tRNA-derived fragment tRF-Glu49 inhibits cell proliferation, migration and invasion in cervical cancer by targeting FGL1.

A transfer RNA (tRNA)-derived fragment (tRF) was found to be a new possible biological marker and target in carcinoma therapy. However, the effect exerted by tRFs on cervical carcinoma remains unclear. In the present study, the potential tumor suppressor gene tRF-Glu49 was identified in cervical carcinoma through tRF and tiRNA microarray investigation. A reverse transcription-quantitative PCR assay then demonstrated that tRF-Glu49 was downregulated in the cervical carcinoma tissue. Further clinicopathological analysis proved that tRF-Glu49 was associated with less aggressive clinical features and improved prognosis. Cell Counting Kit-8 tests, Transwell and Matrigel tests, and xCELLigence system tests revealed that tRF-Glu49 inhibited cervical cell proliferation, migration and invasion processes. Mechanistic investigation revealed that tRF-Glu49 directly regulated the oncogene, fibrinogen-like protein-1 (FGL1). In general, according to the result achieved in the present study, tRF-Glu49 can modulate cervical cell proliferation, migration, and invasion processes through the target process for FGL1, and tRF-Glu49 is likely to be a possible prognostic biological marker in patients with cervical carcinoma. Copyright: © Wang et al.

Introduction

Cervical cancer is the fourth most frequently diagnosed cancer and the fourth leading cause of cancer-associated death in women, with an estimated 604,000 new cases and 342,000 deaths worldwide in 2020 (1,2). At present, numerous therapeutic treatments, consisting of surgeries, chemotherapies, and radiotherapies, have been adopted for treating patients with cervical carcinoma (3,4). Although huge therapeutic progress has been achieved, prognosis remains unideal for patients with cervical carcinoma, particularly for those at an advanced disease stage (5). Metastasis and recurrence primarily cause the failure of treatments (6). Consequently, new and feasible biomarkers and therapies should be identified to improve the treatment of cervical cancer.

A transfer RNA (tRNA)-derived fragment (tRF) refers to a new-type non-coding RNA with the root inside tRNA and a length of 14–35 nucleotides (7–9). It is being increasingly reported that tRF is critical to the cell proliferation process, DNA damage response, tumor progression and neurodegeneration, by controlling gene expression (10,11). As tRF is capable of binding to Argonaute (consistent with miRNAs) and Piwi protein (consistent with piRNAs), the disruption is likely to critically affect carcinoma through the control of gene expression over a range of levels (12). According to previous findings, a tRNA fragment is capable of being a possible biological marker in breast, renal clear cell, colorectal and prostate carcinomas (13–16). A previous study by Goodarzi et al (17) revealed that an endogenous tRF hampers breast carcinoma progression by displacing YBX1. Next, as demonstrated by Honda et al (18), tRNA halves dependent on sex hormone improved cell proliferation in breast and prostate carcinomas. Consequently, the mentioned tRNA derivative arouses increasing concern in terms of human carcinoma diagnosis and as a therapy target (19). Nevertheless, the effect exerted by tRF on cervical carcinoma remains unclear.

In the present study, the tRF and tiRNA array were used to detect aberrantly expressed tRFs in cervical cancer. tRF-27-M3WE8SSP6D2 (labeled in the MINTbase) was selected for further study by comprehensively comparing data such as fold change and P-values. This tRF was named tRF-Glu49, as it is spliced from the 49th nucleotide of tRNA-Glu. Then it was demonstrated that tRF-Glu49 has tumor-suppressor functions in cervical cancer, and mechanistic evidence that tRF-Glu49 exerts its function by targeting fibrinogen-like protein-1 (FGL1) was provided.

Materials and methods

tRF and tiRNA microarray analysis

nrStarTM human tRF&tiRNA PCR array was used to screen the differentiated expressed tRFs between tumor tissues and their matched non-tumor adjacent tissues. Pairwise average-linkage cluster analysis, which is a form of hierarchical clustering, has been applied to the gene expression data using the SPSS statistical software. The Arraystar standard protocol was adopted for preparing the specimens and hybridizing the micro-scale array.

