Puzzling out the role of MIAT LncRNA in hepatocellular carcinoma

Abstract

A non-negligible part of our DNA has been proven to be transcribed into non-protein coding RNA and its intricate involvement in several physiological processes has been highly evidenced. The significant biological role of non-coding RNAs (ncRNAs), including long non-coding RNAs (lncRNAs) has been variously reported. In the current review, the authors highlight the multifaceted role of myocardial infarction-associated transcript (MIAT), a well-known lncRNA, in hepatocellular carcinoma (HCC). Since its discovery, MIAT has been described as a regulator of carcinogenesis in several malignant tumors and its overexpression predicts poor prognosis in most of them. At the molecular level, MIAT is closely linked to the initiation of metastasis, invasion, cellular migration, and proliferation, as evidenced by several in-vitro and in-vivo models. Thus, MIAT is considered a possible theranostic agent and therapeutic target in several malignancies. In this review, the authors provide a comprehensive overview of the underlying molecular mechanisms of MIAT in terms of its downstream target genes, interaction with other classes of ncRNAs, and potential clinical implications as a diagnostic and/or prognostic biomarker in HCC.

Graphical abstract

Abbreviations

ABCG2

ATP Binding Cassette subfamily G member 2

ACE

Angiotensin-converting enzyme gene

ADGRL2

adhesion G protein-coupled receptor L2

ANRIL

Antisense Non-coding RNA in the INK4 Locus

ASO

Antisense Oligonucleotide

ATG7

autophagy related 7

ATM

Ataxia Telangiectasia Mutated

BANCR

BRAF-Activated Non-Protein Coding RNA

CASP1

Caspase 1

CCAT1

Colon Cancer-Associated Transcript 1

CCND1

Cyclin D1

CD8

Cluster of Differentiation 8

CDC16

Cell division cycle protein 16 homolog

CDKN1A

Cyclin Dependent Kinase inhibitor 1A

CDKN2B

Cyclin-Dependent Kinase 4 inhibitor B

CEP170

Centrosomal Protein 170

CK2

Checkpoint Kinase 2

c-Met

Mesenchymal-Epithelial Transition factor

CORO1C

Coronin-like actin-binding protein 1C

CREBRF

CREB3 Regulatory Factor

CTLA4

Cytotoxic T-Lymphocyte Antigen 4

CTNNB1

catenin beta 1

DAPK2

Death-associated protein kinase 2

DDX5

DEAD box polypeptide 5

Derlin-1

Degradation in Endoplasmic Reticulum protein 1

DLG3

Disks large homolog 3

DUSP7

Dual Specificity Phosphatase 7

EGFR

Epidermal Growth Factor Receptor

EMT

Epithelial-Mesenchymal Transition

ENCORI

Encyclopedia of RNA Interactomes

eNOS

Endothelial nitric oxide synthase

EPHA2

Erythropoietin-Producing Hepatocellular receptor A2

EZH2

Enhancer of Zest Homolog 2

FASTKD5

FAST kinase domains 5

FOXP3

Forkhead Box P3

GAPDH

Glyceraldehyde-3-Phosphate Dehydrogenase

GAS5

Growth arrest-specific 5

GDI2

GDP Dissociation Inhibitor 2

GENCODE

Human GENCODE database

GEO

Gene Expression Omnibus

GO

Gene Ontology

GZMK

Granzyme K

HAVCR2

hepatitis A virus cellular receptor 2

HCC

Hepatocellular Carcinoma

HDAC4

Histone Deacetylase 4

HEIH

HCC-specific lncRNA Enhancer of Invasion and Migration

HIF1A

Hypoxia Inducible Factor 1 Subunit Alpha

HOTAIR

HOX Transcript Antisense RNA

HOXA5

Homeobox A5

HSC

hepatic stellate cell

IER2

Immediate Early Response 2

IL-17

Interleukin 17

IPO7

Importin 7

IST1

IST1 factor associated with ESCRT-III

JAG1

Jagged canonical Notch ligand 1

JAK2

Janus Kinase 2

JNK

Jun N-terminal kinase

KCND1

Potassium Voltage-Gated Channel Subfamily D Member 1

KCNQ1

Potassium Voltage-Gated Channel Subfamily Q member 1

KCNQ1OT1

KCNQ1 Overlapping Transcript 1

LAG3

Lymphocyte-Activation Gene 3

LASP1

LIM And SH3 Protein 1

LDB1

LIM Domain-Binding protein 1

LincRNA-p21

Long Intergenic Non-coding RNA-p21

LINGO1

Leucine Rich Repeat And Ig Domain Containing 1

LIPCAR

Long Intergenic Non-Protein Coding RNA for Cardiac Regeneration

lncRNA

Long Non-coding RNA

LncRNA-ATB

Long Non-coding RNA Activated by TGF-β

LncRNA-LET

Long Non-coding RNA Low Expression in Tumor

LONP2

Lon peptidase 2, peroxisomal

LOXL2

Lysyl oxidase homolog 2

LUCAT1

Lung Cancer-Associated Transcript 1

MALAT1

Metastasis-Associated Lung Adenocarcinoma Transcript 1

MEG3

Maternally expressed 3

MEGF8

Multiple Epidermal Growth Factor-like Domains 8

MEIS3

Meis Homeobox 3

MIAT

Myocardial Infarction-Associated Transcript

MIR34A

MicroRNA 34a

miRNA

MicroRNA

MLF2

Myeloid Leukemia Factor 2

MMP14

Matrix metalloproteinase-14

MTCH1

Mitochondrial carrier homolog 1

MYO1B

Myosin IB

NAD

Nicotinamide Adenine Dinucleotide

NBR2

Neighbor Of BRCA1 LncRNA 2

ncRNA

Non-coding RNA

NEAT2

Nuclear Enriched Abundant Transcript 2

NF-κB

Nuclear Factor kappa B

NLM

National Library of Medicine

NO

Nitric Oxide

NONCODEV5

NONCODE database version 5

NONO

Non-POU Domain Containing Octamer Binding

NORAD

Non-Coding RNA Activated By DNA Damage

Notch1

Neurogenic locus notch homolog protein 1

PANDAR

Promoter of CDKN1A Antisense DNA Damage Activated RNA

PCAT-1

Prostate cancer associated transcript-1

PCDH1

Protocadherin 1

PD-1

Programmed Cell Death 1

PDCD1

Programmed cell death protein 1

PD-L1

Programmed Death-Ligand 1 (CD274 molecule)

