Identification and Analysis of Potential Immune-Related Biomarkers in Endometriosis

Omics-based novel strategies in the diagnosis of endometriosis

Endometriosis, an enigmatic and chronic disorder, is considered a debilitating condition despite being benign. Globally, this gynecologic disorder affects up to 10% of females of reproductive age, impacting almost 190 million individuals. A variety of genetic and environmental factors are involved in endometriosis development, hence the pathophysiology and etiology of endometriosis remain unclear. The uncertainty of the etiology of the disease and its complexity along with nonspecific symptoms have led to misdiagnosis or lack of diagnosis of affected people. Biopsy and laparoscopy are referred to as the gold standard for endometriosis diagnosis. However, the invasiveness of the procedure, the unnecessary operation in disease-free women, and the dependence of the reliability of diagnosis on experience in this area are considered the most significant limitations. Therefore, continuous studies have attempted to offer a noninvasive and reliable approach. The recent advances in modern technologies have led to the generation of large-scale biological data sets, known as -omics data, resulting in the proceeding of the -omics century in biomedical sciences. Thereby, the present study critically reviews novel and noninvasive biomarkers that are based on -omics approaches from 2020 onward. The findings reveal that biomarkers identified based on genomics, epigenomics, transcriptomics, proteomics, and metabolomics are potentially able to diagnose endometriosis, predict prognosis, and stage patients, and potentially, in the near future, a multi-panel of these biomarkers will generate clinical benefits.

Construction and evaluation of endometriosis diagnostic prediction model and immune infiltration based on efferocytosis-related genes

Background: Endometriosis (EM) is a long-lasting inflammatory disease that is difficult to treat and prevent. Existing research indicates the significance of immune infiltration in the progression of EM. Efferocytosis has an important immunomodulatory function. However, research on the identification and clinical significance of efferocytosis-related genes (EFRGs) in EM is sparse. Methods: The EFRDEGs (differentially expressed efferocytosis-related genes) linked to datasets associated with endometriosis were thoroughly examined utilizing the Gene Expression Omnibus (GEO) and GeneCards databases. The construction of the protein-protein interaction (PPI) and transcription factor (TF) regulatory network of EFRDEGs ensued. Subsequently, machine learning techniques including Univariate logistic regression, LASSO, and SVM classification were applied to filter and pinpoint diagnostic biomarkers. To establish and assess the diagnostic model, ROC analysis, multivariate regression analysis, nomogram, and calibration curve were employed. The CIBERSORT algorithm and single-cell RNA sequencing (scRNA-seq) were employed to explore immune cell infiltration, while the Comparative Toxicogenomics Database (CTD) was utilized for the identification of potential therapeutic drugs for endometriosis. Finally, immunohistochemistry (IHC) and reverse transcription quantitative polymerase chain reaction (RT-qPCR) were utilized to quantify the expression levels of biomarkers in clinical samples of endometriosis. Results: Our findings revealed 13 EFRDEGs associated with EM, and the LASSO and SVM regression model identified six hub genes (ARG2, GAS6, C3, PROS1, CLU, and FGL2). Among these, ARG2, GAS6, and C3 were confirmed as diagnostic biomarkers through multivariate logistic regression analysis. The ROC curve analysis of GSE37837 (AUC = 0.627) and GSE6374 (AUC = 0.635), along with calibration and DCA curve assessments, demonstrated that the nomogram built on these three biomarkers exhibited a commendable predictive capacity for the disease. Notably, the ratio of nine immune cell types exhibited significant differences between eutopic and ectopic endometrial samples, with scRNA-seq highlighting M0 Macrophages, Fibroblasts, and CD8 Tex cells as the cell populations undergoing the most substantial changes in the three biomarkers. Additionally, our study predicted seven potential medications for EM. Finally, the expression levels of the three biomarkers in clinical samples were validated through RT-qPCR and IHC, consistently aligning with the results obtained from the public database. Conclusion: we identified three biomarkers and constructed a diagnostic model for EM in this study, these findings provide valuable insights for subsequent mechanistic research and clinical applications in the field of endometriosis.

Amplifying T cell-mediated antitumor immune responses in nonsmall cell lung cancer through photodynamic therapy and anti-PD1

