Comprehensive landscape of STEAP family functions and prognostic prediction value in glioblastoma

Copper Homeostasis Based on Cuproptosis-Related Signature Optimizes Molecular Subtyping and Treatment of Glioma

Copper is essential in living organisms and crucial to various physiological processes. Normal physiological conditions are in a state of copper homeostasis to ensure normal biochemical and metabolic processes. Dysregulation of copper homeostasis has been associated with multiple diseases, especially cancer. Cuproptosis is a copper-dependent cell death mediated by excess copper or homeostasis dysregulation. Elesclomol is a common inducer of cuproptosis, carrying copper into the cell and producing excess copper. Cuproptosis modulates tumor proliferation-related signaling pathways and is closely associated with remodeling the tumor microenvironment. In gliomas, the role of cuproptosis and copper homeostasis needs to be better characterized. This study systematically analyzed cuproptosis-related genes (CRGs) and constructed a cuproptosis signature for gliomas. The signature closely links the subtypes and clinical features of glioma patients. The results showed a greater tendency toward dysregulation of copper homeostasis as the malignant grade of glioma patients increased. In addition, CRGs-signature effectively predicted the sensitivity of glioma cells to elesclomol and verified that elesclomol inhibited glioma mainly through inducing cellular cuproptosis. In summary, we found different copper homeostatic features in gliomas and verified the anticancer mechanism of elesclomol, which provides a theoretical basis for developing novel therapeutic strategies for gliomas.

Histone acetylation risk model predicts prognosis and guides therapy selection in glioblastoma: implications for chemotherapy and anti-CTLA-4 immunotherapy

BACKGROUND

Glioblastoma is characterized by high aggressiveness, frequent recurrence, and poor prognosis. Histone acetylation-associated genes have been implicated in its occurrence and development, yet their predictive ability in glioblastoma prognosis remains unclear.

RESULTS

This study constructs a histone acetylation risk model using Cox and LASSO regression analyses to evaluate glioblastoma prognosis. We assessed the model's prognostic ability with univariate and multivariate Cox regression analyses. Additionally, immune infiltration was evaluated using ESTIMATE and TIMER algorithms, and the SubMAP algorithm was utilized to predict responses to CTLA4 inhibitor. Multiple drug databases were applied to assess drug sensitivity in high- and low-risk groups. Our results indicate that the histone acetylation risk model is independent and reliable in predicting prognosis.

CONCLUSIONS

Low-risk patients showed higher immune activity and longer overall survival, suggesting anti-CTLA4 immunotherapy suitability, while high-risk patients might benefit more from chemotherapy. This model could guide personalized therapy selection for glioblastoma patients.

Deciphering glycosylation-driven prognostic insights and therapeutic prospects in glioblastoma through a comprehensive regulatory model

The oncogenesis and development of glioblastoma multiforme have been linked to glycosylation modifications, which are common post-translational protein modifications. Abnormal glycosyltransferase development leads to irregular glycosylation patterns, which hold clinical significance for GB prognosis. By utilizing both single-cell and bulk data, we developed a scoring system to assess glycosylation levels in GB. Moreover, a glycosylation-based signature was created to predict GB outcomes and therapy responsiveness. The study led to the development of an glyco-model incorporating nine key genes. This risk assessment tool effectively stratified GB patients into two distinct groups. Extensive validation through ROC analysis, RMST, and Kaplan-Meier (KM) survival analysis emphasized the model's robust predictive capabilities. Additionally, a nomogram was constructed to predict survival rates at specific time intervals. The research revealed substantial disparities in immune cell infiltration between low-risk and high-risk groups, characterized by differences in immune cell abundance and elevated immune scores. Notably, the glyco-model predicted diverse responses to immune checkpoint inhibitors and drug therapies, with high-risk groups exhibiting a preference for immune checkpoint inhibitors and demonstrated superior responses to drug treatments. Furthermore, the study identified two potential drug targets and utilized Connectivity Map analysis to pinpoint promising therapeutic agents. Clofarabine and YM155 were identified as potent candidates for the treatment of high-risk GB. Our well-crafted glyco-model effectively discriminates patients by calculating the risk score, accurately predicting GB outcomes, and significantly enhancing prognostic assessment while identifying novel immunotherapeutic and chemotherapeutic strategies for GB treatment.

Fluoride Induces Neurocytotoxicity by Disrupting Lysosomal Iron Metabolism and Membrane Permeability

The detrimental effects of fluoride on neurotoxicity have been widely recorded, yet the detailed mechanisms underlying these effects remain unclear. This study explores lysosomal iron metabolism in fluoride-related neurotoxicity, with a focus on the Steap3/TRPML1 axis. Utilizing sodium fluoride (NaF)-treated human neuroblastoma (SH-SY5Y) and mouse hippocampal neuron (HT22) cell lines, our research demonstrates that NaF enhances the accumulation of ferrous ions (Fe2+) in these cells, disrupting lysosomal iron metabolism through the Steap3/TRPML1 axis. Notably, NaF exposure upregulated ACSL4 and downregulated GPX4, accompanied by reduced glutathione (GSH) levels and superoxide dismutase (SOD) activity and increased malondialdehyde (MDA) levels. These changes indicate increased vulnerability to ferroptosis within neuronal cells. The iron chelator deferoxamine (DFO) mitigates this disruption. DFO binds to lysosomal Fe2+ and inhibits the Steap3/TRPML1 axis, restoring normal lysosomal iron metabolism, preventing lysosomal membrane permeabilization (LMP), and reducing neuronal cell ferroptosis. Our findings suggest that interference in lysosomal iron metabolism may mitigate fluoride-induced neurotoxicity, underscoring the critical role of the Steap3/TRPML1 axis in this pathological process.

A Genome-Wide Interaction Study of Erythrocyte ω-3 Polyunsaturated Fatty Acid Species and Memory in the Framingham Heart Study Offspring Cohort

BACKGROUND

Cognitive decline, and more specifically Alzheimer's disease, continues to increase in prevalence globally, with few, if any, adequate preventative approaches. Several tests of cognition are utilized in the diagnosis of cognitive decline that assess executive function, short- and long-term memory, cognitive flexibility, and speech and motor control. Recent studies have separately investigated the genetic component of both cognitive health, using these measures, and circulating fatty acids.

OBJECTIVES

We aimed to examine the potential moderating effect of main species of ω-3 polyunsaturated fatty acids (PUFAs) on an individual's genetically conferred risk of cognitive decline.

METHODS

The Offspring cohort from the Framingham Heart Study was cross-sectionally analyzed in this genome-wide interaction study (GWIS). Our sample included all individuals with red blood cell ω-3 PUFA, genetic, cognitive testing (via Trail Making Tests [TMTs]), and covariate data (N = 1620). We used linear mixed effects models to predict each of the 3 cognitive measures (TMT A, TMT B, and TMT D) by each ω-3 PUFA, single nucleotide polymorphism (SNP) (0, 1, or 2 minor alleles), ω-3 PUFA by SNP interaction term, and adjusting for sex, age, education, APOE ε4 genotype status, and kinship (relatedness).

RESULTS

Our analysis identified 31 unique SNPs from 24 genes reaching an exploratory significance threshold of 1×10-5. Fourteen of the 24 genes have been previously associated with the brain/cognition, and 5 genes have been previously associated with circulating lipids. Importantly, 8 of the genes we identified, DAB1, SORCS2, SERINC5, OSBPL3, CPA6, DLG2, MUC19, and RGMA, have been associated with both cognition and circulating lipids. We identified 22 unique SNPs for which individuals with the minor alleles benefit substantially from increased ω-3 fatty acid concentrations and 9 unique SNPs for which the common homozygote benefits.

