyroids removed and compared with 30 normal samples. The total RNA content of the tumor and corresponding non-tumoral adjacent samples were purified and converted to cDNA. Expression levels of top dysregulated miRNAs and their target and predicted DEG were evaluated using the RT-qPCR method. miR-182 and miR-183 were top upregulated miRs and miR-30d was the most downregulated miR among DEMs. Furthermore, FOXO1 which was shown to be targeted by aforementioned miRNAs, was the most downregulated genes among other DEGs. 10 hub nodes were detected by PPI construction. PTEN was the hub node with highest score. The in vitro gene expression analysis was also showed the same expression pattern in tissues. Significant increase in miR-182-5p and miR-183-5p expressions, as well as a significant decrease in FOXO1 and miR-30d-5p expressions, suggest that PTC cells may tend to preserve their autophagy capability.

Multi-Omics Reveal the Immunological Role and the Theragnostic Value of miR-216a/GDF15 Axis in Human Colon Adenocarcinoma

Colon adenocarcinoma (COAD) is the most common type of gastrointestinal cancer and is still the third leading cause of cancer-related mortality worldwide. Accurate screening tools for early diagnosis and prediction of prognosis and precision treatment strategies are urgently required to accommodate the unmet medical needs of COAD management. We herein aimed to explore the significance of the microRNA (miR)-216a/growth differentiation factor 15 (GDF15) axis in terms of clinical value, tumor immunity, and potential mechanisms in COAD by using multi-omic analysis. The gene expression levels of miR-216a and GDF15 showed an increase in the COAD group compared to those of the normal group. The expression of miR-216a presented a negative correlation with GDF15 in COAD tumor tissue. The use of an in vitro luciferase reporter assay and bioinformatic prediction revealed that miR-216a-3p acted toward translational inhibition on GDF15 by targeting its 3′untranslated region (UTR) site. High miR-216a expression was associated with decreased overall survival (OS), while the high expression of GDF15 was associated with increased OS. Enriched type 1 T-helper (Th1), enriched regulatory T (Treg), enriched eosinophils, and decreased nature killer T-cells (NKTs) in COAD tumor tissue may play counteracting factors on the tumor-regulatory effects of miR-216a and GDF15. In addition, high GDF15 expression had associations with suppressed immunoinhibitory genes and negative correlations with the infiltration of macrophages and endothelial cells. The enrichment analysis revealed that GDF15 and its co-expression network may be implicated in mitochondrial organization, apoptosis signaling, and endoplasmic reticulum (ER) stress response. The Genomics of Drug Sensitivity in Cancer (GDSC) and Cancer Therapeutics Response Portal (CTRP) analysis identified that Gemcitabine acted as a precision treatment for COAD when GDF15 expression was low. This study supports the miR-216a/GDF15 axis as a diagnostic/prognostic panel for COAD, identifies Th1, Treg, eosinophils, and NKTs as counteracting factors, indicates potential relationships underlying immunomodulation, mitochondrial organization, apoptotic signaling, and ER stress and unveil Gemcitabine as a potential drug for the development of treatment strategy when combined with targeting GDF15.

A construction and comprehensive analysis of ceRNA networks and infiltrating immune cells in papillary renal cell carcinoma

Background

As the second most common malignancy in adults, papillary renal cell carcinoma (PRCC) has shown an increasing trend in both incidence and mortality. Effective treatment for advanced metastatic PRCC is still lacking. In this study, we aimed to establish competitive endogenous RNA (ceRNA) networks related to PRCC tumorigenesis, and analyze the specific role of differentially expressed ceRNA components and infiltrating immune cells in tumorigenesis.

