2014 Recipient — Nima Aghaeepour, PhD

Nima Aghaeepour, PhD

Computationally-guided Characterization of Therapy-resistant Ovarian Tumors

Project Summary

Although the majority of patients who present with an aggressive ovarian tumor respond well to initial treatment, 70-90% of them will relapse and die of their disease. One explanation for this is the postulated existence of intrinsically therapy-resistant tumor-initiating cells (TICs) that can regenerate a complete tumor. Because these cells are often rare, standard technologies may be unable to detect them. Mass cytometry is a transformative new proteomics technology that enables characterization of rare and heterogeneous cell populations.

This project makes specific use of several technologies based on the mass cytometry platform to systematically identify and disrupt the signaling pathways that contribute to tumor-initiation at a single-cell-level. We will start by a comprehensive profiling of a wide range of tumors and cell lines. Next, we will use a correlative study against clinical parameters (e.g., time to recurrence), tumor initiation activity, and signaling pathways of interest, to identify candidate TIC populations. Then, an algorithm will mine our high-dimensional measurements of surface markers to identify optimized isolation strategies for functional validation of the TIC candidates in vivo. Finally, we will use a high-throughput mass cytometry technique to screen a wide range of standard-of-care and investigational compounds, including pathway-targeted inhibitors, on the purified TICs. This approach has the unique capability to measure drug responses in terms of tens of phenotypic and signaling pathway on millions of independent cells. This can enable the design of synergistic therapies for targeting multiple TIC compartments with minimal toxicity.

This grant was made possible by a donation from the UC Office of the President Tobacco-Related Disease Research Program.


Nima Aghaeepour, Ph.D. is currently a postdoctoral fellow with Prof. Garry Nolan at Stanford University and the Scholar of the International Society for Advancement of Cytometry. Dr. Aghaeepour completed his B.Sc. in Computer Science at University of Tehran with a focus on both robotics and systems biology. His Ph.D. training in the University of British Columbia was supported by graduate awards from the Canadian Institute of Health Research’s Strategic Training Program in Bioinformatics and the University of British Columbia’s 4Y Award. Dr. Aghaeepour’s current research is focused on computational analysis of signaling abnormalities in ovarian tumors at a single cell level using flow and mass cytometry.