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Record W2318200996 · doi:10.1158/1538-7445.am2013-3108

Abstract 3108: A novel role for hPygo2 in ribosomal RNA transcription.

2013· article· en· W2318200996 on OpenAlexaff
Phillip Andrews, Kenneth R. Kao

Bibliographic record

VenueCancer Research · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicNutrition, Genetics, and Disease
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsBiologyChromatin immunoprecipitationChromatin remodelingChromatinCell biologyTranscription (linguistics)HistoneRibosomal proteinMolecular biologyRibosomeGene expressionRNAPromoterGeneGenetics

Abstract

fetched live from OpenAlex

Abstract Background: Several ribosomes are required for each translated messenger RNA. During cell growth and division, a significant proportion of cellular resources are devoted to the production of ribosomes, but the epigenetic mechanisms by which cells adjust to this requirement are not fully understood. We have previously demonstrated that human Pygopus 2 (hPygo2) is highly expressed in, and required for the growth of a number of different cancers. hPygo2 functions as a chromatin remodeling protein through direct association with trimethylated Histone H3 at lysine4 (H3K4me3). It is here that hPygo2 likely serves as an adapter to which histone acetyltransferases can bind and promote further chromatin remodeling events required for transcription. We now present evidence that hPygo2 is involved in chromatin remodeling at the ribosomal (r)RNA promoter during proliferative growth of cancer cells. Methods: Immunoprecipitation (IP) and immunofluorescence (IF) was performed in breast (MCF7), ovarian (SKOV3) and cervical (HeLa) cancer cells. siRNAs were designed to specifically deplete hPygo2. For hPygo2 binding to the ribosomal gene promoter, chromatin IPs were used and analyzed by conventional or quantitative (q) PCR. 47S rRNA expression was measured by qPCR or by pulse-chase with either Br-UTP or 3H-uridine. Cell cycle analysis was performed by flow cytometry. Results: We found that hPygo2 interacted with UBF-1 and Treacle, two nucleolar proteins involved in 47S rRNA transcription. hPygo2 co-localized with UBF-1 and Treacle along with newly synthesized de novo rRNA in the nucleoli of cancer cells. hPygo2 was further detected at the ribosomal gene promoter along with core components of the rDNA transcription complex, including RNA polymerase I. Furthermore, hPygo2 was required for Histone H4 acetylation at the rRNA promoter and for transcription of the 47S pre-rRNA. Depletion of hPygo2 was accompanied by activation of the ribosomal stress response, detected by the binding of ribosomal protein L11 to hdm2, thereby inhibiting its E3 ubiquitin ligase activity resulting in p53 dependent growth arrest. Conclusion: Our results suggest that chromatin remodeling function of hPygo2 may serve to augment or maintain 47S pre-rRNA transcription required for ribosome biogenesis in cancer. Citation Format: Phillip G. P. Andrews, Kenneth R. Kao. A novel role for hPygo2 in ribosomal RNA transcription. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 3108. doi:10.1158/1538-7445.AM2013-3108

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.051
GPT teacher head0.364
Teacher spread0.313 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2013
Admission routes1
Has abstractyes

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