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Abstract LB-90: Molecular mechanism of TAZ-induced lung tumorigenesis

2014· article· en· W2049044463 on OpenAlexaff
Adel B Alharbi, Hongchao Shan, Yawei Hao, Xiaolong Yang

Bibliographic record

VenueCancer Research · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHippo pathway signaling and YAP/TAZ
Canadian institutionsQueen's University
Fundersnot available
KeywordsCarcinogenesisHippo signaling pathwayBiologyCancer researchActivator (genetics)Cell cultureCell growthCell biologyNude mouseCellNeoplastic transformationGeneMolecular biologySignal transductionGenetics

Abstract

fetched live from OpenAlex

Abstract The transcriptional co-activator with PDZ-binding domain (TAZ) is a transcriptional co-activator and major component of an emerging signaling pathway called the Hippo pathway that plays critical roles in tumorigenesis, organ size control, stem cell renewal, drug resistance, etc. Recently, we have provided the first biological evidence that TAZ is over-expressed in non-small cell lung cancer (NSCLC) cells and over-expression of TAZ can transform HBE135 immortalized non-tumorigenic human lung epithelial cells (Zhou et al., 2011). However, the cellular genes mediating TAZ-induced transformation are unknown. In addition, there is no in vivo mouse model established to study the roles of TAZ in lung tumorigenesis in vivo. To address these issues, we have carried out the following experiments: First, a Dox-inducible lentiviral expression system was used to overexpress constitutively active TAZ (TAZ-S89A) in a mouse immortalized lung epithelial cell line (E10). Overexpression of TAZ-S89A in E10 cells caused increased cell proliferation, transformation, and tumor formation in vivo in nude mice. Next, tumorigenic stable cell lines (TAZS89A-TM) were established after isolating TAZS89A-induced tumors from mice. Second, to identify the downstream genes mediating TAZ-induced tumor formation, the technology of Next-generation sequencing (RNA-seq) was performed on the new tumorigenic cell line E10-TAZ-TM to identify downstream genes transcriptionally regulated by TAZ after induction of TAZ by Dox. By analyzing the data and confirming them using qRT-PCR, multiple significant oncogenes were found activated by TAZ overexpression. Third, these genes were knocked down by shRNAs in the tumorigenic E10-TAZS89A-TM cell line and tested whether they are important in TAZ-induced cell proliferation, transformation and tumor formation in mice. Finally, since previous studies indicate that TAZ is involved in mammary cell growth by interacting with transcription factor TEAD or through its WW domain, we also tested whether these genes are activated through TEAD-binding domain or WW-domain of TAZ. E10 stable cell lines overexpressing inducible TAZ mutant with amino acid mutations in TEAD-binding domain (TAZ-F52A/F53A) or WW domain (TAZ-W152A/P155A) were established, followed by qRT-PCR analysis. The TEAD-binding domain of TAZ was found necessary for activation of the identified genes and maintaining TAZ-induced oncogenic effects in lung cells. In conclusion, this project established the first in vivo xenograft mouse model system using TAZ-overexpressing lung epithelial cells, and identified the downstream target genes mediating TAZ-induced lung tumorigenesis. Citation Format: Adel B. Alharbi, Hongchao Shan, Yawei Hao, Xiaolong Yang. Molecular mechanism of TAZ-induced lung tumorigenesis. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr LB-90. doi:10.1158/1538-7445.AM2014-LB-90

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 score0.009

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 communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.044
GPT teacher head0.369
Teacher spread0.325 · 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
Published2014
Admission routes1
Has abstractyes

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