Introduction
Hepatic diseases, along with their complications
such as cirrhosis and liver cancer, contribute significantly to
mortality, morbidity and healthcare costs. According to data
released by the World Health Organization, the global burden of
hepatic diseases is substantial and continues to increase (1). Each year, hepatic disease
contributes to ~2 million deaths, accounting for 4% of total
mortality. Most deaths are attributable to cirrhosis or
hepatocellular carcinoma (HCC), whereas acute hepatitis accounts
for a smaller fraction. Globally, cirrhosis most frequently arises
from viral hepatitis, alcohol abuse and non-alcoholic fatty liver
disease (NAFLD) (2). However,
addressing liver diseases is fraught with challenges because of the
shortage of specific diagnostic markers and effective therapeutic
targets, which result in inadequate access to diagnostic
investigations and treatments (3). Although recognized biomarkers such
as galectin-3 have been proposed as diagnostic and therapeutic
targets for liver diseases, their sensitivity and specificity in
early detection are limited, high-lighting the necessity of
developing novel molecular indicators to address this urgent need
(4). Therefore, identifying more
specific markers is essential to enhance the diagnosis and
treatment of hepatic diseases.
Among the various influencing factors, transfer RNA
(tRNA)-derived small RNA (tsRNA) plays a vital role in the
pathogenesis of hepatic diseases. The existence of tRNA in all
living organisms has established its status as one of the most
necessary and classic RNA types in nature (5). However, its functions are not
limited to classical roles, existing research shows that tRNA can
perform multiple non-classical functions either by itself or in the
form of small fragments produced by specific cleavage (6). tsRNA generated from specific
cleavage sites of tRNA/precursor tRNA is gradually growing into an
important active category among small non-coding RNAs (sncRNAs)
(7). With the increasing
diversity of non-coding RNA types, machine learning-based
classification tools that utilize intrinsic sequence features have
emerged to facilitate transcriptome annotation across various
species (8). A series of
evidence no longer regards tsRNA as the product of tRNA
degradation. They not only participate in transcription,
translation and post-transcriptional regulation, but also widely
influence cell type specialization during development by regulating
cell proliferation, growth and metabolism (9). At the pathological level,
abnormalities of tsRNAs are associated with diseases such as
diabetes (10), infections
(11) and cancer (12). It is worth noting that epigenetic
transcriptome modifications profoundly affect the function of
non-coding RNA by regulating their processing, stability and
subcellular localization (13).
tsRNAs inherit a wide range of post-transcriptional modifications
from their parent tRNA, including m5C, m1A,
and pseudo-uridine. These modifications not only protect tRNA from
nuclease cleavage but also determine the biogenesis, half-life and
target binding ability of tsRNAs. Therefore, this regulatory layer
adds a crucial dimension to our understanding of the gene
regulation mediated by tsRNAs in liver diseases.
The present review conducts a comprehensive
examination of tsRNAs, covering their discovery, classification,
biogenesis, detection methods, biological functions, and their
regulatory roles in the gut-liver axis. The biogenesis and
molecular functions of tsRNAs in hepatocytes are the primary focus
of the present review. Their potential for clinical application was
also highlighted, specifically in diagnosing, prognosticating, and
treating hepatic diseases. Finally, current obstacles in tsRNA
research were examined and future directions were discussed, with
particular emphasis on liver diseases.
Biology of tsRNAs
Classification and nomenclature of
tsRNAs
tRNA-derived small RNAs (tsRNAs) are a newly
identified class of functional sncRNAs (14). The biogenesis of these molecules
involves site-specific cleavage of either precursor tRNAs
(pre-tRNAs) or mature tRNAs (14,15). Pre-tRNAs, which are transcribed
by RNA polymerase III, possess a 5′ leader sequence and a 3′ tail
sequence. The 5′ leader is excised by the ribonucleoprotein enzyme
RNase P, while RNase Z cleaves the 3′ tail at the first unpaired
base adjacent to the 3′ end of the tRNA (16). Following this cleavage, tRNA
nucleotidyl transferase adds a non-templated cholangiocarcinoma
(CCA) sequence to the 3′ end of the mature tRNA (7,17). Typically, mature tRNAs are
composed of 70-90 nucleotides (nt). They assume a cloverleaf-like
secondary structure featuring four loops: the dihydrouracil
(D-loop), anticodon loop, variable loop and pseudo-uridine (TψC)
loop (18).
The cleavage sites within pre-tRNAs or mature tRNAs
serve as the basis for classifying tsRNAs into two main categories.
The first is tRNA-derived fragments (tRFs), which are 14-30 nt in
length. The second is tRNA halves (30-50 nt), which are also called
tRNA-derived stress-induced RNAs (tiRNAs) because they are
generated in response to stress (7,19-22). Stress-induced tiRNAs arise from
the selective cleavage of the anticodon loop within mature tRNAs.
This cleavage is carried out by various endonucleases, including
angiogenin (ANG) (21), RNase L
in vertebrates, Rny1 in yeast, and other enzymes not yet identified
(7). Typical stressors that
trigger tiRNA production include thermal shock, hypoxia and viral
infection (23). Based on their
sequence composition, tiRNAs are subdivided into 5′-tiRNAs
(spanning the 5′ end to the anticodon, including the D-loop) and
3′-tiRNAs (extending from the anticodon to the 3′ end, encompassing
the TψC loop) (24).
tRFs are ncRNAs that arise from mature or pre-tRNAs,
generally 14-30 nt in length. Depending on the position of the
cleavage site on either pre-tRNA or tRNA, tdFs are classified into
tRF-5, tRF-3, tRF-2, tRF-1, internal tRF (i-tRFs) and other tRFs
(25). tRF-5 molecules start at
the 5′-end of the tRNA and stop at either the D-loop or the
anticodon loop, and are subsequently categorized according to
length as tRF-5a (14-16 nt), tRF-5b (22-24 nt), or tRF-5c (28-30
nt). tRF-3 molecules, on the other hand, run from the 3′-end to the
T loop of mature tRNAs and are further separated into tRF-3a and
tRF-3b based on size (18 or 22 nt) (22,26). The tRF-2 subclass is produced
when enzymes cleave the anticodon loop, leaving the 5′ and 3′
terminal regions intact while preserving both the anticodon loop
and part of the anticodon stem (27). The tRF-1 subclass arises from
cleavage of the pre-tRNA's 3′ terminus by RNase Z or ELAC2.
Pre-tRNAs carry a 3′ tail composed of a poly-U sequence, which
corresponds to the RNA polymerase III termination signal (28). The i-tRFs, previously referred to
as tsRNA-2s, represent a heterogeneous collection of tsRNAs that
originate from the anticodon stem-loop region of mature tRNAs
(29). Furthermore, i-tRFs can
be classified into A-tRF, D-tRF, and V-tRF according to their
cleavage initiation sites (15).
Minor unannotated subgroups of tsRNAs have also been reported, but
their biological roles and classification remain to be further
clarified (30) (Fig. 1).
Early studies named these RNA fragments according to
their position of origin, including 5′-tRF, 3′-tRF, 5′-tRNA half,
and 3′-tRNA halves. In the present review, a clear grouping method
was used that assigns fragments to five classes (tRF-5, tRF-3,
tRF-2, tRF-1 and i-tRF) by where the RNA is cleaved. Different
databases use different naming systems. For example, tRFdb uses
names like tRF-3001b. MINTbase uses names like tRF-23-R9J89O9N9.
tsRBase uses names such as hsa_tsr014055. However, functional
studies often name fragments based on the parent tRNA. Examples are
tRF-Gln-CTG-026 and 5′-tsRNA-Gly-GCC. As a result, one fragment can
have multiple names. tRF-34, for instance, is the same fragment as
5′-tsRNA-Gly-GCC. i-tRFs have also been called tsRNA-2s. In the
present review, tsRNAs are the authors' general term for all
tRNA-derived small RNAs. It matches the tsRNAs used by some
authors. When individual fragments were discussed, the name from
the original study was used and its group was marked from the
authors' scheme when it was first named (23,27).
Biogenesis and regulation of tsRNAs
Specific nucleases orchestrate the tightly regulated
biogenesis of tsRNAs, while tRNA modifications further modulate
this process. It takes place under conditions of physiological
homeostasis as well as in response to stress stimuli, such as
oxidative stress, heat shock, or nutrient deprivation (31-33). Mature tRNAs or precursor tRNAs
(pre-tRNAs) serve as primary substrates, with cleavage events
generating distinct tsRNA subtypes based on nuclease specificity
and cleavage sites. In the process of tiRNA generation,
angiopoietin (ANG) plays a key role as a ribonuclease in response
to stress. Under physiological conditions, ANG binds to
ribonuclease inhibitor 1 and is thus confined within the cell
nucleus. After the activation of the stress signal, ANG
translocates from the nucleus to the cytoplasm, where it
preferentially cleaves the anticodon loop region of mature tRNA. It
shows a significant preference for the purine-pyrimidine
dinucleotide site (cleaving efficiency is CpA > CpG > UpA
> UpG in sequence). In addition, ANG can occasionally generate
short-chain tRF-5s (34-36).
In addition to its well-known role in miRNA
processing, Dicer is also involved in generating shorter (14-30 nt)
tRNA-derived fragments. By cleaving specific structural loops on
the pre-tRNA precursors, Dicer can generate subtypes such as
tRF-5a, tRF-5b, tRF-3a and tRF-3b. However, the degree of
dependence of different tRF types on Dicer varies, and the
generation of some tRFs does not require Dicer, which reveals the
complexity of the related pathways (37,38). By contrast, the processing of the
precursor tRNA is specifically carried out by RNase Z/ELAC2, which
removes the 3′ trailer sequence containing the RNA polymerase
III-dependent poly (U) termination signal, generating tRF-1s during
the classical tRNA maturation process (39,40). In lower eukaryotes such as yeast,
members of the RNase T2 family (such as Rny1) can cleave the
anticodon loop of mature tRNA under oxidative stress conditions to
produce tiRNAs in an ANG-independent manner, thereby complementing
the function of ANG (33).
Crucially, tRNA modifications play a central role by
regulating the production process of tsRNA. Methyltransferases such
as NSun2 and DNMT2 can catalyze cytosine-5 methylation (m5C) at
specific positions of tRNA (for example, NSun2 acts on C48/49/50,
and DNMT2 acts on C38). This modification can protect tRNA from
nuclease cleavage, thereby inhibiting the excessive generation of
tsRNA. Conversely, once these modifications are absent, the
sensitivity of tRNA to ANG or Dicer increases accordingly, which in
turn leads to abnormal accumulation of tiRNA or tRF (41-43). This indicates that the
nuclease-driven cleavage event and the modifiers-mediated
regulatory mechanism jointly determine the compositional
characteristics of tsRNA, leading to the generation of subtypes
with distinct functions that participate in various downstream
cellular processes.
Distinctions and crosstalk with other
non-coding RNAs
With the continuous improvement of next-generation
sequencing technology, an increasing number of small RNA types with
unique functions have been identified, among which tRNA-derived
fragments have become one of the core research fields (44). Although tsRNAs share certain
common features with other sncRNAs, including microRNAs (miRNAs or
miRs), they are unique in their biogenic pathways and regulatory
mechanisms, thus standing out among the non-coding RNA family.
Despite being of similar size and both being involved in
post-transcriptional regulation, their generation pathways and
functional mechanisms are significantly different. miRNAs are
usually transcribed from independent genes and processed by Drosha
and Dicer. tsRNAs are produced by cleavage from precursor or mature
tRNAs by enzymes such as ANG or Dicer under specific conditions,
particularly stress (36,45).
At the functional level, miRNAs mainly bind to Ago2 in the
Argonaute (Ago) protein family and inhibit target mRNA through
complementary seed sequence pairing. By contrast, tsRNAs tend to
bind to Ago1, Ago3 and Ago4, and can regulate gene expression
through non-classical pathways, such as replacing the RNA-binding
protein YBX1 or regulating translation initiation factors (24,46). Previous studies have suggested
that there is crosstalk between two types of molecules: tsRNAs can
compete with miRNAs for binding to Ago proteins, thereby affecting
the silencing efficiency mediated by miRNAs, but it does not
significantly change the abundance of miRNAs (47). These differences highlight the
independent yet associated roles of tsRNAs and miRNAs in the ncRNA
regulatory network.
In addition to miRNAs, tsRNAs can also functionally
interact with various types of non-coding RNAs, including
PIWI-interacting RNAs (piRNAs), long non-coding RNAs (lncRNAs) and
circular RNAs (circRNAs). These RNAs each have their own
characteristics in biosynthesis and regulatory mechanisms (48). Among them, piRNAs are 23-32 nt in
length and are mainly expressed in germline cells, exerting
transposon silencing and genomic stability maintenance functions
through the PIWI protein family (49,50). PiRNAs are processed from long
single-stranded precursors, and their 3′ ends undergo
2′-O-methylation modification catalyzed by HENMT1. This
modification not only enhances their stability but also facilitates
PIWI loading. By contrast, tsRNAs are derived from tRNA and are
often induced to be generated under cellular stress conditions
(51,52). Although both tsRNAs and piRNAs
can bind to Ago family proteins (the former binds to AGO and the
latter to PIWI), their functional pathways are largely different.
Specifically, piRNAs mainly mediate transposon silencing at the
transcriptional and post-transcriptional levels within the
germline. By contrast, tsRNAs focus more on translation regulation
and stress response in somatic cells (53). At present, research on the direct
mechanistic crosstalk between the two remains insufficient.
However, in specific physiological scenarios (such as sperm
maturation and intergenerational inheritance), the two may converge
through sharing RNA-binding proteins or epigenetic regulatory
networks (43,54).
lncRNAs are defined as transcripts longer than 200
nt. This type of RNA can regulate gene expression through multiple
pathways, such as participating in chromatin remodeling, causing
transcriptional interference, and functioning as a molecular
scaffold (55). In addition,
certain lncRNAs can also act as competitive endogenous RNAs,
isolating miRNAs by binding to them, thereby altering the pool of
available miRNAs within cells and indirectly influencing the
regulatory network mediated by tsRNA (56). There is already evidence
suggesting that tsRNA may also reciprocally regulate the stability
or function of lncRNA through direct base-pairing or competing with
RNA-binding proteins. However, these mechanisms still need to be
further clarified (57).
CircRNAs owe their high stability and their capacity
to act as miRNA sponges, protein baits, or translation templates to
their covalently closed loop configuration. Previous studies have
confirmed that some circRNAs can interact with tsRNAs (58). For instance, circRNA-104075 can
adsorb tsRNA-0009, thereby weakening the inhibitory effect of
TsRNA-0009 on YBX1 and accelerating the progression of HCC
(59). In addition, due to the
lack of free terminals, circRNAs may tolerate exonuclease
degradation and may affect the half-life or subcellular
localization of tsRNA in specific cellular environments (60). However, the crosstalk mechanisms
among tsRNA-piRNA, tsRNA-lncRNA, and tsRNA-circRNA have largely
remained unexplored. In the future, integrating multi-omics methods
to map these interaction networks and assess their physiological
correlations in development and disease is an urgent task in this
field.
Molecular functions of tsRNAs in
hepatocytes
tsRNAs are widely involved in various physiological
processes such as mRNA silencing, intercellular communication, gene
expression regulation, post-transcriptional modification, and the
balance between cell proliferation and death (61). Among the numerous molecular
events regulated by tsRNAs, translation control is the most
thoroughly studied process. A large amount of evidence indicates
that under various stimulating conditions, tsRNAs mainly inhibit
protein synthesis through different mechanisms (26). They can bind to ribosomes to
regulate the translation process. For instance, tsRNA-mediated
suppression of tiRNA-5s downregulates mitochondrial pyruvate
carrier 1 by inhibiting translation, thereby weakening
mitochondrial respiration (62).
The 5′ tRNA halves derived from tRNA-Pro specifically bind to 18S
rRNA and then directly bind to 80S ribosomes to suppress
translation (63). Furthermore,
the ψ-mTOG, a tsRNA modified by pseudo-uridine, can bind to PABPC1,
hindering the recruitment of PAIP1 and thereby selectively
inhibiting the translation of mRNAs containing the 5′ PES motif.
After the deletion of this tsRNA, global translation is enhanced,
cell differentiation is abnormal, and the long-term reconstruction
function is defective in HSPCs (64). Another study has shown that
tsRNA-1 (tRF-Gln-CTG-026) from tRNA-Gln-CTG inhibits global protein
synthesis in mice, likely by weakening the interaction between the
pre-rRNA processing protein TSR1 and the pre-40S ribosomal subunit
(65). Notably, tsRNAs can also
enhance translation, indicating that they have functional diversity
in translation regulation. For example, a 22-nt tsRNA-3 originating
from tRNA-Leu-CAG was shown to bind mRNAs that encode ribosomal
proteins, including RPS28 and RPS15, thereby promoting their
translation and subsequently increasing ribosome biogenesis
(66). Follow-up investigations
further revealed that two specific 5′tRNA halves, namely
5′-tiRNA-Pro-CGG-1 and 5-tiRNA-Cys-GCA-27, enhanced cap-dependent
translation in granulocyte-monocyte progenitors (67). However, the molecular bases of
these effects were not investigated.
