Analysis of Ferroptosis-Mediated Modification Patterns and Tumor Immune Microenvironment Characterization in Uveal Melanoma

Programmed Cell Death-Related Gene Signature Associated with Prognosis and Immune Infiltration and the Roles of HMOX1 in the Proliferation and Apoptosis were Investigated in Uveal Melanoma

BACKGROUND

Uveal melanoma (UVM) is the most common primary ocular malignancy, with a wide range of symptoms and outcomes. The programmed cell death (PCD) plays an important role in tumor development, diagnosis, and prognosis. There is still no research on the relationship between PCD-related genes and UVM. A novel PCD-associated prognostic model is urgently needed to improve treatment strategies.

OBJECTIVE

We aim to screen PCD-related prognostic signature and investigate its proliferation ability and apoptosis in UVM cells.

METHODS

The clinical information and RNA-seq data of the UVM patients were collected from the TCGA cohort. All the patients were classified using consensus clustering by the selected PCD-related genes. After univariate Cox regression and PPI network analysis, the prognostic PCD-related genes were then submitted to the LASSO regression analysis to build a prognostic model. The level of immune infiltration of 8-PCD signature in high- and low-risk patients was analyzed using xCell. The prediction on chemotherapy and immunotherapy response in UVM patients was assessed by GDSC and TIDE algorithm. CCK-8, western blot and Annexin V-FITC/PI staining were used to explore the roles of HMOX1 in UVM cells.

RESULTS

A total of 8-PCD signature was constructed and the risk score of the PCD signature was negatively correlated with the overall survival, indicating strong predictive ability and independent prognostic value. The risk score was positively correlated with CD8 Tcm, CD8 Tem and Th2 cells. Immune cells in high-risk group had poorer overall survival. The drug sensitivity demonstrated that cisplatin might impact the progression of UVM and better immunotherapy responsiveness in the high-risk group. Finally, Overespression HMOX1 (OE-HMOX1) decreased the cell viability and induced apoptosis in UVM cells. Recuse experiment results showed that ferrostatin-1 (fer-1) protected MP65 cells from apoptosis and necrosis caused by OE-HMOX1.

CONCLUSION

The PCD signature may have a significant role in the tumor microenvironment, clinicopathological characteristics, prognosis and drug sensitivity. More importantly, HMOX1 depletion greatly induced tumor cell growth and inhibited cell apoptosis and fer-1 protected UVM cells from apoptosis and necrosis induced by OE-HMOX1. This work provides a foundation for effective therapeutic strategy in tumour treatment.

Glutathione‑degrading enzymes in the complex landscape of tumors (Review)

Glutathione (GSH)‑degrading enzymes are essential for starting the first stages of GSH degradation. These enzymes include extracellular γ‑glutamyl transpeptidase (GGT) and intracellular GSH‑specific γ‑glutamylcyclotransferase 1 (ChaC1) and 2. These enzymes are essential for cellular activities, such as immune response, differentiation, proliferation, homeostasis regulation and programmed cell death. Tumor tissue frequently exhibits abnormal expression of GSH‑degrading enzymes, which has a key impact on the development and spread of malignancies. The present review summarizes gene and protein structure, catalytic activity and regulation of GSH‑degrading enzymes, their vital roles in tumor development (including regulation of oxidative and endoplasmic reticulum stress, control of programmed cell death, promotion of inflammation and tumorigenesis and modulation of drug resistance in tumor cells) and potential role as diagnostic biomarkers and therapeutic targets.

ChaC1 upregulation reflects poor prognosis in a variety of cancers: analysis of the major missense SNPs of ChaC1 as an aid to refining prognosis

The ChaC1 enzyme that catalyzes cytosolic glutathione degradation is highly upregulated in several cancers. In a systematic review of gene signature panels for cancer prognosis based on oxidative stress and ferroptosis genes, we observed that ChaC1 was found in panels in a wide variety of different cancers, with the upregulation correlating with poor prognosis. Since SNPs can have an impact on functionality and prognosis, ChaC1 SNPs from various databases were also investigated. Six frequently observed missense SNPs were chosen for reconstruction, and their functionality was evaluated. Three out of six SNPs resulted in either a partial or complete loss of ChaC1 function, and these SNPs had the changes R72Q, A156V, and G173S in their proteins. This study highlights the importance of ChaC1 in cancer prognosis across a wide variety of cancers. Additionally, the information on the SNPs of ChaC1 with altered enzymatic activities would improve the prognostic ability of these panels and facilitate treatment regimens.

