Pan‐cancer analysis of iron metabolic landscape across the Cancer Genome Atlas

MDH2 regulates the sensitivity of clear cell renal cell carcinoma to ferroptosis through its interaction with FSP1

Malate dehydrogenase 2 is a pivotal enzyme in the tricarboxylic acid cycle. Recent studies have highlighted the significant involvement of MDH2 in the pathogenesis and progression of diverse types of tumors, yet its precise mechanistic underpinnings remain elusive. This study revealed a significant decrease in MDH2 expression in renal cancer tissues. And knocking out MDH2 was observed to hinder the proliferation of normal renal tubular epithelial cells but notably enhance the proliferation of ccRCC. Furthermore, mechanistically, we found that MDH2 inhibits the proliferation of ccRCC by promoting ferroptosis, while enhancing the sensitivity of ccRCC to ferroptosis inducers, promoting lipid peroxidation. We also demonstrated that MDH2 regulates the ubiquitination of FSP1 through protein-protein interactions, leading to a decrease in FSP1 protein levels and maintaining high sensitivity of ccRCC to ferroptosis. In conclusion, our study demonstrates that the reduced MDH2 expression in ccRCC results in increased expression of FSP1, thereby reducing its sensitivity to ferroptosis. It unveils a non-metabolic role for the downregulation of MDH2 in ccRCC progression.

NOX2 Enzyme Mimicking Nano-Networks Regulate Tumor-Associated Macrophages to Initiate Both Innate and Adaptive Immune Effects

Macrophages, capable of both direct killing and antigen presentation, are crucial for the interplay between innate and adaptive immunity. However, strategies mainly focus on polarizing tumor-associated macrophages (TAMs) to M1 phenotype, while overlooking the inefficient antigen cross-presentation due to hyperactive hydrolytic protease within lysosomes which leads to antigen degradation. In light of the significant influence of reactive oxygen species (ROS) on TAMs' polarization and the inhibition of phagosomal proteolysis, a novel nanosystem termed OVA-Fe-GA (OFG) is engineered, drawing inspiration from the NOX2 enzyme's role. OFG integrates ovalbumin (OVA) and a network composed of Fe-gallic acid (GA), emulating the NOX2 enzyme's sequential ROS generation process ("O2 to O2 •- to H2O2/•OH"). Furthermore, it elucidates a biological mechanism that augments antigen cross-presentation by suppressing the expression of cysteine proteases. OFG restores the innate anti-tumor functionality of TAMs and significantly amplifies their antigen cross-presentation (4.5-fold compared to the PBS control group) in B16-OVA tumor-bearing mice. Notably, the infiltration and activity of intratumoral CD8+ T cells are enhanced, indicating an adaptive immune response. Moreover, OFG exhibits excellent photothermal properties, thereby fostering a system antitumor immune response. This study provides a promising strategy for initiating both innate and adaptive immunity via TAMs activation.

Global analysis of iron metabolism-related genes identifies potential mechanisms of gliomagenesis and reveals novel targets

AIMS

This study aimed to investigate key regulators of aberrant iron metabolism in gliomas, and evaluate their effect on biological functions and clinical translational relevance.

METHODS

We used transcriptomic data from multiple cross-platform glioma cohorts to identify key iron metabolism-related genes (IMRGs) based on a series of bioinformatic and machine learning methods. The associations between IMRGs and prognosis, mesenchymal phenotype, and genomic alterations were analyzed in silico. The performance of the IMRGs-based signature in predicting temozolomide (TMZ) treatment sensitivity was evaluated. In vitro and in vivo experiments were used to explore the biological functions of these key IMRGs.

RESULTS

HMOX1, LTF, and STEAP3 were identified as the most essential IMRGs in gliomas. The expression levels of these genes were strongly related to clinicopathological and molecular features. The robust IMRG-based gene signature could be used for prognosis prediction. These genes facilitate mesenchymal transformation, driver gene mutations, and oncogenic alterations in gliomas. The gene signature was also associated with TMZ resistance. HMOX1, LTF, and STEAP3 knockdown in glioma cells significantly reduced cell proliferation, colony formation, migration, and malignant invasion.

CONCLUSION

The study presented a comprehensive view of key regulators underpinning iron metabolism in gliomas and provided new insights into novel therapeutic approaches.

Fatty acid metabolism-related genes as a novel module biomarker for kidney renal clear cell carcinoma: Bioinformatics modeling with experimental verification

BACKGROUNDS

Lipid metabolism reprogramming is a hallmark of cancer, however, the associations between fatty acid metabolism (FAM) and kidney renal clear cell carcinoma (KIRC) prognosis are still less investigated.

METHODS

The gene expression and clinical data of KIRC were obtained from TCGA. Using Cox regression and LASSO regression, a novel prognostic risk score model based on FAM-related genes was constructed, and a nomogram for prediction of overall survival rate of patients with KIRC was proposed. The correlation between risk score and the immune cell infiltration, immune-related function and tumor mutation burden (TMB) were explored. Finally, a hub gene was extracted from the model, and RT-qPCR, Western blot, Immunohistochemical, EdU, Scratch assay and Transwell experiments were conducted to validate and decipher the biomarker role of the hub gene in KIRC theranostics.

RESULTS

In this study, a novel risk score model and a nomogram were constructed based on 20 FAM-related genes to predict the prognosis of KIRC patients with AUC>0.7 at 1-, 3-, and 5-years. Patients in different subgroups showed different phenotypes in immune cell infiltration, immune-related function, TMB, and sensitivity to immunotherapy. In particular, the hub gene in the model, i.e., ACADM, was significantly down-expressed in human KIRC samples, and the knockdown of OCLN promoted proliferation, migration and invasion of KIRC cells in vitro.

CONCLUSIONS

In this study, a novel risk score model and a module biomarker based on FAM-related genes were screened for KIRC prognosis. More clinical carcinogenic validations will be performed for future translational applications of the findings.

Analysis and experimental validation of fatty acid metabolism-related genes prostacyclin synthase (PTGIS) in endometrial cancer

The deregulation of fatty acid metabolism plays a pivotal role in cancer. Our objective is to construct a prognostic model for patients with endometrial carcinoma (EC) based on genes related to fatty acid metabolism-related genes (FAMGs). RNA sequencing and clinical data for EC were obtained from The Cancer Genome Atlas (TCGA). Lasso-Penalized Cox regression was employed to derive the risk formula for the model, the score = esum(corresponding coefficient × each gene's expression). Gene set enrichment analysis (GSEA) was utilized to examine the enrichment of KEGG and GO pathways within this model. Correlation analysis of immune function was conducted using Single-sample GSEA (ssGSEA). The "ESTIMATE" package in R was utilized to evaluate the tumor microenvironment. The support vector machine recursive feature elimination (SVM-RFE) and randomforest maps were employed to identify key genes. The effects of PTGIS on the malignant biological behavior of EC were assessed through CCK-8 assay, transwell invasion assay, cell cycle analysis, apoptosis assay, and tumor xenografts in nude mice. A novel prognostic signature comprising 10 FAMGs (INMT, ACACB, ACOT4, ACOXL, CYP4F3, FAAH, GPX1, HPGDS, PON3, PTGIS) was developed. This risk score serves as an independent prognostic marker validated for EC. According to ssGSEA analysis, the low- and high-risk groups exhibited distinct immune enrichments. The key gene PTGIS was screened by SVM-RFE and randomforest method. Furthermore, we validated the expression of PTGIS through qRT-PCR. In vitro and in vivo experiments also confirmed the effect of PTGIS on the malignant biological behavior of EC.