PFN1

Profilin 1

PGC-1a

Peroxisome proliferator-activated receptor gamma coactivator 1-alpha

PI3K

Phosphatidylinositol 3-Kinase

PLAGL2

Pleomorphic adenoma gene like-2

PRODH

Proline Dehydrogenase 1

PTENP1

Phosphatase and Tensin homolog Pseudogene 1

PVT1

Plasmacytoma Variant Translocation 1

RAN

Ras-related Nuclear protein

Rfam

RNA Families database

RIN1

Ras and Rab Interactor 1

RPL13

Ribosomal Protein L13

RPL23A

Ribosomal Protein L23a

RPLP1

ribosomal protein lateral stalk subunit P1

RPS3

Ribosomal Protein S3

SART3

Spliceosome Associated factor 3

SCHLAP1

SWI/SNF Complex Antagonist Associated With Prostate Cancer 1

SF-1

Steroidogenic Factor 1

SGK1

Serum/Glucocorticoid regulated Kinase 1

siRNA

small interfering RNA

SIRT1

Sirtuin 1

SIX1

Sine oculis homeobox homolog 1

SLC6A6

Solute Carrier Family 6 Member 6

SNPs

Single Nucleotide Polymorphisms

SOX4

SRY-Box Transcription Factor 4

SP1

Specificity Protein 1

SPHK2

Sphingosine Kinase 2

STAT3

Signal Transducer and Activator of Transcription 3

STAU1

Staufen-1

TCF20

Transcription Factor 20

TCGA

The Cancer Genome Atlas

TGF-β2

Transforming Growth Factor beta 2

TIM3

T-cell Immunoglobulin and Mucin-domain containing 3

TME

Tumor Microenvironment

TMEM147

Transmembrane Protein 147

TP53

Tumor Protein p53

TRAF6

TNF Receptor Associated Factor 6

TTC37

Tetratricopeptide repeat domain 37

TUBA1B

Tubulin Alpha 1B

UBA2

Ubiquitin-Like Modifier-Activating Enzyme 2

VEGF

Vascular endothelial growth factor

VELUCT

Viability Enhancing in Lung cancer Transcript

WNT9A

Wnt Family Member 9A

XIST

X-linked X-inactive-specific transcript

YAP1

Yes-associated protein 1

YBX1

Y-box binding protein 1

YWHAE

Tyrosine 3-Monooxygenase/Tryptophan 5-Monooxygenase Activation Protein Epsilon

ZEB1

Zinc finger E-box binding homeobox 1

1. Introduction

Following the completion of “The Human Genome Project” in 2003, the classification of the genome and its elements has been a challenge and the focus of all molecular scientists [1,2]. One of the broad classifications of the genome is categorizing it into protein-coding and non-protein-coding genes [3]. The protein-coding regions of the DNA were once thought to be the most fundamentally functional segment, and as a result, must make up the majority of the DNA [4,5]. Surprisingly, less than 3 % of the genome's transcribed region is translated into proteins [6,7]. Given this, non-coding RNAs (ncRNAs), or non-protein producing RNA, which were previously assumed to be the result of “junk DNA”, attracted attention as it became clear that they do serve a purpose [8,9]. According to databases such as Human GENCODE and NONCODEV5, the major class of ncRNAs are long non-coding RNAs (lncRNAs), with over 100,000 members. Yet to be determined is the precise number of functional lncRNAs [[10], [11], [12], [13], [14]]. Members of this class have transcripts larger than 200 nucleotides and are important regulators [15,16]. LncRNAs can also be divided into subclasses [17,18]. According to one of these classifications, the genomic location of ncRNAs can result in intergenic, intronic, sense, and antisense lncRNAs [9,19,20], as shown in Fig. 1.

Fig. 1.

The possible genomic locations of lncRNAs. Protein-coding genes and their exons are represented by green segments, while lncRNAs and their introns are represented by pink segments. (A) An intergenic lncRNA, transcribed from either DNA strand between two protein-coding genes. (B) An intronic lncRNA, transcribed from protein-coding gene introns. (C) A sense lncRNA, transcribed from the sense strand of protein-coding genes, overlapping with part (or entirely) of a protein-coding sequence and one or more introns. (D) An antisense lncRNA, transcribed from the antisense strand of protein-coding genes, overlapping with a part (or entirely) of a protein-coding sequence and 1 or more introns. (*) Sense and Antisense lncRNAs are subcategories of a larger class called genic lncRNAs.

