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Record W2071998244 · doi:10.1158/1538-7445.am10-123

Abstract 123: Cooperative regulation between proliferative signals by activated Ras and inhibitors of apoptosis (IAPs) in gliomagenesis

2010· article· en· W2071998244 on OpenAlexaff
Joydeep Mukherjee, Amparo Wolf, Cynthia Hawkins, Abhijit Guha

Bibliographic record

VenueCancer Research · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCell death mechanisms and regulation
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsSurvivinXIAPGene knockdownCancer researchInhibitor of apoptosisGliomaApoptosisBiologyChemistryProgrammed cell deathCaspaseBiochemistry

Abstract

fetched live from OpenAlex

Abstract Transformation requires not only aberrant proliferation through signaling pathways such as activated Ras as demonstrated by our lab in GBMs, but also aberrant inhibition of regulators of apoptosis. Towards the latter, little is known about the expression and function of a family of proteins known as Inhibitors of Apoptosis Proteins (IAPs), which includes cIAP1, cIAP2, XIAP and Survivin, in GBMs. Human tumors which are prevalent in activating Ras mutations, such as colon and pancreatic cancers, produce high amounts of Survivin. We hypothesize that elevated activity of Ras in GBMs, as previously described by us, leads to aberrant expression of IAPs in GBMs and through its anti-apoptotic functions plays a role in glioma transformation. Our previously described GFAP:12V-HaRas (RasB8) transgenic mouse glioma model was utilized. Elevated expression of activated Ras in the mouse gliomas was accompanied with increased expression of XIAP and Survivin. This was also prevalent in expression in human GBM cells, with elevated Ras activity. Knockdown of Ha-Ras in human and mouse GBM cells, by transfecting with couple of siRNA targeted against Ha-Ras gene, significantly decreased XIAP and Survivin levels. Knockdown of Ha-Ras in the mouse and human GBM cells increased their sensitivity to apoptosis inducing chemotherapy. Current experiments include a genetic approach to down regulate Ras activity, by expression of a dominant-negative form of the Ha-Ras (Ha-Ras N17), in GBM cells and evaluating regulation of XIAP and Survivin expression. These experiments will be complemented with farnesyl transferase inhibitors to also inhibit Ras activity in the glioma cells. A Tet-inducible strategy to over express activated Ha-Ras in both transformed and non-transformed mouse and human astrocytes is being undertaken. These in vitro studies will be complemented by in vivo studies involving breeding our RasB8 glioma model to double transgenics with GFAP-Cre regulated decreased expression of Survivinflox/flox in astrocytes, with a postulated decrease in gliomagenic potential. The results to date and those underway are highly suggestive of the thesis that elevated Ras activity leads to glial transformation by not only mitogenic signals, but also by cooperative expression of anti-apoptotic proteins, such as IAPS. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 123.

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 score0.002
Threshold uncertainty score0.008

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.029
GPT teacher head0.350
Teacher spread0.322 · 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
Published2010
Admission routes1
Has abstractyes

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