tRNA over-expression in breast cancer and functional consequences
Open accessAbstract
Increased proliferation and elevated levels of protein synthesis are characteristics of transformed and tumor cells. Though components of the translation machinery are often misregulated in cancers, what role tRNA plays in cancer cells has not been explored. We compare genome-wide tRNA expression in cancer-derived versus non-cancer-derived breast cell lines, as well as tRNA expression in breast tumors versus normal breast tissues. In cancer-derived versus non-cancer-derived cell lines, nuclear-encoded tRNAs increase by up to 3-fold and mitochondrial-encoded tRNAs increase by up to 5-fold. In tumors versus normal breast tissues, both nuclear- and mitochondrial-encoded tRNAs increase up to 10-fold. This tRNA over-expression is selective and coordinates with the properties of cognate amino acids. Nuclear- and mitochondrial-encoded tRNAs exhibit distinct expression patterns, indicating that tRNAs can be used as biomarkers for breast cancer. We also performed association analysis for codon usage-tRNA expression for the cell lines. tRNA isoacceptor expression levels are not geared towards optimal translation of house-keeping or cell line specific genes. Instead, tRNA isoacceptor expression levels may favor the translation of cancer-related genes having regulatory roles. Our results suggest a functional consequence of tRNA over-expression in tumor cells. tRNA isoacceptor over-expression may increase the translational efficiency of genes relevant to cancer development and progression.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
A human tRNA microarray has been developed for tRNA quantification and has been applied in tRNA profiling in HIV-1, specific human tissues and tumor cells, and in identifying the complete interactome of tRNA-binding proteins.
“A human tRNA microarray has been developed for tRNA quantification and has been applied in tRNA profiling in HIV-1 (51), as well as of specific human tissues and tumor cells, and in identifying the complete interactome of tRNA-binding proteins (136 -138).”
From Role of host tRNAs and aminoacyl-tRNA synthetases in retroviral replication (2019) · cites this paper as [137]
The Introduction (page not available in our copy) says the authors applied a human tRNA microarray to breast cancer cell lines, breast tumors, and normal breast tissue, supporting the tumor and tissue profiling portion. It describes the array as previously developed, and our copy does not report identifying a complete interactome of tRNA-binding proteins. HIV-1 profiling is attached to a separate citation (51) in the citing sentence. (LLM, conf=0.86)
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
No references could be resolved yet.
Research works printed but not linked: 31
- [1]Bjornsti MA Houghton PJ Lost in translation: dysregulation of cap-dependent translation and cancer Cancer Cell 2004 5 519 523 15193254
- [2]Pandolfi PP Aberrant mRNA translation in cancer pathogenesis: an old concept revisited comes finally of age Oncogene 2004 23 3134 3137 15094762
- [3]Ruggero D Pandolfi PP Does the ribosome translate cancer? Nat Rev Cancer 2003 3 179 192 12612653
- [4]White RJ RNA polymerase III transcription and cancer Oncogene 2004 23 3208 3216 15094770
- [5]Winter AG Sourvinos G Allison SJ Tosh K Scott PH Spandidos DA White RJ RNA polymerase III transcription factor TFIIIC2 is overexpressed in ovarian tumors Proc. Natl Acad. Sci. USA 2000 97 12619 12624 11058163 PMC18813
- [6]Marshall L White RJ Non-coding RNA production by RNA polymerase III is implicated in cancer Nat. Rev. Cancer 2008 8 911 914 18987635
- [7]Chen W Bocker W Brosius J Tiedge H Expression of neural BC200 RNA in human tumours J. Pathol. 1997 183 345 351 9422992