2. Roles and functions of lncRNAs

Alternatively, lncRNAs can be classified according to their functional role [17]. As already indicated, lncRNAs have a significant regulatory function, modulating the activity of genes, RNAs, proteins, organelles, and nuclear condensates [21,22]. More specifically, lncRNA functions include one or more of the following: chromatin remodeling, histone modification, RNA-DNA-DNA triplex formation through direct pairing with the DNA, gene silencing, transcriptional regulation of genes through silencing or enhancing respective mRNA expression, nuclear condensate formation, post-transcriptional modifications exerted by direct protein-binding, miRNA sponging, and mRNA stabilization. Additionally, lncRNAs may affect mitochondrial function, intercellular exosomal transport, and cell regulation [12,20,23,24]. Table 1 lists functional roles played by lncRNAs.

Table 1.

Molecular and functional roles of lncRNAs.

Molecular role	Functional role	References
Epigenetic regulation	Chromatin remodeling	[25]
	Histone modification	[26]
	Gene silencing	[27]
	Triplex formation	[28]
Transcriptional regulation	Promotion via promotor regions and/or transcription factor modulation	[29,30]
	Suppression via promotor regions and/or transcription factor modulation	[31]
Post-transcription regulation	Protein binding	[32]
	mRNA stabilizing activity	[33]
	miRNA sponging (lncRNAs function as competing endogenous RNA)	[34,35]
Nuclear scaffolding and condensates	–	[12]
Organelle regulation	Mitochondrial modulation of apoptosis, metabolism, and nucleus crosstalk	[36,37]
	Exosomal release	[38]

3. LncRNAs as potential theranostic agents (biomarkers and/or therapeutic agents)

The functional roles of lncRNAs unravel their crucial role in various aspects of cellular homeostasis [39]. Moreover, lncRNAs have the potential to serve as non-invasive prognostic markers, diagnostic markers, and/or potential therapeutic agents/targets in a variety of diseases, such as cancer, diabetes, and genetic diseases which perfectly classifies them as theranostic agents with great potential in several malignant and non-malignant contexts [12,14,40,41].

Specifically, several lncRNAs have been characterized as non-invasive biomarkers quantifiable in liquid biopsies [42]. LncRNAs show tissue-specific expression patterns, which aid in the traceability of different cancer types [43]. Additionally, they are abundant in plasma samples, enabling their easy detection. Although it is still unclear whether exosomal or free lncRNAs contribute more to the detectable fraction, exosomal lncRNAs are known to be stable in biological fluids, due to their resistance and stability against RNases [42,44,45].

Exosomal lncRNAs constitute promising candidates for therapeutic intervention in various diseases since they are increasingly recognized as key players in intercellular communication, controlling cellular functions, and affecting disease states. These characteristics also raise the possibility of employing non-oncogenic exosomal lncRNAs therapeutically for internalization and cell-specific effects after a disease mechanism has been thoroughly elucidated [42,45]. Other hypotheses have been put forth in which lncRNAs act as the therapeutic targets rather than the therapeutic agents [6,15].

LncRNAs that foster neovasculature, drug resistance, or cancer cell-to-cell communication could constitute promising targets [45]. Similarly, by identifying the binding domains of an oncogenic lncRNA that is responsible for triggering a certain signaling pathway, a complimentary chemical can be synthesized and delivered to block that lncRNA and subsequently inhibit its tumor-promoting action. Although such an approach has merit, it currently has the challenge of inadequate motif structural knowledge [12,[46], [47], [48]]. Additionally, lncRNAs were demonstrated to be the less toxic and more potent biological alternatives to proteins [12]. Jiang et al. highlighted how current technology can be used to pave the path for the usage of lncRNAs as therapeutic agents [12,49].

Metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) [14,15,18], HOX transcript antisense RNA (HOTAIR) [41,50], H19 imprinted maternally expressed transcript (H19) [16,22], colon cancer associated transcript 1 (CCAT1) [13,21], and hepatocellular carcinoma up-regulated EZH2-associated long non-coding RNA (HEIH) [7] are some of the well-known lncRNA members with the potential to serve as biomarkers or therapeutic agents/targets for several malignancies such as breast, liver, and brain tumors, while LIPCAR, CDKN2B antisense RNA 1 (ANRIL), and KCNQ1 opposite strand/antisense transcript 1 (KCNQ1OT1) are well-studied lncRNAs in terms of non-malignant disorders such as cardiovascular diseases [42,51,52].

4. LncRNAs in oncology

Focusing on the role of lncRNAs in cancer, several studies have identified and correlated many lncRNAs to a diverse range of malignancies. LncRNAs are pivotal regulators in the complex landscape of oncology. Aberrant expression of lncRNAs is associated with various cancers (Table 2). In addition to the ones that were before listed, HEIH and sONE act as significant breast cancer regulators [7,53,54]. LncRNA activated by TGF-β (LNCRNA-ATB) and NPTN intronic transcript 1 (LNCRNA-LET) are associated with HCC. CCAT1, as its name suggests, is linked to colorectal cancer, while promoter of CDKN1A antisense DNA damage activated RNA (PANDAR) and colon cancer associated transcript 2 (CCAT2) are two examples of lncRNAs important for lung cancer progression and prognosis [20,55]. Lung cancer-related transcript 1 (LUCAT1), is involved in breast cancer, ovarian cancer, thyroid cancer, and renal cell carcinoma [56], as well as H19, plays a role in breast cancer, colorectal cancer, and lung cancer [20,34,51,55].

Table 2.

Potential oncogenic and tumor-suppressive lncRNAs in several malignant contexts.