Tissue specimens and tissue microarrays (TMAs)

Overall, two groups of patient samples were included in the present study. Written informed consent was obtained from all the patients. The first group consisted of 38 primary cervical carcinoma tissue pairs and nearby normal tissue. Tissues were collected from patients who underwent surgery in the Obstetrics and Gynecology Department of the Affiliated Suqian Hospital of Xuzhou Medical University (Suqian, China), between February 2019 and December 2020. The age distribution of patients (53.8±6.7 years) is inside the usual range of 40–67 years for patients with cervical carcinoma. Specimens of this group of patients were applied for detecting tRF-Glu49 expression by reverse transcription-quantitative (RT-q)PCR. The respective pathological and clinical features of the patients were investigated.

The second group included 92 patients who underwent surgery from January 2011 to September 2013, with 5 years of follow-up information and detailed clinicopathological characteristics. The age distribution of the participants ranged from 37 to 76 years (56.8±9.7 years). This group of specimens, which contained 92 pairs of cervical tissues as well as their nearby normal tissues, was used for TMA. All paired tumor and normal tissues received confirmations from experienced pathologists.

Patients who received pre-operation radiotherapy or chemotherapy were excluded to discharge the radiative effects. The present study was approved by the Ethics Committee of the Affiliated Suqian Hospital of Xuzhou Medical University (Suqian, China; approval number, 2019152). TMA was constructed by Shanghai Outdo Biotech Co., Ltd (http://www.superchip.com.cn/introduction.html) and scanned by Aperio ImageScope (Leica Microsystems, Inc.).

Cell culture, siRNA, tRF mimics and inhibitor transfection

Cervical cell lines of humans (Caski, C33A, SiHa, HeLa and HaCaT) were purchased from Procell Life Science & Technology Co., Ltd. The cells were incubated in RPMI-1640 medium (Invitrogen; Thermo Fisher Scientific, Inc.) supplemented with 10% fetal bovine serum (FBS; Thermo Fisher Scientific, Inc.) at 37°C in an atmosphere containing 5% CO2.

Obtained cervical cell lines were transfected with either the mimics inhibitor or the miRNA mimics. Transfection of these cell lines under 50% confluency was performed using 100 nM of tRF mimics/inhibitors (targeting tRF-Glu49; Guangzhou RiboBio Co., Ltd.) or siRNAs (targeting FGL1), using the Lipofectamine® RNA imax reagent (Invitrogen; Thermo Fisher Scientific, Inc.) at room temperature (~20°C) for 20 min, in accordance with the manufacturer's protocol. Subsequent experiments were performed after transfection and incubation for 24 h.

The sequences of all the primers for siRNAs and RT-qPCR used in the present study are listed in Tables SI and SII. The control, mimics and inhibitors for tRF transfection were designed by Guangzhou RiboBio Co., Ltd. For the newly found tRFs, Guangzhou RiboBio Co., Ltd. was provided with the sequences and the structures and the primers were commercially designed.

Extraction of RNAs and RT-qPCR

Extraction of total RNA from cervical carcinoma cells and tissues was achieved using TRIzol® reagent (Invitrogen; Thermo Fisher Scientific, Inc.), in accordance with the manufacturer's protocol. Next, RNA was quantified through the measurement of the absorbance at 260 and 280 nm. The synthesis of complementary DNA was achieved using a RevertAid First Strand cDNA SynTotal Tool according to the manufacturer's protocol (Thermo Fisher Scientific, Inc.). Based on an Applied Biosystems 7900 Real-Time PCR System (Applied Biosystems; Thermo Fisher Scientific, Inc.), RT-qPCR was performed with the use of an SYBR Green I Real-Time PCR Kit (Shanghai GenePharma Co., Ltd.). PCR was performed with initial denaturation at 95°C for 3 min and 30 cycles of denaturation for 30 sec at 95°C, annealing for 45 sec at 60°C and extension for 60 sec at 72°C. GAPDH and snRNA U6 acted as the internal control. The expression levels of mRNAs and miRNAs were determined using the 2−ΔΔCq method for relative quantification of gene expression. The primer for tRF-Glu49 was provided by Guangzhou RiboBio Co., Ltd.