Methods

CeRNA networks were established to identify the key ceRNAs related to PRCC tumorigenesis based on the 318 samples from The Cancer Genome Atlas database (TCGA), including 285 PRCC and 33 normal control samples. The R package, “CIBERSORT,” was used to evaluate the infiltration of 22 types of immune cells. Then we identified the significant ceRNAs and immune cells, based on which two nomograms were obtained for predicting the prognosis in PRCC patients. Finally, we investigated the co‐expression of PRCC‐specific immune cells and core ceRNAs via Pearson correlation test.

Results

COL1A1, H19, ITPKB, LDLR, TCF4, and WNK3 were identified as hub genes in ceRNA networks. Four prognostic‐related tumor‐infiltrating immune cells, including T cells CD4 memory resting, Macrophages M1, and Macrophages M2 were revealed. Pearson correlation test indicated that Macrophage M1 was negatively related with COL1A1 (p < 0.01) and LDLR (p < 0.01), while Macrophage M2 was positively related with COL1A1 (p < 0.01), TCF4 (p < 0.01), and H19 (p = 0.032). Two nomograms were conducted with favorable accuracies (area under curve of 1‐year survival: 0.935 and 0.877; 3‐year survival: 0.849 and 0.841; and 5‐year survival: 0.818 and 0.775, respectively).

Conclusion

The study constructed two nomograms suited for PRCC prognosis predicting. Moreover, we concluded that H19‐miR‐29c‐3p‐COL1A1 axis might promote the polarization of M2 macrophages and inhibit M1 macrophage activation through Wnt signaling pathway, collaborating to promote PRCC tumorigenesis and lead to poor overall survival of PRCC patients.

CancerMIRNome: an interactive analysis and visualization database for miRNome profiles of human cancer

MicroRNAs (miRNAs), which play critical roles in gene regulatory networks, have emerged as promising diagnostic and prognostic biomarkers for human cancer. In particular, circulating miRNAs that are secreted into circulation exist in remarkably stable forms, and have enormous potential to be leveraged as non-invasive biomarkers for early cancer detection. Novel and user-friendly tools are desperately needed to facilitate data mining of the vast amount of miRNA expression data from The Cancer Genome Atlas (TCGA) and large-scale circulating miRNA profiling studies. To fill this void, we developed CancerMIRNome, a comprehensive database for the interactive analysis and visualization of miRNA expression profiles based on 10 554 samples from 33 TCGA projects and 28 633 samples from 40 public circulating miRNome datasets. A series of cutting-edge bioinformatics tools and machine learning algorithms have been packaged in CancerMIRNome, allowing for the pan-cancer analysis of a miRNA of interest across multiple cancer types and the comprehensive analysis of miRNome profiles to identify dysregulated miRNAs and develop diagnostic or prognostic signatures. The data analysis and visualization modules will greatly facilitate the exploit of the valuable resources and promote translational application of miRNA biomarkers in cancer. The CancerMIRNome database is publicly available at http://bioinfo.jialab-ucr.org/CancerMIRNome.

Identification of serum prognostic marker miRNAs and construction of microRNA-mRNA networks of esophageal cancer

Esophageal cancer is a common tumor of the digestive system with poor prognosis. This study was to gain a better understanding of the mechanisms involved in esophageal cancer and to identify new prognostic markers. We downloaded the esophageal cancer miRNA expression profile microarray data (GSE113740, GSE112264, GSE122497, GSE113486, and GSE106817) from the GEO database, extracted the esophageal cancer miRNA sequencing data from The Cancer Genome Atlas (TCGA) database, and then used a bioinformatics approach to select common differentially expressed miRNAs (DEMs). Differentially expressed genes (DEGs) were selected by predicting DEM target genes using the miRWalk database and intersecting with differential genes obtained from TCGA database for esophageal cancer. The STRING database was used to obtain protein-protein interaction (PPI) relationships to construct the DEM-DEG network. Furthermore, we selected core genes and core miRNAs associated with esophageal cancer prognosis by performing survival and univariate/multivariate COX analysis on DEMs and DEGs in the network and performed GSEA analysis on core genes alone, and finally the expression of the markers was verified by qPCR in esophageal cancer cell lines Eca109, SKGT-4 and normal esophageal epithelial cells HEEC. Nine DEMs were obtained, of which three were upregulated and six were downregulated, and 326 DEGs were obtained, of which 105 were upregulated and 221 were downregulated. Survival univariate/multivariate COX analysis revealed that five genes, ZBTB16, AQP4, ADCYAP1R1, PDGFD, and VIPR2, and two microRNAs, miR-99a-5p, and miR-508-5p, were related to esophageal cancer prognosis. GSEA analysis showed that the following genes may be involved in esophageal cancer prognosis: ZBTB16 may through the MTOR signaling pathway, AQP4 through the GNRH signaling pathway, ADCYAP1R1 through the PPAR signaling pathway, VIPR2 through the P53 signaling pathway and PDGFD through the PENTOSE-PHOSPHATE signaling pathway.

