Hypoxia organizes unique cellular niches in the tumor microenvironment in a mouse model of triple negative breast cancer.
- Abstract number
- 103
- Presentation Form
- Submitted Talk
- Corresponding Email
- [email protected]
- Session
- Stream 5: High-plex Cytometry
- Authors
- Abigail J. Walke (4), Dr. Noemi Kedei (1), Dr. Lisa A. Ridnour (2), Adam Teixeira (4), Dr. Elijah F. Edmondson (3), Adelaide L. Wink (4), Dr. William F. Heinz (4), Dr. Jinqiu Chen (1), Dr. David A. Wink (2), Dr. Stephen J. Lockett (4), Dr. David A. Scheiblin (4)
- Affiliations
-
1. Collaborative Protein Technology Resource, Center for Cancer Research, National Cancer Institute
2. Laboratory of Cancer Immunometabolism, Center for Cancer Research, National Cancer Institute
3. Molecular Histopathology Laboratory, Frederick National Laboratory for Cancer Research
4. Optical Microscopy and Analysis Laboratory, Frederick National Laboratory for Cancer Research
- Keywords
tumor microenvironment, multiplex immunofluorescence, metabolism, hypoxia, cellular niches
- Abstract text
Metabolism, oxygen tension, nutrient status and immune cell infiltration within the tumor microenvironment (TME) are hallmarks in determining patient outcome[1]. Hypoxia and nutrient deprivation induce chemoresistance, metastatic tumor phenotype, and immunosuppression driving poor prognosis[1, 2, 3, 4]. While immunosuppression has emerged as a key target in cancer therapy, many immune modulators fail in part by altered metabolic-associated phenotypes[2]. Thus, it is important to improve our current understanding of the relationship of hypoxic regions and immune and tumor cell phenotypes across the TME. The heterogeneous TME consists of functional groups of cells, termed cellular niches, which are thought to impact disease progression. We define three cellular niches within 4T1 tumors, which evolve over time (1) a therapeutic resistant cellular niche (TRCN), (2) an immunosuppressive cellular niche (ICN), and (3) an epithelial to mesenchymal cellular niche (EMTCN). A multiplex immunofluorescence (MIF) microscopy-based platform was developed to identify and correlate these distinct cellular niches. We used the 4T1 syngeneic mouse tumor model that resembles human triple negative breast cancer (TNBC) to detect and analyze such niches as they develop over time and increased tumor size. Regions of necrosis, hypoxic tumor, normoxic tumor, fibrosis, vascularization, stroma, and immune cell types were identified and quantified across tumors.
We hypothesize that O2 and nutrient deprivation, in part through metabolic changes, have profound effects on immune polarization, and therapeutic efficacy. To address this hypothesis, cell phenotypes and their spatial location across 4T1 tumors grown from 9 - 30 days after 4T1 cell implantation were analyzed. Since hypoxia plays a role in therapeutic resistance, hypoxic and vascularized tumor regions were spatially identified to give insight regarding the development of TRCN. Hypoxic regions increase as tumors age and grow. Moreover, there were alterations in the vascularization (identified by CD31+ cells) within the TME where CD31+ cells were further away from areas of hypoxia in early smaller tumors. In late larger tumors, CD31+ cells were increased and closer to areas of hypoxia suggesting that angiogenesis increased as the tumor progresses. However, the function of these vessels, if any was unknown.
To better understand the ICN, hot/cold immune environments across tumors were further classified across tumors by identifying immune cell compositions and their spatial relationships. We first delineated necrotic regions across the tumors. These necrotic regions increased with tumor age, size, and had significantly higher numbers of neutrophil-like cells (CD11b+ and Ly6G+) suggesting an increased innate immune / wound healing response in these areas. As CD4/CD8 ratios are commonly analyzed in tumors, we next spatially identified all individual t-helper (CD4+) and cytotoxic t-cells (CD8+) in these tumors. Toward this end, a shift in the adaptive immune microenvironment from a higher proportion of CD4+ cells around the early smaller tumors to a greater CD8+ proportion infiltrating the late larger tumors were observed. Concurrent with this shift, an increase in exhausted cytotoxic t-cells (CD8+ PD-1+) was identified in the tumor suggesting a greater immunosuppressive phenotype in certain microenvironments of late larger tumors. Previous studies have reported that CD8+ T-cells expressing both PD-1 and CD38 can suppress immune response. Thus, we enumerated CD8+ T cells positive for both PD-1 and CD38. We found that such triple positive cells increased as tumors aged and grew reinforcing the immunosuppressive phenotype.
The existence of the EMTCN was addressed by enumerating the EMT markers E-cadherin and vimentin. A decrease in E-cadherin positive cells along with an increase in vimentin positive cells indicate a transition of cells to the migratory mesenchymal phenotype with increased metastatic potential. Furthermore, cells positive for both proteins are known to be chemo resistant and to have a stem cell like phenotype. Our results showed the presence of all three phenotypes: cell positive for E-cadherin alone, vimentin alone, or both E-cadherin and vimentin. The three phenotypes of cells often clustered in different areas of the tumor suggesting the existence of EMTCNs.
Taken together, these results identify different types of cellular niches in 4T1 tumors that changes with tumor age and size. Ongoing studies are investigating further aspects of the geography of 4T1 tumors, including inflammation markers, fibrosis, other immune markers, and proliferation. In conclusion, therapeutic-resistant, immunosuppressive, and epithelial to mesenchymal cell niches have been identified as spatially distinct niches within 4T1 tumors. These results provide new insights into the progression of this aggressive tumor and in turn should lead to new diagnostics and improved therapies that could be targeted to the spatial-temporal characteristics of these cellular niches.
- References
[1] Lyssiotis, CA and Kimmelman, AC. Metabolic Interactions in the Tumor Microenvironment. Trends Cell Biol. 2017 Nov; 27(11): 863-875
[2] Pietrobon, V and Marincola, FM. Hypoxia and the phenomenon of immune exclusion. Journal of Translational Medicine. 2021 Jan; 19(9).
[3] Scharping, NE and Delgoffe, GM. Tumor Microenvironment Metabolism: A New Checkpoint for Anti-Tumor Immunity. Vaccines. 2016 Dec; 4(4):46.
[4] Renner, K et al. Metabolic Hallmarks of Tumor and Immune Cells in the Tumor Microenvironment. Front. Immunol. 2017 Mar.
[5] We gratefully acknowledge contributions of the Molecular Histopathology Laboratory at NCI – Frederick and support from Dr. David Goldstein, Office of Science and Technology Resources, CCR. Funded by NCI Contract No. 75N91019D00024.