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Expression Profiles of Trna-Derived Fragments and Their Potential Roles in Multiple Myeloma

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Expression Profiles of Trna-Derived Fragments and Their Potential Roles in Multiple Myeloma OncoTargets and Therapy Dovepress open access to scientific and medical research Open Access Full Text Article ORIGINAL RESEARCH Expression Profiles of tRNA-Derived Fragments and Their Potential Roles in Multiple Myeloma Cong Xu1 Background: Multiple myeloma is an incurable hematologic malignancy. The discovery of Yunfeng Fu2 mechanisms may help to find new therapeutic targets and prolong survival. tRNA-related fragments (tRF) and tRNA halves (tiRNA) are small RNA derived from tRNAs and 1Department of Hematology, The Third Xiangya Hospital of Central South implicated in a wide variety of pathological processes, including cancer initiation and University, Changsha, 410000, People’s progression. However, there are almost no research reporting the role of these tRNA derived 2 Republic of China; Department of Blood fragments in myeloma as far as we know. Transfusion, The Third Xiangya Hospital of Central South University, Changsha, Methods: In this study, we proposed the expression profiles of tRFs/tiRNAs in myeloma 410000, People’s Republic of China through RNA-sequencing in new diagnosed myeloma and healthy donors. The expression of selected tRFs/tiRNAs was further validated in clinical specimens by qPCR. Bioinformatic analysis was performed to predict their potential roles in multiple myeloma. Results: A total of 33 upregulated tRFs/tiRNAs and 22 downregulated tRFs/tiRNAs were identified. GO enrichment and KEGG pathway analysis were performed to analyze the functions of one significantly up-regulated and one significantly down-regulated tRNA- derived fragments. tRFs/tiRNAs may be involved in MM initiation and progression. Conclusion: We concluded that tRFs/tiRNAs were dysregulated and could be potential biomarkers for multiple myeloma. Keywords: multiple myeloma, tRNA related fragments, tRNA halves, cancer initiation Introduction Multiple myeloma (MM) is the second most common hematological malignancy and is characterized by the accumulation of malignant plasma cells in the bone marrow.1 With the advent of new drugs, such as proteasome inhibitors and immu­ nomodulatory agents, the outcomes of patients with MM have steadily improved. Despite improvements in response and survival rates, MM remains a costly and incurable disease.2,3 Elucidating the mechanisms governing MM development is pivotal to optimizing the clinical efficacy and prolonging survival. Myeloma cells are dependent on multiple factors at all stages of tumor development and progres­ sion. Among these factors, noncoding RNAs (ncRNAs) play critical roles.4,5 The largest portion of the mammalian genome is transcribed into RNA species with little or no coding potential, which are known as ncRNAs. An explosion of interest in RNA biology has identified a variety of regulatory functions for ncRNAs.6,7 With the rapid development of high-throughput sequencing in recent years, a new class of small ncRNAs derived from tRNAs has attracted increasing attention from researchers. Correspondence: Yunfeng Fu According to the cleavage site, these tRNA derived fragments can be broadly Tel/Fax + 86-73188618511 Email [email protected] classified into two main groups: tRNA related fragments (tRFs) generated from OncoTargets and Therapy 2021:14 2805–2814 2805 © 2021 Xu and Fu. This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php). Xu and Fu Dovepress mature or precursor tRNA and tRNA halves (tiRNAs) Table 1 Primers for qRT-PCR Validation of Candidate tRFs/ generated by specific cleavage in the anticodon loops of tiRNAs 8 mature tRNA. On the basis of mapped positions on the Primer precursor or mature tRNA transcript, tRFs/tiRNAs are iRNA-1:34-Glu- F: 5ʹAGGCTCCCACATGGTCTAGC3’ subdivided into five types: tRF-5, tRF-3, tRF-1, tRF-2 TTC-2 R: 5ʹCAGTGCAGGGTCCGAGGTAT3’ and tiRNA. tRFs/tiRNAs are involved in various molecu­ tRF-60:76-Arg- F: 5ʹATTATCCTGGCTGGCTCGCC3’ lar processes through translation regulation, epigenetic ACG-1-M2 R: 5ʹCCGAGGTATTCGCACTGGA3’ regulation and RNA silencing.9,10 Accumulating evidence supports the significance of tRF-1:23-Ala-AGC F: 5ʹTAAACCGGGGGTATAGCTCAGT3’ -1-M3 R:5ʹCAGTGCAGGGTCCGAGGTAT3’ tRFs/tiRNAs in multiple human diseases, including cancer. For example, some sex hormone-dependent tRF-1:16-Lys-TTT F: 5ʹCTTTGCCCGGATAGCTCAGT3’ tRNA-derived RNAs were found to enhance cell pro­ -3-M2 R: 5ʹCAGTGCAGGGTCCGAGGTAT3’ liferation in breast cancer cells and to act as oncogenes tRF-1:22-Leu-AAG F: 5ʹATTGGTAGCGTGGCCGAGT3’ in breast cancer.11 tRF-1001, which is present in the -4-M2 R: 5ʹCGCAGGGTCCGAGGTATTC3’ cytoplasm and produced by the tRNA 3ʹ-endonuclease tRF-+1:T14-Gly- F: 5ʹACCCTGCGGTACCACTTTGT3’ ELAC2, is essential for the proliferation of prostate TCC-1 