IRF2-ferroptosis related gene is associated with prognosis and EMT in gliomas

Ferroptosis is a new type of programmed cell death that has excellent anti-tumor potential in different tumors. However, the research on ferroptosis in glioma is still incomplete. In this study, we aimed to revealed the relationship between ferroptosis-related genes (FRGs) and glioma. We collected gene expression profiles of glioma patients from the TCGA and CGGA databases. All glioma samples were classified into five subtypes using the R software ConsensusClusterPlus. Subsequently, we performed single sample gene set enrichment analysis (ssGSEA) to explore the correlation between different subtypes and immune status and ferroptosis. Then co-expression modules were constructed via weighted gene co-expression network analysis (WGCNA). A Gene Ontology (GO) analysis was conducted to analyze the potential biological functions of the genes in the modules. Finally, we identified 10 hub genes using the PPI network. The in vitro experiments were used to validate our predictions. We found that the expression level of IRF2 is positively correlated with the grade of glioma. The overexpression of IRF2 could protect glioma cells from ferroptosis and enhance the invasive and migratory abilities. Silence of IRF2 had the opposite effect. In conclusion, we demonstrated a novel ferroptosis-related signature for predicting prognosis, and IRF2 could be a potential biomarker for diagnosis and treatment in glioma.     

Establishment and experimental validation of an immune miRNA signature for assessing prognosis and immune landscape of patients with colorectal cancer

As essential regulators of gene expression, miRNAs are engaged in the initiation and progression of colorectal cancer (CRC), including antitumour immune response. In this study, we proposed an integrated algorithm, ImmuMiRNA, for identifying miRNA modulators of immune-associated pathways. Based on these immune-associated miRNAs, we applied the LASSO algorithm to develop a reliable and individualized signature for evaluating overall survival (OS) and inflammatory landscape of CRC patients. An external public data set and qRT-PCR data from 40 samples were further utilized to validate this signature. As a result, an immune-associated miRNA prognostic signature (IAMIPS) consisting of three miRNAs (miR-194-3P, miR-216a-5p and miR-3677-3p) was established and validated. Patients in the high-risk group possessed worse OS. After stratification for clinical factors, the signature remained a powerful independent predictor for OS. IAMIPS displayed much better accuracy than the traditional clinical stage in assessing the prognosis of CRC. Further analysis revealed that patients in the high-risk group were characterized by inflammatory response, abundance immune cell infiltration, and higher immune checkpoint profiles and tumour mutation burden (TMB). In conclusion, the IAMIPS is highly predictive of OS in patients with CRC, which may serve as a powerful prognostic tool to further optimize immunotherapies for cancer.     

Development and validation of stable ferroptosis- and pyroptosis-related signatures in predicting prognosis and immune status in breast cancer

To develop and validate the predictive effects of stable ferroptosis- and pyroptosis-related features on the prognosis and immune status of breast cancer (BC). We retrieved as well as downloaded ferroptosis- and pyroptosis-related genes from the FerrDb and GeneCards databases. The minimum absolute contraction and selection operator (LASSO) algorithm in The Cancer Genome Atlas (TCGA) was used to construct a prognostic classifier combining the above two types of prognostic genes with differential expression, and the Integrated Gene Expression (GEO) dataset was used for validation. Seventeen genes presented a close association with BC prognosis. Thirteen key prognostic genes with prognostic value were considered to construct a new expression signature for classifying patients with BC into high- and low-risk groups. Kaplan–Meier analysis revealed a worse prognosis in the high-risk group. The receiver operating characteristic (ROC) curve and multivariate Cox regression analysis identified its predictive and independent features. Immune profile analysis showed that immunosuppressive cells were upregulated in the high-risk group, and this risk model was related to immunosuppressive molecules. We successfully constructed combined features of ferroptosis and pyroptosis in BC that are closely related to prognosis, clinicopathological and immune features, chemotherapy efficacy and immunosuppressive molecules. However, further experimental studies are required to verify these findings.     

