

Our Science
At Auron, we are shifting the paradigm of cancer treatment to target key drivers of dysregulated differentiation and cellular plasticity in tumors. This type of therapy, called differentiation therapy, offers life-saving, transformative treatments for patients and their families.


What is differentiation therapy?
Cellular differentiation is the normal developmental process by which immature cells rapidly proliferate and change their function and phenotype as they mature into their terminally differentiated state. Poorly differentiated cells are often associated with high-grade, aggressive tumors. During tumorigenesis, cancer cells can hijack normal differentiation pathways to promote rapid proliferation of immature tumor cells. Differentiation therapy aims to target hijacked differentiation pathways and cellular plasticity mechanisms in cancer cells to stop tumor cell growth by promoting differentiation and/or cell death.




Our approach
Utilize machine learning to understand normal differentiation
At Auron, we have built a proprietary, machine learning platform called AURigin that integrates large, multi-omic datasets from primary human tissue samples to enable a systems-biology understanding of normal cellular differentiation. Using our proprietary machine learning models, we build atlases that define the normal differentiation states of cells and the pathways that drive terminal differentiation.


Determine drivers of dysregulated differentiation and cellular plasticity in cancer
Dysregulated differentiation in tumors can arise from: i. a block in the normal differentiation cascade, ii. de-differentiation of terminally differentiated cells to a more immature cell state, or iii. in some cases, transdifferentiation of cells through cellular plasticity mechanisms that enable a transformation from one cell fate to a different cell fate. In each form of dysregulated differentiation, the cancer cells can access multiple cell states that are normally transient during development, but are maintained in the tumor. Furthermore, de- and trans-differentiation are tumor escape routes used by cancers to become resistant to otherwise effective patient therapies. The key to treating these tumors is to first define these altered differentiation states, and then identify the pathways that have been co-opted by the cancer cells to drive tumor initiation and growth. By mapping tumors onto our proprietary, multi-omic normal differentiation atlases, we can determine the differentiation state of tumors and the hijacked pathways driving the dysregulation. We then therapeutically target these hijacked pathways to stop tumor cell growth or block tumor escape by promoting maturation and/or cell death.
Target dysregulated differentiation and cellular plasticity mechanisms in well-defined patient populations
Based on the differentiation state of a tumor, our atlas-based computational platform also allows us to define patient stratification and efficacy biomarkers associated with each target of interest. We then use these ‘responder IDs’ to identify specific patient populations for clinical trial enrollment and to track clinical efficacy. We also use our differentiation atlases to define the heterogeneity of a tumor and to inform clinical trial design and rational combination strategies.