Apart from their functions in translation control,
tsRNAs also participate in transcriptional and post-transcriptional
gene regulation. One investigation demonstrated that 5′
tRFGlu/CTC and 5′ tRFGly/GCC interact with
their own DNA templates, forming R-loop structures that prevent the
generation of tRNA-DNA hybrids. This, in turn, promotes the
transcription of the genes encoding 5′ tRFGlu/CTC and 5′
tRFGly/GCC (68).
Subsequent research revealed that 5 tRFCys, a member of
the 5′ tRNA half family, facilitates the oligomerization of
Nucleolin along with its associated metabolic transcripts Mthfd1l
and Pafah1b1. This process leads to the assembly of a higher-order
ribonucleoprotein complex that stabilizes these transcripts,
thereby protecting them from exonucleolytic degradation (69). In fact, besides its roles in
modulating transcription, tsRNA also exhibits a regulatory function
in the process of reverse transcription. Of interest, tRFs can be
detected in cells infected with HTLV-1. One such fragment,
tRF-3019, was identified in virus particles and demonstrated the
capacity to initiate HTLV-1 reverse transcription (70).
Similar to miRNAs, tsRNAs facilitate gene silencing
via assembly of the RNA-induced silencing complex, resulting in
post-transcriptional gene suppression (22). Additionally, dicer-dependent
tsRNAs mediate nascent RNA silencing by guiding Ago2 cleavage
toward introns of nascent transcripts (38). Multiple tsRNA types, tRF-1s,
tRF-3s and tRF-5s, can bind AGO1-4 (71). Upon loading onto AGO proteins,
which are core RISC components, tsRNAs direct the degradation of
sequence-matched targets (38,72). One illustrative study by Green
et al (73) showed that
IL-1β stimulation of chondrocytes triggers tRNA-Cys-GCA cleavage
and elevates tRF-3003a production. This tRF binds the AGO2/GW182
complex to assemble AGO-RISC, which then targets the JAK3 mRNA
3′-untranslated region (UTR), thereby silencing JAK3 and
downregulating IL-6 via inhibition of the JAK/STAT pro-inflammatory
axis (73). A parallel mechanism
operates in OA anterior cruciate ligament cells, where tRF365
silences IKBKB through 3′-UTR targeting, as verified by dual
luciferase reporter assays (74). However, only a limited number of
tsRNAs combined with AGO have been identified, and numerous tsRNAs
exhibit weak interactions with AGO proteins (19). Therefore, the specific molecular
mechanisms underlying the function of tsRNAs within hepatocytes
remain elusive (Fig. 1).
tsRNAs in the pathogenesis of hepatic
diseases
Altered expression levels of tsRNAs have been
observed across a wide range of hepatic diseases, suggesting their
potential utility as both diagnostic markers and therapeutic
targets. The present review consolidates recent progress in
understanding the role of tsRNAs in various liver pathologies,
while also examining the experimental approaches employed in
tsRNA-related studies. Furthermore, it highlights the current
limitations in existing research, with particular emphasis on
challenges in data mining (75).
Liver cancer
Globally, HCC remains one of the most frequently
diagnosed cancers and represents a major subtype of liver cancer.
With an age-adjusted worldwide incidence of 10.1 cases per 100,000
person-years, this malignancy ranks as the sixth most common
neoplasm and the third leading cause of cancer-related mortality
(76). In China, the incidence
and mortality rates reach 17.64 per 100,000 and 15.33 per 100,000,
respectively, indicating that HCC continues to pose a significant
public health burden for the Chinese population (77). Therefore, a thorough
clarification of the molecular mechanisms involved in the
occurrence and evolution of HCC is expected to provide support for
early diagnosis and promote the discovery of new therapeutic
targets.
tsRNA has been confirmed to be widely involved in
the occurrence and evolution of various tumors. With the
development of RNA sequencing technology, its expression profile
and potential functions in cancer cells have been deeply analyzed.
Existing studies have shown that abnormal expression of tsRNA
exists in various tumors (27,78), especially in liver cancer
tissues, where its expression pattern is significantly different
from that of normal liver tissues (15). Moreover, tsRNAs can exist stably
in abundant body fluids such as blood, serum and urine in a free
form or encapsulated in extracellular vesicles (EVs), thereby
participating in intercellular communication in the tumor
microenvironment (TME) (15).
This type of abnormally regulated tsRNA plays a key role in
cancer-related biological processes. Previous study focuses on its
function in promoting the proliferation and invasion of liver
cancer cells.
One of the fundamental characteristics of cancer is
the continuous proliferation and uncontrolled growth of cells, a
process involving multiple genes and proteins, especially certain
kinases and their receptors (79). After transfection with the
Gly-tRF mimic, the mRNA level of Nedd4 family interacting protein 2
(NDFIP2) decreased. NDFIP2 is an activator of the Nedd4 family E3
ubiquitin ligases (80). Gly-tRF
is highly expressed in HCC cell lines and tumor tissues and can
promote the migration of HCC cells and epithelial-mesenchymal
transition. Mechanistically, Gly-tRF inhibited the mRNA expression
of NDFIP2 by directly binding to the 3′UTR of NDFIP2 and
subsequently activated the AKT signaling pathway to accelerate the
progression of HCC (81).
Although numerous literatures have associated tsRNA with the
proliferation of liver cancer cells, its downstream signaling
pathways have long been unclear. For instance, LeuCAG3′tsRNA, which
is critical for cell viability, has been demonstrated to promote
the growth of HCC (66). With
the development of molecular biology techniques, these pathways
have gradually been clarified. A recent investigation has shown
that a type of 5′-tsRNA-Gley-GCC (tRF-34) is upregulated in both
HCC tissues and cell lines. The mechanism is to target the 3′-UTR
of DAB2IP and downregulate its expression, thereby activating the
MEK/ERK signaling axis and enhancing the secretion of VEGFA by HCC
cells to the culture supernatant (82). Similarly, another 5′-tsRNA,
namely 5′tRF-Gly, can also promote the progression of HCC. It
exerts an oncogenic effect through direct interaction with
carcinoembryonic antigen-related cell adhesion molecule 1
(CEACAM-1), thereby promoting disease progression (83). In addition to its known function
of targeting nuclear genes, tsRNA can also drive the progression of
HCC by regulating mitochondrial genes. For instance,
hypoxia-induced tRF-3Thr−CGT has been reported to target
human mitochondrial peptide deformylase, leading to mitochondrial
energy metabolism remodeling and enhancing the migration and
invasion abilities of HCC cells (84). It is worth noting that tsRNAs are
implicated in both tumor-promoting and tumor-suppressing
activities. HCETSR, a specific tRF that is significantly
downregulated in HCC, shows a strong correlation with advanced
tumor burden and increased HCC mortality. Mechanistically, HCETSR
disrupts the interaction between SPTBN1 and the membrane-associated
catenin complex (β-catenin, α-catenin and P120-catenin) by binding
to SPTBN1, which in turn facilitates nuclear translocation of the
complex. Moreover, HCETSR exerts a dual effect on β-catenin
homeostasis: It stabilizes the protein by inhibiting proteasomal
degradation while simultaneously reducing nascent β-catenin
synthesis (85). Furthermore, Wu
et al (86) has proved
that 5′-tiRNA-Gln interacts with EIF4A1 to reduce related mRNA
binding through the intramolecular G-quadruplex structure, and this
process partially inhibits translation and HCC progression.
As a key immune interface, the liver employs its
resident non-parenchymal cells (that is, Kupffer cells, liver
sinusoidal endothelial cells and hepatic stellate cells) as primary
sentinels for translocated molecular products (87). Consequently, investigating how
tsRNAs interact with liver immune cells has become a key avenue for
research into HCC pathogenesis. In patients undergoing hepatectomy
for HCC, NK cell cytotoxicity is markedly impaired, a condition
that strongly correlates with post-resection HCC recurrence and
poor prognosis (88).
Encouragingly, related study revealed that tRF5-GlyGCC interacts
with KDM6B to epigenetically upregulate Runx2, which in turn
transcriptionally activates ITGBL1 and S100A9 expression in HCC
cells. This cascade directly reduces NK cell cytotoxicity while
also attracting myeloid-derived suppressor cells to inhibit NK cell
function, thereby promoting HCC progression (89). Furthermore, a recent
investigation demonstrated that migrasomes enriched with
tsRNA-10105 contribute to an immunosuppressive microenvironment in
HCC by inducing M2 macrophage polarization. These migrasome-induced
M2 macrophages can promote the proliferation and metastasis of HCC
(90). However, the molecular
interaction mechanism between tsRNA and liver immune cells remains
unclear, which restricts the overall understanding of the
regulatory network for the pathogenesis of HCC. Therefore, future
research urgently needs to focus on the functional role and
mechanism of action of tsRNA in liver immune cells, which will be
an important direction for in-depth analysis of the pathogenesis of
liver cancer (Fig. 2).
 | Figure 2Oncogenic and tumor-suppressive
tsRNAs orchestrate the TME in HCC. The different roles of oncogenic
and tumor-suppressive tsRNAs regulating HCC progression and
immunity are presented. The oncogenic tRNA-derived fragments found
inside cancer cells (including Gly-tRF, tRF-34, 5′-tRF-Gly and
tRF-3Thr-CGT) activate tumor signaling pathways such as
NDFIP2/AKT, DAB2IP/MEK/ERK and CEACAM1, and promote mitochondrial
metabolic reprogramming to drive HCC progression. Tumor-suppressive
tsRNAs (including HCETSR and 5′-tiRNA-Gln) can induce the
depolymerization of the Catenin complex by down-regulating SPTBN1
and EIF4A1, thereby blocking the translation of oncogenic proteins.
HCC-derived tsRNAs-10105 can drive the polarization of M2-type
macrophages and simultaneously inhibit the cytotoxic activity of NK
cells, thereby reshaping the tumor microenvironment. Meanwhile,
oncogenic tRF5-GlyGCC can further weaken the anti-tumor immune
response by upregulating Runx2 and inducing ITGBL1 and S100A9
expression. This figure comprehensively presents the intrinsic
correlation between tsRNA expression imbalance, metabolic
reprogramming, and immune escape in HCC. TME, tumor
microenvironment; HCC, hepatocellular carcinoma; tsRNA, transfer
RNA-derived RNA; CEACAM, carcinoembryonic antigen-related cell
adhesion molecule. |
Metabolic dysfunction-associated
steatotic liver disease (MASLD)
In recent years, with the continuous increase in the
burden of metabolic diseases, the prevalence of MASLD has also
risen significantly. MASLD covers a continuous disease spectrum
ranging from simple fatty liver, metabolic dysfunction-related
steatohepatitis, to liver cirrhosis and even HCC (91). As the main types, NAFLD and
non-alcoholic steatohepatitis (NASH) pose a serious threat to human
health and impose a heavy socio-economic burden. However, the exact
molecular mechanisms of both have not yet been fully elucidated.
Against this backdrop, tsRNAs offer a novel perspective for
understanding the pathological processes related to NAFLD.
The core pathological feature of NAFLD is the
excessive deposition of lipids in liver cells, which induces
chronic inflammation and promotes the progression of liver injury.
The imbalance of lipid metabolism homeostasis is the direct cause
of lipid accumulation in hepatocytes, and this process initiates
hepatic steatosis and the emergence of NAFLD (92). The advancement of NAFLD is
regulated by multiple factors, such as genetic background and
environmental factors (93).
Research has demonstrated that tsRNA-Glu-CTC plays a key role in
hepatocyte lipid metabolism. Mechanistically, this tsRNA
translocates into the nucleus and enhances the transcription of
Srebp2 by recognizing the E-box motif within its promoter
region. Furthermore, it directly binds to the nSREBP2 protein to
form a complex, jointly activating SREBP2 expression and
consequently upregulating the expression of genes related to liver
lipid synthesis. Unlike the common inhibitory regulation of miRNA,
this tsRNA exhibits typical transcriptional activation. Silencing
tsRNA-Glu-CTC can significantly alleviate diet-induced
hypercholesterolemia and atherosclerosis, suggesting that, as an
important activating molecule of SREBP2, it is the core regulatory
factor of lipid metabolism (94)
(Fig. 3).
 | Figure 3Schematic of tsRNA-related regulatory
mechanisms in MASLD. This figure illustrates the mechanism by which
tsRNAs promote MASLD pathogenesis through multiple pathways such as
regulating liver lipid metabolism, mediating inter-organ signal
communication, and participating in inflammatory responses under
metabolic stress. Among them, tsRNA-Glu-CTC can bind to the SREBF2
promoter and form a complex with nSREBP2, thereby promoting the
upregulation of SREBF2 expression and further activating downstream
lipid synthesis-related genes, ultimately leading to pathological
lipid accumulation in the liver. The tRF-Ser-GCT from adipocytes
promotes fat storage via the β2-adrenoceptor. Furthermore, it also
aggravates MASLD progression through inter-organ communication
between adipose tissues and livers. Additionally, tRF-3001b
inhibits autophagy by repressing Prkaa1, with autophagic
dysfunction accelerating disease onset, while TEC upregulates
tRF-47 to suppress pyroptosis, a key inflammatory pathway, and
protect against liver injury. The removal of Maf1 increases the
production of tsRNA from precursor tRNA and confers MASLD
resistance. It highlights the critical role of tsRNAs in the
development of MASLD and their potential as novel therapeutic
targets. tsRNA, transfer RNA-derived RNA; MASLD,
dysfunction-associated steatotic liver disease; TEC,
tectorigenin. |
In addition to the liver, the regulatory role of
tsRNAs in adipose tissue should not be ignored either, as adipose
metabolism is closely related to the occurrence and development of
NAFLD. The generation of tRF-Ser-GCT depends on the processing of
mitochondrial tRNASer-GCT by the ribonuclease P complex. Hsd17b10
is not only indispensable in this process but also participates in
maintaining the normal lipid metabolism of adipocytes. At the
mechanistic level, tRF-Ser-GCT directly targets the Adrenoceptor
Beta 2, a key regulator of metabolic homeostasis, and thereby
inhibits its expression. In vivo experiments further
confirmed that restoring the expression of tRF-Ser-GCT in
Hsd17b10-deficient mice could, to some extent, reverse the decline
in adipose tissue mass and the reduction in adipogenic gene
expression (95). Although
previous studies have identified a large number of tsRNAs involved
in fat deposition, most of these molecules still lack clear
regulatory mechanism analysis. These existing datasets have laid an
important foundation for in-depth clarification of the epigenetic
regulatory network of NAFLD (96) (Fig. 3).
Autophagy, as a key catabolic pathway within cells,
maintains cellular homeostasis by degrading and recycling damaged
organelles, misfolded proteins and biological macromolecules.
Impaired function of this process is regarded as one of the
important triggers for the development of NAFLD (97,98). During the process of NAFLD,
autophagy in the liver has a bidirectional regulatory effect. Its
protective functions of eliminating lipid droplets and alleviating
cellular stress constitute the primary defense line against liver
damage. Previous studies have shown that abnormal expression of
tsRNAs is closely related to the progression of NAFLD regulated by
autophagy. Distinct tsRNAs can influence the onset and severity of
the disease by altering autophagic activity. For example, tRF-3001b
directly binds to and suppresses Prkaa1 expression, with Prkaa1
being a critical gene involved in autophagy. Knockdown of tRF-3001b
markedly worsens NAFLD disease progression and lowers hepatic
triglyceride and cholesterol concentrations in NAFLD mouse models,
and the established autophagy inhibitor chloroquine can
dramatically abrogate the phenotypic effects induced by tRF-3001b
deficiency (99) (Fig. 3).
A separate study demonstrated that tectorigenin
(TEC) increases tRF-47 expression. Silencing of tRF-47 diminished
the protective actions of TEC against NASH in cell-based assays,
encompassing the blockade of autophagy, activation of pyroptosis,
and discharge of pro-inflammatory factors. Correspondingly, in
vivo suppression of tRF-47 promoted lipid-triggered liver
damage and lipid accumulation (100). Of note, emerging evidence
suggests that Maf1 knockout may enhance resistance to NAFLD via
regulation of tsRNAs and autophagy: Within the livers of
Maf1-deficient mice, precursor tRNA production is upregulated
(despite unaltered mature tRNA levels), indicating enhanced
precursor tRNA conversion into tsRNAs; in parallel,
autophagy-generated amino acids and spermidine concentrations are
also elevated (99,101) (Fig. 3).
In summary, tsRNA is deeply involved in the
pathological processes of MASLD and NASH by regulating four core
genetic programs: Lipid metabolism, apoptosis, inflammation and
fibrogenesis. This mechanistic understanding provides a new
opportunity for targeted intervention of tsRNA at the molecular
level in the treatment of the aforementioned diseases.
Additionally, tsRNAs can actively promote disease progression by
mediating signal communication among damaged liver cells, hepatic
stellate cells and immune cells, facilitating the transformation
from simple steatosis to steatohepatitis and fibrosis (102).