Tumor immune cell clustering and its association with survival in African American women with ovarian cancer

New technologies, such as multiplex immunofluorescence microscopy (mIF), are being developed and used for the assessment and visualization of the tumor immune microenvironment (TIME). These assays produce not only an estimate of the abundance of immune cells in the TIME, but also their spatial locations. However, there are currently few approaches to analyze the spatial context of the TIME. Therefore, we have developed a framework for the spatial analysis of the TIME using Ripley’s K, coupled with a permutation-based framework to estimate and measure the departure from complete spatial randomness (CSR) as a measure of the interactions between immune cells. This approach was then applied to epithelial ovarian cancer (EOC) using mIF collected on intra-tumoral regions of interest (ROIs) and tissue microarrays (TMAs) from 160 high-grade serous ovarian carcinoma patients in the African American Cancer Epidemiology Study (AACES) (94 subjects on TMAs resulting in 263 tissue cores; 93 subjects with 260 ROIs; 27 subjects with both TMA and ROI data). Cox proportional hazard models were constructed to determine the association of abundance and spatial clustering of tumor-infiltrating lymphocytes (CD3+), cytotoxic T-cells (CD8+CD3+), and regulatory T-cells (CD3+FoxP3+) with overall survival. Analysis was done on TMA and ROIs, treating the TMA data as validation of the findings from the ROIs. We found that EOC patients with high abundance and low spatial clustering of tumor-infiltrating lymphocytes and T-cell subsets in their tumors had the best overall survival. Additionally, patients with EOC tumors displaying high co-occurrence of cytotoxic T-cells and regulatory T-cells had the best overall survival. Grouping women with ovarian cancer based on both cell abundance and spatial contexture showed better discrimination for survival than grouping ovarian cancer cases only by cell abundance. These findings underscore the prognostic importance of evaluating not only immune cell abundance but also the spatial contexture of the immune cells in the TIME. In conclusion, the application of this spatial analysis framework to the study of the TIME could lead to the identification of immune content and spatial architecture that could aid in the determination of patients that are likely to respond to immunotherapies.     

Tumor immune microenvironment: sanctuary of tumor and target for immunotherapy

The tumor immune microenvironment (TIME) is the cellular environment in which tumors exist. This includes: surrounding blood vessels, immune cells, fibroblasts, bone marrow-derived inflammatory cells, lymphocytes, signaling molecules, immune checkpoint proteins and the extracellular matrix (ECM). The TIME plays a critical role in cancer progression and regulation. Tumors can influence the microenvironment by releasing extracellular signals, promoting tumor angiogenesis and inducing peripheral immune tolerance, while the immune cells in the microenvironment can affect the growth and evolution of cancerous cells. The molecules and cells in the TIME influence disease outcome by altering the balance of suppressive versus cytotoxic responses in the vicinity of the tumor. Having a better understanding of the tumor immune microenvironment will pave the way for identifying new targets for immunotherapies that promote cancer elimination.     

BTN3A2 serves as a prognostic marker and favors immune infiltration in triple-negative breast cancer

Immune infiltration is reported to be highly associated with tumor progress. Since butyrophilin subfamily 3 member A2 (BTN3A2) serves as a crucial mediator in immune activation, we aimed to investigate the correlation of BTN3A2 in immune infiltration and tumor prognosis via extensive-cancer analysis. The levels of BTN3A2 expression in extensive cancers were analyzed with Oncomine and TIMER databases. Univariate cox and multivariate cox regression analyses were conducted to assess the associations of BTN3A2 to prognosis of various cancers. The correlations of BTN3A2 with immune infiltration were assessed by TIMER database. It suggested that BTN3A2 was a potential prognosis signature for breast cancer (BRCA) and ovarian cancer (OV). However, immune infiltrations were highly correlated with BTN3A2 in triple-negative breast cancer (TNBC), compared with OV and other subtypes of BRCA. Multivariate cox regression analysis revealed that BTN3A2 was an independently prognostic signature of TNBC, as well as weighted correlation network analysis suggested BTN3A2 was only correlated with TNBC, rather than other subtypes of BRCA. Immune cell subtypes correlation analysis showed that BTN3A2 was highly correlated with general T, CD8+ T, T helper type 1, exhausted T cells, and dendritic cells in TNBC. And the coexpression geneset of BTN3A2 was mainly involved in T-cell receptor interaction and the nuclear factor-κB (NF-κB) signaling pathway. Collectively, BTN3A2 that was positively associated with better prognosis could be served as a special diagnostic and independently prognostic marker for TNBC by regulating the T-cell receptor interaction and NF-κB signaling pathways.     