CONCLUSIONS

In this GWIS of ω-3 PUFA species on cognitive outcomes, we identified 8 unique genes with plausible biology suggesting individuals with specific polymorphisms may have greater potential to benefit from increased ω-3 PUFA intake. Additional replication in prospective settings with more diverse samples is needed.

Cuproptosis in glioblastoma: unveiling a novel prognostic model and therapeutic potential

Glioblastoma, a notably aggressive brain tumor, is characterized by a brief survival period and resistance to conventional therapeutic approaches. With the recent identification of "Cuproptosis," a copper-dependent apoptosis mechanism, this study aimed to explore its role in glioblastoma prognosis and potential therapeutic implications. A comprehensive methodology was employed, starting with the identification and analysis of 65 cuproptosis-related genes. These genes were subjected to differential expression analyses between glioblastoma tissues and normal counterparts. A novel metric, the "CP-score," was devised to quantify the cuproptosis response in glioblastoma patients. Building on this, a prognostic model, the CP-model, was developed using Cox regression techniques, designed to operate on both bulk and single-cell data. The differential expression analysis revealed 31 genes with distinct expression patterns in glioblastoma. The CP-score was markedly elevated in glioblastoma patients, suggesting an intensified cuproptosis response. The CP-model adeptly stratified patients into distinct risk categories, unveiling intricate associations between glioblastoma prognosis, immune response pathways, and the tumor's immunological environment. Further analyses indicated that high-risk patients, as per the CP-model, exhibited heightened expression of certain immune checkpoints, suggesting potential therapeutic targets. Additionally, the model hinted at the possibility of personalized therapeutic strategies, with certain drugs showing increased efficacy in high-risk patients. The CP-model offers a promising tool for glioblastoma prognosis and therapeutic strategy development, emphasizing the potential of Cuproptosis in cancer treatment.

Deciphering Glioblastoma: Fundamental and Novel Insights into the Biology and Therapeutic Strategies of Gliomas

Gliomas constitute a diverse and complex array of tumors within the central nervous system (CNS), characterized by a wide range of prognostic outcomes and responses to therapeutic interventions. This literature review endeavors to conduct a thorough investigation of gliomas, with a particular emphasis on glioblastoma (GBM), beginning with their classification and epidemiological characteristics, evaluating their relative importance within the CNS tumor spectrum. We examine the immunological context of gliomas, unveiling the intricate immune environment and its ramifications for disease progression and therapeutic strategies. Moreover, we accentuate critical developments in understanding tumor behavior, focusing on recent research breakthroughs in treatment responses and the elucidation of cellular signaling pathways. Analyzing the most novel transcriptomic studies, we investigate the variations in gene expression patterns in glioma cells, assessing the prognostic and therapeutic implications of these genetic alterations. Furthermore, the role of epigenetic modifications in the pathogenesis of gliomas is underscored, suggesting that such changes are fundamental to tumor evolution and possible therapeutic advancements. In the end, this comparative oncological analysis situates GBM within the wider context of neoplasms, delineating both distinct and shared characteristics with other types of tumors.

SMG9 is a novel prognostic-related biomarker in glioma correlating with ferroptosis and immune infiltrates

Background

Glioma is the most frequent type of malignancy that may damage the brain with high morbidity and mortality rates and patients' prognoses are still dismal. Ferroptosis, a newly uncovered mode of programmed cell death, may be triggered to destroy glioma cells. Nevertheless, the significance of ferroptosis-related genes (FRGs) in predicting prognosis in glioma individuals is still a mystery.

Methods

The CGGA (The Chinese Glioma Atlas), GEO (Gene Expression Omnibus), and TCGA (The Cancer Genome Atlas) databases were all searched to obtain the glioma expression dataset. First, TCGA was searched to identify differentially expressed genes (DEGs). This was followed by a machine learning algorithm-based screening of the glioma's most relevant genes. Additionally, these genes were subjected to Gene Ontology (GO) and KEGG (Kyoto Encyclopedia of Genes and Genomes) functional enrichment analyses. The chosen biological markers were then submitted to single-cell, immune function, and gene set enrichment analysis (GSEA). In addition, we performed functional enrichment and Mfuzz expression profile clustering on the most promising biological markers to delve deeper into their regulatory mechanisms and assess their clinical diagnostic capacities.

Results

We identified 4444 DEGs via differential analysis and 564 FRGs from the FerrDb database. The two were subjected to intersection analysis, which led to the discovery of 143 overlapping genes. After that, glioma biological markers were identified in fourteen genes by the use of machine learning methods. In terms of its use for clinical diagnosis, SMG9 stands out as the most significant among these biomarkers.

Conclusion

In light of these findings, the identification of SMG9 as a new biological marker has the potential to provide information on the mechanism of action and the effect of the immune milieu in glioma. The promise of SMG9 in glioma prognosis prediction warrants more study.

A novel prognostic signature and therapy guidance for hepatocellular carcinoma based on STEAP family

BACKGROUND

The six-transmembrane epithelial antigen of prostate (STEAP) family members are known to be involved in various tumor-related biological processes and showed its huge potential role in tumor immunotherapy.

METHODS

Biological differences were investigated through Gene set enrichment analysis (GSEA) and tumor microenvironment analysis by CIBERSORT. Tumor mutation burden (TMB), immunotherapy response and chemotherapeutic drugs sensitivity were estimated in R.

RESULTS

We established a prognostic signature with the formula: risk score = STEAP1 × 0.3994 + STEAP4 × (- 0.7596), which had a favorable concordance with the prediction. The high-risk group were enriched in cell cycle and RNA and protein synthesis related pathways, while the low-risk group were enriched in complement and metabolic related pathways. And the risk score was significantly correlated with immune cell infiltration. Most notably, the patients in the low-risk group were characterized with increased TMB and decreased tumor immune dysfunction and exclusion (TIDE) score, indicating that these patients showed better immune checkpoint blockade response. Meanwhile, we found the patients with high-risk were more sensitive to some drugs related to cell cycle and apoptosis.

CONCLUSIONS

The novel signature based on STEAPs may be effective indicators for predicting prognosis, and provides corresponding clinical treatment recommendations for HCC patients based on this classification.

STEAP4 modulates cell proliferation and oxidative stress in benign prostatic hyperplasia

Benign prostatic hyperplasia (BPH) is a quite common chronic disease plagued elderly men and its etiology remains unclear. It was reported that the six-transmembrane epithelial antigen of prostate 4 (STEAP4) could modulate cell proliferation/apoptosis ratio and oxidative stress in cancers. Our current study aimed to explore the expression, biological function, and underlying mechanism of STEAP4 in BPH progress. Human prostate tissues and cell lines were utilized. qRT-PCR and immunofluorescence staining were employed. STEAP4 knockdown (STEAP4-KD) or STEAP4 overexpression (STEAP4-OE) cell models were established. Cell proliferation, cell cycle, apoptosis, and reactive oxygen species (ROS) were determined by cell counting kit-8 (CCK-8) assay and flow cytometry. Apoptosis-related proteins and antioxidant enzymes were identified by Western Blot. In addition, the epithelial-mesenchymal transition (EMT) process and fibrosis biomarker (collagen I and α-SMA) were analyzed. It was indicated that STEAP4 was mainly located in the prostate epithelium and upregulated in BPH tissues. STEAP4 deficiency induced apoptosis and inhibited cell survival, but had no effect on the cell cycle, fibrosis, and EMT process. In addition, ROS changes were observed in the STEAP4-KD model. Consistently, overproduction of STEAP4 suppressed apoptosis and promoted cell proliferation, as well as facilitated ROS production. We further examined AKT / mTOR, p38MAPK / p-p38MAPK, and WNT/ β-Catenin signaling pathway and demonstrated that STEAP4 regulated the proliferation and apoptosis of prostate cells through AKT / mTOR signaling, rather than p38MAPK / p-p38MAPK and WNT/ β-Catenin pathways. Furthermore, activating AKT / mTOR signaling with SC79 significantly reversed apoptosis triggered by STEAP4 deficiency, whereas suppressing AKT / mTOR signaling with MK2206 reduced the increase of cell viability triggered by STEAP4 overproduction. Our original data demonstrated that STEAP4 is crucial in the onset and progression of prostate hyperplasia and may become a new target for the treatment of BPH.

