Transfer RNA-derived small RNAs (tsRNAs) in gastric cancer

Transfer RNA-derived small RNAs (tsRNAs) are newly discovered noncoding RNAs (ncRNAs). According to the specific cleavage of nucleases at different sites of tRNAs, the produced tsRNAs are divided into tRNA-derived stress-inducible RNAs (tiRNAs) and tRNA-derived fragments (tRFs). tRFs and tiRNAs have essential biological functions, such as mRNA stability regulation, translation regulation and epigenetic regulation, and play significant roles in the occurrence and development of various tumors. Although the roles of tsRNAs in some tumors have been intensively studied, their roles in gastric cancer are still rarely reported. In this review, we focus on recent advances in the generation and classification of tsRNAs, their biological functions, and their roles in gastric cancer. Sixteen articles investigating dysregulated tsRNAs in gastric cancer are summarized. The roles of 17 tsRNAs are summarized, of which 9 were upregulated and 8 were downregulated compared with controls. Aberrant regulation of tsRNAs was closely related to the main clinicopathological factors of gastric cancer, such as lymph node metastasis, Tumor-Node-Metastasis (TNM) stage, tumor size, and vascular invasion. tsRNAs participate in the progression of gastric cancer by regulating the PTEN/PI3K/AKT, MAPK, Wnt, and p53 signaling pathways. The available literature suggests the potential of using tsRNAs as clinical biomarkers for gastric cancer diagnosis and prognosis and as therapeutic targets for gastric cancer treatment.


Introduction
Gastric cancer (GC), the fourth most common cause of tumor-associated death, poses a severe threat to human health worldwide, especially in East Asia (1). The initial symptoms of gastric cancer are not specific or obvious, so most patients have already reached an advanced stage at the time of diagnosis and thus miss the optimal treatment period. Therefore, finding biomarkers that can identify early GC and new targets for GC treatment is of great significance.
Transfer RNA-derived small RNAs (tsRNAs) are newly discovered noncoding RNAs (ncRNAs) that were once mistakenly considered random degradation products of transfer RNAs (tRNAs). In recent years, with the development of high-throughput sequencing technology and advances in bioinformatics analysis, tsRNAs have received increasing attention in cancer research (2,3). Based on the specific cleavage at different sites of precursor tRNAs or mature tRNAs, the generated tsRNAs are classified into tRNA-derived stress-induced RNAs (tiRNAs) and tRNA-derived fragments (tRFs). Based on the splicing site within the tRNA, tiRNAs can be classified into 5′-tiRNAs and 3′-tiRNAs. tRFs can be classified into tRF-1, tRF-2, tRF-3, tRF-5, and i-tRF. Studies have shown that tRFs and tiRNAs have essential biological functions, such as RNA silencing, translation regulation and epigenetic regulation, and play significant roles in the occurrence and development of various tumors (4,5). Although the roles of tsRNAs in some tumors have been intensively studied, their roles in GC are still rarely reported.
In this review, we focus on the recent advances in the generation and classification of tsRNAs, their biological functions, and their roles in gastric cancer. We also discuss the potential of using tsRNAs as clinical biomarkers for cancer diagnosis and prognosis and as therapeutic targets for cancer treatment.
2 Biogenesis and discovery of tsRNAs 2.1 Classification of tRFs and tiRNAs tRNAs, which have a secondary cloverleaf structure containing three hairpin loops: a D loop, an anti-codon loop, and a TyC loop, play important roles in protein biosynthesis. In recent years, precursor tRNAs, also called mature tRNAs, have been shown to be specifically cleaved to produce a new class of ncRNAs, namely, tsRNAs, which can be divided into tiRNAs and tRFs according to their cleavage sites (5). With the application and development of RNA high-throughput sequencing and analysis, more and more tsRNAs have been discovered (6). The high-throughput sequencing approaches work well for more types of RNAs, such as messenger RNA (mRNA), long ncRNA, microRNA (miRNA), or fragments derived from ribosomal RNA, small nuclear RNA, and small nucleolar RNA (7). Recently, a novel tsRNA-and ribosomal RNA-derived small RNAs (rsRNAs) -friendly small ncRNA sequencing method named PANDORA-Seq (panoramic RNA display by overcoming RNA modification aborted sequencing) has been established, which expands our knowledge on the biogenesis and functions of tsRNAs and rsRNAs, as well as the regulatory roles of various RNA modifications (8).