Dysregulated Iron Homeostasis as Common Disease Etiology and Promising Therapeutic Target

Iron is irreplaceably required for animal and human cells as it provides the activity center for a wide variety of essential enzymes needed for energy production, nucleic acid synthesis, carbon metabolism and cellular defense. However, iron is toxic when present in excess and its uptake and storage must, therefore, be tightly regulated to avoid damage. A growing body of evidence indicates that iron dysregulation leading to excess quantities of free reactive iron is responsible for a wide range of otherwise discrete diseases. Iron excess can promote proliferative diseases such as infections and cancer by supplying iron to pathogens or cancer cells. Toxicity from reactive iron plays roles in the pathogenesis of various metabolic, neurological and inflammatory diseases. Interestingly, a common underlying aspect of these conditions is availability of excess reactive iron. This underpinning aspect provides a potential new therapeutic avenue. Existing hematologically used iron chelators to take up excess iron have shown serious limitations for use but new purpose-designed chelators in development show promise for suppressing microbial pathogen and cancer cell growth, and also for relieving iron-induced toxicity in neurological and other diseases. Hepcidin and hepcidin agonists are also showing promise for relieving iron dysregulation. Harnessing iron-driven reactive oxygen species (ROS) generation with ferroptosis has shown promise for selective destruction of cancer cells. We review biological iron requirements, iron regulation and the nature of iron dysregulation in various diseases. Current results pertaining to potential new therapies are also reviewed.

Deregulated expression of the 14q32 miRNA cluster in clear cell renal cancer cells

Clear cell renal cell carcinomas (ccRCC) are characterized by arm-wide chromosomal alterations. Loss at 14q is associated with disease aggressiveness in ccRCC, which responds poorly to chemotherapeutics. The 14q locus contains one of the largest miRNA clusters in the human genome; however, little is known about the contribution of these miRNAs to ccRCC pathogenesis. In this regard, we investigated the expression pattern of selected miRNAs at the 14q32 locus in TCGA kidney tumors and in ccRCC cell lines. We demonstrated that the miRNA cluster is downregulated in ccRCC (and cell lines) as well as in papillary kidney tumors relative to normal kidney tissues (and primary renal proximal tubule epithelial (RPTEC) cells). We demonstrated that agents modulating expression of DNMT1 (e.g., 5-Aza-deoxycytidine) could modulate 14q32 miRNA expression in ccRCC cell lines. Lysophosphatidic acid (LPA, a lysophospholipid mediator elevated in ccRCC) not only increased labile iron content but also modulated expression of a 14q32 miRNA. Through an overexpression approach targeting a subset of 14q32 miRNAs (specifically at subcluster A: miR-431-5p, miR-432-5p, miR-127-3p, and miR-433-3p) in 769-P cells, we uncovered changes in cellular viability and claudin-1, a tight junction marker. A global proteomic approach was implemented using these miRNA overexpressing cell lines which uncovered ATXN2 as a highly downregulated target. Collectively, these findings support a contribution of miRNAs at 14q32 in ccRCC pathogenesis.

Mitochondrial Iron Metabolism: The Crucial Actors in Diseases

Iron is a trace element necessary for cell growth, development, and cellular homeostasis, but insufficient or excessive level of iron is toxic. Intracellularly, sufficient amounts of iron are required for mitochondria (the center of iron utilization) to maintain their normal physiologic function. Iron deficiency impairs mitochondrial metabolism and respiratory activity, while mitochondrial iron overload promotes ROS production during mitochondrial electron transport, thus promoting potential disease development. This review provides an overview of iron homeostasis, mitochondrial iron metabolism, and how mitochondrial iron imbalances-induced mitochondrial dysfunction contribute to diseases.

Integrated bioinformatics analysis and experimental validation reveals fatty acid metabolism-related prognostic signature and immune responses for uterine corpus endometrial carcinoma

Background

Uterine corpus endometrial carcinoma (UCEC) is the third most common gynecologic malignancy. Fatty acid metabolism (FAM) is an essential metabolic process in the immune microenvironment that occurs reprogramming in the presence of tumor signaling and nutrient competition. This study aimed to identify the fatty acid metabolism-related genes (FAMGs) to develop a risk signature for predicting UCEC.

Methods

The differentially expressed FAMGs between UCEC samples and controls from TCGA database were discovered. A prognostic signature was then constructed by univariate, least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analyses. Based on the median risk score, UCEC samples were categorized into high- and low-FAMGs groups. Kaplan-Meier (K-M) curve was applied to determine patients’ overall survival (OS). The independent prognostic value was assessed by uni- and multivariate analyses. The associations between the risk score and immune status, immune score, and drug resistance were evaluated. Quantitative Real-time PCR (qRT-PCR) was utilized to confirm FAMGs expression levels in UCEC cells.

Results

We built a 10-FAMGs prognostic signature and examined the gene mutation and copy number variations (CNV). Patients with a high-FAMGs had a worse prognosis compared to low-FAMGs patients in TCGA train and test sets. We demonstrated that FAMGs-based risk signature was a significant independent prognostic predictor of UCEC. A nomogram was also created incorporating this risk model and clinicopathological features, with high prognostic performance for UCEC. The immune status of each group was varied, and immune score was higher in a low-FAMGs group. HLA-related genes such as DRB1, DMA, DMB, and DQB2 had higher expression levels in the low-FAMGs group. Meanwhile, high-FAMGs patients were likely to response more strongly to the targeted drugs Bortezomib, Foretinib and Gefitinib. The qRT-PCR evidence further verified the significant expression of FAMGs in this signature.

Conclusions

A FAMGs-based risk signature might be considered as an independent prognostic indicator to predict UCEC prognosis, evaluate immune status and provide a new direction for therapeutic strategies.