LncRNA	Cancer Type	Signaling pathway	Expression profile	Impact	Hallmark involved	Reference
H19	Colorectal cancer	Sponging miR-141, thus activating the β-catenin pathway	Upregulated	Oncogenic	Cancer cell stemness and chemoresistance	[57]
	Hepatocellular cancer	Exosomal release increases the expression of endothelial factors	Upregulated	Oncogenic	Angiogenesis	[58]
HOTAIR	Non-small cell lung cancer	Suppression of matrix metalloproteinases and HOXA5 protein	Upregulated	Oncogenic	Cell invasion and metastasis	[59]
MIAT	Lung cancer	Promotor methylation of the MIR34A gene leads to decreased expression and subsequent activation of the PI3K/AKT signaling pathway	Upregulated	Oncogenic	Drug resistance	[60]
	Glioma	Promotor of proliferation, migration, and metastasis of brain cancer cells	Upregulated	Oncogenic	Cancer progression	[61]
PTENP1	Bladder cancer	Exosomal release acts as a miR-17 decoy to regulate PTEN expression	Downregulated	Tumor-suppressive	Cancer progression	[62]
GAS5	Non-small cell lung cancer	Suppression of miR-23a	Downregulated	Tumor-suppressive	Cancer tissue growth and apoptosis	[63,64]
MALAT1 (also known as NEAT2)	Non-small cell lung cancer	MALAT1 promoting activation through Specificity Protein 1 (SP1)	Upregulated	Oncogenic	Cancer cell growth and invasion	[65,66]
	Breast cancer	Exosomal	Upregulated	Oncogenic	Cell proliferation	[67]
	Esophageal squamous cell carcinoma	ATM-CHK2 dephosphorylation leading to unregulated G2/M cell cycle checkpoint	Upregulated	Oncogenic	Cancer cell proliferation, invasion, and metastasis	[68]
CCAT1	Non-small cell lung cancer	CCAT1/miR-130a-3p/SOX4 axis, boosting ABCG2-mediated drug efflux	Upregulated	Oncogenic	Cancer cell chemoresistance	[69]
MEG3	Non-small cell lung cancer	Suppressive action on WNT/b-catenin pathway through TP53, b-catenin, and survivin	Downregulated	Tumor-suppressive	Cancer cell cycle regulation and chemoresistance	[70]
		LC3 cleavage downregulation, suppressing intracellular components autophagy	Downregulated	Tumor-suppressive	Cancer cell chemoresistance	[71]
XIST	Non-small cell lung cancer	LC3 autophagy-factor cleavage promotion and overexpression of ATG7 through miR-17/autophagy axis	Upregulated	Oncogenic	Cancer cell chemoresistance	[72]
	Pancreatic cancer	Compound action of a multitude of pathways, primarily by sponging miRNAs: EGFR/miR-133a, iASSP/miR-140/miR-124, YAP/miR-34a, ZEB1/miR-429, TGF-β2/miR-141–3p, and Notch1/miR-137 pathways	Upregulated	Oncogenic	Cancer cell growth, invasion, and migration	[73]
NEAT1	Triple-negative breast cancer	SOX2 mRNA downregulated expression	Upregulated	Oncogenic	Cancer cell stemness and chemoresistance	[74,75]
	Hemangioma	Sponging of miR-33a-5p enhances NF-κB signaling thus increasing the expression of the HIF1A gene	Upregulated	Oncogenic	Cancer cell proliferation, invasion, and metastasis	[75,76]
	Acute myeloid leukemia	Negative feedback on miR-338-39, potentiating CREBRF	Downregulated	Tumor-suppressive	Cancer cell proliferation, invasion, and metastasis	[75,77]
sONE	Triple-negative breast cancer	Suppression of MYC and enhancement of TP53 thus increasing the concentration of several downstream tumor suppressive mRNAs, including miR-34a, miR-15, miR-16, and let-7a. Additionally, NO production modulator via eNOS posttranscriptional regulation.	Downregulated	Tumor-suppressive	Cancer cell proliferation, invasion, and metastasis	[54,78]

Remarkably, lncRNAs have the potential to be used as biomarkers and therapeutic agents if they are tumor-suppressive, or as therapeutic targets if they are oncogenic. Their potential to serve as therapeutic targets and diagnostic markers holds promise for improving early detection and treatment options in oncology. Fig. 2 represents a graphical presentation of the lncRNAs and their possible association with several solid malignancies. Each lncRNA has distinct effects mediated through different signaling pathways in each cancer context. This proposes a complexity in the mechanisms and interrelated functions of lncRNAs and their subsequent effect.

Fig. 2.

Graphical representation of human tumors and related lncRNAs. Red labels indicate oncogenic lncRNAs, while green labels indicate tumor-suppressive lncRNAs.

5. Methodology

In the current review, the authors aimed at exploring the role of MIAT in HCC. The authors screened the National Library of Medicine (PubMed). To search databases, the descriptors or keywords used were: “MIAT”, “myocardial infarction-associated transcript” “MIAT LncRNA”, “HCC”, “Hepaticellular carcinoma”, and “Oncology”, “LncRNAs” to cover as many articles as possible in the literature. Relevant publications with detailed information were included including research articles, review articles, and book chapters; These selected references were evaluated and summarized in order to fulfill the purpose of this review article.

6. Myocardial infarction associated transcript (MIAT)

Myocardial infarction-associated transcript (MIAT) is a novel lncRNA that has recently been reported to have a fundamental role in several oncological contexts [13,41]. MIAT is located on chromosome 22q12.1 as shown in Fig. 3 [79]. MIAT gene length is around 30 Kb. MIAT is transcribed from the sense strand of the genome, producing a structure with 5 exons and several introns with multiple combinations of single nucleotide polymorphisms (SNPs), and a polyadenylated tail, as shown in Fig. 3. Post-transcriptional splicing gives rise to 4 different variants of spliced lncRNA [[80], [81], [82], [83]]. As indicated by its name, it is predicted that it has a role in cardiovascular diseases such as atherosclerosis, and coronary artery diseases. However, it has been discovered that not only does it influence these diseases, but it also plays a key role in several solid malignancies such as lung cancer, hepatocellular carcinoma, and breast cancer among countless others [20,60,84,85]. The biogenesis of MIAT-like all other lncRNAs is dependent on the cell type and stage, as previously reviewed [17]. Collectively, research studies focusing on MIAT shed light on its complex function and offer a possible path for therapeutic interventions, as discussed below. Different functional mechanisms of MIAT have been described, so far; moreover, this lncRNA has been described to decoy several microRNAs (miRNAs) and thus altering the downstream array of critical signaling pathways dictating cellular proliferation, apoptosis, and inflammation (Fig. 4).