Machine Learning Methods for Gene Selection in Uveal Melanoma

Uveal melanoma (UM) is the most common primary intraocular malignancy with a limited five-year survival for metastatic patients. Limited therapeutic treatments are currently available for metastatic disease, even if the genomics of this tumor has been deeply studied using next-generation sequencing (NGS) and functional experiments. The profound knowledge of the molecular features that characterize this tumor has not led to the development of efficacious therapies, and the survival of metastatic patients has not changed for decades. Several bioinformatics methods have been applied to mine NGS tumor data in order to unveil tumor biology and detect possible molecular targets for new therapies. Each application can be single domain based while others are more focused on data integration from multiple genomics domains (as gene expression and methylation data). Examples of single domain approaches include differentially expressed gene (DEG) analysis on gene expression data with statistical methods such as SAM (significance analysis of microarray) or gene prioritization with complex algorithms such as deep learning. Data fusion or integration methods merge multiple domains of information to define new clusters of patients or to detect relevant genes, according to multiple NGS data. In this work, we compare different strategies to detect relevant genes for metastatic disease prediction in the TCGA uveal melanoma (UVM) dataset. Detected targets are validated with multi-gene score analysis on a larger UM microarray dataset.

Nomogram of uveal melanoma as prediction model of metastasis risk

Background

Since the poor prognosis of uveal melanoma with distant metastasis, we intended to screen out possible biomarkers for uveal melanoma metastasis risk and establish a nomogram model for predicting the risk of uveal melanoma (UVM) metastasis.

Methods

Two datasets of UVM (GSE84976, GSE22138) were selected. Data was analyzed by R language, CTD database and GEPIA.

Results

The co-upregulated genes of two datasets, HTR2B, CHAC1, AHNAK2, and PTP4A3 were identified using a Venn diagram. These biomarkers are combined with clinical characteristics, and Lasso regression was conducted to filter the metastasis-related biomarkers. HTR2B, CHAC1, AHNAK2, PTP4A3, tumor thickness, and retinal detachment (RD) were selected to establish the nomogram.

Conclusion

Our study provides a comprehensive predictive model and personalized risk estimation tool for assessment of 3-year metastasis risk of UVM with a better accuracy.

Ferroptosis induced by DCPS depletion diminishes hepatic metastasis in uveal melanoma

Hepatic metastasis develops in ∼50% of uveal melanoma (UM) patients with scarcely effective treatment resulting in lethality. The underlying mechanism of liver metastasis remains elusive. Ferroptosis, a cell death form characterized by lipid peroxide, in cancer cells may decrease metastatic colonization. In the present study, we hypothesized that decapping scavenger enzymes (DCPS) impact ferroptosis by regulating mRNA decay during the metastatic colonization of UM cells to liver. We found that inhibition of DCPS by shRNA or RG3039 induced gene transcript alteration and ferroptosis through reducing the mRNA turnover of GLRX. Ferroptosis induced by DCPS inhibition eliminates cancer stem-like cells in UM. Inhibition of DCPS hampered the growth and proliferation both in vitro and in vivo. Furthermore, targeting DCPS diminished hepatic metastasis of UM cells. These findings may shed light on the understanding of DCPS-mediated pre-mRNA metabolic pathway in UM by which disseminated cells gain enhanced malignant features to promote hepatic metastasis, providing a rational target for metastatic colonization in UM.

Genetics and RNA Regulation of Uveal Melanoma

Uveal melanoma (UM) is the most common intraocular malignant tumor and the most frequent melanoma not affecting the skin. While the rate of UM occurrence is relatively low, about 50% of patients develop metastasis, primarily to the liver, with lethal outcome despite medical treatment. Notwithstanding that UM etiopathogenesis is still under investigation, a set of known mutations and chromosomal aberrations are associated with its pathogenesis and have a relevant prognostic value. The most frequently mutated genes are BAP1, EIF1AX, GNA11, GNAQ, and SF3B1, with mutually exclusive mutations occurring in GNAQ and GNA11, and almost mutually exclusive ones in BAP1 and SF3B1, and BAP1 and EIF1AX. Among chromosomal aberrations, monosomy of chromosome 3 is the most frequent, followed by gain of chromosome 8q, and full or partial loss of chromosomes 1 and 6. In addition, epigenetic mechanisms regulated by non-coding RNAs (ncRNA), namely microRNAs and long non-coding RNAs, have also been investigated. Several papers investigating the role of ncRNAs in UM have reported that their dysregulated expression affects cancer-related processes in both in vitro and in vivo models. This review will summarize current findings about genetic mutations, chromosomal aberrations, and ncRNA dysregulation establishing UM biology.

