Abstract 3448: Profiling the urinary bladder cancer composition and inter-cellular proximity patterns using single-cell RNA-sequencing and spatial transcriptomics

Abstract Urinary bladder cancer (UBC) has shown to be difficult to treat, attributed to tumor heterogeneity and differences in response to treatment based on molecular subtypes. It is essential that we increase our knowledge the interplay between the tumor, stroma and immune system to improve our knowledge of the TME in UBC and thereby therapeutic options. Herein we employed single-cell RNA sequencing and in situ spatial transcriptomics on bladder samples from two UBC mouse models (model development in PMID 34232958), including in-depth immune clustering to characterize the TME during tumor progression from non-muscle invasive bladder cancer (NMIBC) to the muscle-invasive bladder cancer (MIBC) stage in a semi-spontaneous UBC model. Granulocytes and lymphoid cells were enriched in the carcinogen-induced tumors, while monocytes/macrophages were more prevalent in the reference MB49 cell line-transplantable orthotopic tumor model. Immune activation was generally increased in tumor-bearing mice overall. Lymphoid cell analysis identified NK cells and various T and B cell types, with effector CD8 T cells in carcinogen-induced tumors and scarce naïve CD4 and CD8 cells in MB49 mice. Differentially expressed genes between NMIBC and MIBC stages were predominantly linked to cell proliferation and signaling pathways. Interestingly, inferred cell interaction analysis by CellChat predicted increased Cd6-Alcam signaling within the lymphoid populations between T cells and basal or myeloid cells. Myeloid cell analysis displayed distinct profiles between the two models with infiltration of Ms4a7+ macrophages in the carcinogen-induced model and Iftim1+ macrophages in the MB49 model. Also, stage played a role for myeloid infiltration, with primarily Ccl8+ macrophages enriched in NMIBC, while those in MIBC were predominant of Spp1+ type. Granulocyte analysis identified eight clusters with diverse distributions in carcinogen-induced tumors, including four with strong neutrophil-like phenotypes (Isg, Retnlg, Hif-1, and SigF). Spatial transcriptomics indicated increased monocyte/macrophage tumor influx and interestingly, a significant interaction with bladder mesenchymal cells upon tumor progression. This technique also showed noticeable granulocyte tumor infiltration of penetrated tumor tissue at both the NMIBC and MIBC stages, the latter at higher levels, possibly suggesting spiraling pro-inflammatory TME. This data provide an example of that we need to further improve our knowledge of the myeloid/granulocyte role in UBC and consider how to selectively target subtypes of these cells with pharmacological interventions to improve therapeutic outcome in this severe disease, a disease that often recurs at the NMIBC stage and that presents with a high mortality in the MIBC stage. Citation Format: Alexandros Kostakis, Andrea Behanova, Iliana Kerzeli, Ramy Elgendy, Aikaterini Chourlia, Sven Nelander, Per-Uno Malmstrom, Ulrika Segersten, Milena Doroszko, Anca Dragomir, Carolina Wahlby, Martin Lord, Sara Mangsbo. Profiling the urinary bladder cancer composition and inter-cellular proximity patterns using single-cell RNA-sequencing and spatial transcriptomics [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 3448.

Authors

Institutions

Publication Details

Journal
Cancer Research
Published
2025-04-21
DOI
https://doi.org/10.1158/1538-7445.am2025-3448
Primary Topic
Bladder and Urothelial Cancer Treatments
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Abstract 3448: Profiling the urinary bladder cancer composition and inter-cellular proximity patterns using single-cell RNA-sequencing and spatial transcriptomics

Andrea Beháňová, Aikaterini Chourlia, Sara M. Mangsbo, Iliana Kerzeli et al.
Cancer Research
Bladder and Urothelial Cancer Treatments
article

Abstract 3448: Profiling the urinary bladder cancer composition and inter-cellular proximity patterns using single-cell RNA-sequencing and spatial transcriptomics

Andrea Beháňová, Aikaterini Chourlia, Sara M. Mangsbo, Iliana Kerzeli, Carolina Wählby, Anca Dragomir, Per‐Uno Malmström, Sven Nelander, Martin Lord, Ramy Elgendy, Milena Doroszko, Ulrika Segersten, Alexandros Kostakis
article en

Abstract

Abstract Urinary bladder cancer (UBC) has shown to be difficult to treat, attributed to tumor heterogeneity and differences in response to treatment based on molecular subtypes. It is essential that we increase our knowledge the interplay between the tumor, stroma and immune system to improve our knowledge of the TME in UBC and thereby therapeutic options. Herein we employed single-cell RNA sequencing and in situ spatial transcriptomics on bladder samples from two UBC mouse models (model development in PMID 34232958), including in-depth immune clustering to characterize the TME during tumor progression from non-muscle invasive bladder cancer (NMIBC) to the muscle-invasive bladder cancer (MIBC) stage in a semi-spontaneous UBC model. Granulocytes and lymphoid cells were enriched in the carcinogen-induced tumors, while monocytes/macrophages were more prevalent in the reference MB49 cell line-transplantable orthotopic tumor model. Immune activation was generally increased in tumor-bearing mice overall. Lymphoid cell analysis identified NK cells and various T and B cell types, with effector CD8 T cells in carcinogen-induced tumors and scarce naïve CD4 and CD8 cells in MB49 mice. Differentially expressed genes between NMIBC and MIBC stages were predominantly linked to cell proliferation and signaling pathways. Interestingly, inferred cell interaction analysis by CellChat predicted increased Cd6-Alcam signaling within the lymphoid populations between T cells and basal or myeloid cells. Myeloid cell analysis displayed distinct profiles between the two models with infiltration of Ms4a7+ macrophages in the carcinogen-induced model and Iftim1+ macrophages in the MB49 model. Also, stage played a role for myeloid infiltration, with primarily Ccl8+ macrophages enriched in NMIBC, while those in MIBC were predominant of Spp1+ type. Granulocyte analysis identified eight clusters with diverse distributions in carcinogen-induced tumors, including four with strong neutrophil-like phenotypes (Isg, Retnlg, Hif-1, and SigF). Spatial transcriptomics indicated increased monocyte/macrophage tumor influx and interestingly, a significant interaction with bladder mesenchymal cells upon tumor progression. This technique also showed noticeable granulocyte tumor infiltration of penetrated tumor tissue at both the NMIBC and MIBC stages, the latter at higher levels, possibly suggesting spiraling pro-inflammatory TME. This data provide an example of that we need to further improve our knowledge of the myeloid/granulocyte role in UBC and consider how to selectively target subtypes of these cells with pharmacological interventions to improve therapeutic outcome in this severe disease, a disease that often recurs at the NMIBC stage and that presents with a high mortality in the MIBC stage. Citation Format: Alexandros Kostakis, Andrea Behanova, Iliana Kerzeli, Ramy Elgendy, Aikaterini Chourlia, Sven Nelander, Per-Uno Malmstrom, Ulrika Segersten, Milena Doroszko, Anca Dragomir, Carolina Wahlby, Martin Lord, Sara Mangsbo. Profiling the urinary bladder cancer composition and inter-cellular proximity patterns using single-cell RNA-sequencing and spatial transcriptomics [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 3448.

Cancer ResearchVol. 85(8_Supplement_1)
Uppsala University (SE)
Openalex Percentile: Top 86%
Bladder and Urothelial Cancer Treatments
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.