A new survival model based on ferroptosis-related genes for prognostic prediction in clear cell renal cell carcinoma

Stepwise single-cell data identifies RNA binding proteins associated with the development of head and neck cancer and tumor microenvironment remodeling

Background: Head and neck squamous cell carcinoma (HNSC) is a globally prevalent malignancy with high mortality rates. RNA-binding proteins (RBPs) are crucial regulators of gene expression and play significant roles in cancer development. However, a comprehensive understanding of RBPs at the single-cell level in HNSC remains limited.ObjectiveThis study aims to investigate the role of RBPs in the stepwise progression of HNSC at the single-cell level, focusing on their expression patterns, prognostic potential, and involvement in key signaling pathways.MethodsWe analyzed single-cell RNA-sequencing data from HNSC samples across four stages, from normal tissue to precancerous leukoplakia, then to primary cancer and finally to metastatic tumors, examining the expression of 2141 previously reported RBPs. We identified RBP-based cell clusters and explored their associations with disease stages, cell types, and cancer progression. A prognostic risk model was developed based on RBPs with significant relevance to patient outcomes.ResultsRBPs displayed distinct cell type-specific expression patterns across different stages of HNSC. We found a significant correlation between RBP-based cell clusters and cancer progression. Notably, a prognostic model was constructed using RBPs such as CELF2, which showed downregulation from early leukoplakia to advanced cancer stages. Fibroblast RBPs were dynamically regulated, particularly in extracellular matrix remodeling, with key proteins like CFL1 and PFN1 linked to improved prognosis. Furthermore, we identified heterogeneity in RBP regulation of the Macrophage Migration Inhibitory Factor (MIF) signaling pathway across cell types during the precancerous stage.ConclusionsOur findings highlight the crucial roles of RBPs in HNSC progression and suggest their potential as therapeutic targets and prognostic markers, offering insights into personalized treatment strategies.

Novel signature of ferroptosis-related long non-coding RNA to predict lower-grade glioma overall survival

BACKGROUND

Ferroptosis is a novel type of programmed cell death in various tumors; however, underlying mechanisms remain unclear. We aimed to develop ferroptosis-related long non-coding RNA (FRlncRNA) risk scores to predict lower-grade glioma (LGG) prognosis and to conduct functional analyses to explore potential mechanisms.

METHODS

LGG-related RNA sequencing data were extracted from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) databases. Pearson correlation analysis was used to identify the FRlncRNAs, univariate Cox regression analysis was for identify the prognostic FRlncRNAs, and then intersection FRlncRNAs were screened between TCGA and CGGA. Least absolute shrinkage and selection operator (LASSO) Cox regression was used to develop a risk score to predict LGG prognosis.

RESULTS

A total of nine FRlncRNAs were screened to construct the novel prognostic risk score of LGG, and high-risk score patients had a worse overall survival than low-risk score patients both in TCGA and CGGA datasets. The risk score was quite correlated with clinicopathological characteristics (age, WHO grade, status of MGMT Methtlation, IDH mutation, 1p/19q codeletion, and TMB), and could promote current molecular subtyping systems. Comprehensive analyses revealed that signaling pathways of B-cell receptor and T-cell receptor, immune cells of macrophage cell and CD4+ T cell, tumor microenvironment of stroma score and immune score, and immune checkpoints of PD-1, PD-L1, and CTLA4 were all enriched in the high-risk score group.

CONCLUSION

The nine FRlncRNAs risk scores was a promising biomarker to predict the LGG's prognosis and distinguish the characteristics of molecular and immune.

Hederagenin promotes lung cancer cell death by activating CHAC1-dependent ferroptosis pathway

Lung cancer poses a significant threat globally, especially in China. This puts higher demands on the treatment methods and drugs for lung cancer. Natural plants provide valuable resources for the development of anti-cancer drugs. Hederagenin (Hed) is a triterpenoid compound extracted from ivy leaves and has anti-tumor activity against multifarious cancers, including lung cancer. However, the regulatory mechanism of Hed in lung cancer remains unclear. In this study, we used Hed to treat lung cancer cells, and observed the effect of Hed on cell proliferation (including CCK-8 and colony formation experiments), apoptosis (including flow cytometry and apoptosis gene detection (BAX and Bcl-2)). The results showed that Hed induced lung cancer cell death (inhibiting proliferation and promoting apoptosis). Next, we performed bioinformatics analysis of the expression profile GSE186218 and found that Hed treatment significantly increased the expression of CHAC1 gene. CHAC1 is a ferroptosis-inducing gene. RT-qPCR detection of lung cancer clinical tissues and related cell lines also showed that CHAC1 was lowly expressed in lung cancer. Therefore, we knocked down and overexpressed CHAC1 in lung cancer cells, respectively. Subsequently, cell phenotype experiments showed that down-regulating CHAC1 expression inhibited lung cancer cell death (promoting proliferation and inhibiting apoptosis); on the contrary, up-regulating CHAC1 expression promoted lung cancer cell death. To further verify that Hed exerts anti-tumor effects in lung cancer by promoting CHAC1 expression, we performed functional rescue experiments. The results showed that down-regulating CHAC1 expression reversed the promoting effect of Hed on lung cancer cell death. Mechanistically, in vitro and in vivo experiments jointly demonstrated that Hed exerts anti-cancer effects by promoting CHAC1-induced ferroptosis. In summary, our study further enriches the regulatory mechanism of Hed in lung cancer.

A Deep Insight into Ferroptosis in Renal Disease: Facts and Perspectives

Background

Ferroptosis, a newly recognized form of programmed cell death, is distinguished by its reliance on reactive oxygen species and iron-mediated lipid peroxidation, setting it apart from established types like apoptosis, cell necrosis, and autophagy. Recent studies suggest its role in exacerbating or mitigating diseases by influencing metabolic and signaling pathways in conditions such as tumors and ischemic organ damage. Evidence also links ferroptosis to various kidney diseases, prompting a review of its research status and potential breakthroughs in understanding and treating these conditions.

Summary

In acute kidney disease (AKI), ferroptosis has been confirmed in animal kidneys after being induced by various factors such as renal ischemia-reperfusion and cisplatin, and glutathione peroxidase 4 (GPX4) is linked with AKI. Ferroptosis is associated with renal fibrosis in chronic kidney disease (CKD), TGF-β1 being crucial in this regard. In diabetic nephropathy (DN), high SLC7A11 and low nuclear receptor coactivator 4 (NCOA4) expressions are linked to disease progression. For polycystic kidney disease (PKD), ferroptosis promotes the disease by regulating ferroptosis in kidney tissue. Renal cell carcinoma (RCC) and lupus nephritis (LN) also have links to ferroptosis, with mtDNA and iron accumulation causing RCC and oxidative stress causing LN.

Key Messages

Ferroptosis is a newly identified form of programmed cell death that is associated with various diseases. It targets metabolic and signaling pathways and has been linked to kidney diseases such as AKI, CKD, PKD, DN, LN, and clear cell RCC. Understanding its role in these diseases could lead to breakthroughs in their pathogenesis, etiology, and treatment.

Computational Approach to Identify the Key Genes for Invasive Lobular Carcinoma (ILC) Diagnosis and Therapies

Invasive Lobular Carcinoma (ILC) is a common form of breast cancer that begins in milk-producing glands lobules and spreads to other parts of the breast. According to the American Cancer Society, about 10–15% of breast cancer cases are ILC. ILC risk rises with age. The number of deaths caused by this cancer each year can be decreased through early diagnosis and if accurate therapy is given. However, diagnosis of ILC is difficult due to its development pattern as it grows as single file strands and not as lumps. Treatments of ILC involve chemotherapy, hormonal therapy and radiation therapy. Drugs that are being used for ILC, are commonly used to treat all types of breast cancer and there are no specific drugs that target receptors of ILC are available. Microarray technology’s emergence helps in finding the differentially expressed genes (DEGs) in malignant cells. From the DEGs, highly interacting genes were identified using the online tool, string. Seven key genes were identified based on the interaction and they are FN1, CDKN2A, COL1A1, COL3A1, COL11A1, LEF1 and IL1B. Thus, the drugs targeting these biomarkers were identified by doing molecular docking using the tool Autodock and molecular dynamic (MD) simulation using the tool iMODs. The response of the identified drugs to the ILC cell line was compared with the control drugs by in silico pharmacogenomic analysis and it was found that the identified drugs have a good response to the ILC cell line.

Bridging the gap between clear cell renal cell carcinoma and cutaneous melanoma: the role of SCARB1 in dysregulated cholesterol metabolism

OBJECTIVE

The metabolism of cholesterol has been found to be closely related to the proliferation, invasion, and metastasis of tumors. The purpose of this study was to investigate the correlation between cholesterol metabolic genes and the prognosis of clear cell renal cell carcinoma (ccRCC).

METHODS

Gene expression profiles and clinical information of individuals diagnosed with prevalent malignant tumors were obtained from the TCGA database. For survival analysis, Kaplan-Meier curves were used. Consensus clustering was utilized to identify distinct molecular clusters. LASSO regression analysis was utilized to construct a novel prognostic signature. Differential analysis was used to analyze the differences in gene expression and various evaluation indicators between different subgroups. RT-qPCR and Immunohistochemistry were performed to examine the gene expression. Small interfering RNA transfection, CCK-8, and clone formation assays were conducted to verify the function of the target gene in ccRCC cell lines.

RESULTS

Based on genes involved in cholesterol metabolism related to survival, two molecular ccRCC subtypes were identified with distinct clinical, immune, and biological features. A molecular signature which would be utilized to evaluate the prognosis and the immune status of the tumor microenvironment of ccRCC patients was also established. The SCARB1-mediated cholesterol-dependent metabolism occurred both in ccRCC and skin cutaneous melanoma.

CONCLUSION

A gene signature related to cholesterol metabolism was developed and validated to forecast the prognosis of ccRCC, demonstrating a correlation with immune infiltration. Cholesterol metabolic genes such as SCARB1, were expected to contribute to the diagnosis and precision treatment of both ccRCC and skin cutaneous melanoma.

Cuproptosis-Related Genes CDK1 and COA6 Involved in the Prognosis Prediction of Liver Hepatocellular Carcinoma

Background

Liver hepatocellular carcinoma (LIHC) is the most frequently seen type of primary liver cancer. Cuproptosis is a novel form of cell death highly associated with mitochondrial metabolism. However, the clinical impact and pertinent mechanism of cuproptosis genes in LIHC remain largely unknown.