In situ hybridization (ISH) investigation

The detection of expression levels of tRF-Glu49 in 92 pairs of cervical tissue was achieved through ISH based on probes for tRF-Glu49 (Exiqon; Qiagen). The sequence was TGGTTCCCTGACCGGGAATGCAACCCG with a DIG label at the 5′ and 3′ ends. Researchers displaced TMA into an oven at 60°C for 60 min, and it was incubated as slides overnight at 4°C. Deparaffinized slide was within the solution of ethanol and xylene at room temperature, and subsequently, incubation was achieved by employing Proteinase-K for 7.5 min at 37°C. Slides received 20 min hybridization using a 1,000 nmol/l tRNA-Glu49 probe within one hybridization buffer at 50°C, and subsequently, the cleaning process was performed by employing SSC buffer. The remaining procedure was carried out by employing a revised producer's guideline (20). tRF-Glu49 staining received an intensity scoring based on the 0–2 scale, in accordance with the 1.5-2 (strong), 0.5-1.5 (medium) and 0–0.5 (weak) staining standard. Based on the intensities multiplied by the percentages of positive cells, the aforementioned expression scores were determined. Based on a blind approach, two pathologists assessed a single specimen, and specimens with a score over 1 were considered to show high expression, and those with a score less than or equal to 1 were considered to show low expression.

In vitro cell proliferation, migration, invasion assays and xCELLigence System tests

The proliferation result of cells undergoing the test was obtained with the use of Cell Counting Kit-8 (CCK-8; Roche Applied Science) by complying with the protocol of the study. After transfection, 100 µl CCK-8 solution was injected into a 96-well plate with a density of 1,000-10,000 cells per well. The cells were incubated at 37°C in an atmosphere containing 5% CO2, until the cells covered the well. Wavelength was detected at an absorbance of 450 nm. Regarding the migration assays, HeLa or CaSki treated cells (2.5×105) were plated in the upper chamber of Transwell test inserts (MilliporeSigma) covering 200 µl of serum-free RPMI-1640 under a membrane (8-mm pores). Subsequently, RPMI-1640 supplemented with 10% FBS was plated in the bottom chamber well of a 24-well plate. After being incubated for 24 h, the filter surface cells underwent the fixation (room temperature for 30 min) process by using methanol and the staining (room temperature for 20 min) process by adopting 0.1% crystal violet. Images were captured using digital microscopy. The number of cells was determined within five random fields in terms of the respective chamber. To perform invasion tests, cells under transfection (4×105) received the plating process within the top chamber supplemented by a Matrigel-coated membrane (BD Biosciences) within 500-µl serum-free RPMI-1640, accompanied by a 750 µl 10% FBS-1640 inside the bottom chamber. When the 48-h incubation period was achieved, the invasion function was examined based on the aforementioned description of the migration process. The CIM-plate16 contained 16 wells, as the improved Boyden chamber was available alone, but the examination of the migration of cells in real-time was performed via 8 µm pores of a polyethylene terephthalate membrane onto a gold electrode on the membrane beneath with the use of the xCELLigence system (Agilent).

The researchers set the experimental process in accordance with the guidelines of the producer, in which the membrane received the uncoating (migration) or coating process by using growth-factor-reduced-Matrigel (invasion) (BD BioSciences) (20 µl 1:40 diluted Matrigel per well on the upper surface). The monitoring process for cell index (electrical impedance) was achieved every 15 min. Traces showed the quadruplicate well on average.

