Blood-based biomarkers for risk assessment and early detection of colorectal cancers
There is currently substantial interest in liquid biopsy approaches for colorectal cancer (CRC) screening. Such tests would not supplant existing screening programs (e.g. colonoscopy) but would represent a tool to be integrated with risk models based on subject characteristics to personalize cancer risk assessment and inform on the need for CRC screening, to detect cancer early. The translational objective of this project is to assess the contributions of candidate protein and metabolite biomarkers already identified and undertake a comprehensive proteomic and metabolomics profile that require a small volume of PLCO samples to identify additional candidate biomarkers to develop tests that inform about a subject’s probability of harboring or developing colorectal cancer (CRC).
Specific Aim 1A: To test the predictive performance of candidate protein and metabolite biomarkers that we have identified for detection of colorectal cancer. Using established and standardized assays, we will measure candidate protein and metabolite biomarkers in the PLCO specimen set. Time-dependent (e.g. 0-1 year, 1-2 years, 2+ years) predictive performance estimates for individual biomarkers will be determined, and priority biomarkers advanced for establishing combination rule(s) for risk assessment of colorectal cancer.
Specific Aim 1B: To discover and assess the contributions of additional biomarker candidates identified through comprehensive proteomic and metabolomic profiling for detection of colorectal. Using advanced mass spectrometry technology, we will conduct comprehensive metabolomics and proteomics analyses to identify additional biomarkers that offer potential utility for detection of colorectal cancers. Biomarkers will be prioritized based on their individual predictive performance and their contribution to marker panels indicative of risk of harboring a colorectal cancer.
Specific Aim 2A: To develop a model to predict one-year risk of colorectal cancer. A model based on prioritized biomarkers identified in Aims 1A and 1B will be developed to estimate 1-year probability of an individual receiving a CRC diagnosis. We will adhere to the PCS (Predictability, Computability and Stability) framework for model building. For modeling, the entire PLCO specimen set will be divided into Development and Set-Aside Testing Sets. Modeling and initial validation will be performed using specimens from the Development Set. The predictive performance ((AUC, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), accuracy, F1 score, and precision) of the model(s) will be tested in the PLCO Set-Aside Test Set. We will additionally integrate biomarker panels with risk models that consider patient characteristics.
Specific Aim 2B: To develop a model for five-year risk assessment of colorectal cancer. Building upon profiles generated in Aim 1B, we will assess for proteins and metabolites that are associated with 5-year risk of CRC. The entire specimen set will be split into a Development Set and a Set-Aside Test Set. A model that additionally integrates patient characteristics (see Aim 2A) will be developed to estimate the probability of an individual receiving a CRC diagnosis within 5 years of blood draw. The model will be validated using the Set-Aside Test Set.
Samir Hanash (University of Texas MD Anderson Cancer Center)
Johannes Fahrmann (University of Texas MD Anderson Cancer Center)
Ehsan Irajizad (University of Texas MD Anderson Cancer Center)
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A blood-based metabolomic signature predictive of risk for pancreatic cancer.
Irajizad E, Kenney A, Tang T, Vykoukal J, Wu R, Murage E, Dennison JB, Sans M, Long JP, Loftus M, Chabot JA, Kluger MD, Kastrinos F, Brais L, Babic A, Jajoo K, Lee LS, Clancy TE, Ng K, Bullock A, ...show more Genkinger JM, Maitra A, Do KA, Yu B, Wolpin BM, Hanash S, Fahrmann JF
Cell Rep Med. 2023 Sep 19; Volume 4 (Issue 9): Pages 101194 PUBMED