Alcoholic-associated liver disease
(ALD)
Multiple lines of evidence indicate that various
mediators such as the complement system, reactive oxygen species,
neutrophils, macrophages and lipopolysaccharides play a key role in
the pathogenesis of ALD (103).
Previous studies have found that the deficiency of complement
component 3 (C3) can alleviate ethanol-induced liver steatosis and
inflammatory response. Further mechanism studies revealed that C3
activation upregulates the expression of a glycine tRNA-derived
fragment (Gly-tRF) through its proteolytic fragments C3a and
C3a-des-Arg via a CYP2E1-dependent pathway. After forming a complex
with AGO3, the Gly-tRF can directly bind to the 3′-UTR of Sirtuin 1
(Sirt1), thereby inhibiting the expression of Sirt1. The
downregulation of Sirt1 disrupts the lipid homeostasis of the
liver, manifested as enhanced lipid synthesis and weakened fatty
acid β-oxidation, ultimately promoting hepato-steatosis.
Importantly, the C3-Gly-tRF-Sirt1 signaling axis has been verified
in human ALD tissue samples, suggesting its clinical translational
significance (104). In
addition to the complement system, the role of immune cells in ALD
is also worthy of attention. Recently, Wang et al (105) have observed that
C1Q+ macrophages may perform complex functions in ALD. A
large number of apoptotic neutrophils have been detected in the
liver of ALD, numerous of which are distributed adjacent to
macrophages, suggesting that there may be an interaction between
the two that affects the disease outcome (105) (Fig. 4). However, at present, the
understanding of the functions of tsRNA in immune cells of patients
with ALD remains relatively limited, and its specific molecular
targets are also unclear. In addition, the cross-regulatory
relationship between tsRNA and other known signaling pathways in
the pathogenesis of ALD, such as arrestin domain-containing protein
3 (106) and the
miR-155-5p/SIRT1/VDAC1 pathway (107), remains to be further clarified.
The aforementioned findings provide potential directions for
subsequent research.
Viral hepatitis
The key regulatory role of tsRNAs in the occurrence
of HCC related to viral hepatitis has been confirmed by existing
studies. Specifically, during the viral infection stage, the host
generates the tRF_U3_1 fragment derived from the pre-tRNA
3′-trailer. This fragment acts as a molecular bait, binding the RNA
chaperone La/SSB in the cytoplasm, resulting in a reduction in
La/SSB reserves in the nucleus, inhibiting the expression of viral
genes dependent on this protein, thereby forming an innate
antiviral defense barrier (108). By contrast, under the condition
of chronic hepatitis B virus (HBV) infection, proline tRNA-derived
tRF-3a-Pro is specifically elevated in HCC tissues and peripheral
circulation. It accelerates tumor proliferation by driving the G1/S
phase transition of the cell cycle and can be used as a highly
sensitive serum biomarker (109). The aforementioned findings
reveal the spatiotemporal dynamic characteristics of tsRNAs in
virus-host interactions and tumor evolution: They exert antiviral
response functions during the acute infection period and transform
into cancer-promoting factors in the chronic disease course stage.
Thus, the dynamic recombination of non-coding RNA networks during
the pathogenesis of liver diseases has obtained a novel explanatory
framework (110).
Role of tsRNA in interorgan transport
It was generally considered previously that RNA only
functions within the cells from which it originated. However, in
recent years, this understanding has undergone a fundamental shift;
multiple evidence has shown that ncRNAs can act on distant target
cells and participate in specific regulatory networks. This
transformation can be traced back to the key discovery in
2007-2008: Multiple research teams detected mRNA and miRNA in the
extracellular environment (111,112). Subsequent pioneering research
further confirmed that circulating miRNAs exist in the blood and
their expression patterns are disease-specific (113). These findings jointly reveal
that extracellular ncRNAs act as efficient regulatory factors for
inter-organ communication in various physiological and pathological
processes.
The anatomical and functional connection between the
gut and the liver constitutes the gut-liver axis, which has
significant clinical significance for disease pathogenesis. In this
two-way interaction, the gut microbiota community occupies a core
position. A healthy microbiome provides the host with a variety of
metabolic products through the portal vein, which not only helps
maintain intestinal homeostasis but also significantly regulates
liver function (114). Clinical
evidence shows that disorders of gut-liver communication are
associated with the occurrence of NAFLD, alcoholic liver disease,
and primary sclerosing cholangitis (115). The host and microorganisms have
formed complex interactions in co-evolution to maintain a delicate
balance. Increasing evidence indicates that, in addition to small
molecules, peptides and proteins, small regulatory non-coding RNAs
may also play an important role in cross-domain communication
(116). Among very small RNAs
(vsRNAs), tRFs such as Ile-tRF and Ala-tRF represent an important
biological type and are selectively enriched in outer membrane
vesicles (OMVs). These tRF-derived vsRNAs are thermodynamically
stable and usually contain at least two G-C base pairs and one
stem-loop structure. Bioinformatic analyses predicted that they
could target various human host mRNAs with different functions
(117). It has been previously
found that Escherichia coli produces a special vsRNA called
Ile-tRF-5X, which is selectively induced under environmental stress
conditions and is not affected by transcriptional or translational
inhibition. The tRNA fragment derived from this bacterium, after
being released through OMV, can be transferred to human HCT116
cells and upregulate the expression of MAP3K4 (118). Bacterial-derived tsRNAs can
regulate host cellular processes, while host-derived tsRNAs
inversely modulate the composition of gut microbiota and immune
responses. For example, Fusobacterium nucleatum (F.
nucleatum) can stimulate normal human oral keratinocytes to
release tsRNA-000794 and tsRNA-020498 through exosomes, both of
which inhibit the growth of F. nucleatum, likely by
interfering with protein synthesis. Streptococcus mitis
(S. mitis), a health-associated oral bacterium, is not
affected because its genome lacks sequences highly similar to these
tsRNAs (116). Similar
phenomena are also observed in tRF-His-GTG-1. The expression of
this tsRNA is elevated in peripheral blood mononuclear cells of
patients with systemic lupus erythematosus. It can directly bind to
TLR7/8 to activate the ERK/p38 signaling pathway, thereby inducing
the expression of PPARδ, promoting lipid droplet formation, and
enhancing the phosphorylation of ERK/p38 and the production of
IL-10. After inhibiting tRF-His-GTG-1, both lipid droplet
accumulation and IL-10-dependent pathways are suppressed, thereby
reducing the survival rate of Salmonella (119). These findings indicate that
host tRFs can influence intestinal inflammation and barrier
integrity by regulating the composition of gut microbiota, both of
which are key factors in the progression of liver diseases.
Host-derived tsRNAs can selectively inhibit the growth of pathogens
(such as F. nucleatum) but have no adverse effect on
symbiotic bacteria (such as S. mitis), suggesting that there
is a precise regulatory mechanism that helps maintain microbial
homeostasis. Therefore, tRF is not only a by-product of cellular
stress but also an active mediating factor in the host-microbe
co-evolution process. Disorder at this regulatory level may
accelerate the vicious cycle among impaired barrier function,
bacterial translocation and liver inflammation, thereby
exacerbating conditions such as MASLD (Fig. 5).
 | Figure 5Role of tsRNA in interorgan
transport. The roles of tsRNAs and related non-coding RNAs in
mediating inter-organ communication to drive hepatic disease
pathogenesis are illustrated, focusing on two key regulatory axes.
In the gut-liver axis, hepatic tsRNAs (tsRNA-000794, tsRNA-020498,
tRF-His-GTG-1) modulate gut microbiota (Fusobacterium
nucleatum, Salmonella) and immune mediators (IL-10),
while gut-derived Ile-tRF-5X, delivered via Escherichia coli
OMVs, activates MAPK signaling to promote hepatocyte proliferation.
In the cardio-hepatic axis, hepatocytes from metabolic MASLD
secrete miRNAs (miR-7 and miR-122) that target cardiomyocytes and
endothelial cells, upregulating NLRP3 and downregulating ARL2 to
induce heart failure with preserved ejection fraction (HFpEF).
Collectively, this diagram highlights tsRNAs as key mediators of
inter-organ crosstalk, linking gut and cardiac dysfunction to
hepatic disease progression. tsRNA, transfer RNA-derived RNA;
MASLD, dysfunction-associated steatotic liver disease; OMVs, outer
membrane vesicles; miR or miRNA, microRNA; SLE, systemic lupus
erythematosus. |
Non-coding RNAs also serve an important role in the
communication between the liver and the heart. The nanoscale EVs
secreted by steatosis hepatocytes are rich in specific miRNAs (for
example, miR-122) and proteins. These vesicles can be taken up by
myocardial cells after entering the circulation. Previous studies
have confirmed that EVs derived from fatty liver can directly
damage the mitochondrial function of myocardial cells and inhibit
key enzymes for energy production, ultimately leading to energy
metabolism disorders in the heart. Therefore, the damaged liver can
directly induce heart failure through intercellular substance
transport without relying on the classic blood glucose or lipid
metabolism pathways (120).
This RNA-mediated cross-kingdom communication extends the
understanding of the pathogenesis of liver diseases from the
metabolite and cytokine levels to epitranscriptomic regulation,
providing a potential new direction for RNA-targeted therapy
(Fig. 5).
Clinical potential of tsRNAs as
biomarkers
Diagnostic applications for tsRNAs
The rapid development of high-throughput sequencing
technology has revealed multiple biological functions of tsRNAs,
including their participation in gene expression regulation and
stress signal activation. Accumulating evidence indicates that
ncRNAs such as miRNAs, lncRNAs, tsRNAs and circRNAs (102) play a critical role in the
occurrence and progression of hepatic diseases. Furthermore, the
expression levels of tsRNAs show significant fluctuations during
the development of liver diseases (121). Consequently, tsRNAs are
regarded as potential biomarkers of human liver diseases (122).
Given the high heterogeneity of the clinical
manifestations of liver cancer, molecular markers are expected to
enhance its diagnostic and prognostic efficacy, especially the
tsRNA studies that have emerged in recent years, which have
provided a new perspective (122). In circulating blood,
tRNA-derived fragments can be protected from RNase degradation by
being encapsulated in vesicles or binding to extracellular RNA
carriers. Exosomes, as membranous nanovesicles released by normal
and pathological cells (123),
carry proteins, lipids, and various nucleic acids, and play a key
role in intercellular communication. Previous studies have
confirmed that exosomes are rich in sncRNAs, such as miRNAs,
lncRNAs and circRNAs, and can regulate the initiation and
progression of diseases through interaction with target cells.
Recent evidence further indicates that tsRNA is also highly
enriched in microvesicles and exosomes (14). Zhu et al (124) demonstrated that the levels of
four specific tsRNAs, namely tRNA-ValTAC-3, tRNA-GlyTCC-5,
tRNA-ValAAC-5 and tRNA-GluCTC-5, are significantly elevated in
plasma exosomes from individuals with HCC, suggesting their
potential utility as novel diagnostic markers for this malignancy,
pending validation in independent cohorts. In a parallel
observation, tsRNA-20 (derived from tRNA-Gly-CCC-1-1) and tsRNA-46
(derived from tRNA-Glu-CTC-1-1) exhibit specific differential
expression in the plasma EVs of patients with hepatitis B
virus-related liver failure. Notably, these tsRNAs were reported to
show 100% specificity and 94.80% sensitivity in distinguishing
patients from healthy individuals in that single cohort, although
such performance estimates require confirmation in larger,
multi-center studies (125).
Moreover, distinguishing between hepatocellular adenoma (HCA) and
HCC can be difficult. Nevertheless, an accurate diagnosis is
essential because the treatment and prognosis for these tumors
differ considerably. Thus, relevant diagnostic indicators are
urgently needed. Those identified in dogs may also have
translational value for human medicine, given the similarities
between human and canine HCA and HCC. Previous findings demonstrate
that tRNA-Val expression is markedly lower in HCC tumor tissue than
in HCA tumor tissue or normal liver tissue. A comparable pattern is
observed in plasma EVs and HCC cell lines relative to healthy
controls. These results suggest that tRNA-Val could serve as a
promising detection marker for distinguishing canine HCC from HCA
(126) (Table I).
 | Table IKey tsRNA biomarkers for hepatic
diseases. |
Table I
Key tsRNA biomarkers for hepatic
diseases.
| tsRNA subtype | Expression
pattern | Clinical
relevance |
|---|
| tRNA-ValTAC-3,
tRNA-GlyTCC-5, tRNA-ValAAC-5, tRNA-GluCTC-5 | Increase in
HCC | Herald their
utility as biomarkers for the diagnostic process of this
malignancy |
| tsRNA-20,
tsRNA-46 | Increase in
HBV-Related Acute-on-Chronic Liver Failure | Potential clinical
significance for the diagnosis and treatment of related hepatic
diseases |
| tRNA-Val | Decrease in HCC
tumor tissue | A promising novel
biomarker to distinguish canine HCC from HCA |
| hsa_tsr014055,
tRF-23-R9J89O9N9, tsRNA-Thr-5-0015, tRF-33-RZYQHQ9M739P0J | Increase in
HCC | Has potential
diagnostic value for HCC |
|
tsRNA-Asp-5-0002 | Decrease in
HCC | Is related to TNM
stage, differentiation, and lymph node metastasis |
|
tRF-Gln-TTG-006 | Increase in
HCC | Distinguish HCC
cases from healthy subjects even in the early stage |
| tRF-3a-Pro | Increase in
HBV-related HCC | Serve as a novel
biomarker for HBV-related HCC |
| mt-tRFs
tRHalve3-His-CAU and tRNAleader-Gln-UUG | Increase in
colorectal liver metastases | Specific biomarkers
for early detection, prognostication, and therapeutic targeting in
colorectal liver metastases |
|
tRF-34-JJ6RRNLIK898HR,
tRF-38-0668K87SERM492V, tRF-39-0668K87SERM492E2 | Decrease in
CCA | Serve as a novel
biomarker for CCA |
|
tRF-20-LE2WMK81 | Increase in
CCA | Serve as a novel
biomarker for CCA |
| tRF-Val-CAC-005,
tiRNA-His-GTG-001, tRF-Ala-CGC-006 | Increase in
MASLD | Elevated levels in
MASLD compared to non-MASLD; levels associated with MASLD activity
score |
However, most tRNA-derived fragments circulating in
the bloodstream are not encapsulated within EVs. Evidence suggests
that the majority of extracellular tRNA-derived fragments in serum
are instead associated with extra-vesicular components or bound to
ribonucleoproteins (127).
Recently, liquid biopsy targeting circulating nucleic acids has
gained significant attention in the field of early tumor screening.
Therefore, numerous specific tsRNAs with diagnostic value and
biological functions have been found. In HCC, elevated expression
levels have been observed for hsa_tsr014055 (128), tRF-23-R9J89O9N9 (129), tsRNA-Thr-5-0015 (130) and tRF-33-RZYQHQ9M739P0J
(131). Importantly, combining
these tsRNAs with alpha-fetoprotein (AFP), prothrombin induced by
vitamin K absence-II (PIVKA-II), and des-γ-carboxyprothrombin (DCP)
enhances diagnostic accuracy. Their prognostic value has been
evaluated using Kaplan-Meier curves (128-131). By contrast, tsRNA-Asp-5-0002 is
downregulated in HCC, and its reduced expression correlates with
TNM stage, tumor differentiation and lymph node metastasis.
Receiver operating characteristic (ROC) curve analysis has
suggested that tsRNA-Asp-5-0002 may have favorable diagnostic
performance for HCC in the studied cohort (132). Besides, Zhan et al
(133) has identified
tRF-Gln-TTG-006, which is significantly upregulated in HCC serum.
During the validation phase, it was found that the tRF-Gln-TTG-006
signature differentiated HCC patients from healthy individuals with
high sensitivity and specificity even at early disease stages; its
generalizability awaits external validation (133) (Table I). However, some limitations
should be considered despite these encouraging results. One is that
nearly all of the aforementioned signatures came from single
retrospective cohorts. Estimating accuracy in the same cohort used
for discovery is prone to overfitting. Therefore, current
guidelines require validation in independent patients before a
model can be considered clinically useful (134). The other limitation is that
most studies compared diagnosed patients with healthy controls.
This setup tends to enroll the most severe cases and the healthiest
controls. That inflates sensitivity and specificity compared with
real use (135). External
validation across multiple centers and populations is thus still
needed for each of the candidate tsRNAs described here. Circulating
tsRNA levels shift with age, sex, diet and circadian rhythm;
however, discovery cohorts remain small and single-center. Whether
a signature established in one population remains robust in
another, with different genetic backgrounds, lifestyles, or disease
etiologies, has rarely been tested. Systematic evaluation across
diverse cohorts is therefore essential before any tsRNA biomarker
can be considered generalizable.
