Colorectal cancer (CRC) is one of the leading causes of cancer-related deaths worldwide, highlighting the urgent need for improved preclinical models to evaluate potential therapies. Animal models are essential for elucidating tumor biology and assessing novel therapeutic interventions. Mouse models offer key advantages over existing models, including genetic manipulability, rapid reproduction, cost-effectiveness, and the availability of immunocompetent and immunodeficient strains, enabling precise modeling of human cancers. This protocol focuses on the subcutaneous induction of the bioluminescent colorectal cancer cell line HCT-116 in an immunodeficient murine model, followed by non-invasive bioluminescence imaging using the IVIS system and caliper to monitor tumor progression and growth. Using luminescent cells provides a real-time, quantifiable approach for tracking tumor development and response to therapeutic interventions, reducing the need for invasive procedures. A cohort of mice (n = 12) is required for tumor cell implantation, and luminescence intensity is measured to establish a standardized model for therapeutic testing. Tumor volume is typically calculated using only length and width measurements or width. The current methodology ensures consistent tumor establishment while minimizing° variability, ultimately enhancing the reliability of preclinical assessment. The findings of this study will contribute to refining tumor models for drug testing and improving the translational potential of preclinical research in clinical applications. By employing advanced imaging techniques and a reproducible experimental design, this study aims to improve the accuracy and efficiency of in vivo drug evaluation for colorectal cancer treatment.

Colorectal cancer (CRC) is one of the leading causes of cancer-related deaths worldwide, highlighting the urgent need for improved preclinical models to evaluate potential therapies. Animal models are essential for elucidating tumor biology and assessing novel therapeutic interventions. Mouse models offer key advantages over existing models, including genetic manipulability, rapid reproduction, cost-effectiveness, and the availability of immunocompetent and immunodeficient strains, enabling precise modeling of human cancers. This protocol focuses on the subcutaneous induction of the bioluminescent colorectal cancer cell line HCT-116 in an immunodeficient murine model, followed by non-invasive bioluminescence imaging using the IVIS system and caliper to monitor tumor progression and growth. Using luminescent cells provides a real-time, quantifiable approach for tracking tumor development and response to therapeutic interventions, reducing the need for invasive procedures. A cohort of mice (n = 12) is required for tumor cell implantation, and luminescence intensity is measured to establish a standardized model for therapeutic testing. Tumor volume is typically calculated using only length and width measurements or width. The current methodology ensures consistent tumor establishment while minimizing° variability, ultimately enhancing the reliability of preclinical assessment. The findings of this study will contribute to refining tumor models for drug testing and improving the translational potential of preclinical research in clinical applications. By employing advanced imaging techniques and a reproducible experimental design, this study aims to improve the accuracy and efficiency of in vivo drug evaluation for colorectal cancer treatment.

The prostaglandin E2 receptor EP3 is emerging as a promising therapeutic target in cardiovascular disease due to its involvement in vascular inflammation, platelet aggregation, and vasoconstriction. However, selective EP3 ligands with validated biological activity remain scarce. Here, we combine computational and experimental strategies to discover and validate novel EP3 receptor ligands with therapeutic potential. We implemented a high-throughput, structure- and ligand- based virtual screening pipeline, enabling the efficient exploration of approved drugs and natural compounds from DrugBank and FooDB libraries. Top-scoring candidates were prioritized based on binding energy, and pharmacophoric similarity. Selected hits underwent in silico ADME/Tox profiling using QikProp, identifying molecules with favorable pharmacokinetic and safety parameters. TUCA, masoprocol, and pravastatin sodium emerged as lead candidates and were validated in vitro using endothelial migration and platelet aggregation assays. TUCA exhibited the most consistent inhibitory effect on endothelial migration, while masoprocol, and hydrocortisone significantly reduced platelet aggregation. These findings establish a multidimensional workflow for the rational identification of EP3 ligands and support their potential in cardiovascular therapeutics.