Multiple epigenetic modification profiles reveal the tumor immune microenvironment and clinical outcomes of uveal melanoma

Uveal melanoma (UM) is an aggressive intraocular cancer that, in 50% of cases, spreads to the patient's other systems. The exact cause of the increased metastatic rate is still unknown. Methylation and immune response, metastasis, and the expansion of cancer cells are closely related. Additionally, proteins linked to RNA methylation have come to light as possible cancer treatment targets. However, the relationship between methylation-related genes (MRGs) and the tumor microenvironment (TME) is still not understood. The goal of this work was to discover important MRGs and create a signature for UM patients' prognosis prediction. Using two different data sets, we examined the MRG expression patterns in the transcriptional and genomic regions of 106 UM samples. We discovered a connection between the clinicopathological traits of the patients, their prognosis, the capability of TME cells to infiltrate, and various MRG changes. Following that, we developed an MRGs signature to forecast prognosis, and we evaluated the model's precision in patients with UM. We grouped the patients into multiple categories based on their clinical traits, looked at the survival rates for various groups within various groupings, and tested their accuracy. Additionally, to increase the practical usability of the MRGs model, we created a very accurate nomogram. TIDE scores were higher in the low-risk group. We go over how MGRs could impact UM's TME, immunotherapy responsiveness, prognosis, and clinically significant features. We looked for different chemotherapeutic drugs and cutting-edge targeted agents for patients in diverse subgroups in order to better understand MRGs in UM. This helped in the creation of customized therapy to open new doors. We could also further research the prognosis and develop more efficient immunotherapy regimens.

Cuproptosis-related gene signatures for predicting prognosis of lung adenocarcinoma

Lung cancer (LC) is a common malignancy with high mortality rate, and lung adenocarcinoma (LUAD) is one of the common pathological types. Cuproptosis is a recently discovered new type of cell death dependent on mitochondria. However, the role of cuproptosis in LUAD is unknown. We obtained LUAD transcriptome data from the Cancer Genome Atlas (TCGA). Long-stranded non-coding RNA (LncRNAs) based on cuproptosis prognosis associated with LUAD were constructed for prognostic multi-LncRNA characterization. We divided TCGA-LUAD into training set and validation set to prove feasibility, and all samples were divided into high-risk group or low risk group. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were used to evaluate potential biological functions and explore the relationship between risk models and immunity. We identified 3 differentially expressed LncRNAs associated with LUAD prognosis and constructed prognostic model. Kaplan-Meier (K-M) analysis revealed prognostic model and LUAD prognosis. Our risk assessment model has a good reliability in predicting the prognosis of LUAD and was able to improve predictive ability of tumor mutational burdern. Single sample gene enrichment analysis (ssGSEA) revealed risk subgroups were associated with immune-related functions. The prognostic model based on cuproptosis lncRNA has important value in predicting the survival of LUAD patients.

EZH2-mediated H3K27me3 is a predictive biomarker and therapeutic target in uveal melanoma

Although gene mutations and aberrant chromosomes are associated with the pathogenesis and prognosis of uveal melanoma (UM), potential therapeutic targets still need to be explored. We aim to determine the predictive value and potential therapeutic target of EZH2 in uveal melanoma. Eighty-five uveal melanoma samples were recruited in our study, including 19 metastatic and 66 nonmetastatic samples. qRT-PCR, immunohistochemistry staining, and western blotting were applied to detect the expression of EZH2 and H3K27me3. We found that EZH2 (41/85, 48.24%) and H3K27me3 (49/85, 57.65%) were overexpressed in uveal melanoma. The expression of EZH2 was not significantly associated with metastasis. High H3K27me3 expression was correlated with poor patient prognosis. UNC 1999, an EZH2 inhibitor, can downregulate H3K27me3 expression and has the most potency to inhibit OMM1 cell growth by the cell cycle and ferroptosis pathway. These results indicate that H3K27me3 can be a biomarker predicting a poor prognosis of UM. EZH2 is the potential therapeutic target for UM.

Novel insight into ferroptosis-related genes, molecular subtypes, and immune characteristics in intracranial aneurysms

OBJECTIVES

This study aimed to identify the role of ferroptosis in intracranial aneurysm (IA).