Fig. 3.

Chromosomal locations and Single Nucleotide Polymorphisms (SNPs) in MIAT. MIAT is located on chromosome 22, band q12.1. A simplified view of MIAT is also illustrated with its exons with various splicing combinations and SNPs.

Fig. 4.

MIAT-mRNA interaction network. A network plot representing MIAT-mRNA regulatory network. Data was retrieved from the ENCODE database.

6.1. MIAT cellular localization and single nucleotide polymorphisms (SNPs)

The subcellular localization of MIAT is the nucleus, as demonstrated by a nuclear/cytosol fractionation assay that showed that it is mostly expressed in the nucleus of cardiomyocytes [86]. MIAT is known for its multiple SNPs that are strongly associated with increased susceptibility to myocardial infarction [87]. The fully elucidated sequence and SNP variations of lncRNA MIAT are present in multiple databases, including GeneCaRNA, Rfam, and the National Library of Medicine (NLM) gene dataset. For instance, in the Chinese Han population, the promoter polymorphisms in the MIAT gene Rs5752375 and Rs9608515 were found to be associated with acute myocardial infarction [83]. Furthermore, many different SNPs of MIAT have been shown to have different diverse effects as shown in Fig. 3. For instance, Rs1894720 MIAT polymorphism has been found to increase susceptibility to age-related loss of hearing by tuning the miR-29 b-3p/SIRT1/PGC-1α axis [88]. Another study demonstrated a notable correlation between Rs1894720 in MIAT and paranoid schizophrenia within the Chinese Han population [89].

6.2. MIAT-mRNA and MIAT-miRNA networks

Recent progress in high-throughput sequencing technologies has led to the identification of novel ncRNAs as well as an understanding the regulatory mechanisms for their co-expression including protein-coding genes and ncRNA molecules [90]. Databases are categorized into various classifications depending on their role in storing, displaying, and also analyzing data for ncRNAs.

RNAcentral is one of the most comprehensive databases for ncRNAs, where since its launch in 2014 about 10.2 million ncRNA sequences were identified, sequenced and recorded in it, thus providing invaluable information for subsequent recognition of ncRNAs once sequenced [91]. Also, RNAcentral integrates other ncRNA databases into one platform to allow accessible search for ncRNAs of interest.

NONCODE and LNCipedia are two of about 12 databases that integrate with RNAcentral, particularly to provide in-depth information regarding lncRNAs as well as tRNAs and rRNAs [92,93]. RNAcentral allows sequence similarity search, text search, and genome browsing of ncRNAs which aids in the identification of novel ncRNAs in different species as well as providing GO (Gene ontology) annotations for miRNAs and lncRNAs using RNAcentral identifiers.

LncTarD is a lncRNA-specific database that provides comprehensive information regarding lncRNA functions, regulatory mechanisms, as well as lncRNA-target insights following data retrieval from GEO (gene expression omnibus) database of NCBI as well as PubMed [94]. Another lncRNA database that provides lncRNA-target gene information is LncRNA2Target which includes curated data for both human and mice samples across different pathologies in order to display insightful results through combined analysis of stored lncRNA data in tabular format [95].

ENCORI (The Encyclopedia of RNA interactomes) is also a robust database that is particularly useful for understanding how RNA molecules integrate following results from high throughput sequencing data stored in the database. LncRNA-lncRNA, lncRNA-gene, miRNA-gene, and miRNA-ncRNA are useful integration techniques provided by ENCORI in order to understand how lncRNAs, miRNAs, and protein-coding genes interact together, particularly in cancer contexts [96].

Following in-silico analysis of MIAT-mRNA and MIAT-miRNA interactions using ENCORI, LncTarD, and LncRNA2Target databases, results revealed a comprehensive list of protein-coding genes and miRNAs that directly interact with MIAT in different pathological conditions. MIAT-mRNA network was constructed using Cytoscape software (v.3.10) and revealed 45 interaction nodes with MIAT at different disease states as listed in Table 3, where tumor protein p53 (TP53), transmembrane protein 147 (TMEM147), importin 7 (IPO7), mitochondrial carrier homolog 1 (MTCH1), LIM domain-binding protein 1 (LDB1), ubiquitin-like modifier-activating enzyme 2 (UBA2), coronin‐like actin‐binding protein 1C (CORO1C), IST1 factor associated with ESCRT-III (IST1), and proline dehydrogenase 1 (PRODH) were highlighted in later annotation using gene ontology Fig. 4. Also, MIAT-miRNA interaction resulted in the detection of 9 miRNAs; miR-150, miR-145, miR-148 b, miR-206, miR-181 b, miR-149–5p, miR-214–3p, miR-641, and miR-181a-5p (Table 3); which could provide further understanding of MIAT role in HCC following further analysis. Moreover, gene ontology annotation of MIAT-mRNA interactions revealed several biological processes in which MIAT acts as a regulator of their action through suppressing the top 10 processes which MIAT-related protein-coding genes (n = 45) are directly regulating via GO scoring (Fig. 5), which explains the interconnection between all MIAT-related genes and subsequent GO functions following construction using R programming language (v. 4.0).

