Analysis of ferroptosis-associated genes in Crohn's disease based on bioinformatics

PUFAs add fuel to Crohn's disease-associated AIEC-induced enteritis by exacerbating intestinal epithelial lipid peroxidation

Polyunsaturated fatty acids (PUFAs) have been shown to exacerbate Crohn's disease (CD) by promoting lipid peroxidation (LPO) of intestinal epithelial cells (IECs). Dysbiosis of the gut microbiota may play a crucial role in this process. CD patients often exhibit an increased abundance of Escherichia coli (E. coli) in the gut, and the colonization of adherent-invasive E. coli (AIEC) is implicated in the initiation of intestinal inflammation in CD. However, the impact of AIEC on LPO remains unclear. In this study, we observed that AIEC colonization in the terminal ileum of CD patients was associated with decreased levels of glutathione peroxidase 4 (GPX4) and ferritin heavy chain (FTH) in the intestinal epithelium, along with elevated levels of 4-Hydroxynonenal (4-HNE). In vitro experiments demonstrated that AIEC infection reduced the levels of GPX4 and FTH, increased LPO, and induced ferroptosis in IECs. Furthermore, arachidonic acid (AA) and docosahexaenoic acid (DHA) supplementation in AIEC-infected IECs significantly aggravated LPO and ferroptosis. However, overexpression of GPX4 rescued AIEC-induced LPO and ferroptosis in IECs. Our results further confirmed that AIEC with AA supplementation, associated with excessive LPO and cell death in IECs, worsened colitis in the DSS mouse model and induced enteritis in the antibiotic cocktail pre-treatment mouse model in vivo. Moreover, treatment with ferrostatin-1, a ferroptosis inhibitor, alleviated AIEC with AA supplementation-induced enteritis in mice, accompanied by reduced LPO and cell death in IECs. Our findings suggest that AIEC, in combination with PUFA supplementation, can induce and exacerbate intestinal inflammation, primarily through increased LPO and ferroptosis in IECs.

Comprehensive Analysis of Disulfidptosis-Related LncRNAs in Molecular Classification, Immune Microenvironment Characterization and Prognosis of Gastric Cancer

BACKGROUND

Disulfidptosis is a novel form of programmed cell death that unveils promising avenues for the exploration of tumor treatment modalities. Gastric cancer (GC) is a malignant tumor characterized by high incidence and mortality rate. However, there has been no systematic study of disulfidptosis-related long noncoding RNAs (DRLs) signature in GC patients.

METHODS

The lncRNA expression profiles containing 412 GC samples were acquired from the Cancer Genome Atlas (TCGA) database. Differential expression analysis was performed alongside Pearson correlation analysis to identify DRLs. Prognostically significant DRLs were further screened using univariate COX regression analysis. Subsequently, LASSO regression and multifactorial COX regression analyses were employed to establish a risk signature composed of DRLs that exhibit independent prognostic significance. The predictive value of this risk signature was further validated in a test cohort. The ESTIMATE, CIBERSORT and ssGSEA methodologies were utilized to investigate the tumor immune microenvironment of GC populations with different DRLs profiles. Finally, the correlation between DRLs and various GC drug responses was explored.

RESULTS

We established a prognostic signature comprising 12 disulfidptosis-related lncRNAs (AC110491.1, AL355574.1, RHPN1-AS1, AOAH-IT1, AP001065.3, MEF2C-AS1, AC016394.2, LINC00705, LINC01952, PART1, TNFRSF10A-AS1, LINC01537). The Kaplan-Meier survival analysis revealed that patients in the high-risk group exhibited a poor prognosis. Both univariate and multivariate COX regression models demonstrated that the DRLs signature was an independent prognostic indicator in GC patients. Furthermore, the signature exhibited accurate predictions of survival at 1-, 3- and 5- years with the area under the curve (AUC) values of 0.708, 0.689 and 0.854, respectively. In addition, we also observed significant associations between the DRLs signature and various clinical variables, distinct immune landscape and drug sensitivity profiles in GC patients. The low-risk group patients may be more likely to benefit from immunotherapy and chemotherapy.

CONCLUSIONS

Our study investigated the role and potential clinical implications of DRLs in GC. The risk model constructed by DRLs demonstrated high accuracy in predicting the survival outcomes of GC and improving the treatment efficacy for GC patients.