# Langworthy Diversity Supplement: Image-based models of tumor-immune dynamics in glioblastoma

> **NIH NIH U01** · MAYO CLINIC ARIZONA · 2021 · $46,105

## Abstract

ABSTRACT
Glioblastoma Multiforme (GBM) is the most common of all gliomas with a median survival 14-18 months, despite
aggressive treatment regimens. Immunotherapy is emerging as a promising method to treat cancer; however,
we are not able to identify early response or predict who will respond. These uncertainties pose serious
challenges to being able to effectively apply immunotherapeutic approaches. While biopsies are the most reliable
way to assess the immunological landscape within the tumor, we are limited both spatially and temporally in the
number of biopsies we can obtain, particularly for brain tumor patients. The heterogeneity of the tumor-immune
landscape across patients suggests that a patient-specific approach will be required to accurately assess each
patient’s individual tumor-immune environment and the evolution thereof. As part of the Parent Grant, we will
use non-invasive imaging, image-guided biopsies, computational modeling, and artificial intelligence to bridge
spatial and temporal scales and predict the abundance of glioma associated microglia/macrophages (GAMMs)
comprising each magnetic resonance image (MRI) at the voxel level. Linking the MRI to the biological
heterogeneity using radiomics approaches provides an opportunity to individualize our understanding of the
tumor-immune environment. Specifically, for this supplement, we will use the predictive tumor-immune maps to
develop an immunotherapy response metric termed GAMMs Days Gained (GDG), which is based on the existing
Days Gained metric. GDG will be used to evaluate the GAMM population changes with therapy as depicted by
the predictive map. We expect that the GDG will aid in understanding who will respond based on early predictive
map changes. Additionally, the GDG metric will be compared to results from other immunotherapy response
metrics, including the standard immunotherapy response assessment in neuro-oncology (iRANO) criteria.

## Key facts

- **NIH application ID:** 10381307
- **Project number:** 3U01CA250481-01A1S1
- **Recipient organization:** MAYO CLINIC ARIZONA
- **Principal Investigator:** Peter Canoll
- **Activity code:** U01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $46,105
- **Award type:** 3
- **Project period:** 2021-03-01 → 2026-02-28

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10381307

## Citation

> US National Institutes of Health, RePORTER application 10381307, Langworthy Diversity Supplement: Image-based models of tumor-immune dynamics in glioblastoma (3U01CA250481-01A1S1). Retrieved via AI Analytics 2026-05-29 from https://api.ai-analytics.org/grant/nih/10381307. Licensed CC0.

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