Fascin enhances the vulnerability of breast cancer to erastin-induced ferroptosis

Ferroptosis, which is characterized by intracellular iron accumulation and lipid peroxidation, is a newly described form of regulated cell death that may play a key role in tumour suppression. In the present study, we investigated the expression profiles and biological effects of fascin actin-bundling protein 1 (Fascin, gene name FSCN1) in breast cancer. In addition, bioinformatics analysis of the TCGA cancer database and gain- and loss-of-function studies showed that Fascin enhances sensitivity to erastin-induced ferroptosis. Mechanistically, Fascin directly interacts with cysteine/glutamate transporter (xCT, gene name SLC7A11) and decreases its stability via the ubiquitin-mediated proteasome degradation pathway. Furthermore, we observed that Fascin is substantially upregulated in tamoxifen-resistant breast cancer cell lines, and drug-resistant cells were also more vulnerable to erastin-induced ferroptosis. Taken together, our findings reveal a previously unidentified role of Fascin in ferroptosis by regulating xCT. Thus, ferroptosis activation in breast cancer with high Fascin level may serve as a potential treatment.Subject terms: Cell death, Breast cancer     

Molecular Characteristics and Metastasis Predictor Genes of Triple-Negative Breast Cancer: A Clinical Study of Triple-Negative Breast Carcinomas

Background

Triple-negative breast cancer is a subtype of breast cancer with aggressive tumor behavior and distinct disease etiology. Due to the lack of an effective targeted medicine, treatment options for triple-negative breast cancer are few and recurrence rates are high. Although various multi-gene prognostic markers have been proposed for the prediction of breast cancer outcome, most of them were proven clinically useful only for estrogen receptor-positive breast cancers. Reliable identification of triple-negative patients with a favorable prognosis is not yet possible.

Methodology/Principal Findings

Clinicopathological information and microarray data from 157 invasive breast carcinomas were collected at National Taiwan University Hospital from 1995 to 2008. Gene expression data of 51 triple-negative and 106 luminal breast cancers were generated by oligonucleotide microarrays. Hierarchical clustering analysis revealed that the majority (94%) of triple-negative breast cancers were tightly clustered together carrying strong basal-like characteristics. A 45-gene prognostic signature giving 98% predictive accuracy in distant recurrence of our triple-negative patients was determined using the receiver operating characteristic analysis and leave-one-out cross validation. External validation of the prognostic signature in an independent microarray dataset of 59 early-stage triple-negative patients also obtained statistical significance (hazard ratio 2.29, 95% confidence interval (CI) 1.04–5.06, Cox P = 0.04), outperforming five other published breast cancer prognostic signatures. The 45-gene signature identified in this study revealed that TGF-β signaling of immune/inflammatory regulation may play an important role in distant metastatic invasion of triple-negative breast cancer.

Conclusions/Significance

Gene expression data and recurrence information of triple-negative breast cancer were collected and analyzed in this study. A novel set of 45-gene signature was found to be statistically predictive in disease recurrence of triple-negative breast cancer. The 45-gene signature, if further validated, may be a clinically useful tool in risk assessment of distant recurrence for early-stage triple-negative patients.     

Emerging role of metabolic reprogramming in tumor immune evasion and immunotherapy

Mounting evidence has revealed that the therapeutic efficacy of immunotherapies is restricted to a small portion of cancer patients. A deeper understanding of how metabolic reprogramming in the tumor microenvironment(TME) regulates immunity remains a major challenge to tumor eradication. It has been suggested that metabolic reprogramming in the TME may affect metabolism in immune cells and subsequently suppress immune function. Tumor cells compete with infiltrating immune cells for nutrients and metabolites. Notably, the immunosuppressive TME is characterized by catabolic and anabolic processes that are critical for immune cell function, and elevated inhibitory signals may favor cancer immune evasion. The major energy sources that supply different immune cell subtypes also undergo reprogramming. We herein summarize the metabolic remodeling in tumor cells and different immune cell subtypes and the latest advances underlying the use of metabolic checkpoints in antitumor immunotherapies. In this context, targeting both tumor and immune cell metabolic reprogramming may enhance therapeutic efficacy.     

Multi-omics Analysis of Ferroptosis Regulation Patterns and Characterization of Tumor Microenvironment in Patients with Oral Squamous Cell Carcinoma

Ferroptosis is a newly recognized mechanism of regulated cell death. It was reported to be highly associated with immune therapy and chemotherapy. However, its mechanism of regulation in the tumor microenvironment (TME) and influence on oral squamous cell carcinoma (OSCC) therapy are unknown. We identified a ferroptosis-specific gene-expression signature, an FPscore, developed by a principal component analysis (PCA) algorithm to evaluate the ferroptosis regulation patterns of individual tumor. Multi-omics analysis of ferroptosis regulation patterns was conducted. Three distinct ferroptosis regulation subtypes, which linked to outcomes and the clinical relevance of each patient, were established. A high FPscore of patients with OSCC was associated with a favorable prognosis, a ferroptosis-related immune-activation phenotype, potential sensitivities to the chemotherapy and immunotherapy. Importantly, a high FPscore correlated with a low gene copy number burden and high immune checkpoint expressions. We validated the prognostic value of the FPscore using independent immunotherapy and pan-cancer cohorts. Comprehensive evaluation of individual tumors with distinct ferroptosis regulation patterns provides new mechanistic insights, which may be clinically relevant for the application of combination therapies in OSCC.     

