Association of Aminoacyl-tRNA Synthetases with Cancer

Kim, Doyeun; Kwon, Nam Hoon; Kim, Sung Hoon

doi:10.1007/128_2013_455

Cited by 40 publications

(24 citation statements)

References 154 publications

(256 reference statements)

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“…Numerous genetic mutations are associated with CMT and, interestingly, these mutations are found in several aaRSs (reviewed in (Boczonadi et al 2018;Wei et al 2019), amongst which are the genes for GlyRS (Antonellis et al 2003), TyrRS (Jordanova et al 2006;Blocquel et al 2017), LeuRS or AlaRS (Latour et al 2010). An increasing body of results has also uncovered links with cancer, with almost half the synthetases connected directly or indirectly with cancer (reviewed in (Kim et al 2013). For example, LysRS promotes anabolic cellular processes and growth regulating the mTORC1 pathway (Han et al 2012) while ThrRS can be secreted by apoptotic cells and plays a role in angiogenesis (Arif et al 2009).…”

Section: Aarss In Diseasementioning

confidence: 99%

Aminoacyl-tRNA synthetases

Rubio

Ibba

2020

RNA

263

176

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The aminoacyl-tRNA synthetases are an essential and universally distributed family of enzymes that plays a critical role in protein synthesis, pairing tRNAs with their cognate amino acids for decoding mRNAs according to the genetic code. Synthetases help to ensure accurate translation of the genetic code by using both highly accurate cognate substrate recognition and stringent proofreading of noncognate products. While alterations in the quality control mechanisms of synthetases are generally detrimental to cellular viability, recent studies suggest that in some instances such changes facilitate adaption to stress conditions. Beyond their central role in translation, synthetases are also emerging as key players in an increasing number of other cellular processes, with far-reaching consequences in health and disease. The biochemical versatility of the synthetases has also proven pivotal in efforts to expand the genetic code, further emphasizing the wide-ranging roles of the aminoacyl-tRNA synthetase family in synthetic and natural biology.

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Section: Aarss In Diseasementioning

confidence: 99%

Aminoacyl-tRNA synthetases

Rubio

Ibba

2020

RNA

263

176

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“…Specifically, 28 proteins were identified as ribosomal proteins that play essential roles in protein synthesis and are involved in cancer tumorigenesis (31)(32)(33). In addition, four are aminoacyl-tRNA synthases that are implicated in several noncanonical functions, such as angiogenesis and tumorigenesis (34,35). Therefore, the combination of proteomic and bioinformatics analyses of differentially expressed proteins in tissues improves our understanding of the potential molecules involved in the early stages of cancer tumorigenesis and provides valuable information for lung cancer biomarker discovery.…”

Section: Pathway Analysis Of 133 Proteins Up-regulated In Cancer Tissmentioning

confidence: 99%

Identification and Characterization of Potential Biomarkers by Quantitative Tissue Proteomics of Primary Lung Adenocarcinoma

Hsu

Hsueh

et al. 2016

Molecular & Cellular Proteomics

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Lung cancer is the leading cause of cancer-related death worldwide. Both diagnostic and prognostic biomarkers are urgently needed to increase patient survival. In this study, we identified/quantified 1763 proteins from paired adenocarcinoma (ADC) tissues with different extents of lymph node (LN) involvement using an iTRAQ-based quantitative proteomic analysis. Based on a bioinformatics analysis and literature search, we selected six candidates (ERO1L, PABPC4, RCC1, RPS25, NARS, and TARS) from a set of 133 proteins that presented a 1.5-fold increase in expression in ADC tumors without LN metastasis compared with adjacent normal tissues. These six proteins were further verified using immunohistochemical staining and Western blot analyses. The protein levels of these six candidates were higher in tumor tissues compared with adjacent normal tissues. The ERO1L and NARS levels were positively associated with LN metastasis. Importantly, ERO1L overexpression in patients with early-stage ADC was positively correlated with poor survival, suggesting that ERO1L overexpression in primary sites of early-stage cancer tissues indicates a high risk for cancer micrometastasis. Moreover, we found that knockdown of either ERO1L or NARS reduced the viability and migration ability of ADC cells. Our results collectively provide a potential biomarker data set for ADC diagnosis/prognosis and reveal novel roles of ERO1L and NARS in ADC progression. Molecular & Cellular Proteomics 15:

