Abstract 1127: Single cell network-based analyses reveal dose-dependent increase in myeloid suppressive cell sub-populations in response to radiation therapy

Aparna Krishnan,Shruti Bansal, Samanta Sarti, Michael D. Kissner,Charles Karan,Andrea Califano,Aleksandar Z. Obradovic,Catherine S. Spina

Cancer Research(2024)

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Abstract Background: More than half of all cancer patients undergo radiation therapy (RT) with curative or palliative intent. With the widespread use of immunotherapy to treat cancer, immune effects of radiation are an important consideration in design of sequential and combination therapies. While radiation has been found to deplete lymphocytes, less is known about its effects on the myeloid compartment, which includes both immune activating and suppressive populations. We hypothesized that a network-based analysis of single cell proteogenomic data generated from tumor-infiltrating immune cells can identify druggable proteins in pathways driving unwanted immunosuppressive changes with radiation, particularly among myeloid cells. Methods: Proteogenomic (CITE-Seq) analysis was conducted on CD45+ immune cells from unirradiated and irradiated orthotopic 4T1 murine mammary tumors three- and ten-days after tumor irradiation (8 Gy x 1 or 8 Gy x 3). Based on expression of select surface proteins, analysis of the CITE-Seq data resulted in eight distinct immune clusters, including three myeloid clusters — monocytes, macrophages, and granulocytes. Using VIPER (virtual inference of protein activity by enriched regulon), an algorithm that infers protein activities from weighted expression on each protein’s downstream targets, we identified distinct functional subpopulations within these eight clusters. Further profiling subclusters enriched by RT using the OncoTarget algorithm, we identified druggable proteins with significant inferred activity as potential targets of therapeutic interest. Results: As expected, lymphocytes were persistently depleted after RT on both radiotherapy schedules. However, three distinct subclusters of myeloid cells with immune-suppressive phenotype became enriched following tumor irradiation, with greater enrichment at the lower radiation dose of 8 Gy x 1: TAM2, PMN1, and PMN4. Surface protein expression enabled us to define the immunophenotype and isolate these three cell clusters from murine 4T1 tumors as well as human renal cell carcinoma tumors for further functional analyses. OncoTarget identified a number of druggable targets, including PARP1 for the PMN1 subcluster. Conclusion: Suppressive myeloid subpopulations induced by radiation were identified among the immune cells. Combining radiation therapy with inhibitors of these cell populations may provide therapeutic benefit over radiation therapy alone or in combination with checkpoint inhibitor immunotherapies. Future work will experimentally determine if inhibition of druggable protein targets in these myeloid subpopulations improves the overall efficacy of RT. Citation Format: Aparna Krishnan, Shruti Bansal, Samanta Sarti, Michael D. Kissner, Charles Karan, Andrea Califano, Aleksandar Z. Obradovic, Catherine S. Spina. Single cell network-based analyses reveal dose-dependent increase in myeloid suppressive cell sub-populations in response to radiation therapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1127.
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