# Learning features of optimal CAR T cells for LBCL from patient data

> **NIH NIH K99** · STANFORD UNIVERSITY · 2024 · $171,072

## Abstract

PROJECT SUMMARY/ABSTRACT
Chimeric antigen receptor (CAR) T cells have emerged as breakthrough treatments for patients with hematologic
malignancies, earning 12 approvals from the U.S. Food and Drug Administration (FDA) since 2017. Experimental
CAR T cell therapies have also demonstrated complete remissions in solid tumors, and the FDA is projecting to
grant 10-15 approvals per year by 2025, highlighting the potential of these ‘living therapies’. Despite this, current
CAR T cell designs have not yet mediated sustained efficacy in solid tumors, and only 30-50% of B cell leukemia
and lymphoma patients experience long-term disease control. To develop safe and potent next-generation CAR
T cell therapies, it is critical to understand why existing CAR T cells succeed or fail in patients. As a scientist
trained in both experimental and computational immuno-oncology, I have chosen to focus my career on using a
systems biology approach to uncover the molecular mechanisms governing efficacy of engineered T cell
immunotherapies. This proposal outlines a structured 2-year training plan and a comprehensive 5-year career
development program to complete my training and launch an independent research career. My specific research
goals are: (1) to define the most therapeutically relevant CAR T cell subsets in patients with large B cell
lymphoma (LBCL), and (2) to overcome an immune suppression mechanism of resistance to CAR T cell therapy
for LBCL. First, I will follow individual CAR T cell clones through time in patients treated for LBCL using matched
single-cell sequencing of transcriptome, a panel of surface proteins, and endogenous T cell receptors (Aim 1).
This approach, termed reverse fate mapping, will pinpoint T cell clones in the pre-manufacture apheresis and
infusion products with sought-after properties, including abilities to expand, persist, and home to the tumor. In
Aim 2, I will apply reverse fate mapping and methylation analyses to identify the origin of circulating CAR T
regulatory (Treg) cells that I recently linked to limited CAR T cell efficacy in LBCL. In Aim 3, I will mechanistically
dissect the interplay between Treg and non-Treg CAR T cells to design a potent ‘Treg-free’ CAR T cell therapy for
clinical evaluation. My work will generate a comprehensive CAR T cell atlas and insights, leading to promising
avenues for engineering the next-generation CAR T cell therapies. The results of my proposed research will
positively impact public health, as they will gather sufficient preliminary data for testing a ‘Treg-free’ CD19-CAR T
cell therapy for LBCL in a clinical trial and will deliver fundamental insights into CAR Treg biology that may
generalize to other diseases, including solid tumors, where engineered T cell therapies have not manifested
similarly potent effects as in LBCL. To build upon my skills, I have assembled a mentorship team, including my
primary mentor, Dr. Crystal Mackall, a pioneer in CAR T cell immunotherapies; co-mentor, Dr. Sy...

## Key facts

- **NIH application ID:** 10948863
- **Project number:** 1K99CA293149-01
- **Recipient organization:** STANFORD UNIVERSITY
- **Principal Investigator:** Zinaida Good
- **Activity code:** K99 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $171,072
- **Award type:** 1
- **Project period:** 2024-07-01 → 2024-12-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10948863

## Citation

> US National Institutes of Health, RePORTER application 10948863, Learning features of optimal CAR T cells for LBCL from patient data (1K99CA293149-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10948863. Licensed CC0.

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