Iron metabolism-related genes reveal predictive value of acute coronary syndrome

Iron deficiency has detrimental effects in patients with acute coronary syndrome (ACS), which is a common nutritional disorder and inflammation-related disease affects up to one-third people worldwide. However, the specific role of iron metabolism in ACS progression is opaque. In this study, we construct an iron metabolism-related genes (IMRGs) based molecular signature of ACS and to identify novel iron metabolism gene markers for early stage of ACS. The IMRGs were mainly collected from Molecular Signatures Database (mSigDB) and two relevant studies. Two blood transcriptome datasets GSE61144 and GSE60993 were used for constructing the prediction model of ACS. After differential analysis, 22 IMRGs were differentially expressed and defined as DEIGs in the training set. Then, the 22 DEIGs were trained by the Elastic Net to build the prediction model. Five genes, PADI4, HLA-DQA1, LCN2, CD7, and VNN1, were determined using multiple Elastic Net calculations and retained to obtain the optimal performance. Finally, the generated model iron metabolism-related gene signature (imSig) was assessed by the validation set GSE60993 using a series of evaluation measurements. Compared with other machine learning methods, the performance of imSig using Elastic Net was superior in the validation set. Elastic Net consistently scores the higher than Lasso and Logistic regression in the validation set in terms of ROC, PRC, Sensitivity, and Specificity. The prediction model based on iron metabolism-related genes may assist in ACS early diagnosis.

Novel iron chelator SK4 demonstrates cytotoxicity in a range of tumour derived cell lines

Iron is an essential micronutrient due to its involvement in many cellular processes including DNA replication and OXPHOS. Tumors overexpress iron metabolism linked proteins which allow for iron accumulation driving high levels of proliferation. Our group has designed novel iron chelator SK4 which targets cancer’s “iron addiction.” SK4 comprises of two key moieties: an iron chelation moiety responsible for cytotoxicity and an amino acid moiety which allows entry through amino acid transporter LAT1. We selected LAT1 as a route of entry as it is commonly overexpressed in malignant tumors. SK4 has previously demonstrated promising results in an in vitro model for melanoma. We hypothesized SK4 would be effective against a range of tumor types. We have screened a panel of tumor-derived cell lines from different origins including breast, prostate, ovarian and cervical cancer for SK4 sensitivity and we have found a range of differential sensitivities varying from 111.3 to >500 μM. We validated the iron chelation moiety as responsible for inducing cytotoxicity through control compounds; each lacking a key moiety. Following the screen, we conducted a series of assays to elucidate the mechanism of action behind SK4 cytotoxicity. SK4 was shown to induce apoptosis in triple negative breast cancer cell line MDA MB 231 but not ovarian cancer cell line SKOV3 suggesting SK4 may induce different modes of cell death in each cell line. As MDA MB 231 cells harbor a mutation in p53, we conclude SK4 is capable of inducing apoptosis in a p53-independent manner. SK4 upregulated NDRG1 expression in MDA MB 231 and SKOV3 cells. Interestingly, knockdown of NDRG1 antagonized SK4 in MDA MB 231 cells but not SKOV3 cells suggesting SK4’s mechanism of action may be mediated through NDRG1 in MDA MB 231 cells. In conclusion, we have shown tagging iron chelators with an amino acid moiety to allow entry through the LAT1 transporter represents a double pronged approach to cancer therapy, targeting “iron addiction” and amino acid metabolism dysregulation.

ATP6AP1 is a potential prognostic biomarker and is associated with iron metabolism in breast cancer

Cancer occurrence and progression may be facilitated by aberrant expression of ATPase H+ transporting accessory protein 1 (ATP6AP1). However, the clinical relevance of ATP6AP1 in breast cancer remains unclear. In this study, we investigated the association between ATP6AP1 and breast cancer. Data collected from patients with breast cancer from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) were used in this study. To determine the relationship between ATP6AP1 and breast cancer survival rates, Kaplan-Meier analysis was used. To determine the prognostic value of ATP6AP1, a receiver operating characteristic (ROC) curve was constructed. To identify the major pathways involving ATP6AP1, we performed functional enrichment analysis using gene set enrichment analysis (GSEA). We analyzed the association between ATP6AP1 expression and tumor immunity using the ESTIMATE algorithm and single-sample GSEA (ssGSEA). A nomogram based on a Cox regression analysis was constructed to predict the impact of ATP6AP1 on prognosis. ATP6AP1 expression was significantly upregulated in breast cancer tissues. Moreover, patients with elevated ATP6AP1 expression had shorter total survival rates than those with lower expression levels (p = 0.032). The area under the receiver operating characteristic curve for ATP6AP1 was 0.939. Gene set enrichment analysis revealed that reaction iron uptake and transport, proteasome degradation, glutathione metabolism, and pyruvate metabolism were enriched in the ATP6AP1 high expression phenotype. The relationship between immune infiltration cells and ATP6AP1 expression, including macrophages, B cells, dendritic cells, cytotoxic cells, NK cells, and T cells, was found to be negative, suggesting that ATP6AP1 overexpression results in immunosuppression. Based on the Cox regression analyses, the calibration plot of the nomogram demonstrated effective performance in predicting breast cancer patients. ATP6AP1 may facilitate breast cancer progression by inhibiting antitumor immunity and promoting iron metabolism and may be a biomarker for breast cancer prognosis.

Establishing a prognostic model of ferroptosis- and immune-related signatures in kidney cancer: A study based on TCGA and ICGC databases

Background

Kidney cancer (KC) is one of the most challenging cancers due to its delayed diagnosis and high metastasis rate. The 5-year survival rate of KC patients is less than 11.2%. Therefore, identifying suitable biomarkers to accurately predict KC outcomes is important and urgent.

Methods

Corresponding data for KC patients were obtained from the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA) databases. Systems biology/bioinformatics/computational approaches were used to identify suitable biomarkers for predicting the outcome and immune landscapes of KC patients.

Results

We found two ferroptosis- and immune-related differentially expressed genes (FI-DEGs) (Klotho (KL) and Sortilin 1 (SORT1)) independently correlated with the overall survival of KC patients. The area under the curve (AUC) values of the prognosis model using these two FI-DEGs exceeded 0.60 in the training, validation, and entire groups. The AUC value of the 1-year receiver operating characteristic (ROC) curve reached 0.70 in all the groups.

Conclusions

Our present study indicated that KL and SORT1 could be prognostic biomarkers for KC patients. Whether this model can be used in clinical settings requires further validation.

Characterization of Fatty Acid Metabolism-Related Genes Landscape for Predicting Prognosis and Aiding Immunotherapy in Glioma Patients

Glioma is a highly malignant brain tumor with a poor survival rate. The involvement of fatty acid metabolism in glioma was examined to find viable treatment options. The information was gathered from the Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA) databases. A prognostic signature containing fatty acid metabolism-dependent genes (FAMDs) was developed to predict glioma outcome by multivariate and most minor absolute shrinkage and selection operator (LASSO) regression analyses. In the TCGA cohort, individuals with a good score had a worse prognosis than those with a poor score, validated in the CGGA cohort. According to further research by “pRRophetic” R package, higher-risk individuals were more susceptible to crizotinib. According to a complete study of the connection between the predictive risk rating model and tumor microenvironment (TME) features, high-risk individuals were eligible for activating the immune cell-associated receptor pathway. We also discovered that anti-PD-1/PD-L1 and anti-CTLA4 immunotherapy are more effective in high-risk individuals. Furthermore, we demonstrated that CCNA2 promotes glioma proliferation, migration, and invasion and regulates macrophage polarization. Therefore, examining the fatty acid metabolism pathway aids our understanding of TME invasion properties, allowing us to develop more effective immunotherapies for glioma.

