Abstract 3853: Predictive and prognostic analysis of KRAS and MSI markers in treatment of urban African American colorectal cancer patients

Background: Advancement of molecular analytic techniques has led to the discovery of a number of genetic biomarkers thought to be associated with prognosis and treatment outcomes in colorectal cancer (CRC). Aim: To analyze response to treatment in a group of CRC patients as a function of their genetic background. Method: A retrospective chart review of patients diagnosed with CRC from 2010- 2012 at Howard University Hospital was undertaken. African American (AA) patients diagnosed with CRC, the majority of whom received 5-Fluorouracil based chemotherapy, were selected. Data was collected from in-patient and out-patient records. Response to treatment was determined by Response Evaluation Criteria In Solid Tumors (RECIST) criteria from prior radiological investigations. The data was analyzed using Kaplan-Meier survival estimate and log rank test to compare the disease free survival (DFS) in correlation with clinical and genetic markers. Results: There were 30 AA patients with CRC who received chemotherapy. The average age of the cohort was 59 years, 53 % (n=16) were females and 80% (n=24) of the CRCs were distal. There were 10% (n=3), 23% (n=7), 37% (n=11), and 30% (n=9) patients at stage I, II, III, and IV, respectively. After three years of follow-up, disease free survival was 0.37 (95%CI: 0.14-0.60). Patients with MSI-H (n=3) had worse DFS. Patients with wild-type (WT) KRAS (n=16) had better DFS than mutant KRAS (n=10). The type of chemotherapy received did not affect response. Conclusions: DFS was worse in patients with a higher stage at the time of diagnosis, as well as, in patients with MSI-H versus MSS. Further study is warranted in AA since CRC patients with MSI-H historically have a better prognosis. DFS was found to be better in patients with WT KRAS, independent of chemotherapeutic regimen. These findings confirm that KRAS mutations negatively affected the prognosis in our study population. Table 1Characteristics of Responders vs Non-respondersCharacteristicsResponderNon-responderP-valueGenderMale770.4Female106Age< 60 years750.9≥60 years108StageI300.026II52III74IV27LocationLeft1590.3Right24MSIMSS157