Background: The incidence of sporadic young-onset colorectal cancer (yCRC) is increasing. Compared with old-onset colorectal cancer (oCRC), yCRC has different clinical and molecular characteristics. However, the difference in the tumor microenvironment (TME) between yCRC and oCRC remains unclear. Methods: Fourteen untreated CRC tumor samples were subjected to single-cell RNA sequencing analysis. Results: B cells and naïve T cells are enriched in yCRC, while effector T cells and plasma cells are enriched in oCRC. Effector T cells of yCRC show decreased interferon-gamma response and proliferative activity; meanwhile, Treg cells in yCRC show stronger oxidative phosphorylation and TGF-β signaling than that in oCRC. The down-regulated immune response of T cells in yCRC may be regulated by immune and malignant cells, as we observed a downregulation of antigen presentation and immune activations in B cells, dendritic cells, and macrophages. Finally, we identified malignant cells in yCRC and oCRC with high heterogeneity and revealed their interactions with immune cells in the TME. Conclusions: Our data reveal significant differences of TME between yCRC and oCRC, of which the TME of yCRC is more immunosuppressive than oCRC. Malignant cells play an essential role in the formation of the suppressive tumor immune microenvironment.

Background: Overweight and obesity are established risk factors for various types of cancers including colorectal cancer (CRC). However the underlying molecular mechanisms remain unclear. An in-depth understanding of the oncologic characteristics of overweight and obese CRC at the single-cell level can provide valuable insights for the development of more effective treatment strategies for CRC. Methods: We conducted single-cell RNA sequencing (scRNA-seq) analysis on tumor and adjacent normal colorectal samples from 15 overweight/obese and 15 normal-weight CRC patients. Immunological and metabolic differences between overweight/obese CRC and non-obese CRC were characterized. Results: We obtained single-cell transcriptomics data from a total of 192,785 cells across all samples. By evaluating marker gene expression patterns, we annotated nine main cell types in the CRC ecosystem. Specifically, we found that the cytotoxic function of effector T cells and NK cells was impaired in overweight/obese CRC compared with non-obese CRC, relating to its metabolic dysregulation. CD4⁺T cells in overweight/obese CRC exhibited higher expression of immune checkpoint molecules. The antigen-presenting ability of DCs and B cells is down-regulated in overweight/obese CRC, which may further aggravate the immunosuppression of overweight/obese CRC. Additionally, dysfunctional stromal cells were identified, potentially promoting invasion and metastasis in overweight/obese CRC. Furthermore, we discovered the up-regulated metabolism of glycolysis and lipids of tumor cells in overweight/obese CRC, which may impact the metabolism and function of immune cells. We also identified inhibitory interactions between tumor cells and T cells in overweight/obese CRC. Conclusions: The study demonstrated that overweight/obese CRC has a more immunosuppressive microenvironment and distinct metabolic reprogramming characterized by increased of glycolysis and lipid metabolism. These findings may have implications for the development of novel therapeutic strategies for overweight/obese CRC patients.

Background: Colorectal cancer (CRC), the third most common malignancy worldwide, exhibits notable sex-specific prognostic differences, yet the underlying biological mechanisms remain poorly understood. Methods: In this study, we conducted single-cell sequencing on 32 CRC samples, followed by pathway enrichment analysis, cell-cell interaction analysis, and transcription factor analysis. The co-expression of GZMB and the transcription factor EOMES in CD8+ T cells was detected using multiplex immunohistochemistry. Western blot and TUNEL assays were employed to validate estrogen-induced apoptosis in CRC cell lines. Results: After quality control, we obtained a total of 167,437 cells across 9 cell types from all samples. Specifically, our analysis revealed sex-based variations in cellular composition, functionality, and intercellular interactions within CRC. Notably, female CRC samples exhibited significant positive correlation between estrogen signaling pathway activation and apoptotic activity, with validation through Western blot and TUNEL assays confirming estrogen-mediated apoptosis induction in CRC cell lines. The immune response was notably enhanced in female CRC, with CD8+ T cells showing increased expression of the EOMES gene regulatory network, thereby boosting T cell immunity. Moreover, B cells of female CRC demonstrated improved capabilities in antigen-presenting and MHC-I interactions with T cells. Additionally, Macro_CCL4 cells engaged in sex-specific TNF-TNFRSF1B crosstalk with CD8+ T cells, potentially leading to enhanced antitumor immunity in females. Conversely, CAF_MMP11 cells exhibiting a myofibroblastic CAF phenotype interacted with malignant epithelial cells via signaling pathways such as THBS, MK, and FN1, likely promoting CRC progression. Conclusions: Our research highlights the distinct immunological and hormonal responses in CRC by sex, which may explain the observed prognostic disparities. These findings may offer additional further biological insights for targeted therapies in CRC.

The integration of cell transcriptomics and spatial coordinates to organize differentiation trajectories remains a challenge. Here we introduce spaTrack, a trajectory inference method using optimal transport to incorporate both transcriptomics and distance of spatial transcriptomics sequencing data into transition costs. spaTrack could construct fine spatial trajectories reflecting the true differentiation topology, as well as trace cell dynamics across multiple samples with temporal intervals. To capture the dynamic drivers, spaTrack models the cell fate as a function of expression profile along temporal intervals driven by transcription factors. Applying spaTrack, we successfully disentangle spatiotemporal trajectories of axolotl telencephalon regeneration and mouse midbrain development. Furthermore, we uncover diverse malignant lineages expanding in a primary tumor. One of the lineages with upregulated extracellular matrix organization implants to the metastatic site and subsequently colonizes to a secondary tumor. Overall, spaTrack greatly facilitates trajectory inference from spatial transcriptomics, providing insights in cell differentiation of broad areas.