# Project 3: Predictors of sensitivity to immunotherapy and targeted treatments based on real world evidence

> **NIH NIH P01** · SLOAN-KETTERING INST CAN RESEARCH · 2024 · $233,452

## Abstract

PROJECT 3 ABSTRACT
Predictors of sensitivity to immunotherapy and targeted treatments based on real world evidence
Project Leaders: Phillipe Bedard (Princess Margaret); Nikolaus Schultz, (MSK)
Approvals of precision medicines directed against defined genomic targets and immune checkpoint inhibitors
(ICIs) for genomic signatures of immunotherapy benefit have transformed the outcomes of many patients whose
tumors harbor these alterations. However, there are unanswered questions about targeting uncommon driver
mutations, as well as the pan-cancer clinical actionability and optimal definition(s) of approved tumor agnostic
genomic biomarkers, such as tumor mutation burden (TMB) for ICI therapy. While each clinical scenario where
these questions remain may be individually rare, hampering the feasibility of prospective clinical trials to address
specific hypotheses, they collectively impact a substantial proportion of patients that might benefit from precision
medicine approaches. The AACR Project GENIE clinical-genomic database is ideally suited for curation of
clinical outcomes of relevant patients with genomic alterations, providing essential additional evidence for
prospective real-world clinical decisions in these scenarios.
Our specific aims are to: 1) Characterize the clinical outcomes of patients treated with immune checkpoint
inhibitor (ICI) therapy and their association with molecular biomarkers; 2) Evaluate the clinical outcomes of
patients with specific driver mutations treated with targeted therapies; and 3) Leverage observational GENIE
data to improve outcome prediction in the OncoKB precision oncology knowledge base. We will investigate
associations between TMB and clinical-pathological characteristics, genomic covariates, and treatment
outcomes with ICI therapy including progression free survival evaluated using PRISSMM methodology and
overall survival with ICI treatment. We will analyze genomic and transcriptomic data from a subset of samples
associated with outliers responses to ICI treatment. We will curate per patient efficacy outcomes for patients with
rare oncogenic driver mutations, including ERBB2 mutations and BRAF class II/III mutations, treated with
matched off-label targeted therapies to investigate tumor type specificity, variant sensitivity, and the impact of
co-mutations on treatment response. We will create an evidence-based framework within the OncoKB precision
medicine knowledge base to include observational data from GENIE and an outcome prediction tool for ICI
treatment with clinical and genomic covariates. The ultimate goal of this Project is to use observational data from
GENIE to develop a better understanding of predictors of sensitivity to immunotherapy and targeted treatments
to inform clinical decision-making.

## Key facts

- **NIH application ID:** 10768977
- **Project number:** 1P01CA275746-01A1
- **Recipient organization:** SLOAN-KETTERING INST CAN RESEARCH
- **Principal Investigator:** Nikolaus Schultz
- **Activity code:** P01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $233,452
- **Award type:** 1
- **Project period:** 2024-09-03 → 2029-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10768977

## Citation

> US National Institutes of Health, RePORTER application 10768977, Project 3: Predictors of sensitivity to immunotherapy and targeted treatments based on real world evidence (1P01CA275746-01A1). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10768977. Licensed CC0.

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