MIR29A Impedes Metastatic Behaviors in Hepatocellular Carcinoma via Targeting LOX, LOXL2, and VEGFA

Primary liver cancer accounts for the third most deadly type of malignant tumor globally, and approximately 80% of the cases are hepatocellular carcinoma (HCC), which highly relies on the activity of hypoxia responsive pathways to bolster its metastatic behaviors. MicroRNA-29a (MIR29A) has been shown to exert a hepatoprotective effect on hepatocellular damage and liver fibrosis induced by cholestasis and diet stress, while its clinical and biological role on the activity hypoxia responsive genes including LOX, LOXL2, and VEGFA remains unclear. TCGA datasets were retrieved to confirm the differential expression and prognostic significance of all genes in the HCC and normal tissue. The Gene Expression Omnibus (GEO) dataset was used to corroborate the differential expression and diagnostic value of MIR29A. The bioinformatic identification were conducted to examine the interaction of MIR29A with LOX, LOXL2, and VEGFA. The suppressive activity of MIR29A on LOX, LOXL2, and VEGF was verified by qPCR, immunoblotting, and luciferase. The effect of overexpression of MIR29A-3p mimics in vitro on apoptosis markers (caspase-9, -3, and poly (ADP-ribose) polymerase (PARP)); cell viability and wound healing performance were examined using immunoblot and a WST-1 assay and a wound healing assay, respectively. The HCC tissue presented low expression of MIR29A, yet high expression of LOX, LOXL2, and VEGFA as compared to normal control. Serum MIR29A of HCC patients showed decreased levels as compared to that of normal control, with an area under curve (AUC) of 0.751 of a receiver operating characteristic (ROC) curve. Low expression of MIR29A and high expression of LOX, LOXL2, and VEGFA indicated poor overall survival (OS). MIR29A-3p was shown to target the 3'UTR of LOX, LOXL2, and VEGFA. Overexpression of MIR29A-3p mimic in HepG2 cells led to downregulated gene and protein expression levels of LOX, LOXL2, and VEGFA, wherein luciferase reporter assay confirmed that MIR29A-3p exerts the inhibitory activity via directly binding to the 3'UTR of LOX and VEGFA. Furthermore, overexpression of MIR29A-3p mimic induced the activity of caspase-9 and -3 and PARP, while it inhibited the cell viability and wound healing performance. Collectively, this study provides novel insight into a clinical-applicable panel consisting of MIR29, LOX, LOXL2, and VEGFA and demonstrates an anti-HCC effect of MIR29A via comprehensively suppressing the expression of LOX, LOXL2, and VEGFA, paving the way to a prospective theragnostic approach for HCC.

Bioinformatics analysis of mRNA and miRNA microarray to identify the key miRNA-mRNA pairs in cisplatin-resistant ovarian cancer

Background

Ovarian cancer (OC) is a gynecological malignancy with the highest mortality rate. Cisplatin (DDP) based chemotherapy is a standard strategy for ovarian cancer. Despite good response rates for initial chemotherapy, almost 80% of the patients treated with DDP based chemotherapy will experience recurrence due to drug-resistant, which will ultimately result in fatality. The aim of the present study was to examine the pathogenesis and potential molecular markers of cisplatin-resistant OC by studying the differential expression of mRNAs and miRNAs between cisplatin resistant OC cell lines and normal cell lines.

