Aberrant expression of GSTM5 in lung adenocarcinoma is associated with DNA hypermethylation and poor prognosis

Identification of 10 differentially expressed genes involved in the tumorigenesis of cervical cancer via next-generation sequencing

Background

The incidence and mortality of cervical cancer remain high in female malignant tumors worldwide. There is still a lack of diagnostic and prognostic markers for cervical carcinoma. This study aimed to screen differentially expressed genes (DEGs) between normal and cervical cancer tissues to identify candidate genes for further research.

Methods

Uterine cervical specimens were resected from our clinical patients after radical hysterectomy. Three patients' transcriptomic datasets were built by the next generation sequencing (NGS) results. DEGs were selected through the edgeR and DESeq2 packages in the R environment. Functional enrichment analysis, including GO/DisGeNET/KEGG/Reactome enrichment analysis, was performed. Normal and cervical cancer tissue data from the public databases TCGA and GTEx were collected to compare the expression levels of 10 selected DEGs in tumor and normal tissues. ROC curve and survival analysis were performed to compare the diagnostic and prognostic values of each gene. The expression levels of candidate genes were verified in 15 paired clinical specimens via quantitative real-time polymerase chain reaction.

Results

There were 875 up-regulated and 1,482 down-regulated genes in cervical cancer samples compared with the paired adjacent normal cervical tissues according to the NGS analysis. The top 10 DEGs included APOD, MASP1, ACKR1, C1QTNF7, SFRP4, HSPB6, GSTM5, IGFBP6, F10 and DCN. GO, DisGeNET and Reactome analyses revealed that the DEGs were related to extracellular matrix and angiogenesis which might influence tumorigenesis. KEGG enrichment showed that PI3K-Akt signaling pathway might be involved in cervical cancer tumorigenesis and progression. The expression levels of selected genes were decreased in tumors in both the public database and our experimental clinical specimens. All the candidate genes showed excellent diagnostic value, and the AUC values exceeded 0.90. Additionally, APOD, ACKR1 and SFRP4 expression levels could help predict the prognosis of patients with cervical cancer.

Conclusions

In this study, we selected the top 10 DEGs which were down-regulated in cervical cancer tissues. All of them had dramatically diagnostic value. APOD, ACKR1 and SFRP4 were associated with the survivals of cervical cancer. C1QTNF7, HSPB6, GSTM5, IGFBP6 and F10 were first reported to be candidate genes of cervical carcinoma.

Identification ATP5F1D as a Biomarker Linked to Diagnosis, Prognosis, and Immune Infiltration in Endometrial Cancer Based on Data-Independent Acquisition (DIA) Analysis

In developed countries, endometrial cancer (EC) is the most prevalent gynecological cancer. ATP5F1D is a subunit of ATP synthase, as well as an important component of the mitochondrial electron transport chain (ETC). ETC plays a compelling role in carcinogenesis. To date, little is known about the role of ATP5F1D in EC. We undertook data-independent acquisition mass spectrometry (DIA-MS) of 20 EC patients, comprising 10 high-grade and 10 low-grade cancer tissues. Biological functions of differentially expressed genes (DEGs) were analyzed by GO and KEGG. The expression level, clinicopathological features, diagnostic potency, prognostic value, RNA modifications, immune characteristics, and therapy response of ATP5F1D were investigated. In total, 77 DEGs were acquired by DIA analysis, which were closely related to regulating immune response and metabolic pathways. Among the five genes (NDUFB8, SLC26A2, RAF1, ATP5F1D, and GSTM5) involving in reactive oxygen species pathway, ATP5F1D showed the most significant differential expression (2.903-fold change). We found ATP5F1D had a high diagnostic value and was associated with a favorable prognosis in EC patients. After analyzing the RNA modifications of ATP5F1D, revealing a negative regulation between them. Additionally, ATP5F1D was closely related to tumor immune infiltration. Our results suggested T-cell dysfunction and TAM-M2 polarization might be the important mechanisms of ATP5F1D to facilitate tumor immune escape. Noticeably, EC patients with ATP5F1D-high expression had better immune treatment responses and were more sensitive to chemotherapy drugs. ATP5F1D can be used as a biomarker for diagnosis, prognosis, and immune infiltration of EC, and offers a crucial reference for personalized treatment of EC patients.

