RESUMO
Ferroptosis plays a key role in aggravating the progression of spinal cord injury (SCI), but the specific mechanism remains unknown. In this study, we constructed a rat model of T10 SCI using a modified Allen method. We identified 48, 44, and 27 ferroptosis genes that were differentially expressed at 1, 3, and 7 days after SCI induction. Compared with the sham group and other SCI subgroups, the subgroup at 1 day after SCI showed increased expression of the ferroptosis marker acyl-CoA synthetase long-chain family member 4 and the oxidative stress marker malondialdehyde in the injured spinal cord while glutathione in the injured spinal cord was lower. These findings with our bioinformatics results suggested that 1 day after SCI was the important period of ferroptosis progression. Bioinformatics analysis identified the following top ten hub ferroptosis genes in the subgroup at 1 day after SCI: STAT3, JUN, TLR4, ATF3, HMOX1, MAPK1, MAPK9, PTGS2, VEGFA, and RELA. Real-time polymerase chain reaction on rat spinal cord tissue confirmed that STAT3, JUN, TLR4, ATF3, HMOX1, PTGS2, and RELA mRNA levels were up-regulated and VEGFA, MAPK1 and MAPK9 mRNA levels were down-regulated. Ten potential compounds were predicted using the DSigDB database as potential drugs or molecules targeting ferroptosis to repair SCI. We also constructed a ferroptosis-related mRNA-miRNA-lncRNA network in SCI that included 66 lncRNAs, 10 miRNAs, and 12 genes. Our results help further the understanding of the mechanism underlying ferroptosis in SCI.
RESUMO
BACKGROUND: To summarize the regulatory role of mRNA-miRNA-lncRNA network associated with endocrine therapy resistance (ETR) in breast cancer. METHODS: We analyzed the differentially expressed genes (DEGs), differentially expressed lncRNAs (DELs), and differentially expressed miRNAs (DEMs) in long-term estrogen-deprived (LTED) estrogen receptor (ER)-positive breast cancer cells (LTED MCF7) (modeling relapse on endocrine therapy) and MCF7 cells in the presence of estrogen (E2) (modeling a patient at primary diagnosis) by mining GSE120929 and GSE120930 datasets. The mRNA-miRNA-lncRNA network was constructed by multiple bioinformatic tools. The prognosis of genes from the network was validated in breast cancer patients with following systemic treatment (endocrine therapy) by GEPIA, Kaplan-Meier plotter and UALCAN database. RESULTS: Totally, 769 DEGs, 33 DEMs, and 10 DELs were selected. The mRNA-miRNA-lncRNA network was established including 60 mRNA nodes, 6 miRNA nodes and 3 lncRNA nodes. A significant module containing 3 nodes and 3 edges was calculated based on the mRNA-miRNA-lncRNA network. The hub genes in the network are ABCG2, ESR1 and GJA1. ESR1/miR-130b-3p/HOTAIR are significantly correlated with the prognosis of breast cancer patients with endocrine therapy. CONCLUSION: This study provides a novel ETR-related mRNA-miRNA-lncRNA network. Further, we suggest that ESR1/miR-130b-3p/HOTAIR may be promising targets for clinical treatment of endocrine therapy-resistant breast cancer.