Methods

Two mRNA datasets (GSE58470 and GSE45553) and two miRNA sequence datasets (GSE58469 and GSE148251) were downloaded from the Gene expression omnibus (GEO) database. Differentially expressed genes (DEGs) and differentially expressed miRNAs (DEMs) were screened by the NetworkAnalyst. Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were conducted to analyze the biological functions of DEGs. The protein-protein interaction network was constructed using STRING and Cytoscape software to identify the molecular mechanisms of key signaling pathways and cellular activities. FunRich and MiRNATip databases were used to identify the target genes of the DEMs.

Results

A total of 380 DEGs, and 5 DEMs were identified. Protein–protein interaction (PPI) network of DEGs containing 379 nodes and 1049 edges was constructed, and 4 key modules and 24 hub genes related to cisplatin-resistant OC were screened. Two hundred ninety-nine target genes of the 5 DEMs were found out. Subsequently, one of these 299 target genes (UBB) belonging to the hub genes of GSE58470 and GSE45553 was identified by MCODE and CytoHubba,which was regulated by one miRNA (mir-454).

Conclusions

One miRNA–mRNA regulatory pairs (mir-454-UBB) was established. Taken together, our study provided evidence concerning the alteration genes involved in cisplatin-resistant OC, which will help to unravel the mechanisms underlying drug resistant.

Genetic variant rs10251977 (G>A) in EGFR-AS1 modulates the expression of EGFR isoforms A and D

Tyrosine kinase inhibitor is an effective chemo-therapeutic drug against tumors with deregulated EGFR pathway. Recently, a genetic variant rs10251977 (G>A) in exon 20 of EGFR reported to act as a prognostic marker for HNSCC. Genotyping of this polymorphism in oral cancer patients showed a similar frequency in cases and controls. EGFR-AS1 expressed significantly high level in tumors and EGFR-A isoform expression showed significant positive correlation (r = 0.6464, p < 0.0001) with reference to EGFR-AS1 expression levels, consistent with larger TCGA HNSCC tumor dataset. Our bioinformatic analysis showed enrichment of alternative splicing marks H3K36me3 and presence of intronic polyA sites spanning around exon 15a and 15b of EGFR facilitates skipping of exon 15b, thereby promoting the splicing of EGFR-A isoform. In addition, high level expression of PTBP1 and its binding site in EGFR and EGFR-AS1 enhances the expression of EGFR-A isoform (r = 0.7404, p < 0.0001) suggesting that EGFR-AS1 expression modulates the EGFR-A and D isoforms through alternative splicing. In addition, this polymorphism creates a binding site for miR-891b in EGFR-AS1 and may negatively regulate the EGFR-A. Collectively, our results suggested the presence of genetic variant in EGFR-AS1 modulates the expression of EGFR-D and A isoforms.

Expression and prognostic value of E2F3 transcription factor in non-small cell lung cancer