Methylation-related differentially expressed genes as potential prognostic biomarkers for cervical cancer

Aim

To discover novel methylation-related differentially expressed genes (MRDEGs) for cervical cancer, with a focus on their potential for early diagnosis and prognostic assessment.

Materials & methods

We integrated data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. TCGA-MRDEGs were identified by analyzing differentially methylated genes (DMGs) and their correlation with gene expression. We examined GEO datasets GSE39001, GSE9750, and GSE46306 for GEO-MRDEGs. Overlapping MRDEGs were subjected to overall survival (OS) analysis to identify prognostic markers. The expression and methylation levels of these genes were validated in a total of 30 tissue samples, comprising 20 from cervical cancer patients and 10 from normal cervical tissues, using qRT-PCR and MassARRAY EpiTYPER Assay.

Results

A total of 314 TCGA-MRDEGs and 40 GEO-MRDEGs were identified. Intersection analysis yielded 10 overlapping MRDEGs. Notably, NOVA1, GSTM5, TRHDE, and CXCL12 were found to have reduced expression and increased methylation in cervical cancer, which correlated with poor prognosis. The methylation status and expression levels of these genes were confirmed in tissue specimens.

Conclusion

We identified four MRDEGs as potential prognostic biomarkers for cervical cancer. Their clinical utility is highlighted, but further validation in larger cohorts is required to establish their clinical significance.

Melatonin reverses EGFR-TKI therapeutic resistance by modulating crosstalk between circadian-related gene signature and immune infiltration patterns in patients with COVID-19 and lung adenocarcinoma

BACKGROUND

Patients with lung cancer exhibit the poorest outcomes when infected with coronavirus disease 2019 (COVID-19). However, the potential impact of COVID-19 on the tumor microenvironment (TME) of lung adenocarcinoma (LUAD) remains unknown.

METHODS

Expression data and clinical information were sourced from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Prognostic, differentially expressed circadian-related genes (CRGs) were identified using multivariate Cox regression and LASSO regression analyses to establish an immune-related gene signature. The clinical value, immune landscape, somatic mutations, and drug sensitivity of high- and low-risk groups were assessed using Kaplan-Meier curves and immunotherapy cohorts. Finally, in vitro and in vivo experiments were conducted to elucidate the molecular function of melatonin in regulating the immune microenvironment and therapeutic resistance.

RESULTS

Three circadian-related patterns and distinct CRGs clusters were identified based on the abnormal expression of 13 CRGs. Circadian genomic phenotypes were identified based on 13 circadian phenotype-related differentially expressed genes (DEGs). A CRGs risk signature was constructed; the high CRGs risk group displayed an immunosuppressive TME, poor survival, and therapy resistance. Melatonin reversed EGFR-tyrosine kinase inhibitor (EGFR-TKI) resistance by regulating immune cell infiltration into the TME, both in vitro and in vivo.

CONCLUSIONS

The investigation revealed crosstalk between CRGs signatures and immune infiltration patterns in LUAD and COVID-19. Melatonin acted as a promising agent to suppress the malignant features of lung cancer and enhance treatment sensitivity by modulating the TME.

