Integration of clinical and transcriptomics reveals programming of the lipid metabolism in gastric cancer

LncRNA RPARP-AS1 promotes the progression of osteosarcoma cells through regulating lipid metabolism

Osteosarcoma (OS) is a highly malignant tumor, and its dysregulated lipid metabolism is associated with tumorigenesis and unfavorable prognosis. Interestingly, long noncoding RNAs (lncRNAs) have emerged as pivotal regulators of lipid metabolism, exerting notable impacts on tumor proliferation. Nevertheless, the involvement of RPARP-AS1, a novel lipid metabolism-associated lncRNA, remains unexplored in the context of OS. This study aims to identify functionally relevant lncRNAs impacting OS proliferation and lipid metabolism and seeks to shed light on the upstream regulatory mechanisms governing lipogenic enzyme activity. Based on comprehensive bioinformatic analysis and the establishment of a risk model, we identified seven lncRNAs significantly associated with clinical characteristics and lipid metabolism-related genes in patients with OS. Among these, RPARP-AS1 was selected for in-depth investigation regarding its roles in OS proliferation and lipid metabolism. Experimental techniques including RT-qPCR, Western blot, cell viability assay, assessment, and quantification of free fatty acids (FFAs) and triglycerides (TGs) were utilized to elucidate the functional significance of RPARP-AS1 in OS cells and validate its effects on lipid metabolism. Manipulation of RPARP-AS1 expression via ectopic expression or siRNA-mediated knockdown led to alterations in epithelial-mesenchymal transition (EMT) and expression of apoptosis-associated proteins, thereby influencing OS cell proliferation and apoptosis. Mechanistically, RPARP-AS1 was found to augment the expression of key lipogenic enzymes (FABP4, MAGL, and SCD1) and potentially modulate the Akt/mTOR pathway, thereby contributing to lipid metabolism (involving alterations in FFA and TG levels) in OS cells. Collectively, our findings establish RPARP-AS1 as a novel oncogene in OS cells and suggest its role in fostering tumor growth through the enhancement of lipid metabolism.

Integrative models of histopathological images and multi-omics data predict prognosis in endometrial carcinoma

Objective

This study aimed to predict the molecular features of endometrial carcinoma (EC) and the overall survival (OS) of EC patients using histopathological imaging.

Methods

The patients from The Cancer Genome Atlas (TCGA) were separated into the training set (n = 215) and test set (n = 214) in proportion of 1:1. By analyzing quantitative histological image features and setting up random forest model verified by cross-validation, we constructed prognostic models for OS. The model performance is evaluated with the time-dependent receiver operating characteristics (AUC) over the test set.

Results

Prognostic models based on histopathological imaging features (HIF) predicted OS in the test set (5-year AUC = 0.803). The performance of combining histopathology and omics transcends that of genomics, transcriptomics, or proteomics alone. Additionally, multi-dimensional omics data, including HIF, genomics, transcriptomics, and proteomics, attained the largest AUCs of 0.866, 0.869, and 0.856 at years 1, 3, and 5, respectively, showcasing the highest discrepancy in survival (HR = 18.347, 95% CI [11.09-25.65], p < 0.001).

Conclusions

The results of this experiment indicated that the complementary features of HIF could improve the prognostic performance of EC patients. Moreover, the integration of HIF and multi-dimensional omics data might ameliorate survival prediction and risk stratification in clinical practice.

Helicobacter pylori promotes gastric intestinal metaplasia through activation of IRF3-mediated kynurenine pathway

BACKGROUND

Metabolic reprogramming is a critical event for cell fate and function, making it an attractive target for clinical therapy. The function of metabolic reprogramming in Helicobacter pylori (H. pylori)-infected gastric intestinal metaplasia remained to be identified.

METHODS

Xanthurenic acid (XA) was measured in gastric cancer cells treated with H. pylori or H. pylori virulence factor, respectively, and qPCR and WB were performed to detect CDX2 and key metabolic enzymes expression. A subcellular fractionation approach, luciferase and ChIP combined with immunofluorescence were applied to reveal the mechanism underlying H. pylori mediated kynurenine pathway in intestinal metaplasia in vivo and in vitro.

RESULTS

Herein, we, for the first time, demonstrated that H. pylori contributed to gastric intestinal metaplasia characterized by enhanced Caudal-related homeobox transcription factor-2 (CDX2) and mucin2 (MUC2) expression, which was attributed to activation of kynurenine pathway. H. pylori promoted kynurenine aminotransferase II (KAT2)-mediated kynurenine pathway of tryptophan metabolism, leading to XA production, which further induced CDX2 expression in gastric epithelial cells. Mechanically, H. pylori activated cyclic guanylate adenylate synthase (cGAS)-interferon regulatory factor 3 (IRF3) pathway in gastric epithelial cells, leading to enhance IRF3 nuclear translocation and the binding of IRF3 to KAT2 promoter. Inhibition of KAT2 could significantly reverse the effect of H. pylori on CDX2 expression. Also, the rescue phenomenon was observed in gastric epithelial cells treated with H. pylori after IRF3 inhibition in vitro and in vivo. Most importantly, phospho-IRF3 was confirmed to be a clinical positive relationship with CDX2.