Methods

From public databases, we systematically assessed common genes from LIHC differentially expressed genes (DEGs) and cuproptosis-related genes using bioinformatics analysis. These common genes were then analyzed by enrichment analysis, mutation analysis, risk score model, and others to find candidate hub genes related to LIHC and cuproptosis. Next, hub genes were determined by expression, clinical factors, immunoassay, and prognostic nomogram.

Results

Based on 129 cuproptosis-related genes and 3492 LIHC DEGs, we totally identified 21 downregulated and 18 upregulated common genes, and they were enriched in pathways, such as zinc ion homeostasis and oxidative phosphorylation. In the mutation analysis, missense mutation was the most common type in LIHC patients, and the common gene F5 had the highest mutation frequency. After LASSO-Cox regression analysis and prognostic analysis, CDK1, ABCB6, LCAT, and COA6 were identified as prognostic signature genes. Among them, ABCB6 and LCAT were lowly expressed in tumors, and CDK1 and COA6 were highly expressed in tumors. In addition, ABCB6 and LCAT were negatively correlated with 6 kinds of immune cells, while CDK1 and COA6 were positively correlated with them. CDK1 and COA6 were identified as hub genes related to LIHC by Cox regression analysis and prognostic nomogram.

Conclusion

CDK1 and COA6 are two oncogenes in LIHC, which are involved in the molecular mechanism of cuproptosis and LIHC. Besides, CDK1 and COA6 can positively regulate the expressions of immune cells in LIHC. In clinical practice, they can be used as immunotherapeutic targets and prognostic predictors in LIHC, which sheds new light on the scientific fields of cuproptosis and LIHC.

Molecular Basis of Unequal Alternative Splicing of Human SCD5 and Its Alteration by Natural Genetic Variations

Alternative splicing (AS) is a major means of post-transcriptional control of gene expression, and provides a dynamic versatility of protein isoforms. Cancer-related AS disorders have diagnostic, prognostic and therapeutic values. Changes in the expression and AS of human stearoyl-CoA desaturase-5 (SCD5) are promising specific tumor markers, although the transcript variants (TVs) of the gene have not yet been confirmed. Our in silico, in vitro and in vivo study focuses on the distribution of SCD5 TVs (A and B) in human tissues, the functionality of the relevant splice sites, and their modulation by certain single-nucleotide variations (SNVs). An order of magnitude higher SCD5A expression was found compared with SCD5B. This unequal splicing is attributed to a weaker recognition of the SCD5B-specific splicing acceptor site, based on predictions confirmed by an optimized minigene assay. The pronounced dominance of SCD5A was largely modified (rs1430176385_A, rs1011850309_A) or even inverted (rs1011850309_C) by natural SNVs at the TV-specific splice sites. Our results provide long missing data on the proportion of SCD5 TVs in human tissues and reveal mutation-driven changes in SCD5 AS, potentially affecting tumor-associated reprogramming of lipid metabolism, thus having prognostic significance, which may be utilized for novel and personalized therapeutic approaches.

Exploring a ferroptosis and oxidative stress-based prognostic model for clear cell renal cell carcinoma

Background

Ferroptosis is a newly defined cell death process triggered by increased iron load and tremendous lipid reactive oxygen species (ROS). Oxidative stress-related ferroptosis is of great important to the occurrence and progression of clear cell renal cell carcinoma (ccRCC), which is particularly susceptibility to ferroptosis agonist. Therefore, exploring the molecular features of ferroptosis and oxidative stress might guide the clinical treatment and prognosis prediction for ccRCC patients.

Methods

The differentially expressed ferroptosis and oxidative stress-associated genes (FPTOSs) between normal renal and ccRCC tissues were identified based on The Cancer Genome Atlas (TCGA) database, and those with prognostic significances were applied to develop a prognostic model and a risk scoring system (FPTOS_score). The clinical parameter, miRNA regulation, tumor mutation burden (TMB), immune cell infiltration, immunotherapy response, and drug susceptibility between two FPTOS-based risk stratifications were determined.

Results

We have identified 5 prognosis-associated FPTOSs (ACADSB, CDCA3, CHAC1, MYCN, and TFAP2A), and developed a reliable FPTOS_socre system to distinguish patients into low- and high-risk groups. The findings implied that patients from the high-risk group performed poor prognoses, even after stratified analysis of various clinical parameters. A total of 30 miRNA-FPTOS regulatory pairs were recognized to identify the possible molecular mechanisms. Meanwhile, patients from the high-risk group exhibited higher TMB levels than those from the low-risk groups, and the predominant mutated driver genes were VHL, PBRM1 and TTN in both groups. The main infiltrating immune cells of high- and low-risk groups were CD8+ T cells and resting mast cells, respectively, and patients from the high-risk groups showed preferable drug responsiveness to anti-PD-1 immunotherapy. Eventually, potential sensitive drugs (cisplatin, BI-D1870, and docetaxel) and their enrichment pathways were identified to guide the treatment of ccRCC patients with high-risk.

Conclusion

Our study comprehensively analyzed the expression profiles of FPTOSs and constructed a scoring system with considerable prognostic value, which would supply novel insights into the personalized treatment strategies and prognostic evaluation of ccRCC patient.

SCD5 Regulation by VHL Affects Cell Proliferation and Lipid Homeostasis in ccRCC

Clear cell renal cell carcinoma (ccRCC) is the most common histological subtype of renal cancer, and inactivation of the VHL tumor suppressor gene is found in almost all cases of hereditary and sporadic ccRCCs. CcRCC is associated with the reprogramming of fatty acid metabolism, and stearoyl-CoA desaturases (SCDs) are the main enzymes controlling fatty acid composition in cells. In this study, we report that mRNA and protein expression of the stearoyl-CoA desaturase SCD5 is downregulated in VHL-deficient cell lines. Similarly, in C. elegans vhl-1 mutants, FAT-7/SCD5 activity is repressed, supporting an evolutionary conservation. SCD5 regulation by VHL depends on HIF, and loss of SCD5 promotes cell proliferation and a metabolic shift towards ceramide production. In summary, we identify a novel regulatory function of VHL in relation to SCD5 and fatty acid metabolism, and propose a new mechanism of how loss of VHL may contribute to ccRCC tumor formation and progression.

Identification and validation of a novel ferroptosis-related gene signature for prognosis and potential therapeutic target prediction in cholangiocarcinoma

Cholangiocarcinoma (CCA) is a highly heterogeneous and aggressive malignancy of the bile ducts with a poor prognosis and high mortality rate. Effective targeted therapy and accurate prognostic biomarkers are still lacking. Ferroptosis is a form of regulated cell death implicated in cancer progression and has emerged as a potential therapeutic target in various cancers. However, a comprehensive analysis of ferroptosis-related genes (FRGs) for predicting CCA prognosis and therapeutic targets and determining the role of ferroptosis in CCA remain to be performed. Here, we developed a prognostic FRG signature using a least absolute shrinkage and selection operator Cox regression analysis in a training cohort. We then validated it using four independent public datasets. The six-FRG signature was developed to predict CCA patient survival, stratifying them into low-risk and high-risk groups based on survival time. Significantly, the high-risk CCA patients had shorter overall survival. A receiver operating characteristic curve analysis further confirmed the prognostic FRG signature's strong predictive ability, indicating that it was an independent prognostic indicator for CCA patients. Furthermore, the high-risk group was associated with fluke infection and high clinical stages. Cancer-associated fibroblast (CAF) score and CAF markers were significantly higher in the high-risk group than the low-risk group. Moreover, our FRG signature could predict immune checkpoint markers for immunotherapy and drug sensitivity. The mRNA expression levels of the six-FRG signature was validated in 10 CCA cell lines and dividing them into low-risk and high-risk groups using the FRG signature. We further showed that high-risk CCA cell lines were more resistant to ferroptosis inducers, including erastin and RSL3, than the low-risk CCA cell lines. Our study constructed a novel FRG signature model to predict CCA prognoses which might provide prognostic biomarkers and potential therapeutic targets for CCA patients. Ferroptosis sensitivity in high-risk and low-risk CCA cell lines suggests that ferroptosis resistance is associated with high-risk group CCA. Therefore, ferroptosis could be a promising therapeutic target for precision therapy in CCA patients.

Construction and validation of a prognostic model for hepatocellular carcinoma: Inflammatory ferroptosis and mitochondrial metabolism indicate a poor prognosis

Background

An increasing number of innovations have been discovered for treating hepatocellular carcinoma (HCC or commonly called HCC) therapy, Ferroptosis and mitochondrial metabolism are essential mechanisms of cell death. These pathways may act as functional molecular biomarkers that could have important clinical significance for determining individual differences and the prognosis of HCC. The aim of this study was to construct a stable and reliable comprehensive model of genetic features and clinical factors associated with HCC prognosis.

Methods

In this study, we used RNA-sequencing (fragments per kilobase of exon model per million reads mapped value) data from the Cancer Genome Atlas (TCGA) database to establish a prognostic model. We enrolled 104 patients for further validation. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes enrichment analyses (KEGG) analysis were used for the functional study of differentially expressed genes. Pan-cancer analysis was performed to evaluate the function of the Differentially Expressed Genes (DEGs). Thirteen genes were identified by univariate and least absolute contraction and selection operation (LASSO) Cox regression analysis. The prognostic model was visualized using a nomogram.

Results

We found that eight genes, namely EZH2, GRPEL2, PIGU, PPM1G, SF3B4, TUBG1, TXNRD1 and NDRG1, were hub genes for HCC and differentially expressed in most types of cancer. EZH2, GRPEL2 and NDRG1 may indicate a poor prognosis of HCC as verified by tissue samples. Furthermore, a gene set variation analysis algorithm was created to analyze the relationship between these eight genes and oxidative phosphorylation, mitophagy, and FeS-containing proteins, and it showed that ferroptosis might affect inflammatory-related pathways in HCC.

Conclusion

EZH2, GRPEL2, NDRG1, and the clinical factor of tumor size, were included in a nomogram for visualizing a prognostic model of HCC. This nomogram based on a functional study and verification by clinical samples, shows a reliable performance of patients with HCC.

