Engineering Immunity in the Tumor Microenvironment Using Spatial Biology and Modeling

I am an instructor at Cedars Sinai Medical Center pursuing a faculty position in Chemical Engineering. My overarching research goal as an independent scientist is to understand and improve immunotherapy by studying the tumor microenvironment. I believe the key to cancer immunotherapy lies in the spatial biology of the tumor, and my research lab will perform systems biology-driven analysis of tumor tissue, develop new computational methods to demystify immune cell spatial biology, and create methods to perturb and study spatial biology. My teaching goal is to demonstrate how translational cancer research embraces complexity and systems biology to achieve clinical results, with the assistance of materials and nanotechnology. These goals are the product of my research journey, where I have integrated materials science, systems biology, and now clinical translational science into my research vision. I will present vignettes for my major projects and publications, and I will summarize how these projects shape my independent research vision and my preliminary data and funding results to achieve these goals.

Research Interests:

My research program will consist of three primary aims. The first aim is to analyze the spatial biology of tumor tissue using computational techniques that I developed. For three years I have been studying tumor spatial biology at Cedars Sinai Medical Center using highly multiplexed spatial protein analysis, with first and co-first authored papers on Hodgkin’s Lymphoma (in preparation), colorectal cancer metastases (resubmitted at Cell Metabolism), and ovarian cancer (under review at PNAS). I will discuss the pipelines created to identify spatial and protein biomarkers to predict patient outcomes, paying close attention to spatial features such as specific ligand-receptor interactions driving immune-tumor aggregation, and localized immune subtypes in tumor vs stromal regions of tissue.

The second aim is to focus on the role of T cells in tumor immunology by studying antigen-specificity using computational and modeling approaches. First, I will briefly describe 4 linked studies where T-cell receptor sequencing was used to study the patient response to vaccination against COVID-19 at population levels using human samples collected at the hospital. Next, I developed a computational strategy that effectively compares T-cell receptors to discover sequence motifs that predict antigen-specificity. Using a computational model based off of the binding-restrictive orientation of the TCR-MHC complex, I consider the sequences of antigen-specific TCRs of all lengths, and perform entropic analysis to identify “essential” and “super-essential” 2-mers, consecutive amino acids needed for antigen recognition. The study, in press at Cell Systems, also considers patterns of 2-mer usage across antigens, and validates computational findings using protein folding simulations with Alphafold.

The third aim of my research program will be to develop materials-based assays to analyze spatial biology. I previously developed tools for single cell analysis and intracellular delivery to study aspects of cancer and immune heterogeneity. I will briefly describe how the techniques used for these tools (microfluidics, high-aspect ratio nanowire penetration into cells, high-avidity T-cell receptor pulldown) will be adapted to study immune cell perturbations in cancer models of immunotherapy.

Teaching Interests:

My primary teaching interest is to drive greater recognition of spatial biology, and to communicate how spatial biology draws from different areas of engineering. This includes experimental method development via materials and chemistries, computational tools for big data and image processing, systems biology insights for interpreting spatial data, and finally device and cellular engineering used to translate spatial insights into clinical settings. I recently organized a 2-day spatial biology symposium at our hospital, which was attended by over 300 people and featured speakers from across the greater Los Angeles area. I also organize a bi-weekly spatial biology seminar series. Our hospital does not have regular coursework or teaching opportunities, so I have been involved in a new initiative called Translational Research in Bioengineering, where I serve as a steering committee member focused on raising awareness of bioengineering techniques in the hospital. I believe that I have a unique teaching perspective, as for the last 5 years I have been positioned at either a small research institute or at a research hospital. An alternative teaching goal of mine is also to de-silo engineering departments by highlighting collaborative opportunities with medical and translational researchers.

Candidate Background:

I am an NCATS KL2 fellow and instructor at Cedars Sinai Medical Center, where I am also the Associate Director of the Spatial Molecular Profiling Core Facility. I study the spatial biology of tumors and T-cell receptor informatics under the mentorship of Dr. Akil Merchant. Previously, I was an F32 Postdoctoral Fellow at the Institute for Systems Biology and Caltech in the lab of Dr. James Heath. I obtained my PhD in Materials Science and Engineering with Dr. Nicholas Melosh at Stanford University, where I was an NSF GRFP and NDSEG fellow.

Figure Caption:

Future Research Areas of Focus. A. Spatial tumor biology: Highly multiplexed protein analysis reveals tumor tissue heterogeneity. B. Biomarker analysis identifies specific immune cell types that predict patient outcomes. C. Spatial focused computational analysis identifies ligand-receptor cell-cell interactions that guide tumor architecture. D. Population analysis of T cell receptor trends over the course of vaccine response. E. T cell informatic analysis identifies motifs with predictive capacity using entropic analysis. F. Micro and nanotechnologies developed and used for tumor and immune cell analysis: Nanostraws for intracellular delivery. G. Microfluidics for antigen-specific cell sorting and sequencing. H. Microfluidics for single cell multi-omics.