Notably, tsRNAs can even elucidate the precise
etiological origins of HCC. For example, a previous study has
characterized the expression profile of tsRNAs in HBV-related HCC
and confirmed the diagnostic potential of serum tRF-3a-Pro. Data
from both animal models and cell-based assays have corroborated
that tRF-3a-Pro represents a candidate molecular marker for
identifying HBV-related HCC. This tsRNA is present at elevated
levels, and its diagnostic value needs confirmation beyond the
discovery cohort. In addition, integrating this candidate with the
conventional detection markers AFP led to enhanced diagnostic value
for this cancer type (109).
Equally important, other noteworthy molecules include the mt-tRFs
tRHalve3-His-CAU and tRNAleader-Gln-UUG, which are linked to an
improved prognosis, alongside the ge-tRF tRFmisc-Tyr-GTA, which
predicts worse clinical outcomes. These RNA fragments exhibit
stable but diverse expression profiles in tumor samples and still
have independent prognostic value after adjusting for clinical
confounding factors. Therefore, they are regarded as candidate
biomarkers, but their specificity and clinical utility require
further validation in independent populations (136). In the diagnosis of liver
cancer, tsRNA can also be applied to the detection of CCA. The
results of high-throughput RNA sequencing showed that, compared
with the adjacent normal tissues, the expression of a large amount
of tsRNA in CCA tissues presented abnormal changes. Among them, the
downregulation of tRF-34/tRF-38/tRF-39 and the upregulation of
tRF-20 were validated by reverse transcription-quantitative PCR
(RT-qPCR), and the differences reached a significant level. These
tsRNAs are enriched in key cancer-related signaling pathways such
as Notch, Hippo and cAMP, suggesting their functional importance in
the pathogenesis of CCA. The distinct expression profiles of these
tsRNAs in CCA tissues highlight their significant potential as a
non-invasive diagnostic marker and provide a promising direction
for improving the early detection and clinical management of this
highly aggressive malignant tumor (137) (Table I).
Apart from liver cancer, tsRNAs also play the role
of biomarkers in the diagnosis of other liver diseases. Dynamic
monitoring of ncRNA may help track the progression of diseases.
Similarly, the levels of tRF-Val-CAC-005, tiRNA-His-GTG-001 and
tRF-Ala-CGC-006 were upregulated in patients with MASLD with more
advanced fibrosis, suggesting that they may be used to assess the
risk of fibrosis progression (138). However, this speculation still
needs to be verified by subsequent studies. Existing reviews show
that research on tsRNA markers mainly focuses on liver cancer
(HCC), while their value in early-stage liver diseases such as
MASLD and liver fibrosis is rarely reported. Given that early
intervention is of decisive significance for the prognosis of liver
diseases, filling this gap should become a key direction for future
research. Furthermore, there is existing evidence indicating that
tsRNAs are closely related to the severity of liver diseases, which
is expected to provide a reference for the risk of disease
progression and thereby make up for the deficiencies of
conventional detection methods and existing markers. Therefore, one
of the main focuses of future research lies in screening for
diagnostic markers of tsRNAs with higher specificity from various
liquid biopsy sources.
Detection technologies for tsRNAs
In the exploration of non-invasive biomarkers,
tRNA-derived RNA has become a key breakthrough due to its
detectable and analyzable properties in body fluids. The
methodological framework of this field relies on two complementary
paradigms: High-throughput sequencing is used for unbiased
discovery, while targeted quantitative detection serves clinical
applications.
Although traditional small RNA sequencing was once
an important cornerstone of discovery research, the widespread RNA
modifications can block linker junctions and reverse transcription,
fundamentally undermine its accuracy and ultimately leading to
biased and incomplete modified tsRNA maps obtained. This limitation
is being addressed by a new generation of methods. PANDORA-seq
employs combinatorial enzymatic treatments to strip key RNA
modifications, thereby unveiling an abundant and previously hidden
landscape of specific tsRNAs and ribosomal RNA-derived small RNAs,
revolutionizing our view of the small RNA repertoire (139). Of note, the choice of
sequencing pipeline should be guided by the research objective.
PANDORA-seq is particularly suited to global characterization of
tsRNA repertoires in tissues and biofluids, as its sequential
enzymatic treatment removes RNA modifications and terminal
structures that otherwise preclude adaptor ligation and reverse
transcription, thus markedly improving the detection of highly
modified tsRNAs (140).
However, modification information is erased during enzymatic
treatment, and modified tsRNAs are over-represented relative to
conventional small RNA-seq, which precludes simultaneous
modification analysis. These features should be considered when
PANDORA-seq data are interpreted and different results across
pipelines are compared. Unlike PANDORA-seq, nanopore-based direct
RNA sequencing reads native RNA molecules directly, without reverse
transcription or amplification. RNA modifications are therefore
preserved and remain detectable in the raw current signal. Because
tsRNAs inherit the modifications of their parental tRNAs, the
capacity of this platform to quantify RNA abundance and
modification status in a single experiment is of particular
interest for tsRNA research. Recent methodological advances in
nanopore sequencing of tRNA populations have demonstrated the
feasibility of such integrated analysis (141). Nevertheless, several
limitations remain. Standard settings should exclude a large
fraction of short RNA reads and favor longer transcripts. And
reprocessing of raw signals is required to recover accurate
abundances (141). Moreover,
its high error rate and large input requirement remain practical
obstacles to routine clinical application, and the accuracy of
modification detection still depends heavily on computational
models (142). In particular,
the inability to efficiently capture molecules shorter than 100 nt
restricts its direct use for most tsRNAs (141). Mim-tRNAseq can complement the
aforementioned methods. Its principle lies in utilizing the
modification-induced misincorporation patterns to achieve
high-resolution quantitative analysis of the abundance and
modification status of tRNA, thereby demonstrating the significant
heterogeneity and modification interdependence in human cells.
However, this method also has several limitations that cannot be
ignored. The initial RNA amount needs to be no less than 0.5
µg, thus making it difficult to adapt to extremely low input
or single-cell samples. Some modifications cannot generate
identifiable misincorporation signals during the reverse
transcription stage. In addition, its detection targets are limited
to mature tRNAs, and the precursor tRNA-derived fragments are still
outside the coverage range (143). Overall, PANDORA-seq has the
strongest sensitivity in discovery; mim-tRNAseq is suitable for the
construction of quantitative modification maps of full-length tRNA,
while nanopore sequencing can maintain the native modification
information. The final technology selection should comprehensively
consider the availability of samples and whether there is a need
for modification analysis.
Through targeted strategies, the biomarker value of
tsRNAs has surpassed the basic discovery stage. The specific tsRNA
signatures have been verified in the early screening, prognosis
prediction and therapeutic effect monitoring of diffuse large
B-cell lymphoma and can be used for high-precision identification
of forensic body fluid sources, thus demonstrating practical
efficacy at the clinical and application levels (144,145). These technological advancements
not only broaden the detectable range of tsRNAs but also enhance
the resolution of RNA modification profiles, providing crucial
support for elucidating their biological functions and evaluating
their potential as biomarkers.
Although certain progress has been made in related
technologies, the detection and quantitative analysis of tsRNA in
body fluids still face multiple technical bottlenecks. One of the
core challenges lies in how to efficiently isolate EVs, which are
the main carriers of tsRNA in biological fluids. Previous studies
have shown that to obtain high-purity EV samples, the separation
process must be optimized, as different operation methods have a
significant impact on both EV yield and RNA composition (146). In the reported validation
studies of tsRNA biomarkers based on RT-qPCR, both diffuse large
B-cell lymphoma and forensic body fluid identification have been
used as typical application scenarios. However, such methods rely
on preset targets and are difficult to discover unknown types of
tsRNA, such as sequencing technology (144). In addition, tsRNA generally has
highly modified and fragmented characteristics, especially tsRNA
derived from mitochondrial tRNA, which further increases the
difficulty of accurate quantification and functional interpretation
(147). Although existing
detection techniques have significantly enhanced the detection
capacity of tsRNA, issues such as sample pretreatment, modification
preferences, and insufficient standardization remain key challenges
hindering tsRNA from becoming a reliable clinical biomarker.
Therapeutic strategies and translational
perspectives of tsRNAs
Given the significant therapeutic potential of
newly identified functional small RNAs in liver diseases, related
research is increasingly focusing on their specific roles in liver
diseases (122). Standard
treatments for end-stage liver disease which are surgical
resection, liver transplantation and standard pharmacological
treatment have a poor clinical outcome, damaging tissue and toxic
effects. Compared with traditional methods, RNA-based therapy, as
an advanced alternative, uses functional small RNAs as therapeutic
agents to alleviate pathological conditions and has been
increasingly pursued for managing hepatic diseases. The key
prerequisite for the success of this therapy lies in the
preparation of highly efficient, safe and highly targeted specific
functional RNA molecules.
In hepatic diseases, tsRNAs can exert therapeutic
effects by directly regulating pathological signaling pathways. As
a key regulatory factor of cellular stress response (6), this type of RNA is deeply involved
in core cellular events in liver injury and liver fibrosis, and
thus is regarded as a potential direct therapeutic target. When the
methyltransferase NSun2 is exhausted, cells produce
tRF-Gln-CTG-026. This molecule inhibits excessive overall protein
synthesis by blocking the binding between TSR1 and 18S rRNA,
thereby promoting the proliferation and survival of hepatocytes
after liver injury. These results support the feasibility of
tRF-Gln-CTG-026 as an RNA-based therapeutic agent for liver injury
intervention (65). In addition,
the tsRNAs regulated by NSun2 also significantly regulate the
capillarization of hepatic sinusoids. A recent study has found that
reduced NSun2 expression alters the functional profiles of
tRF-1-S25 and tRF-5-V31, which regulate sinusoidal capillarization
by targeting key proteins including DUSP1 and FAK (148). Importantly, systemic
administration of inhibitors directed against these tsRNAs rescues
liver fibrosis in mice, indicating that NSun2-dependent tRNA
modifications give rise to tsRNAs that suppress sinusoidal
capillarization. Thus, modulating the DUSP1/FAK/p-FAK axis
represents a novel therapeutic strategy for liver fibrosis
(148). In HCC, 5′-tiRNA-Gln
serves as a tumor suppressor by interacting with eukaryotic
initiation factor 4A1 (EIF4A1) through its G-quadruplex structure,
inhibiting its RNA unwinding function. This suppresses translation
of key oncoproteins ARAF, MEK1/2 and STAT3, thereby blocking
tumor-promoting pathways. As a result, the overexpression of
5′-tiRNA-Gln inhibits the proliferation, migration and invasion of
HCC cells. The expression significance of 5′-tiRNA-Gln in HCC was
found to be negatively related with both these oncoproteins in HCC
tissues thus indicating its therapeutic potential (86). Furthermore, 5′-tRF-GlyCCC, which
serves as the essential functional component of human bone marrow
mesenchymal stem cell-derived EVs (BMSC-EVs), directly binds to the
3′-UTR of FoxO3. This interaction leads to the downregulation of
gluconeogenic genes as well as lipogenic genes, leading to the
mediation of the anti-MAFLD effects of BMSC-EVs (149) (Table II).
| Table IIList of selected tsRNAs involved in
treating hepatic diseases with their molecular mechanism. |
Table II
List of selected tsRNAs involved in
treating hepatic diseases with their molecular mechanism.
| Authors, year | tsRNA subtype | Source | Delivery
system | Molecular/cellular
targets | Hepatic disease
indication | (Refs.) |
|---|
| Gonskikh et
al, 2020 |
tRF-Gln-CTG-026 | Loss of NSun2 | None | TSR1, 18S rRNA | Liver injury | (63) |
| Katopodi et
al, 2025 | tRF-1-S25,
tRF-5-V31 | Reduced NSun2
expression | None | DUSP1/FAK/p-FAK
signaling axis | Liver fibrosis | (142) |
| Qu et al,
2025 | 5′-tiRNA-Gln | Endogenous tumor
suppressor | None | EIF4A1
(G-quadruplex structure binding) | HCC | (84) |
| Rao et al,
2025 | tRF-3040b | Downregulated by
TEC | None | PINK1/PRKN-mediated
mitophagy | NASH | (144) |
| Li et al,
2026 | tRF-31R9J | Upregulated by
TEC | None | histone deacetylase
1, histone H3K18 lactylation/acetylation, pro-ferroptosis
genes | NASH | (145) |
| Cheng et al,
2022 | tRF5-GlyGCC | Endogenous
oncogenic tsRNA | Radiotherapy +
tRF5-Gi@HOP nanocomposite in situ hydrogel | KDM6B/Runx2/ITGBL
1/S100A9, NK cell cytotoxicity | HCC | (87) |
| Yang et al,
2024 | tsr-019759
(tRNAVal-AC-2-1) | Endogenous
oncogenic tsRNA | PEI-modified PLGA
nanoparticles coated with HCC CCM | Reciprocal
crosstalk between HCC cells and M2 TAMs | HCC | (146) |
Besides being direct therapeutic targets, tsRNAs
also act as key regulatory targets for natural bioactive compounds
in hepatic disease treatment. In NASH, the natural compound TEC
demonstrates therapeutic potential. On one hand, TEC mitigates
hepatocyte injury by downregulating tRF-3040b, which promotes
PINK1/PRKN-mediated mitophagy and subsequently inhibits the
GSDME/NLRP3 inflammasome-activated pyroptosis pathway, thereby
alleviating inflammatory damage (150). On the other hand, TEC
upregulates tRF-31R9J. This fragment directly binds to histone
deacetylase 1, reducing histone H3K18 lactylation and acetylation
levels, which in turn suppresses the transcriptional activation of
ferroptosis-promoting genes (ATF3, ATF4 and CHAC1) and ultimately
leads to decreased ferroptosis in hepatic cells (151). Collectively, TEC can target
different tsRNAs and synergistically regulate pyroptosis and
ferroptosis, the two programmed cell death patterns. This dual
regulation, on the one hand, blocks hepatic lipid accumulation, and
on the other hand, alleviates inflammatory responses and enhances
hepatocyte survival, thereby demonstrating multi-dimensional
effects in the treatment of NASH. The aforementioned results not
only deepen the understanding of tsRNA-mediated regulatory
mechanisms in liver lesions but also lay a new theoretical
foundation for multi-target combined intervention strategies
centered on tsRNA (Table
II).
Most patients with HCC present with advanced
disease that is unamenable to curative surgical resection or
localized percutaneous tumor ablation, creating an urgent clinical
need to develop effective combinatorial therapeutic strategies.
Studies have confirmed that tsRNAs can be combined with various
therapeutic approaches to significantly enhance the efficacy of
hepatic disease treatment. Among these, the combination of
radiotherapy and targeting tRF5-GlyGCC has been proven to be a
promising optimized adjuvant therapy for preventing postoperative
HCC recurrence. Radiotherapy plus tRF5-GlyGCC targeting may
optimize postoperative HCC adjuvant therapy. tRF5-GlyGCC binds
KDM6B, activating Runx2 to drive ITGBL1 and S100A9 expression.
ITGBL1 directly, and S100A9 indirectly (via myeloid-derived
suppressor cells), suppress NK cell elimination activity, weakening
antitumor immunity. A tRF5-GlyGCC inhibitor reverses this,
restoring NK cell cytotoxic capacity and synergizing with
radiotherapy to prevent HCC recurrence (89).
The aforementioned studies have demonstrated that
tsRNA-targeted therapy has considerable potential for the treatment
of liver diseases; however, its clinical translation still faces
major challenges. Functional small RNA molecules are readily
degraded by nucleases in vivo and lack efficient
tissue-targeted delivery strategies, thereby limiting their
therapeutic efficacy. Although conventional nanomedicine delivery
systems have improved drug stability to a certain extent, they
remain associated with immune clearance and toxicity, which hinders
precise and sustained intervention in hepatic lesions. Therefore,
the development of novel, highly efficient and safe tsRNA-specific
delivery systems is essential to promote the clinical translation
of tsRNA-targeted therapy (152). Recently, biomimetic
nanotechnology and stimuli-responsive material design have been
employed to construct various engineered nano-delivery platforms
for tsRNA. These platforms not only effectively address the in
vivo stability and targeted accumulation of tsRNA, but also
enable precise temporal regulation of specific pathological
signaling pathways, thereby providing innovative strategies for
personalized combination therapy of liver diseases (153). Gong et al (89) developed a tRF5-Gi@ HOP
nanocomposite powder that forms a water-responsive hydrogel for
sustained local liver release, blocking the tRF5-GlyGCC/KDM6B/Runx2
pathway to reverse NK cell immune suppression and inhibit abdominal
adhesion, providing a targeted and safe tsRNA strategy for
postoperative HCC. Delivery efficiency was verified by drug loading
and 24-day in vitro release; local retention by rheological,
adhesive, and morphological tests; and in vivo efficacy by
radiosensitization, tumor recurrence, and immune infiltration.
