# Antigen Density Sensors for Cell Engineering

> **NIH NIH R35** · STANFORD UNIVERSITY · 2024 · $386,000

## Abstract

Project Summary
 My laboratory combines mechanistic cell biology with synthetic biology, focusing on understanding
cellular behaviors like recognition and communication. We aim to advance the applications of engineered
multicellular systems, particularly in engineered T cells targeting solid tumors. Our research has a foundation on
two main questions.
 1) How can we engineer highly specific cellular recognition? We seek to understand the limits and
synergies of strategies for enhancing cellular specificity. Through a comparative analysis of synthetic circuits,
we will explore mechanisms such multi-step signaling, and molecular titration to optimize T cell discrimination of
tumors from bystander tissue based on antigen density. We also aim to uncover general principles for
engineering gene expression systems and its relationship with genome organization. This may lead to general
rules to engineer robust circuit behavior that could help in therapeutics.
 2) how does multicellular organization affect cellular recognition? In addressing the complexity and
heterogeneity of tumors, we aim for a quantitative understanding of how tissue architecture impacts T cell activity.
Using an engineered spheroid platform, our research will focus into how variation in antigen density in solid
tumors influence the antigen density sensing T cell activity. We anticipate extending this research to include
factors like tumor inhibitory signals, inter T cell communication and the role of chemokine secretion, on T cell
trafficking and tumor infiltration. The fundamental idea in this project is to control the composition and spatial
organization of a spheroid and to study how these properties affect the activity of engineered T cells.
In summary, our group will apply principles of molecular recognition and novel methods in cell and tissue
engineering to understand and control cellular behavior. By systematically deconstructing the problem of how T
cells recognize tumors from bystander tissue based on antigen density and studying the influence of tumor
organization to the immune response, we aim to layout fundamental rules to engineering recognition at the
cellular level and improve therapeutic cells.

## Key facts

- **NIH application ID:** 10941734
- **Project number:** 1R35GM155437-01
- **Recipient organization:** STANFORD UNIVERSITY
- **Principal Investigator:** Rogelio Antonio Hernandez-Lopez
- **Activity code:** R35 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $386,000
- **Award type:** 1
- **Project period:** 2024-06-15 → 2029-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10941734

## Citation

> US National Institutes of Health, RePORTER application 10941734, Antigen Density Sensors for Cell Engineering (1R35GM155437-01). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10941734. Licensed CC0.

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