Program Official

Principal Investigator

Jennifer Sarah
Davis
Awardee Organization

University Of Kansas Medical Center
United States

Fiscal Year
2021
Activity Code
U01
Early Stage Investigator Grants (ESI)
Not Applicable
Project End Date

Colorectal cancer risk factors, risk prediction and blood-based biomarker by tumor consensus molecular subtype

Despite the availability of effective screening techniques, only 40% of colorectal cancer (CRC) cases are diagnosed at a localized stage of disease. This is likely due to a combination of factors, including screening noncompliance, limitations in the screening sensitivity and specificity, and heterogeneity of CRC biology. Specifically the existence of more aggressive tumor subtypes, which may have a shorter natural history, combined with screening inadequacies hinder our ability to detect more early stage disease and further reduce CRC morbidity and mortality. The recently described consensus molecular subtypes (CMS) of CRC include a more aggressive, mesenchymal subtype and provide a framework for stratified risk assessment, screening recommendations and prevention interventions. The four subtypes identified have distinct biology and clinical outcomes, suggesting the possibility of unique risk factors, prevention, and screening strategies. Specifically, CMS1 (Immune, 14% of cases) is associated with high micro-satellite instability (MSI), BRAF mutations and immune infiltration, CMS2 (Canonical, 37%) accounts for the largest percent of tumors and is characterized by activation of WNT and MYC, CMS3 (Metabolic, 13%) is characterized by low somatic copy number alterations, KRAS mutations and tumor metabolic dysregulation, CMS4 (Mesenchymal, 23%) is characterized by stromal infiltration, TGF-β activation, angiogenesis and worse overall and relapse-free survival (Nat Med. 2015, 21:1350). The studies in this proposal utilize the CMS framework to develop and test a risk-prediction tool and test the CMS-specific performance of a validated blood-based three-marker panel. Building on our preliminary data and using the high-quality, longitudinal data and tumor RNA from the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial, we plan to test the associations of CMS with age, smoking status, and tumor stage at diagnosis (Aim 1). Using the associations from aim 1, we plan to build and test a CMS-specific CRC risk prediction tool to facilitate screening and prevention efforts (Aim 2). We also plan to further test the performance of our validated blood-based three-marker panel across CMS and in the years prior to diagnosis (Aim 3). The combination of a CMS-specific risk prediction tool and a validated blood-based biomarker has the potential to greatly improve CRC screening compliance and early detection, leading to a reduction in morbidity and mortality from CRC.