IGF2BP2 regulates the inflammation of fibroblast-like synoviocytes via GSTM5 in rheumatoid arthritis

Rheumatoid arthritis (RA) is a chronic autoimmune disease with an unknown etiology. RA cannot be fully cured and requires lengthy treatment, imposing a significant burden on both individuals and society. Due to the lack of specific drugs available for treating RA, exploring a key new therapeutic target for RA is currently an important task. Activated fibroblast-like synoviocytes (FLSs) play a crucial role in the progression of RA, which release interleukin (IL)-1β, IL-6 and tumor necrosis factor (TNF)-α resulting in abnormal inflammatory reaction in the synovium. A previous study has highlighted the correlation of m6A reader insulin-like growth factor 2 mRNA-binding protein 2 (IGF2BP2) with inflammation-related diseases in human. However, the role of IGF2BP2 in the inflammatory reaction of FLSs during RA progression has not been assessed. In this study, IGF2BP2 expression was decreased in the synovial tissues of RA patients and collagen-induced arthritis (CIA) rats. Intra-articular injection of an adeno-associated virus (AAV) vector overexpressing IGF2BP2 relieved paw swelling, synovial hyperplasia and cartilage destruction in CIA rats. IGF2BP2 overexpression also inhibited lipopolysaccharide (LPS)-mediated RA fibroblast-like synoviocytes (RA-FLSs) migration and invasion accompanied by a decreased level of inflammatory factors in vitro. Conversely, IGF2BP2 suppression promoted RA-FLSs migration and invasion with an elevated level of inflammatory factors in vitro. The sequencing result showed that glutathione S-transferase Mu 5 (GSTM5), a key antioxidant gene, was the target mRNA of IGF2BP2. Further experiments demonstrated that IGF2BP2 strengthened the stability of GSTM5 mRNA, leading to weakened inflammatory reaction and reduced expression of matrix metalloproteinase 9 and 13 (MMP9, MMP13). Therefore, IGF2BP2-GSTM5 axis may represent a potential therapeutic target for RA treatment.

5-Hydroxymethylcytosine in Cell-Free DNA Predicts Immunotherapy Response in Lung Cancer

Immune checkpoint inhibitors (ICIs) drastically improve therapeutic outcomes for lung cancer, but accurately predicting individual patient responses to ICIs remains a challenge. We performed the genome-wide profiling of 5-hydroxymethylcytosine (5hmC) in 85 plasma cell-free DNA (cfDNA) samples from lung cancer patients and developed a 5hmC signature that was significantly associated with progression-free survival (PFS). We built a 5hmC predictive model to quantify the 5hmC level and validated the model in the validation, test, and control sets. Low weighted predictive scores (wp-scores) were significantly associated with a longer PFS compared to high wp-scores in the validation [median 7.6 versus 1.8 months; p = 0.0012; hazard ratio (HR) 0.12; 95% confidence interval (CI), 0.03-0.54] and test (median 14.9 versus 3.3 months; p = 0.00074; HR 0.10; 95% CI, 0.02-0.50) sets. Objective response rates in patients with a low or high wp-score were 75.0% (95% CI, 42.8-94.5%) versus 0.0% (95% CI, 0.0-60.2%) in the validation set (p = 0.019) and 80.0% (95% CI, 44.4-97.5%) versus 0.0% (95% CI, 0.0-36.9%) in the test set (p = 0.0011). The wp-scores were also significantly associated with PFS in patients receiving single-agent ICI treatment (p < 0.05). In addition, the 5hmC predictive signature demonstrated superior predictive capability to tumor programmed death-ligand 1 and specificity to ICI treatment response prediction. Moreover, we identified novel 5hmC-associated genes and signaling pathways integral to ICI treatment response in lung cancer. This study provides proof-of-concept evidence that the cfDNA 5hmC signature is a robust biomarker for predicting ICI treatment response in lung cancer.