Knockdown of SLC39A14 inhibits glioma progression by promoting erastin-induced ferroptosis SLC39A14 knockdown inhibits glioma progression

BACKGROUND

Ferroptosis is a newly classified form of regulated cell death with implications in various tumor progression pathways. However, the roles and mechanisms of ferroptosis-related genes in glioma remain unclear.

METHODS

Bioinformatics analysis was employed to identify differentially expressed ferroptosis-related genes in glioma. The expression levels of hub genes were assessed using real-time reverse transcriptase-polymerase chain reaction (RT-qPCR). To explore the role of SLC39A14 in glioma, a series of in vitro assays were conducted, including cell counting kit-8 (CCK-8), 5-ethynyl-2'-deoxyuridine (EdU), flow cytometry, wound healing, and Transwell assays. Enzyme-linked immunosorbent assay (ELISA) was utilized to measure the levels of indicators associated with ferroptosis. Hematoxylin-eosin (HE) and immunohistochemistry (IHC) staining were performed to illustrate the clinicopathological features of the mouse transplantation tumor model. Additionally, Western blot analysis was used to assess the expression of the cGMP-PKG pathway-related proteins.

RESULTS

Seven ferroptosis-related hub genes, namely SLC39A14, WWTR1, STEAP3, NOTCH2, IREB2, HIF1A, and FANCD2, were identified, all of which were highly expressed in glioma. Knockdown of SLC39A14 inhibited glioma cell proliferation, migration, and invasion, while promoting apoptosis. Moreover, SLC39A14 knockdown also facilitated erastin-induced ferroptosis, leading to the suppression of mouse transplantation tumor growth. Mechanistically, SLC39A14 knockdown inhibited the cGMP-PKG signaling pathway activation.

CONCLUSION

Silencing SLC39A14 inhibits ferroptosis and tumor progression, potentially involving the regulation of the cGMP-PKG signaling pathway.

Transcriptomic Characterization of Copper-Binding Proteins for Predicting Prognosis in Glioma

BACKGROUND

Copper and copper-binding proteins are key components of tumor progression as they play important roles in tumor invasion and migration, but their associations in gliomas remain unclear.

METHODS

Transcriptomic datasets of glioblastoma, low-grade glioma, and normal brain cortex were derived from the TCGA and GTEX databases. Differentially expressed genes (DEGs) of copper-binding proteins were screened and used to construct a prognostic model based on COX and LASSO regression, which was further validated by the CGGA datasets. The expressions of risk-model genes were selectively confirmed via anatomic feature-based expression analysis and immunohistochemistry. The risk score was stratified by age, gender, WHO grade, IDH1 mutation, MGMT promoter methylation, and 1p/19q codeletion status, and a nomogram was constructed and validated.

RESULTS

A total of 21 DEGs of copper-binding proteins were identified and a six-gene risk-score model was constructed, consisting of ANG, F5, IL1A, LOXL1, LOXL2, and STEAP3, which accurately predicted 1-, 3-, and 5-year overall survival rates, with the AUC values of 0.87, 0.88, and 0.82, respectively. The high-risk group had a significantly shorter OS (p < 0.0001) and was associated with old age, wild-type IDH1, a high WHO grade, an unmethylated MGMT promoter, and 1p/19q non-codeletion and had higher levels of immune cell infiltration, cancer-immunity suppressor, and immune checkpoint gene expression as well as a higher TMB.

CONCLUSIONS

The model based on the genes of copper-binding proteins could contribute to prognosis prediction and provide potential targets against gliomas.

Ferroptosis-related STEAP3 acts as predictor and regulator in diffuse large B cell lymphoma through immune infiltration

Diffuse large B cell lymphoma (DLBCL) is a usual-seen hematological malignant tumor possessing molecular and genetic heterogeneity. Ferroptosis induction has been increasingly acknowledged to be an advantageous therapeutic method in tumor treatment by triggering cell death of tumor cells. However, studies on the function of ferroptosis in DLBCL remain scarce, especially the interaction with the tumor immune microenvironment (TIME). The clinical and biological functions of ferroptosis-related genes in DLBCL were still warranted to be explored. A ferroptosis-related risk model was constructed, followed by functional enrichment analyses and evaluation of immune profile. Quantitative real-time PCR, western blotting, and immunohistochemistry were conducted to examine the RNA and protein levels. Dysregulated expression of the major ferroptosis-related genes was found in DLBCL. A prognostic risk model based on 10 ferroptosis-related genes was constructed. The risk score served as an independent prognostic indicator for DLBCL patients in univariate and multivariate Cox regression analysis. Patients with low-risk scores presented a more favorable prognosis. Functional enrichment analysis revealed that immune-related pathways were significantly enriched, and the high-risk group exhibited less immunocyte infiltration, lower immunoscore, and downregulated PD-L1 expression relative to the low-risk group. Two molecular subtypes were determined through consensus clustering of the expression of ferroptosis-related genes. Cluster 1 was relevant to favorable prognosis, higher immunoscore, and elevated PD-L1 expression. More importantly, STEAP3 was screened as a reliable biomarker for DLBCL, and its enhanced expression levels of mRNA and protein were verified in public databases and clinical specimens. Our study demonstrated the crucial role of ferroptosis-related genes including STEAP3 in the TIME of DLBCL and identified promising novel molecular targets for DLBCL treatment.

The role of novel programmed cell death in head and neck squamous cell carcinoma: from mechanisms to potential therapies

Head and neck squamous cell carcinoma (HNSCC) is a common oral cancer with poor prognosis and for which no targeted therapeutic strategies are currently available. Accumulating evidence has demonstrated that programmed cell death (PCD) is essential in the development of HNSCC as a second messenger. PCD can be categorized into numerous different subroutines: in addition to the two well-known types of apoptosis and autophagy, novel forms of programmed cell death (e.g., necroptosis, pyroptosis, ferroptosis, and NETosis) also serve as key alternatives in tumorigenesis. Cancer cells are not able to avoid all types of cell death simultaneously, since different cell death subroutines follow different regulatory pathways. Herein, we summarize the roles of novel programmed cell death in tumorigenesis and present our interpretations of the molecular mechanisms with a view to the development of further potential therapies.

The PANoptosis-related signature indicates the prognosis and tumor immune infiltration features of gliomas

Background

Gliomas are the most common primary tumors of the central nervous system, with high heterogeneity and highly variable survival rates. Accurate classification and prognostic assessment are key to the selection of treatment strategies. One hallmark of the tumor is resistance to cell death. PANoptosis, a novel mode of programmed cell death, has been frequently reported to be involved in the innate immunity associated with pathogen infection and played an important role in cancers. However, the intrinsic association of PANoptosis with glioma requires deeper investigation.