Ferroptosis Biomarkers for Predicting Prognosis and Immunotherapy Efficacy in Adrenocortical Carcinoma

BACKGROUND

Numerous studies have suggested that ferroptosis plays an important regulatory role in cancer cell death. Nonetheless, the potential effects of ferroptosis regulators on the prognosis, the expression of immunomodulatory factors in the tumor microenvironment and on the efficacy of immunotherapy in adrenocortical carcinoma (ACC) remain largely unknown.

METHODS

Public ACC datasets were used to investigate the relationship between ferroptosis regulators and prognosis and clinical features. A ferroptosis scoring system was established for individual cases of ACC using principal component analysis algorithms. Hub ferroptosis-related genes involved in immunoregulation and immunotherapy efficacy in ACC were further identified.

RESULTS

Twenty ferroptosis regulators were differentially expressed in ACC and 17 ferroptosis regulators were closely related to prognosis in ACC. A ferroptosis scoring system was developed based on ACSL4, FANCD2, and SLC7A1 expression, and the ferroptosis regulators could serve as an independent prognostic factor for ACC. Further analyses indicated that the ferroptosis score integrated with the tumor mutation burden (TMB), and immune-checkpoint gene expression could predict prognosis in ACC. RNA isolation and reverse transcription‑quantitative polymerase chain reaction (RT-qPCR) demonstrated significant differences in the expression levels of ACSL4, FANCD2, and SLC7A1 between ACC and normal tissues. Furthermore, FANCD2 was significantly related to immunotherapy efficacy and prognosis in ACC.

CONCLUSION

Our study demonstrated that ferroptosis was significantly associated with prognosis, clinical characteristics, immune-checkpoint gene expression, and tumor microenvironment immune cell infiltration in ACC. The current study provides comprehensive evidence for further research on ferroptosis regulators in ACC and provides new insight into the epigenetic regulation of the antitumor immune response.

A survival model for prognostic prediction based on ferroptosis-associated genes and the association with immune infiltration in lung squamous cell carcinoma

Lung squamous cell carcinoma (LUSC) is the primary pathological type of lung cancer with a less favorable prognosis. This study attempts to construct a ferroptosis-associated signature associated with overall survival (OS) that can predict the prognosis of LUSC and explore its relationship with immune infiltration. A 5 ferroptosis-associated gene model was constructed by LASSO-penalized regression analysis to predict the prognosis of patients with LUSC in the TCGA database and validated in the GEO and TCGA databases. Patients were stratified into high-risk and low-risk groups by the median value of the risk scores, and the former prognosis was significantly worse (P<0.001). Additionally, we found a certain association between the two risk groups and immune infiltration through CIBERSORT. Meanwhile, the differentially expressed genes (DEGs) between normal and tumor tissue were used to perform functional analysis, which showed a significant association with leukocyte transendothelial migration pathways in the TCGA cohort. In addition, immune cell infiltration analysis confirmed that M2 macrophages were significantly highly expressed in the high-risk group. Overall, the model successfully established by ferroptosis-associated genes suggests that ferroptosis may be related to immune infiltration in LUSC.

Construction and validation of a prognostic model for lung adenocarcinoma based on endoplasmic reticulum stress-related genes

Lung adenocarcinoma (LUAD) is one of the most universal types of cancer all over the world and its morbidity continues to rise year by year. Growing evidence has demonstrated that endoplasmic reticulum stress is highly activated in cancer cells and plays a key role in regulating the fate of cancer cells. However, the role and mechanism of endoplasmic reticulum stress in lung adenocarcinoma genesis and development remains unclear. In this research, we developed a prognostic model to predict the overall survival of patients with LUAD utilizing endoplasmic reticulum stress-related genes and screened out potential small molecular compounds, which could assist the clinician in making accurate decisions and better treat LUAD patients. Firstly, we downloaded 419 endoplasmic reticulum stress-related genes (ERSRGs) from Molecular Signatures Database (MSigDB). Secondly, we obtained information about the transcriptome profiling and corresponding clinical data of 59 normal samples and 535 lung adenocarcinoma samples from The Cancer Genome Atlas (TCGA) database. Next, we used the DESeq2 package to identify differentially expressed genes related to endoplasmic reticulum stress. We performed univariate Cox, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analysis to establish a prognostic model for LUAD patients based on ERSRGs. Then, we carried out univariate and multivariate independent prognostic analysis of endoplasmic reticulum stress-related gene (ERSRG) score and some clinical traits of lung adenocarcinoma. Additionally, we developed a clinically applicable nomogram for predicting survival for LUAD patients over one, three, and five years. Moreover, we carried out a drug sensitivity analysis to identify novel small molecule compounds for LUAD treatment. Finally, we examined the tumor microenvironment (TME) and immune cell infiltrating analysis to explore the interactions between immune and cancer cells. 142 differentially expressed ERSRGs were identified by using the DESeq2 package. A prognostic model was built based on 7 differentially expressed ERSRGs after performing univariate Cox regression, LASSO regression, and multivariate Cox regression analysis. According to the results of univariate and multivariate independent prognostic analysis, we found ERSRG score can be used as an independent prognostic maker. Using the Kaplan-Meier curves, we found low-risk patients had higher survival probability than high-risk patients in both training set and test set. A nomogram was drawn to predict 1-, 3-, and 5-year survival probability. The calibration curves explained good performance of the model for the prediction of survival. Phenformin, OSU-03012, GSK-650394 and KIN001-135 were identified as the drugs most likely to provide important information to clinicians about the treatment of LUAD patients. A prognostic prediction model was established based on 7 differentially expressed ERSRGs (PDX1, IGFBP1, DDIT4, PPP1R3G, CFTR, DERL3 and NUPR1), which could effectively predict the prognosis of LUAD patients and give a reference for clinical doctors to help LUAD patients to make better treatment tactics. Based on the 4 small molecule compounds (Phenformin, OSU-03012, GSK-650394 and KIN001-135) we discovered, targeting endoplasmic reticulum stress-related genes may also be a therapeutic approach for LUAD patients.

A ferroptosis-related gene signature associated with immune landscape and therapeutic response in osteosarcoma

BACKGROUND

The role of ferroptosis in tumor progression and immune microenvironment is extensively investigated. However, the potential value of ferroptosis regulators in predicting prognosis and therapeutic strategies for osteosarcoma (OS) patients remains to be elucidated.

METHODS

Here, we extracted transcriptomic and survival data from Therapeutically Applicable Research to Generate Effective Treatments (TARGET) and Gene Expression Omnibus (GEO) to investigate the expression and prognostic value of ferroptosis regulators in OS patients. After comprehensive analyses, including Gene set variation analysis (GSVA), single-sample gene-set enrichment analysis (ssGSEA), Estimated Stromal and Immune cells in Malignant Tumor tissues using Expression (ESTIMATE), single-cell RNA sequencing, and biological experiments, our constructed 8-ferroptosis-regulators prognostic signature effectively predicted the immune landscape, prognosis, and chemoradiotherapy strategies for OS patients.

RESULTS

We constructed an 8-ferroptosis-regulators signature that could predict the survival outcome of OS. The signature algorithm scored samples, and high-scoring patients were more prone to worse prognoses. The tumor immune landscape suggested the positive relevance between risk score and immunosuppression. Interfering HILPDA and MUC1 expression would inhibit tumor cell proliferation and migration, and MUC1 might improve the ferroptosis resistance of OS cells. Moreover, we predicted chemoradiotherapy strategies of cancer patients following ferroptosis-risk-score groups.

CONCLUSION

Dysregulated ferroptosis gene expression can affect OS progression by affecting the tumor immune landscape and ferroptosis resistance. Our risk model can predict OS survival outcomes, and we propose that HILPDA and MUC1 are potential targets for cancer therapy.

Cuproptosis associated genes affect prognosis and tumor microenvironment infiltration characterization in lung adenocarcinoma

Cuproptosis, a newly discovered mechanism of programmed cell death, is important for detailing the metabolic aspects of cancer progression and thereby guiding cancer therapy. An exciting era of translational medicine has led to the rapid development of countless immunotherapeutic strategies. The existing successful cancer immunotherapies have sparked new hope for patients with solid and hematologic malignancies. Hence, it is important to characterize the link between the cuproptosis process and the immunity status in the tumor microenvironment (TME) in Lung Adenocarcinoma (LUAD), which may be able to predict patient's prognosis. In this study, we systematically assessed 10 cuproptosis-associated genes (CAGs) and comprehensively characterized the relationship between cuproptosis and the molecular characteristics and immune cell infiltration of tumor tissue, prognosis and clinical treatment of patients. Subsequently, the CAG_score for predicting overall survival (OS) was established and its reliable predictive ability in LUAD patients was confirmed. Next, we created a highly reliable nomogram to facilitate the clinical viability of the CAG_score. The low CAG_score group, with lower immune cell infiltration, and mutation burden, had a significantly superior OS, which was associated with a better response to immunotherapy. The present study revealed that cuproptosis play a significant role in TME regulation in LUAD. Collectively, we identified a prognostic CAGs-related signature for LUAD patients. This signature may contribute to clarifying the characteristics of TME and enable the exploration of more potent immunotherapy strategies.

Ferroptosis-related gene signature predicts prognosis in kidney renal papillary cell carcinoma

Ferroptosis, an iron-dependent form of selective cell death, is involved in the development of many cancers. However, the role of ferroptosis-related genes (FRGs) in kidney renal papillary cell carcinoma (KIRP) is unclear. In this study, we examined the mRNA expression profiles and clinical data of patients with KIRP from the TCGA cohort. Consequently, 41 differentially-expressed FRGs were screened using the limma package, and 17 prognostic-related FRGs were identified by survival analysis and univariate Cox regression analyses. Thereafter, a ferroptosis-related gene prognostic index (FRGPI) was constructed based on five FRGs (AKR1C3, SAT1, FANCD2, HSBP1 and SQLE), using lasso Cox and multivariate Cox regression analyses. KIRP patients with high FRGPI scores displayed worse outcomes. Furthermore, the FRGPI was shown to be a reliable independent prognostic factor in both the training and testing cohorts. Comprehensive analysis also showed that the FRGPI can distinguish gene mutation, functional enrichment of immune cells and molecular function-related pathways. Interestingly, low FRGPI score could be more benefit from immune checkpoint inhibitors (ICIs) therapy. Then, the two hub prognostic genes (AKR1C3 and FANCD2) as a risk gene for KIRP were identified based on the FRGPI module, and the expression profiles of these two genes were validated using human KIRP cells, besides, we furthermore discovered that Fancd2 is significantly up-regulated in most cancers and is associated with prognosis. In conclusion, these findings showed that FRGPI can accurately predict the prognosis of patients with KIRP, suggesting that this risk model is a promising prognostic biomarker for these patients. Moreover, targeting ferroptosis (FANCD2) could be a potential therapeutic alternative for various cancers.