E2F transcription factor 3 (E2F3) plays a vital role in the development of various types of cancer. To verify whether E2F3 is a suitable biomarker for the prognosis of lung cancer, bioinformatics analysis was performed to determine the differential expression level of E2F3 in lung cancer and the surrounding non-tumor tissues, and the results were confirmed in a NSCLC cell line and a tissue microarray (TMA). The relevance of E2F3 in non-small cell lung cancer (NSCLC) was investigated in 19 studies from the Oncomine database and confirmed in The Cancer Genome Atlas database. In the lung cancer cell line A549, the inhibition of E2F3 mRNA expression level led to decreased tumor cell viability and cell migration, which was determined by a Cell Counting Kit-8 and wound healing assays, respectively. Immunohistochemistry analyses of E2F3, Bcl-2, Bax and caspase-3 were performed in the NSCLC TMA (n=50). The assessment of TMA detected the increase of E2F3 protein expression level in the tumor tissues, as compared with that in the non-tumor tissues, which was also correlated with the increase in expression of Bcl-2 in tumors. Analysis of the clinical data from patients with NSCLC revealed that the overexpression of E2F3 was associated with early lymphatic spreading, and poor patient survival time. The OncomiR website was used to predict the E2F3 upstream microRNAs and determine their prognostic value in patients with NSCLC. The results from the present study revealed that E2F3 was overexpressed at both the transcriptional and translational levels in NSCLC tissues, as compared with that in non-tumor tissues. The overexpression of E2F3 was associated with the upregulation of the anti-apoptotic factor, Bcl-2, which may contribute to uncontrolled tumor growth. Thus, E2F3 was shown to have important oncogenic properties in the development of NSCLC, and it may become a potential biomarker for patients with NSCLC.

The Implications of ncRNAs in the Development of Human Diseases

The mammalian genome comprehends a small minority of genes that encode for proteins (barely 2% of the total genome in humans) and an immense majority of genes that are transcribed into RNA but not encoded for proteins (ncRNAs). These non-coding genes are intimately related to the expression regulation of protein-coding genes. The ncRNAs subtypes differ in their size, so there are long non-coding genes (lncRNAs) and other smaller ones, like microRNAs (miRNAs) and piwi-interacting RNAs (piRNAs). Due to their important role in the maintenance of cellular functioning, any deregulation of the expression profiles of these ncRNAs can dissemble in the development of different types of diseases. Among them, we can highlight some of high incidence in the population, such as cancer, neurodegenerative, or cardiovascular disorders. In addition, thanks to the enormous advances in the field of medical genomics, these same ncRNAs are starting to be used as possible drugs, approved by the FDA, as an effective treatment for diseases.

Omics-Based Platforms: Current Status and Potential Use for Cholangiocarcinoma

Cholangiocarcinoma (CCA) has been identified as a highly malignant cancer that can be transformed from epithelial cells of the bile duct, including intrahepatic, perihilar and extrahepatic. High-resolution imaging tools (abdominal ultrasound, computed tomography and percutaneous transhepatic cholangial drainage) are recruited for diagnosis. However, the lack of early diagnostic biomarkers and treatment evaluation can lead to serious outcomes and poor prognosis (i.e., CA19-9, MUC5AC). In recent years, scientists have established a large number of omics profiles to reveal underlying mechanisms and networks (i.e., IL-6/STAT3, NOTCH). With these results, we achieved several genomic alteration events (i.e., TP53_mut, KRAS_mut) and epigenetic modifications (i.e., DNA methylation, histone modification) in CCA cells and clinical patients. Moreover, we reviewed candidate gene (such as NF-kB, YAP1) that drive gene transcription factors and canonical pathways through transcriptomics profiles (including microarrays and next-generation sequencing). In addition, the proteomics database also indicates which molecules and their directly binding status could trigger dysfunction signatures in tumorigenesis (carbohydrate antigen 19-9, mucins). Most importantly, we collected metabolomics datasets and pivotal metabolites. These results reflect the pharmacotherapeutic options and evaluate pharmacokinetic/pharmacodynamics in vitro and in vivo. We reversed the panels and selected many potentially small compounds from the connectivity map and L1000CDS² system. In this paper, we summarize the prognostic value of each candidate gene and correlate this information with clinical events in CCA. This review can serve as a reference for further research to clearly investigate the complex characteristics of CCA, which may lead to better prognosis, drug repurposing and treatment strategies.