Biosafety was assessed by hepatocyte viability, hemolysis, blood
biochemistry, multi-organ pathology, subcutaneous degradation and
wound staining (89). A second
system, in-tsr/PEI/PLGA@CCM (HCC cell membrane-coated, PEI-modified
PLGA nanoparticles), was shown to disrupt HCC cell-M2 TAM crosstalk
and suppress HCC progression in both subcutaneous and orthotopic
mouse models. Delivery efficiency was evidenced by tumor
accumulation, while biosafety was assessed by serum biochemistry
(ALT/AST), and histopathological examination of major organs
(154) (Table II). Collectively, these
tsRNA-based delivery systems illustrate the potential of
personalized treatment. However, their translational prospects
depend on systematic evaluation of delivery efficiency and
biosafety using the aforementioned standardized indicators. Future
studies should report quantitative biodistribution, hepatocyte
uptake, target knockdown, ALT/AST, liver histopathology and
immunogenicity to enable meaningful cross-study comparisons.
Challenges and knowledge gaps
tsRNAs are an emerging class of regulatory sncRNAs
with diverse molecular functions, but their translational
application in hepatology remains in its infancy. In the present
review, evidence indicating that tsRNAs are not merely degradation
products of tRNA turnover but functional molecules involved in
hepatic gene regulation, stress responses and inter-organ
communication, was consolidated. Although high-throughput
sequencing, bioinformatics and cell-based experiments have been the
principal strategies used to interrogate tsRNA-liver disease
associations (155), critical
appraisal of the current literature reveals that, while certain
foundational principles are becoming established, substantial
controversies, conflicting evidence, and unresolved mechanistic
gaps continue to impede clinical translation.
A broad consensus now exists that tsRNAs are
differentially expressed across the spectrum of hepatic diseases,
including HCC, MASLD, ALD and viral hepatitis, and that they
participate in core pathological processes such as lipid
metabolism, immune evasion and fibrogenesis. Similarly, the
regulatory role of tRNA modifications, particularly m5C methylation
by NSun2 and DNMT2, in governing tsRNA biogenesis is well accepted
across multiple tissues (156).
Nevertheless, when these general principles are applied to specific
hepatic contexts, the evidence becomes markedly contradictory.
The most striking contradiction concerns the
tissue-specific consequences of tRNA modification loss. In the
liver, reduced NSun2 activity generates protective tsRNAs, such as
tRF-Gln-CTG-026, which promotes hepatocyte survival after injury,
and other NSun2-dependent fragments that suppress sinusoidal
capillarization and fibrosis. Conversely, in epidermal tissues,
NSun2 deficiency suppresses tumor formation (157), whereas ALKBH3-mediated removal
of m1A and m3C accelerates ANG-dependent cleavage and yields
pro-tumorigenic tsRNAs (158).
These opposing outcomes suggest that identical epitranscriptomic
modifications can be protective in one cellular environment and
pathogenic in another. Whether this discrepancy reflects
differences in baseline enzyme expression, substrate tRNA
availability, cell-type-specific downstream targets, or divergent
signaling landscapes remains unexplored in hepatic systems.
Crucially, nearly all liver-derived evidence originates from
hepatocyte-centric or bulk-tissue analyses, despite growing
recognition that tumor-derived tsRNAs can reprogram
tumor-associated macrophages and that lineage-specific PUS7
circuits operate in stem cells. Whether NSun2, DNMT2, ALKBH3 and
PUS7 exert consistent or opposing activities across hepatic
parenchymal and non-parenchymal cell populations, and whether the
same modification event can elicit divergent effects depending on
the recipient cell, is a fundamental unresolved question.
A second area of contradiction lies in the
dualistic role of tsRNAs in tumorigenesis. Some fragments, such as
Gly-tRF, tRF-34, and 5′-tRF-Gly, act as oncogenic drivers by
activating AKT, MEK/ERK and CEACAM1 signaling (79-81), whereas others, including HCETSR
and 5′-tiRNA-Gln, exert tumor-suppressive effects by disrupting
β-catenin complex stability or inhibiting EIF4A1-dependent
translation (83,86). This functional dichotomy is not
merely a matter of different tsRNAs having different roles; it
raises a deeper controversy about whether tsRNA-mediated regulation
follows predictable rules based on sequence, subcellular
localization, or AGO-loading preference, or whether biological
output is predominantly context-dependent. Notably, numerous
proposed oncogenic or tumor-suppressive mechanisms have been
validated only in single cell lines or patient cohorts, leaving it
unclear whether contradictory findings reflect true biological
heterogeneity or methodological artifacts such as
cell-line-specific expression backgrounds and off-target effects of
tsRNA mimics.
Beyond conflicting experimental results, several
conceptual controversies persist. First, the relative importance of
AGO-dependent vs. AGO-independent mechanisms remains unresolved.
Early studies emphasized tsRNA-mediated gene silencing through
AGO1-4 loading and RISC assembly, analogous to miRNAs (20). However, subsequent work
demonstrated that numerous tsRNAs bind preferentially to AGO1, AGO3
and AGO4 rather than AGO2, and that a substantial fraction exerts
regulatory effects through non-canonical pathways, such as
displacing RNA-binding proteins (for example, YBX1) or modulating
translation initiation factors (22,44). The critical unresolved
controversy is whether AGO-associated tsRNAs represent the primary
functional pool in hepatocytes or whether protein-displacement and
ribosome-interaction mechanisms dominate in liver pathophysiology.
The limited number of tsRNAs with validated AGO interactions,
combined with evidence that numerous tsRNAs exhibit weak AGO
binding (17), challenges the
assumption that tsRNA function is predominantly miRNA-like.
Second, the physiological significance of
circulating tsRNAs remains contentious. Although their stability in
serum and plasma, whether encapsulated in EVs or bound to
ribonucleoproteins, has fueled enthusiasm for liquid biopsy
applications, it is debated whether these circulating fragments are
actively secreted as intercellular signaling molecules or passively
released as byproducts of cellular injury and tRNA turnover. This
distinction is not merely semantic: If circulating tsRNAs are
primarily damage-associated molecular patterns, their therapeutic
value is limited, whereas active secretion would support their role
as druggable mediators of inter-organ crosstalk. The observation
that bacterial-derived tsRNAs in outer membrane vesicles can
regulate host gene expression, and that host tsRNAs can modulate
gut microbiota composition, supports an active signaling role in
the gut-liver axis. However, the reverse pathway, whether
liver-derived tsRNAs actively shape the intestinal microenvironment
(159,160), remains entirely speculative,
and system-level evidence for tsRNA-mediated liver-heart or
liver-brain communication is virtually absent.
Several knowledge gaps must be addressed to move
the field from descriptive association to mechanistic understanding
and clinical utility.
First, at the cellular level, the
cell-type-specific tsRNA modification landscape in the liver is
unknown. The liver comprises hepatocytes, Kupffer cells, hepatic
stellate cells and sinusoidal endothelial cells, each with distinct
epitranscriptomic machinery and stress responses. Current
bulk-tissue or hepatocyte-centric studies cannot resolve whether
observed tsRNA alterations originate from parenchymal cells, immune
cells, or stromal components, nor can they distinguish
cell-autonomous effects from paracrine signaling. Furthermore,
although tsRNAs are implicated in immune regulation, such as
tRF5-GlyGCC-mediated NK cell suppression and tsRNA-10105-driven M2
macrophage polarization (87,88), the precise molecular targets and
receptor systems on immune cells remain unidentified. At the
inter-organ level, the gut-liver axis has emerged as a key
frontier, yet major gaps persist. While bacterial tsRNAs delivered
via outer membrane vesicles can activate host MAPK signaling
(116), and host tsRNAs can
selectively inhibit pathogen growth (for example, F.
nucleatum) without harming commensals (for example, S.
mitis) (114), the
bidirectional regulatory logic remains opaque. Whether hepatic
tsRNAs are secreted into bile or systemic circulation to modulate
gut microbiota, and whether gut-derived tsRNAs contribute to
extrahepatic organ dysfunction beyond the liver, are critical
unanswered questions. Similarly, the cardio-hepatic communication
axis, in which steatotic hepatocyte-derived EVs deliver ncRNAs to
cardiomyocytes, has been demonstrated for miRNAs (118) but not for tsRNAs, representing
a significant cognitive gap at the systems level.
Second, with respect to technical gaps, the
methodological limitations of tsRNA detection constitute a major
barrier to both discovery and clinical translation. Standard small
RNA sequencing systematically under-represents heavily modified
tsRNAs because m1A, m1G, m22G and m3C modifications block reverse
transcription and adapter ligation. Although PANDORA-seq and
mim-tRNAseq have begun to address this bias, these platforms are
not interchangeable: PANDORA-seq erases modification information
during enzymatic treatment, precluding simultaneous quantification
of abundance and modification status, whereas mim-tRNAseq requires
substantial RNA input (≥0.5 µg) and is restricted to mature
tRNA-derived fragments, excluding pre-tRNA species. Nanopore-based
direct RNA sequencing preserves native modifications but suffers
from high error rates, large input requirements, and inefficient
capture of molecules shorter than 100 nt, rendering it impractical
for most tsRNAs in routine clinical settings (139,143). Consequently, no single platform
currently provides a standardized, modification-aware, and
clinically feasible workflow for tsRNA profiling. Moreover, EV
isolation methods significantly impact both yield and RNA
composition, yet no consensus exists on optimal protocols for
hepatic biofluids. The majority of circulating tsRNAs are not
EV-encapsulated but associated with extra-vesicular
ribonucleoproteins, yet most biomarker studies have focused
exclusively on exosomal fractions, potentially introducing
systematic bias. The lack of standardized blood processing
protocols, reference ranges for healthy populations, and accounting
for confounding variables further undermines the reliability of
circulating tsRNA signatures.
Third, regarding translational gaps, perhaps the
most critical gap is the near-universal absence of large-scale,
multicenter, prospective validation. Nearly all diagnostic tsRNA
signatures for HCC, such as hsa_tsr014055 (128), tRF-23-R9J89O9N9 (129) and tRF-Gln-TTG-006 (133), have been derived from single
retrospective cohorts with small sample sizes. Estimating
diagnostic accuracy within the discovery cohort risks substantial
overfitting. Furthermore, most studies compare diagnosed patients
against healthy controls, a design that artificially inflates
sensitivity and specificity by excluding patients with early-stage
disease, competing liver pathologies, or non-malignant liver
lesions. Whether these signatures maintain performance in
real-world scenarios, where distinguishing HCC from cirrhosis, CCA,
or hepatic adenoma is clinically essential, remains unproven. An
equally important translational gap lies in establishing causality
vs. correlation. Although numerous studies demonstrate that tsRNA
levels correlate with disease severity, prognosis, or histological
grade, few have rigorously established that manipulating a specific
tsRNA alters disease trajectory in vivo through a defined
molecular target. Several proposed diagnostic tsRNAs still lack
validated downstream targets, raising the possibility that their
altered expression reflects epiphenomenal tRNA turnover rather than
causal pathogenic drive. Without target validation and mechanistic
clarity, the rationale for tsRNA-targeted therapeutics remains
speculative.
Addressing these controversies and gaps requires a
coordinated research agenda. At the mechanistic level,
cell-type-specific and spatially resolved tsRNA profiling, ideally
combined with single-cell epitranscriptomics, is needed to resolve
the contradictory roles of modification enzymes across hepatic cell
lineages. Manipulating NSun2, DNMT2, or ALKBH3 in specific cell
populations (for example, hepatocytes vs. Kupffer cells) followed
by functional rescue experiments would clarify whether
tissue-specific effects reflect intrinsic cellular wiring or
paracrine crosstalk (39-41).
At the validation level, the field must move beyond descriptive
biomarker discovery toward rigorous external validation. Future
studies should adopt prospective cohort designs, include clinically
relevant comparator groups (for example, cirrhosis without HCC and
mixed-etiology liver disease), and standardize pre-analytical
variables including fasting status, time of collection and EV
isolation protocols. Integration of tsRNA signatures with
established markers (AFP, PIVKA-II and DCP) should be evaluated in
independent populations to assess additive diagnostic value rather
than isolated performance (126-131). At the therapeutic level,
mechanistic studies must prioritize target identification and
causal validation. For tsRNAs with therapeutic potential, such as
5′-tiRNA-Gln in HCC (86) or
tRF-Gln-CTG-026 in liver injury (65), defining their direct binding
partners (RNA, protein, or ribonucleoprotein complexes) and
resolving their subcellular sites of action is essential. The
development of tsRNA-specific delivery systems, such as the HCC
cell membrane-coated PLGA nanoparticles (in-tsr/PEI/PLGA@ CCM) or
the water-responsive hydrogel tRF5-Gi@HOP (89), represents promising progress.
However, systematic evaluation of hepatocyte uptake efficiency,
target knockdown specificity, off-target effects on physiological
tsRNA networks, immunogenicity, and long-term biosafety, quantified
by standardized metrics including biodistribution, ALT/AST profiles
and liver histopathology, remains incomplete. Without such
standardized benchmarking, cross-study comparison and regulatory
approval will remain elusive.
Finally, the inter-organ dimension of tsRNA biology
demands focused investigation. Bidirectional tsRNA trafficking
along the gut-liver axis, and the potential role of liver-derived
tsRNAs in remote organ dysfunction (for example, heart failure with
preserved ejection fraction in MASLD), should be mapped using
multi-omics integration and organoid co-culture systems. Such
approaches will determine whether tsRNAs are merely biomarkers of
inter-organ disease or active mediators amenable to therapeutic
interception.
Conclusion and future perspectives
In conclusion, tsRNAs have emerged as biologically
active molecules with considerable, but currently unrealized,
potential in hepatology. The functional effects of tsRNA do not
occur randomly; rather, they stem from a precisely regulated
biological production process. tRNA and its precursors are cleaved
at specific sites by nucleases, including angiogenin, Dicer and
RNase Z/ELAC2. This process is further regulated by epigenomic
transcriptome modifications, such as m5C and
pseudo-uridine, resulting in the generation of distinct tsRNA
fragments with specific regulatory characteristics. These fragments
subsequently exert specific biological functions through various
molecular mechanisms, including classic AGO-dependent gene
silencing, ribosome binding, RNA-binding protein displacement, and
transcriptional feedback regulation. In the liver, tsRNA can enter
liver cells to regulate gene expression, translation and stress
responses. Increasing evidence indicates that fluctuations in
tsRNAs expression are closely related to the occurrence and
progression of liver diseases: In HCC, tsRNA drives tumor
progression through oncogenic signal transduction and immune
escape; in dysfunction-associated steatotic liver disease, tsRNA
disrupts lipid homeostasis and autophagy; in ALD, the interaction
between complement and tsRNA amplifies pathological damage. In
viral hepatitis, the RNA cross-dialogue between the host and the
pathogen determines the disease outcome. The diversity of these
mechanisms makes tsRNAs not only a promising non-invasive biomarker
for early diagnosis and prognostic assessment but also a potential
drug target that can be intervened through therapeutic inhibition,
stimulation, or engineered nano-delivery. Although their
differential expression across liver diseases and their mechanistic
versatility in gene regulation are increasingly well documented,
the field is hampered by conflicting evidence on the
tissue-specific consequences of tRNA modifications, unresolved
controversies regarding canonical vs. non-canonical mechanisms, and
substantial translational gaps in validation, standardization, and
delivery. Moving tsRNAs from promising research findings to
trustworthy clinical markers and therapeutic targets will require
integrated, multicenter, mechanism-driven investigations that
explicitly address these contradictions and gaps, rather than
further single-study descriptions.
Availability of data and materials
Not applicable.
Authors' contributions
YCa was chiefly responsible for the composition,
review, and revision of the manuscript. YCh organized the
references and generated the tables and figures. FY established the
structural outline of the manuscript. YY prepared the original
manuscript. TJ participated in the review and critical editing of
the manuscript for significant intellectual content. All authors
read and approved the final version of the manuscript. Data
authentication is not applicable.
Ethics approval and consent to
participate
Not applicable.
Patient consent for publication
Not applicable.
Competing interests
The authors declare that they have no competing
interests.
Acknowledgments
Not applicable.
Funding
The present study was supported by the National Natural Science
Foundation of China (grant nos. 82570746), the Scientific Research
Project of Jiangsu Commission of Health (grant no. K2024037), the
Open project of Jiangsu Provincial Key Laboratory of Laboratory
Medicine (grant nos. JSKLM-T-2025-01, JSKLM-T-2026-01 and
JSKLM-Z-20 25-03) and the Changzhou Longcheng Talents Program
(grant no. CQ20250032).
References
|
1
|
Younossi ZM, Wong G, Anstee QM and Henry
L: The global burden of liver disease. Clin Gastroenterol Hepatol.
