# Project 2:  Deciphering the Dynamic Evolution of the Tumor-Immune Interface

> **NIH NIH U54** · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · 2024 · $422,043

## Abstract

ABSTRACT – PROJECT 2
The central premise of our CSBC MIT/DFCI Center for Systems Biology in Glioblastoma is that high-content
systems-level measurement techniques, employed across a variety of scales (molecular-cellular-tissue) with
cell-type specific and spatial resolution, and combined with data integration, data deconvolution, and
computational modeling, will enable the identification of critical pathways and networks regulating tumor
progression and therapeutic resistance, while also providing biomarkers reflecting tumor state and efficacy of
improved therapeutic strategies. This project aims to apply this same premise to the tumor-immune interface,
defining the molecular pathways and networks underlying the dynamic evolution of the immunosuppressive state
of GBM tumors. To this end, we have designed a multi-tiered project, with the foundation based on carefully
controlled co-evolution of the tumor-immune interface in co-culture model systems in vitro, with temporal
systems-level multi-omic analysis of molecular nodes in specific cell types provided by experimental and
computational deconvolution. Computational modeling of this data coupled to quantitative phenotypic data will
yield predictions as to nodes, pathways, and networks associated with altered immune and tumor states that will
be experimentally verified. In the second Aim, we extend these studies to multiple GEMM and syngeneic murine
models to query the tumor-immune interface in vivo, with spatial and temporal systems-level analysis at different
time points of tumor development and in response to therapy. We also use this Aim to interrogate the role of
different immune cells in mediating the evolution of the tumor-immune interface by engineering mice lacking
various immune cell types and repeating the above studies. Computational modeling of these data connect
molecular networks with dynamic evolution in the more complex in vivo environment. Finally, in the third Aim of
this project, we extend these analyses to geographically distinct regions of human GBM tumors through systems-
level analysis of spatially-guided core biopsies. These human tumor specimens provide ‘ground truth’ data for
our computational models and enable development of quantitative models predicting the therapeutic impact of
different treatment strategies. Together, this project will yield unprecedented systems-level molecular insight into
the tumor-immune interface, enabling identification of novel therapeutic targets to abrogate the
immunosuppressive nature of GBM tumors.

## Key facts

- **NIH application ID:** 10930073
- **Project number:** 5U54CA283114-02
- **Recipient organization:** MASSACHUSETTS INSTITUTE OF TECHNOLOGY
- **Principal Investigator:** Forest M White
- **Activity code:** U54 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $422,043
- **Award type:** 5
- **Project period:** 2023-09-15 → 2028-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10930073

## Citation

> US National Institutes of Health, RePORTER application 10930073, Project 2:  Deciphering the Dynamic Evolution of the Tumor-Immune Interface (5U54CA283114-02). Retrieved via AI Analytics 2026-06-24 from https://api.ai-analytics.org/grant/nih/10930073. Licensed CC0.

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