Methods

The genetics and expression of the 17 reported PANoptosome-related genes were analyzed in glioma. Based on these genes, patients were divided into two subtypes by consensus clustering analysis. After obtaining the differentially expressed genes between clusters, a prognostic model called PANopotic score was constructed after univariate Cox regression, LASSO regression, and multivariate Cox regression. The expression of the 5 genes included in the PANopotic score was also examined by qPCR in our cohort. The prognostic differences, clinical features, TME infiltration status, and immune characteristics between PANoptotic clusters and score groups were compared, some of which even extended to pan-cancer levels.

Results

Gene mutations, CNVs and altered gene expression of PANoptosome-related genes exist in gliomas. Two PANoptotic clusters were significantly different in prognosis, clinical features, immune characteristics, and mutation landscapes. The 5 genes included in the PANopotic score had significantly altered expression in glioma samples in our cohort. The high PANoptotic score group was inclined to show an unfavorable prognosis, lower tumor purity, worse molecular genetic signature, and distinct immune characteristics related to immunotherapy. The PANoptotic score was considered as an independent prognostic factor for glioma and showed superior prognostic assessment efficacy over several reported models. PANopotic score was included in the nomogram constructed for the potential clinical prognostic application. The associations of PANoptotic score with prognostic assessment and tumor immune characteristics were also reflected at the pan-cancer level.

Conclusion

Molecular subtypes of glioma based on PANoptosome-related genes were proposed and PANoptotic score was constructed with different clinical characteristics of anti-tumor immunity. The potential intrinsic association between PANoptosis and glioma subtypes, prognosis, and immunotherapy was revealed.

Identification of STEAP3-based molecular subtype and risk model in ovarian cancer

BACKGROUND

Ovarian cancer (OC) is one of the most common malignancies in women. It has a poor prognosis owing to its recurrence and metastasis. Unfortunately, reliable markers for early diagnosis and prognosis of OC are lacking. Our research aimed to investigate the value of the six-transmembrane epithelial antigen of prostate family member 3 (STEAP3) as a prognostic predictor and therapeutic target in OC using bioinformatics analysis.

METHODS

STEAP3 expression and clinical data were acquired from The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), and Gene Expression Omnibus (GEO). Unsupervised clustering was used to identify molecular subtypes. Prognosis, tumor immune microenvironment (TIME), stemness indexes, and functional enrichment analysis were compared between two definite clusters. Through the least absolute shrinkage and selection operator (LASSO) regression analysis, a STEAP3-based risk model was developed, and the predictive effectiveness of this signature was confirmed using GEO datasets. A nomogram was used to predict the survival possibility of patients. Additionally, TIME, tumor immune dysfunction and exclusion (TIDE), stemness indexes, somatic mutations, and drug sensitivity were evaluated in different risk groups with OC. STEAP3 protein expression was detected using immunohistochemistry (IHC).

RESULTS

STEAP3 displayed marked overexpression in OC. STEAP3 is an independent risk factor for OC. Based on the mRNA levels of STEAP3-related genes (SRGs), two distinct clusters were identified. Patients in the cluster 2 (C2) subgroup had a considerably worse prognosis, higher immune cell infiltration, and lower stemness scores. Pathways involved in tumorigenesis and immunity were highly enriched in the C2 subgroup. A prognostic model based on 13 SRGs was further developed. Kaplan-Meier analysis indicated that the overall survival (OS) of high-risk patients was poor. The risk score was significantly associated with TIME, TIDE, stemness indexes, tumor mutation burden (TMB), immunotherapy response, and drug sensitivity. Finally, IHC revealed that STEAP3 protein expression was noticeably elevated in OC, and overexpression of STEAP3 predicted poor OS and relapse-free survival (RFS) of patients.

CONCLUSION

In summary, this study revealed that STEAP3 reliably predicts patient prognosis and provides novel ideas for OC immunotherapy.

High expression of six-transmembrane epithelial antigen of prostate 3 promotes the migration and invasion and predicts unfavorable prognosis in glioma

Recent studies have suggested that ferroptosis, a form of iron-dependent regulated cell death, might play essential roles in tumor initiation and progression. Six-transmembrane epithelial antigen of prostate 3 (STEAP3) is a ferrireductase involved in the regulation of intracellular iron homeostasis. However, the clinical significance and biological function of STEAP3 in human cancers remain poorly understood. Through a comprehensive bioinformatics analysis, we found that STEAP3 mRNA and protein expression were up-regulated in GBM, LUAD, and UCEC, and down-regulated in LIHC. Survival analysis indicated that STEAP3 had prognostic significance only in glioma. Multivariate Cox regression analysis revealed that high STEPA3 expression was correlated with poor prognosis. STEAP3 expression was significantly negatively correlated with promoter methylation level, and patients with lower STEAP3 methylation level had worse prognosis than those with higher STEAP3 methylation level. Single-cell functional state atlas showed that STEAP3 regulated epithelial-to-mesenchymal transition (EMT) in GBM. Furthermore, the results of wound healing and transwell invasion assays demonstrated that knocking down STEAP3 inhibited the migration and invasion of T98G and U251 cells. Functional enrichment analysis suggested that genes co-expressed with STEAP3 mainly participated in inflammation and immune-related pathways. Immunological analysis revealed that STEAP3 expression was significantly correlated with immune infiltration cells, including macrophages and neutrophils, especially the M2 macrophages. Individuals with low STEAP3 expression were more likely to respond to immunotherapy than those with high STEAP3 expression. These results suggest that STEAP3 promotes glioma progression and highlight its pivotal role in regulating immune microenvironment.

Prognostic Significance of Iron Metabolism Related Genes in Human Lung Adenocarcinoma

Background

Iron metabolism related genes participate in cell proliferation, cell growth, and redox cycling in multiple cancers. Limited studies have revealed the roles and clinical significance of iron metabolism in the pathogenesis and prognosis of lung cancer.

Methods

A total of 119 iron metabolism related genes were extracted from MSigDB database and their prognostic values were determined in The Cancer Genome Atlas lung adenocarcinoma (TCGA-LUAD) dataset and the Gene Expression Profiling Interactive Analysis 2 (GEPIA 2) database. Immunohistochemistry technique and correlations with immune cell infiltration, gene mutation and drug resistance were used to identify the potential and underlying mechanisms of STEAP1 and STEAP2 as prognostic biomarkers of LUAD.

Results

The expression of STEAP1 and STEAP2 are negatively associated with the prognosis of LUAD patients both at the mRNA and protein level. The expression of STEAP1 and STEAP2 was not only negatively correlated with the trafficking degree of CD4+ T immune cells and positively related to most immune cells' trafficking degree, but also significantly associated with gene mutation status, particularly with mutations on TP53 and STK11. Four types of drug resistance showed significant correlation with the expression level of STEAP1 while 13 types of drug resistance were associated with the expression level of STEAP2.

Conclusion

Multiple iron metabolism related genes including STEAP1 and STEAP2 are significantly associated with the prognosis of LUAD patients. STEAP1 and STEAP2 might affect the prognosis of LUAD patients partially through immune cell infiltration, gene mutation and drug resistance, which indicated they were independent prognostic factors for LUAD patients.

Six-Transmembrane Epithelial Antigen of Prostate 4: An Indicator of Prognosis and Tumor Immunity in Hepatocellular Carcinoma

Purpose

The six-transmembrane epithelial antigen of prostate 4 (STEAP4) has been linked to tumor progression via its involvement in inflammatory responses, oxidative stress, and metabolism. However, STEAP4 has rarely been studied in hepatocellular carcinoma (HCC). We explored STEAP4 expression associated with tumor prognosis to understand its role in tumor biology in HCC.