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.

Prognosis and Dissection of Immunosuppressive Microenvironment in Breast Cancer Based on Fatty Acid Metabolism-Related Signature

Fatty acid metabolism has been deciphered to augment tumorigenesis and disease progression in addition to therapy resistance via strengthened lipid synthesis, storage, and catabolism. Breast cancer is strongly associated with the biological function of fatty acid metabolism owing to the abundant presence of adipocytes in breast tissue. It has been unraveled that tumor cells exhibit considerable plasticity based on fatty acid metabolism, responding to extra-tumoral and a range of metabolic signals, in which tumor microenvironment plays a pivotal role. However, the prognostic significance of fatty acid metabolism in breast cancer remains to be further investigated. Alongside these insights, we retrieved 269 reliable fatty acid metabolism-related genes (FMGs) and identified the landscape of copy number variations and expression level among those genes. Additionally, 11 overall survival-related FMGs were clarified by univariate Cox hazards regression analysis in The Cancer Genome Atlas (TCGA) and the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) databases. Subsequently, a prognostic signature based on 6 overall survival (OS)-related FMGs was generated using Lasso Cox hazards regression analysis in TCGA dataset and was validated in two external cohorts. The correlation between the signature and several essential clinical parameters, including T, N, and PAM50 subtypes, was unveiled by comparing the accumulating signature value in various degrees. Furthermore, an optimal nomogram incorporating the signature, age, and American Joint Committee on Cancer (AJCC) stage was constructed, and the discrimination was verified by C-index, the calibration curve, and the decision curve analysis. The underlying implications for immune checkpoints inhibitors, the landscape of tumor immune microenvironment, and the predictive significance in therapy resistance to diverse strategies were depicted ultimately. In conclusion, our findings indicate the potential prognostic connotation of fatty acid metabolism in breast cancer, supporting novel insights into breast cancer patients’ prognosis and administrating effective immunotherapy.

Identification of Ferroptosis-Related Genes as Biomarkers for Sarcoma

Sarcomas are seen as mixed-up nature with genetic and transcriptional heterogeneity and poor prognosis. Although the genes involved in ferroptosis are still unclear, iron loss is considered to be the core of glioblastoma, tumor progression, and tumor microenvironment. Here, we developed and tested the prognosis of SARC, which is a genetic marker associated with iron residues. The ferroptosis-related gene expression, one-way Cox analysis, and least-selection absolute regression algorithm (LASSO) are used to track prognostic-related genes and create risk assessment models. Finally, immune system infiltration and immune control point analysis are used to study the characteristics of the tumor microenvironment related to risk assessment. Moreover, LncRNA–miRNA–mRNA network was contributed in our studies. We determined the biomarker characteristics associated with iron degradation in gene 32 and developed a risk assessment model. ROC analysis showed that its model was accurately predicted, with 1, 2, 3, 4, and 5 years of overall survival in TCGA cohort of SARC patients. A comparative analysis of settings found that overall survival (OS) was lower in the high-risk than that in the low-risk group. The nomogram survival prediction model also helped to predict the OS of SARC patients. The nomogram survival prediction model has strong predictive power for the overall survival of SARC patients in TCGA dataset. GSEA analysis shows that high-risk groups are rich in inflammation, cancer-related symptoms, and pathological processes. High risk is related to immune cell infiltration and immune checkpoint. Our prediction model is based on SARC ferritin-related genes, which may support SARC prediction and provide potential attack points.

Iron, hepcidin, and microcytosis in canine hepatocellular carcinoma

BACKGROUND

Erythrocyte microcytosis in some dogs with hepatocellular carcinoma (HCC) suggests a derangement in systemic iron. Hepcidin, the master regulator of iron, is secreted by the liver in response to interleukin 6 (IL-6) and/or bone morphogenetic protein 6 (BMP6) and can cause microcytosis.

OBJECTIVES

Pilot study to compare the quantities of hepcidin, IL-6, and BMP6 RNA molecules in archival tumoral (HCC) and adjacent peritumoral (non-HCC) hepatic tissue to determine if they are different between tissue types or associated with microcytosis.

METHODS

RNA was isolated from formalin-fixed, paraffin-embedded HCC and non-HCC tissue from seven microcytic dogs and four normocytic dogs. Digital RNA counts of hepcidin, IL-6, or BMP6, and six other iron-regulatory genes were determined using the Nanostring nCounter system. The area of blue on each section was digitally evaluated to measure the extent of Prussian blue staining objectively. Parameters were compared between HCC and non-HCC tissue and between microcytic and normocytic groups.

RESULTS

Hepcidin was decreased, and transferrin receptor 1 (TfR1) was increased in HCC tissue compared with non-HCC tissue. Non-HCC hepcidin RNA counts correlated negatively with MCV and positively with the extent of iron staining. Hepcidin expression was higher in non-HCC tissue of microcytic cases than in normocytic cases.

CONCLUSIONS

Canine HCC cases showed relatively increased iron staining in non-HCC tissue and decreased hepcidin RNA in HCC tissue. Microcytic cases had higher hepcidin RNA in non-HCC tissue than normocytic cases. Future studies may extend these findings to protein quantification, cellular localization of RNA changes, and determining if iron loading in canine liver is a predisposing factor for HCC.

Identification of Five Ferroptosis-Related LncRNAs as Novel Prognosis and Diagnosis Signatures for Renal Cancer

Background: Ferroptosis is a novel regulated cell death that is characterized by iron-dependent oxidative damage. Renal cancer is the second most common cancer of the urinary system, which is highly correlated with iron metabolism. The aim of our present study was to identify suitable ferroptosis-related prognosis signatures for renal cancer.

Methods: We downloaded the RNA-seq count data of renal cancer from The Cancer Genome Atlas database and used the DESeq2, Survival, and Cox regression analyses to screen the prognosis signatures.

Results: We identified 5 ferroptosis-related differentially expressed lncRNAs (FR-DELs) (DOCK8-AS1, SNHG17, RUSC1-AS1, LINC02609, and LUCAT1) to be independently correlated with the overall survival (OS) of patients with renal cancer. The risk assessment model and diagnosis model constructed by those 5 FR-DELs could well predict the outcome and the diagnosis of renal cancer.

Conclusion: Our present study not only suggested those 5 FR-DELs could be used as prognosis and diagnosis signatures for renal cancer but also provided strategies for other cancers in the screening of ferroptosis-related biomarkers.

