Investigation of the association of tRNA-derived fragments (tRF-17-79MP9PP and tRF-18- 79MP9P04) with prostate cancer

Investigation of the association of tRNA-derived fragments (tRF-17-79MP9PP and tRF-18- 79MP9P04) with prostate cancer | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Investigation of the association of tRNA-derived fragments (tRF-17-79MP9PP and tRF-18- 79MP9P04) with prostate cancer Sercan Ergun, Kadir Önem, Deniz Bayçelebi, Ümmet Abur, Özlem Terzi, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7353761/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 23 Oct, 2025 Read the published version in Molecular Biology Reports → Version 1 posted 8 You are reading this latest preprint version Abstract Introduction: This study explores the relationship between the expression levels of two tRNA-derived fragments, tRF-17-79MP9PP and tRF-18-79MP9P04, and the pathophysiology of prostate cancer (PCa). Material and methods A total of 40 patients were included: 8 with benign prostatic hyperplasia (BPH) and 32 with varying PCa grades. Total RNA was extracted from formalin-fixed paraffin-embedded (FFPE) tumor tissues, and tRF-17-79MP9PP and tRF-18-79MP9P04 expression levels were measured. Results Results showed that tRF-17-79MP9PP expression increased with cancer grade (p < 0.001), with advanced PCa having the highest levels. Interestingly, BPH also had higher tRF-17-79MP9PP expression than lower and mild PCa grades. tRF-18-79MP9P04 expression was similar between BPH and lower grades, but significantly higher in mild, higher, and advanced PCa grades (p < 0.001). Additionally, a significant correlation was found between PSA levels and both tRF-17-79MP9PP and tRF-18-79MP9P04 in PCa patients (p < 0.001), except in BPH group. Discussion tRF-17-79MP9PP and tRF-18-79MP9P04 play crucial roles in prostate cancer, showing potential oncogenic behavior in advanced stages, contrary to previous findings suggesting tumor-suppressive roles. Conclusion These findings suggest that higher expression levels of these tRNA-derived fragments could serve as potential biomarkers for differentiating PCa grades. Prostate cancer tRNA-derived fragments expression analysis Figures Figure 1 Figure 2 Figure 3 INTRODUCTION The treatment of prostate cancer (PC) is hindered due to the lack of reliable markers and the inadequacy of treatment methods. As a result, the lifespan of PC patients is shortening worldwide and in our country, and mortality rates are increasing every year. To discover better markers and develop new therapeutic strategies, a better understanding of the molecular mechanisms behind the onset and progression of PC is necessary. The role of small non-coding RNAs, other than microRNAs (miRNAs), in PC is not yet fully understood [ 1 , 2 ] . In addition to their known roles in translation, tRNAs (~ 72 nt) can be processed to form biologically active tRNA-derived fragments (tRFs) (~ 18–50 nt). tRFs are produced by the specific cleavage of precursor tRNAs or mature tRNAs in different regions. The first information regarding tRFs dates back 40 years, when tRNA fragments were observed in cancer patients by Speer et al. [ 3 ] . However, at that time, these products were largely disregarded as non-specific degradation products. Contrary to early studies that viewed tRFs as degradation byproducts, an increasing number of recent studies have revealed the regulatory functions of tRFs. For example, tRFs can bind to Argonaute (AGO) family proteins to regulate gene expression [ 4 , 5 ] , increase rRNA synthesis [ 6 ] , and prevent apoptosis by interacting with cytochrome [ 7 ] . They function as signaling molecules in stress responses and regulate gene expression [ 8 , 9 ] . Therefore, tRFs have broad potential applications in disease diagnosis and treatment. tRFs and tiRNAs (tRNA-derived stress-induced RNAs) may affect cancer development by regulating transcription, altering mRNA stability, inhibiting translation, and regulating ribosome biogenesis [ 10 ] . tRFs can also influence cancer development by regulating cell proliferation, metastasis, apoptosis, and the cell cycle [ 11 , 12 ] . Not all tRNAs are processed into tRFs, suggesting some specificity or selectivity in their biogenesis. Transfer RNAs are transcribed as a premature tRNA transcript by RNA Polymerase III. This premature structure is processed by two endonucleases, RNase P and RNase Z. The byproducts of this step (the 5’-leader and 3’-trailer sequences) may also function as tRFs within the cell. Some tRNAs carry intronic sequences in the anticodon arm that are cleaved by the SEN/TSEN complex, and the anticodon arm undergoes ligation to form the tRNA. The cleaved tRNA undergoes various modifications and folding to take on an L-shaped 3D conformation. Structurally, tRFs are classified into five groups based on the tRNA region from which they originate: tRF-5, tRF-3, i-tRF, 5'-half, and 3'-half. A study showed that the tissue-specific expression of certain tRNAs influences the tissue-specific expression of tRFs [ 13 ] . However, the proteins and factors involved in the processing of tRNAs into tRFs are not yet fully understood. The tRF-18-79MP9P04, which belongs to the tRF-5 subgroup, is derived from mature tRNAVal − AAC and tRNAVal − CAC. It was found that the expression of tRF-18-79MP9P04 was reduced in gastric cancer cells, and it acted as a tumor suppressor by regulating proliferation via the PTEN/PI3K/AKT signaling pathway [ 14 ] . Dubrovska et al. found that the PTEN/PI3K/Akt pathway is closely associated with prostate cancer stem cells and that PI3K could be an effective therapeutic target in prostate cancer [ 15 ] . In this context, tRF-18-79MP9P04 may hold promise for prostate cancer studies, and tRF-18-79MP9P04 has not yet been studied in prostate cancer. The tRF-17-79MP9PP molecule, which is 17 nucleotides long, originates from the 5' mature tRNA. tRF-17-79MP9PP transcripts are found more abundantly in the cytoplasm than in the nucleus within the cell [ 16 ] . It has been observed that the expression of tRF-17-79MP9PP is significantly reduced in breast cancer patients and patients with benign breast diseases compared to healthy controls [ 16 , 17 ] . Additionally, it was found that the level of tRF-17-79MP9PP in tumor tissues was significantly lower compared to non-tumor adjacent tissues. The study suggests that tRF-17-79MP9PP can suppress the TGF-β1/Smad3 signaling pathway by targeting THBS1 in breast cancer cells [ 16 ] . tRF-17-79MP9PP has been shown to act as a tumor suppressor in breast cancer tissues, but it has not yet been studied in prostate cancer. Non-coding RNAs are increasingly being recognized as key regulators of cancer, and better understanding them may provide new insights into cancer treatment. With this study, we aim to investigate the relationship between changes in the expression levels of two different tRFs (tRF-18-79MP9P04 and tRF-17-79MP9PP), which have been studied extensively