“I’m very excited that MPI’s strong technology again has been verified. Until now there has been no useful biomarker for 5-FU efficacy to guide patient treatment. The data show that patients who are not sensitive to treatment with 5-FU have a double risk of dying. I believe that the ability to see the differences in patient’s response to drugs can significantly help us find and develop better cancer treatments.  5-FU is used in millions of patients annually and prediction of who will benefit and who will not – can solve a huge medical need”; Said CEO, Peter Buhl Jensen

 

Background: There is a clinical need for biomarkers of response to adjuvant 5-fluorouracil (5-FU) in colon cancer (CC). The current project seeks to validate a predictive 5-FU gene expression profile. A similar model has recently been validated with MD Anderson in three different clinical settings [1] and with researchers from AstraZeneca with fulvestrant [2]. Methods: The 5-FU profile consisted of in total 205 positively and negatively correlated genes mapped to 669 probe sets (on the ALMAC Colon DSA). This profile was tested using  expression data obtained from a Colon DSA gene expression array from ALMAC  applied on the   PETACC-3 CC population [3] with formalin fixed paraffin embedded (FFPE) tissue from 636 stage III CC patients treated adjuvantly with 5-FU with or without irinotecan. It was also tested on ALMAC Colon DSA data obtained from FFPE tissue from 359 stage II CC patients who did not receive adjuvant treatment [4]. The analyses were performed using Cox proportional hazards (CPH) regression models and Kaplan-Meier curves. The logrank test was used to compare the survival distributions. Results: In the PETACC-3 cohort the 5-FU predictive profile showed a statistically significant association with overall survival (OS) (hazard ratio (HR) = 0.47 (0.34, 0.63), P = 7.4e-07; binary scores). In the untreated cohort no differences were observed in OS (HR = 0.96 (0.67, 1.4), P = 0.849; binary scores). The statistical significance of the effect of the profile score (as continuous variable) adjusted for several relevant clinicopathological parameters including microsatellite instability (MSI) vs stability (MSS) and KRAS mutation status was confirmed in a multivariable CPH model on the PETACC-3 data (Table). Conclusions: Our data could suggest that the present 5-FU signature provides independent predictive information regarding benefit from adjuvant 5-FU in CC patients.

MPI’s lead product DRP is a tool to develop tumor-derived gene signatures that may predict which cancer patients are high likely responders to a given anticancer product. The DRP has been tested in 26 trials where 22 trials showed that the DRP could predict which patients had a positive effect of the treatment. The DRP has also been externally validated and published in collaboration with leading statisticians at the MD Anderson Cancer Center. The DRP method can be used to design the Clinical Development Plan i.e. to select which indications are relevant for a given anticancer drug. Further to and in addition to this, individual patient’s gene patterns can be analyzed as part of a screening procedure for a clinical trial to ensure inclusion of patients who have a high likelihood of response to the drug. The DRP method can be used in all cancer types and has been patented for more than 60 anticancer drugs in the US in 2013.