tiRNAs
tiRNAs, with lengths of 31-40 nucleotides (nt), are generated by cleaving of the anticodon loop of the mature tRNA by angiogenin (ANG) under stress conditions, particularly nutritional deficiency, hypoxia, heat shock, and oxidative stress (9)(10)(11). Therefore, tiRNAs are also called tRNA-derived stress-inducible RNAs and tRNA halves. Based on whether the 5′ or 3′ sequencer of the anticodon cleavage position is included, tiRNAs are classified into two basic types: 5′-tiRNAs (including the 5′ end of the mature tRNA to the terminus of the anticodon loop) and 3′-tiRNAs (including the anticodon loop to the 3′ end of the mature tRNA) ( Figure 1) (9,11). According to a recent study, it was found that ANG is not the only ribonuclease to produce tiRNAs because the production of some tiRNAs is dependent on RNase L cleavage (12). In addition, the other type of tRNA halves called sex hormone-dependent tRNA-derived RNAs (SHOT-RNAs), which are not induced by various stress stimuli but rather by hormones and are cleaved by ANG, can be highly expressed in hormone receptor-positive breast and prostate cancer cells (13).
Currently, there are differences in the nomenclature of tsRNAs in different databases and studies (16,20,29,30). In the tRFdb database, tRFs of each organism are named in the order in which they were identified, with the first tRF-5 named 5001, the first tRF-3 named 3001, and the first tRF-1 named 1001. Also, the tRF-5s with lengths of 15, 22 and 31 nt are attached with "a", "b" or "c", respectively, and the tRF-3s with lengths of 18 and 22 nt are attached with "a" and "b", respectively (e.g., tRF-3019a, tRF-3017A) (16). The TDRmapper database provides a name for each tsRNA containing three components that indicate the parent tRNA "family" from which it is derived, the size, and the region in the mature or pre-tRNA from which it is derived (17). MINTbase v2.0 derives a unique license plate name for each tRF based on the sequence (e.g., tRF-19-3L7L73JD) (20). In addition, in some studies, tRFs are also named by their length (e.g., tRF-25) (31,32).  The main classification of tRNA-derived fragments (tRFs) and tRNA halves (tiRNAs). In the figure, the tRNA sources of tRFs and tiRNAs are shown, with the color of the tRNA source matching that of the ncRNA product (9).
In conclusion, scholars have continued to study databases on tsRNAs in recent years, discovering an increasing number of tsRNAs and exploring their mechanisms of action. However, establishing a standardized nomenclature rule for tiRNAs and tRFs has faced several problems, including the extensive chemical modifications of tRNAs, difficulty in obtaining the exact origin of tsRNAs, and the fact that only a few tsRNAs have been experimentally validated (30).
In order to facilitate understanding and memory, a new and consistent naming method based on the structure and sequence of tsRNAs will be adopted in this paper. Taking "tRF -+1: T18 Arg ACG-3-M1-17: C>A" as an example, the name can be divided into 5 parts: tRF, +1: T18, Arg ACG-3, M1, 17: C>A. The first component of the name indicates the types of tsRNAs, which can be divided into tRFs and tiRNAs, and "tsRNA" means those not included in the databases. The second component of the name indicates the region in the mature or pre-tRNA from which the read is derived, which includes three situations that "1:18", "+1:T18" and "-1:L18", representing tsRNAs alignment to the 1:18 base of mature tRNA, to the 1:18 base of pre-tRNA 3'tailer, and to the 1:18 base of pre-tRNA 5'leader, respectively. The third part of the name, "Arg ACG-3", where "Arg" is short for the tRNA amino acid, "ACG" is the anticodon and "3" is a unique identifier for each tRNA family, represents the tRNA from which tsRNA is derived. The fourth component of the name, "M1", refers to the comparison of the tsRNA to several tRNAs. If the tsRNA is compared to three tRNAs, it is written as "M3". The last component of the name is "17:C> A", where "17" indicates the mutation of the base after base 17 on the tsRNA (i.e., base 18) and "C> A" means that the corresponding base on the tRNA is "C", while the corresponding base on the tsRNA is "A".

Biological functions of tsRNAs
Studies have shown that tsRNAs have a wide range of biological functions, including regulating the stability of mRNA, translation regulation, and epigenetic regulation (2)(3)(4)15). The biological functions of tsRNAs are very complex and require further elucidation. The biological functions and molecular mechanisms studied more thoroughly in recent years are summarized as follows.

