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PhD publication A. Rifi

Radiomic features are typically used in machine learning models and are proven to generate reliable results when predicting tumor grade and responses to treatment. In Amir’s new paper, an innovative approach is proposed where dedicated in vivo experiments are used to correlate biological meaning to specific radiomic features.

Read all about it in:

A.L. Rifi, I. Dufait, C. El Aisati; M. De Ridder; K. Barbé. Interpretability and Repeatability of Radiomic Features: Applied on In Vivo Tumor Models. IEEE Transactions on Instrumentation and Measurement (2023).

https://doi.org/10.1109/TIM.2023.3269101

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PhD publication L. Kerkhove

Radiotherapy is a cornerstone for the treatment of colorectal cancer. Tumor cells present in an environment lacking oxygen (hypoxia) are resistant, leading to patient relapse. Altering redox homeostasis and inducing cell death of hypoxic cancer cells is a promising strategy to overcome radioresistance. In this study, redox homeostasis was targeted, and cell death (ferroptosis) was induced in colorectal cancer cells by treating them with the FDA-approved drug sulfasalazine. Overall, sulfasalazine treatment improved the response to radiotherapy in a model system of human colorectal cancer cells.

Lisa’s publication reveals sulfasalazine as a promising radiosensitizer of hypoxic human colorectal cancer through the disturbance of redox homeostasis and ferroptosis induction.

L. Kerkhove, F. Geirnaert, A.L. Rifi, K.L. Law, A. Gutiérrez, I. Oudaert, C. Corbet, T. Gevaert, I. Dufait, M. De Ridder. Repurposing Sulfasalazine as a Radiosensitizer in Hypoxic Human Colorectal Cancer. Cancers (2023). 15(8):2363.

https://doi.org/10.3390/cancers15082363