Evidence map›Paper›PMID 23844615›Full record

ReviewExpert opinion on drug discovery2013

Xenograft and genetically engineered mouse model systems of osteosarcoma and Ewing's sarcoma: tumor models for cancer drug discovery.

Valerie B Sampson, Davida F Kamara, E Anders Kolb

Abstract readReview
In one paragraph

Review in Expert opinion on drug discovery, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

22 citing papers in PubMed.

  1. The veterinary quarterly · 2025
    Article
  2. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Valerie B SampsonA.I. duPont Hospital for Children, Cancer Therapeutics Laboratory , 1701 Rockland Rd, Wilmington DE, 19803 , USA.
Davida F Kamara
E Anders Kolb

Funding

Center for Pediatric ResearchP20GM103464 · NIGMS · NEMOURS CHILDREN'S HOSPITAL, DELAWARE · PI SHAFFER, THOMAS H · 2012 to 2014
$5.6M
NIGMS NIH HHS P20 GM103464
6 · The paper itself

Abstract

introductionThere are > 75 histological types of solid tumors that are classified into two major groups: bone and soft-tissue sarcomas. These diseases are more prevalent in children, and pediatric sarcomas tend to be highly aggressive and rapidly progressive. Sarcomas in adults may follow a more indolent course, but aggressive tumors are also common. Sarcomas that are metastatic at diagnosis, or recurrent following therapy, remain refractory to current treatment options with dismal overall survival rates. A major focus of clinical trials, for patients with sarcoma, is to identify novel and more effective therapeutic strategies targeted to genomic or proteomic aberrations specific to the malignant cells. Critical to the understanding of the potential for targeted therapies are models of disease that are representative of clinical disease and predictive of relevant clinical responses. AREAS COVERED: In this article, the authors discuss the use of mouse xenograft models and genetically engineered mice in cancer drug discovery. The authors provide a special focus on models for the two most common bone sarcomas: osteosarcoma (OS) and Ewing's sarcoma (ES). EXPERT OPINION: Predicting whether a new anticancer agent will have a positive therapeutic index in patients with OS and ES remains a challenge. The use of mouse sarcoma models for understanding the mechanisms involved in the response of tumors to new treatments is an important step in the process of drug discovery and the development of clinically relevant therapeutic strategies for these diseases.

Indexed as

Mice, TransgenicAnimalsAntineoplastic AgentsBone NeoplasmsDrug DiscoveryMiceOsteosarcomaSarcoma, EwingSarcoma, ExperimentalXenograft Model Antitumor AssaysAntineoplastic Agents

Identifiers

PMID23844615
PMCPMC4122324

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.