Regulating the stability of mRNA
tsRNAs can regulate the stability of mRNAs. On the one hand, some tsRNAs exhibit the same sequences as miRNAs with similar mechanisms of action (15). Huang et al. found that tRF derived from tRNALeu was comparable in sequence to miR-1280 derived from pre-miRNA and inhibited the Notch signaling pathway by directly interacting with the JAG2 mRNA 3′ untranslated region (UTR), thereby inhibiting the proliferation of colorectal cancer cells (33). Some tsRNAs form an RNA-induced silencing complex (RISC) with Argonaute (AGO) proteins in a manner similar to how miRNAs silence mRNA, suggesting that tsRNAs may play a major role in RNA silencing (34). On the other hand, tRFs can bind to RNA-binding proteins (RBPs) and posttranscriptionally regulate gene expression, and RBPs interact with targeted RNAs to control their stability (15). YBX1 is an RBP that is highly overexpressed in several types of cancers. Goodarzi et al. found that under the induction of hypoxic stress in breast cancer cells, some tRFs derived from tRNAAsp, tRNAGlu, tRNAGly and tRNATyr can suppress the stability of multiple oncogenic transcripts by displacing their 3' UTR from the RBP YBX1 and eventually inhibit the proliferation of breast cancer cells (35).

Translation regulation
tsRNAs can regulate translation levels. A recent study found that LeuCAG3'tsRNA enhances translation by promoting ribosome biogenesis (36). Keam et al. also proposed that the 5' tRF Gln19 interacts with the human multisynthetase complex (MSC) and increases ribosomal and poly(A)-binding protein translation (37). On the other hand, tsRNAs can inhibit translation by interfering with translation initiation and elongation. Lyons et al. found that G4-tiRNA disrupts the assembly of the 40S ribosomal subunit by directly targeting the HEAT1 structural domain of eIF4G, a major scaffolding protein necessary for translation initiation, ultimately inhibiting translation initiation (38). In addition, Gebetsberger et al. showed that a tRF-5 derived from a valine tRNA-derived fragment (Val-tRF) under certain stress conditions in the halophilic archaeon Haloferax volcanii competes with mRNA for binding to the small ribosomal subunit, thus affecting translation initiation and inhibiting subsequent protein biosynthesis (39).

Epigenetic regulation
Some studies have shown that tsRNAs can act as epigenetic regulators to maintain genome stability by targeting and inhibiting transposable elements (TEs) (40). TEs are DNA sequences that can "move" from one location in the genome to another, and the movement of TEs driven by intact and active transposons is highly mutagenic and must be tightly controlled (41). Therefore, the transcription of TEs is often repressed by epigenetic marks, such as histone modification and DNA methylation (41). Studies have shown that some tRF-3s of 18 and 22 nt in length derived from mature mouse tRNAs could match endogenous retroviruses (ERVs) o f l o n g t e r m i n a l r e p e a t s ( L T R s ) , a n d 2 2 n t t R F s posttranscriptionally silenced coding-competent ERVs, while 18 nt tRFs specifically interfered with reverse transcription and retrotransposon mobility (42,43). In addition, Chen et al. revealed that injecting tsRNA fractions from the sperm of male mice fed a high-fat diet into normal zygotes led to metabolic disorders in F1 offspring and altered the gene expression of metabolic pathways in the early embryos and islets of F1 offspring, which was unrelated to DNA methylation at CpG enrichment regions, indicating that sperm tsRNAs represent a paternal epigenetic factor that may mediate the intergenerational inheritance of diet-induced metabolic disorders (44). Zhang et al. revealed that deletion of a mouse tRNA methyltransferase, DNMT2, altered the sperm small RNA expression profile, including levels of tsRNAs and rsRNAs, and abolished sperm small ncRNAmediated transmission of high-fat-diet-induced metabolic disorders to offspring (45). Recently, Boskovic et al. discovered a specific tRF-5, tRF-Gly-GCC, which plays a role in the production of a variety of ncRNAs. The regulation of U7 snRNA by tRF-Gly-GCC modulates heterochromatin-mediated transcriptional repression of MERVL elements by supporting the production of a sufficient amount of histone proteins (46).

Roles of tsRNAs in gastric cancer
Growing evidence indicates that tsRNAs play essential roles in tumor development and progression, and their dysregulated expression has some clinical value. In this review, using PubMed, we identified 16 articles published between 2015 and 2022 on dysregulated tsRNAs in GC, involving a total of 17 tsRNAs, of which 9 were upregulated and 8 were downregulated. The potential value of tsRNAs in diagnosing and treating GC is now comprehensively described according to their potential clinical value and the degree of research on their mechanisms. Furthermore, their underlying mechanisms of action in GC were analyzed in depth (Tables 2, 3).