Understanding the role of cysteine in ferroptosis: progress & paradoxes

Cysteine is a conditionally essential amino acid required for the synthesis of proteins and many important intracellular metabolites. Cysteine depletion can trigger iron-dependent nonapoptotic cell death-ferroptosis. Despite this, cysteine itself is normally maintained at relatively low levels within the cell, and many mechanisms that could act to buffer cysteine depletion do not appear to be especially effective or active, at least in cancer cells. How do we reconcile these seemingly paradoxical features? Here, we describe the regulation of cysteine and its contribution to ferroptosis and speculate about how the levels of this amino acid are controlled to govern nonapoptotic cell death.

Integrative analysis of the molecular mechanisms, immunological features and immunotherapy response of ferroptosis regulators across 33 cancer types

Ferroptosis is a recently described mode of cell death caused by the accumulation of intracellular iron and lipid reactive oxygen species (ROS), which play critical roles in tumorigenesis and cancer progression. However, the underlying molecular mechanisms and promising biomarkers of ferroptosis among cancers remain to be elucidated. In this study, 30 ferroptosis regulators in ferroptosis-related signaling pathways were identified and analyzed in 33 cancer types. We found transcriptomic aberrations and evaluated the prognostic value of ferroptosis regulators across 33 cancer types. Then, we predicted and validated potential transcription factors (including E2F7, KLF5 and FOXM1) and therapeutic drugs (such as cyclophosphamide, vinblastine, and gefitinib) that target ferroptosis regulators in cancer. Moreover, we explored the molecular mechanisms of ferroptosis and found that signaling pathways such as the IL-1 and IL-2 pathways are closely associated with ferroptosis. Additionally, we found that ferroptosis regulators have a close relationship with immunity-related parameters, including the immune score, immune cell infiltration level, and immune checkpoint protein level. Finally, we determined a ferroptosis score using GSVA method. We found that the ferroptosis score effectively predicted ferroptotic cell death in tumor samples. And ferroptosis score is served as an independent prognostic indicator for the incidence and recurrence of cancers. More importantly, patients with high ferroptosis scores received greater benefit from immunotherapy. We aslo created an online webserver based on the nomogram prognostic model to predict the survival in immunotherapy cohort. The reason for this outcome is partially the result of patients with a high ferroptosis rate also having high immune scores, HLA-related gene expression and immune checkpoint protein expression, such as PDL2 and TIM3. Moreover, patients with high ferroptosis scores exhibited CD8 T cell and TIL infiltration and immune-related signaling pathway enrichment. In summary, we systematically summarize the molecular characteristics, clinical relevance and immune features of ferroptosis across cancers and show that the ferroptosis score can be used as a prognostic factor and for the evaluation of immunotherapy effects.

Nanomedicine Targets Iron Metabolism for Cancer Therapy

Iron is an essential element for cell proliferation and homeostasis by engaging in cell metabolism including DNA synthesis, cell cycle, and redox cycling; however, iron overload could contribute to tumor initiation, proliferation, metastasis, and angiogenesis. Therefore, manipulating iron metabolisms, such as using iron chelators, transferrin receptor 1 (TFR1) Abs, and cytotoxic ligands conjugated to transferrin, has become a considerable strategy for cancer therapy. However, there remain major limitations for potential translation to the clinic based on the regulation of iron metabolism in cancer treatment. Nanotechnology has made great advances for cancer treatment by improving the therapeutic potential and lowering the side‐effects of the proved drugs and those under various stages of development. Early studies that combined nanotechnology with therapeutic means for the regulation of iron metabolism have shown certain promise for developing specific treatment options based on the intervention of cancer iron acquisition, transportation, and utilization. In this review, we summarize the current understanding of iron metabolism involved in cancer and review the recent advances in iron‐regulatory nanotherapeutics for improved cancer therapy. We also envision the future development of nanotherapeutics for improved treatment for certain types of cancers.

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.

Proteogenomic analysis of pancreatic cancer subtypes

Pancreatic cancer remains a significant public health problem with an ever-rising incidence of disease. Cancers of the pancreas are characterised by various molecular aberrations, including changes in the proteomics and genomics landscape of the tumour cells. Therefore, there is a need to identify the proteomic landscape of pancreatic cancer and the specific genomic and molecular alterations associated with disease subtypes. Here, we carry out an integrative bioinformatics analysis of The Cancer Genome Atlas dataset, including proteomics and whole-exome sequencing data collected from pancreatic cancer patients. We apply unsupervised clustering on the proteomics dataset to reveal the two distinct subtypes of pancreatic cancer. Using functional and pathway analysis based on the proteomics data, we demonstrate the different molecular processes and signalling aberrations of the pancreatic cancer subtypes. In addition, we explore the clinical characteristics of these subtypes to show differences in disease outcome. Using datasets of mutations and copy number alterations, we show that various signalling pathways previously associated with pancreatic cancer are altered among both subtypes of pancreatic tumours, including the Wnt pathway, Notch pathway and PI3K-mTOR pathways. Altogether, we reveal the proteogenomic landscape of pancreatic cancer subtypes and the altered molecular processes that can be leveraged to devise more effective treatments.

Identification of Iron Metabolism-Related Genes as Prognostic Indicators for Lower-Grade Glioma

Lower-grade glioma (LGG) is characterized by genetic and transcriptional heterogeneity, and a dismal prognosis. Iron metabolism is considered central for glioma tumorigenesis, tumor progression and tumor microenvironment, although key iron metabolism-related genes are unclear. Here we developed and validated an iron metabolism-related gene signature LGG prognosis. RNA-sequence and clinicopathological data from The Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA) were downloaded. Prognostic iron metabolism-related genes were screened and used to construct a risk-score model via differential gene expression analysis, univariate Cox analysis, and the Least Absolute Shrinkage and Selection Operator (LASSO)-regression algorithm. All LGG patients were stratified into high- and low-risk groups, based on the risk score. The prognostic significance of the risk-score model in the TCGA and CGGA cohorts was evaluated with Kaplan-Meier (KM) survival and receiver operating characteristic (ROC) curve analysis. Risk- score distributions in subgroups were stratified by age, gender, the World Health Organization (WHO) grade, isocitrate dehydrogenase 1 (IDH1) mutation status, the O6-methylguanine-DNA methyl-transferase (MGMT) promoter-methylation status, and the 1p/19q co-deletion status. Furthermore, a nomogram model with a risk score was developed, and its predictive performance was validated with the TCGA and CGGA cohorts. Additionally, the gene set enrichment analysis (GSEA) identified signaling pathways and pathological processes enriched in the high-risk group. Finally, immune infiltration and immune checkpoint analysis were utilized to investigate the tumor microenvironment characteristics related to the risk score. We identified a prognostic 15-gene iron metabolism-related signature and constructed a risk-score model. High risk scores were associated with an age of > 40, wild-type IDH1, a WHO grade of III, an unmethylated MGMT promoter, and 1p/19q non-codeletion. ROC analysis indicated that the risk-score model accurately predicted 1-, 3-, and 5-year overall survival rates of LGG patients in the both TCGA and CGGA cohorts. KM analysis showed that the high-risk group had a much lower overall survival than the low-risk group (P < 0.0001). The nomogram model showed a strong ability to predict the overall survival of LGG patients in the TCGA and CGGA cohorts. GSEA analysis indicated that inflammatory responses, tumor-associated pathways, and pathological processes were enriched in high-risk group. Moreover, a high risk score correlated with the infiltration immune cells (dendritic cells, macrophages, CD4+ T cells, and B cells) and expression of immune checkpoint (PD1, PDL1, TIM3, and CD48). Our prognostic model was based on iron metabolism-related genes in LGG, can potentially aid in LGG prognosis, and provides potential targets against gliomas.