Patients and Methods

STEAP4 mRNA and protein expressions were primarily analyzed using bioinformatics tools based on The Cancer Genome Atlas database to understand the expression pattern, molecular mechanism, prognostic impact, and association with immune cell infiltration. We further investigated the association between STEAP4 protein expression and clinicopathological parameters and their predictive value in HCC patients using immunohistochemical staining of tissue microarrays.

Results

The expression of STEAP4 mRNA and protein in HCC tissues was significantly lower than in normal liver tissues. Reduced expression of STEAP4 was linked to advanced HCC stages, poor recurrence-free survival (RFS), and overall survival. Furthermore, reduced STEAP4 expression was a significant predictor of worse RFS in univariate and multivariate analyses in the immunohistochemical cohort. GO, KEGG, and GSEA analyses revealed that STEAP4 is related to numerous biological processes and pathways, including drug metabolism, DNA replication, RNA metabolism, and immune response. In terms of the immune system, the decreased level of STEAP4 was correlated with the immunosuppressive microenvironment.

Conclusion

Our data indicated that reduced STEAP4 expression was significantly associated with tumor aggressiveness and poor prognosis, possibly because of its link to various biological processes and induction of HCC immune evasion. Therefore, STEAP4 expression may serve as a potential prognostic biomarker for cancer progression and immunity, as well as a therapeutic target in HCC.

Clinicopathological and prognostic significance of COX-2 in glioma patients: a meta-analysis

BACKGROUND

In recent years, cyclooxygenase-2 (COX-2) has been identified as a cancer stem cell (CSC) marker in gliomas. Nevertheless, the clinical and prognostic significance of COX-2 in glioma patients remains controversial.

OBJECTIVE

To evaluate the correlation of COX-2 with the prognosis in glioma patients.

METHODS

Eligible studies on this subject were included, and pooled odd ratios (ORs) and hazard ratios (HRs) with 95% confidence intervals (95%CIs) were estimated. Publication bias was assessed through funnel plots, and heterogeneity and sensitivity were analyzed as well.

RESULTS

In the present study, 11 articles with a total of 641 patients were included. The high expression of COX-2 in glioma patients was negatively associated with overall survival (OS) (n = 11; HR = 2.26; 95%CI = 1.79-2.86), and the subgroup analysis showed no differences in OS between Asian (n = 5; HR = 2.16; 95%CI = 1.57-2.97) and non-Asian (n = 6; HR = 2.39; 95%CI = 1.69-3.38) glioma patients. The Begg funnel plots test indicated that there was no evident risk of publication bias in the meta-analysis.

CONCLUSION

The present study suggests that COX-2 could be recommended as a useful pathological and prognostic biomarker in the clinical practice.

STEAP3 can predict the prognosis and shape the tumor microenvironment of clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is a common malignant tumor of the urinary system characterized by poor prognosis and difficult treatment. It has been reported that iron metabolism dysregulation is a common phenomenon in ccRCC and is closely related to the process of ccRCC. But still now, the exact function and underlying mechanisms of iron metabolism dysregulation in ccRCC have not been fully elucidated. In this study, we comprehensively investigated the prognostic value and potential role of STEAP3 (an iron metabolism-related gene) in ccRCC. STEAP3 is significantly up-regulated in ccRCC. High STEAP3 expression is associated with gender, hemoglobin level, pathological grade, tumor stage and significantly predicts an unfavorable prognosis of ccRCC patients. Functional enrichment analysis and evaluation of the tumor microenvironment indicated that STEAP3 was involved in the remodeling of tumor extracellular matrix and the shaping of an immune-suppressive tumor microenvironment to promote tumor metastasis and evade immune killing. Besides, the expression of STEAP3 is also associated with the expression of various immune checkpoint molecules and the IC50 of targeted drugs. Finally, we verified STEAP3 by RT-qPCR and IHC staining. In conclusion, we found that STEAP3 can serve as a candidate prognostic biomarker for ccRCC, and targeting STEAP3 and its biological processes may provide new references for the individualized treatment of ccRCC.

Ferroptosis and Its Potential Role in Glioma: From Molecular Mechanisms to Therapeutic Opportunities

Glioma is the most common intracranial malignant tumor, and the current main standard treatment option is a combination of tumor surgical resection, chemotherapy and radiotherapy. Due to the terribly poor five-year survival rate of patients with gliomas and the high recurrence rate of gliomas, some new and efficient therapeutic strategies are expected. Recently, ferroptosis, as a new form of cell death, has played a significant role in the treatment of gliomas. Specifically, studies have revealed key processes of ferroptosis, including iron overload in cells, occurrence of lipid peroxidation, inactivation of cysteine/glutathione antiporter system Xc- (xCT) and glutathione peroxidase 4 (GPX4). In the present review, we summarized the molecular mechanisms of ferroptosis and introduced the application and challenges of ferroptosis in the development and treatment of gliomas. Moreover, we highlighted the therapeutic opportunities of manipulating ferroptosis to improve glioma treatments, which may improve the clinical outcome.

Recent Advances in Copper-Based Organic Complexes and Nanoparticles for Tumor Theranostics

Treatment of drug-resistant forms of cancer requires consideration of their hallmark features, such as abnormal cell death mechanisms or mutations in drug-responding molecular pathways. Malignant cells differ from their normal counterparts in numerous aspects, including copper metabolism. Intracellular copper levels are elevated in various cancer types, and this phenomenon could be employed for the development of novel oncotherapeutic approaches. Copper maintains the cell oxidation levels, regulates the protein activity and metabolism, and is involved in inflammation. Various copper-based compounds, such as nanoparticles or metal-based organic complexes, show specific activity against cancer cells according to preclinical studies. Herein, we summarize the major principles of copper metabolism in cancer cells and its potential in cancer theranostics.

STEAP1-4 (Six-Transmembrane Epithelial Antigen of the Prostate 1-4) and Their Clinical Implications for Prostate Cancer

Simple Summary

Despite recent therapeutic advances in the treatment of prostate cancer, metastatic castration-resistant prostate cancer continues to cause significant morbidity and mortality. New research into highly expressed proteins in metastatic castration-resistant prostate cancer shows that Six-Transmembrane Epithelial Antigen of the Prostate 1–4 (STEAP1–4) are significant drivers of prostate cancer aggressiveness and metastasis. STEAP1, in particular, is highly expressed on the plasma membrane of prostate cancer cells and has received significant attention as a potential therapeutic target. This review highlights what is known about STEAP1–4 and identifies knowledge gaps that require further research.

Abstract

Six-Transmembrane Epithelial Antigen of the Prostate 1–4 (STEAP1–4) compose a family of metalloproteinases involved in iron and copper homeostasis and other cellular processes. Thus far, five homologs are known: STEAP1, STEAP1B, STEAP2, STEAP3, and STEAP4. In prostate cancer, STEAP1, STEAP2, and STEAP4 are overexpressed, while STEAP3 expression is downregulated. Although the metalloreductase activities of STEAP1–4 are well documented, their other biological functions are not. Furthermore, the properties and expression levels of STEAP heterotrimers, homotrimers, heterodimers, and homodimers are not well understood. Nevertheless, studies over the last few decades have provided sufficient impetus to investigate STEAP1–4 as potential biomarkers and therapeutic targets for prostate cancer. In particular, STEAP1 is the target of many emerging immunotherapies. Herein, we give an overview of the structure, physiology, and pathophysiology of STEAP1–4 to provide context for past and current efforts to translate STEAP1–4 into the clinic.

