# Radioimmunogenomic Habitat Phenotypes to Predict Efficacy of Neoadjuvant Immunotherapies in Non-Small Cell Lung Cancer

> **NIH NIH R01** · UNIVERSITY OF TX MD ANDERSON CAN CTR · 2022 · $661,394

## Abstract

ABSTRACT
Lung cancer is the leading cause of cancer-related mortality in the United States and worldwide. The efficacy of
immune checkpoint inhibitors (ICIs) in patients with metastatic non-small lung cancer (NSCLC) prompted the
clinical investigation of these agents in the early-stage operable setting. Several theoretical advantages exist
when we administer ICIs before surgery (neoadjuvant) rather than postoperatively (adjuvant), including an
opportunity to address micrometastases early in the course of treatment, and may impart immunologic memory
to prevent tumor recurrence. Indeed, the results from our preclinical models of resectable NSCLC demonstrated
that combined neoadjuvant ICIs resulted in fewer lung metastases, greater immune infiltration of tumors, and
longer overall survival compared with mice treated with monotherapy or adjuvant combined ICIs. Those results
informed the first reported randomized phase 2 study testing neoadjuvant ICI combinations in patients with
resectable NSCLC using major pathologic response (MPR, ≤10% viable tumor) as a surrogate endpoint for
clinical efficacy (NEOSTAR, PI: Cascone). Neoadjuvant chemoimmunotherapy has been shown to be highly
promising for resectable NSCLC, and is now being tested in one of the phase 3 randomized studies in patients
with operable NSCLC (CheckMate-77T, Lead PI: Cascone). However, a major shortcoming of all of the
neoadjuvant trials, is that no validated biomarker exists that can be used to stratify patients. Consequently, many
of these patients on these trials do not achieve an MPR at surgery, indicating that limited benefit may be gained
from induction ICIs. By delaying surgery in patients who may not benefit, the risks of disease progression and of
eliminating a chance to offer potentially curative surgery upfront occur. The ongoing evaluation of molecular
biomarkers of clinical benefit to ICIs has proved disappointing as evidenced by the significant intertrial variability,
possibly related to intratumor heterogeneity. By contrast, radiologic imaging provides a holistic view of tumor
characteristics and interactions with the adjacent tissue. Built on our promising preliminary data, we propose to
spearhead radiographic and radiogenomics strategies to address this unmet clinical need. We hypothesize that
imaging phenotypes reflect tumor microenvironment, and quantitative imaging phenotyping will shed light on our
understanding of the mechanisms of response to ICIs and yield surrogates of clinical efficacy. We will leverage
the parallel assessment of well-curated data from unique clinical trials and immunocompetent mouse models to
develop new imaging biomarkers and validate their clinical and biological relevance. The strength of this proposal
is our interdisciplinary team with the requisite expertise and ability to treat patients, obtain and analyze high-
quality, longitudinal imaging and biospecimens and rapidly evaluate putative imaging biomarkers for therapeutic
response and clin...

## Key facts

- **NIH application ID:** 10489755
- **Project number:** 5R01CA262425-02
- **Recipient organization:** UNIVERSITY OF TX MD ANDERSON CAN CTR
- **Principal Investigator:** Tina Cascone
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $661,394
- **Award type:** 5
- **Project period:** 2021-09-16 → 2026-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10489755

## Citation

> US National Institutes of Health, RePORTER application 10489755, Radioimmunogenomic Habitat Phenotypes to Predict Efficacy of Neoadjuvant Immunotherapies in Non-Small Cell Lung Cancer (5R01CA262425-02). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10489755. Licensed CC0.

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