RNA immunoprecipitation (RIP)

The present study employed the EZMagna RIP Tool (MilliporeSigma) by complying with the manufacturer's protocol. HeLa or CaSki cells underwent the lysis process within a complete RIP lysis buffer (MilliporeSigma). Then, the extract of cells underwent incubation by using a magnetic bead under 6 h conjugation following control anti-IgG antibody or anti-Argonaute 2 (AGO2) (MilliporeSigma; catalog nos. HPA058075 for anti-AGO2 and SAB5600285 for anti-IgG; diluted 1,000 times) at 4°C. The beads received the washing and incubation process by using Proteinase K for removing the protein. Lastly, purified RNA was subjected to RT-qPCR.

Luciferase reporter test

Based on TargetScan (version 8.0; http://www.targetscan.org/vert_80/), the binding site of 3′untranslated region (UTR) areas and tRF-Glu49 underwent prediction. The fragment sequence underwent synthesis and, subsequently, the insertion process (Lipofectamine RNAimax reagent; Invitrogen) in the pcDNA3.1 (+) and psiCHECK-2 vector (Promega Corporation). The vectors underwent an overall sequencing-based verification, and luciferase activity (after transfection for 18 h) underwent evaluation with the use of the Dual Luciferase Test Kit (Promega Corporation) following the manufacturer's protocol. Renilla luciferase activity was used as a comparison.

Biotin-coupled RNA capture

The 1-day transfection for 3′ end biotinylated short oligonucleotides mimicking tRF-Glu or control biotin-RNA (Guangzhou RiboBio Co., Ltd.) was achieved in CaSki or HeLa cells under 20 nmol/l. The biotin-coupled RNA complex underwent the pull-down process through incubation (1 h at room temperature) of the cell lysate with streptavidin-coated magnetic beads (7×107 beads, ~100 µl/sample; Ambion; Thermo Fisher Scientific, Inc.). FGL1 and tRF-Glu49 abundance in bound fractions underwent assessment using RT-qPCR.

In silico analysis

Using DAVID 6.8 (https://david.ncifcrf.gov/), based on the default rat whole genome background, Gene Ontology (GO) (http://geneontology.org/) analysis was performed to help elucidate the concrete biological functions of specific genes, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways enrichment was employed to identify the critical signal pathways of the differential expressed genes (regulated by tRF-Glu49). Information on tRFs was collected from MINTbase v2.0 (https://cm.jefferson.edu/MINTbase/). Any GO terms and KEGG pathways with P<0.05 were considered significantly enriched. TargetScan, miRanda (http://www.microrna.org/microrna/getDownloads.do) and TargetRank (http://hollywood.mit.edu/targetrank/) were used to identify the candidate target genes of tRF-Glu49. Predicted downstream target genes were ranked according to the criteria set for each bioinformatics tool. The predicted genes from all data mining tools were then compiled into a Venn diagram drawn by R project to identify common target genes.

Statistical analysis

Statistical analysis was performed using SPSS version 19.0 software (IBM Corp.). The clinical data adoption rate (%) was descriptive statistics. Researchers adopted both paired and unpaired t-tests to analyze the differential expression data from qPCR of 38 paired carcinoma tissues. For the cervical TMA data (Table I), which contains 92 pairs of both cervical carcinomas and their matched non-tumor tissues, as well as the long-term follow-up records for evaluating the clinical utility of tRF-Glu49 among patients with cervical cancer, chi-square test was applied in addition to Kruskal-Wallis test with Dunn's post hoc test to investigate and assess multiple comparisons between two or more groups. In the present study, the survival curve was also generated with the use of the Kaplan-Meier approach, and the difference in survival curves was examined with the use of the log-rank test. P<0.05 was considered to indicate a statistically significant difference.

Table I.

Association of tRF-Glu49 expression with clinicopathological characteristics of patients with cervical cancer.

