MétaCan
Menu
← Back to cohort
Record W2328620161 · doi:10.1158/1538-7445.am2012-961

Abstract 961: Pathways of tumorigenesis promoted by the growth factor progranulin in SW-13 adrenocortical carcinoma cells

2012· article· en· W2328620161 on OpenAlexaff
Yonghua Zhang, Amin Ismail, Andrew Bateman

Bibliographic record

VenueCancer Research · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer, Hypoxia, and Metabolism
Canadian institutionsMcGill University
Fundersnot available
KeywordsBiologyCancer researchAphidicolinCell growthAdrenocortical carcinomaCell cycleEndocrinologyInternal medicineCancerMedicine

Abstract

fetched live from OpenAlex

Abstract Adrenocortical carcinomas are highly malignant cancers, with a very low 5 year survival rate. The SW-13 cell line originated from a stage IV adrenocortical carcinoma, but is only poorly tumorigenic in mice. It can, however, be made highly tumorigenic in vivo if it is engineered to express a limited number of growth factors including progranulin (PGRN, also called PCDGF, granulin epithelin precursor, or proepithelin) and secreted FGFs. This provides a model system to study the transition of an adrenocortical carcinoma from low to a high malignant potential. PGRN is a secreted glycoprotein growth factor that is over produced by many cancers including those of the breast, ovary, endometrium, prostate, bladder, and liver. It acts on cancer growth by increasing mitosis, decreasing apoptosis and stimulating invasion. In addition, PGRN has been implicated as a stimulator of tumor stroma growth in breast cancer. We examined the expression of PGRN in SW-13 cells at different stages of the cell cycle. Cells were synchronized using two independent agents, L-Mimosine and aphidicolin to arrest cell division. Washout of the drugs released the SW-13 cells into the cell cycles with slow (L-Mimosine) or rapid (aphidicolin) kinetics, and PGRN expression increased in parallel with the increased proportion of cells in active cell division. Depleting PGRN mRNA levels slowed reentry into the cell cycle following drug removal. Inhibition of MEK1/2, phosphatidylinositol-3 kinase (PI3K), protein kinase C (PKC) and phospholipase-C-α (PLCγ) impairs proliferation of SW-13 cells carrying only empty vector (SW-13V) with differential effects on mitosis and apoptosis. In cells with elevated PGRN, (SW-13P), the anti-proliferative effects of inhibiting MEK1/2, PI3K and PKC, but not PLCγ, are attenuated. Inhibition of the stress kinase p38 increases proliferation of SW-13V, but not SW-13P cells, suggesting that PGRN and p38 have opposing effects on proliferation. Inhibition of p38 enhances the phosphorylation of MEK1/2 in SW-13V cells, while inhibiting PKC decreases it, suggesting that PKC and p38 pathways interact with the PGRN-regulated MEK1/2 signaling cascade. Transcriptional profiling indicated that expression of PGRN modulated levels of proteins in the Wnt and Notch-signaling pathways. These results suggest that PGRN expression may be coordinated with the cell cycle, and, may promote tumorigenesis by intervening in several signaling pathways. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 961. doi:1538-7445.AM2012-961

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

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)0.0010.001

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 head0.050
GPT teacher head0.334
Teacher spread0.284 · 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 designObservational
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
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueCancer Research→Same topicCancer, Hypoxia, and Metabolism→French-language works237,207→