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“…TPR domains can be found in a diverse number of proteins, where they mediate protein-protein interactions; particularly in the formation of protein complexes. The strong significant (P<0.001) over-representation with aminoacyl-tRNA synthetase functions (and the weaker, though still significant over-representation of amino acid metabolism functions) observed here is particularly interesting, as there is evidence that TPR-containing proteins can act as interacting mediators and co-chaperones in the formation of aminoacyl-tRNA synthetases (Han et al, 2007; Kim et al, 2014); suggesting that this protein may have a role in assisting amino acid loading of tRNAs in Arabidopsis. The third gene interrogated (AT1G80270) had a significant enrichment of edges with (i) RNA processing (P<0.001) and (ii) protein biosynthesis - organelle translation machineries (P<0.05).…”

Section: Applicationmentioning

confidence: 71%

Enhancing the biological relevance of Gene Co-expression Networks: A plant mitochondrial case study

Law

Kellgren

Björk

et al. 2019

Preprint

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Gene Co-expression Networks (GCNs) are obtained by a variety of mathematical of models commonly derived on data sampled from diverse developmental processes, tissue types, pathologies, mutant backgrounds, and stress conditions. These networks aim to identify genes with similar expression dynamics, but are prone to introduce false-positive and -negative relations, especially in the instance of large and highly complex datasets. With the aim of optimizing the relevance of edges in GCNs and enhancing global biological insight, we propose a novel approach that involves a data-centering step performed simultaneously per gene and per sub-experiment, called centralisation within sub-experiments (CSE).Using a gene set encoding for the plant mitochondrial proteome as a case study, our results show that CSE-based GCNs had significantly more edges within the majority of the considered functional sub-networks, such as the mitochondrial electron transport chain and its sub-complexes, than GCNs not using CSE; thus demonstrating that the CSE-based GCNs are efficient at predicting those canonical functions and associated pathways, also referred to as the “core network”. Furthermore, we show that CSE, in conjunction with conventional correlation analyses can be used to fine-tune the prediction of the function for uncharacterised genes; while in combination with analyses based on non-centralised data can augment those conventional stress analyses with the innate connections underpinning the dynamic system examined.Therefore, CSE appears as an alternative method to conventional batch correction approaches. The method is easy to implement into a pre-existing GCN analysis pipeline and can provide accentuated biological relevance to conventional GCNs by allowing users to delineate a “core” gene network.Author SummaryGene Co-expression networks (GCNs) are the product of a variety of mathematical models that identify causal relationships in gene expression dynamics, but are prone to the misdiagnoses of false-positives and -negatives, especially in the instance of large and highly complex datasets. In light of the burgeoning output of next generation sequencing projects performed on any species, under different developmental or clinical conditions, the statistical power and complexity of these networks will undoubtedly increase, while their biological relevance will be fiercely challenged. Here, we propose a novel approach to primarily generate a “core” GCN with augmented biological relevance. Our method, which involves data-centering steps and thus effectively removes all primary treatment / tissue /patient effects, is simple to employ and can be easily implemented into pre-existing GCN analysis pipelines. The gained biological relevance of such an approach was validated using a subcellular gene set encoding for the plant mitochondrial proteome, and by applying numerous steps to challenge its application.

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Association of Aminoacyl-tRNA Synthetases with Cancer

Cited by 40 publications

References 154 publications

Aminoacyl-tRNA synthetases

Aminoacyl-tRNA synthetases

Identification and Characterization of Potential Biomarkers by Quantitative Tissue Proteomics of Primary Lung Adenocarcinoma

Enhancing the biological relevance of Gene Co-expression Networks: A plant mitochondrial case study

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