- [8]Chen W Heierhorst J Brosius J Tiedge H Expression of neural BC1 RNA: induction in murine tumours Eur. J. Cancer 1997 33 288 292 9135502
- [9]Marshall L Kenneth NS White RJ Elevated tRNA(iMet) synthesis can drive cell proliferation and oncogenic transformation Cell 2008 133 78 89 18394991
- [10]Zouridis H Hatzimanikatis V Effects of codon distributions and tRNA competition on protein translation Biophys. J. 2008 95 1018 1033 18359800 PMC2479585
- [11]Bertucci F Goncalves A Clinical proteomics and breast cancer: strategies for diagnostic and therapeutic biomarker discovery Future Oncol. 2008 4 271 287 18407739
- [12]Payne SJ Bowen RL Jones JL Wells CA Predictive markers in breast cancer – the present Histopathology 2008 52 82 90 18171419
- [13]Rennstam K Hedenfalk I High-throughput genomic technology in research and clinical management of breast cancer. Molecular signatures of progression from benign epithelium to metastatic breast cancer Breast Cancer Res. 2006 8 213 16895590 PMC1779477
- [14]Lander ES Linton LM Birren B Nusbaum C Zody MC Baldwin J Devon K Dewar K Doyle M FitzHugh W Initial sequencing and analysis of the human genome Nature 2001 409 860 921 11237011
- [15]Lowe TM Eddy SR tRNAscan-SE: a program for improved detection of transfer RNA genes in genomic sequence Nucleic Acids Res. 1997 25 955 964 9023104 PMC146525
- [16]Soll D Transfer RNA: an RNA for all seasons The RNA World 1993 Cold Spring Harbor, NY Cold Spring Harbor Laboratory Press 157 184
- [17]Dittmar KA Goodenbour JM Pan T Tissue-specific differences in human transfer RNA expression PLoS Genet. 2006 2 e221 17194224 PMC1713254
- [18]Saikia M Dai Q Decatur WA Fournier MJ Piccirilli JA Pan TA Systematic, ligation-based approach to study RNA modifications RNA 2006 12 2025 2033 16963711 PMC1624908
- [19]Dittmar KA Sorensen MJ Elf J Ehrenberg M Pan T Selective charging of tRNA isoacceptors induced by amino-acid starvation EMBO Rep. 2005 6 151 157 15678157 PMC1299251
- [20]Dittmar KA Mobley EM Radek AJ Pan T Exploring the regulation of tRNA distribution on the genomic scale J. Mol. Biol. 2004 337 31 47 15001350
- [21]Zaborske JM Narasimhan J Jiang L Wek SA Dittmar KA Freimoser F Pan T Wek RC Genome-wide analysis of tRNA charging and activation of the eIF2 kinase Gcn2p J. Biol. Chem. 2009 284 25254 25267 19546227 PMC2757228
- [22]Zhou Y Goodenbour JM Godley LA Wickrema A Pan T High levels of tRNA abundance and alteration of tRNA charging by bortezomib in multiple myeloma Biochem. Biophys. Res. Commun. 2009 385 160 164 19450555 PMC2774282
- [23]Neve RM Chin K Fridlyand J Yeh J Baehner FL Fevr T Clark L Bayani N Coppe JP Tong F A collection of breast cancer cell lines for the study of functionally distinct cancer subtypes Cancer Cell 2006 10 515 527 17157791 PMC2730521
- [24]Xu Y Kool ET High sequence fidelity in a non-enzymatic DNA autoligation reaction Nucleic Acids Res. 1999 27 875 881 9889286 PMC148260
- [25]Xu Y Karalkar NB Kool ET Nonenzymatic autoligation in direct three-color detection of RNA and DNA point mutations Nat. Biotechnol. 2001 19 148 152 11175729
- [26]Ikemura T Correlation between the abundance of Escherichia coli transfer RNAs and the occurrence of the respective codons in its protein genes: a proposal for a synonymous codon choice that is optimal for the E. coli translational system J. Mol. Biol. 1981 151 389 409 6175758
- [27]Ikemura T Correlation between the abundance of yeast transfer RNAs and the occurrence of the respective codons in protein genes. Differences in synonymous codon choice patterns of yeast and Escherichia coli with reference to the abundance of isoaccepting transfer RNAs J. Mol. Biol. 1982 158 573 597 6750137
- [28]Kanaya S Yamada Y Kudo Y Ikemura T Studies of codon usage and tRNA genes of 18 unicellular organisms and quantification of Bacillus subtilis tRNAs: gene expression level and species-specific diversity of codon usage based on multivariate analysis Gene 1999 238 143 155 10570992
