Assessing the diagnostic utility of tRNA-derived fragments as biomarkers of head and neck cancer

Roughly 54,000 individuals are diagnosed with head and neck cancers in the United States yearly. Transfer RNA-derived fragments (tRF) are the products of enzymatic cleavage of precursor tRNAs, and have been proposed for use as biomarkers of head and neck cancer. In this study, we aim to further analyze the utility that tRFs might provide as biomarkers of head and neck cancer. tRF read counts were obtained for 453 tumor and 44 adjacent normal tissue samples and used to construct a gradient boosting diagnostic model. Although we identified 129 tRFs that were significantly dysregulated between these samples, the model achieved a sensitivity of only 69 % and a specificity of 59 %. tRFs are thought to induce the degradation of mRNA transcripts containing a complementary "seed" region. Despite the above performances, we chose to explore this concept of translational regulation by analyzing these tRFs for inverse correlation to the expression of select oncogenes and tumor suppressor genes implicated in head and neck cancer. Among others, CysGCA 5'-half and LysCTT 3'-tRF were upregulated in the tumor samples, and corresponded to decreased expression of PIK3R1, AKT1, and CPEB3. These transcripts were further found to contain numerous significantly complementary sites at which tRF-mediated mRNA degradation might occur. Although these tRFs did appear to correlate to many of the oncogenic metrics analyzed, we believe that additional research is needed before they might be used to improve the diagnosis, treatment, and survival of patients with this disease.

Authors

Institutions

Publication Details

Journal
Translational Oncology
Published
2024-09-23
DOI
https://doi.org/10.1016/j.tranon.2024.102135
Citations
1
Primary Topic
RNA modifications and cancer
Type
article
Field-Weighted Citation Impact
0.23

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Assessing the diagnostic utility of tRNA-derived fragments as biomarkers of head and neck cancer

Matthew Uzelac, Weg M. Ongkeko
1 citations
Translational Oncology
RNA modifications and cancer
0.23
article

Assessing the diagnostic utility of tRNA-derived fragments as biomarkers of head and neck cancer

Matthew Uzelac, Weg M. Ongkeko
article en
1 citations

Abstract

Roughly 54,000 individuals are diagnosed with head and neck cancers in the United States yearly. Transfer RNA-derived fragments (tRF) are the products of enzymatic cleavage of precursor tRNAs, and have been proposed for use as biomarkers of head and neck cancer. In this study, we aim to further analyze the utility that tRFs might provide as biomarkers of head and neck cancer. tRF read counts were obtained for 453 tumor and 44 adjacent normal tissue samples and used to construct a gradient boosting diagnostic model. Although we identified 129 tRFs that were significantly dysregulated between these samples, the model achieved a sensitivity of only 69 % and a specificity of 59 %. tRFs are thought to induce the degradation of mRNA transcripts containing a complementary "seed" region. Despite the above performances, we chose to explore this concept of translational regulation by analyzing these tRFs for inverse correlation to the expression of select oncogenes and tumor suppressor genes implicated in head and neck cancer. Among others, CysGCA 5'-half and LysCTT 3'-tRF were upregulated in the tumor samples, and corresponded to decreased expression of PIK3R1, AKT1, and CPEB3. These transcripts were further found to contain numerous significantly complementary sites at which tRF-mediated mRNA degradation might occur. Although these tRFs did appear to correlate to many of the oncogenic metrics analyzed, we believe that additional research is needed before they might be used to improve the diagnosis, treatment, and survival of patients with this disease.

Translational OncologyVol. 50
UC San Diego Health System (US), VA San Diego Healthcare System (US)
University of California, San Diego
Good health and well-being
Openalex Percentile: Top 42%
RNA modifications and cancer
0.23
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.