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. 2024 Oct 2;25(19):10631.
doi: 10.3390/ijms251910631.

Computational Analysis Suggests That AsnGTT 3'-tRNA-Derived Fragments Are Potential Biomarkers in Papillary Thyroid Carcinoma

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Computational Analysis Suggests That AsnGTT 3'-tRNA-Derived Fragments Are Potential Biomarkers in Papillary Thyroid Carcinoma

Annie N Do et al. Int J Mol Sci. .

Abstract

Transfer-RNA-derived fragments (tRFs) are a novel class of small non-coding RNAs that have been implicated in oncogenesis. tRFs may act as post-transcriptional regulators by recruiting AGO proteins and binding to highly complementary regions of mRNA at seed regions, resulting in the knockdown of the transcript. Therefore, tRFs may be critical to tumorigenesis and warrant investigation as potential biomarkers. Meanwhile, the incidence of papillary thyroid carcinoma (PTC) has increased in recent decades and current diagnostic technology stands to benefit from new detection methods. Although small non-coding RNAs have been studied for their role in oncogenesis, there is currently no standard for their use as PTC biomarkers, and tRFs are especially underexplored. Accordingly, we aim to identify dysregulated tRFs in PTC that may serve as biomarker candidates. We identified dysregulated tRFs and driver genes between PTC primary tumor samples (n = 511) and adjacent normal tissue samples (n = 59). Expression data were obtained from MINTbase v2.0 and The Cancer Genome Atlas. Dysregulated tRFs and genes were analyzed in tandem to find pairs with anticorrelated expression. Significantly anticorrelated tRF-gene pairs were then tested for potential binding affinity using RNA22-if a heteroduplex can form via complementary binding, this would support the hypothesized RNA silencing mechanism. Four tRFs were significantly dysregulated in PTC tissue (p < 0.05), with only AsnGTT 3'-tRF being upregulated. Binding affinity analysis revealed that tRF-30-RY73W0K5KKOV (AsnGTT 3'-tRF) exhibits sufficient complementarity to potentially bind to and regulate transcripts of SLC26A4, SLC5A8, DIO2, and TPO, which were all found to be downregulated in PTC tissue. In the present study, we identified dysregulated tRFs in PTC and found that AsnGTT 3'-tRF is a potential post-transcriptional regulator and biomarker.

Keywords: PTC; THCA; biomarker; non-coding RNA; tRF; tRNA-derived fragment; thyroid cancer; thyroid carcinoma.

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Conflict of interest statement

The authors declare no conflicts of interest.

Figures

Figure 1
Figure 1
Box plots depicting the differential expression of tRFs between primary papillary thyroid carcinoma (PTC), primary tumor samples (n = 511), and normal samples (n = 59). All results were filtered by p < 0.05 following the Benjamini–Hochberg correction.
Figure 2
Figure 2
Box plots depicting the differential expression of genes that have been implicated in thyroid cancer between primary papillary thyroid carcinoma (PTC) primary tumor samples (n = 511) and normal samples (n = 59). All results were filtered by p < 0.05 following the Benjamini–Hochberg correction.
Figure 3
Figure 3
Scatterplots showing the negative relationship between tRF expression and gene expression (r < 0, p < 0.05). Gene expression was plotted against tRF expression and formatted with trendlines. All results were filtered by p < 0.05 following the Benjamini–Hochberg correction.
Figure 4
Figure 4
Binding affinity between anticorrelated tRF-gene pairs was predicted using base pair complementarity. Bar plots depicting each instance of predicted binding between tRF-30-RY73W0K5KKOV (AsnGTT 3′-tRF) and the target gene (SLC26A4, SLC5A8, DIO2, and TPO). (A) shows the negative logarithm of the test statistic and the target region’s start and end position in brackets. The dotted red line indicates the benchmark for statistical significance (−log(0.05)). (B) depicts the corresponding binding energy predicted to be released by the heteroduplex in Kcal/mol.

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This research received no external funding.