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The focus of our NCI grant is brain cancer “radio-pathomics”. Briefly, high-grade brain cancer (glioblastoma) is a devastating disease that very few patients survive long-term. The average life expectancy is 15 months, and throughout therapy patients undergo serial MR imaging for monitoring tumor response. It is not well understood how heterogeneity at the cellular and molecular levels affects the macroscopic imaging characteristics of these tumors. The long-term goal of this project is to provide imaging tools and biomarker integration strategies for individualizing glioblastoma treatment. The overall objective is to combine radiographic imaging with histopathological samples (i.e., radio-pathomics) to create and validate predictive tools for accurately defining tumor margins and spatial molecular profiles. Our central hypothesis is that microscopic glioblastoma cytological features and spatially dependent molecular profiles are reliably detectable and quantifiable with macroscopic MR imaging. Two specific aims will objectively test this hypothesis by first determining which microscopic tissue features contribute to distinct measurements with MR imaging, and second, determining the performance of machine learning algorithms for predictively mapping these heterogeneous histological features. This study leverages and is responsible for building our brain bank. This project has been extended to study Alzheimer’s disease in a similar fashion.

Our Novocure funded project is focused on a new treatment. Therapy with tumor treatment fields (TTFields) has recently been FDA approved for the treatment of newly diagnosed glioblastoma due to a recent clinical trial that showed improvement in progression free survival and overall survival compared to standard therapy. TTFields also have a role in the recurrent glioblastoma treatment where it has demonstrated equal efficacy to second-line chemotherapy also has been shown to tumor progression and improve overall survival. Though preclinical studies are ongoing, glioblastoma patients who have undergone TTField therapy have not yet been assessed at autopsy to determine both the pathological signature of TTField treatment, and the pattern of failure. This study will determine how the underlying pathological signatures of tumors treated with TTFields differ from those naïve to TTFields by comparing tumor tissue at autopsy. We will also assess the imaging to determine whether the TTFields effect on cell division varies spatially.

Our Froedtert Foundation grant focusses on tumor adaptation to therapy. This proposal will test the hypothesis that gliomas develop resistance to treatment, based on stereotyped patterns of genomic alterations. This study will determine how the molecular landscape of these gliomas evolve, from the time of initial diagnosis to end-of-life. To accomplish this, we will compare genomic, epigenomic, and transcriptomic tumor signatures from pre-therapy gliomas with molecular data from the same patients at autopsy. This will provide a rigorous, comprehensive characterization of the molecular evolution of treatment-resistant gliomas. Data generated in this project will inform future studies aimed at anticipating adaptive changes in gliomas, and at quickly targeting such changes with stronger evidence-based therapies. Our collaborators at the Jackson Laboratory are the organizers of the GLASS consortium, which is a multi-center international group focused on combining tissue datasets for better understanding tumor evolution of treatment response. Our contribution includes autopsy samples, unavailable elsewhere.