Hepatic metastasis (HM) and lymph node metastasis in pancreatic ductal adenocarcinoma (PDAC) are associated with worse overall survival, largely due to the immunosuppressive microenvironment. However, the key immunosuppressive cells within this microenvironment remain inadequately defined. This study aimed to identify the cells contributing to HM and lymph node metastasis in PDAC and to investigate their regulatory mechanisms.

Single-cell RNA sequencing was used to profile the tumor microenvironment in HM, lymph node-negative, and lymph node-positive (LNP) PDAC tissues. Bioinformatic analyses revealed subtypes of immunosuppressive myeloid-derived suppressor cells (MDSCs). Immunofluorescence and flow cytometry were performed to detect the distribution and proportion of interleukin-1 receptor antagonist (IL1RA+) MDSCs. The immunosuppressive and pro-tumorigenic functions of IL1RA+ MDSCs were analyzed using enzyme-linked immunosorbent assay, quantitative reverse transcription polymerase chain reaction, Western blotting, and Transwell assays. Patient-derived xenograft mouse models were employed to validate the role of IL1RA+ MDSCs in vivo.

Polymorphonuclear-MDSCs were found to be recruited to metastatic PDAC tissues. Among these, IL1RA+ MDSCs were enriched in HM/LNP tissues and correlated with poorer prognosis. IL1RA+ MDSCs promoted M2 macrophage polarization and suppressed the activity of natural killer cells and cytotoxic T cells. Furthermore, IL1RA+ MDSCs accelerated PDAC migration and progression by upregulating epithelial–mesenchymal transition-related proteins in both in vitro and in vivo models.

IL1RA+ MDSCs represent a key immunosuppressive and pro-tumorigenic subtype in HM/LNP PDAC, providing a solid theoretical basis for prognostic prediction and the development of immunotherapeutic strategies targeting these cells in HM/LNP PDAC.

Cell cycle checkpoint-related genes (CCCRGs) are implicated in the development and progression of hepatocellular carcinoma (HCC). However, their precise roles and underlying mechanisms remain insufficiently characterized and require further investigation. This study aimed to explore the prognostic significance of CCCRGs in HCC, and to investigate the mechanism by which they promote the progression of HCC.

HCC datasets from The Cancer Genome Atlas and International Cancer Genome Consortium were analyzed to identify hub genes. A prognostic model was constructed and validated using Kaplan–Meier analysis, nomogram, calibration curves, decision curve analysis, and receiver operating characteristic analysis. Immune infiltration patterns were assessed using single sample gene set enrichment analysis, while pathway activities were evaluated via gene set variation analysis. Single-cell RNA sequencing data from GSE149614 were analyzed with Seurat and CellChat to investigate cell–cell communication. Patient-derived HCC specimens were examined through immunohistological evaluation, HCC cell lines were used for in vitro functional assays, and in vivo tumor growth was assessed through animal experiments.

CCCRGs showed significant associations with prognosis, malignant biological behavior, and immune responses in HCC. Centromere protein (CENP) I was identified as a critical hub gene that markedly promoted HCC proliferation, metastasis, and epithelial–mesenchymal transition, while inhibiting apoptosis. Mechanistically, CENPI suppressed YAP phosphorylation, enhancing its nuclear translocation and thereby driving malignant progression. Additionally, CENPI impaired immune effector cell infiltration, likely by disrupting tumor antigen presentation and chemokine-mediated CD8+ T cell chemotaxis, thereby promoting immune escape.

This study underscores the prognostic significance of CCCRGs in HCC and identifies CENPI as a key driver of tumor progression through the Hippo pathway. Furthermore, it reveals CENPI’s role in promoting immune escape, suggesting novel therapeutic targets for HCC treatment.

Organoids are derived from self-organizing stem cells and form three-dimensional structures that are structurally and functionally similar to in vivo tissues. With the ability to replicate the in vivo microenvironment and maintain genetic stability, organoids have become a powerful tool for elucidating developmental mechanisms, accurately modeling disease processes, and efficiently screening drug candidates, and have also demonstrated significant value in the field of traditional Chinese medicine (TCM)-including applications in screening active components of TCM, studying TCM pharmacodynamic mechanisms, evaluating TCM safety, and verifying the effects of traditional non-pharmacological therapies such as acupuncture and yoga. Organoids can be cultured using air-liquid interface systems, bioreactors, and vascularization techniques. They are widely used in drug screening, disease modeling, precision medicine, and toxicity assessment. However, current limitations include high costs, difficulty in accurately replicating the microenvironment, and ethical concerns. In this review, we systematically retrieve, synthesize, and analyze relevant literature to elucidate the culture methods of organoid technology, its diverse applications across various fields, and the challenges it faces. In the future, integration with artificial intelligence may provide new insights and strategies for drug development and disease research and the modernization of TCM.