Identifying Mutational Drivers of Late Stage Colon Cancer

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This proposal seeks to identify cancer specific gene mutations that are linked with important clinical and epidemiological characteristics of colon cancer (CC). 'Driver' gene mutations are directly related to clinical behavior in virtually all cancers. However, mutations that drive CC progression, from the eady curable disease to late stage incurable disease, are yet to be identified. Recent studies by our group and our collaborators have identified 140 candidate cancer genes (CAN genes) in CC. We also found that virtually all the CAN gene mutations found in metastatic CCs are also found in the antecedent primary cancer. This surprising result gives us an opportunity to explore CAN gene mutations in multiple clinical settings. To enable these studies, we have constructed a large biorepository containing CCs from patients treated at a large medical center over the last 20 years. The majority of these specimens are formalin-fixed paraffin embedded [FFPE]. We have developed sophisticated approaches to enhance the utility of DNA extracted from FFPE materials. These include reliable extraction of large DNA fragments. We also developed the technologies and processes to 'DNA capture' targeted exonal fragments and identify mutations from FFPE material using a 'next generation' sequencer. We have developed an infrastructure and knowledge base to support high throughput tissue processing and sequencing. We propose to use these methods to identify CAN gene mutations which appear only in late stage CCs. Also we will functionally dissect the role of these genes using cell line and xenograft mouse models. As CC is one of the cancers with significant disparities attributed to race and gender associated etiologic factors, we will compare CC CAN gene mutations between African American and white patients and between females and male patients, of similar cancer stage and outcome. The former studies will be facilitated by our use of an Ancestry Informative Marker- SNP classification of patients which will be incorporated directly into the DNA sequencing analyses. Our proposals have the potential to significantly advance the understanding of the biological basis for cancer metastasis and to gain insights into racial/gender based differences in etiology and outcomes among CC patients.