Colorectal cancer (CRC) is one of the most common cancers worldwide. Despite improvement in standardized screening methods and the development of promising therapies, the 5-year survival rates are as low as 10% in the metastatic setting. Metabolomics, the study of metabolites on a large scale, has provided new insight into disease diagnosis and biomarkers identification. We chose topotecan as an anti-cancer drug in this context because, as far as we know, there are no studies examining the effect of this anti-cancer drug on metabolic alterations in CRC. In this study, untargeted metabolomic analysis study was performed to compare between four animal groups HCT-116 xenograft models treated with topotecan, untreated HCT-116 xenograft models (vehicle controls), positive controls, and negative controls, using UHPLC-ESI-QTOF-MS platform. One way ANOVA analysis discovered 53 statistically significant metabolites among all four groups (p <0.05). T-test revealed that 15 metabolites were statistically significant among vehicle controls and negative controls. Also, 20 metabolites were statistically significant among the potential responders to topotecan and the vehicle controls. In addition, only 1 metabolite was statistically significant among the positive and negative control. Ultimately, by analyzing metabolomic profiles, our findings can create a map that can be utilized to assess the anticancer activity of topotecan in CRC. More studies with larger number of models are needed to verify the implication of the significantly altered metabolites and metabolic pathways in diagnosing and treating CRC.