MétaCan
Menu
Back to cohort
Record W2316751273 · doi:10.1158/1538-7445.am2012-1362

Abstract 1362: Developing genetically flexible mouse models of sarcoma - a novel functional genomics platform

2012· article· en· W2316751273 on OpenAlexaff
Amar Gupta, Serena Menezes, Leah Kabaroff, Brendan C. Dickson, Carol J. Swallow, Rebecca A. Gladdy

Bibliographic record

VenueCancer Research · 2012
Typearticle
Languageen
FieldMedicine
TopicNeuroblastoma Research and Treatments
Canadian institutionsMount Sinai Hospital
Fundersnot available
KeywordsBiologyGermlineSarcomaSkeletal muscleCancer researchTransgeneGenetically modified mouseDesminGreen fluorescent proteinPathologyImmunohistochemistryImmunologyMedicineGeneticsGeneVimentinEndocrinology

Abstract

fetched live from OpenAlex

Abstract Introduction: Sarcomas are a heterogeneous group of malignant neoplasms that arise from connective tissues and have a disease-specific mortality of 30-50%. Existing mouse models of sarcomagenesis utilize knockout and transgenic mice but it is unclear if fixed germline mutations recapitulate sporadic human cancer. In addition, creating germline mutant mice requires substantial time and resources. We hypothesized that delivery of oncogenes into mouse skeletal muscle using a retroviral (RCAS) system would result in sarcomagenesis and could mitigate the limitations of conventional mouse models. Methods: p16/p19 null mice expressing the retroviral receptor, TVA, under nestin (N-tva) or β-actin (BKE) promoters were used. DF1 chicken fibroblasts, infected with avian-leukosis virus vectors (RCAS) carrying combinations of oncogenes (KrasG12D, c-Myc, IGF2) or GFP alone, were delivered by injection into the hindlegs of neonatal mice and tumor development was monitored. Results: GFP-positive cells were observed following in vitro infection of cultured mouse skeletal muscle with RCAS-GFP and GFP+ myoblasts were identified from mice injected with RCAS-GFP in vivo, suggesting successful cell infection and targeted gene delivery. Sarcomas formed in 30% of p16/p19−/−xN-tva mice at the injection site with a median latency of 23.5 weeks (8-42 weeks). Several subtypes of sarcoma developed in this strain based on morphologic assessment and immunohistochemistry (S100, desmin, and smooth muscle actin). Of these, malignant peripheral nerve sheath tumor (MPNST) that overexpressed EGFR consistent with human MPNST, was the predominant subtype (55%). Although a similar tumor incidence occurred in the p16/p19−/−xBKE strain (32%), the median latency was much shorter, 10.4 weeks (7-25 weeks) and the tumor spectrum shifted to predominantly fibrosarcoma (36%) or rhabdomyosarcoma (36%). No tumors were observed in mice injected with empty RCAS vector or without inactivation of the p16/p19 locus. Gene-anchored PCR revealed retroviral vector DNA integration in 89% of N-tva and 97% of BKE tumors. KrasG12D was the most frequent oncogene isolated. Conclusions: We have generated novel models of sarcomagenesis using the RCAS-TVA system to deliver known sarcoma oncogenes into mouse hind legs with a tumor incidence of ∼30%. With optimization, we will be able to use this genetically flexible system to functionally validate novel candidate sarcoma genes. 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 1362. doi:1538-7445.AM2012-1362

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)0.001
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 score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.002

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 head0.275
GPT teacher head0.421
Teacher spread0.145 · 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
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueCancer ResearchSame topicNeuroblastoma Research and TreatmentsFrench-language works237,207