The microbiota is present in many parts of the human body and plays essential roles. The most typical case is the occurrence and development of cancer. Pancreatic cancer (PC), one of the most aggressive and lethal types of cancer, has recently attracted the attention of researchers. Recent research has revealed that the microbiota regulates PC carcinogenesis via an altered immune response. Specifically, the microbiota, in several sites, including the oral cavity, gastrointestinal tract, and pancreatic tissue, along with the numerous small molecules and metabolites it produces, influences cancer progression and treatment by activating oncogenic signaling, enhancing oncogenic metabolic pathways, altering cancer cell proliferation, and triggering chronic inflammation that suppresses tumor immunity. Diagnostics and treatments based on or in combination with the microbiota offer novel insights to improve efficiency compared with existing therapies.

The microRNAs (miRNAs) are potent regulators of tumorigenesis in various cancers, especially pancreatic cancer. The abnormal expression of miRNAs can be observed in tumor cells. Noteworthy, miRNAs could be transferred by exosomes as small extracellular vesicles in regulation of carcinogenesis. This research focused on exploring the roles and mechanisms of exosomal miR-484, derived from human bone marrow mesenchymal stem cells (hBMSCs), in the context of molecular interactions and regulation of mitochondrial metabolism. Exosomes were isolated for the examination of miR-484 expression. The impacts of hBMSCs-derived exosomal miR-484 on pancreatic cancer cells were studied using various assays. Evaluation of mitochondrial function and metabolism was performed. Wnt/MAPK pathway-related protein expression was assessed, and an in vivo tumor xenograft model was utilized to examine the functions. Our findings demonstrated a decreased miR-484 expression in pancreatic cancer cells. However, hBMSCs-derived exosomal miR-484 inhibited the proliferation and migration of these cells, while inducing apoptosis. Moreover, miR-484 led to an upsurge in reactive oxygen species production, a decrease in ATP levels, and a disruption in mitochondrial metabolism. In vivo analyses showed that hBMSCs-derived exosomal miR-484 lessened tumor size and weight, while also suppressing the expression of mitochondrial biomarkers. Further, there was a decline in β-catenin and p-p38 protein levels both in vitro and in vivo. The addition of LiCl restored the disrupted mitochondrial metabolism. Conclusively, our results suggest that hBMSCs-derived exosomal miR-484 mitigates the malignant transformation and mitochondrial metabolism of pancreatic cancer by deactivating the Wnt/MAPK pathway.

Background: Preoperative evaluation of lymph node (LN) state is of pivotal significance for informing therapeutic decisions in gastric cancer (GC) patients. However, there are no non-invasive methods that can be used to preoperatively identify such status. We aimed at developing a genomic biosignature based model to predict the possibility of LN metastasis in GC patients. Methods: We used the RNA profile retrieving strategy and performed RNA expression profiling in a large GC cohort (GSE62254, n = 300) from Gene Expression Ominus (GEO). In the exploratory stage, 300 GC patients from GSE62254 were involved and the differentially expressed RNAs (DERs) for LN-status were determined using the R software. GC samples in GSE62254 were randomly allocated into a learning set (n = 210) and a verification set (n = 90). By using the Least absolute shrinkage and selection operator (LASSO) regression approach, a set of 23-RNA signatures were established and the signature based nomogram was subsequently built for distinguishing LN condition. The diagnostic efficiency, as well as the clinical performance of this model were assessed using the decision curve analysis (DCA). Metascape was used for bioinformatic analysis of the DERs. Results: Based on the genomic signature, we established a nomogram that robustly distinguished LN status in the learning (AUC = 0.916, 95% CI 0.833–0.999) and verification sets (AUC = 0.775, 95% CI 0.647–0.903). DCA demonstrated the clinical value of this nomogram. Functional enrichment analysis of the DERs was performed using bioinformatics methods which revealed that these DERs were involved in several lymphangiogenesis-correlated cascades. Conclusions: In this study, we present a genomic signature based nomogram that integrates the 23-RNA biosignature based scores and Lauren classification. This model can be utilized to estimate the probability of LN metastasis with good performance in GC. The functional analysis of the DERs reveals the prospective biogenesis of LN metastasis in GC.

Background/Aims: Hepatocellular carcinoma (HCC) represents a primary liver malignancy with a multifaceted molecular landscape. The interplay between liquid–liquid phase separation (LLPS) and ferroptosis—a regulated form of cell death—has garnered interest in tumorigenesis. However, the precise role of LLPS and ferroptosis-related genes in HCC progression and prognosis remains obscure. Unraveling this connection could pave the way for innovative diagnosis and therapeutic strategies. Materials and Methods: The differentially expressed genes (DEGs) were identified based on 3 GEO datasets, followed by overlapping with LLPS-related and ferroptosis-related genes. Based on central hub genes, a diagnostic model was developed through LASSO regression and validated using KM survival analysis and real-time quantitative polymerase chain reaction (RT-qPCR). Then the effects of NRAS on the development of HCC and ferroptosis were also detected. Results: We identified 24 DEGs overlapping among HCC-specific, LLPS, and ferroptosis-related genes. A diagnostic model, centered on 5 hub genes, was developed and 7validated. Lower expression of these genes corresponded with enhanced patient survival rates, and they were distinctly overexpressed in HCC cells. NRAS downregulation significantly inhibited HepG2 cell proliferation and migration (P < .01). Fe2+ content and ROS levels were both significantly increased in the si-NRAS group when compared to those in the si-NC group (P < .01), while opposite results were observed for the protein level of GPX4 and GSH content. Conclusion: The diagnostic model with 5 hub genes (EZH2, HSPB1, NRAS, RPL8, and SUV39H1) emerges as a potential innovative tool for the diagnosis of HCC. NRAS promotes the carcinogenesis of HCC cells and inhibits ferroptosis. Cite this article as: Chen W, Zhu T, Pu X, et al. Machine learning diagnostic model for hepatocellular carcinoma based on liquidliquid phase separation and ferroptosis-related genes. Turk J Gastroenterol. 2025;36(2):89-99.