Table 3.

MIAT-mRNA and MIAT-miRNA selected interactions^a reported in non-coding RNA databases.

mRNA or miRNA	Database	Reference
CORO1C	ENCORI	[96]
IPO7
IPO7
IST1
LDB1
MTCH1
PRODH
TMEM147
TP53
UBA2
miR-145	LncTarD/LncRNA2Target	[94,95]
miR-148 b
miR-149–5p
miR-150
miR-181a-5p
miR-181 b
miR-206
miR-214–3p
miR-641

^aMIAT-mRNA and MIAT-miRNA interactions across multiple pathological conditions using ENCORI, LncTarD, and LncRNA2Target databases. Results were retrieved using search API tool identifier for MIAT-related interaction on the mentioned databases.

Fig. 5.

Chord diagram for MIAT gene-function network using GO and ENCORI databases; this diagram describes the top GO expressed biological functions for the 45 genes interacting with MIAT. Results showed that SPHK2, RPS3, IPO7, TP53, RAN, and YWHAE are highly expressed genes from MIAT-based network and are directly interacting with higher of functions compared to the other genes.

6.3. Role of MIAT in solid malignancies

Recently, it has been experimentally reported that MIAT has distinct roles in the tumorigenesis and progression of distinct types of cancer. Briefly, MIAT has been shown to have a pro-tumorigenic activity against the following types of cancer including HCC, breast cancer, non-small cell lung cancer, colorectal cancer, pancreatic cancer, ovarian cancer, gastric cancer, cholangiocarcinoma, and renal cell carcinoma. Mainly, MIAT contributed to the previous types of cancers via increasing the proliferation, the invasion, and the migration. In addition to this, the sponging or interacting activity of MIAT with an array of miRNAs reveals how MIAT up-regulation could increase the cancerous activity of tumor cells via the downstream target genes/proteins of these miRNAs as shown in Fig. 6. We and others have extensively reported the direct involvement of miRNAs and lncRNAs in the hepatocarcinogenesis process [[97], [98], [99], [100], [101], [102], [103]]. The following section will discuss the role of MIAT as a puzzling lncRNA in HCC with its pro-tumorigenic or anti-tumorigenic nature, its mechanism of action in terms of the downstream target genes including their possible signaling pathways, crosstalk between different classes of ncRNAs and lastly, its clinical eligibility to be a predictive diagnostic and/or prognostic marker.

Fig. 6.

Validated MIAT lncRNA-miRNAs-mRNAs interaction network in carcinogenesis. Crosstalk between MIAT lncRNA, its microRNA prey and their respective targets, and the cancer hallmarks that are altered due to these interactions, in different malignant contexts. The potential of some microRNAs, such as miR-133 and miR-212, to target MIAT, is also highlighted. Red arrows signify downregulation effect mediated by lncRNA MIAT on the several microRNAs. Green arrows signify upregulation effect on the downstream targets, subsequent to the respective microRNA suppression.

7. Hepatocellular carcinoma (HCC)

HCC is considered one of the most lethal solid malignancies with high relapse rates and poor prognosis [97,98]. A myriad of factors could be listed under the etiology of the disease, as these factors have a profound impact on the initiation and progression of the disease. For instance, many research studies have revealed that unhealthy diet, alcohol, smoking, hepatitis C virus, and aflatoxin are the drivers for inflammation–causing conditions that eventually cause HCC. Although there are considerable scientific records for the causative reasons for the pathogenesis of HCC, there is still a gap that needs to be filled regarding how the non-coding part of our genome could have a non-negligible role in the aggravation of this disease.

7.1. Role of MIAT in chronic liver diseases

Chronic liver diseases (CLD), including cirrhosis, fibrosis, alcoholic liver disease, and chronic hepatitis, are important precursors of HCC. A recent study showed that elevated MIAT expression during liver fibrosis is linked to increased hepatic stellate cell (HSC) proliferation and collagen expression, while MIAT knockdown demonstrated a marked suppression of fibrosis progression and collagen accumulation in vivo. MIAT acts as a sponge for miR-3085–5p, showing a negative correlation with miR-3085–5p levels in cirrhotic patients and activated HSCs. The study underscores the role of MIAT in HSC activation through the miR-3085–5p/YAP1, where MIAT inhibition leads to reduced yes-associated protein 1 (YAP1) levels and subsequent suppression of the epithelial-to-mesenchymal transition (EMT) process [104]. While the detailed function of MIAT in alcoholic liver disease and chronic hepatitis has not yet been investigated, to the best of our knowledge, given its role in fibrosis and cirrhosis there is potential for a similar influential role in other forms of CLD. Going beyond merely acting as precursors to HCC, these observations imply that MIAT could contribute to the pathogenesis of HCC through inflammation, fibrosis, and other aspects inherent to CLD. Hence, understanding the role of MIAT in CLD could provide useful insights into the molecular mechanism of hepatocellular carcinogenesis.

7.2. Role of MIAT in HCC pathogenesis

As indicated in the literature, a unanimous consensus across multiple studies underscores the robust correlation between MIAT presence and the onset of HCC. A study focusing on lncRNAs associated with epithelial-mesenchymal transition (EMT) in HCC presented MIAT on top of the list of lncRNAs that were both differentially expressed in HCC and positively correlated with EMT in HCC. On the molecular level, it was reported that MIAT plays an oncogenic and metastatic role in HCC as upon MIAT knockdown in HCC cell lines, a significant reduction in the levels of Cadherin-1 (e-cadherin, an epithelial marker) and an elevation in the levels of Cadherin-2 (n-cadherin, a mesenchymal marker) was observed [105].