in various types of cancer but not yet in prostate cancer tissues, and the pathophysiology of prostate cancer. MATERIALS AND METHODS Collection of retrospective samples Formalin-fixed paraffin-embedded (FFPE) tumor tissues taken from patients who applied to the Ondokuz Mayıs University Faculty of Medicine (OMÜTF) Urology Clinic between January 2021 and January 2022 and were diagnosed with BPH and prostate cancer by the Pathology clinic were included in the study. The study population consists of 8 benign prostatic hyperplasia (BPH) and 32 PCa patients with gradually increased grades. Of PCa patients, 8 were lower grade (Gleason score:6), 8 were mild grade (Gleason score:7, PSA 10), and 8 were advanced grade (Gleason score ≥ 8). After FFPE tissue samples are collected, they will be stored at + 4 degrees until RNA isolation. Care was taken to ensure that the demographic characteristics of the patient groups were similar. RNA isolation and cDNA extraction from FFPE tissue samples Sections were taken from FFPE tissue samples using a microtome device with the thickness and number specified in the kit. RNA was isolated from the obtained sections using the miRNeasy FFPE Kit (Qiagen GmbH, Hilden, Germany) protocol. 5X All-In-One RT MasterMix (ABM, Richmond, BC, Canada) was used to convert the obtained RNA into cDNA. The working procedure in the kit protocol was followed. The mixtures were exposed to 25°C for 10 min, 50°C for 60 min, 85°C for 5 min and 4°C for 5 min within the reverse transcription (RT) program on the GeneAmp PCR system 9700 (Applied Biosystems, Foster City, CA). cDNAs were stored at -20°C until Real-Time PCR was performed. When necessary, cDNAs were stored at -80°C to extend their shelf life. Spectrophotometric method was used to determine the quantity and quality of cDNA samples obtained before Real-Time PCR experiments. Quality and quantity determination was performed using Multiskan GO spectrophotometer (Thermo Scientific, NH, USA). tRF expression analysis by Real-Time PCR For gene expression analysis, qPCR method will be applied and Rotor-Gene Q (Qiagen GmbH, Hilden, Germany) device was used for this purpose. Expressions of two different selected tRFs (tRF-18-79MP9P04 and tRF-17-79MP9PP) were performed using expression primers specifically designed for these tRFs. As an internal control, SNORD48 gene, which is an essential housekeeping gene, was used for tRF expression analysis and Hs_SNORD48_1_SG QuantiTect Primer Assay (Qiagen GmbH, Hilden, Germany) was used as a primer specific to this gene. BlasTaq™ 2X qPCR MasterMix (ABM, Richmond, BC, Canada) was used in the premix prepared for gene expression analysis and qPCR reaction was performed by entering the operating conditions specified in the protocol of this kit into the Rotor-Gene Q (Qiagen GmbH, Hilden, Germany) device. Statistical analysis SPSS 21 program (IBM software, Pointe Claire, Quebec, Canada) was used for statistical analysis of tRFs whose expression levels were to be measured. Student's t test was used for pairwise comparisons and one-way variance (One Way ANOVA) test was used for more than two comparisons. A value of p < 0.05 was considered statistically significant and an evaluation was made at a confidence interval of 0.95. In the method based on partial amounts, the measurement values ​​of tRFs whose expression was to be measured were normalized with SNORD48. Ct (Cp, Crossing points) values ​​were obtained in the qRT-PCR method. Using the Ct values ​​obtained from tissues of BPH and prostate cancer patients at different stages, the relevant tRF expression levels were compared statistically. The following formula was used with the Ct values obtained during this comparison: 2 -ΔΔCT = 2 -(ΔCT (a target sample)-ΔCT (a reference sample)) . All experimental process is presented in Fig. 1 . RESULTS In this study, we aimed to investigate the relationship between changes in the expression levels of two different tRNA-derived fragments (tRF-18-79MP9P04, tRF-31-U5YKFN8DYDZDD and tRF-17-79MP9PP) and the pathophysiology of prostate cancer (PCa). The study population consisted of 8 patients with benign prostatic hyperplasia (BPH) and 32 patients with PCa of gradually increasing grade. Eight of the PCa patients were low-grade (Gleason score:6), 8 were mild-grade (Gleason score:7, PSA 10), and 8 were advanced-grade (Gleason score ≥ 8). Total RNA including small non-coding RNAs were isolated from formalin-fixed paraffin-embedded (FFPE) tumor tissues of 40 patients with the relevant kit and the obtained RNA samples were converted to cDNA. The measured values of tRFs whose expression was measured by the fractional quantification method were normalized with SNORD48. The demographic/clinical information of the patients obtained is presented in Table 1 (Table 1). Table 1. Demographic/clinical information of patients Group BPH Lower grade (Gleason score 6) Mild grade ( Gleason score:7, PSA10 ) Advanced grade (Gleason score ≥8) n 8 8 8 8 8 Age Mean Range 71.37 58-81 54.75 47-64 62.62 54-71 66.5 60-76 62.37 53-70 PSA Mean Range 4.45 0.9-11.5 6.31 1.7-12 6.61 4.6-8.4 17.1 11-25.2 13.06 1.5-41 The 2-ΔCt method was used to calculate the relative fold expression changes of the samples. As a result, it was determined that the expression level of tRF-17-79MP9PP increased in direct correlation to the increasing cancer grade (p < 0.001) although BPH group had higher expression level of tRF-17-79MP9PP than lower, mild, and higher grades. Also, the expression level of tRF-17-79MP9PP in advanced grade was statistically significantly higher than other study groups (p < 0.001) (Fig. 2). Also, it was observed that the expression levels of tRF-18-79MP9P04 were similar in BPH and low-grade groups, but mild, high and advanced grades had statistically significantly higher tRF-18-79MP9P04 expression levels than BPH and low-grade groups (p < 0.001) (Fig. 3). According to the correlation analysis of all the study population, there was a statistically significant correlation between PSA levels and expression levels of both tRF-17-79MP9PP and tRF-18-79MP9P04, separately (p 0.05) however there were significant correlation for lower (p < 0.001), mild (p < 0.001), higher (p < 0.001) and advanced grades (p < 0.05). Study data suggest that higher expression levels of tRF-17-79MP9PP and tRF-18-79MP9P04 may provide potential for the differential diagnosis of PCa, especially for higher grades. DISCUSSION Prostate cancer is a common type of cancer in men and a serious health problem that needs to be treated. In recent years, research into the understanding and treatment of prostate cancer has revealed the importance of non-coding RNAs [ 18 ] . Non-coding RNAs are defined as RNA molecules that do not code for proteins but have various regulatory roles in cellular processes. Non-coding RNAs involved in the development and progression of prostate cancer may play an important role in understanding the disease and even in identifying potential