ZIA BC 011492 (ZIA) | |||
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Title | Biomarkers in Cancer Diagnosis,Prognosis, and Therapeutic Outcome | ||
Institution | NCI, Bethesda, MD | ||
Principal Investigator | Harris, Curtis | NCI Program Director | N/A |
Cancer Activity | N/A | Division | CCR |
Funded Amount | $1,106,309 | Project Dates | 10/01/2012 - 00/00/0000 |
Fiscal Year | 2014 | Project Type | Intramural |
Research Topics w/ Percent Relevance | Cancer Types w/ Percent Relevance | ||
Cancer (100.0%) Digestive Diseases (40.0%) Inflammatory Bowel Disease (20.0%) |
Colon/Rectum (40.0%) Lung (60.0%) |
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Research Type | |||
Cancer Progression and Metastasis Technology Development and/or Marker Discovery |
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Abstract | |||
In the LHC Molecular Genetics & Carcinogenesis Section we have been building a Knowledge Network of lung cancer to support our ongoing efforts to enhance disease subtyping and contribute to a more detailed taxonomy that will lead to more precise clinical management of this complex disease. Our strategy is to begin by analyzing resources from our NCI-MD cohort and then validate those findings in additional cohorts throughout the world. We acquire multiple levels of genomic data from patients and controls using different types of biospecimens. After results are validated in multiple cohorts, we integrate them as part of our Information Commons. When possible, we use the same patients for different studies as this allows for a full integration of the different levels of data to determine if it improves cancer taxonomy. The multiple layers of information gathered provide a view of each component of the 1. Exposome. The identification and precise measure of the collective contributions of exogenous (e.g., smoking, radon, environmental pollutants) and endogenous (e.g., hormones, inflammation) exposures to an individual's disease predisposition are key components of the Information Commons and provide insights into disease biology, health disparities and opportunities for intervention. External Exposome We identified a germline Single Nucleotide Polymorphism (SNP) in the dopamine D1 receptor (DRD1) that modulates risk of lung cancer among individuals exposed to secondhand smoke during childhood. Interestingly, this polymorphism modulates risk in both ever smokers and never smokers. The relationship is also evident in African Americans and European Americans. Internal Exposome: Inflammation We have conducted numerous studies on the role of inflammation in lung carcinogenesis. Recently, we have studied whether markers of inflammation, such as pro-inflammatory cytokines and C-reactive protein, are predictors of lung cancer diagnosis and prognosis. In the NCI-MD study and validated in the PLCO cohort, we demonstrated that increased levels of IL-6, CRP and IL-8 are associated with lung cancer diagnosis and are elevated up to 5 years before diagnosis in the case of IL-8. We have demonstrated that a combined IL-6 and IL-8 signature is both associated with poor outcome in stage I lung cancer patients, a population for which accurate predictors of outcome are both needed and lacking (Ryan BM, et al., J Thorac.Oncolgy, In Press, 2014). In addition, our health disparity research has identified specific inflammatory profiles associated with risk in African Americans and in European Americans and recent efforts have also integrated our biomarker data with genetic data, where an interaction between a 3'UTR SNP in the IL-8 receptor and putative target for miR-516a-3p binding, and IL-8 was identified. We also continue to study the mechanisms of this circulating inflamed signature in cancer. 2. Genome In collaboration with Takashi Kohno, we are investigating Oncogenic fusions act as driver mutations in lung cancer without KRAS mutations, and thus represent promising therapeutic targets for the treatment of such cancers (Nakaoku T, et al., Clin Cancer Res 20: 3087-3093, 2014). 3. Transcriptome We have developed a cancer-related gene expression signature that is a robust prognostic classifier for stage I lung cancer. Our goal was to evaluate the expression of genes with a mechanistic role in lung cancer to increase the odds of finding a robust classifier for stage I lung cancer. We developed a classifier based on the expression of BRCA1, HIF1A, DLC1, and XPO1 that could classify patients into risk groups in 5 independent cohorts (Patent Pending). This classifier was significantly associated with prognosis in subgroup analyses of Stage I, Stage IA and Stage IB separately demonstrating the potential clinical utility of this classifier (patent pending). We have now gone on to validate this classifier in 12 publically available cohorts. We included every p" |