Identification and Validation of a Novel Ferroptotic Prognostic Genes-Based Signature of Clear Cell Renal Cell Carcinoma

Renal cell carcinoma (RCC), as one of the primary urological malignant neoplasms, shows poor survival, and the leading pathological type of RCC is clear cell RCC (ccRCC). Differing from other cell deaths (such as apoptosis, necroptosis, pyroptosis, and autophagy), ferroptosis is characterized by iron-dependence, polyunsaturated fatty acid oxidization, and lipid peroxide accumulation. We analyzed the ferroptosis database (FerrDb V2), Gene Expression Omnibus database, The Cancer Genome Atlas database, and the ArrayExpress database. Nine genes that were differentially expressed and related to prognosis were involved in the ferroptotic prognostic model via the least absolute shrinkage and selection operator Cox regression analysis, which was established in ccRCC patients from the kidney renal clear cell carcinoma (KIRC) cohort in TCGA database, and validated in ccRCC patients from the E-MTAB-1980 cohort in the ArrayExpress database. The signature could be an independent prognostic factor for ccRCC, and high-risk patients showed worse overall survival. The Gene Ontology and Kyoto Encyclopedia of Genes and Genomes were utilized to investigate the potential mechanisms. The nine genes in ccRCC cells with erastin or RSL3 treatment were validated to find the crucial gene. The glutaminase 2 (GLS2) gene was upregulated during ferroptosis in ccRCC cells, and cells with GLS2 shRNA displayed lower survival, a lower glutathione level, and a high lipid peroxide level, which illustrated that GLS2 might be a ferroptotic suppressor in ccRCC.

Cuprotosis-Related Genes: Predicting Prognosis and Immunotherapy Sensitivity in Pancreatic Cancer Patients

Based on TCGA, GTEx, and TIMER databases and various bioinformatics analysis methods, the potential biological roles of cuprotosis-related genes in pancreatic cancer were deeply explored, and a predictive model for pancreatic cancer patients was constructed. We downloaded the RNA-Seq data and clinicopathological and predictive data of 179 pancreatic cancer tissues and 332 adjacent normal tissues from TCGA and GTEx databases. The differential expression of cuprotosis-related genes in pancreatic cancer tissue and adjacent normal tissue was analyzed, and the LASSO regression algorithm was used to construct a prediction model and verify the validity of the model prediction. Based on the LASSO regression algorithm, a predictive model composed of three genes LIPT1, LIAS, and DLAT was screened. The corresponding survival curves showed that the constructed prediction model could significantly distinguish the prognosis of pancreatic cancer patients, and the prognosis of patients in the high-risk group was worse (P = 0.00557). The ROC curve showed that the area under the curve of the predictive model for predicting the 4-, 5-, and 6-year survival rates in pancreatic cancer was 0.816, 0.836, and 0.956, respectively. The AUC value of this risk model was significantly higher than 0.7, which could more accurately predict the prognosis of pancreatic cancer patients. This study determined a risk-scoring model of cuprotosis-related genes, which can provide an essential basis for judging the prognosis of pancreatic cancer patients.

Machine learning-based prognosis signature for survival prediction of patients with clear cell renal cell carcinoma

The sole clinicopathological characteristic is not enough for the prediction of survival of patients with clear cell renal cell carcinoma (ccRCC). However, the survival prediction model constructed by machine learning technology for patients with ccRCC using clinicopathological features is rarely reported yet. In this study, a total of 5878 patients diagnosed as ccRCC from four independent patient cohorts were recruited. The least absolute shrinkage and selection operator analysis was implemented to identify optimal clinicopathological characteristics and calculate each coefficient to construct the prognosis model. In addition, weighted gene co-expression network and gene enrichment analysis associated with risk score were also carried out. Three clinicopathologic features were selected for the construction of the prognosis risk score model as the prognostic factors of ccRCC, including tumor size, tumor grade, and tumor stage. In the CPTAC (Clinical Proteomic Tumor Analysis Consortium) cohort, the General cohort, the SEER (Surveillance, Epidemiology, and End Results) cohort, and the Huashan cohort, patients with high-risk score had worse clinical outcomes than patients with low-risk score (hazard ratio 5.15, 4.64, 3.96, and 5.15, respectively). Further functional enrichment analysis demonstrated that our machine learning-based risk score was significantly connected with some cell proliferation-related pathways, consisting of DNA repair, cell division, and cell cycle. In summary, we developed and validated a machine learning-based prognosis prediction model, which might contribute to clinical decision-making for patients with ccRCC.

The potential value of cuprotosis (copper-induced cell death) in the therapy of clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) accounts for 75% of the total incidence of renal cancer, and every year the number of morbidity and mortality increases, posing a serious threat to public health. The current main treatment methods for kidney cancer include drug-targeted therapy and immunotherapy. Although there are many treatment options for kidney cancer, they all have limitations, including drug resistance, unsatisfied long-term benefits, and adverse effects. Therefore, it is crucial to identify more effective therapeutic targets. As a newly discovered mechanism of cell death, copper-induced cell death (cuprotosis) is closely related to changes in cell metabolism, particularly in copper metabolism. Current studies have shown that the key signaling pathway of cuprotosis, the FDX1 (Ferredoxin 1)-LIAS (Lipoic Acid Synthetase) axis, plays an important role in the regulation of cellular oxidative stress, which can directly affect cell survival via inducing or promoting cancer cell death. Therefore, we speculated that this regulatory cell death mechanism might serve as a potential therapeutic target for the clinical treatment of renal cancer. To test this, we first performed a pan-cancer analysis based on cuprotosis-related genomic and transcriptomic levels to reveal the expression of cuprotosis in cancer. Next, GSVA-clustering analysis was performed with data from the Cancer Genome Atlas (TCGA) cohort, and the cohort was divided into three clusters according to the gene enrichment levels of cuprotosis marker genes. In addition, we analyzed the potential of using cuprotosis in clinical treatment from multiple perspectives, including chemotherapeutic drug susceptibility test, immune target inhibition treatment responsiveness, and histone modification. Combining the results of multi-omics analysis, we focused on the feasibility of this novel regulatory cell death mechanism in ccRCC treatment and further constructed a prognostic model. Finally, we verified our results by integrating the patient's gene expression information and radiomics information. Our study provides new insights into the development and clinical application of targeting cuprotosis pathway.

Systematic Construction and Validation of a Novel Ferroptosis-Related Gene Model for Predicting Prognosis in Cervical Cancer

Background and Purpose. Ferroptosis, a mechanism of cell death that is iron-dependent, participates in various pathologies of cancer (CC). Nevertheless, the specific function that ferroptosis plays in the onset and progression of cervical cancer (CC) is yet uncertain. This research sought to examine the value of ferroptosis-related genes (FRGs) in the progression and prognosis of CC. Methods. Datasets containing RNA sequencing and corresponding clinical data of cervical cancer patients were obtained from searching publicly accessible databases. The “NMF” R package was conducted to calculate the matrix of the screened prognosis gene expression. Ferroptosis-related differential genes in cervical cancer were detected using the “limma” R function and WGCNA. The least absolute shrinkage and selection operator (LASSO) algorithm and Cox regression analysis were conducted to develop a novel prognostic signature. The prediction model was verified by the nomogram integrating clinical characteristics; the GSE44001 dataset was used as an external verification. Then, the immune status and tumor mutation load were explored. Finally, immunohistochemistry as well as quantitative polymerase chain reaction (RT-qPCR) was utilized to ascertain the expression of FRGs. Results. Two molecular subgroups (cluster 1 and cluster 2) with different FRG expression patterns were recognized. A ferroptosis-related model based on 4 genes (VEGFA, CA9, DERL3, and RNF130) was developed through TCGA database to identify the unfavorable prognosis cases. Patients in cluster 1 showed significantly decreased overall survival in contrast with those in cluster 2 ( $P<0.05$ ). The LASSO technique and Cox regression analysis were both utilized to establish the independence of the prognostic model. The validity of nomogram prognostic predictions has been well demonstrated for 3- and 5-year survival in both internal and external data validation cohorts. These two subgroups showed striking differences in tumor-infiltrating leukocytes and tumor mutation burden. The low-risk subgroup showed a longer overall survival time with a higher immune cell score and higher tumor mutation rate. Gene functional enrichment analyses revealed predominant enrichment in various tumor-associated signaling pathways. Finally, the expression of each gene was confirmed by immunohistochemistry and RT-qPCR. Conclusion. A novel and comprehensive ferroptosis-related gene model was proposed for cervical cancer which was capable of distinguishing the patients independently with high risk for poor survival, and targeting ferroptosis may represent a promising approach for the treatment of CC.

Eukaryotic Translation Initiation Factor 5A Independently Predicts Poor Prognosis of Cholangiocarcinoma Patients and Regulates the Ferroptosis and Mitochondrial Apoptosis

Cholangiocarcinoma (CCA) is a hepatobiliary carcinoma characterized by the differentiation of bile duct cells, and the patients with CCA often have a poor prognosis. Eukaryotic translation initiation factor 5A (eIF5A) is reported to have multiple biological activities. Targeted activation of ferroptosis may be a therapeutic strategy for cancer. Nevertheless, the effects of eIF5A and ferroptosis on CCA are still elucidated. Our study explored the effects of eIF5A in CCA, and the mechanisms also are studied. In this paper, TCGA database analysis suggested that eIF5A was upregulated in CCA, and high expression of eIF5A might predict a poor prognosis. Moreover, FANCD2, SLC7A11, and HSPB1 were significantly overexpressed in CCA. The results indicated that eIF5A was overexpressed in CCA tissues and cells. Further experiments demonstrated that eIF5A silencing decreased CCA cell activity and enhanced ferroptosis and mitochondrial apoptosis. In addition, upregulation of eIF5A showed the opposite effect on CCA cells compared with downregulation of eIF5A. Finally, the silencing of eIF5A could restrain the growth of xenografted tumors and promote ferroptosis. Overall, eIF5A enlarged CCA cell activity and attenuated ferroptosis and mitochondrial apoptosis. The results suggested that assessment of eIF5A might provide help for the diagnosis and treatment of CCA.