therapeutic targets [ 19 ] . These RNA molecules play a critical role in the growth and spread of cancer cells by forming a complex network in the regulation of gene expression and control of cellular functions. Therefore, understanding the effects of non-coding RNAs on prostate cancer is an important step towards developing new therapeutic strategies and identifying potential biomarkers that may influence the course of the disease [ 1 ] . Transfer RNA (tRNA) fragments (tRFs) are a class of RNA molecules that have recently garnered significant attention for their role in regulating gene expression and cellular functions. These small RNAs are derived from the cleavage or modification of tRNAs and are implicated in several cellular processes, particularly in the regulation of translation, gene expression, and responses to cellular stress [ 20 ] . Emerging studies indicate that tRFs may contribute to the development and progression of diseases like cancer, with their regulatory influence on gene expression potentially affecting key aspects such as cancer cell growth, metastasis, and resistance to treatment [ 21 ] . The tRF-17-79MP9PP molecule, which is 17 nucleotides long, is derived from the 5' end of mature tRNA. It is more prevalent in the cytoplasm than in the nucleus within the cell [ 16 ] . Research has shown that tRF-17-79MP9PP expression is significantly lower in breast cancer and benign breast disease patients compared to healthy individuals [ 16 , 17 ] . Additionally, its levels were markedly reduced in tumor tissues compared to adjacent non-tumor tissues. The study suggests that tRF-17-79MP9PP may inhibit the TGF-β1/Smad3 signaling pathway by targeting THBS1 in breast cancer cells [ 16 ] . While it functions as a tumor suppressor in breast cancer, tRF-17-79MP9PP has not yet been explored in prostate cancer research. tRF-5026a (tRF ID: tRF-18-79MP9P04), a member of the tRF-5 subgroup, originates from mature tRNAVal-AAC and tRNAVal-CAC. In gastric cancer cells, tRF-18-79MP has been shown to have reduced expression and function as a tumor suppressor by controlling cell proliferation via the PTEN/PI3K/AKT signaling pathway [ 14 ] . It was reported that the PTEN/PI3K/AKT pathway is strongly linked to prostate cancer stem cells, suggesting PI3K as a potential therapeutic target for prostate cancer [ 15 ] . Given this connection, tRF-18-79MP may hold promise for prostate cancer research, though it has not yet been investigated in this context. In this study, it was determined that the expression level of tRF-17-79MP9PP increased in direct proportion to the increasing cancer grade (p < 0.001) although BPH group had higher expression level of tRF-17-79MP9PP than lower, mild, and higher grades. Also, the expression level of tRF-17-79MP9PP in advanced grade was statistically significantly higher than other study groups (p < 0.001) (Fig. 2 ). Moreover, it was observed that the expression levels of tRF-18-79MP9P04 were similar in BPH and low-grade groups, but mild, high and advanced grades had statistically significantly higher tRF-18-79MP9P04 expression levels than BPH and low-grade groups (p < 0.001) (Fig. 3 ). According to the correlation analysis of all the study population, there was a statistically significant positive correlation between PSA levels and expression levels of both tRF-17-79MP9PP and tRF-18-79MP9P04, separately (p 0.05) however there were significant positive correlation for lower (p < 0.001), mild (p < 0.001), higher (p < 0.001) and advanced grades (p < 0.05). When we compare our study findings with the studies in the literature in which tRF-17-79MP9PP and tRF-18-79MP9P04 were analyzed, there is a significant difference. When we look at the studies in the literature, we see that tRF-17-79MP9PP and tRF-18-79MP9P04 assume a tumor suppressor role, but in our study, they assume a potential oncogenic role with increased expression levels in advanced stages of prostate cancer. We can explain this by the fact that, like non-coding RNAs in general, they have a very sensitive regulation and can play very different roles in different cancers. Non-coding RNAs can exhibit a dual role in cancer progression by functioning as both tumor suppressors and oncogenes, depending on the cellular context [ 22 – 24 ] . For example, miR-21 is well-known for its oncogenic role in many cancers [ 25 ] , where it promotes cell proliferation and inhibits apoptosis by targeting tumor suppressor genes such as PTEN [ 26 ] . Similarly, long non-coding RNA HOTAIR is frequently described as an oncogene that promotes metastasis and cancer progression by altering chromatin structure [ 27 ] , but in some contexts, it has been shown to exhibit tumor-suppressive functions by inhibiting cell migration and invasion [ 28 ] . This dual functionality is also observed in tRNA-derived fragments (tRFs), which can either suppress tumor growth by inhibiting oncogenic signaling pathways or support cancer progression by modulating cellular stress responses [ 21 ] . The ability of ncRNAs to function in both suppressive and oncogenic roles underscores their complexity and potential as therapeutic targets in cancer treatment. As a limitation of the study, we analyzed the roles of tRF-17-79MP9PP and tRF-18-79MP9P04 in PC pathophysiology through transcriptional activity. However, there are thousands of tRF targets in the cell, so this pathway and its interactions may have many different regulators. Therefore, conducting functional analyses will enable us to cover all these interactions and reach more realistic conclusions regarding the role of tRFs in the pathophysiology of prostate cancer. All in all, higher expression levels of tRF-17-79MP9PP and tRF-18-79MP9P04 could be valuable for distinguishing prostate cancer. These elevated levels might be particularly useful for identifying higher-grade tumors. Thus, they have potential as biomarkers in the differential diagnosis of prostate cancer. Declarations Conflict of interest No conflict declared. Approval of the research protocol by an Institutional Reviewer Board The study was approved by Ondokuz Mayıs University Clinical Research Ethics Committee (Approval no: 2021/617) (Supplementary 1). Informed Consent N/A Registry and the Registration No. of the study/trial N/A Animal Studies N/A FUNDING This project was supported financially by Ondokuz Mayıs University Scientific Research Projects Coordination Unit (BAPKOP), with the project number PYO.TIP.1901.22.001. Author Contribution S.E., S.O.A. N.T.H. and S.G. wrote the main manuscript text. S.O.A., D.D., and Y.K. prepared Figures 1–3. K.Ö., D.B., Ü.A. and Ö.T. contributed to data collection and analysis. All authors reviewed and approved the manuscript. References Ramalho-Carvalho, J., et al., Deciphering the function of non-coding RNAs in prostate cancer. Cancer and Metastasis Reviews, 2016. 35 (2): p. 235-262. 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Medical Oncology, 2018. 