Pathology Shared Resource (PSR) The Pathology Shared Resource (PSR) was created to provide Norris Cotton Cancer Center (NCCC) investigators from different backgrounds (e.g., physicians, basic scientists, diagnosticians) access to a CLIA- certified, CAP-accredited facility with standardized laboratory protocols for histologic, quantitative imaging and molecular analysis. The ultimate goal of the PSR is to provide NCCC investigators with state-of-the-art technical and professional support leading to quality results for clinical and pre-clinical studies. The PSR has consolidated institutional expertise and experience by combining responsibility for providing for and supporting both clinical and research utilization of these services. The PSR supports human tissue and cell procurement/acquisition (i.e., handling, storage, distribution and biobanking); histology and immunohistochemical analysis; molecular pathology analysis (i.e., genotyping, next-generation sequencing, quantitative PCR, tissue microarrays; cell processing services); and cytogenetics analysis. The PSR is directed by Dr. Gregory Tsongalis, who oversees a staff of 12 that includes two Research Associates, two Histotechnologists, an Apheresis Nurse, and seven additional technical specialists. The PSR is organized to identify as early as possible the needs of researchers in developing and supporting their translational research project, providing them with technical support and consultation. Further, many Pathology faculty become involved in collaborating on individual research projects by reviewing proposals, selecting appropriate tissues, designing IHC staining and molecular testing algorithms, creating tissue arrays, suggesting alternative biomarker testing, and scoring IHC expression levels. The PSR has supported NCCC Members in each of the six Research Programs: Cancer Control (2 members), Cancer Epidemiology (6 members), Cancer Mechanisms (12 members), Molecular Therapeutics (27 members), Cancer Imaging & Radiobiology (7 members), and Immunology & Cancer Immunotherapy (12 members).

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Center Core Grants (P30)
Project #
5P30CA023108-39
Application #
9404364
Study Section
Subcommittee I - Transistion to Independence (NCI)
Project Start
Project End
Budget Start
2017-12-01
Budget End
2018-11-30
Support Year
39
Fiscal Year
2018
Total Cost
Indirect Cost
Name
Dartmouth College
Department
Type
DUNS #
041027822
City
Hanover
State
NH
Country
United States
Zip Code
Smith, T Jarrod; Sondermann, Holger; O'Toole, George A (2018) Co-opting the Lap System of Pseudomonas fluorescens To Reversibly Customize Bacterial Cell Surfaces. ACS Synth Biol 7:2612-2617
Gorlova, Olga Y; Li, Yafang; Gorlov, Ivan et al. (2018) Gene-level association analysis of systemic sclerosis: A comparison of African-Americans and White populations. PLoS One 13:e0189498
Schmit, Stephanie L; Edlund, Christopher K; Schumacher, Fredrick R et al. (2018) Novel Common Genetic Susceptibility Loci for Colorectal Cancer. J Natl Cancer Inst :
Cai, Yunliang; Wu, Shaoju; Zhao, Wei et al. (2018) Concussion classification via deep learning using whole-brain white matter fiber strains. PLoS One 13:e0197992
Trentham-Dietz, Amy; Ergun, Mehmet Ali; Alagoz, Oguzhan et al. (2018) Comparative effectiveness of incorporating a hypothetical DCIS prognostic marker into breast cancer screening. Breast Cancer Res Treat 168:229-239
Moulton, Haley; Tosteson, Tor D; Zhao, Wenyan et al. (2018) Considering Spine Surgery: A Web-Based Calculator for Communicating Estimates of Personalized Treatment Outcomes. Spine (Phila Pa 1976) 43:1731-1738
Ji, Xuemei; Bossé, Yohan; Landi, Maria Teresa et al. (2018) Identification of susceptibility pathways for the role of chromosome 15q25.1 in modifying lung cancer risk. Nat Commun 9:3221
Ferreiro-Iglesias, Aida; Lesseur, Corina; McKay, James et al. (2018) Fine mapping of MHC region in lung cancer highlights independent susceptibility loci by ethnicity. Nat Commun 9:3927
Bronson, Mackenzie R; Kapadia, Nirav S; Austin, Andrea M et al. (2018) Leveraging Linkage of Cohort Studies With Administrative Claims Data to Identify Individuals With Cancer. Med Care 56:e83-e89
Gorlov, Ivan; Orlow, Irene; Ringelberg, Carol et al. (2018) Identification of gene expression levels in primary melanoma associated with clinically meaningful characteristics. Melanoma Res 28:380-389

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