The ribosome, (slow) beating heart of cancer (stem) cell

Bastide, Amandine; David, Alexandre

doi:10.1038/s41389-018-0044-8

Cited by 97 publications

(79 citation statements)

References 202 publications

(208 reference statements)

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“…Other studies also report that RP perturbations can affect the translation of hundreds of genes organized in coherent functional groups [24,39]. RPs are routinely dysregulated in the context of cancer [36,40], and adjusted throughout cell growth and metabolic cycles [41]. Our measurements of differential RP stoichiometries of ribosomes isolated via sucrose gradients also suggest broader mRNA specificity [23].…”

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confidence: 63%

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Ribosome stoichiometry: from form to function.

Emmott

Jovanović

Slavov

2018

Preprint

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The existence of eukaryotic ribosomes with distinct ribosomal protein (RP) stoichiometry and regulatory roles in protein synthesis been speculated for over sixty years. Recent advances in mass spectrometry and high throughput analysis have begun to identify and characterize distinct ribosome stoichiometry in yeast or mammalian systems. In addition to RP stoichiometry, ribosomes play host to a vast array of protein modifications, effectively expanding the number of human RPs from 80 to many thousands of distinct proteoforms. Is it possible these proteoforms combine to function as a 'ribosome code' to tune protein synthesis? We outline the specific benefits that translational regulation by specialized ribosomes can offer and discuss the means and methodologies available to correlate and characterize RP stoichiometry with function. We highlight previous research with a focus on formulating hypotheses that can guide future experiments and crack the 'ribosome code'.Ribosomes, the cellular machinery of protein synthesis, are present at up to ten million copies per cell in mammals. Despite their abundance and the wide array of known modifications to both ribosomal proteins (RPs) and rRNA, study of the direct role of the ribosome in tuning cellular translation has until recently taken a back seat to posttranscriptional regulation at the level of translation initiation. The hypothesis that ribosomes actively regulate protein synthesis as part of normal development and physiology dates back to the 1950s [1]. In the ensuing decades, numerous albeit inconclusive, observations have supported this hypothesis, and a subset of those are shown in Figure 1, color-coded by the type of evidence.For many years, the dominant 'abundance' model of translational regulation by the ribosome suggested a limited role for ribosomes in translation regulation [2]. In this model, if ribosomes have different initiation affinity for different transcripts, a global decrease in the availability of free ribosomes selectively decreases the initiation rates of different transcripts to varying degrees [2]. This mechanism, recently reviewed by Mills and Green [4], relies on the non-linear dependence of translation initiation on free ribosomes and applies quite generally. Indeed, recent research from the Sankaran lab suggested this mechanisms could explain the failure of erythroid lineage commitment seen with Diamond-Blackfan anaemia [5] 2 by the abundance model is limited in magnitude by the changes of total ribosomal content and in flexibility since it provides unidirectional regulation for all proteins.The concept of ribosome specialization In the 'specialized' ribosome model, ribosomes do not possess constant structure or composition (Figure 2A, B), and instead exhibit altered stoichiometry of what were previously thought to represent 'core' ribosomal proteins (Figure 1) [7,8]. In this model, different ribosomal compositions are functional and have specific roles in translation. Specialized ribosomes could co-exist within cells, or between ...

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confidence: 63%

“…Much of this evidence is in the context of mutation or knockout settings rather than in wild-type cells [5, 35,36]. Conceivably, each ribosomal structure -characterized by its rRNA and protein composition, and their modifications -might be specific to a single mRNA transcript, or even a single transcript isoform.…”

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confidence: 99%

Ribosome stoichiometry: from form to function.

Emmott

Jovanović

Slavov

2018

Preprint

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“…It is implicated in regulation of ribosomal translation [201] and has increased expression associated with poorer survival in lung cancer patients [202]. The interactions described above suggest gemcitabine may be more effective in the context of “oncogenic ribosomes” [262]. (6) CKA2 , the alpha catalytic subunit of casein kinase 2, has two human homologs, CSNK2A1 and CSNK2A2, which were OES with gemcitabine.…”

Section: Resultsmentioning

confidence: 99%

A humanized yeast phenomic model of deoxycytidine kinase to predict genetic buffering of nucleoside analog cytotoxicity