21:1978–1991. 2023. View Article : Google Scholar : PubMed/NCBI
|
|
2
|
Devarbhavi H, Asrani SK, Arab JP, Nartey
YA, Pose E and Kamath PS: Global burden of liver disease: 2023
update. J Hepatol. 79:516–537. 2023. View Article : Google Scholar : PubMed/NCBI
|
|
3
|
Miao L, Targher G, Byrne CD, Cao YY and
Zheng MH: Current status and future trends of the global burden of
MASLD. Trends Endocrinol Metab. 35:697–707. 2024. View Article : Google Scholar : PubMed/NCBI
|
|
4
|
Sotoudeheian M: Galectin-3 and severity of
liver fibrosis in metabolic dysfunction-associated fatty liver
disease. Protein Pept Lett. 31:290–304. 2024. View Article : Google Scholar : PubMed/NCBI
|
|
5
|
Lei L and Burton ZF: Evolution of life on
earth: tRNA, Aminoacyl-tRNA synthetases and the genetic code. Life
(Basel). 10:212020.PubMed/NCBI
|
|
6
|
Su Z, Wilson B, Kumar P and Dutta A:
Noncanonical roles of tRNAs: tRNA fragments and beyond. Annu Rev
Genet. 54:47–69. 2020. View Article : Google Scholar : PubMed/NCBI
|
|
7
|
Huang T, Zhao Y, Jiang G and Yang Z:
tsRNA: A promising biomarker in breast cancer. J Cancer.
15:2613–2626. 2024. View Article : Google Scholar : PubMed/NCBI
|
|
8
|
Choubisa BK, Sharma A, Sharma NK, Farooqi
MS, Mishra DC, Chaturvedi KK, Lal SB, Arora A and Jha GK:
CLnc-Pred: A machine learning approach to predict long non-coding
RNAs in crops. Curr Genomics. 26:726–739. 2025. View Article : Google Scholar : PubMed/NCBI
|
|
9
|
Liang Y, Ji D, Ying X, Ma R and Ji W:
tsRNA modifications: An emerging layer of biological regulation in
disease. J Adv Res. 74:403–414. 2025. View Article : Google Scholar :
|
|
10
|
Cosentino C, Toivonen S, Diaz Villamil E,
Atta M, Ravanat JL, Demine S, Schiavo AA, Pachera N, Deglasse JP,
Jonas JC, et al: Pancreatic β-cell tRNA hypomethylation and
fragmentation link TRMT10A deficiency with diabetes. Nucleic Acids
Res. 46:10302–10318. 2018. View Article : Google Scholar : PubMed/NCBI
|
|
11
|
Deng J, Ptashkin RN, Chen Y, Cheng Z, Liu
G, Phan T, Deng X, Zhou J, Lee I, Lee YS and Bao X: Respiratory
syncytial virus utilizes a tRNA fragment to suppress antiviral
responses through a novel targeting mechanism. Mol Ther.
23:1622–1629. 2015. View Article : Google Scholar : PubMed/NCBI
|
|
12
|
Falconi M, Giangrossi M, Zabaleta ME, Wang
J, Gambini V, Tilio M, Bencardino D, Occhipinti S, Belletti B,
Laudadio E, et al: A novel 3′-tRNA(Glu)-derived fragment acts as a
tumor suppressor in breast cancer by targeting nucleolin. FASEB J.
33:13228–13240. 2019. View Article : Google Scholar : PubMed/NCBI
|
|
13
|
Mehmood R: Ramifications of m6A
modification on ncRNAs in cancer. Curr Genomics. 25:158–170. 2024.
View Article : Google Scholar : PubMed/NCBI
|
|
14
|
Weng Q, Wang Y, Xie Y, Yu X, Zhang S, Ge
J, Li Z, Ye G and Guo J: Extracellular vesicles-associated
tRNA-derived fragments (tRFs): biogenesis, biological functions,
and their role as potential biomarkers in human diseases. J Mol Med
(Berl). 100:679–695. 2022. View Article : Google Scholar : PubMed/NCBI
|
|
15
|
Zhou M, He X, Zhang J, Mei C, Zhong B and
Ou C: tRNA-derived small RNAs in human cancers: roles, mechanisms,
and clinical application. Mol Cancer. 23:762024. View Article : Google Scholar : PubMed/NCBI
|
|
16
|
Phizicky EM and Hopper AK: tRNA biology
charges to the front. Genes Dev. 24:1832–1860. 2010. View Article : Google Scholar : PubMed/NCBI
|
|
17
|
Abdelhamid AM, Abaza T, Kotb WT, Mohamed
AH, Gad MZ, Metwally AM, Coulouarn C and Youness RA: Emerging role
of transfer RNA-derived small RNAs (tsRNAs) in hepatocellular
carcinoma. Expert Rev Mol Diagn. 25:939–956. 2025. View Article : Google Scholar : PubMed/NCBI
|
|
18
|
Orellana EA, Siegal E and Gregory RI: tRNA
dysregulation and disease. Nat Rev Genet. 23:651–664. 2022.
View Article : Google Scholar : PubMed/NCBI
|
|
19
|
Lee S, Kim J, Valdmanis PN and Kim HK:
Emerging roles of tRNA-derived small RNAs in cancer biology. Exp
Mol Med. 55:1293–1304. 2023. View Article : Google Scholar : PubMed/NCBI
|
|
20
|
Liu B, Cao J, Wang X, Guo C, Liu Y and
Wang T: Deciphering the tRNA-derived small RNAs: Origin,
development, and future. Cell Death Dis. 13:242021. View Article : Google Scholar : PubMed/NCBI
|
|
21
|
Yamasaki S, Ivanov P, Hu GF and Anderson
P: Angiogenin cleaves tRNA and promotes stress-induced
translational repression. J Cell Biol. 185:35–42. 2009. View Article : Google Scholar : PubMed/NCBI
|
|
22
|
Di Fazio A and Gullerova M: An old friend
with a new face: tRNA-derived small RNAs with big regulatory
potential in cancer biology. Br J Cancer. 128:1625–1635.
2023.PubMed/NCBI
|
|
23
|
Kim HK, Yeom JH and Kay MA: Transfer
RNA-Derived Small RNAs: Another layer of gene regulation and novel
targets for disease therapeutics. Mol Ther. 28:2340–2357. 2020.
View Article : Google Scholar : PubMed/NCBI
|
|
24
|
Shen Y, Yu X, Zhu L, Li T, Yan Z and Guo
J: Transfer RNA-derived fragments and tRNA halves: Biogenesis,
biological functions and their roles in diseases. J Mol Med (Berl).
96:1167–1176. 2018. View Article : Google Scholar : PubMed/NCBI
|
|
25
|
Magee R and Rigoutsos I: On the expanding
roles of tRNA fragments in modulating cell behavior. Nucleic Acids
Res. 48:9433–9448. 2020. View Article : Google Scholar : PubMed/NCBI
|
|
26
|
Wang M, Guo J, Chen W, Wang H and Hou X:
Emerging roles of tRNA-derived small RNAs in injuries. PeerJ.
12:e183482024. View Article : Google Scholar : PubMed/NCBI
|
|
27
|
Chen Y, Shao Z and Wu S: Research progress
on the tsRNA biogenesis, function, and application in lung cancer.
Noncoding RNA Res. 10:63–69. 2024. View Article : Google Scholar : PubMed/NCBI
|
|
28
|
Sobala A and Hutvagner G: Transfer
RNA-derived fragments: Origins, processing, and functions. Wiley
Interdiscip Rev RNA. 2:853–862. 2011. View Article : Google Scholar : PubMed/NCBI
|
|
29
|
Telonis AG, Loher P, Honda S, Jing Y,
Palazzo J, Kirino Y and Rigoutsos I: Dissecting tRNA-derived
fragment complexities using personalized transcriptomes reveals
novel fragment classes and unexpected dependencies. Oncotarget.
6:24797–24822. 2015. View Article : Google Scholar : PubMed/NCBI
|
|
30
|
Jiang Y, Liu S, Li G, Tang C, Zhang Y, Li
J, Tan Z, Zhang S, Chen Z and Li S: Biological functions of tsRNAs
and research advances in human disease. Biochem Biophys Rep.
45:1024382026.PubMed/NCBI
|
|
31
|
Guzzi N, Cieśla M, Ngoc PCT, Lang S, Arora
S, Dimitriou M, Pimková K, Sommarin MNE, Munita R, Lubas M, et al:
Pseudouridylation of tRNA-Derived fragments steers translational
control in stem cells. Cell. 173:1204–1216.e26. 2018. View Article : Google Scholar : PubMed/NCBI
|
|
32
|
Elkordy A, Mishima E, Niizuma K, Akiyama
Y, Fujimura M, Tominaga T and Abe T: Stress-induced tRNA cleavage
and tiRNA generation in rat neuronal PC12 cells. J Neurochem.
146:560–569. 2018. View Article : Google Scholar : PubMed/NCBI
|
|
33
|
Thompson DM and Parker R: The RNase Rny1p
cleaves tRNAs and promotes cell death during oxidative stress in
Saccharomyces cerevisiae. J Cell Biol. 185:43–50. 2009. View Article : Google Scholar : PubMed/NCBI
|
|
34
|
Rashad S, Niizuma K and Tominaga T: tRNA
cleavage: A new insight. Neural Regen Res. 15:47–52. 2020.
View Article : Google Scholar :
|
|
35
|
Pizzo E, Sarcinelli C, Sheng J, Fusco S,
Formiggini F, Netti P, Yu W, D'Alessio G and Hu GF:
Ribonuclease/angiogenin inhibitor 1 regulates stress-induced
subcellular localization of angiogenin to control growth and
survival. J Cell Sci. 126(Pt 18): 4308–4319. 2013.PubMed/NCBI
|
|
36
|
Su Z, Kuscu C, Malik A, Shibata E and
Dutta A: Angiogenin generates specific stress-induced tRNA halves
and is not involved in tRF-3-mediated gene silencing. J Biol Chem.
294:16930–16941. 2019. View Article : Google Scholar : PubMed/NCBI
|
|
37
|
Kumar P, Anaya J, Mudunuri SB and Dutta A:
Meta-analysis of tRNA derived RNA fragments reveals that they are
evolutionarily conserved and associate with AGO proteins to
recognize specific RNA targets. BMC Biol. 12:782014. View Article : Google Scholar : PubMed/NCBI
|
|
38
|
Di Fazio A, Schlackow M, Pong SK, Alagia A
and Gullerova M: Dicer dependent tRNA derived small RNAs promote
nascent RNA silencing. Nucleic Acids Res. 50:1734–1752. 2022.
View Article : Google Scholar : PubMed/NCBI
|
|
39
|
Martinez G: tRNA-derived small RNAs: New
players in genome protection against retrotransposons. RNA Biol.
15:170–175. 2018. View Article : Google Scholar :
|
|
40
|
Zhu P, Yu J and Zhou P: Role of
tRNA-derived fragments in cancer: Novel diagnostic and therapeutic
targets tRFs in cancer. Am J Cancer Res. 10:393–402.
2020.PubMed/NCBI
|
|
41
|
Blanco S, Dietmann S, Flores JV, Hussain
S, Kutter C, Humphreys P, Lukk M, Lombard P, Treps L, Popis M, et
al: Aberrant methylation of tRNAs links cellular stress to
neuro-developmental disorders. EMBO J. 33:2020–2039. 2014.
View Article : Google Scholar : PubMed/NCBI
|
|
42
|
Schaefer M, Pollex T, Hanna K, Tuorto F,
Meusburger M, Helm M and Lyko F: RNA methylation by Dnmt2 protects
transfer RNAs against stress-induced cleavage. Genes Dev.
24:1590–1595. 2010. View Article : Google Scholar : PubMed/NCBI
|
|
43
|
Zhang Y, Zhang X, Shi J, Tuorto F, Li X,
Liu Y, Liebers R, Zhang L, Qu Y, Qian J, et al: Dnmt2 mediates
intergenerational transmission of paternally acquired metabolic
disorders through sperm small non-coding RNAs. Nat Cell Biol.
20:535–540. 2018. View Article : Google Scholar : PubMed/NCBI
|
|
44
|
Zhao Y, Li X, Ye C, Huang C, Lv X and Li
J: The biogenesis, mechanism and function of the tRNA-derived small
RNA (tsRNA): A review compared with microRNA. Am J Cancer Res.
13:1656–1666. 2023.PubMed/NCBI
|
|
45
|
Zhou K, Diebel KW, Holy J, Skildum A,
Odean E, Hicks DA, Schotl B, Abrahante JE, Spillman MA and Bemis
LT: A tRNA fragment, tRF5-Glu, regulates BCAR3 expression and
proliferation in ovarian cancer cells. Oncotarget. 8:95377–95391.
2017. View Article : Google Scholar : PubMed/NCBI
|
|
46
|
Goodarzi H, Liu X, Nguyen HC, Zhang S,
Fish L and Tavazoie SF: Endogenous tRNA-derived fragments suppress
breast cancer progression via YBX1 displacement. Cell. 161:790–802.
2015. View Article : Google Scholar : PubMed/NCBI
|
|
47
|
Haussecker D, Huang Y, Lau A, Parameswaran
P, Fire AZ and Kay MA: Human tRNA-derived small RNAs in the global
regulation of RNA silencing. RNA. 16:673–695. 2010. View Article : Google Scholar : PubMed/NCBI
|
|
48
|
Li X, Peng J and Yi C: The
epitranscriptome of small non-coding RNAs. Noncoding RNA Res.
6:167–173. 2021. View Article : Google Scholar : PubMed/NCBI
|
|
49
|
Ozata DM, Gainetdinov I, Zoch A, O'Carroll
D and Zamore PD: PIWI-interacting RNAs: small RNAs with big
functions. Nat Rev Genet. 20:89–108. 2019. View Article : Google Scholar
|
|
50
|
Czech B, Munafò M, Ciabrelli F, Eastwood
EL, Fabry MH, Kneuss E and Hannon GJ: piRNA-guided genome defense:
From biogenesis to silencing. Annu Rev Genet. 52:131–157. 2018.
View Article : Google Scholar : PubMed/NCBI
|
|
51
|
Lim SL, Qu ZP, Kortschak RD, Lawrence DM,
Geoghegan J, Hempfling AL, Bergmann M, Goodnow CC, Ormandy CJ, Wong
L, et al: HENMT1 and piRNA stability are required for adult male
germ cell transposon repression and to define the spermatogenic
program in the mouse. PLoS Genet. 11:e10056202015. View Article : Google Scholar : PubMed/NCBI
|
|
52
|
Gainetdinov I, Colpan C, Cecchini K, Arif
A, Jouravleva K, Albosta P, Vega-Badillo J, Lee Y, Özata DM and
Zamore PD: Terminal modification, sequence, length, and
PIWI-protein identity determine piRNA stability. Mol Cell.
81:4826–4842.e8. 2021. View Article : Google Scholar : PubMed/NCBI
|
|
53
|
Chen Q, Zhang X, Shi J, Yan M and Zhou T:
Origins and evolving functionalities of tRNA-derived small RNAs.
Trends Biochem Sci. 46:790–804. 2021. View Article : Google Scholar : PubMed/NCBI
|
|
54
|
Sharma U, Conine CC, Shea JM, Boskovic A,
Derr AG, Bing XY, Belleannee C, Kucukural A, Serra RW, Sun F, et
al: Biogenesis and function of tRNA fragments during sperm
maturation and fertilization in mammals. Science. 351:391–396.
2016. View Article : Google Scholar : PubMed/NCBI
|
|
55
|
Statello L, Guo CJ, Chen LL and Huarte M:
Gene regulation by long non-coding RNAs and its biological
functions. Nat Rev Mol Cell Biol. 22:96–118. 2021. View Article : Google Scholar
|
|
56
|
Paraskevopoulou MD and Hatzigeorgiou AG:
Analyzing MiRNA-LncRNA interactions. Methods Mol Biol.
1402:271–286. 2016. View Article : Google Scholar : PubMed/NCBI
|
|
57
|
Li X, Yang L and Chen LL: The biogenesis,
functions, and challenges of circular RNAs. Mol Cell. 71:428–442.
2018. View Article : Google Scholar : PubMed/NCBI
|
|
58
|
Kristensen LS, Andersen MS, Stagsted LVW,
Ebbesen KK, Hansen TB and Kjems J: The biogenesis, biology and
characterization of circular RNAs. Nat Rev Genet. 20:675–691. 2019.
View Article : Google Scholar : PubMed/NCBI
|
|
59
|
Zhang X, Xu Y, Qian Z, Zheng W, Wu Q, Chen
Y, Zhu G, Liu Y, Bian Z, Xu W, et al: circRNA_104075 stimulates
YAP-dependent tumorigenesis through the regulation of HNF4a and may
serve as a diagnostic marker in hepatocellular carcinoma. Cell
Death Dis. 9:10912018. View Article : Google Scholar : PubMed/NCBI
|
|
60
|
Enuka Y, Lauriola M, Feldman ME, Sas-Chen
A, Ulitsky I and Yarden Y: Circular RNAs are long-lived and display
only minimal early alterations in response to a growth factor.
Nucleic Acids Res. 44:1370–1383. 2016. View Article : Google Scholar :
|
|
61
|
Ma X, Xu J and Li G: tsRNA, cell death and
disease: Connecting the dots. Noncoding RNA Res. 13:109–120. 2025.
View Article : Google Scholar : PubMed/NCBI
|
|
62
|
Bayazit MB, Jacovetti C, Cosentino C,
Sobel J, Wu K, Brozzi F, Rodriguez-Trejo A, Stoll L, Guay C and
Regazzi R: Small RNAs derived from tRNA fragmentation regulate the
functional maturation of neonatal β cells. Cell Rep. 40:1110692022.