GM-CSF-secreting cancer immunotherapies: preclinical analysis of the mechanism of action

Granulocyte-macrophage colony-stimulating factor (GM-CSF)-secreting tumor cell immunotherapies have demonstrated long-lasting, and specific anti-tumor immune responses in animal models. The studies reported here specifically evaluate two aspects of the immune response generated by such immunotherapies: the persistence of irradiated tumor cells at the immunization site, and the breadth of the immune response elicited to tumor associated antigens (TAA) derived from the immunotherapy. To further define the mechanism of GM-CSF-secreting cancer immunotherapies, immunohistochemistry studies were performed using the B16F10 melanoma tumor model. In contrast to previous reports, our data revealed that the irradiated tumor cells persisted and secreted high levels of GM-CSF at the injection site for more than 21 days. Furthermore, dense infiltrates of dendritic cells were observed only in mice treated with GM-CSF-secreting B16F10 cells, and not in mice treated with unmodified B16F10 cells with or without concurrent injection of rGM-CSF. In addition, histological studies also revealed enhanced neutrophil and CD4+ T cell infiltration, as well as the presence of apoptotic cells, at the injection site of mice treated with GM-CSF-secreting tumor cells. To evaluate the scope of the immune response generated by GM-CSF-secreting cancer immunotherapies, several related B16 melanoma tumor cell subclones that exist as a result of genetic drift in the original cell line were used to challenge mice previously immunized with GM-CSF-secreting B16F10 cells. These studies revealed that GM-CSF-secreting cancer immunotherapies elicit T cell responses that effectively control growth of related but antigenically distinct tumors. Taken together, these studies provide important new insights into the mechanism of action of this promising novel cancer immunotherapy. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Typical tumor immune microenvironment status determine prognosis in lung adenocarcinoma

BackgroundImmune cells, vital components of tumor microenvironment, regulate tumor survival and progression. Lung adenocarcinoma (LUAD), the tumor with the highest mortality rate worldwide, reconstitutes tumor immune microenvironment (TIME) to avoid immune destruction. Data have shown that TIME influences LUAD prognosis and predicts immunotherapeutic efficacy. The related information about the role of TIME's characteristics in LUAD is limited.MethodsWe performed unsupervised consensus clustering via machine-learning techniques to identify TIME clusters among 1906 patients and gathered survival data. The characteristics of TIME clusters of LUAD were visualized by multi-omics analysis, pseudo-time dynamic analysis, and enrichment analysis. TIME score model was constructed by principal component analysis. Comprehensive analysis and validation were conducted to test the prognostic efficacy and immunotherapeutic response of TIME score.ResultsTIME clusters (A, B and C) were constructed and exhibited different immune infiltration states. Multi-omics analyses included significant mutated genes (SMG), copy number variation (CNV) and cancer stemness that were significantly different among the three clusters. TIME cluster A had a lower SMG, lower CNV, and lower stemness but a higher immune infiltration level compared to TIME clusters B and C. TIME score showed that patients in low TIME score group had higher overall survival rates, higher immune infiltration level and high expression of immune checkpoints. In validation cohorts, low TIME score subgroup had better drug sensitivity and favorable immunotherapeutic response.ConclusionWe constructed a stable model of LUAD immune microenvironment characteristics that may improve the prognostic accuracy of patients, provide improved explanations of LUAD responses to immunotherapy, and provide new strategies for LUAD treatment.     

A robust immune-related lncRNA signature for the prognosis of human colorectal cancer

Background: Colorectal cancer (CRC) is one of the most prevalent malignant cancers worldwide. Immune-related long non-coding RNAs (IRlncRNAs) are proved to be essential in the development and progression of carcinoma. The purpose of the present study was to develop and validate a prognostic IRlncRNA signature for CRC patients.Methods: Gene expression profiles of CRC samples were downloaded from The Cancer Genome Atlas (TCGA) database. Immune-related genes were obtained from the ImmPort database and were used to identify IRlncRNA by correlation analysis. Through LASSO Cox regression analyses, a prognostic signature was constructed. Functional enrichment analysis was performed by gene set enrichment analysis (GSEA). TIMER2.0 web server and tumor immune dysfunction and exclusion (TIDE) algorithm were employed to analyze the association between our model and tumor-infiltrating immune cells and immunotherapy response. The expression levels of IRlncRNAs in cell lines were detected by quantitative real-time PCR (qPCR).Results: A 9-IRlncRNA signature was developed by a LASSO Cox proportional regression model. Based on the signature, CRC patients were divided into high- and low-risk groups with different prognoses. GSEA results indicated that patients in high-risk group were associated with cancer-related pathways. In addition, patients in low-risk group were found to have more infiltration of anti-tumor immune cells and might show a favorable response to immunotherapy. Finally, the result of qPCR revealed that most IRlncRNAs were differently expressed between normal and tumor cell lines.Conclusion: The constructed 9-IRlncRNA signature has potential to predict the prognosis of CRC patients and may be helpful to guide personalized immunotherapy.     

