# Understanding and Mimicking TCR Recognition with Therapeutic Monoclonal Antibodies.

> **NIH NIH R35** · SLOAN-KETTERING INST CAN RESEARCH · 2021 · $1,062,000

## Abstract

Abstract
The goals of my research since 1978 have been to distinguish the features of cancer cells from
healthy cells in order to be able to discover and develop safe and selective, innovative
immunotherapies. Here, we leverage my past body of work that has evolved from native mouse
antibodies, to humanized mAb, to various potent conjugates of these mAb, to TCRm antibodies,
and ultimately to BiTE forms and CAR forms to create the latest generation of agents and
experiments now proposed. This scientific progression has been sustained for more than 3
decades. This work is innovative, as noted by our numerous therapeutic firsts and more than 3
dozen patents, including: human antibodies for the treatment of acute leukemia, targeted alpha-
particle therapies, in vivo alpha-particle isotope generators, oncogenic fusion point vaccines,
human TCR mimic antibodies to intracellular oncogenic proteins, and most recently, various
innovative CAR technologies, now in progress. Several of the antibodies and vaccines reached
late stage, national clinical trials such as a WT1 vaccine, Galenpepimut, and our alpha
generator-Lintuzumab. But now, how do we achieve true cancer specificity? The immune
system has evolved the T cell and TCR as a highly efficient and truly selective system capable
of recognizing viral and mutated intracellular proteins derived from inside the cell. Therefore, in
this OIA the questions are: Is it possible to make truly cancer selective monoclonal antibodies,
and various derived molecular platforms, that will be effective therapeutically by mimicking a
TCR? What are the obstacles and cancer resistance mechanisms to this approach and how will
they be overcome? How do we select the right target epitopes and also avoid inevitable off-
targets that may cause toxicity? The following issues will be addressed: A. Target choices: What
are the best epitopes from a biochemical, biophysical, or immunological point of view? Are
certain classes of proteins or structures of peptides preferred? How do we design screens for
TCRm? B. Can we modulate the expression of the epitopes or the antigen presentation
machinery? How is the MHC ligandome generally affected by these drugs and is this important?
C. Predictive tools: Can we develop proteomic and genetic tools to create general rules and to
help guide us to picking epitopes and predicting which may be safe? D. What cancer
therapeutic platform for the TCRm makes the most sense in light of what we have learned about
the biology and immunology of the epitope, as well as the predictions of specificity from the tool
sets?

## Key facts

- **NIH application ID:** 10238855
- **Project number:** 5R35CA241894-02
- **Recipient organization:** SLOAN-KETTERING INST CAN RESEARCH
- **Principal Investigator:** DAVID A SCHEINBERG
- **Activity code:** R35 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $1,062,000
- **Award type:** 5
- **Project period:** 2020-08-14 → 2027-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10238855

## Citation

> US National Institutes of Health, RePORTER application 10238855, Understanding and Mimicking TCR Recognition with Therapeutic Monoclonal Antibodies. (5R35CA241894-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10238855. Licensed CC0.

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