The roles of tsRNAs as biomarkers for cancer diagnosis and prognosis
The tsRNAs reported in the literature, whether upregulated or downregulated, have potential clinical value.

Abnormally high expression of tsRNAs as biomarkers in GC
Huang et al. discovered that tsRNA-32:62-chrM.tRNA2-ValTAC exists stably in GC cells, tissues, and serum (47). The levels of tsRNA-32:62-chrM.tRNA2-ValTAC in serum, tumor tissues, and GC cell lines are considerably higher than those in samples from normal physical examination populations and gastritis patients, para-cancerous tissues, and normal gastric epithelial cells. The study found that the expression of serum tsRNA-32:62-chrM.tRNA2-ValTAC in GC patients decreased significantly after the operation. The survival time of patients with high expression of this tRF was significantly shorter than that of patients with low expression. Its high expression is positively correlated with tumor invasion, vascular invasion, Tumor-Node-Metastasis (TNM) stage, and lymph node metastasis. On the other hand, compared with conventional markers, such as CEA, CA199 and CA724, tsRNA-32:62-chrM.tRNA2-ValTAC has higher sensitivity and specificity in the differentiation and diagnosis of malignant and benign gastric tumors. The combined use of tsRNA-32:62-chrM.tRNA2-ValTAC with CEA, CA199 and CA724 has more diagnostic potency and good clinical application potential (47).
Gu et al. revealed that the serum levels of tRF-1:29-Gln-TTG-1-M3 show a gradient change among GC patients, gastritis patients, and healthy donors (48). The increased tRF-1:29-Gln-TTG-1-M3 levels are positively linked to differentiation grade, T stage, lymph node status, and TNM stage. TRF-1:29-Gln-TTG-1-M3 belongs to tRF-5, which is mainly located in the nucleus, and is continuously secreted in tumor cells with good stability and specificity. Receiver operating characteristic (ROC) analysis showed that the serum expression level of tRF-1:29-Gln-TTG-1-M3 can significantly distinguish GC patients from healthy donors or gastritis patients. The sensitivity of tRF-1:29-Gln-TTG-1-M3, CEA, and CA199 in the joint diagnosis of GC is 90%, while that of tRF-1:29-Gln-TTG-1-M3 and CA724 in the joint diagnosis of GC is 82%, which are both higher than the sensitivity of a single tumor marker. Meanwhile, through the analysis of the postoperative survival curve and the expression level of tRF-1:29-Gln-TTG-1-M3 in GC patients, investigators found that tRF-1:29-Gln-TTG-1-M3 can be monitored dynamically in GC patients after the operation. In addition, there is no significant correlation between Helicobacter pylori infection and the expression level of tRF-1:29-Gln-TTG-1-M3 (48).
Zhang et al. found that the differential expression of tRF-1:23-Val-CAC-2 in the serum of GC patients is higher than that of gastritis patients and healthy donors, which can clearly distinguish GC patients from gastritis patients and healthy people (49). The investigators found that serum tRF-1:23-Val-CAC-2 expression levels are significantly reduced in GC patients after the operation, and low expression of the tRF is associated with a prolonged overall survival (OS). High expression is positively correlated with T stage, lymph node metastasis, TNM stage, and neurological/vascular invasion. ROC analysis showed that tRF-1:23-Val-CAC-2 is more effective for early GC diagnosis than the conventional GC biomarkers CEA, CA199 and CA724, and the combination of the tRF and the conventional biomarkers further improves the diagnostic efficiency (49).
Not clear yet. High levels promote proliferation and invasion and inhibits apoptosis in GC cells.
It binds to the chaperone molecule EEF1A1, mediates its transport into the nucleus and promotes its interaction with MDM2, thus inhibiting the downstream molecular pathway of p53 and promoting GC progression.