Ferroptosis-Related Long Non-Coding RNA signature predicts the prognosis of Head and neck squamous cell carcinoma

Background: Head and neck squamous cell carcinoma (HNSCC) are head and neck cancers. On the other hand, ferroptosis is a novel iron-dependent and ROS reliant type of cell death observed various disease conditions.Method: We constructed a prognostic multilncRNA signature based on ferroptosis-related differentially expressed lncRNAs in HNSCC.Results: We identified 25 differently expressed lncRNAs associated with prognosis of HNSCC. Kaplan-Meier analyses revealed the high-risk lncRNAs signature associated with poor prognosis of HNSCC. Moreover, the AUC of the lncRNAs signature was 0.782, underscoring their utility in prediction HNSCC prognosis. Indeed, our risk assessment model was superior to traditional clinicopathological features in predicting HNSCC prognosis. GSEA revealed the immune and tumor-related pathways in the low risk group individuals. Moreover, TCGA revealed T cell functions including cytolytic activity, HLA, regulation of inflammationp, co-stimulation, co-inhibition and coordination of type II INF response were significantly different between the low-risk and high-risk groups. Immune checkpoints such as PDCD-1 (PD-1), CTLA4 and LAG3, were also expressed differently between the two risk groups.Conclusion: A novel ferroptosis-related lncRNAs signature impacts on the prognosis of HNSCC.     

Genetic analysis of potential biomarkers and therapeutic targets in ferroptosis from coronary artery disease

Ferroptosis plays a key role in the death of cells including cardiomyocytes, and it is related to a variety of cardiac diseases. However, the role of ferroptosis‐related genes (FRGs) in coronary artery disease (CAD) is not well characterized. We downloaded CAD‐related information and FRGs from the gene expression omnibus (GEO) database and Ferroptosis Database (FerrDb) respectively. A total of 10 CAD‐related DE‐FRGs were obtained, which were closely linked to autophagy regulation and immune response. Subsequently, CA9, CBS, CEBPG, HSPB1, SLC1A4, STMN1 and TRIB3 among the 10 DE‐FRGs were identified as marker genes by LASSO and SVM‐RFE algorithms, which had tolerable diagnostic capabilities. Subsequent functional enrichment analysis showed that these marker genes may play a corresponding role in CAD by participating in the regulation of immune response, amino acid metabolism, cell cycle and multiple pathways related to the pathogenesis of CAD. Furthermore, a total of 58 drugs targeting 7 marker genes had been obtained. On the contrary, the ceRNA network revealed a complex regulatory relationship based on the marker genes. Also, CIBERSORT analysis showed that the changes in the immune microenvironment of CAD patients may be related to CBS, HSPB1 and CEBPG. We developed a diagnostic potency and provided an insight for exploring the mechanism for CAD. Before clinical application, further research is needed to test its diagnostic value for CAD.     

Ferroptosis in Cancer Progression: Role of Noncoding RNAs

Ferroptosis is a novel form of programmed cell death, and it is characterized by iron-dependent oxidative damage, lipid peroxidation and reactive oxygen species accumulation. Notable studies have revealed that ferroptosis plays vital roles in tumor occurrence and that abundant ferroptosis in cells can inhibit tumor progression. Recently, some noncoding RNAs (ncRNAs), particularly microRNAs, long noncoding RNAs, and circular RNAs, have been shown to be involved in biological processes of ferroptosis, thus affecting cancer growth. However, the definite regulatory mechanism of this phenomenon is still unclear. To clarify this issue, increasing studies have focused on the regulatory roles of ncRNAs in the initiation and development of ferroptosis and the role of ferroptosis in progression of various cancers, such as lung, liver, and breast cancers. In this review, we systematically summarized the relationship between ferroptosis-associated ncRNAs and cancer progression. Moreover, additional evidence is needed to identify the role of ferroptosis-related ncRNAs in cancer progression. This review will help us to understand the roles of ncRNAs in ferroptosis and cancer progression and may provide new ideas for exploring novel diagnostic and therapeutic biomarkers for cancer in the future.