# Bioinformatics and experimental validation of ferroptosis-related genes in steroid-induced osteonecrosis of the femoral head

## TL;DR

This study identifies key genes linked to ferroptosis in steroid-induced osteonecrosis of the femoral head, validating them experimentally and suggesting potential therapeutic drugs.

## Contribution

The study identifies and experimentally validates novel ferroptosis-related genes as potential biomarkers and drug targets for steroid-induced osteonecrosis.

## Key findings

- Four core ferroptosis-related genes (GCLC, GABARAPL2, CISD2, NCOA4) were identified and validated in SONFH bone tissue.
- A predictive nomogram model based on these genes showed strong diagnostic reliability and validity.
- Potential drugs targeting these genes, such as Diethyl sulfate and Meloxicam, were predicted.

## Abstract

Steroid-induced osteonecrosis of the femoral head (SONFH) is a progressive condition that causes increasing disability. It is thought to result from reduced blood flow and oxygen levels in the femoral head, with reactive oxygen species (ROS) playing a key role in triggering ferroptosis. However, the role of ferroptosis in SONFH progression remains underexplored. This study aimed to identify and validate key genes associated with ferroptosis in SONFH using bioinformatics.

The study analyzed the SONFH dataset GSE123568, which includes data from 30 SONFH patients and 10 controls. Weighted gene co-expression network analysis (WGCNA) was used to identify differentially expressed genes (DEGs) between the SONFH and control groups. Core genes were identified by intersecting DEGs with ferroptosis-related genes retrieved from FerrDb V2. The diagnostic performance of the key genes was assessed using the receiver operating characteristic (ROC) curve, and a predictive nomogram model was developed. Interaction analysis of these genes was conducted to explore their link with immune infiltration. The expression of these genes in bone tissue from SONFH patients was validated. Finally, drug-protein interactions were predicted using the DSigDB database.

Differential expression analysis identified 384 DEGs, which were significantly involved in inflammatory pathways. WGCNA revealed four key genes after intersecting DEGs with relevant module genes and ferroptosis-related genes. A nomogram model based on these genes demonstrated strong reliability and validity. Immune infiltration analysis showed significant differences between SONFH patients and controls, with notable associations between immune cell infiltration and the expression of the four core genes. Validation through quantitative real-time PCR (qRT-PCR) and Western blot confirmed that the expression of GCLC, GABARAPL2, CISD2, and NCOA4 was significantly lower in SONFH bone tissue compared to controls (P < 0.05). Additionally, potential therapeutic drugs targeting these genes, including Diethyl sulfate, Meloxicam, and NIMUSTINE, were predicted.

This study identifies GABARAPL2, CISD2, NCOA4, and GCLC as potential diagnostic biomarkers associated with immune cell infiltration in SONFH, offering new insights for future research and clinical applications.