		Expression level of tRF-Glu49
Clinicopathological characteristics	Total (n=92)	Low (n=44)	High (n=48)	P-value
Age, years				0.949
<50	39	19	20
≥50	53	25	28
Tumor size, cm				0.089
<4	43	16	27
≥4	49	28	21
Lymph node metastasis				0.007
Negative	56	20	36
Positive	36	24	12
Differentiation				0.271
Well	27	13	14
Moderate	37	14	23
Poor	28	17	11
TNM stage				0.009
I	31	11	20
II	32	15	17
III	29	18	11
Human papillomavirus status				0.37
Negative	26	10	16
Positive	66	34	32

tRF, tRNA-derived fragment.

Results

Profiling of tRFs and tiRNAs in cervical carcinoma

The full view of the PCR array results including 2512 potential human tRF and tiRNA in 5 tumor tissues and 5 non-tumor adjacent tissues are revealed in Fig. 1A. The results have been used for identifying tRNA fragments that demonstrate differentially expressed states (defined as fold change >2 and P<0.05). A total of 15 downregulated and 12 upregulated tRNA fragments from cervical carcinoma were screened out and selected from the 2512 potential tRF and tiRNA according to the results of PCR array presented in Fig. 1B.

Figure 1.

Screening and verifying of differentially expressed tRNA fragments between cervical carcinoma and nearby normal tissues. (A) Hierarchical clustering heatmap. Each row represents a tRF and each column represents a specimen. (B) A total of 15 downregulated and 12 upregulated tRNA fragments in cervical carcinoma. (C) Basic information of tRF-27-M3WE8SSP6D2 from MINTbase (https://cm.jefferson.edu/MINTbase/). (D) tRF-27-M3WE8SSP6D2 was derived from 3′ ends of tRNA-Glu-CTC and tRNA-Leu-TTC with the length of 27 nt. tRF, tRNA-derived fragment.

Taking abundance and differentiation into account, tRF-27-M3WE8SSP6D2 (fold change=−4.71; P<0.05) was chosen for further study of information on this fragment. As demonstrated in Fig. 1D, tRF-27-M3WE8SSP6D2 was derived from the 3′ end of mature tRNA-Glu-TTC and tRNA-Glu-CTC. Given the MINTbase v2.0, tRF-27-M3WE8SSP6D2 was a 27-nt long 3′-tRF (5′-CGGGTTCGATTCCCGGTCAGGGAACCA-3′) (Fig. 1C).

Overexpression of tRF-Glu49 is associated with less aggressive clinical features and improved prognosis

Expression levels of tRF-Glu49 were detected in tissure microarrays by ISH (Fig.2A) and 38 paired fresh cervical carcinoma patient tissues through qPCR. (tumors and their paired normal tissues adjacent to the tumors). As shown in Fig. 2B, t-test was used to conduct the analysis and tRF-Glu49 was significantly lowly expressed in cervical carcinoma tissues, with average downregulation folds of 4.14 (P<0.001; Fig. 2B).

Figure 2.

Overexpression of tRF-Glu49 is associated with less aggressive clinical features and poor prognosis in patients with cervical carcinoma. (A) tRF-Glu49 staining received an intensity scoring based on the 0–2 scale, in accordance with the 1.5–2 (strong), 0.5–1.5 (medium) and 0–0.5 (weak) staining standard. (B) tRF-Glu49 was significantly low-expressed in 38 cervical carcinoma tissue specimens assessed by quantitative PCR. (C) Low expression of tRF-Glu49 displayed a significant association with advanced FIGO staging (High) and lymph node metastasis (Low) by in situ hybridization investigation in tissue microarray covering 92 pairs of cervical carcinoma and matched non-tumor tissue specimens. (D) According to Kaplan-Meier Plotter, patients carrying a larger amount of tRF-Glu49 had improved overall survival among 92 patients with cervical carcinoma after surgery. *P<0.05. tRF, tRNA-derived fragment.

Cervical TMA was applied, covering 92 pairs of both cervical carcinomas with their matched non-tumor tissues, and the long-term follow-up records for evaluating the clinical utility of tRF-Glu49 among patients with cervical cancer (Table I).