35 : p. 1-10. Javanmardi, S., et al., miR-21, an oncogenic target miRNA for cancer therapy: molecular mechanisms and recent advancements in chemo and radio-resistance. Current gene therapy, 2016. 16 (6): p. 375-389. Meng, F., et al., MicroRNA-21 regulates expression of the PTEN tumor suppressor gene in human hepatocellular cancer. Gastroenterology, 2007. 133 (2): p. 647-658. Gupta, R.A., et al., Long non-coding RNA HOTAIR reprograms chromatin state to promote cancer metastasis. nature, 2010. 464 (7291): p. 1071-1076. Liu, X.-h., et al., Lnc RNA HOTAIR functions as a competing endogenous RNA to regulate HER2 expression by sponging miR-331-3p in gastric cancer. Molecular cancer, 2014. 13 : p. 1-14. Additional Declarations No competing interests reported. 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09:08:37","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7353761/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7353761/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s11033-025-11176-w","type":"published","date":"2025-10-23T16:16:36+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":89656351,"identity":"d8079d47-5aea-4b1b-b49c-fabfd9a499e9","added_by":"auto","created_at":"2025-08-22 10:28:42","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":113557,"visible":true,"origin":"","legend":"\u003cp\u003eDiagrammatic drawing of the research\u003c/p\u003e","description":"","filename":"Figure1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7353761/v1/e7c2f12d5ff70e7a0dfa2baa.jpeg"},{"id":89657719,"identity":"9b1731fe-35fd-4a86-b92e-62434fc9fc3a","added_by":"auto","created_at":"2025-08-22 10:36:42","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":363151,"visible":true,"origin":"","legend":"\u003cp\u003etRF-17-79MP9PP expression levels between groups\u003c/p\u003e","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7353761/v1/680db69c8309fccbcaec2c23.jpg"},{"id":89656353,"identity":"f0340443-5cdd-446b-bb8a-3cb693a9f6c3","added_by":"auto","created_at":"2025-08-22 10:28:42","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":388553,"visible":true,"origin":"","legend":"\u003cp\u003etRF-18-79MP9P04 expression levels between groups\u003c/p\u003e","description":"","filename":"Figure3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7353761/v1/74d52472137643b666efa529.jpg"},{"id":94490731,"identity":"9bcb12c6-9ad9-49a6-988e-55e0c67dfb6e","added_by":"auto","created_at":"2025-10-27 17:14:24","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1584902,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7353761/v1/7aecb2fd-79b6-42e8-9cf1-75abec090bd5.pdf"},{"id":89656358,"identity":"ca2ba740-98e5-46c6-a490-237627837383","added_by":"auto","created_at":"2025-08-22 10:28:42","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":246190,"visible":true,"origin":"","legend":"\u003cp\u003esupplemental materials\u003c/p\u003e\n\u003cp\u003e1. Ondokuz Mayis University Clinical Research Ethics Committee Approval\u003c/p\u003e","description":"","filename":"Supplementary1ClinicalResearchEthicsCommitteeApproval.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7353761/v1/0fe5388e4f27c25660d794d4.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Investigation of the association of tRNA-derived fragments (tRF-17-79MP9PP and tRF-18- 79MP9P04) with prostate cancer","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eThe treatment of prostate cancer (PC) is hindered due to the lack of reliable markers and the inadequacy of treatment methods. As a result, the lifespan of PC patients is shortening worldwide and in our country, and mortality rates are increasing every year. To discover better markers and develop new therapeutic strategies, a better understanding of the molecular mechanisms behind the onset and progression of PC is necessary. The role of small non-coding RNAs, other than microRNAs (miRNAs), in PC is not yet fully understood \u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eIn addition to their known roles in translation, tRNAs (~\u0026thinsp;72 nt) can be processed to form biologically active tRNA-derived fragments (tRFs) (~\u0026thinsp;18\u0026ndash;50 nt). tRFs are produced by the specific cleavage of precursor tRNAs or mature tRNAs in different regions. The first information regarding tRFs dates back 40 years, when tRNA fragments were observed in cancer patients by Speer et al. \u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e. However, at that time, these products were largely disregarded as non-specific degradation products. Contrary to early studies that viewed tRFs as degradation byproducts, an increasing number of recent studies have revealed the regulatory functions of tRFs. For example, tRFs can bind to Argonaute (AGO) family proteins to regulate gene expression \u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e, increase rRNA synthesis \u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e, and prevent apoptosis by interacting with cytochrome \u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e. They function as signaling molecules in stress responses and regulate gene expression \u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e. Therefore, tRFs have broad potential applications in disease diagnosis and treatment. tRFs and tiRNAs (tRNA-derived stress-induced RNAs) may affect cancer development by regulating transcription, altering mRNA stability, inhibiting translation, and regulating ribosome biogenesis \u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e. tRFs can also influence cancer development by regulating cell proliferation, metastasis, apoptosis, and the cell cycle \u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eNot all tRNAs are processed into tRFs, suggesting some specificity or selectivity in their biogenesis. Transfer RNAs are transcribed as a premature tRNA transcript by RNA Polymerase III. This premature structure is processed by two endonucleases, RNase P and RNase Z. The byproducts of this step (the 5\u0026rsquo;-leader and 3\u0026rsquo;-trailer sequences) may also function as tRFs within the cell. Some tRNAs carry intronic sequences in the anticodon arm that are cleaved by the SEN/TSEN complex, and the anticodon arm undergoes ligation to form the tRNA. The cleaved tRNA undergoes various modifications and folding to take on an L-shaped 3D conformation. Structurally, tRFs are classified into five groups based on the tRNA region from which they originate: tRF-5, tRF-3, i-tRF, 5'-half, and 3'-half. A study showed that the tissue-specific expression of certain tRNAs influences the tissue-specific expression of tRFs \u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/sup\u003e. However, the proteins and factors involved in the processing of tRNAs into tRFs are not yet fully understood.