Using a rhabdomyosarcoma patient‐derived xenograft to examine precision medicine approaches and model acquired resistance. Issue 9 (31st March 2014)
- Record Type:
- Journal Article
- Title:
- Using a rhabdomyosarcoma patient‐derived xenograft to examine precision medicine approaches and model acquired resistance. Issue 9 (31st March 2014)
- Main Title:
- Using a rhabdomyosarcoma patient‐derived xenograft to examine precision medicine approaches and model acquired resistance
- Authors:
- Monsma, David J.
Cherba, David M.
Richardson, Patrick J.
Vance, Sean
Rangarajan, Sanjeet
Dylewski, Dawna
Eugster, Emily
Scott, Stephanie B.
Beuschel, Nicole L.
Davidson, Paula J.
Axtell, Richard
Mitchell, Deanna
Lester, Eric P.
Junewick, Joseph J.
Webb, Craig P.
Monks, Noel R. - Abstract:
- <abstract abstract-type="main"> <title> <x xml:space="preserve">Abstract</x> </title> <sec id="pbc25039-sec-0001" sec-type="section"> <title>Background</title> <p>Precision (Personalized) medicine has the potential to revolutionize patient health care especially for many cancers where the fundamental disease etiology remains either elusive or has no available therapy. Here we outline a study in alveolar rhabdomyosarcoma, in which we use gene expression profiling and a series of drug prediction algorithms combined with a matched patient‐derived xenograft (PDX) model to test bioinformatically predicted therapies.</p> </sec> <sec id="pbc25039-sec-0002" sec-type="section"> <title>Procedure</title> <p>A PDX model was developed from a patient biopsy and a number of drugs identified using gene expression analysis in combination with drug prediction algorithms. Drugs chosen from each of the predictive methodologies, along with the patient's standard‐of‐care therapy (ICE‐T), were tested <italic>in vivo</italic> in the PDX tumor. A second study was initiated using the tumors that re‐grew following the ICE‐T treatment. Further expression analysis identified additional therapies with potential anti‐tumor efficacy.</p> </sec> <sec id="pbc25039-sec-0003" sec-type="section"> <title>Results</title> <p>A number of the predicted therapies were found to be active against the tumors in particular BGJ398 (FGFR2) and ICE‐T. Re‐transplanted ICE‐T treated tumorgrafts demonstrated a decreased<abstract abstract-type="main"> <title> <x xml:space="preserve">Abstract</x> </title> <sec id="pbc25039-sec-0001" sec-type="section"> <title>Background</title> <p>Precision (Personalized) medicine has the potential to revolutionize patient health care especially for many cancers where the fundamental disease etiology remains either elusive or has no available therapy. Here we outline a study in alveolar rhabdomyosarcoma, in which we use gene expression profiling and a series of drug prediction algorithms combined with a matched patient‐derived xenograft (PDX) model to test bioinformatically predicted therapies.</p> </sec> <sec id="pbc25039-sec-0002" sec-type="section"> <title>Procedure</title> <p>A PDX model was developed from a patient biopsy and a number of drugs identified using gene expression analysis in combination with drug prediction algorithms. Drugs chosen from each of the predictive methodologies, along with the patient's standard‐of‐care therapy (ICE‐T), were tested <italic>in vivo</italic> in the PDX tumor. A second study was initiated using the tumors that re‐grew following the ICE‐T treatment. Further expression analysis identified additional therapies with potential anti‐tumor efficacy.</p> </sec> <sec id="pbc25039-sec-0003" sec-type="section"> <title>Results</title> <p>A number of the predicted therapies were found to be active against the tumors in particular BGJ398 (FGFR2) and ICE‐T. Re‐transplanted ICE‐T treated tumorgrafts demonstrated a decreased response to ICE‐T recapitulating the patient's refractory disease. Gene expression profiling of the ICE‐T treated tumorgrafts identified cytarabine (SLC29A1) as a potential therapy, which was shown, along with BGJ398, to be highly active <italic>in vivo</italic>.</p> </sec> <sec id="pbc25039-sec-0004" sec-type="section"> <title>Conclusions</title> <p>This study illustrates that PDX models are suitable surrogates for testing potential therapeutic strategies based on gene expression analysis, modeling clinical drug resistance and hold the potential to assist in guiding prospective patient care. Pediatr Blood Cancer 2014;61:1570–1577. © 2014 Wiley Periodicals, Inc.</p> </sec> </abstract> … (more)
- Is Part Of:
- Pediatric blood & cancer. Volume 61:Issue 9(2014:Sep.)
- Journal:
- Pediatric blood & cancer
- Issue:
- Volume 61:Issue 9(2014:Sep.)
- Issue Display:
- Volume 61, Issue 9 (2014)
- Year:
- 2014
- Volume:
- 61
- Issue:
- 9
- Issue Sort Value:
- 2014-0061-0009-0000
- Page Start:
- 1570
- Page End:
- 1577
- Publication Date:
- 2014-03-31
- Subjects:
- Tumors in children -- Periodicals
Blood -- Diseases -- Periodicals
Cancer in children -- Periodicals
618.92 - Journal URLs:
- http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1545-5017 ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1002/pbc.25039 ↗
- Languages:
- English
- ISSNs:
- 1545-5009
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 6417.533500
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 2969.xml