METHODS

GSE122897, GSE75436, GSE15629, and GSE75434 datasets were downloaded from the Gene Expression Omnibus database. The differentially expressed ferroptosis-related genes (DEFRGs) were selected to construct a diagnostic model integrating with machine learning. Then, a consensus clustering algorithm was performed to classify IA patients into distinct ferroptosis-related clusters. Functional analyses, including GO, KEGG, GSVA, and GSEA analyses, were conducted to elucidate the underlying mechanisms. ssGSEA and xCell algorithms were performed to uncover the immune characteristics.

RESULTS

We identified 28 DEFRGs between IAs and controls from the GSE122897 dataset. GO and KEGG results showed that these genes were enriched in cytokine activity, ferroptosis, and the IL-17 signaling pathway. Immune analysis showed that the IAs had higher levels of immune infiltration. A four FRGs model (MT3, CDKN1A, ZEP69B, and ABCC1) was established and validated with great IA diagnostic ability. We divided the IA samples into two clusters and found that cluster 2 had a higher proportion of rupture and immune infiltration. We identified 10 ferroptosis phenotypes-related markers in IAs.

CONCLUSION

Ferroptosis and the immune microenvironment are closely associated with IAs, providing a basis for understanding the IA development.

Construction of a ferroptosis-associated circRNA-miRNA-mRNA network in age-related macular degeneration

Age-related macular degeneration (AMD) is a leading cause of severe vision impairment in the aging population. However, the underlying molecular mechanism remains unclear. Ferroptosis is a novel non-apoptotic programmed cell death pathway, that contributes to AMD. In addition, non-coding RNA-led epigenetic profile was identified in the regulation of AMD progression. Considering that non-coding RNAs are vital regulators of ferroptosis-related genes in various pathological events, we explored and constructed a ferroptosis-associated circRNA-miRNA-mRNA network in AMD. Differential expression of fourteen ferroptosis-associated genes were identified based on our microarray analysis and the FerrDb tool at the threshold of P < 0.05 and log₂|fold change| ≥ 1, which were subsequently validated by the public datasets. We further screened eight miRNAs via public datasets and the miRNet database. Based on these eight miRNAs, 23 circRNAs were mined using the Starbase tool. Taking all these together, we obtained a ferroptosis-related network with 414 pairs of circRNA-miRNA-mRNA, which are potential targets in future AMD treatments.

Crosstalk of three novel types of programmed cell death defines distinct microenvironment characterization and pharmacogenomic landscape in breast cancer

Background

Prior studies have highlighted that novel programmed cell death (PCD) modalities, including ferroptosis, pyroptosis, and necroptosis, are correlated with tumor progression and antitumor immunity. Nonetheless, comprehensive analysis of tumor microenvironment (TME) profiles mediated by the crosstalk of distinct PCD forms has not been conducted in breast cancer (BC).

Methods

Here, we curated 34 identified PCD-associated genes (PCDAGs) and applied the consensus clustering algorithm to establish PCD-mediated tumor patterns in BC. Subsequently, based on prognostic differentially expressed genes extracted from distinct PCD-mediated patterns, we applied the LASSO algorithm to construct CD_Score. Furthermore, the correlation analysis between CD_Score and TME features, molecular subtypes, clinicopathological characteristics, drug response, and immunotherapeutic efficacy was performed.

Results

Three distinct PCD-clusters were determined among 2,038 BC samples, which did not only display different clinical outcomes but highly correlated to the established immunological tumor phenotypes: “desert,” “excluded,” and “inflamed” immune profiles. Based on the CD_Score derived from the PCD-related gene signature, BC patients could be stratified into CD_Score-low and -high group, of which the former displayed satisfactory survival outcome and enhanced immune infiltration. Further exploration identified that the CD_Score-high group significantly correlated with elevated neoantigen load and higher mutation frequency in SMGs (e.g., TP53 and MAP3K1) and reduced expression of immune checkpoint proteins.

Conclusions

This research is the first to emphasize the close relationship between distinct cell death modalities and the diversity and complexity of immune infiltration in TME. We established the CD_Score, which could help enhance our cognition of TME features and facilitate the clinical application of immunotherapy.

