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Record W2325719154 · doi:10.1158/1538-7445.fbcr11-b32

Abstract B32: Telomerase activity confers growth and DNA damage survival advantages in telomerase-negative transformed human cells

2011· article· en· W2325719154 on OpenAlexaff
Helen B. Fleisig, Judy M.Y. Wong

Bibliographic record

VenueCancer Research · 2011
Typearticle
Languageen
FieldMedicine
TopicTelomeres, Telomerase, and Senescence
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsTelomeraseTelomereTelomerase reverse transcriptaseBiologyCarcinogenesisCell growthOncogeneCell cycleCancer researchTelomerase RNA componentCell biologyCellMolecular biologyCancerDNAGeneticsGene

Abstract

fetched live from OpenAlex

Abstract Constitutively high telomerase activity is detected in more than 85% of human cancers. Together with the activation of oncogenic growth through RAS-oncogene-associated signal transduction pathways and the inactivation of tumor suppressor pathways regulated by p53 and Rb, telomerase reverse transcriptase expression promotes tumorigenic transformation of human cells. The prevalence of telomerase, rather than a homologous recombination-based mechanism, for telomere length maintenance in human cancers, suggests that telomerase has auxiliary roles in tumorigenesis. Here, we investigate growth advantages provided by the telomerase enzyme in oncogene-transformed human cells that do not require telomerase activity for telomere length control. We employed retroviral vector directed expression of telomerase components in human cell models that utilize the alternate lengthening of telomeres (ALT) mechanism for telomere maintenance. Forced expression of telomerase in ALT cells did not abolish the ALT mechanism, and ALT molecular characteristics were maintained in the resultant cell lines. Our data indicates that in these oncogene-transformed ALT cells, telomerase activity accelerates cell growth kinetics and promotes anchorage-independent growth. Co-culture experiments demonstrated that this growth advantage conferred by telomerase activity is not transferable by cytokine exchange and not likely the result of increased cellular crosstalk. Growth advantages provided by telomerase required all functional aspects of the enzyme. Dissociation-of-activities telomerase mutants and other functionally defective versions of telomerase were unable to promote oncogene-transformed cell growth, implying that canonical telomerase activities may be involved. Telomerase-positive ALT cells pass through the cell division phases of the cell cycle with increased kinetics, suggesting that the observed cell growth advantage is cumulative over cycles of proliferation. In addition, telomerase-positive ALT cells displayed an increased tolerance to the cytotoxic effects of DNA damaging agents that cause double-stranded DNA breaks. We conclude that telomerase expression provides growth and survival advantages to oncogene-transformed human cells; this supports the development of telomerase-based anticancer chemotherapies targeting these growth-promoting effects. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the Second AACR International Conference on Frontiers in Basic Cancer Research; 2011 Sep 14-18; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2011;71(18 Suppl):Abstract nr B32.

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 score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
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)0.0040.001

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 head0.130
GPT teacher head0.402
Teacher spread0.273 · 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
Published2011
Admission routes1
Has abstractyes

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