Contribution of prognostic ferroptosis-related subtypes classification and hub genes of sepsis

BACKGROUND

Sepsis in patients is a great threat to human health due to its high incidence rate, its rapid and unpredictable progression, as well as it is difficult to treat, and it has poor prognosis. Ferroptosis is a newly discovered type of cell death characterized by the iron-dependent peroxide aggregation. Furthermore, ferroptosis is different from other forms of cell death, namely apoptosis, necrosis, pyroptosis and autophagy. Our study investigated the role of ferroptosis-related genes in sepsis.

METHODS

The GSE65682 dataset from the Gene Expression Omnibus (GEO) database was used to screen ferroptosis-related genes associated with sepsis, and the GSE134347 dataset for the external validation of selected hub genes. The univariate Cox regression analysis, Kaplan-Meier (K-M) survival analysis and weighted gene co-expression network analysis (WGCNA) were used to identify hub genes. Evaluation of the immune cell infiltration in sepsis was used to explain the immune heterogeneity among the cell subtypes. Gene set variation analysis (GSVA) and transcriptional regulatory analysis of selected hub genes further elucidated the probable mechanism of ferroptosis-related genes associated with prognosis in sepsis. Finally, we constructed a competing endogenous RNA (ceRNA) network model.

RESULTS

A total of 479 RNA-seq data points were used for analysis, including 365 samples from patients who survived sepsis and 114 samples from patients who succumbed to sepsis from the available GSE65682 dataset. Consequently, the univariate Cox regression analysis and consensus clustering analysis divide all 479 sepsis samples into two clusters of "survivals" vs. "non-survivals". Following complex analysis were identified as the most important ferroptosis-related genes. Indeed, the WGCNA and K-M analyses associated the expression patterns of NEDD4L and SIAH2 hub genes as the best prognosis for the survival of sepsis (p < 0.05). The expression trend was also consistent with the survival trend of the NEDD4L and SIAH2 hub genes by the external validation of GSE134347 (p < 0.05). Immune cell infiltration analysis indicated that the types and numbers of different immune cells vary among different subtypes and NEDD4L and SIAH2 hub genes. For example, NEDD4L and SIAH2 gene expression had a positive correlation with M0 macrophages and a negative correlation with neutrophils (p > 0.05). Finally, analysis of two hub genes and transcription factors (TFs) showed that 71 TFs were predicted to be related to NEDD4L while 64 TFs to SIAH2 by the Cistrome DB online database.

CONCLUSION

We suggest that NEDD4L and SIAH2 hub genes are involved in the ferroptosis-associated sepsis. The pattern of NEDD4L and SIAH2 expression in patients undergoing sepsis may have prognostic potential for the severity of sepsis and eventually for patients' survival.

Combined HIF-1α and SHH Up-Regulation Is a Potential Biomarker to Predict Poor Prognosis in Postoperative Hepatocellular Carcinoma

BACKGROUND

Hypoxia-inducible factor-1α (HIF-1α) or sonic hedgehog (SHH) is associated with hepatocellular carcinoma (HCC) progression. Hypoxia inhibits ferroptosis, which induces cancer cell death. However, the correlation between the combined HIF-1α and SHH up-regulation with prognosis, and the association between SHH and ferroptosis remain unclear. This study aimed to investigate them.

METHODS

We detected the expression of HIF-1α and SHH in HCC. Cox regression, clinical data, and Kaplan-Meier analyses were performed. In vitro cell experiments verified the relationship between HIF-1α and SHH, and observed the invasion of hypoxic HCC cells. The correlation between SHH and ferroptosis was also analyzed.

RESULTS

HIF-1α and SHH expression levels were significantly correlated with HCC (p < 0.0001). HIF-1α and SHH expression levels were found to be associated with TNM stage (p = 0.0121, p = 0.0078, respectively), vascular invasion (p < 0.0001, p < 0.0001, respectively), and recurrence (p = 0.0212, p = 0.0392, respectively). The combined upregulation of HIF-1α and SHH was an independent factor for predicting the overall survival (OS) of patients with HCC (p = 0.003), who had the shortest OS (p = 0.0009). SHH paralleled the increase in HIF-1α expression, which promotes cancer cell invasion. The upregulation of SHH was related to the inhibition of the expression of ferroptosis-related factors (FANCD2, p < 0.0001 and FTH1, p = 0.0009) in HCC.

CONCLUSION

Combined HIF-1α and SHH upregulation is a potentially poor prognosis indicator in patients with HCC because the upregulation of SHH inhibits ferroptosis in hypoxic cancer cells.

STAT6 inhibits ferroptosis and alleviates acute lung injury via regulating P53/SLC7A11 pathway

Compelling evidences have revealed the emerging role of ferroptosis in the pathophysiological process of acute lung injury (ALI), but its modulation is not clear. Here, we identified that STAT6 acted as a critical regulator of epithelium ferroptosis during ALI. Firstly, STAT6 expression and activity were increased in the ALI mice models caused by crystalline silica (CS), LPS and X-ray exposure. Followed by confirming the contribution of ferroptosis in the above ALI with ferrostatin-1 and deferoxamine intervention, bioinformatic analyses revealed that STAT6 expression was negatively correlated with ferroptosis. Consistently, lung epithelium-specific depletion of STAT6 in mice or STAT6 knockdown in cultured epithelial cells exacerbated ferroptosis in the above ALI. While overexpression of STAT6 in lung epithelial cells attenuated the ferroptosis. Mechanistically, SLC7A11 is a typical ferroptosis-related gene and negatively regulated by P53. CREB-binding protein (CBP) is a critical acetyltransferase of P53 acetylation, showing valuable regulation on targets' transcription. Herein, we found that STAT6 negatively regulates ferroptosis through competitively binding with CBP, which inhibits P53 acetylation and transcriptionally restores SLC7A11 expression. Finally, pulmonary-specific STAT6 overexpression decreased the ferroptosis and attenuated CS and LPS induced lung injury. Our findings revealed that STAT6 is a pivotal regulator of ferroptosis, which may be a potential therapeutic target for the treatment of acute lung injury.

Construction and Validation of a 6-Ferroptosis Related Gene Signature for Prognosis and Immune Landscape Prediction in Melanoma

Ferroptosis is a newly discovered form of non-apoptotic cell death that relies on iron-mediated oxidative damage, playing a crucial role in the progression and therapy resistance of melanoma. Hence, the potential value of ferroptosis-related genes (FRGs) as a prognostic model and therapeutic target in melanoma requires further investigation. In this study, the relationship between FRGs and melanoma was revealed by analyzing the mRNA expression profiles from The Cancer Genome Atlas (TCGA) and Gene Expression Synthesis (GEO). A 6-FRGs signature was constructed by Univariate, multivariate, and lasso Cox regression analyses in the TCGA cohort. The GEO database was used to validate the efficacy of the signature. The protein and mRNA expression level of the signature genes were examined in real-world melanoma tissues via immunohistochemical and quantificational real-time polymerase chain reaction (qRT-PCR). Functional enrichment analysis and immune-related analysis were conducted to identify the potential biological functions and pathways of the signature. Ten putative small molecule drugs were predicted by Connectivity Map (CMAP). As a result, a 6-FRGs signature was constructed to stratify melanoma patients into two risk groups. Compared with the low-risk group, patients in the high-risk group had a worse prognosis and a lower ImmuneScore. Immune-related pathways were enriched in the low-risk group. Immune Function and immune cell infiltration of the low-risk group were significantly higher than that of the high-risk group. The differential expression of these six FRGs in melanoma and adjacent normal tissues was confirmed. Moreover, higher expression of immune checkpoint molecules and a greater sensitivity to immunotherapy were observed in the low-risk group. Some small molecular drugs in the CMAP database hold the potential to treat melanoma. Overall, we identified a novel FRGs signature for prognostic prediction in melanoma. Based on the signature-related immune infiltration landscape found in our study, targeting the FRGs might be a therapeutic alternative for melanoma.

A Novel Predictive Model for Adrenocortical Carcinoma Based on Hypoxia- and Ferroptosis-Related Gene Expression

Background

The impact of hypoxia on ferroptosis is important in cancer proliferation, but no predictive model combining hypoxia and ferroptosis for adrenocortical carcinoma (ACC) has been reported. The purpose of this study was to construct a predictive model based on hypoxia- and ferroptosis-related gene expression in ACC.

Methods

We assessed hypoxia- and ferroptosis-related gene expression using data from 79 patients with ACC in The Cancer Genome Atlas (TCGA). Then, a predictive model was constructed to stratify patient survival using least absolute contraction and selection operation regression. Gene expression profiles of patients with ACC in the Gene Expression Omnibus (GEO) database were used to verify the predictive model.

Results

Based on hypoxia-related gene expression, 79 patients with ACC in the TCGA database were divided into three molecular subtypes (C1, C2, and C3) with different clinical outcomes. Patients with the C3 subtype had the shortest survival. Ferroptosis-related genes exhibited distinct expression patterns in the three subtypes. A predictive model combining hypoxia- and ferroptosis-related gene expression was constructed. A nomogram was constructed using age, sex, tumor stage, and the predictive gene model. Gene ontology and Kyoto Encyclopedia of Genes and Genomes analyses revealed that the gene signature was mainly related to the cell cycle and organelle fission.

Conclusion

This hypoxia-and ferroptosis-related gene signature displayed excellent predictive performance for ACC and could serve as an emerging source of novel therapeutic targets in ACC.

Ferroptosis-related local immune cytolytic activity in tumor microenvironment of basal cell and squamous cell carcinoma

BACKGROUND

Ferroptosis, a recently discovered form of cell death, whose role in basal cell carcinoma (BCC) and squamous cell carcinoma (SCC) has not been well disclosed. To improve our understanding of the differences in tumor progression and therapeutic effects between BCC and SCC, and to find potential therapeutic targets, this study systematically analyzed ferroptosis-related genes (FRGs) and their associated local immune cytolytic activity (LICA) and tumor microenvironment (TME) metabolic function differences.

METHODS

Two bulk RNA-seq datasets, GSE7553 and GSE125285, from the Gene Expression Omnibus database were compared within and between groups to screen for common differentially expressed genes (DEGs) for enrichment analysis. The currently recognized FRGs in DEGs gene set were selected as the targets to analyze their correlation and difference in LICA and TME metabolic functions. And validated using immune cell populations from another single-cell RNA-seq (scRNA-seq) dataset (GSE123813) to accurately understand the difference in LICA. All of the gene sets for functional enrichment analysis comes from published results and MSigDB database.

