Bioinformatics Analyses Reveal the Prognostic Value and Biological Roles of SEPHS2 in Various Cancers

Selenoprotein S (SELENOS) is a potential prognostic biomarker for brain lower grade glioma

BACKGROUND

Selenium, an essential micronutrient, primarily exists as selenocysteine in various selenoproteins. Selenoprotein S (SELENOS) is crucial in the development of human cancer. This study aimed to explore the correlation between SELENOS gene expression and the prognosis of brain lower-grade glioma (LGG).

METHODS

SELENOS protein and mRNA expression in human normal and tumor tissues were explored through the HPA database. SELENOS expression differences between normal and tumor tissues, along with its prognostic significance in gliomas, were analyzed using the TCGA, GTEx datasets, while the CGGA dataset was used to further assess its prognostic potential in a Chinese cohort. The association between SELENOS expression and tumor immune infiltration was also assessed. Multivariate and univariate Cox models were used to screen for clinicopathological parameters associated with SELENOS expression. The GDSC datasets was utilized to explore the connection between SELENOS and chemotherapeutic responses in LGG. A protein-protein interaction network for SELENOS was created. SELENOS expression in LGG cell lines were determined by Western blotting and qRT-PCR, and its functions were ascertained by routine in vitro experiments.

RESULTS

SELENOS was upregulated in 11 cancers and downregulated in 10 cancers relative to the corresponding normal tissues, and correlated significantly with the prognosis, especially for GBM, LGG and GBMLGG. Furthermore, It displayed a positive correlation with immune cell infiltration levels in LGG. Multivariate and Univariate Cox analyses confirmed that the impact of SELENOS on the prognosis of LGG is the combined result of factors such as age and tumor grade. The expression of SELENOS was significantly negatively correlated with temozolomide IC50 in LGG. We found that SELENOS interacts with 10 proteins, which are upregulated in LGG compared to human normal tissues. The expression of these interactors is positively correlated with SELENOS expression and LGG survival/prognosis. In vitro experiments confirmed the aberrant expression of SELENOS in LGG cell lines, and siRNA-mediated knockdown of SELENOS reduced the proliferation, viability, invasion and migration of LGG cells, and induced apoptosis.

CONCLUSIONS

SELENOS is a potential prognostic marker and therapeutic target for LGG, and its low expression is associated with favorable prognosis in LGG.

Introducing effective genes in lymph node metastasis of breast cancer patients using SHAP values based on the mRNA expression data

OBJECTIVE

Breast cancer, a global concern predominantly impacting women, poses a significant threat when not identified early. While survival rates for breast cancer patients are typically favorable, the emergence of regional metastases markedly diminishes survival prospects. Detecting metastases and comprehending their molecular underpinnings are crucial for tailoring effective treatments and improving patient survival outcomes.

METHODS

Various artificial intelligence methods and techniques were employed in this study to achieve accurate outcomes. Initially, the data was organized and underwent hold-out cross-validation, data cleaning, and normalization. Subsequently, feature selection was conducted using ANOVA and binary Particle Swarm Optimization (PSO). During the analysis phase, the discriminative power of the selected features was evaluated using machine learning classification algorithms. Finally, the selected features were considered, and the SHAP algorithm was utilized to identify the most significant features for enhancing the decoding of dominant molecular mechanisms in lymph node metastases.

RESULTS

In this study, five main steps were followed for the analysis of mRNA expression data: reading, preprocessing, feature selection, classification, and SHAP algorithm. The RF classifier utilized the candidate mRNAs to differentiate between negative and positive categories with an accuracy of 61% and an AUC of 0.6. During the SHAP process, intriguing relationships between the selected mRNAs and positive/negative lymph node status were discovered. The results indicate that GDF5, BAHCC1, LCN2, FGF14-AS2, and IDH2 are among the top five most impactful mRNAs based on their SHAP values.

