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.

Full text

Non-coding RNA Research 9 (2024) 547–559
Available online 11 January 2024
2468-0540/© 2024 The Authors. Publishing services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd. This is an open access article under the CC
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Puzzling out the role of MIAT LncRNA in hepatocellular carcinoma
Rawan Amr Elmasri
a
, Alaa A. Rashwan
a
,
b
, Sarah Hany Gaber
a
, Monica Mosaad Rostom
c
,
Paraskevi Karousi
d
, Montaser Bellah Yasser
e
, Christos K. Kontos
d
, Rana A. Youness
a
,
*
a
Molecular Genetics Research Team (MGRT), Biology and Biochemistry Department, Faculty of Biotechnology, German International University (GIU), New
Administrative Capital, 11835, Cairo, Egypt
b
Biotechnology Graduate Program, School of Sciences and Engineering, The American University in Cairo (AUC), 11835, Cairo, Egypt
c
Pharmacology and Toxicology Department, Faculty of Pharmacy and Biotechnology, German University in Cairo (GUC), 11835, Cairo, Egypt
d
Department of Biochemistry and Molecular Biology, Faculty of Biology, National and Kapodistrian University of Athens, Panepistimiopolis, 15701, Athens, Greece
e
Bioinformatics Group, Center for Informatics Sciences (CIS), School of Information Technology and Computer Science (ITCS), Nile University, Giza, Egypt
ARTICLE INFO
Keywords:
Long non-coding RNA (lncRNA)
Myocardial infarction associated transcript
(MIAT)
Liver cancer
Metastasis
microRNA (miRNA)
Theranostics
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 signicant 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.
1. Introduction
Following the completion of “The Human Genome Project” in 2003,
the classication of the genome and its elements has been a challenge
and the focus of all molecular scientists [1,2]. One of the broad classi-
cations 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]. Surpris-
ingly, 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 [10–14]. Members of this class
have transcripts larger than 200 nucleotides and are important regula-
tors [15,16]. LncRNAs can also be divided into subclasses [17,18]. Ac-
cording to one of these classications, the genomic location of ncRNAs
can result in intergenic, intronic, sense, and antisense lncRNAs [9,19,
20], as shown in Fig. 1.
2. Roles and functions of lncRNAs
Alternatively, lncRNAs can be classied according to their functional
role [17]. As already indicated, lncRNAs have a signicant regulatory
function, modulating the activity of genes, RNAs, proteins, organelles,
and nuclear condensates [21,22]. More specically, lncRNA functions
include one or more of the following: chromatin remodeling, histone
modication, 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 modications exerted by
direct protein-binding, miRNA sponging, and mRNA stabilization.
* Corresponding author. Molecular Genetics Research Team (MGRT), Biology and Biochemistry Department, Faculty of Biotechnology, German International
University (GIU), New Administrative Capital, 11835, Cairo, Egypt.
E-mail addresses: rana.youness@giu-uni.de, rana.youness21@gmail.com (R.A. Youness).
Contents lists available at ScienceDirect
Non-coding RNA Research
journal homepage: www.keaipublishing.com/en/journals/non-coding-rna-research
https://doi.org/10.1016/j.ncrna.2024.01.006
Received 29 October 2023; Received in revised form 31 December 2023; Accepted 9 January 2024

Non-coding RNA Research 9 (2024) 547–559
548
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 Specicity 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-specic 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-specic 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 Prolin 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
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Additionally, lncRNAs may affect mitochondrial function, intercellular
exosomal transport, and cell regulation [12,20,23,24]. Table 1 lists
functional roles played by lncRNAs.
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 po-
tential 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 classies them
as theranostic agents with great potential in several malignant and
non-malignant contexts [12,14,40,41].
Specically, several lncRNAs have been characterized as non-
invasive biomarkers quantiable in liquid biopsies [42]. LncRNAs
show tissue-specic 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 uids,
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 func-
tions, and affecting disease states. These characteristics also raise the
possibility of employing non-oncogenic exosomal lncRNAs therapeuti-
cally for internalization and cell-specic effects after a disease mecha-
nism 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]. Simi-
larly, 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 [12,46–48]. Additionally, lncRNAs were demon-
strated 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 dis-
orders such as cardiovascular diseases [42,51,52].
4. LncRNAs in oncology
Focusing on the role of lncRNAs in cancer, several studies have
identied and correlated many lncRNAs to a diverse range of malig-
nancies. 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 signicant 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 tran-
script 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].
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 func-
tions of lncRNAs and their subsequent effect.
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 fulll 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.
SP1 Specicity 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 Modier-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-specic transcript
YAP1 Yes-associated protein 1
YBX1 Y-box binding protein 1
YWHAE Tyrosine 3-Monooxygenase/Tryptophan 5-
Monooxygenase Activation Protein Epsilon
ZEB1 Zinc nger E-box binding homeobox 1
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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 [80–83]. As indicated by its name, it is pre-
dicted that it has a role in cardiovascular diseases such as atheroscle-
rosis, and coronary artery diseases. However, it has been discovered that
not only does it inuence these diseases, but it also plays a key role in
several solid malignancies such as lung cancer, hepatocellular carci-
noma, 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 func-
tional 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 inammation (Fig. 4).
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.
R.A. Elmasri et al.