Nomograms for prognostic risk assessment in glioblastoma multiforme: Applications and limitations

Glioblastoma multiforme (GBM) is the most common and aggressive form of brain cancer. Prognosis evaluation is of great significance in guiding individualized treatment and monitoring of GBM. By integrating different prognostic variables, nomograms simplify the statistical risk prediction model into numerical estimates for death or recurrence, and are hence widely applied in prognosis prediction. In the past two decades, the application of high-throughput profiling technology and the establishment of TCGA database and other public data deposits have provided opportunities to identify cancer-related molecules and prognostic biomarkers. As a result, both molecular features and clinical characteristics of cancer have been reported to be the key factors in nomogram model construction. This article comprehensively reviewed 35 studies of GBM nomograms, analyzed the present situation of GBM nomograms, and discussed the role and significance of nomograms in personalized risk assessment and clinical treatment decision-making. To facilitate the application of nomograms in the prognostic prediction of GBM patients, a website has been established for the online access of nomograms based on the studies of this review, which is called Consensus Nomogram Spectrum for Glioblastoma (CNSgbm) and is accessible through https://bioinfo.henu.edu.cn/nom/NomList.jsp.

Identification of a pyroptosis-related prognosis gene signature and its relationship with an immune microenvironment in gliomas

BACKGROUND

Glioma is the most common type of primary brain cancer, and the prognosis of most patients with glioma is poor. Pyroptosis is a newly discovered inflammatory programmed cell death. However, the expression of pyroptosis-related genes (PRGs) in glioma and its correlation with prognosis are unclear.

METHODS

27 pyroptosis genes differentially expressed between glioma and adjacent normal tissues were identified. All glioma cases could be stratified into 2 subtypes based on these differentially expressed PRGs. The prognostic value of each PRG was evaluated to construct a prognostic model.

RESULTS

A novel 16-gene signature was constructed by using the least absolute shrinkage and selection operator Cox regression method. Then, patients with glioma were divided into low- and high-risk groups in the TCGA cohort. The survival rate of patients in the low-risk group was significantly higher than that in the high-risk group (P = .001). Patients with glioma from the Gene Expression Omnibus (GEO) cohort were stratified into 2 risk groups by using the median risk score. The overall survival (OS) of the low-risk group was longer than that of the high-risk group (P = .001). The risk score was considered an independent prognostic factor of the OS of patients with glioma. Gene ontology and Kyoto Encylopedia of Genes and Genomes analysis showed that the differentially expressed PRGs were mainly related to neutrophil activation involved in immune responses, focal adhesion, cell cycle, and p53 signaling pathway.

CONCLUSION

PRGs could predict the prognosis of glioma and play significant roles in a tumor immune microenvironment.

A Ferroptosis Molecular Subtype-Related Signature for Predicting Prognosis and Response to Chemotherapy in Patients with Chronic Lymphocytic Leukemia

Ferroptosis is a type of regulated cell death catalyzed by the iron-dependent accumulation of lipid hydroperoxides to lethal levels. Chronic lymphocytic leukemia (CLL) is a chronic lymphoproliferative disorder. However, the understanding of ferroptosis in CLL remains largely poor. In this study, we investigated the stratification and prognostic role of ferroptosis-related genes in CLL patients of ICGC cohort. We obtained fourteen genes with prognostic value by screening 110 ferroptosis-related genes (FRGs). Based on the expression profiles of these 14 genes, we classified CLL patients into two clusters. Most of the FRGs were highly expressed in cluster 1, and cluster 1 was associated with better overall survival (OS). Subsequently, we developed an eight-gene signature (TP63, STEAP3, NQO1, ELAVL1, PRKAA1, HELLS, FANCD2, and CDKN2A) by using LASSO analysis. This risk signature divided CLL patients into high- and low-risk groups. We used Cox regression analysis and ROC analysis demonstrated the risk signature was reliable and robust. And we validated the risk model in an external cohort (GSE22762). We also conducted enrichment analysis and genomic mutation analysis. Finally, we explored the potential effect of chemotherapy between the two risk groups. Our study contributed to understanding the role of ferroptosis in CLL and facilitated personalized and precision treatment.

Ferroptosis Modulation: Potential Therapeutic Target for Glioblastoma Treatment

Glioblastoma multiforme is a lethal disease and represents the most common and severe type of glioma. Drug resistance and the evasion of cell death are the main characteristics of its malignancy, leading to a high percentage of disease recurrence and the patients’ low survival rate. Exploiting the modulation of cell death mechanisms could be an important strategy to prevent tumor development and reverse the high mortality and morbidity rates in glioblastoma patients. Ferroptosis is a recently described type of cell death, which is characterized by iron accumulation, high levels of polyunsaturated fatty acid (PUFA)-containing phospholipids, and deficiency in lipid peroxidation repair. Several studies have demonstrated that ferroptosis has a potential role in cancer treatment and could be a promising approach for glioblastoma patients. Thus, here, we present an overview of the mechanisms of the iron-dependent cell death and summarize the current findings of ferroptosis modulation on glioblastoma including its non-canonical pathway. Moreover, we focused on new ferroptosis-inducing compounds for glioma treatment, and we highlight the key ferroptosis-related genes to glioma prognosis, which could be further explored. Thereby, understanding how to trigger ferroptosis in glioblastoma may provide promising pharmacological targets and indicate new therapeutic approaches to increase the survival of glioblastoma patients.

A Novel CRISPR/Cas9 Screening Potential Index for Prognostic and Immunological Prediction in Low-Grade Glioma

Glioma is a malignancy with the highest mortality in central nervous system disorders. Here, we implemented the computational tools based on CRISPR/Cas9 to predict the clinical outcomes and biological characteristics of low-grade glioma (LGG). The transcriptional expression profiles and clinical phenotypes of LGG patients were retrieved from The Cancer Genome Atlas and Chinese Glioma Genome Atlas. The CERES algorithm was used to screen for LGG-lethal genes. Cox regression and random survival forest were adopted for survival-related gene selection. Nonnegative matrix factorization distinguished patients into different clusters. Single-sample gene set enrichment analysis was employed to create a novel CRISPR/Cas9 screening potential index (CCSPI), and patients were stratified into low- and high-CCSPI groups. Survival analysis, area under the curve values (AUCs), nomogram, and tumor microenvironment exploration were included for the model validation. A total of 20 essential genes in LGG were used to classify patients into two clusters and construct the CCSPI system. High-CCSPI patients were associated with a worse prognosis of both training and validation set (p < 0.0001) and higher immune fractions than low-CCSPI individuals. The CCSPI system had a promising performance with 1-, 3-, and 5-year AUCs of 0.816, 0.779, 0.724, respectively, and the C-index of the nomogram model reached 0.743 (95% CI = 0.725–0.760). Immune-infiltrating cells and immune checkpoints such as PD-1/PD-L1 and POLD3 were positively associated with CCSPI. In conclusion, the CCSPI had prognostic value in LGG, and the model will deepen our cognition of the interaction between the CNS and immune system in different LGG subtypes.