- [29]Hu Y Analysis of genomic and proteomic data using advanced literature mining J. Proteome Res. 2003 2 405 412 12938930
- [30]Eisenberg E Levanon EY Human housekeeping genes are compact Trends Genet. 2003 19 362 365 12850439
- [31]Hatfield D Rice M Aminoacyl-tRNA(anticodon): codon adaptation in human and rabbit reticulocytes Biochem. Int. 1986 13 835 842 3643795
Cited by
Sorted by citations
Codon optimality, bias and usage in translation and mRNA decay
Hanson, G., & Coller, J. (2018) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm.2017.91 · Cited by 825 · see citing works
New frontiers in translational control of the cancer genome
Truitt, M. L., & Ruggero, D. (2016) · Nature Reviews Cancer · doi:10.1038/nrc.2016.27 · Cited by 378 · see citing works
Silent Substitutions Predictably Alter Translation Elongation Rates and Protein Folding Efficiencies
Spencer, P. S., Siller, E., Anderson, J. F., & Barral, J. M. (2012) · Journal of Molecular Biology · doi:10.1016/j.jmb.2012.06.010 · Cited by 278 · see citing works
Kwon, N. H., Kang, T., Lee, J. Y., Kim, H. H., Kim, H. R., Hong, J., Oh, Y. S., Han, J. M., Ku, M. J., Lee, S. Y., et al. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1103922108 · Cited by 120 · see citing works
Codon and amino acid content are associated with mRNA stability in mammalian cells
Forrest, M. E., Pinkard, O., Martin, S., Sweet, T. J., Hanson, G., & Coller, J. (2020) · PLOS ONE · doi:10.1371/journal.pone.0228730 · Cited by 116 · see citing works
The Role of Translation Control in Tumorigenesis and Its Therapeutic Implications
Xu, Y., & Ruggero, D. (2020) · Annual Review of Cancer Biology · doi:10.1146/annurev-cancerbio-030419-033420 · Cited by 67 · see citing works
Role of host tRNAs and aminoacyl-tRNA synthetases in retroviral replication
Jin, D., & Musier-Forsyth, K. (2019) · Journal of Biological Chemistry · doi:10.1074/jbc.rev118.002957 · Cited by 67 · see citing works
Profiling non-lysyl tRNAs in HIV-1
Pavon-Eternod, M., Wei, M., Pan, T., & Kleiman, L. (2010) · RNA · doi:10.1261/rna.1928110 · Cited by 62 · see citing works
Self-citation
- Authors
- Pavon-Eternod, M., Gomes, S., Geslain, R., Dai, Q., Rosner, M. R., & Pan, T.
- Affiliations
- University of Chicago (US)
- Corresponding author
- Rosner, Marsha Rich
- Pan, Tao
- Venue
- Nucleic Acids Research
- Publisher
- Oxford University Press (OUP)
- Published
- 2009-09-25
- Volume
- 37
- Issue
- 21
- Pages
- 7268-7280
- ISSN
- 0305-1048 (ISSN-L)
- 1362-4962
- PMC
- PMC2790902
- OpenAlex
- W2112243735
- Cited by
- 296
- References
- 0
- Citations by year
- 2026: 7 · 2025: 10 · 2024: 8 · 2023: 21 · 2022: 22 · 2021: 23 · 2020: 28 · 2019: 25 · 2018: 23 · 2017: 22 · 2016: 29 · 2015: 19 · 2014: 22 · 2013: 8 · 2012: 12
- FWCI
- 3.90
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Nucleic Acids Research (publishedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- Funders
- National Institutes of Health (W81XWH)
- National Institute of General Medical Sciences (T32GM007183)
- Congressionally Directed Medical Research Programs (W81XWH-07-1-0595)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA and protein synthesis mechanisms
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA modifications and cancer
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › PI3K/AKT/mTOR signaling in cancer
- Keywords
- breast cancer, mitochondrial tRNA, tRNA isoacceptors, codon usage, translation efficiency, tumor markers, cancer cell lines, protein synthesis
- MeSH terms
- Breast, Breast Neoplasms, Cell Line, Codon, Female, Humans, Nucleotides, RNA, Transfer, Oligonucleotide Array Sequence Analysis, Gene Expression Profiling, Cell Line, Tumor, Genes, Neoplasm
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review