Santos

Icyuz

Pound

et al. 2019

Preprint

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10Knowledge about synthetic lethality can be applied to enhance the efficacy of 11 anti-cancer therapies in individual patients harboring genetic alterations in their cancer 12 that specifically render it vulnerable. We investigated the potential for high-resolution 13 phenomic analysis in yeast to predict such genetic vulnerabilities by systematic, 14 comprehensive, and quantitative assessment of drug-gene interaction for gemcitabine 15 and cytarabine, substrates of deoxycytidine kinase that have similar molecular structures 16 yet distinct anti-tumor efficacy. Human deoxycytidine kinase (dCK) was conditionally 17 expressed in the S. cerevisiae genomic library of knockout and knockdown (YKO/KD) 18 strains, to globally and quantitatively characterize differential drug-gene interaction for 19 gemcitabine and cytarabine. Pathway enrichment analysis revealed that autophagy, 20 histone modification, chromatin remodeling, and apoptosis-related processes influence 21 gemcitabine specifically, while drug-gene interaction specific to cytarabine was less 22 enriched in Gene Ontology. Processes having influence over both drugs were DNA 23 repair and integrity checkpoints and vesicle transport and fusion. Non-GO-enriched 24 genes were also informative. Yeast phenomic and cancer cell line pharmacogenomics 25 data were integrated to identify yeast-human homologs with correlated differential gene 26 2 expression and drug-efficacy, thus providing a unique resource to predict whether 27 differential gene expression observed in cancer genetic profiles are causal in tumor-28 specific responses to cytotoxic agents. 29 30 Keywords: 31 yeast phenomics, gene-drug interaction, genetic buffering, quantitative high 32 throughput cell array phenotyping (Q-HTCP), cell proliferation parameters (CPPs), 33 gemcitabine, cytarabine, recursive expectation-maximization clustering (REMc), 34 pharmacogenomics 35 36 Introduction: 37Genomics has enabled targeted therapy aimed at cancer driver genes and 38 oncogenic addiction [1], yet traditional cytotoxic chemotherapeutic agents remain among 39 the most widely used and efficacious anti-cancer therapies [2]. Changes in the genetic 40 network underlying cancer can produce vulnerabilities to cytotoxic chemotherapy that 41 further influence the therapeutic window and provide additional insight into their 42 mechanisms of action [3,4]. A potential advantage of so-called synthetic lethality-based 43 treatment strategies is that they could have efficacy against passenger gene mutation or 44 compensatory gene expression, while classic targeted therapies are directed primarily at 45 driver genes ( Fig. 1A). Quantitative high throughput cell array phenotyping of the yeast 46 knockout and knockdown libraries provides a phenomic means for systems level, high- 47resolution modeling of gene interaction [5][6][7][8][9], which is applied here to predict cancer-48 relevant drug-gene interaction through integration with cancer pharmacogenomics 49 resources ( Fig. 1B). 50Nucleoside analogs include a diverse group of co...

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“…17 Functional connection of the nucleolus to cell cycle is further evidenced by a nucleolar surveillance system, in which the cell cycle checkpoint system senses and acts to avert nucleolar stress arising from ribosomal synthesis impairment. [38][39][40][41] To the myriad of control mechanisms that underlie this pivotal cellular structure, this study has added a new and important regulatory pathway by linking members of apoptotic pathway-from p53/CEP-1 to caspase/ CED-3-to the expression of FIB-1 and ribosomal RNA, and consequently nucleolar size in C. elegans (Figure 6). This mechanism also hinges on a key nucleolar deubiquitinylase USP36, which has been implicated in the stabilization of fibrillarin and the large subunit of RNA polymerase I (Rpa190), and consequently the homeostasis of nucleolar structure and ribosome biogenesis.…”

Section: Discussionmentioning

confidence: 99%

Nucleolar control by a non‐apoptotic p53‐caspases‐deubiquitinylase axis promotes resistance to bacterial infection

Chen

Chu

et al. 2019

The FASEB Journal

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This is an open access article under the terms of the Creat ive Commo ns Attri butio n-NonCo mmercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes. AbstractThe nucleolus is best known for its cellular role in regulating ribosome production and growth. More recently, an unanticipated role for the nucleolus in innate immunity has recently emerged whereby downregulation of fibrillarin and nucleolar contraction confers pathogen resistance across taxa. The mechanism of this downregulation, however, remains obscure. Here we report that rather than fibrillarin itself being the proximal factor in this pathway, the key player is a fibrillarin-stabilizing deubiquitinylase USP-33. This was discovered by a candidate-gene search of Caenorhabditis elegans in which CED-3 caspase was revealed to execute targeted cleavage of USP-33, thus destabilizing fibrillarin. We also showed that cep-1 and ced-3 mutant worms altered nucleolar size and decreased antimicrobial peptide gene, spp-1, expression rendering susceptibility to bacterial infection. These phenotypes were reversed by usp-33 knockdown, thus linking the CEP-1-CED-3-USP-33 pathway with nucleolar control and resistance to bacterial infection in worms. Parallel experiments with the human analogs of caspases and USP36 revealed similar roles in coordinating these two processes. In summary, our work outlined a conserved cascade that connects cell death signaling to nucleolar control and innate immune response.

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The ribosome, (slow) beating heart of cancer (stem) cell

Cited by 97 publications

References 202 publications

Ribosome stoichiometry: from form to function.

Ribosome stoichiometry: from form to function.

A humanized yeast phenomic model of deoxycytidine kinase to predict genetic buffering of nucleoside analog cytotoxicity

Nucleolar control by a non‐apoptotic p53‐caspases‐deubiquitinylase axis promotes resistance to bacterial infection

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