The impact of microRNAs on alterations of gene regulatory networks in allergic diseases

Allergic diseases including asthma are worldwide on the rise and contribute significantly to health expenditures. Allergic diseases are prototypic diseases with a strong gene by environment interaction component and epigenetic mechanisms might mediate the effects of the environment on the disease phenotype. MicroRNAs, small non-coding RNAs (miRNAs), regulate gene expression post-transcriptionally. Functional single-stranded miRNAs are generated in multiple steps of enzymatic processing from their precursors and mature miRNAs are included into the RNA-induced silencing complex (RISC). They imperfectly base-pair with the 3'UTR region of targeted genes leading to translational repression or mRNA decay. The cellular context and microenvironment as well the isoform of the mRNA control the dynamics and complexity of the regulatory circuits induced by miRNAs that regulate cell fate decisions and function. MiR-21, miR-146a/b and miR-155 are among the best understood miRNAs of the immune system and implicated in different diseases including allergic diseases. MiRNAs are implicated in the induction of the allergy reinforcing the Th2 phenotype (miR-19a, miR-24, miR-27), while other miRNAs promote regulatory T cells associated with allergen tolerance or unresponsiveness. In the current chapter we describe in detail the biogenesis and regulatory function of miRNAs and summarize current knowledge on miRNAs in allergic diseases and allergy relevant cell fate decisions focusing mainly on immune cells. Furthermore, we evoke the principles of regulatory loops and feedback mechanisms involving miRNAs on examples with relevance for allergic diseases. Finally, we show the potential of miRNAs and exosomes containing miRNAs present in several biological fluids that can be exploited with non-invasive procedures for diagnostic and potentially therapeutic purposes.

Host⁻MicroRNA⁻Microbiota Interactions in Colorectal Cancer

Changes in gut microbiota composition have consistently been observed in patients with colorectal cancer (CRC). Yet, it is not entirely clear how the gut microbiota interacts with tumor cells. We know that tumor cells undergo a drastic change in energy metabolism, mediated by microRNAs (miRNAs), and that tumor-derived miRNAs affect the stromal and immune cell fractions of the tumor microenvironment. Recent studies suggest that host intestinal miRNAs can also affect the growth and composition of the gut microbiota. Our previous CRC studies showed a high-level of interconnectedness between host miRNAs and their microbiota. Considering all the evidence to date, we postulate that the altered nutrient composition and miRNA expression in the CRC microenvironment selectively exerts pressure on the surrounding microbiota, leading to alterations in its composition. In this review article, we present our current understanding of the role of miRNAs in mediating host–microbiota interactions in CRC.

Aging, Melatonin, and the Pro- and Anti-Inflammatory Networks

Aging and various age-related diseases are associated with reductions in melatonin secretion, proinflammatory changes in the immune system, a deteriorating circadian system, and reductions in sirtuin-1 (SIRT1) activity. In non-tumor cells, several effects of melatonin are abolished by inhibiting SIRT1, indicating mediation by SIRT1. Melatonin is, in addition to its circadian and antioxidant roles, an immune stimulatory agent. However, it can act as either a pro- or anti-inflammatory regulator in a context-dependent way. Melatonin can stimulate the release of proinflammatory cytokines and other mediators, but also, under different conditions, it can suppress inflammation-promoting processes such as NO release, activation of cyclooxygenase-2, inflammasome NLRP3, gasdermin D, toll-like receptor-4 and mTOR signaling, and cytokine release by SASP (senescence-associated secretory phenotype), and amyloid-β toxicity. It also activates processes in an anti-inflammatory network, in which SIRT1 activation, upregulation of Nrf2 and downregulation of NF-κB, and release of the anti-inflammatory cytokines IL-4 and IL-10 are involved. A perhaps crucial action may be the promotion of macrophage or microglia polarization in favor of the anti-inflammatory phenotype M2. In addition, many factors of the pro- and anti-inflammatory networks are subject to regulation by microRNAs that either target mRNAs of the respective factors or upregulate them by targeting mRNAs of their inhibitor proteins.