Spatial transcriptomics reveals site-specific cellular and metabolic heterogeneity in bladder carcinoma in situ
- 1University of California San Diego
Abstract
Bladder carcinoma in situ (CIS) is a multifocal, non-muscle-invasive disease with a high risk of progression to muscle-invasive cancer. Current management strategies are often guided by genomic profiling of single tumor samples, which incompletely capture tumor heterogeneity and may contribute to treatment failure. In particular, the multifocal nature of CIS raises uncertainty regarding the uniformity of genomic, immunologic, and microenvironmental features across anatomically distinct sites within the same patient. To address this, we performed spatial transcriptomic profiling of CIS-containing tissue from four anatomically distinct sites within a single individual. Unsupervised clustering with marker-based annotation, integrated with metabolic inference, identified epithelial tumor populations alongside stromal, immune, and smooth muscle compartments. While key cellular states were conserved, their spatial organization and relative abundance varied by site. Metabolic analysis further revealed region-specific microenvironments shaped by local cellular architecture. These findings indicate that both cellular composition and metabolic activity are spatially structured. Collectively, these results demonstrate that CIS exhibits significant intra-patient heterogeneity not captured by single-site profiling. These findings require validation in larger cohorts but support multi-region sampling could help improve risk stratification, biomarker development, and prediction of response to intravesical therapies, with potential implications for more personalized treatment strategies.
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BibTeX
@misc{myers2026spatial,
title = {{Spatial transcriptomics reveals site-specific cellular and metabolic heterogeneity in bladder carcinoma in situ}},
author = {T. Myers and A. Salmasi and M. F. Meagher and S. Azari and S. Donato and I. Kalcheva and S. J. Song and H. Zhang and K. Yuen and A. Bagrodia and T. F. Stewart and M. Liss and A. Bartko},
howpublished = {bioRxiv},
year = {2026},
month = aug,
doi = {10.64898/2026.08.27.741603},
url = {https://www.biorxiv.org/content/10.64898/2026.08.27.741603v1},
note = {CC BY-NC},
}
RIS
TY - UNPB
TI - Spatial transcriptomics reveals site-specific cellular and metabolic heterogeneity in bladder carcinoma in situ
AU - T. Myers
AU - A. Salmasi
AU - M. F. Meagher
AU - S. Azari
AU - S. Donato
AU - I. Kalcheva
AU - S. J. Song
AU - H. Zhang
AU - K. Yuen
AU - A. Bagrodia
AU - T. F. Stewart
AU - M. Liss
AU - A. Bartko
PY - 2026
DA - 2026/08/27
PB - bioRxiv
DO - 10.64898/2026.08.27.741603
UR - https://www.biorxiv.org/content/10.64898/2026.08.27.741603v1
AB - Bladder carcinoma in situ (CIS) is a multifocal, non-muscle-invasive disease with a high risk of progression to muscle-invasive cancer. Current management strategies are often guided by genomic profiling of single tumor samples, which incompletely capture tumor heterogeneity and may contribute to treatment failure. In particular, the multifocal nature of CIS raises uncertainty regarding the uniformity of genomic, immunologic, and microenvironmental features across anatomically distinct sites within the same patient. To address this, we performed spatial transcriptomic profiling of CIS-containing tissue from four anatomically distinct sites within a single individual. Unsupervised clustering with marker-based annotation, integrated with metabolic inference, identified epithelial tumor populations alongside stromal, immune, and smooth muscle compartments. While key cellular states were conserved, their spatial organization and relative abundance varied by site. Metabolic analysis further revealed region-specific microenvironments shaped by local cellular architecture. These findings indicate that both cellular composition and metabolic activity are spatially structured. Collectively, these results demonstrate that CIS exhibits significant intra-patient heterogeneity not captured by single-site profiling. These findings require validation in larger cohorts but support multi-region sampling could help improve risk stratification, biomarker development, and prediction of response to intravesical therapies, with potential implications for more personalized treatment strategies.
ER -