CONCLUSION

The prominent identified mRNAs including GDF5, BAHCC1, LCN2, FGF14-AS2, and IDH2, are implicated in lymph node metastasis. This study holds promise in elucidating a thorough insight into key candidate genes that could significantly impact the early detection and tailored therapeutic strategies for lymph node metastasis in patients with breast cancer.

Current Understanding of Human Polymorphism in Selenoprotein Genes: A Review of Its Significance as a Risk Biomarker

Selenium has been proven to influence several biological functions, showing to be an essential micronutrient. The functional studies demonstrated the benefits of a balanced selenium diet and how its deficiency is associated with diverse diseases, especially cancer and viral diseases. Selenium is an antioxidant, protecting the cells from damage, enhancing the immune system response, preventing cardiovascular diseases, and decreasing inflammation. Selenium can be found in its inorganic and organic forms, and its main form in the cells is the selenocysteine incorporated into selenoproteins. Twenty-five selenoproteins are currently known in the human genome: glutathione peroxidases, iodothyronine deiodinases, thioredoxin reductases, selenophosphate synthetase, and other selenoproteins. These proteins lead to the transport of selenium in the tissues, protect against oxidative damage, contribute to the stress of the endoplasmic reticulum, and control inflammation. Due to these functions, there has been growing interest in the influence of polymorphisms in selenoproteins in the last two decades. Selenoproteins' gene polymorphisms may influence protein structure and selenium concentration in plasma and its absorption and even impact the development and progression of certain diseases. This review aims to elucidate the role of selenoproteins and understand how their gene polymorphisms can influence the balance of physiological conditions. In this polymorphism review, we focused on the PubMed database, with only articles published in English between 2003 and 2023. The keywords used were "selenoprotein" and "polymorphism". Articles that did not approach the theme subject were excluded. Selenium and selenoproteins still have a long way to go in molecular studies, and several works demonstrated the importance of their polymorphisms as a risk biomarker for some diseases, especially cardiovascular and thyroid diseases, diabetes, and cancer.

Pharmacogenomic Analysis of Combined Therapies against Glioblastoma Based on Cell Markers from Single-Cell Sequencing

Glioblastoma is the most common and aggressive form of primary brain cancer and the lack of viable treatment options has created an urgency to develop novel treatments. Personalized or predictive medicine is still in its infancy stage at present. This research aimed to discover biomarkers to inform disease progression and to develop personalized prophylactic and therapeutic strategies by combining state-of-the-art technologies such as single-cell RNA sequencing, systems pharmacology, and a polypharmacological approach. As predicted in the pyroptosis-related gene (PRG) transcription factor (TF) microRNA (miRNA) regulatory network, TP53 was the hub gene in the pyroptosis process in glioblastoma (GBM). A LASSO Cox regression model of pyroptosis-related genes was built to accurately and conveniently predict the one-, two-, and three-year overall survival rates of GBM patients. The top-scoring five natural compounds were parthenolide, rutin, baeomycesic acid, luteolin, and kaempferol, which have NFKB inhibition, antioxidant, lipoxygenase inhibition, glucosidase inhibition, and estrogen receptor agonism properties, respectively. In contrast, the analysis of the cell-type-specific differential expression-related targets of natural compounds showed that the top five subtype cells targeted by natural compounds were endothelial cells, microglia/macrophages, oligodendrocytes, dendritic cells, and neutrophil cells. The current approach-using the pharmacogenomic analysis of combined therapies-serves as a model for novel personalized therapeutic strategies for GBM treatment.

Selenoprotein GPX1 is a prognostic and chemotherapy-related biomarker for brain lower grade glioma

OBJECTIVE

Glutathione peroxidase 1 (GPX1) is a major selenoprotein in most animal tissues, primarily expressed in the cytoplasm and mitochondria of cells and peroxidase structures of certain cells. GPX1 expression is highly correlated with carcinogenesis and disease progression. The goal of the study was to determine the association between GPX1 expression and tumor therapy, and to identify GPX1 prognostic value in various malignancies.