CONCLUSION

These finding suggested H. pylori contributed to gastric intestinal metaplasia through KAT2-mediated kynurenine pathway of tryptophan metabolism via cGAS-IRF3 signaling, targeting the kynurenine pathway could be a promising strategy to prevent gastric intestinal metaplasia caused by H. pylori infection. Video Abstract.

Bioinformatic analysis of underlying mechanisms of Kawasaki disease via Weighted Gene Correlation Network Analysis (WGCNA) and the Least Absolute Shrinkage and Selection Operator method (LASSO) regression model

BACKGROUND

Kawasaki disease (KD) is a febrile systemic vasculitis involvingchildren younger than five years old. However, the specific biomarkers and precise mechanisms of this disease are not fully understood, which can delay the best treatment time, hence, this study aimed to detect the potential biomarkers and pathophysiological process of KD through bioinformatic analysis.

METHODS

The Gene Expression Omnibus database (GEO) was the source of the RNA sequencing data from KD patients. Differential expressed genes (DEGs) were screened between KD patients and healthy controls (HCs) with the "limma" R package. Weighted gene correlation network analysis (WGCNA) was performed to discover the most corresponding module and hub genes of KD. The node genes were obtained by the combination of the least absolute shrinkage and selection operator (LASSO) regression model with the top 5 genes from five algorithms in CytoHubba, which were further validated with the receiver operating characteristic curve (ROC curve). CIBERSORTx was employed to discover the constitution of immune cells in KDs and HCs. Functional enrichment analysis was performed to understand the biological implications of the modular genes. Finally, competing endogenous RNAs (ceRNA) networks of node genes were predicted using online databases.

RESULTS

A total of 267 DEGs were analyzed between 153 KD patients and 92 HCs in the training set, spanning two modules according to WGCNA. The turquoise module was identified as the hub module, which was mainly enriched in cell activation involved in immune response, myeloid leukocyte activation, myeloid leukocyte mediated immunity, secretion and leukocyte mediated immunity biological processes; included type II diabetes mellitus, nicotinate and nicotinamide metabolism, O-glycan biosynthesis, glycerolipid and glutathione metabolism pathways. The node genes included ADM, ALPL, HK3, MMP9 and S100A12, and there was good performance in the validation studies. Immune cell infiltration analysis revealed that gamma delta T cells, monocytes, M0 macrophage, activated dendritic cells, activated mast cells and neutrophils were elevated in KD patients. Regarding the ceRNA networks, three intact networks were constructed: NEAT1/NORAD/XIST-hsa-miR-524-5p-ADM, NEAT1/NORAD/XIST-hsa-miR-204-5p-ALPL, NEAT1/NORAD/XIST-hsa-miR-524-5p/hsa-miR-204-5p-MMP9.

CONCLUSION

To conclude, the five-gene signature and three ceRNA networks constructed in our study are of great value in the early diagnosis of KD and might help to elucidate our understanding of KD at the RNA regulatory level.

Generation and multiomic profiling of a TP53/CDKN2A double-knockout gastroesophageal junction organoid model

Inactivation of the tumor suppressor genes tumor protein p53 (TP53) and cyclin-dependent kinase inhibitor 2A (CDKN2A) occurs early during gastroesophageal junction (GEJ) tumorigenesis. However, because of a paucity of GEJ-specific disease models, cancer-promoting consequences of TP53 and CDKN2A inactivation at the GEJ have not been characterized. Here, we report the development of a wild-type primary human GEJ organoid model and a CRISPR-edited transformed GEJ organoid model. CRISPR-Cas9-mediated TP53 and CDKN2A knockout (TP53/CDKN2AKO) in GEJ organoids induced morphologic dysplasia and proneoplastic features in vitro and tumor formation in vivo. Lipidomic profiling identified several platelet-activating factors (PTAFs) among the most up-regulated lipids in CRISPR-edited organoids. PTAF/PTAF receptor (PTAFR) abrogation by siRNA knockdown or a pharmacologic inhibitor (WEB2086) reduced proliferation and other proneoplastic features of TP53/CDKN2AKO GEJ organoids in vitro and tumor formation in vivo. In addition, murine xenografts of Eso26, an established human esophageal adenocarcinoma cell line, were suppressed by WEB2086. Mechanistically, TP53/CDKN2A dual inactivation disrupted both the transcriptome and the DNA methylome, likely mediated by key transcription factors, particularly forkhead box M1 (FOXM1). FOXM1 activated PTAFR transcription by binding to the PTAFR promoter, further amplifying the PTAF-PTAFR pathway. Together, these studies established a robust model system for investigating early GEJ neoplastic events, identified crucial metabolic and epigenomic changes occurring during GEJ model tumorigenesis, and revealed a potential cancer therapeutic strategy. This work provides insights into proneoplastic mechanisms associated with TP53/CDKN2A inactivation in early GEJ neoplasia, which may facilitate early diagnosis and prevention of GEJ neoplasms.