RESULTS

Ten FRGs were used to further analyze the differences in LICA and TME metabolic functions between BCC and SCC. In the SCC samples, LICA (e.g. Treg, CCR, Cytolytic activity, etc.) and TME metabolic functions (e.g. lipid and energy, etc.) were significantly related to ferroptosis genes (e.g. SLC1A5, CD44, NQO1, HMOX1 and STEAP3), and the ferroptosis potential index were also significantly higher than that in the BCC samples. Finally, based on these ten FRGs and related enrichment results, we postulated a model of NQO1 homeostasis regulated by FRGs during induction of ferroptosis in SCC.

CONCLUSIONS

The results showed that three FRGs, SLC1A5, CD44 and NQO1, have significant potential in targeted therapies for SCC chemotherapy resistance. And two FRGs, STEAP3 and HMOX1, formed a synergistic effect on the occurrence of ferroptosis in tumor cells. Our findings can be used as the main research materials for metastasis and chemotherapy resistance in SCC patients.

SLC1A5 Prefers to Play as an Accomplice Rather Than an Opponent in Pancreatic Adenocarcinoma

Background: SLC1A5, a ferroptosis regulator gene, plays a dual role in cancer regulation. However, the roles of SLC1A5 in pancreatic adenocarcinoma (PAAD) remain elusive.

Methods: SLC1A5’s expression and somatic mutation information were determined by TCGA, GEO, Oncomine, and cBioPortal databases. Its prognostic value was assessed in TCGA cohort and was validated in three independent cohorts. The effects of SLC1A5 on the tumor immune microenvironment were analyzed by the CIBERSORT algorithm, ssGSEA method, and TISIDB and TIMER databases. The “oncoPredict” R package, TIDE algorithm, ImmuCellAI online tool, and GSE35141 and GSE59357 datasets were used to ascertain its therapeutic correlations. GSEA and Western blot were applied to reveal the effects of SLC1A5 on the mTORC1 signaling pathway and ferroptosis process. The biofunctions of SLC1A5 were assessed by MTT, wound-healing, Transwell, and xenograft assays.

Results: SLC1A5 was significantly upregulated in the PAAD samples but was not commonly accompanied with somatic mutation (2.3%). Overexpression of SLC1A5 led to a poor prognosis and was identified as an independent prognostic factor. Moreover, high SLC1A5 expression suppressed the antitumor immune process by changing the infiltrating levels of immune cells. As for therapeutic correlations, SLC1A5 was related to the efficacy of dasatinib, sunitinib, sorafenib, and imatinib but may not predict that of radiotherapy, chemotherapeutic drugs, and immune checkpoints inhibitors (ICIs). Notably, the overexpression of SLC1A5 could activate the mTORC1 signaling pathway and may increase the cellular sensitivity to ferroptosis. Finally, the overexpression of SLC1A5 markedly promoted proliferation, migration, and invasion of pancreatic cancer cells. At the in vivo level, SLC1A5 deletion inhibited tumor growth in a mice xenograft model.

Conclusions: SLC1A5 prefers to play as an accomplice rather than an opponent in PAAD. Our findings provide novel insights into PAAD treatment.

Identification of co-expression hub genes for ferroptosis in kidney renal clear cell carcinoma based on weighted gene co-expression network analysis and The Cancer Genome Atlas clinical data

Renal clear cell carcinoma (KIRC) is one of the most common tumors worldwide and has a high mortality rate. Ferroptosis is a major mechanism of tumor occurrence and development, as well as important for prognosis and treatment of KIRC. Here, we conducted bioinformatics analysis to identify KIRC hub genes that target ferroptosis. By Weighted gene co-expression network analysis (WGCNA), 11 co-expression-related genes were screened out. According to Kaplan Meier's survival analysis of the data from the gene expression profile interactive analysis database, it was identified that the expression levels of two genes, PROM2 and PLIN2, are respectively related to prognosis. In conclusion, our findings indicate that PROM2 and PLIN2 may be effective new targets for the treatment and prognosis of KIRC.

Identification of a Novel Ferroptosis-Related Gene Signature for Prediction of Prognosis in Bladder Urothelial Carcinoma

BACKGROUND

sBladder urothelial carcinoma is the most prevalent type of bladder cancer, characterized by drug resistance, high recurrence rate, and unfavorable prognosis. Ferroptosis is a newly discovered type of non-apoptotic cell death, which has been reported to be strongly correlated with tumor occurrence and development.

OBJECTIVE

In this study, we characterized ferroptosis-specific biomarkers to elucidate the association between ferroptosis-related genes (FRGs) and bladder urothelial carcinoma.

METHODS

The TCGA and GEO database were adopted to obtain data and corresponding clinicopathological information. Univariate and multivariate cox regression were performed to establish a ferroptosis-related model. Besides, the KM plot visualized prognosis between high risk and low risk groups. Moreover, cBioportal platform was used to gather information on genetic alteration and DNA methylation of hub FRGs in BLCA patients. Additionally, the GSEA software was used to detect the difference in gene expression between high-risk and low-risk subgroups.

RESULTS

Six ferroptosis-related genes were identified to be highly correlated with overall survival. Besides, we explored the genetic variations of these FRGs, as well as the correlation between FRG expression and copy number values. Additionally, the DNA methylation status of these FRGs was determined. Moreover, we constructed a ferroptosis risk model with the six FRGs to predict the prognosis of BLCA. The results demonstrated that a higher risk score indicated an unfavorable prognosis. The ferroptosis signature was associated with clinical and molecular characteristics and could be regarded as an independent prognostic factor for BLCA patients.

CONCLUSIONS

In summary, we established and verified a ferroptosis risk model which had the potential to independently predict the prognosis of bladder urothelial carcinoma.

Functions, Roles, and Biological Processes of Ferroptosis-Related Genes in Renal Cancer: A Pan-Renal Cancer Analysis

Ferroptosis is a cell death process discovered in recent years, highly related to cancer, acute kidney injury, and other diseases. In this study, a pan-renal cancer analysis of ferroptosis-associated genes in renal cancer was performed to construct a multigene joint signature for predicting prognosis in renal cancer patients. First, gene expression profiles were downloaded from the TCGA and GTEx databases to search for genes significantly associated with renal cancer prognosis through differential gene expression analysis, weighted gene co-expression network analysis (WGCNA), and survival analysis. Thereafter, the gene-set enrichment analysis (GSEA) was used to identify the biological processes in which ferroptosis-associated genes might be involved. Weighted gene co-expression network analysis resulted in 4,434 differentially expressed genes (DEGs) and 42 co-expression modules, among which ferroptosis-related genes were distributed in 11 gene modules. The survival analysis screening resulted in three DEGs associated with renal cancer prognosis, namely SLC7A11, HMOX1, and MT1G. Specifically, SLC7A11 and HMOX1 were upregulated in renal cancer tissues, while MT1G was downregulated. Receiver operating characteristic (ROC) curves, combined with Kaplan–Meier and Cox regression analysis, revealed that high expression of SLC7A11 was a prognostic risk factor for four different renal cancers, that low expression of HMOX1 was a poor prognostic marker for patients, and that increased expression of MT1G increased the prognostic risk for three additional classes of renal cancer patients, except for renal papillary cell carcinoma. The GSEA results showed that the ferroptosis-related genes from these screens were mainly associated with signaling pathways related to tumor progression and tumor immunity. This study provides potential biological markers for prognosis prediction in renal cancer patients with different subtypes, and these results imply that ferroptosis is highly associated with renal carcinogenesis progression.

Application of Regulatory Cell Death in Cancer: Based on Targeted Therapy and Immunotherapy

The development of cancer treatment methods is constantly changing. For common cancers, our treatment methods are still based on conventional treatment methods, such as chemotherapy, radiotherapy, and targeted drug therapy. Nevertheless, the emergence of tumor resistance has a negative impact on treatment. Regulated cell death is a gene-regulated mode of programmed cell death. After receiving specific signal transduction, cells change their physical and chemical properties and the extracellular microenvironment, resulting in structural destruction and decomposition. As research accumulates, we now know that by precisely inducing specific cell death patterns, we can treat cancer with less collateral damage than other treatments. Many newly discovered types of RCD are thought to be useful for cancer treatment. However, some experimental results suggest that some RCDs are not sensitive to cancer cell death, and some may even promote cancer progression. This review summarizes the discovered types of RCDs, reviews their clinical efficacy in cancer treatment, explores their anticancer mechanisms, and discusses the feasibility of some newly discovered RCDs for cancer treatment in combination with the immune and tumor microenvironment.

A Novel Prognostic Ferroptosis-Related Long Noncoding RNA Signature in Clear Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) is the most common primary malignancy of renal cancer in adults. Ferroptosis is critically associated with the prognosis of ccRCC. However, knowledge of long noncoding RNA- (lncRNA-) related ferroptosis that affects the prognosis of ccRCC is still insufficient. Using the LASSO regression, we created a risk model based on differentially expressed ferroptosis-related lncRNAs (FRLRS) in ccRCC. The analysis of Kaplan-Meier for survival, area under the curve (AUC) for diagnosis, nomogram for predicting overall survival, and gene expression for immune checkpoints were performed based on the screened independent prognostic factors. Nine lncRNAs were found to be associated with ccRCC prognosis. Furthermore, the prognostic AUC of the FRLRS signature was 0.78, demonstrating its usefulness in predicting ccRCC prognosis. The lncRNA risk model outperformed the standard clinical variables in predicting ccRCC prognosis. Finally, The Cancer Genome Atlas revealed that T cell functions, such as cytolytic activity, human leukocyte antigen activity, inflammation regulation, and type II interferon response coordination, are significantly different between two different risk levels of ccRCC. Immune checkpoints were also expressed differently in programmed cell death 1 receptor, inducible T cell costimulator, cytotoxic T-lymphocyte antigen-4, and leukocyte-associated immunoglobulin-like receptor 1. The nine FRLRS signature models may affect the prognosis of ccRCC.