METHODS

The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), and Human Protein Atlas (HPA) databases were used to detect the levels of GPX1 expression in human tumor tissues and normal tissues. Indeed, correlations between GPX1 and tumor purity, tumor mutation burden (TMB), microsatellite instability (MSI), and DNA mismatch repair genes (MMRs) were explored using the TCGA cohort. Functional and enrichment analyses were performed by the GeneMANIA database and Gene Set Enrichment Analysis (GSEA), respectively. Cox regression models and Kaplan - Meier curves were used to screen for independent risk factors and estimate brain lower-grade glioma (LGG) survival probability. The Chinese Glioma Genome Atlas (CGGA) database was used to determine whether GPX1 had a race-specific effect on overall survival (OS) in LGG. The cross-interaction between GPX1 and chemoradiotherapy on LGG OS was determined by Kaplan - Meier curves. Logistic regression models of multiplicative interactions were constructed. Furthermore, the relationship between GPX1 and LGG treatment regimens was also explored through the Genomics of Drug Sensitivity in Cancer (GDSC) database.

RESULTS

GPX1 was highly expressed in various tumors, GPX1 overexpression was significantly correlated with the poor prognosis of LGG. GPX1 was found to be an independent predictive factor for LGG in both univariate and multivariate Cox models. The nomogram showed a high predictive accuracy (C-index: 0.804, 95% CI: 0.74-0.86). In addition, GPX1 was significantly associated with TMB, MSI, and MMRs in diverse cancers. GPX1 was involved in IL6/JAK/STAT3, inflammatory response, and apoptosis signaling pathways. Besides, non-radiotherapy, chemotherapy, and low GPX1 expression were important factors affecting the better prognosis of LGG. GPX1 acted as a tumor promoter, which has taken the worst effect on LGG survival, but a multiplicative interaction of GPX1*chemoradiotherapy may improve the poor clinical outcome. GPX1 was negatively correlated with the half inhibition concentration (IC50) of temozolomide (TMZ) (Spearman = -0.44, P = 4.52 ×10^-26).

CONCLUSION

In LGG patients, high GPX1 expression was linked to a shorter OS. The interaction between GPX1 and chemoradiotherapy exhibits a beneficial clinical effect and chemotherapy was recommended for LGG patients, especially for those with high GPX1 expression. Besides, high GPX1 expression can predict TMZ sensitivity in LGG, providing potential evidence for chemotherapy. On the whole, this study presents a wealth of biological as well as clinical significance for the roles of GPX1 in human tumors, particularly in LGG.

Metabolism of Selenium, Selenocysteine, and Selenoproteins in Ferroptosis in Solid Tumor Cancers

A potential target of precision nutrition in cancer therapeutics is the micronutrient selenium (Se). Se is metabolized and incorporated as the amino acid selenocysteine (Sec) into 25 human selenoproteins, including glutathione peroxidases (GPXs) and thioredoxin reductases (TXNRDs), among others. Both the processes of Se and Sec metabolism for the production of selenoproteins and the action of selenoproteins are utilized by cancer cells from solid tumors as a protective mechanism against oxidative damage and to resist ferroptosis, an iron-dependent cell death mechanism. Protection against ferroptosis in cancer cells requires sustained production of the selenoprotein GPX4, which involves increasing the uptake of Se, potentially activating Se metabolic pathways such as the trans-selenation pathway and the TXNRD1-dependent decomposition of inorganic selenocompounds to sustain GPX4 synthesis. Additionally, endoplasmic reticulum-resident selenoproteins also affect apoptotic responses in the presence of selenocompounds. Selenoproteins may also help cancer cells adapting against increased oxidative damage and the challenges of a modified nutrient metabolism that result from the Warburg switch. Finally, cancer cells may also rewire the selenoprotein hierarchy and use Se-related machinery to prioritize selenoproteins that are essential to the adaptations against ferroptosis and oxidative damage. In this review, we discuss both the evidence and the gaps in knowledge on how cancer cells from solid tumors use Se, Sec, selenoproteins, and the Se-related machinery to promote their survival particularly via resistance to ferroptosis.