Spatial transcriptome and single-cell reveal the role of nucleotide metabolism in colorectal cancer progression and tumor microenvironment

Abstract

Abstract Background The intricacies of nucleotide metabolism within tumor cells specific to colorectal cancer (CRC) remain insufficiently characterized. A nuanced examination of particular tumor clusters and their dynamic interplay with the tumor microenvironment (TME) may yield profound insights into these therapeutically auspicious communicative networks. Methods By integrating ten types of single-cell enrichment scoring methods, we carried out enrichment analysis on CRC cell types, which was validated through four additional single-cell cohorts. Groups of tumor cells were determined using the average values of the scores. Using cellphonedb, monocle, inferCNV, SCENIC, and Cytotrace, functional analyses were performed. Utilizing the RCTD approach, single-cell groupings were mapped onto spatial transcriptomics, analyzing cell dependency and pathway activity to distinguish between tumor cell subtypes. Differential expression analysis identified core genes in nucleotide metabolism, with single-cell and spatial transcriptomics analyses elucidating the function of these genes in tumor cells and the immune microenvironment. Prognostic models were developed from bulk transcriptome cohorts to forecast responses to immune therapy. Laboratory experiments were conducted to verify the biological function of the core gene. Results Nucleotide metabolism is significantly elevated in tumor cells, dividing them into two groups: NUhighepi and NUlowepi. The phenotype NUhighepi was discerned to exhibit pronounced malignant attributes. Utilizing the analytical tool stlearn for cell-to-cell communication assessment, it was ascertained that NUhighepi engages in intimate interactions with fibroblasts. Corroborating this observation, spatial transcriptome cell interaction assessment through MISTy unveiled a particular reliance of NUhighepi on fibroblasts. Subsequently, we pinpointed NME1, a key gene in nucleotide metabolism, affirming its role in thwarting metastasis via in vitro examination. Utilizing multiple machine learning algorithms, a stable prognostic model (NRS) has been developed, capable of predicting survival and responses to immune therapy. In addition, targeted drugs have been identified for both high and low scoring groups. Laboratory experiments have revealed that NME1 can inhibit the proliferation and invasion of CRC tumor cells. Conclusion Our study elucidates the potential pro-tumor mechanism of NUhighepi and the role of NME1 in inhibiting metastasis, further deepening the understanding of the role of nucleotide metabolism in colorectal cancer, and providing valuable targets for disrupting its properties.