EventsCancersScape: Spatial Biology of the Tumor Ecosystem
Published
This submission belongs to the session S2. Spatial Intra-Tumoral Heterogeneity in the Tumor Microenvironment of the event CancersScape: Spatial Biology of the Tumor Ecosystem
Published date
05 Nov, 2025
Academic Editor
author-avatarSamuel Mok
Citation
Basant Gamal, Olamide Animasahun, Erin Seeley, Kathryn Lu, Javier A. Gomez, Yadira Pacheco, Akshay Basi, Christopher Pacheco, Jared K. Burks, Deepak Nagrath, Samuel C. Mok, Sammy Ferri-Borgogno, Unplugging glutamine: how to crash the ovarian cancer party, in Proceedings of CancersScape: Spatial Biology of the Tumor Ecosystem, Barcelona, 5 November–7 November 2025, MDPI: Basel, Switzerland
Share
Email
Facebook
Twitter
LinkedIn

Unplugging glutamine: how to crash the ovarian cancer party

Kathryn Lu 1
Yadira Pacheco 1
Christopher Pacheco 4
image
1. Department of Gynecologic Oncology and Reproductive Medicine, the University of Texas MD Anderson Cancer Center, Houston, TX, USA, USA
2. Department of chemical engineering, The University of Michigan, Ann Arbor, MI, USA
3. Department of Chemistry, University of Texas at Austin, Austin, TX, USA
4. Department of Leukemia, the University of Texas MD Anderson Cancer Center, Houston, TX, USA, USA
Abstract

High-grade serous ovarian cancer (HGSC) is typically diagnosed at an advanced stage, with frequent chemoresistant relapse despite strong response to platinum/taxane-based chemotherapy. Recent studies have shown that cancer-associated fibroblasts (CAFs) within the tumor microenvironment (TME) produce modifying factors, like cytokines, that significantly modulate malignant phenotypes in HGSC. We identified an unrecognized mechanism wherein metabolic reprogramming via an upregulated glutamine anabolic pathway occurs in reactive CAFs within HGSC tissue. This dysfunctional pathway endows CAFs with atypical metabolic flexibility, using noncanonical carbon and nitrogen sources, producing glutamine in the nutrient-poor tumor microenvironment. We demonstrated that normally fed C57BL/6 mice injected with syngeneic fallopian epithelial cell-derived cancer cells exhibited markedly higher tumor burden than those on a glutamine-free (GF) diet. Tumor-bearing mice treated with a glutaminase inhibitor showed reduced tumor burden relative to vehicle-treated controls, indicating that glutamine depletion hinders tumor growth and inhibits disease progression. Imaging mass cytometry (IMC) and mass spectrometry imaging (MSI) applied to serial sections from murine tissue microarrays investigated whether the tumor immune microenvironment mediates the effect of glutamine deprivation on reducing tumor burden. Our results demonstrated that GF diet mice exhibited alterations in the cellular composition of the TME with significantly reduced tumor burden. Compared to control mice, GF diet mice had enhanced B-cell-related immune response, decreased stemness and levels of epithelial–mesenchymal transition (EMT) cancer cells, and lower density of activated CAFs. Neighborhoods surrounding EPCAM+ PANCK+ tumor cells in GF-fed mice were more densely populated with various cell types, particularly neutrophils, and enriched in metabolic signatures such as kynurenic acid and indole-3-carbinol. Sequential immunofluorescence (seqIF) studies validated IMC and MSI findings, characterizing the functional properties of cell phenotypes while showing different neighborhoods between GF and control groups. Our findings suggest that glutamine is central in metabolic reprogramming of the ovarian tumor immune microenvironment, effecting spatially resolved cellular and metabolic profiles of the ovarian TME.

Keywords
Spatial Biology
cancer
Sequential immunofluorescence
seqIF
High-grade serous ovarian cancer
tumor immune microenvironment
imaging mass cytometry
IMC
mass spectrometry imaging
MSI
glutamine
Dual Strategy for Glioblastoma Treatment: Targeted Photothermal Ablation and Macrophage-Mediated Nanoparticle Distribution
Systems biology pipeline reveals anticancer potential of Curcuma amada in prostate cancer: integrated approach combining network pharmacology, bioinformatics, spatial profiling and experimental validation