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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]. Further-
more, 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-1
α
axis [88].
Another study demonstrated a notable correlation between Rs1894720
in MIAT and paranoid schizophrenia within the Chinese Han population
[89].
Table 1
Molecular and functional roles of lncRNAs.
Molecular role Functional role References
Epigenetic regulation Chromatin remodeling [25]
Histone modication [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]
Table 2
Potential oncogenic and tumor-suppressive lncRNAs in several malignant contexts.
LncRNA Cancer Type Signaling pathway Expression
prole
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 Specicity 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 efux
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]
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6.2. MIAT-mRNA and MIAT-miRNA networks
Recent progress in high-throughput sequencing technologies has led
to the identication 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 classications 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 identied, 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 inte-
grate 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 identication of novel ncRNAs in different
species as well as providing GO (Gene ontology) annotations for miRNAs
and lncRNAs using RNAcentral identiers.
LncTarD is a lncRNA-specic 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 mole-
cules 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 in-
teractions using ENCORI, LncTarD, and LncRNA2Target databases, re-
sults 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 dis-
ease states as listed in Table 3, where tumor protein p53 (TP53),
transmembrane protein 147 (TMEM147), importin 7 (IPO7), mito-
chondrial carrier homolog 1 (MTCH1), LIM domain-binding protein 1
(LDB1), ubiquitin-like modier-activating enzyme 2 (UBA2), coronin-
like actin-binding protein 1C (CORO1C), IST1 factor associated with
ESCRT-III (IST1), and proline dehydrogenase 1 (PRODH) were high-
lighted in later annotation using gene ontology Fig. 4. Also, MIAT-
Fig. 2. Graphical representation of human tumors and related lncRNAs. Red labels indicate oncogenic lncRNAs, while green labels indicate tumor-
suppressive lncRNAs.
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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. More-
over, 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. 3. Chromosomal locations and Single Nucleotide Polymorphisms (SNPs) in MIAT. MIAT is located on chromosome 22, band q12.1. A simplied 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.
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
a
MIAT-mRNA and MIAT-miRNA interactions across multiple pathological
conditions using ENCORI, LncTarD, and LncRNA2Target databases. Results
were retrieved using search API tool identier for MIAT-related interaction on
the mentioned databases.
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(Fig. 5), which explains the interconnection between all MIAT-related
genes and subsequent GO functions following construction using R
programming language (v. 4.0).
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.
Briey, 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 re-
veals 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 pro-
cess [97–103]. 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.
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 pro-
found 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 aatoxin are the drivers for
inammation–causing conditions that eventually cause HCC. Although
there are considerable scientic records for the causative reasons for the
pathogenesis of HCC, there is still a gap that needs to be lled 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, brosis, alcoholic
liver disease, and chronic hepatitis, are important precursors of HCC. A
recent study showed that elevated MIAT expression during liver brosis
is linked to increased hepatic stellate cell (HSC) proliferation and
collagen expression, while MIAT knockdown demonstrated a marked
suppression of brosis 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-
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.
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Non-coding RNA Research 9 (2024) 547–559
555
mesenchymal transition (EMT) process [104]. While the detailed func-
tion of MIAT in alcoholic liver disease and chronic hepatitis has not yet
been investigated, to the best of our knowledge, given its role in brosis
and cirrhosis there is potential for a similar inuential 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 inammation, brosis, 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 signicant 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.
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.
Specically, 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 his-
tone 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
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.
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Non-coding RNA Research 9 (2024) 547–559
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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 broblast 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, inltrating
the tumor microenvironment (TME), have an enormous impact in
stopping the tumor cells from proliferation, invasion, and dissemination
[115–117]. 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 im-
mune cells and mediators in HCC. Analyzing the TIMER database
showed a positive correlation between MIAT and immune cells: cyto-
toxic T lymphocytes, T helper cells, macrophages, dendritic cells, neu-
trophils, 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 signicant 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 tran-
scription 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
conrmed 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 signicantly
elevated after treatment of HCC cells with sorafenib. Hence, the resis-
tance 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 sup-
ported 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].
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.
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Non-coding RNA Research 9 (2024) 547–559
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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 specic 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 specic lncRNAs.
Additionally, given the deregulation of MIAT in HCC cell lines upon
sorafenib treatment, MIAT expression levels could be leveraged to pre-
dict the response of cancer patients to specic treatments, guiding the
development of personalized therapeutic strategies for improved out-
comes. 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 resis-
tance [121].
Collectively, MIAT has immense potential in the clinical manage-
ment 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 ndings into clinical practice
requires caution and remains a signicant 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 re-
mains 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 thera-
peutic target. Furthermore, considering the involvement of MIAT with
other diseases like myocardial infarction and diabetic retinopathy,
studying its systemic inuence 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.
Ethics approval and consent to participate
Not applicable.
Consent for publication
Not applicable.
Availability of data and material
Not applicable.
Funding
Not applicable.
Declaration of competing interest
None.
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, Meth-
odology, 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.
Acknowledgements
Not applicable.
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