Experimental translational cancer research
We develop next-generation strategies for translational cancer medicine by combining emerging technologies with clinically driven questions. Our work addresses tumor heterogeneity and rare metastatic cell populations through complementary approaches including cell-barcode–based precision lethality and radioligand therapy. By integrating tumor organoids, single-cell and spatial profiling, high-throughput drug screening, and deep learning, we aim to enable more precise and durable cancer treatments.
Our overarching goal is to improve cancer treatment by addressing tumor heterogeneity and therapy resistance. We focus on identifying and eliminating rare tumor cell populations that survive standard treatments and ultimately drive relapse and metastasis. Tumor heterogeneity—arising from genomic instability, clonal selection, and interactions with the tumor microenvironment—is a fundamental cause of treatment failure, yet remains insufficiently addressed in current drug development.
Research Goals
​We address this challenge through three complementary therapeutic strategies that target heterogeneity through distinct mechanisms. Precision Lethality explicitly confronts clonal diversity by identifying drug combinations that eliminate resistant tumor subclones missed by standard therapy. Radiopharmaceutical Therapy circumvents molecular heterogeneity by delivering radiation via targeted carriers, enabling bystander killing of neighboring tumor cells even when target expression is heterogeneous. Differentiation Therapy targets residual tumor cells that escape cytotoxic treatment by driving them into stable, less malignant states, building on principles already used clinically.
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To understand and overcome tumor heterogeneity at a mechanistic level, we develop and apply lineage-tracing and single-cell technologies that link clonal dynamics to molecular state, spatial organization, and therapeutic response during treatment. These approaches allow us to directly measure how individual tumor subclones respond to therapy, identify the populations that persist, and rationally refine our therapeutic strategies.
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To maximize clinical relevance, we work closely with clinicians and focus on optimizing and extending existing treatment modalities rather than developing entirely new ones. Our research is inherently multidisciplinary, integrating experimental biology, genomics, computational analysis, and clinical collaboration to pursue high-risk, high-reward approaches with the potential to substantially improve cancer therapy.