\u003c/p\u003e\u003cp\u003eThe tRF-18-79MP9P04, which belongs to the tRF-5 subgroup, is derived from mature tRNAVal\u0026thinsp;\u0026minus;\u0026thinsp;AAC and tRNAVal\u0026thinsp;\u0026minus;\u0026thinsp;CAC. It was found that the expression of tRF-18-79MP9P04 was reduced in gastric cancer cells, and it acted as a tumor suppressor by regulating proliferation via the PTEN/PI3K/AKT signaling pathway \u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e. Dubrovska et al. found that the PTEN/PI3K/Akt pathway is closely associated with prostate cancer stem cells and that PI3K could be an effective therapeutic target in prostate cancer \u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e. In this context, tRF-18-79MP9P04 may hold promise for prostate cancer studies, and tRF-18-79MP9P04 has not yet been studied in prostate cancer.\u003c/p\u003e\u003cp\u003eThe tRF-17-79MP9PP molecule, which is 17 nucleotides long, originates from the 5' mature tRNA. tRF-17-79MP9PP transcripts are found more abundantly in the cytoplasm than in the nucleus within the cell \u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e. It has been observed that the expression of tRF-17-79MP9PP is significantly reduced in breast cancer patients and patients with benign breast diseases compared to healthy controls \u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e. Additionally, it was found that the level of tRF-17-79MP9PP in tumor tissues was significantly lower compared to non-tumor adjacent tissues. The study suggests that tRF-17-79MP9PP can suppress the TGF-β1/Smad3 signaling pathway by targeting THBS1 in breast cancer cells \u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e. tRF-17-79MP9PP has been shown to act as a tumor suppressor in breast cancer tissues, but it has not yet been studied in prostate cancer.\u003c/p\u003e\u003cp\u003eNon-coding RNAs are increasingly being recognized as key regulators of cancer, and better understanding them may provide new insights into cancer treatment. With this study, we aim to investigate the relationship between changes in the expression levels of two different tRFs (tRF-18-79MP9P04 and tRF-17-79MP9PP), which have been studied extensively in various types of cancer but not yet in prostate cancer tissues, and the pathophysiology of prostate cancer.\u003c/p\u003e"},{"header":"MATERIALS AND METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eCollection of retrospective samples\u003c/h2\u003e\u003cp\u003eFormalin-fixed paraffin-embedded (FFPE) tumor tissues taken from patients who applied to the Ondokuz Mayıs University Faculty of Medicine (OM\u0026Uuml;TF) Urology Clinic between January 2021 and January 2022 and were diagnosed with BPH and prostate cancer by the Pathology clinic were included in the study. The study population consists of 8 benign prostatic hyperplasia (BPH) and 32 PCa patients with gradually increased grades. Of PCa patients, 8 were lower grade (Gleason score:6), 8 were mild grade (Gleason score:7, PSA\u0026thinsp;\u0026lt;\u0026thinsp;10), 8 were higher grade (Gleason score:7, PSA\u0026thinsp;\u0026gt;\u0026thinsp;10), and 8 were advanced grade (Gleason score\u0026thinsp;\u0026ge;\u0026thinsp;8). After FFPE tissue samples are collected, they will be stored at +\u0026thinsp;4 degrees until RNA isolation. Care was taken to ensure that the demographic characteristics of the patient groups were similar.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eRNA isolation and cDNA extraction from FFPE tissue samples\u003c/h3\u003e\n\u003cp\u003eSections were taken from FFPE tissue samples using a microtome device with the thickness and number specified in the kit. RNA was isolated from the obtained sections using the miRNeasy FFPE Kit (Qiagen GmbH, Hilden, Germany) protocol. 5X All-In-One RT MasterMix (ABM, Richmond, BC, Canada) was used to convert the obtained RNA into cDNA. The working procedure in the kit protocol was followed. The mixtures were exposed to 25\u0026deg;C for 10 min, 50\u0026deg;C for 60 min, 85\u0026deg;C for 5 min and 4\u0026deg;C for 5 min within the reverse transcription (RT) program on the GeneAmp PCR system 9700 (Applied Biosystems, Foster City, CA). cDNAs were stored at -20\u0026deg;C until Real-Time PCR was performed. When necessary, cDNAs were stored at -80\u0026deg;C to extend their shelf life. Spectrophotometric method was used to determine the quantity and quality of cDNA samples obtained before Real-Time PCR experiments. Quality and quantity determination was performed using Multiskan GO spectrophotometer (Thermo Scientific, NH, USA).\u003c/p\u003e\n\u003ch3\u003etRF expression analysis by Real-Time PCR\u003c/h3\u003e\n\u003cp\u003eFor gene expression analysis, qPCR method will be applied and Rotor-Gene Q (Qiagen GmbH, Hilden, Germany) device was used for this purpose. Expressions of two different selected tRFs (tRF-18-79MP9P04 and tRF-17-79MP9PP) were performed using expression primers specifically designed for these tRFs. As an internal control, SNORD48 gene, which is an essential housekeeping gene, was used for tRF expression analysis and Hs_SNORD48_1_SG QuantiTect Primer Assay (Qiagen GmbH, Hilden, Germany) was used as a primer specific to this gene. BlasTaq\u0026trade; 2X qPCR MasterMix (ABM, Richmond, BC, Canada) was used in the premix prepared for gene expression analysis and qPCR reaction was performed by entering the operating conditions specified in the protocol of this kit into the Rotor-Gene Q (Qiagen GmbH, Hilden, Germany) device.\u003c/p\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eSPSS 21 program (IBM software, Pointe Claire, Quebec, Canada) was used for statistical analysis of tRFs whose expression levels were to be measured. Student's t test was used for pairwise comparisons and one-way variance (One Way ANOVA) test was used for more than two comparisons. A value of p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant and an evaluation was made at a confidence interval of 0.95. In the method based on partial amounts, the measurement values ​​of tRFs whose expression was to be measured were normalized with SNORD48. Ct (Cp, Crossing points) values ​​were obtained in the qRT-PCR method. Using the Ct values ​​obtained from tissues of BPH and prostate cancer patients at different stages, the relevant tRF expression levels were compared statistically. The following formula was used with the Ct values obtained during this comparison: 2\u003csup\u003e-ΔΔCT\u003c/sup\u003e = 2\u003csup\u003e-(ΔCT (a target sample)-ΔCT (a reference sample))\u003c/sup\u003e. All experimental process is presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"RESULTS","content":"\u003cp\u003eIn this study, we aimed to investigate the relationship between changes in the expression levels of two different tRNA-derived fragments (tRF-18-79MP9P04, tRF-31-U5YKFN8DYDZDD and tRF-17-79MP9PP) and the pathophysiology of prostate cancer (PCa). The study population consisted of 8 patients with benign prostatic hyperplasia (BPH) and 32 patients with PCa of gradually increasing grade. Eight of the PCa patients were low-grade (Gleason score:6), 8 were mild-grade (Gleason score:7, PSA\u0026thinsp;\u0026lt;\u0026thinsp;10), 8 were high-grade (Gleason score:7, PSA\u0026thinsp;\u0026gt;\u0026thinsp;10), and 8 were advanced-grade (Gleason score\u0026thinsp;\u0026ge;\u0026thinsp;8). Total RNA including small non-coding RNAs were isolated from formalin-fixed paraffin-embedded (FFPE) tumor tissues of 40 patients with the relevant kit and the obtained RNA samples were converted to cDNA. The measured values of tRFs whose expression was measured by the fractional quantification method were normalized with SNORD48. The demographic/clinical information of the patients obtained is presented in Table\u0026nbsp;1 (Table\u0026nbsp;1).