View Article : Google Scholar
|
|
63
|
Gonskikh Y, Gerstl M, Kos M, Borth N,
Schosserer M, Grillari J and Polacek N: Modulation of mammalian
translation by a ribosome-associated tRNA half. RNA Biol.
17:1125–1136. 2020. View Article : Google Scholar : PubMed/NCBI
|
|
64
|
Guzzi N, Muthukumar S, Cieśla M, Todisco
G, Ngoc PCT, Madej M, Munita R, Fazio S, Ekström S, Mortera-Blanco
T, et al: Pseudouridine-modified tRNA fragments repress aberrant
protein synthesis and predict leukaemic progression in
myelodysplastic syndrome. Nat Cell Biol. 24:299–306. 2022.
View Article : Google Scholar : PubMed/NCBI
|
|
65
|
Ying S, Li P, Wang J, Chen K, Zou Y, Dai
M, Xu K, Feng G, Zhang C, Jiang H, et al: tRF-Gln-CTG-026
ameliorates liver injury by alleviating global protein synthesis.
Signal Transduct Target Ther. 8:1442023. View Article : Google Scholar : PubMed/NCBI
|
|
66
|
Kim HK, Fuchs G, Wang S, Wei W, Zhang Y,
Park H, Roy-Chaudhuri B, Li P, Xu J, Chu K, et al: A
transfer-RNA-derived small RNA regulates ribosome biogenesis.
Nature. 552:57–62. 2017. View Article : Google Scholar : PubMed/NCBI
|
|
67
|
Kfoury YS, Ji F, Mazzola M, Sykes DB,
Scherer AK, Anselmo A, Akiyama Y, Mercier F, Severe N, Kokkaliaris
KD, et al: tiRNA signaling via stress-regulated vesicle transfer in
the hematopoietic niche. Cell Stem Cell. 28:2090–2103.e9. 2021.
View Article : Google Scholar : PubMed/NCBI
|
|
68
|
Chen L, Xu W, Liu K, Jiang Z, Han Y, Jin
H, Zhang L, Shen W, Jia S, Sun Q and Meng A: 5′ Half of specific
tRNAs feeds back to promote corresponding tRNA gene transcription
in vertebrate embryos. Sci Adv. 7:eabh04942021. View Article : Google Scholar
|
|
69
|
Liu X, Mei W, Padmanaban V, Alwaseem H,
Molina H, Passarelli MC, Tavora B and Tavazoie SF: A pro-metastatic
tRNA fragment drives Nucleolin oligomerization and stabilization of
its bound metabolic mRNAs. Mol Cell. 82:2604–2617.e8. 2022.
View Article : Google Scholar : PubMed/NCBI
|
|
70
|
Ruggero K, Guffanti A, Corradin A, Sharma
VK, De Bellis G, Corti G, Grassi A, Zanovello P, Bronte V, Ciminale
V and D'Agostino DM: Small noncoding RNAs in cells transformed by
human T-cell leukemia virus type 1: A role for a tRNA fragment as a
primer for reverse transcriptase. J Virol. 88:3612–3622. 2014.
View Article : Google Scholar : PubMed/NCBI
|
|
71
|
Rosace D, López J and Blanco S: Emerging
roles of novel small non-coding regulatory RNAs in immunity and
cancer. RNA Biol. 17:1196–1213. 2020. View Article : Google Scholar : PubMed/NCBI
|
|
72
|
Kuscu C, Kumar P, Kiran M, Su Z, Malik A
and Dutta A: tRNA fragments (tRFs) guide Ago to regulate gene
expression post-transcriptionally in a Dicer-independent manner.
RNA. 24:1093–1105. 2018. View Article : Google Scholar : PubMed/NCBI
|
|
73
|
Green JA, Ansari MY, Ball HC and Haqqi TM:
tRNA-derived fragments (tRFs) regulate post-transcriptional gene
expression via AGO-dependent mechanism in IL-1β stimulated
chondrocytes. Osteoarthritis Cartilage. 28:1102–1110. 2020.
View Article : Google Scholar : PubMed/NCBI
|
|
74
|
Long D, Xu Y, Mao G, Xin R, Deng Z, Liao
H, Li Z, Yang Z, Yu B, Yang Z, et al: tRNA-derived fragment TRF365
regulates the metabolism of anterior cruciate ligament cells by
targeting IKBKB. Cell Death Discov. 8:192022. View Article : Google Scholar : PubMed/NCBI
|
|
75
|
Wang Q, Ying X, Huang Q, Wang Z and Duan
S: Exploring the role of tRNA-derived small RNAs (tsRNAs) in
disease: Implications for HIF-1 pathway modulation. J Mol Med
(Berl). 102:973–985. 2024. View Article : Google Scholar : PubMed/NCBI
|
|
76
|
Forner A, Reig M and Bruix J:
Hepatocellular carcinoma. Lancet. 391:1301–1314. 2018. View Article : Google Scholar : PubMed/NCBI
|
|
77
|
Chen C, Xu Q, Wang T, Yuan Y, Hu Z, Li X,
Zheng X and Lei H: Comparative analysis of liver cancer burden
trends in China and worldwide between 1990 and 2021. Front Public
Health. 13:15132102025. View Article : Google Scholar : PubMed/NCBI
|
|
78
|
Balatti V, Nigita G, Veneziano D, Drusco
A, Stein GS, Messier TL, Farina NH, Lian JB, Tomasello L, Liu CG,
et al: tsRNA signatures in cancer. Proc Natl Acad Sci USA.
114:8071–8076. 2017. View Article : Google Scholar : PubMed/NCBI
|
|
79
|
Hanahan D and Weinberg RA: Hallmarks of
cancer: The next generation. Cell. 144:646–674. 2011. View Article : Google Scholar : PubMed/NCBI
|
|
80
|
O'Leary CE, Riling CR, Spruce LA, Ding H,
Kumar S, Deng G, Liu Y, Seeholzer SH and Oliver PM: Ndfip-mediated
degradation of Jak1 tunes cytokine signalling to limit expansion of
CD4+ effector T cells. Nat Commun. 7:112262016. View Article : Google Scholar : PubMed/NCBI
|
|
81
|
Zhou Y, Hu J, Liu L, Yan M, Zhang Q, Song
X, Lin Y, Zhu D, Wei Y, Fu Z, et al: Gly-tRF enhances LCSC-like
properties and promotes HCC cells migration by targeting NDFIP2.
Cancer Cell Int. 21:5022021. View Article : Google Scholar : PubMed/NCBI
|
|
82
|
Xu T, Hua H, Song F, Zhang N, Gao C and
Chen Z: tRF-34-P4R8YP9LON4VHM promotes hepatocellular carcinoma
progression and tumour cell-induced angiogenesis via the MEK/ERK
Pathway. J Cell Mol Med. 29:e705602025. View Article : Google Scholar : PubMed/NCBI
|
|
83
|
Liu D, Wu C, Wang J, Zhang L, Sun Z, Chen
S, Ding Y and Wang W: Transfer RNA-derived fragment 5'tRF-Gly
promotes the development of hepatocellular carcinoma by direct
targeting of carcinoembryonic antigen-related cell adhesion
molecule 1. Cancer Sci. 113:3476–3488. 2022. View Article : Google Scholar : PubMed/NCBI
|
|
84
|
Qu X, Liu B, Jin D, Ma Y, Liu M, Yan X, Su
J and Zhou L: Hypoxia-induced tRF-3(Thr-CGT) promotes
hepatocellular carcinoma progression via mitochondrial energy
metabolism remodeling dependent on the mtDNA-translation mechanism.
Front Pharmacol. 16:15493732025. View Article : Google Scholar : PubMed/NCBI
|
|
85
|
Rui T, Zhu K, Mao Z, Wu J, Pan Y, Ye Q,
Chen C, Xiang A, Guo J, Tang N, et al: A Novel tRF, HCETSR, derived
from tRNA-Glu/TTC, inhibits HCC malignancy by regulating the
SPBTN1-catenin complex axis. Adv Sci (Weinh). 12:e24152292025.
View Article : Google Scholar : PubMed/NCBI
|
|
86
|
Wu C, Liu D, Zhang L, Wang J, Ding Y, Sun
Z and Wang W: 5'-tiRNA-Gln inhibits hepatocellular carcinoma
progression by repressing translation through the interaction with
eukaryotic initiation factor 4A-I. Front Med. 17:476–492. 2023.
View Article : Google Scholar : PubMed/NCBI
|
|
87
|
Maslennikov R, Poluektova E, Zolnikova O,
Sedova A, Kurbatova A, Shulpekova Y, Dzhakhaya N, Kardasheva S,
Nadinskaia M, Bueverova E, et al: Gut microbiota and bacterial
translocation in the pathogenesis of liver fibrosis. Int J Mol Sci.
24:165022023. View Article : Google Scholar : PubMed/NCBI
|
|
88
|
Cheng Y, Gong Y, Chen X, Zhang Q, Zhang X,
He Y, Pan L, Ni B, Yang F, Xu Y, et al: Injectable adhesive
hemostatic gel with tumor acidity neutralizer and neutrophil
extracellular traps lyase for enhancing adoptive NK cell therapy
prevents post-resection recurrence of hepatocellular carcinoma.
Biomaterials. 284:1215062022. View Article : Google Scholar : PubMed/NCBI
|
|
89
|
Gong Y, Zeng F, Zhang F, Liu X, Li Z, Chen
W, Liu H, Li X, Cheng Y, Zhang J, et al: Radiotherapy plus a
self-gelation powder encapsulating tRF5-GlyGCC inhibitor
potentiates natural kill cell immunity to prevent hepatocellular
carcinoma recurrence. J Nanobiotechnology. 23:1002025. View Article : Google Scholar : PubMed/NCBI
|
|
90
|
Pan L, Zhou R, Wen Z, Lin Y, Cai H, Lin C,
Xu X, Ruan L, Zeng Y, Zhang H, et al: tsRNA-10105-enriched
migrasomes mediate hepatocellular carcinoma immunosuppressive
microenvironment by inducing M2 Macrophage polarization. Exp Cell
Res. 453:1147292025. View Article : Google Scholar : PubMed/NCBI
|
|
91
|
Guan Y, Kim Y, Wang Y, Cho YE, Xiang X,
Kim SJ, Yao T, Feng D, Hwang S and Gao B: Adipocyte death promotes
hepatic infiltration of S100A8+ macrophages and steatotic liver
disease progression in mice. J Clin Invest. 135:e1906352025.
View Article : Google Scholar : PubMed/NCBI
|
|
92
|
Siapoush S, Milani M, Zarghami N,
Ebrahimi-Kalan A, Rezaei R and Rahmati M: Targeting key players in
lipid biosynthesis for NAFLD and NASH treatment. Cell Mol Biol
(Noisy-le-grand). 70:117–133. 2024. View Article : Google Scholar : PubMed/NCBI
|
|
93
|
Zhao N, Zhang X, Ding J, Pan Q, Zheng MH,
Liu WY, Luo G, Qu J, Li M, Li L, et al: SEMA7AR148W mutation
promotes lipid accumulation and NAFLD progression via increased
localization on the hepatocyte surface. JCI Insight. 7:e1541132022.
View Article : Google Scholar : PubMed/NCBI
|
|
94
|
Li X, Hernandez R, Zhang X, Tang S, Yuan
X, Wu J, Pham K, Rawal HC, Heinrich EC, Zhang S, et al: A
cholesterol-responsive hepatic tRNA-derived small RNA regulates
cholesterol homeostasis and atherosclerosis development. Nat
Commun. 16:110432025. View Article : Google Scholar : PubMed/NCBI
|
|
95
|
Shen L, Lei Y, Zhao X, Wang X, Chen D,
Wang K, Zhong Y, Liao T, Yang Y, Chen L, et al: RNase P generated
tRF(Ser-GCT) promotes fat storage in adipocytes via Adrb2
signaling. J Biol Chem. 301:1108202025. View Article : Google Scholar : PubMed/NCBI
|
|
96
|
Liao T, Gan M, Lei Y, Wang Y, Chen L, Shen
L and Zhu L: Dynamic changes in the transcriptome of tRNA-derived
small RNAs related with fat metabolism. Sci Data. 10:7032023.
View Article : Google Scholar : PubMed/NCBI
|
|
97
|
Lin CW, Zhang H, Li M, Xiong X, Chen X,
Chen X, Dong XC and Yin XM: Pharmacological promotion of autophagy
alleviates steatosis and injury in alcoholic and non-alcoholic
fatty liver conditions in mice. J Hepatol. 58:993–999. 2013.
View Article : Google Scholar : PubMed/NCBI
|
|
98
|
Li G, Sun L, Xin C, Hao T, Kharel P,
Manning AC, O'Connor CL, Moore H, Lei S, Gokulnath P, et al: A
hypoxia-responsive tRNA-derived small RNA confers renal protection
through RNA autophagy. Science. 389:eadp53842025. View Article : Google Scholar : PubMed/NCBI
|
|
99
|
Zhu J, Cheng M and Zhao X: A tRNA-derived
fragment (tRF-3001b) aggravates the development of nonalcoholic
fatty liver disease by inhibiting autophagy. Life Sci.
257:1181252020. View Article : Google Scholar : PubMed/NCBI
|
|
100
|
Zhu J, Wen Y, Zhang Q, Nie F, Cheng M and
Zhao X: The monomer TEC of blueberry improves NASH by augmenting
tRF-47-mediated autophagy/pyroptosis signaling pathway. J Transl
Med. 20:1282022. View Article : Google Scholar : PubMed/NCBI
|
|
101
|
Willemin G, Mange F, Praz V, Lorrain S,
Cousin P, Roger C, Willis IM and Hernandez N: Contrasting effects
of whole-body and hepatocyte-specific deletion of the RNA
polymerase III repressor Maf1 in the mouse. Front Mol Biosci.
10:12978002023. View Article : Google Scholar : PubMed/NCBI
|
|
102
|
Raptis D, Kolli ST, Agarwal S, Komminni
PK, Bhattarai P, Hablani P, Kumar R, Das P, McIntosh M, Kladas M,
et al: Extracellular RNAs in liquid biopsy: Applications in MASLD
and MASH diagnosis and monitoring. Diagnostics (Basel).
15:23462025. View Article : Google Scholar : PubMed/NCBI
|
|
103
|
Roychowdhury S, McMullen MR, Pritchard MT,
Hise AG, van Rooijen N, Medof ME, Stavitsky AB and Nagy LE: An
early complement-dependent and TLR-4-independent phase in the
pathogenesis of ethanol-induced liver injury in mice. Hepatology.
49:1326–1334. 2009. View Article : Google Scholar : PubMed/NCBI
|
|
104
|
Zhong F, Hu Z, Jiang K, Lei B, Wu Z, Yuan
G, Luo H, Dong C, Tang B, Zheng C, et al: Complement C3 activation
regulates the production of tRNA-derived fragments Gly-tRFs and
promotes alcohol-induced liver injury and steatosis. Cell Res.
29:548–561. 2019. View Article : Google Scholar : PubMed/NCBI
|
|
105
|
Wang Y, Guan Y, Feng D, Maccioni L, Parra
MA, Peiffer B, Mackowiak B, Kuwabara T, Mori K, Mukoyama M, et al:
Infiltrating macrophages replace Kupffer cells and play diverse
roles in severe alcohol-associated hepatitis. Cell Mol Immunol.
22:1262–1275. 2025. View Article : Google Scholar : PubMed/NCBI
|
|
106
|
Tang Y, Zhou H, Pan X, Zhong Z, Liu H and
Guo Y: Arrestin domain containing 3 promotes alcohol-induced liver
steatosis by reducing stearoyl-CoA desaturase-1 ubiquitinated
degradation. Metabolism. 167:1561752025. View Article : Google Scholar : PubMed/NCBI
|
|
107
|
Ma Q, Huang S, Li MY, Luo QH, Chen FM,
Hong CL, Yan HH, Qiu J, Zhao KL, Du Y, et al: Dihydromyricetin
regulates the miR-155-5p/SIRT1/VDAC1 pathway to promote liver
regeneration and improve alcohol-induced liver injury.