Prognostic Ferroptosis-Related lncRNA Signatures Associated With Immunotherapy and Chemotherapy Responses in Patients With Stomach Cancer

Ferroptosis is associated with the prognosis and therapeutic responses of patients with various cancers. LncRNAs are reported to exhibit antitumor or oncogenic functions. Currently, few studies have assessed the combined effects of ferroptosis and lncRNAs on the prognosis and therapy of stomach cancer. In this study, transcriptomic and clinical data were downloaded from TCGA database, and ferroptosis-related genes were obtained from the FerrDb database. Through correlation analysis, Cox analysis, and the Lasso algorithm, 10 prognostic ferroptosis-related lncRNAs (AC009299.2, AC012020.1, AC092723.2, AC093642.1, AC243829.4, AL121748.1, FLNB-AS1, LINC01614, LINC02485, LINC02728) were screened to construct a prognostic model, which was verified in two test cohorts. Risk scores for patients with stomach cancer were calculated, and patients were divided into two risk groups. The low-risk group, based on the median value, had a longer overall survival time in the KM curve, and a lower proportion of dead patients in the survival distribution curve. Potential mechanisms and possible functions were revealed using GSEA and the ceRNA network. By integrating clinical information, the association between lncRNAs and clinical features was analyzed and several features affecting prognosis were identified. Then, a nomogram was developed to predict survival rates, and its good predictive performance was indicated by a relatively high C-index (0.67118161) and a good match in calibration curves. Next, the association between these lncRNAs and therapy was explored. Patients in the low-risk group had an immune-activating environment, higher immune scores, higher TMB, lower TIDE scores, and higher expression of immune checkpoints, suggesting they might receive a greater benefit from immune checkpoint inhibitor therapy. In addition, a significant difference in the sensitivity to mitomycin. C, cisplatin, and docetaxel, but not etoposide and paclitaxel, was observed. In summary, this model had guiding significance for prognosis and personalized therapy. It helped screen patients with stomach cancer who might benefit from immunotherapy and guided the selection of personalized chemotherapeutic drugs.

Abnormal Iron and Lipid Metabolism Mediated Ferroptosis in Kidney Diseases and Its Therapeutic Potential

Ferroptosis is a newly identified form of regulated cell death driven by iron-dependent phospholipid peroxidation and oxidative stress. Ferroptosis has distinct biological and morphology characteristics, such as shrunken mitochondria when compared to other known regulated cell deaths. The regulation of ferroptosis includes different molecular mechanisms and multiple cellular metabolic pathways, including glutathione/glutathione peroxidase 4(GPX4) signaling pathways, which are involved in the amino acid metabolism and the activation of GPX4; iron metabolic signaling pathways, which are involved in the regulation of iron import/export and the storage/release of intracellular iron through iron-regulatory proteins (IRPs), and lipid metabolic signaling pathways, which are involved in the metabolism of unsaturated fatty acids in cell membranes. Ferroptosis plays an essential role in the pathology of various kidneys diseases, including acute kidney injury (AKI), chronic kidney disease (CKD), autosomal dominant polycystic kidney disease (ADPKD), and renal cell carcinoma (RCC). Targeting ferroptosis with its inducers/initiators and inhibitors can modulate the progression of kidney diseases in animal models. In this review, we discuss the characteristics of ferroptosis and the ferroptosis-based mechanisms, highlighting the potential role of the main ferroptosis-associated metabolic pathways in the treatment and prevention of various kidney diseases.

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.

Genetic Profiles of Ferroptosis in Malignant Brain Tumors and Off-Target Effects of Ferroptosis Induction

Glioblastoma represents the most devastating form of human brain cancer, associated with a very poor survival rate of patients. Unfortunately, treatment options are currently limited and the gold standard pharmacological treatment with the chemotherapeutic drug temozolomide only slightly increases the survival rate. Experimental studies have shown that the efficiency of temozolomide can be improved by inducing ferroptosis – a recently discovered form of cell death, which is different from apoptosis, necrosis, or necroptosis and, which is characterized by lipid peroxidation and reactive oxygen species accumulation. Ferroptosis can also be activated to improve treatment of malignant stages of neuroblastoma, meningioma, and glioma. Due to their role in cancer treatment, ferroptosis-gene signatures have recently been evaluated for their ability to predict survival of patients. Despite positive effects during chemotherapy, the drugs used to induce ferroptosis – such as erastin and sorafenib – as well as genetic manipulation of key players in ferroptosis – such as the cystine-glutamate exchanger xCT and the glutathione peroxidase GPx4 – also impact neuronal function and cognitive capabilities. In this review, we give an update on ferroptosis in different brain tumors and summarize the impact of ferroptosis on healthy tissues.

Identification of immune subtypes of Ph-neg B-ALL with ferroptosis related genes and the potential implementation of Sorafenib

BACKGROUND

The clinical outcome of Philadelphia chromosome-negative B cell acute lymphoblastic leukemia (Ph-neg B-ALL) varies considerably from one person to another after clinical treatment due to lack of targeted therapies and leukemia's heterogeneity. Ferroptosis is a recently discovered programmed cell death strongly correlated with cancers. Nevertheless, few related studies have reported its significance in acute lymphoblastic leukemia.

METHODS

Herein, we collected clinical data of 80 Ph-neg B-ALL patients diagnosed in our center and performed RNA-seq with their initial bone marrow fluid samples. Throughout unsupervised machine learning K-means clustering with 24 ferroptosis related genes (FRGs), the clustered patients were parted into three variant risk groups and were performed with bioinformatics analysis.

RESULTS

As a result, we discovered significant heterogeneity of both immune microenvironment and genomic variance. Furthermore, the immune check point inhibitors response and potential implementation of Sorafenib in Ph-neg B-ALL was also analyzed in our cohort. Lastly, one prognostic model based on 8 FRGs was developed to evaluate the risk of Ph-neg B-ALL patients.

CONCLUSION

Jointly, our study proved the crucial role of ferroptosis in Ph-neg B-ALL and Sorafenib is likely to improve the survival of high-risk Ph-neg B-ALL patients.

Regulated Cell Death in Urinary Malignancies

Urinary malignancies refer to a series of malignant tumors that occur in the urinary system and mainly include kidney, bladder, and prostate cancers. Although local or systemic radiotherapy and chemotherapy, immunotherapy, castration therapy and other methods have been applied to treat these diseases, their high recurrence and metastasis rate remain problems for patients. With in-depth research on the pathogenesis of urinary malignant tumors, this work suggests that regulatory cell death (RCD) plays an important role in their occurrence and development. These RCD pathways are stimulated by various internal and external environmental factors and can induce cell death or permit cell survival under the control of various signal molecules, thereby affecting tumor progression or therapeutic efficacy. Among the previously reported RCD methods, necroptosis, pyroptosis, ferroptosis, and neutrophil extracellular traps (NETs) have attracted research attention. These modes transmit death signals through signal molecules, such as cysteine-aspartic proteases (caspase) family and tumor necrosis factor-α (TNF-α) that have a wide and profound influence on tumor proliferation or death and even change the sensitivity of tumor cells to therapy. This review discussed the effects of necroptosis, pyroptosis, ferroptosis, and NETs on kidney, bladder and prostate cancer and summarized the latest research and achievements in these fields. Future directions and possibility of improving the denouement of urinary system tumors treatment by targeting RCD therapy were also explored.

Dipetidyl peptidase-4 and transferrin receptor serve as prognostic biomarkers for acute myeloid leukemia

Background

Acute myeloid leukemia (AML) is the most common hematological malignancy in adult patients. Ferroptosis-related signatures have been shown to act as regulators of the progression of multiple cancer types, but the role of ferroptosis in AML remains to be elucidated. We performed the present study to preliminarily investigate the roles of ferroptosis-related genes (FRGs) in AML.

Methods

The transcriptome data of AML patients was downloaded from The Cancer Genome Atlas (TCGA) and the transcriptome data of normal samples was obtained from the Genotype-Tissue Expression (GTEx) database. FRGs were selected via public articles. Expression levels of FRGs between AML and normal samples were analyzed. The prognostic model based on FRGs was constructed via lasso regression. The expression levels and prognostic role of FRGs were identified from the risk model. We also performed validation experiments to verify the expression levels of the final selected genes via immunohistochemistry, polymerase chain reaction (PCR), and RNA-seq. Finally, we explored the associations between immune infiltration, drug sensitivity, and the selected FRGs.

Results

The transcriptome data of 151 AML samples were retrieved from TCGA and 70 bone marrow normal samples were retrieved from the GTEx database. Additionally, 23 FRGs were collected from the published articles. There were 22 differentially expressed FRGs, and among them, dipetidyl peptidase-4 (DPP4) (P= 0.011, HR =1.504), GPX4 (P=0.055, HR =1.569), LPCAT3 (P<0.001, HR =2.243), SLC7A11 (P=0.012, HR =2.243), and transferrin receptor (TFRC) (P=0.029, 0.774) had a significant influence on the prognosis of AML patients via lasso regression. The area under the curve (AUC) values of the 1-, 3-, and 5-year receiver operating characteristic (ROC) curves of the FRG signatures indicated that this model is novel and effective method for predicting the prognosis of AML patients. DPP4 (P<0.001) was overexpressed while LPCAT3 (P<0.001), TFRC (P<0.001), GPX4 (P<0.001), and SLC7A11 (P<0.001) were downregulated, further validation experiment results indicated that DPP4 was significantly downregulated but TFRC was upregulated in AML samples. Dysregulation of DPP4 and TFRC influence numbers of chemotherapy regimens sensitivity.

Conclusions

DPP4 and TFRC act as biomarkers for predicting and diagnosing AML, and their expression levels also have significant correlations with drug resistance in AML.

Ferroptosis regulators, especially SQLE, play an important role in prognosis, progression and immune environment of breast cancer

BACKGROUND

Ferroptosis, a new form of programmed cell death, has great potential for cancer treatment. However, the roles of ferroptosis-related (FR) genes in breast cancer (BC) remain elusive.

MATERIALS AND METHODS

Using TCGA database, a novel FR risk signature was constructed through the Lasso regression analysis. Meanwhile, its prognostic value was assessed by a series of survival analyses. Besides, a nomogram was constructed to predict the overall survival rate (OSR) of individual at 1,3,5 year. Four validation cohorts (n = 2248), including METABRIC, GSE58812, GSE20685 and ICGC-KR datasets, were employed to test the prognostic value of FR risk signature. The effects of FR risk signature on BC immune microenvironment were explored by CIBERSORT algorithm and ssGSEA method. The histological expressions of FR risk genes were presented by HPA database. The biofunctions of SQLE were determined by qPCR, MTT, wound-healing and Transwell assays.

