# Systems analysis of cell-cell communication networks and immune activity in the melanoma tumor microenvironment

> **NIH NIH U01** · YALE UNIVERSITY · 2023 · $549,997

## Abstract

PROJECT SUMMARY
Understanding the dynamic cell-cell communication networks that establish immunological activity in the tumor
microenvironment (TME) would transform therapeutic strategies to help cancer patients that are unresponsive
to checkpoint inhibitors (CPIs). To this end, the overall objective of this proposal is to determine networks of
intercellular secreted signals that distinguish ineffective tumor-immune responses from effective ones in order to
identify new targets to improve efficacy of cancer immunotherapy (CIT). To achieve this objective, extensive
single-cell analysis will be performed on mouse models of melanoma and samples from human melanoma
patients in response to CPI-targeting of T cells, and CITs targeting tumor associated monocytes and
macrophages (TAMs). These data will be computationally analyzed to construct cell-cell interaction networks
between stromal, tumor, and immune cells to identify interactions that maintain immunosuppressive TMEs,
predict how to target them, and test these predictions experimentally. The central hypothesis tested in this
proposal is that intercellular signaling networks between TAMs and other cells in the TME are central to
suppressing immune activity, and that TAM-mediated networks are critical to reestablishing an effective TME
immune response, especially in cases of CPI resistance due to inadequate T cell responses. The rationale for
the proposed research is that identifying cell-cell interactions that distinguish immunosuppressive versus
immunosupportive TMEs will serve as a roadmap of new targets to test in unresponsive tumors. Aim 1 will
develop computational models that can distinguish between an ineffective versus effective anti-tumor immune
response. These models will be developed by constructing intercellular networks of receptor-ligand interactions
from single-cell RNA sequencing (scRNA-seq) and pathology data in growing and regressing murine and human
melanoma tumors. The models will be used to identify targets mediating cell-cell interactions that will be validated
experimentally. The objective of Aim 2 will be to determine how the functional plasticity of macrophages and
other myeloid cells contributes to an immunosuppressive TME in mice and human melanomas. Interactome
maps will be expanded to identify interactions between myeloid cell subsets and other cell types in the tumor
over time and with treatment. The proposed research is innovative because, rather than focusing solely on
isolated end points (e.g., T cell infiltration), it will identify the network of intercellular communication that stabilizes
those endpoints. With respect to cancer systems biology, the proposed research is innovative because it will
combine new computational methods–for defining cell subsets and network interactions from scRNA-seq data
and constructing predictive classification models–with syngeneic mouse melanoma models and human patient
samples that are ideally suited to evaluate CIT responses. The ...

## Key facts

- **NIH application ID:** 10696224
- **Project number:** 5U01CA238728-04
- **Recipient organization:** YALE UNIVERSITY
- **Principal Investigator:** MARCUS W BOSENBERG
- **Activity code:** U01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2023
- **Award amount:** $549,997
- **Award type:** 5
- **Project period:** 2020-07-01 → 2025-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10696224

## Citation

> US National Institutes of Health, RePORTER application 10696224, Systems analysis of cell-cell communication networks and immune activity in the melanoma tumor microenvironment (5U01CA238728-04). Retrieved via AI Analytics 2026-05-21 from https://api.ai-analytics.org/grant/nih/10696224. Licensed CC0.

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