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1.\u003c/strong\u003e Demographic/clinical information of patients\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"699\" class=\"fr-table-selection-hover\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGroup\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.6884%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBPH\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4208%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLower grade (Gleason score 6)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMild grade\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(\u003c/strong\u003e\u003cstrong\u003eGleason score:7,\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003ePSA\u0026lt;10)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHigher grade\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(\u003c/strong\u003e\u003cstrong\u003eGleason score:7,\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003ePSA\u0026gt;10\u003c/strong\u003e\u003cstrong\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAdvanced grade (Gleason score \u0026ge;8)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003en\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.6884%;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4208%;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Mean\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Range\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.6884%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e71.37\u003c/p\u003e\n \u003cp\u003e58-81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4208%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e54.75\u003c/p\u003e\n \u003cp\u003e47-64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e62.62\u003c/p\u003e\n \u003cp\u003e54-71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e66.5\u003c/p\u003e\n \u003cp\u003e60-76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e62.37\u003c/p\u003e\n \u003cp\u003e53-70\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003ePSA\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Mean\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Range\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.6884%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e4.45\u003c/p\u003e\n \u003cp\u003e0.9-11.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4208%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e6.31\u003c/p\u003e\n \u003cp\u003e1.7-12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e6.61\u003c/p\u003e\n \u003cp\u003e4.6-8.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e17.1\u003c/p\u003e\n \u003cp\u003e11-25.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e13.06\u003c/p\u003e\n \u003cp\u003e1.5-41\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eThe 2-\u0026Delta;Ct method was used to calculate the relative fold expression changes of the samples. As a result, it was determined that the expression level of tRF-17-79MP9PP increased in direct correlation to the increasing cancer grade (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) although BPH group had higher expression level of tRF-17-79MP9PP than lower, mild, and higher grades. Also, the expression level of tRF-17-79MP9PP in advanced grade was statistically significantly higher than other study groups (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig.\u0026nbsp;2).\u003c/p\u003e\n\u003cp\u003eAlso, it was observed that the expression levels of tRF-18-79MP9P04 were similar in BPH and low-grade groups, but mild, high and advanced grades had statistically significantly higher tRF-18-79MP9P04 expression levels than BPH and low-grade groups (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig.\u0026nbsp;3).\u003c/p\u003e\n\u003cp\u003eAccording to the correlation analysis of all the study population, there was a statistically significant correlation between PSA levels and expression levels of both tRF-17-79MP9PP and tRF-18-79MP9P04, separately (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). When we analyzed this correlation within the groups, there was no significant correlation in BPH group (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05) however there were significant correlation for lower (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), mild (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), higher (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and advanced grades (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e\n\u003cp\u003eStudy data suggest that higher expression levels of tRF-17-79MP9PP and tRF-18-79MP9P04 may provide potential for the differential diagnosis of PCa, especially for higher grades.\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eProstate cancer is a common type of cancer in men and a serious health problem that needs to be treated. In recent years, research into the understanding and treatment of prostate cancer has revealed the importance of non-coding RNAs \u003csup\u003e[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/sup\u003e. Non-coding RNAs are defined as RNA molecules that do not code for proteins but have various regulatory roles in cellular processes. Non-coding RNAs involved in the development and progression of prostate cancer may play an important role in understanding the disease and even in identifying potential therapeutic targets \u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e. These RNA molecules play a critical role in the growth and spread of cancer cells by forming a complex network in the regulation of gene expression and control of cellular functions. Therefore, understanding the effects of non-coding RNAs on prostate cancer is an important step towards developing new therapeutic strategies and identifying potential biomarkers that may influence the course of the disease \u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eTransfer RNA (tRNA) fragments (tRFs) are a class of RNA molecules that have recently garnered significant attention for their role in regulating gene expression and cellular functions. These small RNAs are derived from the cleavage or modification of tRNAs and are implicated in several cellular processes, particularly in the regulation of translation, gene expression, and