SNU-333 Cells as an Appropriate Cell Line for the Orthotopic Renal Cell Carcinoma Model

Objective: To investigate a feasible candidate for an appropriate cell line for the orthotopic renal cell carcinoma (RCC) model. Methods: Normal human proximal tubule cells (HK-2) and RCC cells were used for MTT assay, Western blotting, sphere-forming assay, and orthotopic injection of BALB/c-nude mice. Immunohistochemistry was adopted in tissue arrays and orthotopic tumors. Results: Primary RCC cells showed resistance to a GPX4 inhibitor compared to HK-2 and to metastatic RCC cells, Caki-1. Caki-2 and SNU-333 cells showed resistance to ferroptosis via increased GPX4 and FTH1, respectively. RCC cells showed increased αSMA, in which Caki-2 and SNU-333 cells exhibited different epithelial–mesenchymal transition and cancer stem cell markers. Caki-1 and SNU-333 cells formed spheres in vitro and orthotopic tumor masses in vivo. The injected SNU-333 tumor only showed high intensities of CD10 and PAX8, markers of renal origin. Conclusion: SNU-333 cell line exhibited resistance via iron metabolism and stemness, and had tumor-initiating capacities in vitro and in vivo. These results suggest that among the cells tested, SNU-333 cells were the most promising for the establishment of an orthotopic RCC model for further researches.

A Novel Prognostic Model Based on Ferroptosis-Related Gene Signature for Bladder Cancer

Background

Bladder cancer (BC) is a molecular heterogeneous malignant tumor; the treatment strategies for advanced-stage patients were limited. Therefore, it is vital for improving the clinical outcome of BC patients to identify key biomarkers affecting prognosis. Ferroptosis is a newly discovered programmed cell death and plays a crucial role in the occurrence and progression of tumors. Ferroptosis-related genes (FRGs) can be promising candidate biomarkers in BC. The objective of our study was to construct a prognostic model to improve the prognosis prediction of BC.

Methods

The mRNA expression profiles and corresponding clinical data of bladder urothelial carcinoma (BLCA) patients were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. FRGs were identified by downloading data from FerrDb. Differential analysis was performed to identify differentially expressed genes (DEGs) related to ferroptosis. Univariate and multivariate Cox regression analyses were conducted to establish a prognostic model in the TCGA cohort. BLCA patients from the GEO cohort were used for validation. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and single-sample gene set enrichment analysis (ssGSEA) were used to explore underlying mechanisms.

Results

Nine genes (ALB, BID, FADS2, FANCD2, IFNG, MIOX, PLIN4, SCD, and SLC2A3) were identified to construct a prognostic model. Patients were classified into high-risk and low-risk groups according to the signature-based risk score. Receiver operating characteristic (ROC) and Kaplan–Meier (K–M) survival analysis confirmed the superior predictive performance of the novel survival model based on the nine-FRG signature. Multivariate Cox regression analyses showed that risk score was an independent risk factor associated with overall survival (OS). GO and KEGG enrichment analysis indicated that apart from ferroptosis-related pathways, immune-related pathways were significantly enriched. ssGSEA analysis indicated that the immune status was different between the two risk groups.

Conclusion

The results of our study indicated that a novel prognostic model based on the nine-FRG signature can be used for prognostic prediction in BC patients. FRGs are potential prognostic biomarkers and therapeutic targets.

A novel ferroptosis-related 12-gene signature predicts clinical prognosis and reveals immune relevancy in clear cell renal cell carcinoma

BACKGROUND

Clear cell renal cell carcinoma (ccRCC) is still highly aggressive and lethal even with various therapeutic approaches. As the kidney is an iron metabolism-related organ, exploring and assessing the clinical value of ferroptosis, an iron-dependent regulated cell death, is practical and important.

METHODS

Prognostic ferroptosis-related differentially expressed genes (DEGs) were identified from the KIRC cohort in the cancer genome atlas (TCGA) database, from which a prognostic signature was established using Lasso-penalized Cox regression analysis. Each patient in the KIRC cohort and the E-MTAB-1980 cohort (from the ArrayExpress database) was assigned a calculated signature-correlated risk score and categorized to be either in the high- or low-risk group divided by the median risk score in the KIRC cohort. Then, the independent prognostic value of the signature was further assessed by Kaplan-Meier (K-M) survival, time-dependent receiver operating characteristic (ROC) and Cox regression analyses based on overall survival (OS) in both cohorts. Finally, risk-related DEGs were identified in both cohorts and subjected to enrichment analyses for Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and immune infiltration.

RESULTS

Among 60 ferroptosis-related genes, 32 prognostic DEGs were identified, from which we constructed a prognostic 12-gene signature with CARS1, HMGCR, CHAC1, GOT1, CD44, STEAP3, AKR1C1, CBS, DPP4, FANCD2, SLC1A5 and NCOA4. Patients in both cohorts were divided into high- and low-risk groups, which were visually distributed in two sets and had positive-risk-related mortality. The K-M survival and the ROC curves validated that the signature has prognostic value with P < 0.05 and area under the curve > 0.7 in both cohorts, respectively. Multivariate Cox regression further confirmed the risk score as an independent prognostic predictor for OS. Commonly enriched terms in GO and KEGG not only showed a high iron correlation but also, interestingly, immune relevance of 3 immune cells (macrophages, mast cells and regulatory T cells) and 1 immune-related function (antigen processing cell co-stimulation).

CONCLUSION

We established a novel 12 ferroptosis-related-gene signature that was proven to be an independent prognostic predictor for OS and inferred to be related to tumour immunity in ccRCC; however, the underlying mechanism is still poorly characterized and needs further exploration.

