Ribosomopathy-like properties of murine and human cancers

Kulkarni, S. B.; Dolezal, James M.; Wang, Huabo; Jackson, Laura E.; Lu, Jie; Frodey, Brian P.; Dosunmu-Ogunbi, Atinuke; Li, Youjun; Fromherz, Marc; Kang, Audry; Santana-Santos, Lucas; Benos, Panayiotis V.; Prochownik, Edward V.

doi:10.1371/journal.pone.0182705

Cited by 33 publications

(65 citation statements)

References 52 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Together, these data argue for a role for Rps26-deficient cells in cancer progression. Furthermore, these data also demonstrate that cancer cells have found diverse means to effect loss of ribosomal protein stoichiometry, including changes in RP gene expression (Ajore et al, 2017;Guimaraes and Zavolan, 2016;Kulkarni et al, 2017;Vlachos, 2017), downregulation of the assembly factor Ltv1 leading to substoichiometric, Rps3, Rps10 and Asc1/RACK1 (Collins et al, 2018), and bypass of Rio1, leading to Rps26-deficient ribosomes.…”

Section: Bypassing the Rio1 Checkpoint Disturbs Protein Homeostasis Amentioning

confidence: 65%

“…haploinsufficiency results in a predisposition to the development of specific forms of cancer (Armistead and Triggs-Raine, 2014;Sulima et al, 2017;Vlachos, 2017), and furthermore, ribosomes from cancer cells often lose the stoichiometry of ribosomal proteins, including Rps26, which is correlated with poor patient outcomes (Ajore et al, 2017;Guimaraes and Zavolan, 2016;Kulkarni et al, 2017;Vlachos, 2017). Together, these data argue for a role for Rps26-deficient cells in cancer progression.…”

Section: Bypassing the Rio1 Checkpoint Disturbs Protein Homeostasis Amentioning

confidence: 99%

See 1 more Smart Citation

A kinase-dependent checkpoint prevents escape of immature ribosomes into the translating pool

Parker

Collins

Korona

et al. 2019

Preprint

View full text Add to dashboard Cite

Premature release of nascent ribosomes into the translating pool must be prevented, as these do not support viability and may be prone to mistakes. Here we show that the kinase Rio1, the nuclease Nob1, and its binding partner Pno1 cooperate to establish a checkpoint that prevents the escape of immature ribosomes into polysomes. Nob1 blocks mRNA recruitment, and rRNA cleavage is required for its dissociation from nascent 40S subunits, thereby setting up a checkpoint for maturation. Rio1 releases Nob1 and Pno1 from pre-40S ribosomes to discharge nascent 40S into the translating pool. Weakly binding Nob1 and Pno1 mutants can bypass the requirement for Rio1, and Pno1 mutants rescue cell viability. In these strains, immature ribosomes escape into the translating pool, where they cause fidelity defects and perturb protein homeostasis. Thus, the Rio1-Nob1-Pno1 network establishes a checkpoint that safeguards against the release of immature ribosomes into the translating pool.

show abstract

Section: Bypassing the Rio1 Checkpoint Disturbs Protein Homeostasis Amentioning

confidence: 65%

Section: Bypassing the Rio1 Checkpoint Disturbs Protein Homeostasis Amentioning

confidence: 99%

A kinase-dependent checkpoint prevents escape of immature ribosomes into the translating pool

Parker

Collins

Korona

et al. 2019

Preprint

View full text Add to dashboard Cite

show abstract

“…An alternative use of oxaloacetate, namely in gluconeogenesis, seems unlikely given the high rates of cell growth, the high glucose content of the cell culture medium used in these studies, and the fact that fibroblast gluconeogenesis is typically low (69,70). In addition to feedback inhibition of lactate dehydrogenase (LDH) by pyruvate and lactate (81), pyruvate carboxylase's 10 -30-fold lower K m value for pyruvate may also play a role (82)(83)(84)(85).…”

Section: Metabolic and Oncogenic Adaptations To Pdh Inactivationmentioning

confidence: 99%

“…Total lysates from WT and KO Rat1a-MycER cells were prepared in the presence of protease and phosphatase inhibitors as described previously (50,59,83). After SDS-PAGE, proteins were transformed to polyvinylidene difluoride membranes (Merck Millipore, Burlington, MA) and then probed with the antibodies listed in Table S2.…”

Section: Western Blottingmentioning

confidence: 99%

Metabolic and oncogenic adaptations to pyruvate dehydrogenase inactivation in fibroblasts