responses to cellular stress \u003csup\u003e[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/sup\u003e. Emerging studies indicate that tRFs may contribute to the development and progression of diseases like cancer, with their regulatory influence on gene expression potentially affecting key aspects such as cancer cell growth, metastasis, and resistance to treatment \u003csup\u003e[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThe tRF-17-79MP9PP molecule, which is 17 nucleotides long, is derived from the 5' end of mature tRNA. It is more prevalent in the cytoplasm than in the nucleus within the cell \u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e. Research has shown that tRF-17-79MP9PP expression is significantly lower in breast cancer and benign breast disease patients compared to healthy individuals \u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e. Additionally, its levels were markedly reduced in tumor tissues compared to adjacent non-tumor tissues. The study suggests that tRF-17-79MP9PP may inhibit the TGF-β1/Smad3 signaling pathway by targeting THBS1 in breast cancer cells \u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e. While it functions as a tumor suppressor in breast cancer, tRF-17-79MP9PP has not yet been explored in prostate cancer research.\u003c/p\u003e\u003cp\u003etRF-5026a (tRF ID: tRF-18-79MP9P04), a member of the tRF-5 subgroup, originates from mature tRNAVal-AAC and tRNAVal-CAC. In gastric cancer cells, tRF-18-79MP has been shown to have reduced expression and function as a tumor suppressor by controlling cell proliferation via the PTEN/PI3K/AKT signaling pathway \u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e. It was reported that the PTEN/PI3K/AKT pathway is strongly linked to prostate cancer stem cells, suggesting PI3K as a potential therapeutic target for prostate cancer \u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e. Given this connection, tRF-18-79MP may hold promise for prostate cancer research, though it has not yet been investigated in this context.\u003c/p\u003e\u003cp\u003eIn this study, it was determined that the expression level of tRF-17-79MP9PP increased in direct proportion to the increasing cancer grade (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) although BPH group had higher expression level of tRF-17-79MP9PP than lower, mild, and higher grades. Also, the expression level of tRF-17-79MP9PP in advanced grade was statistically significantly higher than other study groups (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Moreover, it was observed that the expression levels of tRF-18-79MP9P04 were similar in BPH and low-grade groups, but mild, high and advanced grades had statistically significantly higher tRF-18-79MP9P04 expression levels than BPH and low-grade groups (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAccording to the correlation analysis of all the study population, there was a statistically significant positive correlation between PSA levels and expression levels of both tRF-17-79MP9PP and tRF-18-79MP9P04, separately (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). When we analyzed this correlation within the groups, there was no significant correlation in BPH group (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05) however there were significant positive correlation for lower (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), mild (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), higher (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and advanced grades (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e\u003cp\u003eWhen we compare our study findings with the studies in the literature in which tRF-17-79MP9PP and tRF-18-79MP9P04 were analyzed, there is a significant difference. When we look at the studies in the literature, we see that tRF-17-79MP9PP and tRF-18-79MP9P04 assume a tumor suppressor role, but in our study, they assume a potential oncogenic role with increased expression levels in advanced stages of prostate cancer. We can explain this by the fact that, like non-coding RNAs in general, they have a very sensitive regulation and can play very different roles in different cancers. Non-coding RNAs can exhibit a dual role in cancer progression by functioning as both tumor suppressors and oncogenes, depending on the cellular context \u003csup\u003e[\u003cspan additionalcitationids=\"CR23\" citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/sup\u003e. For example, miR-21 is well-known for its oncogenic role in many cancers \u003csup\u003e[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]\u003c/sup\u003e, where it promotes cell proliferation and inhibits apoptosis by targeting tumor suppressor genes such as PTEN \u003csup\u003e[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/sup\u003e. Similarly, long non-coding RNA HOTAIR is frequently described as an oncogene that promotes metastasis and cancer progression by altering chromatin structure \u003csup\u003e[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/sup\u003e, but in some contexts, it has been shown to exhibit tumor-suppressive functions by inhibiting cell migration and invasion \u003csup\u003e[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]\u003c/sup\u003e. This dual functionality is also observed in tRNA-derived fragments (tRFs), which can either suppress tumor growth by inhibiting oncogenic signaling pathways or support cancer progression by modulating cellular stress responses \u003csup\u003e[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/sup\u003e. The ability of ncRNAs to function in both suppressive and oncogenic roles underscores their complexity and potential as therapeutic targets in cancer treatment.\u003c/p\u003e\u003cp\u003eAs a limitation of the study, we analyzed the roles of tRF-17-79MP9PP and tRF-18-79MP9P04 in PC pathophysiology through transcriptional activity. However, there are thousands of tRF targets in the cell, so this pathway and its interactions may have many different regulators. Therefore, conducting functional analyses will enable us to cover all these interactions and reach more realistic conclusions regarding the role of tRFs in the pathophysiology of prostate cancer.\u003c/p\u003e\u003cp\u003eAll in all, higher expression levels of tRF-17-79MP9PP and tRF-18-79MP9P04 could be valuable for distinguishing prostate cancer. These elevated levels might be particularly useful for identifying higher-grade tumors. Thus, they have potential as biomarkers in the differential diagnosis of prostate cancer.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eConflict of interest\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo conflict declared.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eApproval of the research protocol by an Institutional Reviewer Board\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was approved by Ondokuz Mayıs University Clinical Research Ethics Committee (Approval no: 2021/617) (Supplementary 1).