Abnormally low expression of tsRNAs as biomarkers in GC
Zhu et al. found that the expression of tiRNA-50:84-Glu-TTC-2 is downregulated in GC tissues, plasma and GC cell lines, and its level is closely related to tumor size (53). The AUCs of tiRNA-50:84-Glu-TTC-2 in tissue and plasma were 0.779 and 0.835, respectively. When tissues and plasma were used in combination, tiRNA-50:84-Glu-TTC-2 showed a sensitivity, specificity, and AUC of 84.7%, 92.8%, and 0.915, respectively. The OS of patients with lower expression of tiRNA-50:84-Glu-TTC-2 was considerably lower than that of patients with higher expression. Univariate analysis indicated that TNM stage, lymphatic metastasis, and tiRNA-50:84-Glu-TTC-2 expression in tissues are associated with OS, while multivariate analysis revealed that lymphatic metastasis is a detrimental factor for OS (53).
tsRNAs are stable and highly enriched in plasma with good sensitivity and specificity. As shown in Table 4, tsRNAs have higher diagnostic potency than conventional biomarkers, and tsRNAs in combination with conventional biomarkers show even more significant diagnostic potency. In summary, recent studies found that tsRNA-32:62-chrM.tRNA2-ValTAC, tRF-1:29-Gln-TTG-1-  Table 4). The differential expression of tsRNAs was closely correlated with the clinicopathological factors of GC, with tsRNAs being highly correlated with lymph node metastasis, TNM stage, tumor size, and vascular invasion (Figure 2). In conclusion, tsRNAs could serve as novel biomarkers for GC diagnosis.
Wang et al. demonstrated that tRF-1:24-chrM.Gln-TTG expression is significantly downregulated in GC tissues, and animal experiments showed that low levels of tRF-1:24-chrM.Gln-TTG significantly promote tumor growth capacity in mice (55). tRF-1:24-chrM.Gln-TTG can function as a miRNA-like fragment, bind to the AGO2 protein, and directly silence the expression of GPR78, a member of the G-protein-coupled receptor superfamily, by complementing the 3'UTR of GPR78 mRNA, thereby inhibiting the proliferation, invasion and metastasis of GC cells and  (56). The investigators discovered that tRF-1:24-chrM.Gln-TTG further inhibits GC cell proliferation, migration and invasion by downregulating the expression of CCND2, FZD3 and VANGL1 to participate in the Wnt pathway while promoting apoptosis. In addition, tRF-1:24-chrM.Gln-TTG can significantly enrich MAPK. It was speculated that it may participate in the critical process of tumor progression through the p38 MAPK signaling pathway and may also participate in the occurrence and metastasis of GC by targeting organs, lymphatic circulation, Th1/Th2 cell differentiation and inflammation (56). Zheng et al. found that a 5′-tiRNA named tiRNA-1:34-Val-CAC-2 is significantly downregulated in GC cells and tissues and inhibits GC cell proliferation and metastasis (57). The upregulated tiRNA-1:34-Val-CAC-2 promotes its interaction with the AGO2 protein to silence the expression of LRP6, an essential membrane protein receptor of the Wnt/b-catenin signaling pathway, by targeting LRP6 mRNA in a miRNA-like manner and further inhibits the metastasis and proliferation of GC cells and promotes the apoptosis of GC cells through the Wnt/b-catenin signaling pathway (57). Xu et al. disclosed that tRF-+1:T17-Glu-TTC-2-2 is significantly downregulated in GC tissues and cells, and animal experiments showed that tRF-+1:T17-Glu-TTC-2-2 could significantly reduce the capacity of tumor growth in mice (58). The upregulated tRF-+1: T17-Glu-TTC-2-2 inhibits the MAPK signaling pathway by downregulating the expression of ERK1/2, JNK and p38, thus significantly inhibiting the proliferation, migration and invasion of GC cells both in vitro and in vivo (58).
Xu et al. also found that tRF-+1:T15-Val-CAC-1 is significantly expressed at low levels in GC cell lines and tissues, and animal experiments showed that tRF-+1:T15-Val-CAC-1 could inhibit the proliferation of xenograft tumors in mice (59). tRF-+1:T15-Val-CAC-1 regulates the classical MAPK signaling pathway and inhibits the proliferation of GC cells by interacting with the AGO2 protein and then silencing the expression of the oncogenic gene CACNA1d (59).
Shen et al. also found that tiRNA-1:33-Gly-GCC-1 is downregulated in cell lines and plasma of GC patients (61). The upregulated expression of tiRNA-1:33-Gly-GCC-1 inhibits GC cell proliferation by arresting GC cells at the G0/G1 phase, and it also inhibits GC cell migration and promotes apoptosis (61).
In summary, tsRNAs play an essential role in tumorigenesis and development ( Figure 3). We found that tRF-58:75-Ala-AGC-1, tRF-58:76-Val-TAC-1-M2, tRF-+1:T15-Val-CAC-1, tRF-1:24-chrM.Gln-TTG and tiRNA-1:34-Val-CAC-2 have a common feature, that is, they can bind to the AGO2 protein as miRNAlike fragments to silence the expression of target genes and affect the progression of GC (Figure 3). Among them, tRF-58:75-Ala-AGC-1 and tRF-58:76-Val-TAC-1-M2 specifically bind to the 3'UTR of FBXO47 and NELL2 to form an RISC by interacting with AGO2 and negatively regulate FBXO47 and NELL2 expression to promote GC progression, respectively. tRF-+1:T15-Val-CAC-1 and tRF-1:24-chrM.Gln-TTG complement the 3'UTR of CACNA1d and GPR78 mRNA, and interact with the AGO2 protein and then silence the expression of CACNA1d and GPR78 to inhibit GC progression, respectively. It has been proved that tiRNA-1:34-Val-CAC-2 is regulated by LRP6 by binding to AGO2, and a 3'UTR regulatory site has also been detected, but the correlation between tiRNA-1:34-Val-CAC-2 and 3'UTR of LRP6 has not been explained. Additionally, there is another different mode of action. tRF-60:76-Val-CAC-2 directly binds to the chaperone molecule EEF1A1 and promotes its interaction with MDM2 to inhibit the downstream molecular pathway of p53 and promote GC progression. The researchers only found the effect of tsRNA-5:23-tRNA-Val-AAC-1-M7 and tiRNA-1:33-Gly-GCC-1 on the biological function of gastric cancer and did not explore its regulatory mechanism. Moreover, studies about tsRNA-1:18-tRNA-Val-AAC-1-M8 and tRF-+1:T17-Glu-TTC-2-2 also only discovered the tsRNAs can regulate some important signaling pathways and did not reveal the mechanisms of their action. The other tsRNAs related to GC in our paper were only verified as biomarkers, without in-depth investigation of their mechanisms. There are also some interesting findings that tRF-3a is the main upregulated type of tsRNA in GC, while tRF-5a and tRF-5c are the main downregulated types, suggesting that tRF-3a may play an essential role in the development of GC (52). However, more data is needed to confirm this hypothesis due to the inadequacy of currently available data. These studies suggest that tsRNAs may serve as promising therapeutic targets and biomarkers of GC. Further exploration of tsRNA-related pathways is necessary to establish the GC regulatory network of tsRNAs to help clinicians better diagnose and treat GC. Expression of tsRNAs as biomarkers and correlation with clinicopathological factors. Summarizing the upregulated and downregulated tsRNAs as biomarkers in gastric cancer, the abnormal expression of tsRNAs is closely related to the main clinicopathologic factors of gastric cancer, such as lymph node metastasis, TNM stage, tumor size, and vascular invasion. TNM, Tumor-Node-Metastasis.