QTL mapping of human retina DNA methylation identifies 87 gene-epigenome interactions in age-related macular degeneration

DNA methylation provides a crucial epigenetic mark linking genetic variations to environmental influence. We have analyzed array-based DNA methylation profiles of 160 human retinas with co-measured RNA-seq and >8 million genetic variants, uncovering sites of genetic regulation in cis (37,453 methylation quantitative trait loci and 12,505 expression quantitative trait loci) and 13,747 DNA methylation loci affecting gene expression, with over one-third specific to the retina. Methylation and expression quantitative trait loci show non-random distribution and enrichment of biological processes related to synapse, mitochondria, and catabolism. Summary data-based Mendelian randomization and colocalization analyses identify 87 target genes where methylation and gene-expression changes likely mediate the genotype effect on age-related macular degeneration. Integrated pathway analysis reveals epigenetic regulation of immune response and metabolism including the glutathione pathway and glycolysis. Our study thus defines key roles of genetic variations driving methylation changes, prioritizes epigenetic control of gene expression, and suggests frameworks for regulation of macular degeneration pathology by genotype-environment interaction in retina.

Revealing the mechanism of 755-nm long-pulsed alexandrite laser in inhibiting infantile hemangioma endothelial cells through transcriptome sequencing

Laser therapy has shown promising outcomes in treating infantile hemangiomas. However, the molecular mechanisms underlying laser treatment for IH remain incompletely elucidated. This study aimed to unravel the molecular mechanisms of laser therapy in IH treatment. We evaluated the inhibitory effects of laser treatment on the proliferation and promotion of apoptosis in human hemangioma endothelial cells (HemECs) through cell counting kit-8 (CCK-8) assay, Hoechst 33342 staining, and flow cytometric analysis. Transcriptome sequencing analysis of HemECs following laser treatment revealed a significant decrease in the expression level of the GSTM5 gene. The qRT-PCR and western blot analysis also showed that GSTM5 expression in HemECs was downregulated compared to human umbilical vein endothelial cells (HUVECs), and concomitantly, the p62-Nrf2 pathway was suppressed. Using siRNA to downregulate GSTM5 expression, we observed that inhibiting GSTM5 expression could restrain cell proliferation, elevate intracellular ROS levels, and induce apoptosis in HemECs. Furthermore, upon inhibition of the p62-Nrf2 pathway using p62-specific siRNA, a significant decrease in GSTM5 expression and an elevation in intracellular ROS levels were noted in laser-treated HemECs. These findings suggested that laser treatment may operate by inhibiting the p62-Nrf2 pathway, thereby downregulating GSTM5 expression, elevating ROS levels, and consequently inducing apoptosis in HemECs.

Analysis of glutathione Stransferase mu class 5 gene methylation as a prognostic indicator in low-grade gliomas

BACKGROUND

Low-grade gliomas (LGG) are a variety of brain tumors that show different clinical outcomes. The methylation of the GSTM5 gene has been noted in the development of LGG, however, its prognostic importance remains uncertain.

OBJECTIVE

The objective of this study was to examine the correlation between GSTM5 DNA methylation and clinical outcomes in individuals diagnosed with LGG.

METHODS

Analysis of GSTM5 methylation levels in LGG samples was conducted using data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets. The overall survival based on GSTM5 methylation status was evaluated using Kaplan-Meier curves. The DNA methylation heatmap for particular CpG sites in the GSTM5 gene was visualized using the "pheatmap" R package.

RESULTS

The study analyzed that LGG tumors had higher levels of GSTM5 methylation than normal tissues. There was an inverse relationship discovered between GSTM5 expression and methylation. LGG patients with hypermethylation of GSTM5 promoter experienced a positive outcome. Age, grade, and GSTM5 methylation were determined as independent prognostic factors in LGG through both univariate and multivariate Cox regression analyses.

CONCLUSION

Methylation of GSTM5 DNA, specifically at certain CpG sites, is linked to a positive outlook in patients with LGG. Utilizing the "pheatmap" R package to visualize GSTM5 methylation patterns offers important information for identifying prognostic markers and therapeutic targets in low-grade gliomas.

Identifying and Validating GSTM5 as an Immunogenic Gene in Diabetic Foot Ulcer Using Bioinformatics and Machine Learning

Background

A diabetic foot ulcer (DFU) is a serious, long-term condition associated with a significant risk of disability and mortality. However, research on its biomarkers is still limited. This study utilizes bioinformatics and machine learning methods to identify immune-related biomarkers for DFU and validates them through external datasets and animal experiments.