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInformed Consent\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eN/A\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRegistry and the Registration No. of the study/trial\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;N/A\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAnimal Studies\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eN/A\u003c/p\u003e\n\u003cp\u003eFUNDING\u003c/p\u003e\n\u003cp\u003eThis project was supported financially by Ondokuz Mayıs University Scientific Research Projects Coordination Unit (BAPKOP), with the project number PYO.TIP.1901.22.001.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eS.E., S.O.A. N.T.H. and S.G. wrote the main manuscript text. S.O.A., D.D., and Y.K. prepared Figures 1\u0026ndash;3. K.\u0026Ouml;., D.B., \u0026Uuml;.A. and \u0026Ouml;.T. contributed to data collection and analysis. All authors reviewed and approved the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eRamalho-Carvalho, J., et al., \u003cem\u003eDeciphering the function of non-coding RNAs in prostate cancer.\u003c/em\u003e Cancer and Metastasis Reviews, 2016. \u003cstrong\u003e35\u003c/strong\u003e(2): p. 235-262.\u003c/li\u003e\n\u003cli\u003eErg\u0026uuml;n, S., et al., \u003cem\u003eThe interrelationship between fyn and Mir-128/193a-5p/494 in imatinib resistance in prostate cancer.\u003c/em\u003e Anti-Cancer Agents in Medicinal Chemistry (Formerly Current Medicinal Chemistry-Anti-Cancer Agents), 2023. \u003cstrong\u003e23\u003c/strong\u003e(3): p. 360-365.\u003c/li\u003e\n\u003cli\u003eSpeer, J., et al., \u003cem\u003etRNA breakdown products as markers for cancer.\u003c/em\u003e Cancer, 1979. \u003cstrong\u003e44\u003c/strong\u003e(6): p. 2120-2123.\u003c/li\u003e\n\u003cli\u003eLi, Z., et al., \u003cem\u003eExtensive terminal and asymmetric processing of small RNAs from rRNAs, snoRNAs, snRNAs, and tRNAs.\u003c/em\u003e Nucleic acids research, 2012. \u003cstrong\u003e40\u003c/strong\u003e(14): p. 6787-6799.\u003c/li\u003e\n\u003cli\u003eMaute, R.L., et al., \u003cem\u003etRNA-derived microRNA modulates proliferation and the DNA damage response and is down-regulated in B cell lymphoma.\u003c/em\u003e Proceedings of the National Academy of Sciences, 2013. \u003cstrong\u003e110\u003c/strong\u003e(4): p. 1404-1409.\u003c/li\u003e\n\u003cli\u003eCouvillion, M.T., et al., \u003cem\u003eA Tetrahymena Piwi bound to mature tRNA 3\u0026prime; fragments activates the exonuclease Xrn2 for RNA processing in the nucleus.\u003c/em\u003e Molecular cell, 2012. \u003cstrong\u003e48\u003c/strong\u003e(4): p. 509-520.\u003c/li\u003e\n\u003cli\u003eSaikia, M., et al., \u003cem\u003eAngiogenin-cleaved tRNA halves interact with cytochrome c, protecting cells from apoptosis during osmotic stress.\u003c/em\u003e Molecular and cellular biology, 2014.\u003c/li\u003e\n\u003cli\u003eSchimmel, P., \u003cem\u003eThe emerging complexity of the tRNA world: mammalian tRNAs beyond protein synthesis.\u003c/em\u003e Nature reviews Molecular cell biology, 2018. \u003cstrong\u003e19\u003c/strong\u003e(1): p. 45-58.\u003c/li\u003e\n\u003cli\u003eKim, H.K., et al., \u003cem\u003eA transfer-RNA-derived small RNA regulates ribosome biogenesis.\u003c/em\u003e Nature, 2017. \u003cstrong\u003e552\u003c/strong\u003e(7683): p. 57-62.\u003c/li\u003e\n\u003cli\u003eLi, S., Z. 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Total RNA was extracted from formalin-fixed paraffin-embedded (FFPE) tumor tissues, and tRF-17-79MP9PP and tRF-18-79MP9P04 expression levels were measured.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eResults showed that tRF-17-79MP9PP expression increased with cancer grade (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), with advanced PCa having the highest levels. Interestingly, BPH also had higher tRF-17-79MP9PP expression than lower and mild PCa grades. tRF-18-79MP9P04 expression was similar between BPH and lower grades, but significantly higher in mild, higher, and advanced PCa grades (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Additionally, a significant correlation was found between PSA levels and both tRF-17-79MP9PP and tRF-18-79MP9P04 in PCa patients (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), except in BPH group.\u003c/p\u003e\u003ch2\u003eDiscussion\u003c/h2\u003e\u003cp\u003etRF-17-79MP9PP and tRF-18-79MP9P04 play crucial roles in prostate cancer, showing potential oncogenic behavior in advanced stages, contrary to previous findings suggesting tumor-suppressive roles.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eThese findings suggest that higher expression levels of these tRNA-derived fragments could serve as potential biomarkers for differentiating PCa grades.\u003c/p\u003e","manuscriptTitle":"Investigation of the association of tRNA-derived fragments (tRF-17-79MP9PP and tRF-18- 79MP9P04) with prostate cancer","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-22 10:28:37","doi":"10.21203/rs.3.rs-7353761/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-09-17T14:18:50+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-16T17:34:00+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"13575003033530288548783919063803323766","date":"2025-09-01T20:26:02+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"141174121776489768889130742802717585581","date":"2025-08-15T12:38:09+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-08-14T15:20:26+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-08-14T13:05:11+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-08-14T13:03:44+00:00","index":"","fulltext":""},{"type":"submitted","content":"Molecular Biology Reports","date":"2025-08-12T09:01:40+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"molecular-biology-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"mole","sideBox":"Learn more about [Molecular Biology Reports](https://www.springer.com/journal/11033)","snPcode":"11033","submissionUrl":"https://submission.nature.com/new-submission/11033/3","title":"Molecular Biology Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"772ca051-5a8a-4a8c-90c3-d89f7f9d8f03","owner":[],"postedDate":"August 22nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-10-27T16:25:46+00:00","versionOfRecord":{"articleIdentity":"rs-7353761","link":"https://doi.org/10.1007/s11033-025-11176-w","journal":{"identity":"molecular-biology-reports","isVorOnly":false,"title":"Molecular Biology Reports"},"publishedOn":"2025-10-23 16:16:36","publishedOnDateReadable":"October 23rd, 2025"},"versionCreatedAt":"2025-08-22 10:28:37","video":"","vorDoi":"10.1007/s11033-025-11176-w","vorDoiUrl":"https://doi.org/10.1007/s11033-025-11176-w","workflowStages":[]},"version":"v1","identity":"rs-7353761","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7353761","identity":"rs-7353761","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}