A novel mitochondria-related gene signature in esophageal carcinoma: prognostic, immune, and therapeutic features

Metabolic subtypes and immune landscapes in esophageal squamous cell carcinoma: prognostic implications and potential for personalized therapies

BACKGROUND

This study aimed to identify metabolic subtypes in ESCA, explore their relationship with immune landscapes, and establish a metabolic index for accurate prognosis assessment.

METHODS

Clinical, SNP, and RNA-seq data were collected from 80 ESCA patients from the TCGA database and RNA-seq data from the GSE19417 dataset. Metabolic genes associated with overall survival (OS) and progression-free survival (PFS) were selected, and k-means clustering was performed. Immune-related pathways, immune infiltration, and response to immunotherapy were predicted using bioinformatic algorithms. Weighted gene co-expression network analysis (WGCNA) was conducted to identify metabolic genes associated with co-expression modules. Lastly, cell culture and functional analysis were performed using patient tissue samples and ESCA cell lines to verify the identified genes and their roles.

RESULTS

Molecular subtypes were identified based on the expression profiles of metabolic genes, and univariate survival analysis revealed 163 metabolic genes associated with ESCA prognosis. Consensus clustering analysis classified ESCA samples into three distinct subtypes, with MC1 showing the poorest prognosis and MC3 having the best prognosis. The subtypes also exhibited significant differences in immune cell infiltration, with MC3 showing the highest scores. Additionally, the MC3 subtype demonstrated the poorest response to immunotherapy, while the MC1 subtype was the most sensitive. WGCNA analysis identified gene modules associated with the metabolic index, with SLC5A1, NT5DC4, and MTHFD2 emerging as prognostic markers. Gene and protein expression analysis validated the upregulation of MTHFD2 in ESCA. MTHFD2 promotes the progression of ESCA and may be a potential therapeutic target for ESCA.

CONCLUSION

The established metabolic index and identified metabolic genes offer potential for prognostic assessment and personalized therapeutic interventions for ESCA, underscoring the importance of targeting metabolism-immune interactions in ESCA. MTHFD2 promotes the progression of ESCA and may be a potential therapeutic target for ESCA.

Inhibition of FoxO1 alleviates polycystic ovarian syndrome by reducing inflammation and the immune response

The aim of this study was to explore the role of forkhead box transcription Factor O1 (FoxO1) in chronic inflammation in polycystic ovary syndrome (PCOS). A PCOS rat model was constructed as an in vivo model by letrozole induction, and granulosa cells (GCs) from PCOS rats were isolated and cultured as an in vitro cellular model. FoxO1 was knocked down by shRNA and siRNA in the PCOS rat model and GCs model, respectively. H&E staining was conducted to evaluate the effect of FoxO1 inhibition on ovarian pathology and dysfunction in PCOS rats. The levels of inflammatory cytokines in the ovaries and uterus of PCOS rats and in GCs were assessed by ELISA. Flow cytometry was used to evaluate the changes in the contents of neutrophils and macrophages in the peripheral blood and spleen of PCOS rats. CCK-8 assays and Annexin V-FITC/PI staining were performed to evaluate the proliferation and apoptosis of GCs. The expression of genes and proteins related to the TLR4/NF-κB/NLRP3 pathway in GCs was determined by RT-qPCR and Western blotting. The results indicated that FoxO1 was highly expressed in PCOS rat model. Inhibition of FoxO1 significantly mitigated the pathological changes and dysfunction in the ovaries of PCOS rats while also suppressing inflammation and fibrosis in the ovaries and uterus. Moreover, knocking down FoxO1 facilitated the restoration of the normal ratio of neutrophils and macrophages in the peripheral blood and spleen of PCOS rats and promoted M2 polarization of macrophages. Additionally, inhibition of FoxO1 promoted the proliferation of GCs and inhibited the inflammatory response in GCs. Furthermore, FoxO1 knockdown inhibited the activation of the NF-κB pathway and the formation of the NLRP3 inflammasome in GCs. In conclusion, inhibition of FoxO1 can alleviate PCOS by inhibiting the TLR4/NF-κB/NLRP3 pathway to reduce inflammation and the immune response.

Identification of a novel five ferroptosis-related gene signature as a promising prognostic model for breast cancer

BACKGROUND

Breast cancer (BCa) is a major challenge for women's health worldwide. Ferroptosis is closely related to tumorigenesis and cancer progression. However, the prognostic value of ferroptosis-related genes in BCa remains unclear, and more accurate prognostic models are urgently needed.

METHODS

Gene expression profiles and clinical information of BCa patients were collected from public databases. LASSO and multivariate Cox regression analysis were utilized to construct the prognostic gene signature. Kaplan-Meier plotter, receiver operating characteristic (ROC) curves, and nomogram were used to validate the prognostic value of the gene signature. Gene set enrichment analysis was performed to explore the molecular functions and signaling pathways.

RESULTS

Differentially expressed ferroptosis-related genes between BCa samples and normal tissues were obtained. A novel five-gene signature including BCL2, SLC40A1, TFF1, APOOL, and PRAME was established for prognosis prediction. Patients stratified into high-risk or low-risk group displayed significantly different survival. Kaplan-Meier and ROC curves showed a good performance for survival prediction in different cohorts. Biological function analysis revealed that the five-gene signature was associated with cancer progression, immune infiltration, immune response, and drug resistance. Nomogram including the five-gene signature was established.

CONCLUSION

A novel five ferroptosis-related gene signature and nomogram could be used for prognostic prediction in BCa.