Small animals provide invaluable model systems in a broad range of disciplines in cancer research including cancer biology, genetics, immunology, stem cell biology, and experimental therapeutics. Effective utilization of these models often demands application of non-invasive imaging methodologies. These techniques allow for longitudinal studies of disease progression and response to therapy as well as providing unique information that is not accessible via other methodologies, The major impediment to the application of these methodologies is that the highly specialized instrumentation and diverse expertise necessary is generally beyond the reach of the individual PI. The Small Animal Imaging Core (SAIC) is a shared resource within the Abramson Cancer Center (ACC) that serves researchers within ACC, the university and surrounding institutions. The core provides state of the art instrumentation and a renowned support staff with the expertise necessary to apply a broad range of imaging modalities to small animal models. Supported modalities include magnetic resonance imaging (MRI), positron emission tomography (PET), computed tomography (CT), single photon emission computed tomography (SPECT), ultrasound imaging (US) and bioluminescence imaging (to detect luciferase and green fluorescent protein). Each imaging modality is supported by a faculty Director with extensive experience in the application and development of the corresponding imaging modality to small animals. In addition, the SAIC provides limited animal housing for rats and mice allowing multiple imaging sessions to be performed on a particular animal over an extended period without risking infection of the general population of animals. The facility also provides support for data transfer and analysis. Over 25 ACC members have used the core in the last year. ACC member usage was 53% of the total core usage. CCSG support represents 28% of the proposed core budget with the remaining funding coming from charge backs and institutional support.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Center Core Grants (P30)
Project #
5P30CA016520-38
Application #
8593276
Study Section
Subcommittee G - Education (NCI)
Project Start
Project End
Budget Start
2013-12-01
Budget End
2014-11-30
Support Year
38
Fiscal Year
2014
Total Cost
$208,895
Indirect Cost
$86,401
Name
University of Pennsylvania
Department
Type
DUNS #
042250712
City
Philadelphia
State
PA
Country
United States
Zip Code
19104
Taylor, Laura A; Abraham, Ronnie M; Tahirovic, Emin et al. (2017) High ALDH1 expression correlates with better prognosis in tumorigenic malignant melanoma. Mod Pathol 30:634-639
Rebecca, Vito W; Nicastri, Michael C; McLaughlin, Noel et al. (2017) A Unified Approach to Targeting the Lysosome's Degradative and Growth Signaling Roles. Cancer Discov 7:1266-1283
Till, Jacob E; Yoon, Changhwan; Kim, Bang-Jin et al. (2017) Oncogenic KRAS and p53 Loss Drive Gastric Tumorigenesis in Mice That Can Be Attenuated by E-Cadherin Expression. Cancer Res 77:5349-5359
Ewens, Kathryn G; Bhatti, Tricia R; Moran, Kimberly A et al. (2017) Phosphorylation of pRb: mechanism for RB pathway inactivation in MYCN-amplified retinoblastoma. Cancer Med 6:619-630
Chee, Wonshik; Lee, Yaelim; Im, Eun-Ok et al. (2017) A culturally tailored Internet cancer support group for Asian American breast cancer survivors: A randomized controlled pilot intervention study. J Telemed Telecare 23:618-626
Zang, Tianzhu; Taplin, Mary-Ellen; Tamae, Daniel et al. (2017) Testicular vs adrenal sources of hydroxy-androgens in prostate cancer. Endocr Relat Cancer 24:393-404
Walter, David M; Venancio, Olivia S; Buza, Elizabeth L et al. (2017) Systematic In Vivo Inactivation of Chromatin-Regulating Enzymes Identifies Setd2 as a Potent Tumor Suppressor in Lung Adenocarcinoma. Cancer Res 77:1719-1729
Carrer, Alessandro; Parris, Joshua L D; Trefely, Sophie et al. (2017) Impact of a High-fat Diet on Tissue Acyl-CoA and Histone Acetylation Levels. J Biol Chem 292:3312-3322
Fennelly, Colin; Amaravadi, Ravi K (2017) Lysosomal Biology in Cancer. Methods Mol Biol 1594:293-308
Safo, Sandra E; Li, Shuzhao; Long, Qi (2017) Integrative analysis of transcriptomic and metabolomic data via sparse canonical correlation analysis with incorporation of biological information. Biometrics :

Showing the most recent 10 out of 955 publications