RESULTS

We constructed a novel FR risk signature consisting of eight genes. High FR risk led a poor prognosis and was identified as an independent prognostic factor. Besides, A higher proportion of patients with luminal A type was observed in low-risk group (53%), while a higher proportion of patients with basal type in high-risk group (24%). FR risk score could discriminate the prognostic difference of most clinical subgroups, except for M1 stage, HER2 and basal types. Moreover, its prognostic value was successfully validated in other four cohorts. Through immune analyses, we found that the reduced infiltration levels of CD8+ and NK cells, whereas the enhanced activity of antigen presentation process appeared in high FR risk. Then, FR risk score was found to weakly correlate with the expressions of six immune checkpoints. Through the experiments in vitro, we confirmed that overexpression of SQLE could promote, whereas blocking SQLE could inhibit the proliferative, migrative and invasive abilities of BC cells.

CONCLUSIONS

FR risk signature was conducive to BC prognostic assessment. High FR risk level was closely associated with BC immunosuppression, but may not predict ICIs efficacy. Moreover, SQLE was identified as a crucial cancer-promoting gene in BC. Our findings provide new insights into prognostic assessment and molecular mechanism of BC.

Over-expression of lncRNA TMEM161B-AS1 promotes the malignant biological behavior of glioma cells and the resistance to temozolomide via up-regulating the expression of multiple ferroptosis-related genes by sponging hsa-miR-27a-3p

A growing body of evidence suggests that long-chain non-coding RNA (lncRNA) plays an important role in the malignant biological behavior and drug resistance of glioblastoma (GBM) cells. In this study, we analyzed the role and potential mechanism of lncRNA TMEM161B-AS1 in the malignant biological behavior of GBM cells and temozolomide (TMZ) resistance. Studies have found that FANCD2 and CD44 are significantly related to the occurrence of GBM, TMZ resistance and the survival of GBM patients. Knockdown of TMEM161B-AS1 down-regulated the expression of FANCD2 and CD44 by sponging hsa-miR-27a-3p, inhibited the proliferation, migration, invasion and promoted apoptosis, ferroptosis of U87 cells and U251 cells. Down-regulation of lncRNA TMEM161B-AS1 and/or over-expression of hsa-miR-27a-3p down-regulated the expression of FANCD2 and CD44, and inhibited the tumor growth in nude mice. These results demonstrated that the lncRNA TMEM161B-AS1-hsa-miR-27a-3p-FANCD2/CD44 signal axis regulated the malignant biological behavior of GBM and TMZ resistance. These findings were expected to provide promising therapeutic targets for the treatment of glioma.

Analysis of Ferroptosis-Related Gene Expression and Prognostic Factors of Renal Clear Cell Carcinoma Based on TCGA Database

Introduction

Renal clear cell carcinoma (ccRCC) is a common tumor of the urinary system, most of which are primary malignant tumors with high metastatic rate and remaining incurable. Ferroptosis is a newly discovered form of iron-dependent programmed cell necrosis in recent years, which is inextricably linked to the occurrence and development of tumors progression. Due to the complexity of the interaction between genes in ccRCC, the research on the pathogenesis of ccRCC is still not remarkably accurate. Therefore, whether ferroptosis-related genes (FRGs) can play a role in predicting prognosis in ccRCC needs to be discussed.

Methods

We entered the Cancer Genome Mapping Project (TCGA) database and downloaded the relevant genes and clinical research data of ccRCC patients. Lasso Cox regression was used to construct a multi-gene prognostic model in the TCGA cohort. R language software was used for drawing pictures related to our study.

Results

Most of the genes involved in ferroptosis (86.2%) existing differences between the tumor and normal tissues in the TCGA public gene database. In terms of univariate Cox regression analysis, 20 differentially expressed genes (DEGs) were associated with prognosis and survival (P<0.05). A prognostic model of 12 FRGs was constructed, and patients were segmented into two different groups depending on how risky they are. Considering overall survival, the high-risk group is dramatically lower than the low-risk group (P<0.001). In multivariate Cox regression analysis, risk scores and stage turned out be an independent prognostic factor (P<0.001). GO and KEGG analysis and ssGSEA analysis of DEGs revealed that these genes were related to immune-related pathways (P<0.05).

Conclusion

This study established and identified the changes in FRGs expression and prognostic factors of ccRCC, which can be helpful for prognosis evaluation and clinical treatment of this disease.

Identification of a Novel Ferroptosis-Related Gene Prognostic Signature in Bladder Cancer

Background

Ferroptosis is a newly found non-apoptotic forms of cell death that plays an important role in tumors. However, the prognostic value of ferroptosis-related genes (FRG) in bladder cancer (BLCA) have not been well examined.

Methods

FRG data and clinical information were collected from The Cancer Genome Atlas (TCGA). Then, significantly different FRGs were investigated by functional enrichment analyses. The prognostic FRG signature was identified by univariate cox regression and least absolute shrinkage and selection operator (LASSO) analysis, which was validated in TCGA cohort and Gene Expression Omnibus (GEO) cohort. Subsequently, the nomogram integrating risk scores and clinical parameters were established and evaluated. Additionally, Gene Set Enrichment Analyses (GSEA) was performed to explore the potential molecular mechanisms underlying our prognostic FRG signature. Finally, the expression of three key FRGs was verified in clinical specimens.

Results

Thirty-two significantly different FRGs were identified from TCGA–BLCA cohort. Enrichment analyses showed that these genes were mainly related to the ferroptosis. Seven genes (TFRC, G6PD, SLC38A1, ZEB1, SCD, SRC, and PRDX6) were then identified to develop a prognostic signature. The Kaplan–Meier analysis confirmed the predictive value of the signature for overall survival (OS) in both TCGA and GEO cohort. A nomogram integrating age and risk scores was established and demonstrated high predictive accuracy, which was validated through calibration curves and receiver operating characteristic (ROC) curve [area under the curve (AUC) = 0.690]. GSEA showed that molecular alteration in the high- or low-risk group was closely associated with ferroptosis. Finally, experimental results confirmed the expression of SCD, SRC, and PRDX6 in BLCA.

Conclusion

Herein, we identified a novel FRG prognostic signature that maybe involved in BLCA. It showed high values in predicting OS, and targeting these FRGs may be an alternative for BLCA treatment. Further experimental studies are warranted to uncover the mechanisms that these FRGs mediate BLCA progression.

A New Survival Model Based on ADAMTSs for Prognostic Prediction in Clear Cell Renal Cell Carcinoma

The main purpose of this study was to explore the genetic variation, gene expression, and clinical significance of ADAMTSs (a disintegrin and metalloprotease domains with thrombospondin motifs) across cancer types. Analysis of data from the TCGA (The Cancer Genome Atlas) database showed that the ADAMTSs have extensive CNV (copy number variation) and SNV (single nucleotide variation) across cancer types. Compared with normal tissues, the methylation of ADAMTSs in cancer tissues is also significantly different, which affects the expression of ADAMTS gene and the prognosis of cancer patients. Through gene expression analysis, we found that ADAMTS family has significant changes in gene expression across cancer types and is closely related to the prognosis of carcinoma, especially in ccRCC (clear cell renal cell carcinoma). LASSO regression analysis was used to establish a prognostic model based on the ADAMTSs to judge the prognosis of patients with ccRCC. Multiple Cox regression analysis suggested that age, grade, stage, and risk score of the prognostic model of ccRCC were independent prognostic factors in patients with renal clear cell carcinoma. These findings indicate that the ADAMTSs-based survival model can accurately predict the prognosis of patients with ccRCC and suggest that ADAMTSs are a potential prognostic biomarker and therapeutic target in ccRCC.

The Uniqueness of Clear Cell Renal Cell Carcinoma: Summary of the Process and Abnormality of Glucose Metabolism and Lipid Metabolism in ccRCC

Kidney cancer is a cancer with an increasing incidence in recent years. Clear cell renal cell carcinoma (ccRCC) accounts for up to 80% of all kidney cancers. The understanding of the pathogenesis, tumor progression, and metastasis of renal carcinoma is not yet perfect. Kidney cancer has some characteristics that distinguish it from other cancers, and the metabolic aspect is the most obvious. The specificity of glucose and lipid metabolism in kidney cancer cells has also led to its being studied as a metabolic disease. As the most common type of kidney cancer, ccRCC has many characteristics that represent the specificity of kidney cancer. There are features that we are very concerned about, including the presence of lipid droplets in cells and the obesity paradox. These two points are closely related to glucose metabolism and lipid metabolism. Therefore, we hope to explore whether metabolic changes affect the occurrence and development of kidney cancer by looking for evidence of changes on expression at the genomic and protein levels in glucose metabolism and lipid metabolism in ccRCC. We begin with the representative phenomenon of abnormal cancer metabolism: the Warburg effect, through the collection of popular metabolic pathways and related genes in the last decade, as well as some research hotspots, including the role of ferroptosis and glutamine in cancer, systematically elaborated the factors affecting the incidence and metastasis of kidney cancer. This review also identifies the similarities and differences between kidney cancer and other cancers in order to lay a theoretical foundation and provide a valid hypothesis for future research.

Genomic analysis uncovers prognostic and immunogenic characteristics of ferroptosis for clear cell renal cell carcinoma

In this study, the characteristic patterns of ferroptosis in clear cell renal cell carcinoma (ccRCC) were systematically investigated with the interactions between ferroptosis and the tumor microenvironment (TME). On the mRNA expression profiles of 57 ferroptosis-related genes (FRGs), three ferroptosis patterns were constructed, with distinct prognosis and immune cell infiltrations (especially T cells and dendritic cells). The high ferroptosis scores were characterized by poorer prognosis, increased T cell infiltration, higher immune and stromal scores, elevated tumor mutation burden, and enhanced response to anti-CTLA4 immunotherapy. Meanwhile, the low ferroptosis scores were distinctly associated with enhanced tumor purity and amino acid and fatty acid metabolism pathways. Following validation, the ferroptosis score was an independent and effective prognostic factor. Collectively, ferroptosis could be involved in the diverse and complex TME. Evaluation of the ferroptosis patterns may heighten the comprehension about immune infiltrations in the TME, assisting oncologists to generate individualized immunotherapeutic strategies.