The expression of tRF-Glu49 was detected by ISH. As revealed in Fig. 2C, the results of chi-square test were presented using the box plots, in addition to the table showing the Kruskal-Wallis test difference in the medians of tRF-Glu49 expression among all FIGO stages of cervical cancer. Chi-square test results indicated that the low expression of tRF-Glu49 was significantly associated with lymph node metastasis and advanced FIGO staging. The Kruskal-Wallis test revealed that the median of tRF-Glu49 expression in metastatic lymph nodes was highly significantly different compared with the medians of non-metastatic lymph nodes (P=0.0027). For FIGO cervical cancer staging, the differences among each different FIGO stage were mostly significant except the group of stage I and stage II (P=0.0063). The differences were extremely significant (P<0.001) for the groups of stage I and stage IVB, stage II and stage IVB, as well as stage III and stage IVB (Fig. 2C). Based on Kaplan-Meier investigation and log-rank test, the overall survival (OS) calculation was performed. As revealed in Fig. 2D, cases with lower tRF-Glu49 expression exhibited poor OS (P=0.003).

Biological functions of tRF-Glu49 ceRNET in vitro

Before the biological study of tRF-Glu49 in cervical carcinoma in vitro, the expression profile of tRF-Glu49 in cervical carcinoma cell lines was first assessed by RT-qPCR. tRF-Glu49 was relatively highly expressed in the CaSki cell line, but it was lowly expressed in the HeLa cell line (Fig. 3A). Thus, the two aforementioned cell lines, the transfected the Caski cell line and the HeLa cell line, were used as the controls for conducting the subsequent study. The Caski cells were transfected with the inhibitor NC, while the HeLa cells were transfected with mimics NC. Effects of mimics and inhibitor of tRF-Glu49 were also assessed in cervical carcinoma cells (Fig. S1).

Figure 3.

Biological functions of tRF-Glu49 in vitro. (A) Expression profile of tRF-Glu49 in cervical carcinoma cell lines by reverse transcription-quantitative PCR investigation. (B and C) Effects of tRF-Glu49 parts on proliferating ability exhibited by (B) Caski and (C) HeLa cells assessed by Cell Counting Kit-8 assays. (D-G) Effects of tRF-Glu49 on migrating and invading ability exhibited by (D and E) Caski and (F and G) HeLa cells assessed by Transwell and Matrigel assays and xCELLigence System test (magnification, ×40). Statistical significances were assessed by Student's t-test compared with the control group. **P<0.001. tRF, tRNA-derived fragment.

On performing CCK-8 tests, it was found that knockdown of tRF-Glu49 could significantly increase the proliferative capacity of CaSki cells. Concurrently, overexpression of tRF-Glu49 could significantly decrease the proliferative capacity of HeLa cells (Fig. 3B and C). Transwell and Matrigel tests (Fig. 3D) and xCELLigence system test (Fig. 3E) demonstrated that tRF-Glu49 knockdown significantly promoted cervical carcinoma cell migration and invasion. By contrast, tRF-Glu49 overexpression significantly reduced the cell migration and invasion processes (Fig. 3F and G). Collectively, these results suggested that tRF-Glu49 inhibited the cervical cell proliferation, migration and invasion processes.

tRF-Glu49 directly regulates FGL1 expression in cervical carcinoma cells

To explore the molecular mechanism underlying the influence of tRF-Glu49 on cervical carcinoma cells, a nucleocytoplasmic separation test was first performed and it was found that tRF-Glu49 was mainly expressed in the cytoplasm (Fig. 4A). Acting like small interfering RNA is a classical way for tRNA fragments with 3′CCA tails to function in the cytoplasm. Hence, mRNA target-predicting databases (TargetRank, miRanda, and TargetScan) were used to predict target genes according to binding sites in the 3′UTR.