7.2.1. Crosstalk between MIAT and miR-214–3p

A study by Huang et al. discovered that HCC cell lines (HepG2, Huh-7, SK-HEP-1, and HLE) and patient tissue samples have higher levels of MIAT expression than adjacent normal tissues and normal hepatocyte cell line (L02); this could be considered as an indication that MIAT has a role in the pathogenesis of HCC. Mechanistically, it has been found that the H3/H4 epigenetic acetylation of the MIAT promoter in tumor tissues is the reason behind the elevated expression of MIAT in HCC tumor tissues and cell lines. Nonetheless, it has been experimentally validated that MIAT sponges the tumor-suppressor miRNA, miR-214–3p, in HCC cell lines and accordingly ranks MIAT as an oncogenic lncRNA in HCC [106]. In addition to this, MIAT knockdown in vivo resulted in the elevation of miR-214–3p levels, and subsequently, of catenin beta 1 (CTNNB1 or β-catenin) and enhancer of zest homolog 2 (EZH2) which are the downstream targets of miR-214–3p [107], as shown in Fig. 7.

Fig. 7.

Graphical representation of signaling cascades and ncRNAs circuits drawn downstream MIAT in HCC. A summary for all reported oncogenic related genes, immunogenic related genes and ncRNA-miRNA circuits reported to be modulated by MIAT in HCC.

7.2.2. Crosstalk between MIAT and miR-520 d-3p

The role of MIAT as a miRNA sponge in the evolution of HCC was underlined in another study [108]. This work showed that miR-520 d-3p, which was previously proven to have an anti-tumorigenic function in HCC, is downregulated by MIAT. The authors found that MIAT expression affected the downstream target genes of miR-520 d-3p. Specifically, a positive association between MIAT and erythropoietin-producing hepatocellular receptor A2 (EPHA2), a miR-520 d-3p downstream target gene was recorded. It has been shown in this study and other studies that EPHA2 regulates MYC proto-oncogene (MYC) and cyclin D1 (CCND1), which are involved in cell cycle regulation and proliferation, and that inducing the expression of miR-520 d-3p in HCC cells results in a reduction in MYC and CCND1 expression by inhibition of EPHA2 [109,110], as shown in Fig. 7.

7.2.3. Crosstalk between MIAT and miR-22–3p

It was also shown that MIAT promotes the survival of HCC cells to survive against cellular senescence via regulating the miR-22–3p/SIRT1 axis (Fig. 7) [111]. Sirtuin 1 (SIRT1) protein is a NAD–dependent histone deacetylase that was reported for its inhibitory effect on cellular senescence via preventing apoptosis, maintaining cellular metabolism, and preventing cells from oxidative stress [112]. This work discovered that MIAT is a senescence-associated lncRNA in addition to being a differentially expressed lncRNA in HCC by analyzing The Cancer Genome Atlas (TCGA) liver cancer dataset. Experimental validation of whether cellular senescence is activated or not in the presence of MIAT was validated in human fibroblast 2BS cells and oncogene-induced 2BS cells. It was shown that MIAT was highly present in 2BS young cells whereas its expression decreased during the cellular senescence process of 2BS cells. The decrease of MIAT expression levels via its knockdown in 2BS cells led to an increase of senescence–associated beta-galactosidase activity, cell cycle arrest, and cell proliferation inhibition. Similar results were obtained, showing that the MIAT expression levels are lower in the HCC senescence models (HEPG2 and SMMC-7721) than in the normal cell lines [111].

7.3. Role of MIAT in HCC chemoresistance and immunotherapy

An important hallmark of cancer in general and HCC in particular is the immune escape [14,16,21,22,113,114]. Immune cells, infiltrating the tumor microenvironment (TME), have an enormous impact in stopping the tumor cells from proliferation, invasion, and dissemination [[115], [116], [117]]. Another considerable barrier in HCC therapeutic protocols is high incidence rates of resistance to the conventional anticancer agents that would consequently lead to more aggressive tumors and a rapid relapse in many cases [50,118]. MIAT is involved in the immune cellular response and associated non-cellular components at the TME. In a study performed by Peng et al. , a bioinformatics analysis was carried out using the TIMER database to explore the relationship between MIAT and immune cells and mediators in HCC. Analyzing the TIMER database showed a positive correlation between MIAT and immune cells: cytotoxic T lymphocytes, T helper cells, macrophages, dendritic cells, neutrophils, and B cells. This positive correlation was also found between MIAT, and the expression of immune checkpoint inhibitors programmed cell death 1 (PDCD1 or PD-1), CD274 molecule (PD-L1), cytotoxic T-lymphocyte associated protein 4 (CTLA4), lymphocyte activating 3 (LAG3), and hepatitis A virus cellular receptor 2 (HAVCR2, also known as TIM3). A deeper analysis was performed by using the single-cell sequencing techniques for the CD45⁺ immune cells in HCC. Results showed that MIAT contributes to tumor immunosuppression since MIAT expression was high in forkhead box P3 (FOXP3) and CD4 positive T cells and PD-1 and granzyme K (GZMK) and CD8 subunit alpha (CD8) positive T cells in tumors and blood, hepatic lymph nodes, and ascites. FOXP3+ CD4⁺ T cells and PDCD1+/GZMK + CD8⁺ T cells correspond to regulatory T cells and exhaustive T cells, respectively [119].