Ferroptosis Associates With Diagnosis and Prognosis by Promoting Antitumor Immune Response in Melanoma

Immunotherapy has greatly improved the clinical benefits of cancer treatment, especially in melanoma. Ferroptosis is a novel mechanism of cell death which relates to immunity. This study aimed at understanding the potential link between ferroptosis and cancer immunocompetent in melanoma using multiple bioinformatics analyses. By the WGCNA assay, we first constructed a key module–gene of ferroptosis, which was strongly correlated with the diagnosis, prognosis, and infiltration of immune cells in melanoma. The elevated module–gene could effectively distinguish melanoma from normal tissues and acted as a good prognostic marker. The module–gene of ferroptosis was positively correlated with the infiltration of immune cells. In particular, the module was positively correlated with the expression of PD-L1 and sensitively increased after effective anti-PD-1 treatment. Furthermore, the differential expression of the module–gene between normal and tumor tissues was observed in pan-cancer. The similarity correlations of the module–gene with infiltration of immune cells and the expressions of PD-L1 were confirmed in the pan-cancer level. Our study demonstrated that the key module–gene of ferroptosis was closely related with diagnosis, prognosis, and anti-immune response in melanoma, as well as in pan-cancer.

Development and Validation of a Ferroptosis-Related lncRNAs Prognosis Model in Oral Squamous Cell Carcinoma

Objectives: Ferroptosis is an iron-dependent form of programmed cell death, which affects the prognosis of many cancers. Some long non-coding RNA (lncRNA) can affect the prognosis of cancer by regulating the process of ferroptosis. However, the role of ferroptosis-related lncRNA (frlncRNA) in oral squamous cell carcinoma (OSCC) is not yet clear.

Materials and Methods: The data of OSCC patients were downed from The Cancer Genome Atlas (TCGA). After univariate and multivariate Cox regression analysis, the prognosis-related ferroptosis-related lncRNAs were obtained to construct a prognostic model. Calculated the risk score to divide patients into high and low risk groups, and evaluated the predictive ability of the model and the differential expression of immunity in the high and low risk groups.

Results: The prognostic model for OSCC was constructed based on 8 prognostic-related frlncRNAs which co-expressed with 25 mRNAs. Kaplan-Meier analyses displayed that the risk score is inversely proportional to patient survival. Receiver operating characteristic (ROC) and decision curve analysis (DCA) indicated that the risk score is superior to other clinical characteristics, and independent prognostic analysis demonstated that risk score is independent factor for the overall survival (OS) rate. The results of immunological analysis showed differences in immune cells, functions, immune checkpoints, and m6A expression between high and low risk groups.

Conclusion: We constructed an OSCC patients prognosis model based on 8 frlncRNAs, which can provide prognostic evaluation and immune analysis for OSCC patients, and provided new direction for OSCC targeted therapy.

A Novel Ferroptosis-Related lncRNA Prognostic Model and Immune Infiltration Features in Skin Cutaneous Melanoma

Background: Skin cutaneous melanoma (SKCM) is an aggressive malignant skin tumor. Ferroptosis is an iron-dependent cell death that may mobilize tumor-infiltrating immunity against cancer. The potential mechanism of long non-coding RNAs (lncRNAs) in ferroptosis in SKCM is not clear. In this study, the prognostic and treatment value of ferroptosis-related lncRNAs was explored in SKCM, and a prognostic model was established.

Methods: We first explored the mutation state of ferroptosis-related genes in SKCM samples from The Cancer Genome Atlas database. Then, we utilized consensus clustering analysis to divide the samples into three clusters based on gene expression and evaluated their immune infiltration using gene-set enrichment analysis (GSEA) ESTIMATE and single-sample gene-set enrichment analysis (ssGSEA) algorithms. In addition, we applied univariate Cox analysis to screen prognostic lncRNAs and then validated their prognostic value by Kaplan–Meier (K-M) and transcripts per kilobase million (TPM) value analyses. Finally, we constructed an 18-ferroptosis-related lncRNA prognostic model by multivariate Cox analysis, and SKCM patients were allocated into different risk groups based on the median risk score. The prognostic value of the model was evaluated by K-M and time-dependent receiver operating characteristic (ROC) analyses. Additionally, the immunophenoscore (IPS) in different risk groups was detected.

Results: The top three mutated ferroptosis genes were TP53, ACSL5, and TF. The SKCM patients in the cluster C had the highest ferroptosis-related gene expression with the richest immune infiltration. Based on the 18 prognosis-related lncRNAs, we constructed a prognostic model of SKCM patients. Patients at low risk had a better prognosis and higher IPS.

Conclusion: Our findings revealed that ferroptosis-related lncRNAs were expected to become potential biomarkers and indicators of prognosis and immunotherapy treatment targets of SKCM.