Assistant Professor of Pathology
Bio
Biological systems are thought to be exceedingly ‘complex’–comprised of many parts and sets of unintuitive interactions between parts conferring system function. My lab is interested in elucidating principles of structure, function, and adaptability relationships with the ultimate goals of (i) characterizing ‘personalized’ variation in biological systems with high-fidelity, (ii) creating tools to genetically engineer variation in a rational way, and (iii) engineering natural-like, adaptive systems de novo. We use a blend of theory, computation, and experiment applied to a range of model systems spanning neural networks to electronic health record data to complex ecosystems inhabiting humans in addressing these concepts.
A tool of ‘single-cell transcriptional profiling’ (scRNA seq)—gives the ability to measure how much any single human gene in the entire genome is turned ‘on’ or ‘off’ within a single cell. Utilizing scRNA seq on patient tissue samples offers the potential to identify cell populations and genes responsible for disease pathology in a highly precise manner. In diseases like TNBC where there are no treatment options outside of routine chemotherapy, scRNA seq holds the potential to make precision medicine a reality. Our laboratory has created a new method, SCALES (Spectral Correlation Analysis of Layered Evolutionary Signals), to precisely identify drivers of pathology. Preliminary results show substantial promise in precisely defining transcriptional signatures of TNBC. This study is centered around validating statistical predictions with the goal of establishing a framework to identify high-value targets for gene therapy. If successful, we believe we can develop new treatments for TNBC, reflecting a new paradigm for data-driven precision medicine.
Arjun Raman, MD, PhD
University of Chicago
Newly funded researchers pursuing high-risk, high-reward breast cancer studies in their first or second academic positions.
Past
Early Investigator
Abde Abukhdeir, PhD
The molecular variants that lead or contribute to drug resistance in breast cancer
Past
Early Investigator
Nan Chen, MD
Discovering novel biomarkers of therapy response and resistance in metastatic triple-negative breast cancer patients
Past
Early Investigator
Peiwen Chen, PhD
Targeting macrophage reprogramming in brain metastatic breast cancer
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