R: 5ʹCGCAGGGTCCGAGGTATTC3’ 12 cancer cells and colorectal cancer cells. Upregulated U6 F: 5ʹGCTTCGGCAGCACATATACTAAAAT3’ or downregulated tRFs/tiRNAs are both involved in the R: 5ʹCGCTTCACGAATTTGCGTGTCAT3’ occurrence and development of solid tumors.13,14 In hematological malignancies, limited data have demon­ strated the potential roles played by tRFs/tiRNAs in National Comprehensive Cancer Network (NCCN). Bone leukemia and lymphoma.15,16 To the best of our knowl­ marrow was obtained from NDMM patients and healthy edge, few studies have described the roles played by donors after informed consent. tRFs/tiRNAs in the mechanism underlying MM. One study showed that smoldering multiple myeloma Table 2 Baseline Characteristics of MM Patients and Healthy patients with lower expression levels of 3′-tRF- Donors LeuAAG/TAG, i-tRF-GluCTC, and i-tRF-ProTGG were at great risk of suffering from MM.17 However, MM Healthy Donors (n=20) (n=18) the expression profile of tRFs/tiRNAs in myeloma patients compared to healthy people has not been Age determined. Median - yr 59 55 Range - yr 38–75 31–68 In this study, we investigated the expression profiles of tRFs/tiRNAs in paired newly diagnosed MM and healthy Sex donor samples through RNA-sequencing and quantitative Male 11(55.0) 11(61.1) Female 9(45.0) 7(38.9) real-time PCR (qPCR) verification. Next, using bioinfor­ matics analysis, we characterized the functions of these ECOG performance RNAs in the initiation and progression of MM. These status 0 7(35.0) – findings may provide potential biomarkers and therapeutic 1 11(55.0) – targets for MM. 2 2(10.0) – R-ISS stage Materials and Methods I 3(15.0) – Clinical Samples II 6(30.0) – III 11(55.0) – This study was approved by ethics committee of the third Xiangya hospital. Twenty new diagnosed MM(NDMM) Cytogenetics patients and 18 healthy donors were enrolled, respectively. High risk 6(30.0) – Standard risk 12(60.0) – The diagnosis of NDMM was based on the diagnostic Unknown/missing 2(10.0) – criteria of symptomatic multiple myeloma defined by 2806 http://doi.org/10.2147/OTT.S302594 OncoT argets and Therapy 2021:14 DovePress Dovepress Xu and Fu RNA Extraction and Quantitative RT-PCR Library Preparation and Sequencing Validation Firstly, total RNA samples were pretreated to remove Firstly, plasma cells were enriched from bone marrow RNA modifications that interfere with small RNA-seq samples using the anti-human CD138 magnetic- library construction. The libraries then were denatured as activated cell sorting (MACS) beads (Miltenyi, single-stranded DNA molecules, captured on Illumina Germany). The purity of separated plasma cells was flow cells, amplified in situ as sequencing clusters and sequenced for 50 cycles on Illumina NextSeq 500 system above 90% (identified by flow cytometry). Total RNA following the manufacturer’s instructions. Image analysis was then extracted from enriched plasma cells using and base calling were conducted by Solexa pipeline v1.8 TRIzol (Invitrogen, USA) following the instruction man­ (Off-Line Base Caller software, v1.8). ual. Prepared RNA was preserved at −80°C. RNA sam­ Sequencing quality was examined by FastQC. The ples were qualified and quantified by agarose gel abundance of tRFs/tiRNAs was evaluated by sequencing electrophoresis and NanoDrop ND-1000 (NanoDrop, counts and normalized as counts per million of total USA). qRT-PCR was implemented using ViiA 7 Real- aligned reads (CPM). R package edgeR was used to cal­ time PCR System (Applied Biosystems) and 2 × PCR culate the differentially expressed tRFs/tiRNAs. Master Mix. U6 small nuclear RNA (snRNA) was used Hierarchical clustering, Volcano plots, Pie plots and Venn as internal reference. The fold changes were calculated plots were constructed by R or Perl. and normalized by U6. The primers used are listed in Table 1. RNA quality is shown in Supplementary Table 1. Bioinformatic Analysis of tRFs/tiRNAs RNA integrity number (RIN) was evaluated by Agilent We used TargetScan algorithms to predict gene targets of BioAnalyzer 2100 and was all above 7. tRFs/tiRNAs.18 Gene Ontology (GO) and Kyoto A B 10 tiRNA-5 10 tiRNA-5 tRF-5c tRF-5c tRF-5b tRF-5b tRF-5a tRF-5a r r e e b b 5 5 tRF-3b tRF-3b m m u u n n tRF-1 tRF-3a tRF-2 tRF-1 0 0 C A G C C C T T T T C G G G C T G A T T T T T T A C C G C T T C C T T C G A C T T C A A A T T C G G G T A A C C T G T C T T A T C -T G A C T G C T A -G -C - -C -G - - r- - -T -A - - - - -A - - - - - - - - l- - s n u y y s s r l g n ln ly le u u s s r r r r r l a la y l l l l y y e h a r l I e e y y e h h h y a A C G G G G L L S T V A G G G L L L L S T T T T V V C D tiRNA-5 tRF-1 tRF-5c (1) tRF-1(2) (1) tRF-2 tiRNA-5(3) (1) tRF-3b(2) tRF-5b (1) tRF-1 (1) tRF-1 tRF-3b tRF-2 tRF-5a tRF-3a tRF-5b tRF-3b tRF-5a (7) tRF-5a tRF-5c tRF-3a(6) tRF-5b tRF-5a(5) tiRNA-5 tRF-5c tiRNA-5 tRF-5c (13) tRF-5b (6) tRF-3b(6) Figure 1 Categories of tRFs/tiRNAs in MM patients and healthy donors.
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