Similar Datasets
Project description:tRFs quantification in HaCaT cell culture
| PRJNA490195 | ENA
Project description:Despite being the leading cause of lung cancer death, the underlying molecular mechanisms driving metastasis progression are still not fully understood. tRNAs can generate a group of 18-40nt small RNA fragments named tRNA-derived small RNAs (tsRNAs) or tRNA-derived fragments (tRFs). Transfer RNA-derived fragments (tRFs) have been implicated in various biological processes in cancer. However, the role of tRFs in the development and progression of lung adenocarcinoma (LUAD) remains unclear. In the present study, we hypothesized that certain tRFs might become induced during LUAD metastatic progression. In this study, micropapillary and solid component was defined as high-risk, other component was defined as low-risk and adjcent tissue was defined as normal control. Our data revealed a series of dysregulated tRFs in 3 paired LUAD high-risk tissues, low-risk tissues and normal controls.
2024-07-04 | GSE271302 | GEO
Project description:tRNA-derived fragments (tRFs) are new noncoding RNAs, and recent studies have shown that tRNAs and tRFs have important functions in cell metabolism via posttranscriptional regulation of gene expression. However, whether tRFs regulate cellular metabolism of the anterior cruciate ligament (ACL) remains elusive. The aim of this study was to investigate the role and action mechanism of tRFs in ACL cell metabolism. Arraystar_tRF&tiRNA was used to determine tRFs and tiRNA expression profiles in human OA ACL cells and NA ACL cells。
2022-04-12 | GSE200433 | GEO
Project description:To explore the potential involvement of tRNA derived fragments (tRFs) in the human aortic vascular smooth muscle cells (HASMCs), we conducted tRFs profiling in three pairs of differentiated HASMCs (treated with PBS) and dedifferentiated HASMCs (treated with PDGF-BB 50 ng/ml) by microarray. Our results showed that tRFs were aberrantly expressed in dedifferentiated HASMCs compared with differentiated HASMCs and provided potential targets for novel insights into VSMC differentiation or vascular remodeling diseases.
2023-01-31 | GSE212737 | GEO
Project description:tRNA fragments (tRFs) populations analysis in mutants affecting tRNAs processing and tRNA methylation
| PRJEB35713 | ENA
Project description:Background: Congenital heart disease (CHD) is one of the most predominant birth defects that cause infant death worldwide. The timely and successful surgical treatment of CHD on newborns after delivery requires accurate detection and reliable diagnosis during pregnancy. However, there are no biomarkers that can serve as an early diagnostic factor for CHD patients. tRNA-derived fragments (tRFs) have been reported to play an important role in the occurrence and progression of numerous diseases, but their roles in CHD remains unknown. Methods: High-throughput sequencing was performed on the peripheral blood of pregnant women with abnormal fetal heart and normal fetal heart, and 728 differentially expressed tRFs/tiRNAs were identified, among which the top 18 tRFs/tiRNAs were selected as predictive biomarkers of CHD. Then, quantitative reverse transcriptase polymerase chain reaction verified the expression of tRFs/tiRNAs in more clinical samples, and the correlation between tRFs/tiRNAs abnormalities and CHD was analyzed. Results: tRF-58:74-Gly-GCC-1 and tiRNA-1:35-Leu-CAG-1-M2 may be promising biomarkers. Through further bioinformatics analysis, we predicted that TRF-58:744-GLy-GCC-1 could induce CHD by influencing biological metabolic processes. Conclusions: our results provide a theoretical basis for the abnormally expressed tRF-58:74-Gly-GCC-1 in maternal peripheral blood as a new potential biomarker for the accurate diagnosis of CHD during pregnancy.
2023-03-01 | GSE221349 | GEO
Project description:Breast cancer is one of the most common cancers in the world and non-triple-negative breast cancer (non-TNBC) accounts for 80-90% of all invasive breast cancers. Early detection of breast cancer is considered as key to successful treatment. Conventionally，breast imaging and needle core biopsy are used for detection and monitoring of disease progression. However, small volume changes may be ignored on imaging and traditional biopsy is spatially and temporally limited, leading to a significant lag time in detecting cancer progression. This thus prompted renewed focus on early and accurate diagnosis. In this article, we committed to investigate whether there exists accurate molecule in peripheral blood which can help diagnose breast cancer. tRNA-derived fragments (tRFs) have been reported to be involved in many pathological processes, but whether it can serve as biomarkers for the diagnosis of breast cancer remains unclear. Using high-throughput sequencing technology, we identified 4021 differentially expressed tRFs in normal breast epithelial cell lines and non-triple-negative breast cancer cell lines and 8 tRFs were selected to construct a signature to predict the non-TNBC. Further, qRT-PCR was conducted to verify its expression and to analyze the correlation between dysregulated tRFs and breast cancer. The results indicated that tDR-7816, tDR-5334, tDR-4733 might be promising biomarkers. Through further bioinformatics analysis, we predicted that tDR-7816 influences xenobiotic metabolic process that support the oncogenesis of breast cancer. Taken together, our results provide a rationale for using circulating tDR-7816 expression as a novel potential biomarker to diagnose early non-TNBC patients.
2019-10-30 | GSE134992 | GEO
Project description:Purpose:In recent years, tRFs(transfer RNA-Derived Fragments) & tiRNAs (transfer RNA-Derived Stress-induced RNAs or tRNA halves) have been shown to have vital roles in cancer biology. We aimed to reveal the expression profile of tRFs&tiRNAs in breast cancer tissues in the study, and to explore their potential as biomarkers of breast cancer. Methods:We characterize tRFs&tiRNAs expression profiles in 6 pairs of breast cancer tissues and adjacent normal samples.Then we selected six tRFs&tiRNAs with significant expression and added 10 pairs of samples to verify the selected genes by qPCR in 16 pairs of breast cancer tissues along with the previous 6 pairs. Results:We found 31 differentially expressed tRFs&tiRNAs across our dataset, out of which 17 were up-regulated, 14 were down-regulated. Compared with 16 breast cancer tissues and healthy controls by qPCR, the results demonstrated that AS-tDR-001430, AS-tDR-001130 and AS-tDR-000779 were significantly expressed in breast cancer tissues (p < 0.001). AS-tDR-000779 was significantly up-regulated, AS-tDR-001430 and AS-tDR-001130 were significantly down-regulated which the expression patterns were similar to the sequencing results. Conclusions:Our studies have demonstrated that there were significantly expressed tRFs&tiRNAs in breast cancer tissues. They are hopefully to become biomarkers and would be valuable researches in this area.
2020-01-21 | GSE123967 | GEO
Project description:Here, we adopt a method that combines tRNA-seq and cp-RNA-seq to identify and quantify tRFs and tRNAs in plants. We provide a high-quality expression atlas of tRFs and tRNAs in Arabidopsis and rice, and uncovers complex tRFs repertoire and the dynamic expressions of tRNA genes in plants.
2021-01-01 | GSE124608 | GEO
Project description:8-week brain total tRNA, total tRNA fragments (tRFs), and ribosome-contained tRNAs were sequenced using MiSeq.
2021-03-31 | GSE153757 | GEO