Prognostic value of fatty acid metabolism-related genes in patients with hepatocellular carcinoma

The deregulation of fatty acid metabolism plays a crucial role in cancer. However, the prognostic value of genes involved in the metabolism in hepatocellular carcinoma (HCC) remains largely unknown. We first constructed a multi-fatty acid metabolic gene prognostic model of HCC based on The Cancer Genome Atlas (TCGA) and further validated it using the International Cancer Genome Consortium (ICGC) database. The model was integrated with the clinical parameters, and a nomogram was built and weighted. Moreover, immune cell infiltration of the tumor microenvironment was investigated. A prognostic model was constructed using 6 selected fatty acid metabolism-related genes, and HCC patients were divided into high- and low-risk groups. Receiver operating characteristic curve (ROC) analysis, principal component analysis (PCA), and t-distributed stochastic neighbor embedding (t-SNE) analysis showed the optimal performance of the model. The concordance index (C-index), ROC curve, calibration plot and decision curve analysis (DCA) all confirmed the satisfactory predictive capacity of the nomogram. The analysis of immune cell infiltration in HCC patients revealed a correlation with different risk levels. Our findings indicate that a prognostic model based on fatty acid metabolism-related genes has superior predictive capacities, which provides the possibility for further improving the individualized treatment of patients with HCC.

SUV39H1 deficiency suppresses clear cell renal cell carcinoma growth by inducing ferroptosis

Clear cell renal cell carcinoma (ccRCC) is a common kidney malignancy characterized by a poor prognosis. Suppressor of variegation 3-9 homolog 1 (SUV39H1), which encodes a histone H3 lysine 9 methyltransferase, has been reported to act as an oncogene in many cancers. However, it is unclear whether SUV39H1 is involved in ccRCC. Here, we report that SUV39H1 expression is frequently upregulated in ccRCC tumors and is significantly correlated with ccRCC progression. SUV39H1 expression level is an independent risk factor for cancer prognosis, and integration with several known prognostic factors predicted ccRCC patient prognosis with improved accuracy than the conventional SSIGN (stage, size, grade and necrosis) prognostic model. Mechanistically, we discovered that siRNA knockdown or pharmacological inhibition of SUV39H1 induced iron accumulation and lipid peroxidation, leading to ferroptosis that disrupted ccRCC cell growth in vitro and in vivo. We also show that SUV39H1 deficiency modulated the H3K9me3 status of the DPP4 (dipeptidyl-peptidase-4) gene promoter, resulting in upregulation of its expression that contributes to ferroptosis. Taken together, our findings provide the mechanistic insight into SUV39H1-dependent epigenetic control of ccRCC tumor growth and indicate that SUV39H1 may serve as a potential therapeutic target for ccRCC treatment.

Reversing oncogenic transformation with iron chelation

Cancer cells accumulate iron to supplement their aberrant growth and metabolism. Depleting cells of iron by iron chelators has been shown to be selectively cytotoxic to cancer cells in vitro and in vivo. Iron chelators are effective at combating a range of cancers including those which are difficult to treat such as androgen insensitive prostate cancer and cancer stem cells. This review will evaluate the impact of iron chelation on cancer cell survival and the underlying mechanisms of action. A plethora of studies have shown iron chelators can reverse some of the major hallmarks and enabling characteristics of cancer. Iron chelators inhibit signalling pathways that drive proliferation, migration and metastasis as well as return tumour suppressive signalling. In addition to this, iron chelators stimulate apoptotic and ER stress signalling pathways inducing cell death even in cells lacking a functional p53 gene. Iron chelators can sensitise cancer cells to PARP inhibitors through mimicking BRCAness; a feature of cancers trademark genomic instability. Iron chelators target cancer cell metabolism, attenuating oxidative phosphorylation and glycolysis. Moreover, iron chelators may reverse the major characteristics of oncogenic transformation. Iron chelation therefore represent a promising selective mode of cancer therapy.

A novel four-gene of iron metabolism-related and methylated for prognosis prediction of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a liver disease with a complex underlying mechanism, and patients with HCC have low survival rates. Iron metabolism plays a crucial role in the pathogenesis of HCC; however, the prognostic value of iron metabolism-related and methylated genes for HCC needs to be further explored. In the present study, we identified differentially expressed genes (DEGs) that play a role in iron metabolism and DNA methylation in HCC from The Cancer Genome Atlas. Four of these DEGs, whose expression levels are correlated with HCC prognosis, namely, RRM2, FTCD, CYP2C9, and ATP6V1C1, were further used to construct a prognostic model for HCC, wherein the risk score was calculated using the gene expression of the four DEGs. This could be used to predict the overall survival of HCC patients for 1, 3, and 5 years. Results of a multivariate Cox regression analysis further indicated that the risk score was an independent variable correlated with the prognosis of HCC patients. The identified gene signature was further validated using an independent cohort of HCC patients from the International Cancer Genome Consortium. Weighted gene co-expression network analysis and gene set enrichment analysis were performed to identify potential regulatory mechanisms of the gene signature in HCC. Taken together, we identified key prognostic factors of iron metabolism-related and methylated genes for HCC, providing a potential treatment strategy for HCC.

An Iron Metabolism-Related SLC22A17 for the Prognostic Value of Gastric Cancer

Purpose

Gastric cancer (GC) is a type of malignant cancer with a poor prognosis. The iron’s metabolism plays an important role in the process of GC. The aim of this study was to evaluate the effectiveness of SLC22A17, associated with iron metabolism, in predicting the prognosis of GC patients.

Materials and Methods

We analyzed genes related to iron metabolism of gastric cancer mRNA-seq data from TCGA database. We identified an iron metabolism-related SLC22A17 as an independent prognostic factor using univariate and multivariate Cox regression analysis.

Results

Further research showed that SLC22A17 was related with many pathways involved in the process of gastric cancer, and the expression was associated with diverse cancer-infiltrating immune cells. The expression of SLC22A17 was associated with T (Topography).

Conclusion

We validated that SLC22A17 associated with iron metabolism could serve as a prognostic biomarker for GC patients.

Iron Dysregulation in Human Cancer: Altered Metabolism, Biomarkers for Diagnosis, Prognosis, Monitoring and Rationale for Therapy

Simple Summary

Iron is the more abundant metal ion in humans. It is essential for life as it has a role in various cellular processes involved, for instance, in cell metabolism and DNA synthesis. These functions are crucial for cell proliferation, and it is therefore not surprising that iron is accumulated in tumors. In this review, we describe normal and altered iron homeostasis mechanisms. We also provide a vision of iron-related proteins with altered expression in cancers and discuss their potential as diagnostic and/or prognostic biomarkers. Finally, we give an overview of therapeutic strategies acting on iron metabolism to fight against cancers.

Abstract

Iron (Fe) is a trace element that plays essential roles in various biological processes such as DNA synthesis and repair, as well as cellular energy production and oxygen transport, and it is currently widely recognized that iron homeostasis is dysregulated in many cancers. Indeed, several iron homeostasis proteins may be responsible for malignant tumor initiation, proliferation, and for the metastatic spread of tumors. A large number of studies demonstrated the potential clinical value of utilizing these deregulated proteins as prognostic and/or predictive biomarkers of malignancy and/or response to anticancer treatments. Additionally, the iron present in cancer cells and the importance of iron in ferroptosis cell death signaling pathways prompted the development of therapeutic strategies against advanced stage or resistant cancers. In this review, we select relevant and promising studies in the field of iron metabolism in cancer research and clinical oncology. Besides this, we discuss some co-existing discrepant findings. We also present and discuss the latest lines of research related to targeting iron, or its regulatory pathways, as potential promising anticancer strategies for human therapy. Iron chelators, such as deferoxamine or iron-oxide-based nanoparticles, which are already tested in clinical trials, alone or in combination with chemotherapy, are also reported.

