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CPL Projects

Laboratory Research Objectives

The McIntosh Laboratory develops and applies computational proteomic strategies primarily for discovering and evaluating serum diagnostic and early detection biomarkers, especially for ovarian cancer.

Selected Funded Projects in the Lab

Serum proteomics using recombinant libraries and mass spectrometry to identify ovarian and breast cancer diagnostics (PI: McIntosh): The Early Detection Research Network funds this project. Its goal is to use serum proteomics approaches based on scFv combined with mass spectrometry to discover serum-based tumor biomarkers that work well together to identify breast and ovarian cancer at their early stages.

Use of proximal fluid (ascites) to identify recombinant libraries relevant for serum based discovery of ovarian cancer (PI: McIntosh). This Department of Defense funded project uses recombinant antibodies and mass spectrometry to identify candidate proteins that are first identified in tumor associated fluids.

Biomarker validation for ovarian early detection markers. Pacific Ovarian Cancer Research Consortium (POCRC) (Project lead McIntosh, PI: Urban): This research represents the early detection project on the FHCRC Ovarian Cancer SPORE, an NCI-funded translational research program. This project intends to confirm individual analytes of interest for ovarian cancer molecular diagnostics.

Comprehensive profiling of the contents and variation in the normal plasma proteome (PI: McIntosh): This project, funded by the Canary Foundation, intends to characterize the proteome variation over time within and between women in a cohort of women at-risk for breast or ovarian cancer and to relate those characteristics to the performance of proteins when used in a screening program.

Integrative genomic and proteomic profiling of the ovarian cancer plasma proteome (PI: McIntosh): This project, funded by the Canary Foundation, intends to use genomic approaches to interpreting mass spectrometry data in order to identify protein biomarkers associated with molecular changes in ovarian cancer.

Identification of protein markers for Huntington's disease in the Cerebral Spinal Fluid (CSF) and plasma of HD affected and unaffected individuals (PI: McIntosh): This project, funded by the HighQ Foundation, interrogates the CSF proteome and plasma of HD affected and unaffected individuals in order to identify potential markers for tracking and monitoring disease progression.



Selected Collaborative Projects

Cancer Biomarker Discovery and Validation: Proof-of-Principle in the Mouse (PI: Hartwell, Nelson): This biomarker discovery consortium is funded by the Paul G. Allen Family Foundation. The proposed biomarker discovery and validation platform will: (1) discover proteins in blood that closely associate with the presence of a malignancy in the host; (2) confirm and characterize the behavior of these candidate protein biomarkers through the course of malignant progression using independent methods to reduce the number of candidates for the validation step; and (3) validate that a given protein biomarker is sufficiently sensitive to detect the presence of a tumor prior to obvious clinical disease and be specific to the tumor (i.e. distinct from generic illness or other malignancies).

Tissue proteomics for identifying markers for pancreas cancer (PI: Brentnall): This project applies proteomics approaches to pancreas cancer and non-cancer tissue in order to identify approaches to diagnose pancreas cancer.

Breast Cancer Biomarker Discovery Consortium (PI: Hartwell, Carr): This breast cancer biomarker discovery consortium project funded by the Entertainment Industry Foundation/Women's Cancer Research Fund brings together research laboratories from the Broad Institute, FHCRC, ISB, and PNNL. As the informatics core, we will apply the informatics tools developed by the CPL to organize and integrate the proteomic and genomic analyses performed at each participating lab. The Informatics Core will also describe a common set of experimental ontologies, centrally process data, and present integrated data to consortium investigators.