Intraductal papillary mucinous neoplasm (IPMN) is a common pancreatic precancerous lesion, with increasing incidence in recent years. However, the mechanisms of IPMN progression into invasive cancer remain unclear. The mRNA expression data of IPMN/PAAD patients were extracted from the TCGA and GEO databases. First, based on GSE19650, we analyzed the molecular alterations, tumor stemness, immune landscape, and transcriptional regulation of IPMN progression. The results indicated that gene expression changed dramatically, specifically at the intraductal papillary-mucinous adenoma (IPMA) stage. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Kyoto Encyclopedia of Genes and Genomes (GSEA) pathway analyses showed that glycoprotein-related, cell cycle, and P53 pathways displayed the most significant changes during progression. With IPMN progression, tumor stemness increased continuously, and KRAS, ERBB3, RUNX1, and ELF3 are essential driver genes affecting tumor stemness. Motif analysis suggested that KLF4 may be a specific transcription factor that regulates gene expression in the IPMA stage, while MYB and MYBL1 control gene expression in the IPMC and invasive stages, respectively. Then, GSE19650 and GSE71729 transcriptome data were combined to perform the least absolute shrinkage and selection operator (LASSO) method and Cox regression analysis to develop an 11-gene prediction model (KCNK1, FHL2, LAMC2, CDCA7, GPX3, C7, VIP, HBA1, BTG2, MT1E, and LYVE1) to predict the prognosis of pancreatic cancer patients. The reliability of the model was validated in the GSE71729 and TCGA databases. Finally, 11 additional IPMN patients treated in our hospital were included, and the immune microenvironment changes during IPMN progression were analyzed by immunohistochemistry (IHC). IHC results suggest that Myeloid-derived suppressor cells (MDSCs) and macrophages may be key in the formation of immunosuppressive microenvironment of IPMN progression. Our study deepens our understanding of IPMN progression, especially the changes in the immune microenvironment. The findings of this work may contribute to the development of new therapeutic strategies for IPMN.

Since TNM staging has limitations for predicting post-operative outcomes and relapse, more effective prediction tools need to be researched and developed. Lymphovascular invasion, LVI, as a histopathological feature, has been widely shown to have a correlation with poor prognosis and early recurrence of lung adenocarcinoma (LUAD). However, LVI assessment is limited by subjective bias, and therefore its efficacy in practical clinical application needs further clarification. The aim of this study was to formulate a new signature based on LVI-related genes to predict prognosis and recurrence in patients with lung adenocarcinoma. Clinicopathological information, gene sequencing data and whole slide images (WSIs) of LUAD patients were downloaded from the Cancer Genome Atlas (TCGA) databases. LVI statue were evaluated by professional pathologists, and then the differentially expressed genes (LVI DEGs) associated with LVI were screened. The least absolute shrinkage and selection operator (LASSO) and Step Cox regression models were used to construct LVI-associated risk scores (LVRS), including PAQR4, ARGHEF6, CKS1B, CFTR and SEC14L4. The validity of the LVRS score was evaluated on multiple external datasets and our JSSZL cohort dataset. Using LVRS scores and clinical information, nomogram were constructed for use by clinicians. In addition, we further explored the relationship between LVRS score and clinicopathological features, immune infiltration, tumor mutational load, and immunotherapy response, and confirmed the expression of key genes in LVRS score in lung adenocarcinoma tissues using qRT-PCR and immunohistochemistry (IHC) techniques. Based on the LVRS, patients could be classified into high-LVRS and low-LVRS groups. It was found that OS and PFS were significantly worse in the high-LVRS group than in the low-LVRS group (p < 0.001). By ROC curve analysis, it could be found that the nomogram combining LVRS and clinical information could accurately predict the prognosis of LUAD patients with the area under the curve of 1,3,5-year survival rate could reach 0.754, 0.741 and 0.735. The results of univariate and multivariate analysis showed that LVRS was an independent prognostic factor. At the same time, there were significant differences in the mutation profiles and immune microenvironment between the high-LVRS and low-LVRS groups, with the high-LVRS group having a significantly higher mutation rate than the low-LVRS group and exhibiting immunological "cold" features. By the experimental results, higher expression levels of PAQR4 and CKS1B were found in LUAD tissues, while lower expression levels of ARGHEF6, CFTR and SEC14L4 were observed. The LVRS established in this study serves as a valid tool to predict the prognosis and recurrence status of lung adenocarcinoma patients and has a predictive effect on the response to postoperative treatment. The establishment of LVRS may offer some theoretical support to clinical treatment strategies for patients with lung adenocarcinoma following surgical intervention.