Summary and perspectives
With the in-depth exploration of the biological functions and mechanisms of tsRNAs, they are increasingly considered therapeutic targets and new biomarkers for cancer (53). In this report, we review the recent progress in the generation and classification of tsRNAs, their biological functions and their roles in GC and summarize the 17 tsRNAs that have been identified to be upregulated and downregulated in GC, providing evidence to support the clinical value of tsRNAs in GC. However, there are several limitations of the existing studies. First, there are differences in the nomenclature of tsRNAs in different databases and studies, which is an obstacle for summarizing tsRNAs; thus, a standardized nomenclature rule and a high-coverage database are needed for a more concise understanding of tsRNAs. Second, the mechanism of tsRNA dysregulation in GC needs to be studied more deeply, especially in regards to tiRNAs, the data for which are insufficient; the current research is mostly focused on miRNA-like mechanisms of action. Third, the involved signaling pathways only include the Wnt/b-catenin, MAPK, PTEN/PI3K/AKT and p53 signaling pathways. Many studies are needed to confirm the existence of other pathways and fully understand the regulatory network of tsRNAs in GC. Finally, chemotherapy resistance is one of the challenges of GC clinical treatment, and there are no reports of tsRNAs involved in GC resistance mechanisms in the literature. It is still urgent to study whether tsRNAs are involved in drug resistance mechanisms. In conclusion, tsRNAs bring new hope to GC diagnosis and treatment, but further research is needed before they can be put into clinical applications.

Data Availability Statement
Data sharing is not applicable to this article as no new data were created or analyzed in this study.

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