Photodynamic therapy (PDT) is nowadays widely employed in cancer treatment. We sought to assess the efficacy of combining PDT with anti-programmed cell death protein 1 (PD1) and to investigate the associated mechanisms in nonsmall cell lung cancer (NSCLC). We established a xenograft tumor model in C57BL/6J mice using Lewis lung carcinoma (LLC) cells, recorded tumor growth, and quantified reactive oxygen species (ROS) levels using a ROS detection kit. Pathological changes were assessed through H&E staining, while immunofluorescence (IF) was used to determine the expression of CD8 and Foxp3. Transcriptomic analysis was conducted, analyzing differential expressed genes (DEGs) among control, PDT, and PDT combined with anti-PD1 (PDT+anti-PD1) groups. Functional enrichment analysis via Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) was performed. The Cancer Genome Atlas (TCGA) database was utilized to analyze the expression of aminolevulinate synthase gene (ALAS2), integrin alpha10 (ITGA10), ATP1A2, a disintegrin and metalloprotease 12 (ADAM12), and Lox1 in lung adenocarcinoma and adjacent tissues, with concurrent immune infiltration analysis. Quantitative real-time polymerase chain reaction and western blot were employed to measure mRNA and protein expression levels. Treatment with PDT combined with anti-PD1 significantly inhibited tumor growth and increased the number of CD8+ cells while decreasing Foxp3+ cells. Immune infiltration results presented ALAS2, ADAM12, and ITGA10 were associated with various types of T cells or macrophages. Additionally, the expression levels of EGFR, ERK, and PI3K/Akt were suppressed after PDT with anti-PD1 treatment. Our findings collectively suggest that PDT combined with anti-PD1 treatment could enhance the infiltration of CD8+ T cells, suppressing tumor growth, and this effect was associated with ALAS2, ITGA10, and ADAM12. The underlying mechanism might be linked to EGFR, ERK, and PI3K/Akt signaling. Overall, this study provides valuable insights into the application of PDT combined with anti-PD1 treatment in NSCLC.

Machine learning algorithms for a novel cuproptosis-related gene signature of diagnostic and immune infiltration in endometriosis

Endometriosis (EMT) is an aggressive disease of the reproductive system, also called "benign cancer". However, effective treatments for EMT are still lacking in clinical practice. Interestingly, immune infiltration is significantly involved in EMT pathogenesis. Currently, no studies have shown the involvement of cuproptosis-related genes (CRGs) in regulating immune infiltration in EMT. This study identified three CRGs such as GLS, NFE2L2, and PDHA1, associated with EMT using machine learning algorithms. These three CRGs were upregulated in the endometrium of patients with moderate/severe EMT and downregulated in patients with infertility. Single sample genomic enrichment analysis (ssGSEA) revealed that these CRGs were closely correlated with autoimmune diseases such as systemic lupus erythematosus. Furthermore, these CRGs were correlated with immune cells such as eosinophils, natural killer cells, and macrophages. Therefore, profiling patients based on these genes aid in a more accurate diagnosis of EMT progression. The mRNA and protein expression levels of GLS, NFE2L2 and PDHA1 were validated by qRT-PCR and WB studies in EMT samples. These findings provide a new idea for the pathology and treatment of endometriosis, suggesting that CRGs such as GLS, NFE2L2 and PDHA1 may play a key role in the occurrence and development of endometriosis.

The Role of Selected Dietary Factors in the Development and Course of Endometriosis

Endometriosis is a chronic disease with a complex, heterogeneous pathogenesis that affects about 10% of women of reproductive age, causing pain and leading to infertility. Treatment consists of administering pharmacological agents (resulting in a reduction of estrogen levels and inflammation), as well as the surgical removal of endometriotic lesions. Unfortunately, despite a wide range of available therapies, there is still a high recurrence rate after surgery. Consequently, it is necessary to improve the outcome of patients with endometriosis. In this context, there is growing interest in possible dietary modification to support or complement classic treatment options and even serve as a potential alternative to hormone therapy. In addition, a growing number of studies indicate positive effects of selected dietary factors on the development and course of endometriosis. This review article focuses on the potentially beneficial effects of compounds from the polyphenol group (curcumin, epigallocatechin gallate, quercetin, resveratrol), vitamins, and selected micronutrients on endometriosis. The results indicate the potential of the selected ingredients in fighting the disease. However, most of the studies have been performed on experimental animal models, with a smaller proportion looking at the actual effects of use among women. Therefore, well-designed studies are needed to assess the importance of a well-chosen diet and the effects of specific dietary factors on the health of women suffering from endometriosis.

Promotion of BST2 expression by the transcription factor IRF6 affects the progression of endometriosis

Background

Endometriosis (EM) is a benign, multifactorial, immune-mediated inflammatory disease that is characterized by persistent activation of the NF-κB signaling pathway and some features of malignancies, such as proliferation and lymphangiogenesis. To date, the pathogenesis of EM is still unclear. In this study, we investigated whether BST2 plays a role in the development of EM.

Methods

Bioinformatic analysis was performed with data from public databases to identify potential candidate targets for drug treatment. Experiments were conducted at the cell, tissue, and mouse EM model levels to characterize the aberrant expression patterns, molecular mechanisms, biological behaviors of endometriosis as well as treatment outcomes.

Results

BST2 was significantly upregulated in ectopic endometrial tissues and cells compared with control samples. Functional studies indicated that BST2 promoted proliferation, migration, and lymphangiogenesis and inhibited apoptosis in vitro and in vivo. The transcription factor (TF) IRF6 induced high BST2 expression by directly binding the BST2 promoter. The underlying mechanism by which BST2 functions in EM was closely related to the canonical NF-κB signaling pathway. New lymphatic vessels may serve as a channel for the infiltration of immune cells into the endometriotic microenvironment; these immune cells further produce the proinflammatory cytokine IL-1β, which in turn further activates the NF-κB pathway to promote lymphangiogenesis in endometriosis.

Conclusion

Taken together, our findings provide novel insight into the mechanism by which BST2 participates in a feedback loop with the NF-κB signaling pathway and reveal a novel biomarker and potential therapeutic target for endometriosis.