Lung adenocarcinoma (LUAD) remains a major cause of cancer-related mortality, and there are currently few reliable biomarkers available for accurate prognosis and effective targeted therapy. Accumulating evidence demonstrates that senescent cells play an important role in tumor progression and immune evasion; nevertheless, their specific contribution to LUAD pathogenesis has not yet been fully elucidated. Accordingly, a five-gene senescence-related risk model comprising FGF2, GAPDH, CCNA2, ENO1, and DKK1 was established using the Least Absolute Shrinkage and Selection Operator regression applied to bulk RNA sequencing data obtained from The Cancer Genome Atlas (TCGA). Patients stratified as high risk by this model exhibited significantly poorer overall survival and progression-free survival, accompanied by marked activation of pathways associated with immune infiltration, epithelial–mesenchymal transition, and extracellular matrix remodeling. Integrative single-cell RNA sequencing analysis further revealed a distinct epithelial subpopulation (E9) defined by preferential activation of the senescence-associated gene DKK1. This subpopulation, which emerged from integrative single-cell transcriptomic analysis, exhibited pronounced senescence-associated characteristics, significantly increased cellular stemness, and extensive intercellular communication capacity, and uniquely expressed COL17A1 together with transcriptional programs that were strongly associated with epidermal development. Pseudotime analyses consistently positioned E9 cells at an early stage of tumor evolution. At the functional level, DKK1 contributed to senescence-associated phenotypic features, thereby promoting tumor cell migration and metastatic potential. From a clinical perspective, patients with concurrent high levels of COL17A1 and DKK1 expression experienced significantly worse clinical outcomes. Collectively, these findings identify a senescence-driven epithelial subpopulation that contributes to LUAD progression via DKK1-mediated activation of aging-related pathways and highlight DKK1 as a potential therapeutic target.

Background: Ginsenoside Rb2 has demonstrated antitumor activity in multiple malignancies, yet its role in cervical cancer and the underlying mechanism remain unclear. This study investigated the effects of Rb2 on cervical cancer progression and explored whether metabolic reprogramming contributes to PD-L1 regulation. Methods: Cell proliferation, migration, invasion, glycolytic activity, lactate production, histone lactylation, and PD-L1 expression were evaluated in cervical cancer cells using CCK-8, EdU, colony formation, wound-healing, Transwell, Seahorse analysis, RT-qPCR, western blotting, flow cytometry, and ChIP-qPCR. LDHA regulation was examined by protein and mRNA stability assays, pharmacological inhibition, lysosome immunoprecipitation, gain- and loss-of-function studies, co-immunoprecipitation, molecular docking, and biotinylated Rb2 pull-down assays. T-cell function was assessed by Jurkat T-cell–tumor cell co-culture and IL-2 ELISA. Xenograft models and clinical samples were used for validation. Results: Rb2 significantly inhibited cervical cancer cell proliferation, migration, invasion, and xenograft tumor growth, reducing HeLa and SiHa cell viability by approximately 23.4% and 25.7%, respectively. Rb2 selectively downregulated PD-L1 and suppressed glycolysis and lactate production, with reduced H3K18la/H4K12la lactylation at the PD-L1 promoter. LDHA was the primary glycolytic enzyme reduced by Rb2, without changes in its mRNA. Rb2 decreased LDHA protein stability and promoted its autophagy-lysosome-dependent degradation, with p62 required and the p62–LDHA interaction enhanced by Rb2. Rb2-pretreated tumor cells restored IL-2 production by co-cultured Jurkat T cells, whereas LDHA overexpression reversed this effect. LDHA overexpression partially rescued Rb2’s effects, and LDHA correlated positively with PD-L1 in cervical cancer tissues. Conclusions: Rb2 suppresses cervical cancer progression by promoting p62-dependent autophagic degradation of LDHA, thereby inhibiting glycolysis-associated H3K18la and PD-L1 transcription. These findings reveal a p62/LDHA/H3K18la/PD-L1 signaling axis through which Rb2 exerts its antitumor effects.