Comprehensive Landscape of STEAP Family Members Expression in Human Cancers: Unraveling the Potential Usefulness in Clinical Practice Using Integrated Bioinformatics Analysis

The human Six-Transmembrane Epithelial Antigen of the Prostate (STEAP) family comprises STEAP1-4. Several studies have pointed out STEAP proteins as putative biomarkers, as well as therapeutic targets in several types of human cancers, particularly in prostate cancer. However, the relationships and significance of the expression pattern of STEAP1-4 in cancer cases are barely known. Herein, the Oncomine database and cBioPortal platform were selected to predict the differential expression levels of STEAP members and clinical prognosis. The most common expression pattern observed was the combination of the over- and underexpression of distinct STEAP genes, but cervical and gastric cancer and lymphoma showed overexpression of all STEAP genes. It was also found that STEAP genes’ expression levels were already deregulated in benign lesions. Regarding the prognostic value, it was found that STEAP1 (prostate), STEAP2 (brain and central nervous system), STEAP3 (kidney, leukemia and testicular) and STEAP4 (bladder, cervical, gastric) overexpression correlate with lower patient survival rate. However, in prostate cancer, overexpression of the STEAP4 gene was correlated with a higher survival rate. Overall, this study first showed that the expression levels of STEAP genes are highly variable in human cancers, which may be related to different patients’ outcomes.

Modulation of Tumor Immune Microenvironment and Prognostic Value of Ferroptosis-Related Genes, and Candidate Target Drugs in Glioblastoma Multiforme

Glioblastoma multiforme (GBM) is the most common type of malignant brain tumor, among which IDH1-wild type GBM has a poor prognosis. Recent studies have shown that ferroptosis-related genes (FRGs) are correlated with the development and progression of cancer. In GBM, the role of FRGs associated with IDH1 status as biological indicators and therapeutic targets remains to be clarified. Ten of FRGs (STEAP3, HSPB1, MAP1LC3A, SOCS1, LOX, CAPG, CP, GDF15, CDKN1A, and CD44) associated with IDH1 status in GBM were identified as key genes through screening by survival analysis and Random Forest using The Cancer Genome Atlas (TCGA) datasets, and the protein expressions of key genes were verified. Transwell and qPCR results showed that ferroptosis promoted the migration of glioblastoma cells and affected the expression of key genes. Our study established the ferroptosis-related prognostic model for GBM patients based on ten key genes by a different modeling method from previous study, the GSVA algorithm. Further, we took the methods of functional enrichment analysis, clinical characteristics, immune cell infiltration, immunomodulator, ESTIMATE and single nucleotide variant (SNV) analysis to study the molecular mechanisms of prognostic model and key genes. The results showed that ten key genes were strongly associated with immune-related factors and were significantly involved in the p53 signaling pathway, senescence and autophagy in cancer, and in the negative regulation of protein kinase activity. Moreover, potential therapeutic drugs were identified by Virtual Screening and Molecular Docking. Our study indicated that the novel ferrotosis-related prognostic model for GBM patients and key genes possessed the prognostic and therapeutic values.

METTL3-mediated m6A modification of STEAP2 mRNA inhibits papillary thyroid cancer progress by blocking the Hedgehog signaling pathway and epithelial-to-mesenchymal transition

Papillary thyroid cancer (PTC) is a common endocrine system malignancy all over the world. Aberrant expression of six transmembrane epithelial antigen of the prostate 2 (STEAP2) has been functionally associated with cancer progression in many cancers. Nevertheless, its biological function in PTC is still unclear. Here, we found that PTC tissues had preferentially downregulated STEAP2 as compared with noncancerous tissues. Low STEAP2 expression correlated with aggressive clinicopathological characteristics and dismal prognosis in patients with PTC. We performed gain- and loss-of-function experiments, including cell proliferation assay (Cell Counting Kit-8 assay), EdU (5-ethynyl-2'-deoxyuridine) and colony formation assays, transwell migration, and invasion assays, and constructed a nude mouse xenograft tumor model. The results demonstrated that STEAP2 overexpression inhibited PTC cell proliferation, migration, and invasion in vitro and inhibited lung metastasis and tumorigenicity in vivo. Conversely, silencing STEAP2 yielded the opposite results in vitro. Mechanistically, bioinformatics analysis combined with validation experiments identified STEAP2 as the downstream target of methyltransferase-like 3 (METTL3)-mediated N6-methyladenosine (m6A) modification. METTL3 stabilized STEAP2 mRNA and regulated STEAP2 expression positively in an m6A-dependent manner. We also showed that m6A-mediated STEAP2 mRNA translation initiation relied on a pathway dependent on the m6A reader protein YTHDF1. Rescue experiments revealed that silencing STEAP2 partially rescued the tumor-suppressive phenotype induced by METTL3 overexpression. Lastly, we verified that the METTL3-STEAP2 axis functions as an inhibitor in PTC by suppressing epithelial-mesenchymal transition and the Hedgehog signaling pathway. Taken together, these findings strongly suggest that METTL3-mediated STEAP2 m6A modification plays a critical tumor-suppressive role in PTC progression. The METTL3-STEAP2 axis may be a potential therapeutic molecular target against PTC.

Expression and prognostic analyses of the significance of STEAP1 and STEAP2 in lung cancer

PURPOSE

Lung cancer is the leading cause of cancer-related mortality. STEAP1 and STEAP2 are overexpressed in various cancers. The purpose of this study was to evaluate the expression and prognostic value of STEAP1 and STEAP2 in patients with lung cancer.

METHODS

The mRNA expression and protein expression of STEAP1 and STEAP2 and their prognostic characteristics were examined using Oncomine, GEPIA, and Kaplan-Meier (KM) plotters. The correlation analysis of STEAP1 and STEAP2 gene and protein levels was conducted using GeneMANIA and STRING. KEGG pathway analysis was used to explore the related signal pathways of STEAP 1 and STEAP2. Immunohistochemical methods were used to compare the expression of STEAP2 in normal lung and non-small cell lung cancer (NSCLC) tissues. Real-time quantitative polymerase chain reaction, western blotting, and immunocytochemistry were used to evaluate the expression of STEAP1 and STEAP2 in three lung cancer cell lines and normal lung epithelial cell lines.

RESULTS

Analysis of the Oncomine database and GEPIA showed that STEAP1 was upregulated and STEAP2 was downregulated in lung cancer tissue, and both expressions were related to the clinical stage of lung cancer. Immunohistochemical analysis showed that STEAP1 protein expression was significantly upregulated in lung cancer compared to that in adjacent tissues. The expression of STEAP1 was positively correlated with the migration and invasion abilities of lung cancer cells. Compared with paracancer tissues, the expression of STEAP2 protein in lung cancer was significantly downregulated and was correlated with the histological grade of squamous cell carcinoma, pathological classification of adenocarcinoma, tumor, lymph node, and metastasis clinical stage, and lymph node metastasis. The expression of STEAP2 was negatively correlated with the migration and invasion abilities of lung cancer cells. The KM curve showed that the downregulation of STEAP1 expression and upregulation of STEAP2 expression were related to a good lung cancer prognosis.

CONCLUSION

STEAP1 and STEAP2 are expected to be potential diagnostic and prognostic markers for lung cancer, which may provide more accurate prognostic indicators for lung cancer.

Ferroptosis Involvement in Glioblastoma Treatment

Glioblastoma multiforme (GBM) is one of the deadliest brain tumors. Current standard therapy includes tumor resection surgery followed by radiotherapy and chemotherapy. Due to the tumors invasive nature, recurrences are almost a certainty, giving the patients after diagnosis only a 12–15 months average survival time. Therefore, there is a dire need of finding new therapies that could potentially improve patient outcomes. Ferroptosis is a newly described form of cell death with several implications in cancer, among which GBM. Agents that target different molecules involved in ferroptosis and that stimulate this process have been described as potentially adjuvant anti-cancer treatment options. In GBM, ferroptosis stimulation inhibits tumor growth, improves patient survival, and increases the efficacy of radiation and chemotherapy. This review provides an overview of the current knowledge regarding ferroptosis modulation in GBM.

