Abstract 2068: Mapping the spatial whole transcriptome from normal to tumor tissue in renal clear cell carcinoma: tumorigenesis and microenvironmental shifts at single-cell resolution

Abstract Renal clear cell carcinoma (ccRCC) develops through significant molecular and spatial reprogramming, transforming normal kidney tissue into a malignant state and reshaping the tumor microenvironment. To investigate the transition from normal to cancerous tissue, we utilized the CosMx® Whole Transcriptome (WTX) panel to perform high-resolution spatial transcriptomic imaging of FFPE sections containing ccRCC and adjacent normal kidney. H&E staining on the same tissue sections enabled direct correlation of molecular profiles with histopathological features, uncovering novel insights into tumorigenesis. FFPE tissue sections comprising equal parts ccRCC and adjacent normal kidney tissue underwent CosMx WTX imaging to analyze approximately 19, 000 genes at single-cell resolution. The same sections were stained with H&E, providing histopathological context for tumor boundaries, tumor-normal interfaces, and regions of vascularization or necrosis. Custom software aligned transcriptomic and histopathological images, enabling the integration of molecular and morphological data for downstream analyses and AI model development. CosMx WTX detected thousands of transcripts per cell with exceptional sensitivity and accuracy. Spatial transcriptomics revealed distinct transcriptional programs and cell-type-specific changes across normal and tumor regions. Ligand-receptor analysis identified critical interactions driving tumorigenesis, while comparative analysis between transcriptome profile and H&E stain highlighted molecular shifts in tumor-adjacent normal areas, preserving renal tubule morphology but exhibiting subtle transcriptomic alterations. The tumor-normal interface displayed unique gene expression signatures, identifying spatially restricted therapeutic targets. This study presents a high-resolution spatial atlas of ccRCC, detailing molecular and cellular transitions from normal to tumor tissue. Integrating CosMx WTX with H&E-guided annotation not only identifies the tumor-normal interface as critical for understanding progression but also highlights the potential for AI-powered diagnostic tools. By linking transcriptomic signatures to routine histopathological images, this work sets the stage for future advancements in automated cell typing and transcriptome prediction, transforming research in clinical workflows and precision oncology. -Bruker Confidential- Citation Format: Shanshan He, Liang Zhang, Michael Patrick, Sierra McKenzie, Haiyan Zhai, Christine Kang, Michael Deryck Rhodes, Joseph Beechem. Mapping the spatial whole transcriptome from normal to tumor tissue in renal clear cell carcinoma: tumorigenesis and microenvironmental shifts at single-cell resolution [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 2068.

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Journal
Cancer Research
Published
2025-04-21
DOI
https://doi.org/10.1158/1538-7445.am2025-2068
Primary Topic
Single-cell and spatial transcriptomics
Type
article
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article

Abstract 2068: Mapping the spatial whole transcriptome from normal to tumor tissue in renal clear cell carcinoma: tumorigenesis and microenvironmental shifts at single-cell resolution

Michael Patrick, Christine Kang, Shanshan He, Joseph Beechem et al.
Cancer Research
Single-cell and spatial transcriptomics
article

Abstract 2068: Mapping the spatial whole transcriptome from normal to tumor tissue in renal clear cell carcinoma: tumorigenesis and microenvironmental shifts at single-cell resolution

Michael Patrick, Christine Kang, Shanshan He, Joseph Beechem, Liang Zhang, Shaun McKenzie, Michael Rhodes, Haiyan Zhai
article en

Abstract

Abstract Renal clear cell carcinoma (ccRCC) develops through significant molecular and spatial reprogramming, transforming normal kidney tissue into a malignant state and reshaping the tumor microenvironment. To investigate the transition from normal to cancerous tissue, we utilized the CosMx® Whole Transcriptome (WTX) panel to perform high-resolution spatial transcriptomic imaging of FFPE sections containing ccRCC and adjacent normal kidney. H&E staining on the same tissue sections enabled direct correlation of molecular profiles with histopathological features, uncovering novel insights into tumorigenesis. FFPE tissue sections comprising equal parts ccRCC and adjacent normal kidney tissue underwent CosMx WTX imaging to analyze approximately 19, 000 genes at single-cell resolution. The same sections were stained with H&E, providing histopathological context for tumor boundaries, tumor-normal interfaces, and regions of vascularization or necrosis. Custom software aligned transcriptomic and histopathological images, enabling the integration of molecular and morphological data for downstream analyses and AI model development. CosMx WTX detected thousands of transcripts per cell with exceptional sensitivity and accuracy. Spatial transcriptomics revealed distinct transcriptional programs and cell-type-specific changes across normal and tumor regions. Ligand-receptor analysis identified critical interactions driving tumorigenesis, while comparative analysis between transcriptome profile and H&E stain highlighted molecular shifts in tumor-adjacent normal areas, preserving renal tubule morphology but exhibiting subtle transcriptomic alterations. The tumor-normal interface displayed unique gene expression signatures, identifying spatially restricted therapeutic targets. This study presents a high-resolution spatial atlas of ccRCC, detailing molecular and cellular transitions from normal to tumor tissue. Integrating CosMx WTX with H&E-guided annotation not only identifies the tumor-normal interface as critical for understanding progression but also highlights the potential for AI-powered diagnostic tools. By linking transcriptomic signatures to routine histopathological images, this work sets the stage for future advancements in automated cell typing and transcriptome prediction, transforming research in clinical workflows and precision oncology. -Bruker Confidential- Citation Format: Shanshan He, Liang Zhang, Michael Patrick, Sierra McKenzie, Haiyan Zhai, Christine Kang, Michael Deryck Rhodes, Joseph Beechem. Mapping the spatial whole transcriptome from normal to tumor tissue in renal clear cell carcinoma: tumorigenesis and microenvironmental shifts at single-cell resolution [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 2068.

Cancer ResearchVol. 85(8_Supplement_1)
Bruker (United States) (US)
Openalex Percentile: Top 93%
Single-cell and spatial transcriptomics
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