Phytomedicine. 139:1565222025. View Article : Google Scholar : PubMed/NCBI
|
|
108
|
Cho H, Lee W, Kim GW, Lee SH, Moon JS, Kim
M, Kim HS and Oh JW: Regulation of La/SSB-dependent viral gene
expression by pre-tRNA 3′ trailer-derived tRNA fragments. Nucleic
Acids Res. 47:9888–9901. 2019. View Article : Google Scholar : PubMed/NCBI
|
|
109
|
Si J, Zou Y, Gao Y, Chen J, Jiang W, Shen
X, Zhu C and Yao Q: tRF-3a-Pro: A transfer RNA-derived small RNA as
a novel biomarker for diagnosis of hepatitis B virus-related
hepatocellular carcinoma. Cell Prolif. 58:e700062025. View Article : Google Scholar : PubMed/NCBI
|
|
110
|
Testoni B, Scholtès C, Plissonnier ML,
Paturel A, Berby F, Facchetti F, Villeret F, Degasperi E, Scott B,
Hamilton A, et al: Quantification of circulating HBV RNA expressed
from intrahepatic cccDNA in untreated and NUC treated patients with
chronic hepatitis B. Gut. 73:659–667. 2024. View Article : Google Scholar :
|
|
111
|
Skog J, Würdinger T, van Rijn S, Meijer
DH, Gainche L, Sena-Esteves M, Curry WT Jr, Carter BS, Krichevsky
AM and Breakefield XO: Glioblastoma microvesicles transport RNA and
proteins that promote tumour growth and provide diagnostic
biomarkers. Nat Cell Biol. 10:1470–1476. 2008. View Article : Google Scholar : PubMed/NCBI
|
|
112
|
Valadi H, Ekström K, Bossios A, Sjöstrand
M, Lee JJ and Lötvall JO: Exosome-mediated transfer of mRNAs and
microRNAs is a novel mechanism of genetic exchange between cells.
Nat Cell Biol. 9:654–659. 2007. View Article : Google Scholar : PubMed/NCBI
|
|
113
|
Li J, Fang J, Jiang X, Zhang Y, Vidal-Puig
A and Zhang CY: RNAkines are secreted messengers shaping health and
disease. Trends Endocrinol Metab. 35:201–218. 2024. View Article : Google Scholar : PubMed/NCBI
|
|
114
|
Pabst O, Hornef MW, Schaap FG, Cerovic V,
Clavel T and Bruns T: Gut-liver axis: Barriers and functional
circuits. Nat Rev Gastroenterol Hepatol. 20:447–461. 2023.
View Article : Google Scholar : PubMed/NCBI
|
|
115
|
Tilg H, Adolph TE and Trauner M: Gut-liver
axis: Pathophysiological concepts and clinical implications. Cell
Metab. 34:1700–1718. 2022. View Article : Google Scholar : PubMed/NCBI
|
|
116
|
He X, Li F, Bor B, Koyano K, Cen L, Xiao
X, Shi W and Wong DTW: Human tRNA-Derived Small RNAs modulate
host-oral microbial interactions. J Dent Res. 97:1236–1243. 2018.
View Article : Google Scholar : PubMed/NCBI
|
|
117
|
Diallo I, Ho J, Lalaouna D, Massé E and
Provost P: RNA sequencing unveils very small RNAs with potential
regulatory functions in Bacteria. Front Mol Biosci. 9:9149912022.
View Article : Google Scholar : PubMed/NCBI
|
|
118
|
Diallo I, Ho J, Lambert M, Benmoussa A,
Husseini Z, Lalaouna D, Massé E and Provost P: A tRNA-derived
fragment present in E. coli OMVs regulates host cell gene
expression and proliferation. PLoS Pathog. 18:e10108272022.
View Article : Google Scholar : PubMed/NCBI
|
|
119
|
Chen YM, Tang KT, Huang ST, Liu HJ and
Liao TL: tRF-His-GTG-1 promotes Salmonella survival through
modulation of lipid metabolism and immune signaling. Cell Commun
Signal. 23:4972025. View Article : Google Scholar : PubMed/NCBI
|
|
120
|
Capone F, Häseli SP, Liu L, Strocchi S,
Langenberg C, Lusis AJ, Pietzner M, Muoio DM, Rider OJ, Raman B, et
al: HFpEF and MASLD: Converging mechanisms and clinical
implications. Nat Rev Cardiol. 23:584–608. 2026. View Article : Google Scholar : PubMed/NCBI
|
|
121
|
Zhao S, Wang Y, Zhou L, Li Z and Weng Q:
Exploring the potential of tsRNA as biomarkers for diagnosis and
treatment of neurogenetic disorders. Mol Neurobiol. 62:8518–8539.
2025. View Article : Google Scholar : PubMed/NCBI
|
|
122
|
Zuo Y, Chen S, Yan L, Hu L, Bowler S,
Zitello E, Huang G and Deng Y: Development of a tRNA-derived small
RNA diagnostic and prognostic signature in liver cancer. Genes Dis.
9:393–400. 2021. View Article : Google Scholar : PubMed/NCBI
|
|
123
|
He C, Zheng S, Luo Y and Wang B: Exosome
theranostics: Biology and translational medicine. Theranostics.
8:237–255. 2018. View Article : Google Scholar : PubMed/NCBI
|
|
124
|
Zhu L, Li J, Gong Y, Wu Q, Tan S, Sun D,
Xu X, Zuo Y, Zhao Y, Wei YQ, et al: Exosomal tRNA-derived small RNA
as a promising biomarker for cancer diagnosis. Mol Cancer.
18:742019. View Article : Google Scholar : PubMed/NCBI
|
|
125
|
Xu W, Yu M, Wu Y, Jie Y, Li X, Zeng X,
Yang F and Chong Y: Plasma-derived exosomal SncRNA as a promising
diagnostic biomarker for early detection of HBV-related
acute-on-chronic liver failure. Front Cell Infect Microbiol.
12:9233002022. View Article : Google Scholar : PubMed/NCBI
|
|
126
|
Hashimoto S, Hasan MDN, Arif M, Nozaki N,
Husna AA, Furusawa Y, Sogawa T, Takahashi K, Kuramoto T, Noguchi A,
et al: Aberrantly expressed tRNA-Val fragments can distinguish
canine hepatocellular carcinoma from canine hepatocellular adenoma.
Genes (Basel). 15:10242024. View Article : Google Scholar : PubMed/NCBI
|
|
127
|
Yuan T, Huang X, Woodcock M, Du M, Dittmar
R, Wang Y, Tsai S, Kohli M, Boardman L, Patel T and Wang L: Plasma
extracellular RNA profiles in healthy and cancer patients. Sci Rep.
6:194132016. View Article : Google Scholar : PubMed/NCBI
|
|
128
|
Xu J, Chen B, Qi J, Wu J, Feng W, Jin K,
Bao H, Chen L and Wang F: Evaluation of serum hsa_tsr014055 as a
potential biomarker for diagnosis and prognosis of hepatocellular
carcinoma. Ann Med. 57:25289782025. View Article : Google Scholar : PubMed/NCBI
|
|
129
|
Jin K, Mao Z, Tang Y, Feng W, Ju S, Jing
R, Chen J and Zong W: tRF-23-R9J89O9N9:A novel liquid biopsy marker
for diagnosis of hepatocellular carcinoma. Clin Chim Acta.
572:1202612025. View Article : Google Scholar : PubMed/NCBI
|
|
130
|
Jin K, Wu J, Yang J, Chen B, Xu J, Bao H,
Zong W, Xie C, Chen L and Wang F: Identification of serum
tsRNA-Thr-5-0015 and combined with AFP and PIVKA-II as novel
biomarkers for hepatocellular carcinoma. Sci Rep. 14:288342024.
View Article : Google Scholar : PubMed/NCBI
|
|
131
|
Li X, Li Y, Yuan J, Zhang W, Xu T, Jing R
and Ju S: Serum tRF-33-RZYQHQ9M739P0J as a novel biomarker for
auxiliary diagnosis and disease course monitoring of hepatocellular
carcinoma. Heliyon. 10:e300842024. View Article : Google Scholar : PubMed/NCBI
|
|
132
|
Ma X, Chen B, Tang Y, Ju S, Jing R, Feng W
and Zong W: Exploring the clinical application and biological
function of novel tsRNA tsRNA-Asp-5-0002 in hepatocellular
carcinoma. Gene. 956:1494592025. View Article : Google Scholar : PubMed/NCBI
|
|
133
|
Zhan S, Yang P, Zhou S, Xu Y, Xu R, Liang
G, Zhang C, Chen X, Yang L, Jin F and Wang Y: Serum mitochondrial
tsRNA serves as a novel biomarker for hepatocarcinoma diagnosis.
Front Med. 16:216–226. 2022. View Article : Google Scholar : PubMed/NCBI
|
|
134
|
Collins GS, Dhiman P, Ma J, Schlussel MM,
Archer L, Van Calster B, Harrell FE Jr, Martin GP, Moons KGM, van
Smeden M, et al: Evaluation of clinical prediction models (part 1):
From development to external validation. BMJ. 384:e0748192024.
View Article : Google Scholar : PubMed/NCBI
|
|
135
|
Hall MK, Kea B and Wang R: Recognising
bias in studies of diagnostic tests part 1: Patient selection.
Emerg Med J. 36:431–434. 2019. View Article : Google Scholar : PubMed/NCBI
|
|
136
|
Zirnbauer R, Ammon D, Renner A, Hartman N,
Kalinina P, Starlinger P, Stremitzer S, Schwarz C, Kaczirek K,
Bergmann M, et al: Differential prognostic roles and clinical
implications of mitochondrial and genomic tRNA-derived fragments in
colorectal liver metastases. J Transl Med. 23:7862025. View Article : Google Scholar : PubMed/NCBI
|
|
137
|
Li YK, Yan LR, Wang A, Jiang LY, Xu Q and
Wang BG: RNA-sequencing reveals the expression profiles of tsRNAs
and their potential carcinogenic role in cholangiocarcinoma. J Clin
Lab Anal. 36:e246942022. View Article : Google Scholar : PubMed/NCBI
|
|
138
|
Huang P, Tu B, Liao HJ, Huang FZ, Li ZZ,
Zhu KY, Dai F, Liu HZ, Zhang TY and Sun CZ: Elevation of plasma
tRNA fragments as a promising biomarker for liver fibrosis in
nonalcoholic fatty liver disease. Sci Rep. 11:58862021. View Article : Google Scholar : PubMed/NCBI
|
|
139
|
Shi J, Zhang Y, Tan D, Zhang X, Yan M,
Zhang Y, Franklin R, Shahbazi M, Mackinlay K, Liu S, et al:
PANDORA-seq expands the repertoire of regulatory small RNAs by
overcoming RNA modifications. Nat Cell Biol. 23:424–436. 2021.
View Article : Google Scholar : PubMed/NCBI
|
|
140
|
Shi J and Zhang Y, Li Y, Zhang L, Zhang X,
Yan M, Chen Q and Zhang Y: Optimized identification and
characterization of small RNAs with PANDORA-seq. Nat Protoc.
20:3314–3338. 2025. View Article : Google Scholar : PubMed/NCBI
|
|
141
|
Lucas MC, Pryszcz LP, Medina R, Milenkovic
I, Camacho N, Marchand V, Motorin Y, Ribas de Pouplana L and Novoa
EM: Quantitative analysis of tRNA abundance and modifications by
nanopore RNA sequencing. Nat Biotechnol. 42:72–86. 2024. View Article : Google Scholar :
|
|
142
|
Katopodi XL, Begik O and Novoa EM: Toward
the use of nanopore RNA sequencing technologies in the clinic:
Challenges and opportunities. Nucleic Acids Res. 53:gkaf1282025.
View Article : Google Scholar
|
|
143
|
Behrens A, Rodschinka G and Nedialkova DD:
High-resolution quantitative profiling of tRNA abundance and
modification status in eukaryotes by mim-tRNAseq. Mol Cell.
81:1802–1815.e7. 2021. View Article : Google Scholar : PubMed/NCBI
|
|
144
|
Rao J, Xia L, Li Q, Ma N, Li X, Li J, Zhu
L, Zhao P, Zeng Y, Zhou S, et al: A 6-tsRNA signature for early
detection, treatment response monitoring, and prognosis prediction
in diffuse large B cell lymphoma. Blood Cancer J. 15:792025.
View Article : Google Scholar : PubMed/NCBI
|
|
145
|
Li Z, Zhou B, Su M, Ren H, Li J, Wang L
and Zhang L: Quantitative differential analysis of tsRNAs for
forensic body fluid identification: RT-qPCR-based discrimination
derived from epithelial cell fluids screening. Forensic Sci Int
Genet. 80:1033382026. View Article : Google Scholar
|
|
146
|
Yang W, Liu Y, Wang J, Liu T, Tian T, Li
T, Ding L, Chen W, Wang H, Zhu J, et al: Optimizing of a suitable
protocol for isolating tissue-derived extracellular vesicles and
profiling small RNA patterns in hepatocellular carcinoma. Liver
Int. 44:2672–2686. 2024. View Article : Google Scholar : PubMed/NCBI
|
|
147
|
Zhang X, Shi J, Thakore P, Gonzales AL,
Earley S, Chen Q, Zhou T and Feng Earley Y: Mitochondrial small RNA
alterations associated with increased lysosome activity in an
Alzheimer's disease mouse model uncovered by PANDORA-seq. Int J Mol
Sci. 26:30192025. View Article : Google Scholar : PubMed/NCBI
|
|
148
|
Li P, Ying S, Zou Y, Wang X, Zhang R,
Huang C, Dai M, Xu K, Feng G, Li X, et al: NSun2-Mediated tsRNAs
alleviate liver fibrosis via FAK dephosphorylation. Cell Prolif.
58:e700582025. View Article : Google Scholar : PubMed/NCBI
|
|
149
|
Yang C, Chen H, Huang X, Li Y, Wen S, Zhou
L and Yuan X: BMSC-derived extracellular vesicles affect
gluconeogenesis and lipogenesis by releasing 5'-tRF-GlyCCC to
improve MAFLD insulin sensitivity. Cell Biol Toxicol. 42:192026.
View Article : Google Scholar : PubMed/NCBI
|
|
150
|
Zhu J, Tang W, Wu X, Mu M, Zhang Q and
Zhao X: Tectorigenin improves metabolic dysfunction-associated
steatohepatitis by down-regulating tRF-3040b and promoting
mitophagy to inhibit pyroptosis pathway. Biochem Biophys Res
Commun. 720:1501182024. View Article : Google Scholar : PubMed/NCBI
|
|
151
|
Zhu J, Wu X, Mu M, Zhang Q and Zhao X:
TEC-mediated tRF-31R9J regulates histone lactylation and
acetylation by HDAC1 to suppress hepatocyte ferroptosis and improve
non-alcoholic steatohepatitis. Clin Epigenetics. 17:92025.
View Article : Google Scholar : PubMed/NCBI
|
|
152
|
Dilliard SA and Siegwart DJ: Passive,
active and endogenous organ-targeted lipid and polymer
nanoparticles for delivery of genetic drugs. Nat Rev Mater.
8:282–300. 2023. View Article : Google Scholar : PubMed/NCBI
|
|
153
|
Mo J, Shi H, Ren K, Chen Z and Sheng X:
Emerging biomedical applications of herbal extracts-based
biomaterials. Biointerphases. 20:0408022025. View Article : Google Scholar : PubMed/NCBI
|
|
154
|
Zhou Z, Chen B, Liu J, Feng W, Ren Z, Jin
K, Li Y, Ju L, Chen L, Zhu G and Wang F: tRNA-Derived small RNA
accelerates tumorigenesis through crosstalk with tumor-associated
macrophages, and downregulation with cell membrane-modified polymer
nanoparticles enables treatment response. ACS Appl Mater
Interfaces. 17:41610–41625. 2025. View Article : Google Scholar : PubMed/NCBI
|
|
155
|
Du J, Huang T, Zheng Z, Fang S, Deng H and
Liu K: Biological function and clinical application prospect of
tsRNAs in digestive system biology and pathology. Cell Commun
Signal. 21:3022023. View Article : Google Scholar : PubMed/NCBI
|
|
156
|
Tuorto F, Liebers R, Musch T, Schaefer M,
Hofmann S, Kellner S, Frye M, Helm M, Stoecklin G and Lyko F: RNA
cytosine methylation by Dnmt2 and NSun2 promotes tRNA stability and
protein synthesis. Nat Struct Mol Biol. 19:900–905. 2012.
View Article : Google Scholar : PubMed/NCBI
|
|
157
|
Blanco S, Bandiera R, Popis M, Hussain S,
Lombard P, Aleksic J, Sajini A, Tanna H, Cortés-Garrido R, Gkatza
N, et al: Stem cell function and stress response are controlled by
protein synthesis. Nature. 534:335–340. 2016. View Article : Google Scholar : PubMed/NCBI
|
|
158
|
Chen Z, Qi M, Shen B, Luo G, Wu Y, Li J,
Lu Z, Zheng Z, Dai Q and Wang H: Transfer RNA demethylase ALKBH3
promotes cancer progression via induction of tRNA-derived small
RNAs. Nucleic Acids Res. 47:2533–2545. 2019. View Article : Google Scholar :
|
|
159
|
Lang X, Luo J, Li F, Zeng J, Liu G, Yu C,
Guo Y, Xu H, Liu Q and Cao Y: FungiSNC: An integrated database for
fungi small non-coding RNAs based on high-throughput sequencing. J
Adv Res. 84:187–201. 2026. View Article : Google Scholar :
|
|
160
|
Liang Y, Qi W, Dong X and Li J: Archaeal
RNA processing and regulation: Expanding the functional landscape.
Microbiol Mol Biol Rev. 89:e00318242025. View Article : Google Scholar : PubMed/NCBI
|