Wang

Kulkarni

et al. 2019

Journal of Biological Chemistry

Self Cite

View full text Add to dashboard Cite

Edited by Eric R. FearonEukaryotic cell metabolism consists of processes that generate available energy, such as glycolysis, the tricarboxylic acid (TCA) cycle, and oxidative phosphorylation (Oxphos), and those that consume it, including macromolecular synthesis, the maintenance of ionic gradients, and cellular detoxification. By converting pyruvate to acetyl-CoA (AcCoA), the pyruvate dehydrogenase (PDH) complex (PDC) links glycolysis and the TCA cycle. Surprisingly, disrupting the connection between glycolysis and the TCA cycle by inactivation of PDC has only minor effects on cell replication. However, the molecular basis for this metabolic re-equilibration is unclear. We report here that CRISPR/Cas9-generated PDH-knockout (PDH-KO) rat fibroblasts reprogrammed their metabolism and their response to short-term c-Myc (Myc) oncoprotein overexpression. PDH-KO cells replicated normally but produced surprisingly little lactate. They also exhibited higher rates of glycolysis and Oxphos. In addition, PDH-KO cells showed altered cytoplasmic and mitochondrial pH, redox states, and mitochondrial membrane potential (⌬⌿M). Conditionally activated Myc expression affected some of these parameters in a PDH-dependent manner. PDH-KO cells had increased oxygen consumption rates in response to glutamate, but not to malate, and were depleted in all TCA cycle substrates between ␣-ketoglutarate and malate despite high rates of glutaminolysis, as determined by flux studies with isotopically labeled glutamine. Malate and pyruvate were diverted to produce aspartate, thereby potentially explaining the failure to accumulate lactate. We conclude that PDH-KO cells maintain proliferative capacity by utilizing glutamine to supply high rates of AcCoA-independent flux through the bottom portion of the TCA cycle while accumulating pyruvate and aspartate that rescue their redox defects.

show abstract

“…In murine models of hepatoblastoma and hepatocellular carcinoma (HCC), we have previously observed that most transcripts encoding the 80 proteins comprising the 40S and 60S ribosomal subunits were significantly increased relative to those in normal livers [9,10]. Because these increases were not uniform, the overall transcript expression patterns were altered as well.…”

Section: Introductionmentioning

confidence: 99%

Sequential analysis of transcript expression patterns improves survival prediction in multiple cancers

2020

Self Cite

View full text Add to dashboard Cite

Background: Long-term survival in numerous cancers often correlates with specific whole transcriptome profiles or the expression patterns of smaller numbers of transcripts. In some instances, these are better predictors of survival than are standard classification methods such as clinical stage or hormone receptor status in breast cancer. Here, we have used the method of "t-distributed stochastic neighbor embedding" (t-SNE) to show that, collectively, the expression patterns of small numbers of functionally-related transcripts from fifteen cancer pathways correlate with long-term survival in the vast majority of tumor types from The Cancer Genome Atlas (TCGA). We then ask whether the sequential application of t-SNE using the transcripts from a second pathway improves predictive capability or whether t-SNE can be used to refine the initial predictive power of whole transcriptome profiling. Methods: RNAseq data from 10,227 tumors in TCGA were previously analyzed using t-SNE-based clustering of 362 transcripts comprising 15 distinct cancer-related pathways. After showing that certain clusters were associated with differential survival, each relevant cluster was re-analyzed by t-SNE with a second pathway's transcripts. Alternatively, groups with differential survival identified by whole transcriptome profiling were subject to a second, t-SNE-based analysis. Results: Sequential analyses employing either t-SNE➔t-SNE or whole transcriptome profiling➔t-SNE analyses were in many cases superior to either individual method at predicting long-term survival. We developed a dynamic and intuitive R Shiny web application to explore the t-SNE based transcriptome clustering and survival analysis across all TCGA cancers and all 15 cancer-related pathways in this analysis. This application provides a simple interface to select specific t-SNE clusters and analyze survival predictability using both individual or sequential approaches. The user can recreate the relationships described in this analysis and further explore many different cancer, pathway, and cluster combinations. Non-R users can access the application on the web at https://chpupsom19.shinyapps.io/ Survival_Analysis_tsne_umap_TCGA. The application, R scripts performing survival analysis, and t-SNE clustering results of TCGA expression data can be accessed on GitHub enabling users to download and run the application locally with ease (https://github.com/RavulaPitt/Sequential-t-SNE/).

show abstract

Ribosomopathy-like properties of murine and human cancers

Cited by 33 publications

References 52 publications

A kinase-dependent checkpoint prevents escape of immature ribosomes into the translating pool

A kinase-dependent checkpoint prevents escape of immature ribosomes into the translating pool

Metabolic and oncogenic adaptations to pyruvate dehydrogenase inactivation in fibroblasts

Sequential analysis of transcript expression patterns improves survival prediction in multiple cancers

Contact Info

Product

Resources

About