The ferroptosis and iron-metabolism signature robustly predicts clinical diagnosis, prognosis and immune microenvironment for hepatocellular carcinoma

BACKGROUND

In this study, we comprehensively analyzed genes related to ferroptosis and iron metabolism to construct diagnostic and prognostic models and explore the relationship with the immune microenvironment in HCC.

METHODS

Integrated analysis, cox regression and the least absolute shrinkage and selection operator (LASSO) method of 104 ferroptosis- and iron metabolism-related genes and HCC-related RNA sequencing were performed to identify HCC-related ferroptosis and iron metabolism genes.

RESULTS

Four genes (ABCB6, FLVCR1, SLC48A1 and SLC7A11) were identified to construct prognostic and diagnostic models. Poorer overall survival (OS) was exhibited in the high-risk group than that in the low-risk group in both the training cohort (P < 0.001, HR = 0.27) and test cohort (P < 0.001, HR = 0.27). The diagnostic models successfully distinguished HCC from normal samples and proliferative nodule samples. Compared with low-risk groups, high-risk groups had higher TMB; higher fractions of macrophages, follicular helper T cells, memory B cells, and neutrophils; and exhibited higher expression of CD83, B7H3, OX40 and CD134L. As an inducer of ferroptosis, erastin inhibited HCC cell proliferation and progression, and it was showed to affect Th17 cell differentiation and IL-17 signaling pathway through bioinformatics analysis, indicating it a potential agent of cancer immunotherapy.

CONCLUSIONS

The prognostic and diagnostic models based on the four genes indicated superior diagnostic and predictive performance, indicating new possibilities for individualized treatment of HCC patients. Video Abstract.

The Landscape of Iron Metabolism-Related and Methylated Genes in the Prognosis Prediction of Clear Cell Renal Cell Carcinoma

Background: Clear cell renal cell carcinoma (ccRCC) is characteristics of resistance to chemotherapy and radiotherapy. The prognosis of ccRCC was dismay with immense diversity. Iron metabolism disturbance is a common phenomenon in ccRCC. The purpose of our study is to identify and validate the candidate prognostic gene signature of iron metabolism and methylation closely related to the poor prognosis of ccRCC through comprehensive bioinformatics analysis in The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases.

Methods: The prognostic iron metabolism-related genes were screened according to the overlapping differentially expressed genes (DEGs) from the TCGA database. We built a prognostic model using risk score method to predict OS, each ccRCC patient's risk score was calculated, and the resulting score can divide these patients into two categories according to the cut-point risk score. The prognostic significance of the hub genes was further evaluated with the Kaplan-Meier (KM) survival and Receiver Operating Characteristic (ROC) curve analysis. Univariate and multivariate Cox regression analysis was implemented to evaluate the impact of each variable on OS. Furthermore, the prediction power of the 25 gene signatures has been validated using an independent ccRCC cohort from the GEO database. The Gene Set Enrichment Analysis (GSEA) identified the characteristics of hub related oncogenes. Finally, we utilize Weighted Gene Co-expression Network Analysis (WGCNA) to investigate the co-expression network based on these DEGs.

Results: In this study, we identified and validated 25 iron metabolism-related and methylated genes as the prognostic signatures, which differentiated ccRCC patients into high and low risk subgroups. The KM analysis showed that the survival rate of the high-risk patients was significantly lower than that of the low-risk patients. The risk score calculated with 25 gene signatures could largely predict OS and DFS for 1, 3, and 5 years in patients with ccRCC.

Conclusions: Taken together, we identified the key iron metabolism-related and methylated genes for ccRCC through a comprehensive bioinformatics analysis. This study provides a reliable and robust gene signature for the prognostic predictor of ccRCC patients and maybe provides a promising treatment strategy for this lethal disease.

[Progress on epigenetic regulation of iron homeostasis]

Iron homeostasis plays an important role for the maintenance of human health. It is known that iron metabolism is tightly regulated by several key genes, including divalent metal transport-1(DMT1), transferrin receptor 1(TFR1), transferrin receptor 2(TFR2), ferroportin(FPN), hepcidin(HAMP), hemojuvelin(HJV) and Ferritin H. Recently, it is reported that DNA methylation, histone acetylation, and microRNA (miRNA) epigenetically regulated iron homeostasis. Among these epigenetic regulators, DNA hypermethylation of the promoter region of FPN, TFR2, HAMP, HJV and bone morphogenetic protein 6 (BMP6) genes result in inhibitory effect on the expression of these iron-related gene. In addition, histone deacetylase (HADC) suppresses HAMP gene expression. On the contrary, HADC inhibitor upregulates HAMP gene expression. Additional reports showed that miRNA can also modulate iron absorption, transport, storage and utilization via downregulation of DMT1, FPN, TFR1, TFR2, Ferritin H and other genes. It is noteworthy that some key epigenetic regulatory enzymes, such as DNA demethylase TET2 and histone lysine demethylase JmjC KDMs, require iron for the enzymatic activities. In this review, we summarize the recent progress of DNA methylation, histone acetylation and miRNA in regulating iron metabolism and also discuss the future research directions.

Impact of HFE variants and sex in lung cancer

The homeostatic iron regulator protein HFE is involved in regulation of iron acquisition for cells. The prevalence of two common HFE gene variants (H63D, C282Y) has been studied in many cancer types; however, the impact of HFE variants, sex and HFE gene expression in lung cancer has not been studied. We determined the prevalence of HFE variants and their impact on cancer phenotypes in lung cancer cell lines, in lung cancer patient specimens, and using The Cancer Genome Atlas (TCGA) database. We found that seven out of ten human lung cancer cell lines carry the H63D or C282Y HFE variant. Analysis of lung cancer specimens from our institute (Penn State Hershey Medical Center) revealed a sex and genotype interaction risk for metastasis in lung adenocarcinoma (LUAD) patients; H63D HFE is associated with less metastasis in males compared to wild type (WT) HFE; however, females with the H63D HFE variant tend to develop more metastatic tumors than WT female patients. In the TCGA LUAD dataset, the H63D HFE variant was associated with poorer survival in females compared to females with WT HFE. The frequency of C282Y HFE is higher in female lung squamous cell carcinoma (LUSC) patients of TCGA than males, however the C282Y HFE variant did not impact the survival of LUSC patients. In the TCGA LUSC dataset, C282Y HFE patients (especially females) had poorer survival than WT HFE patients. HFE expression level was not affected by HFE genotype status and did not impact patient's survival, regardless of sex. In summary, these data suggest that there is a sexually dimorphic effect of HFE polymorphisms in the survival and metastatic disease in lung cancer.