A significant aspect by which MIAT exerts its action is its cellular localization. With the assistance of lncLocator, the cellular location of MIAT was expected to be in the nucleus [120]. This was a sign that MIAT plays a role in gene expression regulation via interacting with transcription factors in the nucleus [120]. These transcription factors include Janus kinase 2 (JAK2), solute carrier family 6 member 6 (SLC6A6), potassium voltage-gated channel subfamily D member 1 (KCND1), Meis homeobox 3 (MEIS3), and Ras and Rab interactor 1 (RIN1). The correlation between MIAT and immune cells was further confirmed by exploring the correlation between the previously stated target genes and immune cells.

MIAT expression confers HCC resistance against sorafenib [121]. It was found that the resistance in sorafenib is associated with high expression of MIAT in HCC cells and this was also associated with the presence of PD-L1 [121]. Consistent with this, the mRNA and protein of PD-L1 were decreased upon MIAT knockdown in HepG2 and Huh7 cell lines, and the expression of both MIAT and PD-L1 were significantly elevated after treatment of HCC cells with sorafenib. Hence, the resistance of sorafenib in HCC could be attributed to the up-regulation of PD-L1 by MIAT and eventually lead to immune escape [121].

A similar issue of immune escape caused by MIAT in HCC was investigated in another study in terms of the potential regulatory network and mechanism of regulation of PD-L1 by MIAT in HCC cells. It was discovered that MIAT regulates miR-411–5p by functioning as a competitive endogenous RNA that binds to miR-411–5p and inhibits its actions [85]. Upon MIAT knockdown in HepG2 and Huh7 cells, a marked reduction in PD-L1 expression levels was witnessed. Signal transducer and activator of transcription 3 (STAT3), a transcription factor that controls PD-L1 by binding to its promoter, was also shown to be one of the putative targets of miR-411–5p. These results were supported by the transfection of a miR-411–5p oligonucleotide into HCC cells, which resulted in repression in PD-L1 and STAT3 on both mRNA and protein levels [121].

7.4. Potential clinical applications of MIAT

MIAT holds promise as a diagnostic biomarker for various cancers, including HCC. The reported upregulation of MIAT expression in tissue samples may serve as an early indicator of cancer, facilitating timely diagnosis [106]. Moreover, as the expression levels of MIAT have shown potential as prognostic indicators in other types of cancer [122], offering insights into clinical outcomes such as disease progression, metastasis, and overall survival in cancer patients, would be possible in HCC as well. Furthermore, exploring the association between MIAT expression and clinical features specific to HCC, such as tumor stage, grade, and vascular invasion, could enhance our understanding of the role of MIAT in HCC development and progression.

In the realm of cancer therapeutics, MIAT may present itself as a promising therapeutic target. MIAT promotes the growth and invasive abilities of HCC tumor cells [106]. Thus, inhibiting the expression of MIAT may be an effective way to treat HCC. This could potentially be achieved with targeted therapies like small interfering RNAs (siRNAs) or antisense oligonucleotides (ASOs) designed to bind to and cause degradation of specific lncRNAs.

Additionally, given the deregulation of MIAT in HCC cell lines upon sorafenib treatment, MIAT expression levels could be leveraged to predict the response of cancer patients to specific treatments, guiding the development of personalized therapeutic strategies for improved outcomes. Monitoring changes in MIAT expression over time could serve as a valuable tool in tracking the progression of cancer. This longitudinal approach may provide insights into the evolving molecular landscape of tumors and help gauge treatment responses or the emergence of resistance [121].

Collectively, MIAT has immense potential in the clinical management of HCC, including as a non-invasive biomarker for early detection and prognosis, a therapeutic target, and a predictor of therapeutic response. However, further detailed studies and clinical trials are required to validate these applications of MIAT in HCC.

8. Conclusions and future perspectives

While the role of lncRNA MIAT is becoming increasingly apparent in HCC, there are some limitations in the current research. Firstly, most of the studies till now have utilized in vitro cell models, and human trials are lacking. Hence, the translation of these findings into clinical practice requires caution and remains a significant challenge.

Secondly, there is still a lot to be understood about the complex, multi-layered regulatory mechanisms of lncRNA MIAT in HCC. Much of the existing research provides evidence on a molecular level, but the comprehensive picture of physiological and pathological conditions remains incomplete. Another aspect that must be considered is that lncRNA MIAT might operate differently depending on the cellular context, which needs to be further investigated.

In terms of future directions, researchers need to focus on elucidating more detailed mechanisms by which MIAT regulates hepatocellular carcinoma progression. Also, more clinical studies are necessary to establish the potential of MIAT as a diagnostic marker or even a therapeutic target. Furthermore, considering the involvement of MIAT with other diseases like myocardial infarction and diabetic retinopathy, studying its systemic influence could provide profound insight and potentially higher clinical relevance.

In conclusion, while there is promising potential for the role of lncRNA MIAT in HCC research, it is important to acknowledge the limitations and challenges in the current state and to continue striving for a more detailed and comprehensive understanding.

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Declaration of competing interest

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CRediT authorship contribution statement

Rawan Amr Elmasri: Writing – original draft, Methodology, Investigation, Data curation. Alaa A. Rashwan: Writing – original draft, Methodology, Data curation. Sarah Hany Gaber: Visualization, Methodology, Investigation. Monica Mosaad Rostom: Writing – review & editing, Validation, Investigation, Formal analysis. Paraskevi Karousi: Data curation, Writing – original draft, Writing – review & editing. Montaser Bellah Yasser: Data curation, Formal analysis, Methodology, Software. Christos K. Kontos: Writing – review & editing, Validation, Supervision, Investigation, Formal analysis. Rana A. Youness: Writing – review & editing, Writing – original draft, Visualization, Validation, Supervision, Project administration, Methodology, Investigation, Formal analysis, Data curation, Conceptualization.