Abstract 6289: SCplot: an interactive platform for single-cell RNA-seq analysis in colorectal cancer

Background: Single-cell RNA sequencing (scRNA-seq) is a powerful tool for detailed characterization of the processes driving cancer and the interactions between different cell types in neoplastic tissues. However, the large volume of resulting data and the complexity of downstream analytic software and statistical approaches can make it challenging for researchers and clinicians without bioinformatics expertise to extract meaningful insights. To address this need, we developed SCplot, an integrated database and interactive online analysis platform for single-cell colorectal cancer (CRC) RNA-seq data. Methods: SCplot allows users without prior programming experience to explore an integrated single-cell dataset. We compiled eight publicly available raw scRNA-seq CRC datasets from GEO, performed quality control and normalization, combined the datasets, and annotated the cell types. The complete database includes among others 102,195 cancer cells, 19,942 vascular endothelial cells, 25,027 cancer associated fibroblasts, and 7,438 smooth muscle cells. The platform available at www.scplot.com enables downstream analysis features, including differential gene expression, volcano plots, expression heatmaps, and gene-gene correlation analyses across various cell types. Results: To demonstrate SCplot’s utility, we investigated correlations of VEGFA between cancer cells and vascular endothelial cells, cancer-associated fibroblasts, and smooth muscle cells. Notably, the transcription factor JUND was among the top five positively correlated genes to VEGFA in cancer cells in each of these cell types (Pearson’s correlation coefficient: 0.27-0.37, p<0.001). Other strongly positively correlated genes included those involved in cell signaling (TCF4, CALCRL, GNAS) and angiogenesis (MCAM, COL4A1, SOX18). Conversely, negatively correlated genes were associated with immunoregulation (B2G, FKBP2), iron metabolism (FTL, FTH1), apoptosis (SOD1), and cell differentiation (PPDPF). Conclusions: These findings provide new insights into VEGF-driven interactions in CRC, revealing potential therapeutic targets to modulate the tumor microenvironment and disrupt angiogenesis. The SCplot platform can be mined to uncover, visualize, and validate cellular interactions in CRC. Citation Format: William Kothalawala, Balazs Gyorffy. SCplot: an interactive platform for single-cell RNA-seq analysis in colorectal cancer [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 6289.