Featured Scientist

Anum Syed

My primary research interests are in the development of statistical models using quantitative characterizations of intratumoral heterogeneity to predict treatment response and to guide personalized therapy. Currently, I am developing and validating models of whole-tumor states using in vivo quantitative imaging and ex vivo biological data in preclinical models of HER2+ breast cancer. This project involves evaluating tissue and cellular level changes in HER2+ tumor heterogeneity in response to single agent and combination therapies of trastuzumab and paclitaxel.

Longitudinal alterations in tumor cellular and vascular heterogeneity can be evaluated through quantitative imaging and can characterize tumor treatment response prior to downstream changes in tumor size. Using in vivo translational imaging data and ex vivo histology and flow cytometry data, I am working to develop and test statistical models to predict changes in the tumor state over time and in response to treatment. The ultimate goal is to use these models to predict treatment response and guide therapeutic strategies that drive the tumor towards a more sensitized state for improved therapeutic response and optimal patient outcome.

The first column shows SUV maps (in gray-scale) generated from FMISO-PET data of a single mouse, at baseline and day 7 post trastuzumab treatment. The second column highlights the tumor ROI within the SUV map and further segments the tumor into different regions based on thresholded SUV values, demonstrating regional hypoxic heterogeneity within the tumor./blockquote]