Figure 4.

tRF-Glu49 directly regulates FGL1 expression in cervical carcinoma cells. (A) Nucleocytoplasmic separation test revealed that tRF-Glu49 and FGL1 were expressed mainly in cytoplasm. (B) Venn diagram assessing overlapping gene outcomes from TargetRank, miRanda, and TargetScan based on GO and KEGG enrichment investigation prediction and literature reviewing. (C and D) The detection of the expressing states of target gene under the prediction was achieved in (C) HeLa and (D) Caski cells when the transfecting process was conducted with inhibitor or tRF-Glu49 mimic based on reverse transcription-quantitative PCR. (E) Luciferase activity in HeLa cells co-transfected with tRF-Glu49 mimics as well as WT or MUT 3′UTR areas of FGL1. (F) FGL1, together with tRF-Glu49 were efficiently pulled-down using anti-Ago2 in Caski (upper panel) or HeLa (down panel) cells. (G) FGL1 was efficiently enriched by biotin-coupled tRF-Glu49 in cervical carcinoma cells. All data are presented as the mean ± SD. The data statistical significances were assessed by Student's t-test compared with the NC group. *P<0.05 and **P<0.001. FGL1, fibrinogen-like protein-1; tRF, tRNA-derived fragment; GO, Gene Ontology; KEGG, Kyoto Encyclopedia of Genes and Genomes; UTR, untranslated region; WT, wild-type; MUT, mutant.

GO and KEGG pathway enrichment analyses were subsequently performed for selection of pathways (Fig. S2). Based on the genes involved in these pathways, the gene results obtained from TargetRank, miRanda and TargetScan were overlapped. FGL1, CDKN1A, BAK1 and EML4 were revealed to be the four most significantly expressed genes among all. More specific demonstrations of these four selected significant tumor carcinoma-associated genes have been achieved by RT-qPCR.

In the GO enrichment plot of upregulated genes, the expression of FGL1 and CDKN1A are the most significant among all. Furthermore, in its KEGG enrichment plot, it was observed that the expression of BAK1 and EML4 are highly significant (Fig. 4B). GO and KEGG pathway enrichment analyses were subsequently performed for upregulated genes. In the GO enrichment plot of upregulated genes, the expression of FGL1 and CDKN1A are the most significant among all. In addition, in its KEGG enrichment plot, it was obvious that the expression of BAK1 and EML4 are highly significant (Fig. 4B).

As identified from the initial screening result, knockdown of tRF-Glu49 resulted in a significant elevation in FGL1 mRNA levels in Caski cells, while overexpression of tRF-Glu49 resulted in a substantial reduction in FGL1 mRNA levels in HeLa cells (Fig. 4C and D). Moreover, an investigation was conducted on the effects exerted by the expression of FGL1 3′UTR areas, by transfecting the luciferase reporter plasmid psiCHECK-2 carrying the wild-type or mutant FGL1 3′UTR areas into HeLa cells. The results revealed that overexpression of tRF-Glu49 decreased the luciferase activity of the plasmids carrying the wild-type 3′UTR areas (Fig. 4E). A RIP test was conducted to pull down RNA transcripts that bound to AGO2 in Caski and HeLa cells. Eventually, FGL1 and tRF-Glu49 were efficiently pulled down by anti-Ago2 (Fig. 4F). For an in-depth assessment of whether the 3′UTR areas of FGL1 were capable of sponging tRF-Glu49, a pull-down test was carried out using biotin-coupled tRF-Glu49 mimics. It was found that tRF-Glu49 mimics efficiently enriched FGL1 (Fig. 4G).

In the subsequent rescue experiments, the effects of tRF-Glu49 on proliferation (Fig. S3A and B), migration and invasion (Fig. S3C and D) could be eliminated when FGL1 was knocked down or overexpressed. Proof of transfection shown in Fig. S4 demonstrated downregulation of FGL1 in Caski cells transfected with si-FGL1 compared with Caski cells transfected with negative control siRNA, as well as upregulation of FGL1 in HeLa cells transfected with the FGL1 overexpression vector compared with HeLa cells transfected with the corresponding negative control.