DNA Methylation-Driven Genes for Developing Survival Nomogram for Low-Grade Glioma

Low-grade gliomas (LGG) are heterogeneous, and the current predictive models for LGG are either unsatisfactory or not user-friendly. The objective of this study was to establish a nomogram based on methylation-driven genes, combined with clinicopathological parameters for predicting prognosis in LGG. Differential expression, methylation correlation, and survival analysis were performed in 516 LGG patients using RNA and methylation sequencing data, with accompanying clinicopathological parameters from The Cancer Genome Atlas. LASSO regression was further applied to select optimal prognosis-related genes. The final prognostic nomogram was implemented together with prognostic clinicopathological parameters. The predictive efficiency of the nomogram was internally validated in training and testing groups, and externally validated in the Chinese Glioma Genome Atlas database. Three DNA methylation-driven genes, ARL9, CMYA5, and STEAP3, were identified as independent prognostic factors. Together with IDH1 mutation status, age, and sex, the final prognostic nomogram achieved the highest AUC value of 0.930, and demonstrated stable consistency in both internal and external validations. The prognostic nomogram could predict personal survival probabilities for patients with LGG, and serve as a user-friendly tool for prognostic evaluation, optimizing therapeutic regimes, and managing LGG patients.

The Role of Iron in Cancer Progression

Iron is an essential trace element for the human body, and its deficiency or excess can induce a variety of biological processes. Plenty of evidences have shown that iron metabolism is closely related to the occurrence and development of tumors. In addition, iron plays an important role in cell death, which is very important for the development of potential strategies for tumor treatment. Here, we reviewed the latest research about iron metabolism disorders in various types of tumors, the functions and properties of iron in ferroptosis and ferritinophagy, and new opportunities for iron-based on treatment methods for tumors, providing more information regarding the prevention and treatment of tumors.

Identifying the Predictive Role of Oxidative Stress Genes in the Prognosis of Glioma Patients

Background

Gliomas are primary aggressive brain tumors with poor prognoses. Oxidative stress plays a crucial role in the tumorigenesis and drug resistance of gliomas. The aim of the present study was to use integrated bioinformatics analyses to evaluate the prognostic value of oxidative stress-related genes (OSRGs) in glioma.

Material/Methods

Disease- and prognosis-associated OSRGs were identified using microarray and clinical data from the Chinese Glioma Genome Atlas database. Functional enrichment, gene-gene interaction, protein-protein interaction, and survival analyses were performed in screened OSRGs. The protein expression was validated by the Human Protein Atlas database. A risk score model was constructed and verified through Cox regression, receiver operating characteristic curve, principal component, and stratified analyses. The Cancer Genome Atlas (TCGA) database was used for external validation. A nomogram was constructed to facilitate the clinical application.

Results

Twenty-one disease-associated and 14 prognosis-associated OSRGs were identified. Enrichment analyses indicated that these signature OSRGs were involved in tumorigenesis and drug resistance of glioma. The risk score model demonstrated a significant difference in overall survival between the high- and low-risk groups. The area under the curve and hazard ratio (1.296) revealed the independent prognostic value of the model. The model exhibited good predictive efficacy in the TCGA cohort. A clinical nomogram was constructed to calculate survival rates in glioma patients at 1, 3, and 5 years.

Conclusions

Our comprehensive study indicated that OSRGs were valuable for prognosis prediction in glioma, which provides a novel insight into the relationship between oxidative stress and glioma and a potential therapeutic strategy for glioma patients.

Discovery of Cancer-Specific and Independent Prognostic Gene Subsets of the Slit-Robo Family Using TCGA-PANCAN Datasets

The Slit-Robo family of axon guidance molecules works in concert, playing important roles in organ development and cancer. Expressions of individual Slit-Robo genes have been used in calculating univariable hazard ratios (HR_uni) for predicting cancer prognosis in the literature. However, Slit-Robo members do not act independently; hence, hazard ratios from multivariable Cox regression (HR_multi) on the whole gene set can further lead to identification of cancer-specific, novel, and independent prognostic gene pairs or modules. Herein, we obtained mRNA expressions of the Slit-Robo family consisting of four Robos (ROBO1/2/3/4) and three Slits (SLIT1/2/3), along with four types of survival outcome across cancers found in the Cancer Genome Atlas (TCGA). We used cluster heat maps to visualize closely associated pairs/modules of prognostic genes across 33 different cancers. We found a smaller number of significant genes in HR_multi than in HR_uni, suggesting that the former analysis was less redundant. High ROBO4 expression emerged as relatively protective within the family, in both types of HR analyses. Multivariable Cox regression, on the other hand, revealed significantly more HR signatures containing Slit-Robo pairs acting in opposing directions than those containing Slit-Slit or Robo-Robo pairs for disease-specific survival. Furthermore, we discovered, through the online app SmulTCan's lasso regression, Slit-Robo gene subsets that significantly differentiated between high- versus low-risk prognosis patient groups, particularly for renal cancers and low-grade glioma. The statistical pipeline reported herein can help test independent and significant pairs/modules within a codependent gene family for cancer prognostication, and thus should also prove useful in personalized/precision medicine research.

Predictive potential of STEAP family for survival, immune microenvironment and therapy response in glioma

Glioma is the most commonly diagnosed primary tumor of central nervous system. Previous studies found that the six-transmembrane epithelial antigen of prostate (STEAP) family can regulate the biological behaviors of several cancers. However, the role of STEAP family in glioma remains unclear. Here, we systematically evaluated the relationship between STEAP family and prognosis of glioma patients in multiple cohorts. The analysis showed that dysregulation of STEAP family may affect cancer-immunity cycle, immune infiltration and phenotypes resulting in an immunosuppressive microenvironment in glioma. To accurately predict the prognosis of glioma patients, gene-based risk models were established based on the expression of STEAP1, 2 and 3. Multivariate and univariate Cox analyses demonstrated that the risk models could independently predict the prognosis of glioma. Finally, chemotherapy and immune therapy responses for high- and low-risk patients were predicted. In conclusion, this study systematically analyzed the role of STEAP family in glioma and established a model for predicting therapy response in patients with glioma.

Upregulation of the APOBEC3 Family Is Associated with a Poor Prognosis and Influences Treatment Response to Raf Inhibitors in Low Grade Glioma

Apolipoprotein B mRNA-editing enzyme catalytic polypeptide-like 3 (APOBEC3) has been identified as a group of enzymes that catalyze cytosine deamination in single-stranded (ss) DNA to form uracil, causing somatic mutations in some cancers. We analyzed the APOBEC3 family in 33 TCGA cancer types and the results indicated that APOBEC3s are upregulated in multiple cancers and strongly correlate with prognosis, particularly in low grade glioma (LGG). Then we constructed a prognostic model based on family expression in LGG where the APOBEC3 family signature is an accurate predictive model (AUC of 0.85). Gene mutation, copy number variation (CNV), and a differential gene expression (DEG) analysis were performed in different risk groups, and the weighted gene co-expression network analysis (WGCNA) was employed to clarify the role of various members in LGG; CIBERSORT algorithm was deployed to evaluate the landscape of LGG immune infiltration. We found that upregulation of the APOBEC3 family expression can strengthen Ras/MAPK signaling pathway, promote tumor progression, and ultimately reduce the treatment benefits of Raf inhibitors. Moreover, the APOBEC3 family was shown to enhance the immune response mediated by myeloid cells and interferon gamma, as well as PD-L1 and PD-L2 expression, implying that they have immunotherapy potential. Therefore, the APOBEC3 signature enables an efficient assessment of LGG patient survival outcomes and expansion of clinical benefits by selecting appropriate individualized treatment strategies.