Methods

This study used bioinformatics and machine learning to analyze microarray data from the Gene Expression Omnibus (GEO) database to identify key genes associated with DFU. Animal experiments were conducted to validate these findings. This research employs the datasets GSE68183 and GSE80178 retrieved from the GEO database as the training dataset for building a gene machine learning model, and after conducting differential analysis on the data, this study used package glmnet and package e1071 to construct LASSO and SVM-RFE machine learning models, respectively. Subsequently, we validated the model using the training set and validation set (GSE134431). We conducted enrichment analysis, including GSEA and GSVA, on the model genes. We also performed immune functional analysis and immune-related analysis on the model genes. Finally, we conducted immunohistochemistry (IHC) validation on the model genes.

Results

This study identifies GSTM5 as a potential immune-related key target in DFU using machine learning and bioinformatics methods. Subsequent validation through external datasets and IHC experiments also confirms GSTM5 as a critical biomarker for DFU. The gene may be associated with T cells regulatory (Tregs) and T cells follicular helper, and it influences the NF-κB, GnRH, and MAPK signaling pathway.

Conclusion

This study identified and validated GSTM5 as a biomarker for DFU. This finding may potentially provide a target for immune therapy for DFU.

QTL mapping of human retina DNA methylation identifies 87 gene-epigenome interactions in age-related macular degeneration

DNA methylation (DNAm) provides a crucial epigenetic mark linking genetic variations to environmental influence. We analyzed array-based DNAm profiles of 160 human retinas with co-measured RNA-seq and > 8 million genetic variants, uncovering sites of genetic regulation in cis (37,453 mQTLs and 12,505 eQTLs) and 13,747 eQTMs (DNAm loci affecting gene expression), with over one-third specific to the retina. mQTLs and eQTMs show non-random distribution and enrichment of biological processes related to synapse, mitochondria, and catabolism. Summary data-based Mendelian randomization and colocalization analyses identify 87 target genes where methylation and gene-expression changes likely mediate the genotype effect on age-related macular degeneration (AMD). Integrated pathway analysis reveals epigenetic regulation of immune response and metabolism including the glutathione pathway and glycolysis. Our study thus defines key roles of genetic variations driving methylation changes, prioritizes epigenetic control of gene expression, and suggests frameworks for regulation of AMD pathology by genotype-environment interaction in retina.

Quantitative Proteomics Identifies Novel Nrf2-Mediated Adaptative Signaling Pathways in Skeletal Muscle Following Exercise Training

Exercise training (ExT) improves skeletal muscle health via multiple adaptative pathways. Nrf2 is a principal antioxidant transcription factor responsible for maintaining intracellular redox homeostasis. In this study, we hypothesized that Nrf2 is essential for adaptative responses to ExT and thus beneficial for muscle. Experiments were carried out on male wild type (WT) and iMS-Nrf2flox/flox inducible muscle-specific Nrf2 (KO) mice, which were randomly assigned to serve as sedentary controls (Sed) or underwent 3 weeks of treadmill ExT thus generating four groups: WT-Sed, WT-ExT, KO-Sed, and KO-ExT groups. Mice were examined for exercise performance and in situ tibialis anterior (TA) contractility, followed by mass spectrometry-based proteomics and bioinformatics to identify differentially expressed proteins and signaling pathways. We found that maximal running distance was significantly longer in the WT-ExT group compared to the WT-Sed group, whereas this capacity was impaired in KO-ExT mice. Force generation and fatigue tolerance of the TA were enhanced in WT-ExT, but reduced in KO-ExT, compared to Sed controls. Proteomic analysis further revealed that ExT upregulated 576 proteins in WT but downregulated 207 proteins in KO mice. These proteins represent pathways in redox homeostasis, mitochondrial respiration, and proteomic adaptation of muscle to ExT. In summary, our data suggest a critical role of Nrf2 in the beneficial effects of SkM and adaptation to ExT.