Discussion

A recent study used PANDORA-seq to reveal unprecedented landscapes of ribosomal RNA-derived small RNAs, tsRNAs and microRNA dynamics across mouse sperm, liver, spleen, and brain, and cell-specific expression across HeLa cells and embryonic stem cells (21). Previously undetected tRFs were revealed to exist abundantly and were deemed crucial in multiple processes considering their high conservation.

Although tRFs have been known and studied for more than 20 years, they were once considered as one kind of miRNAs. Later, they were confirmed to be a type of cleavage product from tRNAs, different from miRNAs. At present, the research on tRFs remains limited, and most of their functions are yet to be discovered. An increasing number of studies supports the existence of highly abundant miRNA-like tRNA fragments in various cell types (21–24). It has been frequently identified that tRF critically regulates carcinoma-related procedures, and it is likely to be a new diagnosis and therapeutic target in tumor treatments (22,23). In a previous study, MTT and BrdU incorporation tests were used to show the tRF-1001 requirement for cell proliferation in HCT116 cells. The tRF-1001 knockdown caused accumulation of cells in G2 (24). Maute et al found that a 3′tRF named CU1276 is downregulated in lymphoma cells and reduces cell proliferation (25). tRF/miR-1280 was suggested to suppress metastasis in colorectal carcinoma, and an endogenous tRF suppressed tumor metastasis and progression through the displacement of YBX1 in breast carcinoma (17). However, little is known about the roles of tRFs in cervical carcinoma.

The present study, to the best of our knowledge, is the first comprehensive and large-scale evaluation of tRFs in cervical cancer. tRF-Glu49 was identified as a potential tumor suppressor gene, verified as a product of tRNA-Glu and it was confirmed that tRF-Glu49 was significantly decreased in cervical tissues. Furthermore, the present results not only showed that tRF-Glu49 inhibits cell proliferating, migrating, and invading processes in the representative high-expressed Caski cell and low-expressed HeLa cell line, but also exerts its tumor suppressor function in other cervical cancers cells such as SiHa cell line and C33A cell line (data not shown).

At the mechanistic level, studies have demonstrated that tRFs play a major role in RNA silencing through complementation between tRNA fragments and target mRNAs. tRFs associate with Argonaute proteins that critically impact target recognition through RNA interference (RNAi) (26–28).

Fibrinogen refers to a glycoprotein comprising α, β, and γ C-terminus domains, coiled-coil domain and central nodule (29). As highlighted in an increasing number of investigations, a member of the FREP superfamily, FGL1, plays pivotal roles in carcinoma and in modulating immune cell functions (30–34). According to the gene expression state investigation, the expression states of FGL1 grew in solid human tumors, including cervical and lung carcinoma, melanoma, prostate and colorectal carcinoma. At the same time, they showed a reduction in head and neck carcinoma, liver carcinoma, and pancreatic carcinoma in comparison with normal tissues, by complying with the data of the BioGPS TMA database and The Cancer Genome Atlas database (35). In the present study, tRF-Glu49 was found to exert its function by targeting FGL1. When tRF-Glu49 was overexpressed, FGL1 expression was inhibited. The results of the AGO2-RIP test revealed evidence about the likely tRF-Glu49-FGL1 mechanism. Furthermore, as demonstrated by the results of the biotin pull-down test and the luciferase reporter assay, tRF-Glu49 was capable of targeting the 3′UTR areas of FGL1 in a direct manner.

In conclusion, to the best of our knowledge, this is the first study to show that tRF-Glu49 was frequently downregulated in cervical carcinoma tissues and cell lines. The low tRF-Glu49 expression state displayed a significant correlation with clinicopathological features and worse outcomes. tRF-Glu49 played a tumor suppression role in cervical carcinoma progression by directly targeting FGL1. These findings suggested that tRF-Glu49 may serve as a diagnostic and prognostic marker and could be a promising new target for patients with cervical carcinoma. However, the absence of in vivo animal data is a limitation to the present study at the current stage. Further studies on tRFs and cervical cancer are planned to be implemented with in vivo examinations.