A Ferroptosis-Related lncRNAs Signature Predicts Prognosis and Immune Microenvironment for Breast Cancer

Synergistic bioinformatics and sophisticated machine learning unveil ferroptosis-driven regulatory pathways and immunotherapy potential in breast carcinoma

BACKGROUND

The intersection of aberrant iron metabolism and the rapidly advancing field of immunotherapy has emerged as a critical focus in breast cancer (BRCA) therapeutics. Ferroptosis, a distinct form of iron-dependent cell death driven by lipid peroxidation, has garnered increasing attention for its pivotal role in cancer progression.

METHODS

Utilizing extensive datasets from TCGA and GEO, this research extracted a wealth of biological data, including mRNA splicing indices, genomic aberrations, copy number variations (CNV), tumor mutational burden (TMB), and diverse clinical information. Through precise Lasso regression analysis, this research constructed a prognostic model that elucidates the molecular interactions of FRGs in BRCA. Concurrent co-expression network analyses were performed to explore the dynamic interplay between gene expression patterns and FRGs, revealing potential regulatory mechanisms.

RESULTS

This research analysis revealed significant overexpression of FRGs in high-risk BRCA samples, highlighting their prognostic relevance beyond traditional clinical parameters. GSVA identified immune response and cancer-related pathways as predominantly active in high-risk groups, suggesting ferroptosis as a central modulator within the tumor microenvironment. Notably, genes such as ACTL8, VGF, and CPLX2 emerged as markers of tumorigenesis, while IL33 and TP63 were identified as potential key regulators of cancer progression, each exhibiting distinct expression profiles across risk levels. Furthermore, this research incorporated gene correlations, CNV profiles, SNP arrays, and drug susceptibility analyses, contributing to the advancement of precision oncology.

CONCLUSIONS

The integration of bioinformatics and machine learning in this study underscores a strong correlation between FRG expression patterns and BRCA prognosis, affirming their potential as precise biomarkers for personalized immunotherapy.

Current Status and Future Directions of Ferroptosis Research in Breast Cancer: Bibliometric Analysis

BACKGROUND

Ferroptosis, as a novel modality of cell death, holds significant potential in elucidating the pathogenesis and advancing therapeutic strategies for breast cancer.

OBJECTIVE

This study aims to comprehensively analyze current ferroptosis research and future trends, guiding breast cancer research advancements and innovative treatment strategies.

METHODS

This research used the R package Bibliometrix (Department of Economic and Statistical Sciences at the University of Naples Federico II), VOSviewer (Centre for Science and Technology Studies at Leiden University), and CiteSpace (Drexel University's College of Information Science and Technology), to conduct a bibliometric analysis of 387 papers on breast cancer and ferroptosis from the Web of Science Core Collection. The analysis covers authors, institutions, journals, countries or regions, publication volumes, citations, and keywords.

RESULTS

The number of publications related to this field has surged annually, with China and the United States collaborating closely and leading in output. Sun Yat-sen University stands out among the institutions, while the journal Frontiers in Oncology and the author Efferth T contribute significantly to the field. Highly cited papers within the domain primarily focus on the induction of ferroptosis, protein regulation, and comparisons with other modes of cell death, providing a foundation for breast cancer treatment. Keyword analysis highlights the maturity of glutathione peroxidase 4-related research, with breast cancer subtypes emerging as motor themes and the tumor microenvironment, immunotherapy, and prognostic models identified as basic themes. Furthermore, the application of nanoparticles serves as an additional complement to the basic themes.

CONCLUSIONS

The current research status in the field of ferroptosis and breast cancer primarily focuses on the exploration of relevant theoretical mechanisms, whereas future trends and mechanisms emphasize the investigation of therapeutic strategies, particularly the clinical application of immunotherapy related to the tumor microenvironment. Nanotherapy has demonstrated significant clinical potential in this domain. Future research directions should deepen the exploration in this field and accelerate the clinical translation of research findings to provide new insights and directions for the innovation and development of breast cancer treatment strategies.

Targeting the initiator to activate both ferroptosis and cuproptosis for breast cancer treatment: progress and possibility for clinical application

Breast cancer is the most commonly diagnosed cancer worldwide. Metal metabolism is pivotal for regulating cell fate and drug sensitivity in breast cancer. Iron and copper are essential metal ions critical for maintaining cellular function. The accumulation of iron and copper ions triggers distinct cell death pathways, known as ferroptosis and cuproptosis, respectively. Ferroptosis is characterized by iron-dependent lipid peroxidation, while cuproptosis involves copper-induced oxidative stress. They are increasingly recognized as promising targets for the development of anticancer drugs. Recently, compelling evidence demonstrated that the interplay between ferroptosis and cuproptosis plays a crucial role in regulating breast cancer progression. This review elucidates the converging pathways of ferroptosis and cuproptosis in breast cancer. Moreover, we examined the value of genes associated with ferroptosis and cuproptosis in the clinical diagnosis and treatment of breast cancer, mainly outlining the potential for a co-targeting approach. Lastly, we delve into the current challenges and limitations of this strategy. In general, this review offers an overview of the interaction between ferroptosis and cuproptosis in breast cancer, offering valuable perspectives for further research and clinical treatment.

Identification of ferroptosis-related LncRNAs as potential targets for improving immunotherapy in glioblastoma

The effect of ferroptosis-related long non-coding RNAs (lncRNAs) in predicting immunotherapy response to glioblastoma (GBM) remains obscure. This study established a 11-lncRNAs prognostic signature. Differential gene expression analysis, univariate and multivariate Cox regression analyses and the least absolute shrinkage and selection operator (LASSO) regression algorithm were used to identify prognostic ferroptosis-related genes and establish a nomogram model of risk score. Kaplan-Meier survival plots and receiver operating characteristic (ROC) curve analysis were used to evaluate the prognostic accuracy of the model in the TCGA-GBM cohort. To verify the expression of these signatures, we analyzed the expression levels of three lncRNAs (AGAP2-AS1, OSMR-AS1, UNC5B-AS1) in LN229 and U87 cells. The ROC analysis showed that the area under curve (AUC) of this signature is 0.814, suggesting that it has a promising performance on GBM prognostic prediction. Kaplan-Meier analysis showed that the survival rate of GBM patients in high-risk group was significantly lower than low-risk group, and the performance of this signature on GBM prognostic prediction was superior to conventional clinicopathological factors. Further qRT-PCR experiment also confirmed our prediction of lncRNA signatures. These ferroptosis-related lncRNAs might be therapeutic targets for glioblastoma, and targeting these lncRNAs can also improve the efficacy of immunotherapy, especially immune checkpoint inhibitors. Mechanistically, these findings might attribute to N6-methyladenosine (m6A) mRNA modification on lncRNAs.

Identification of a ferroptosis-related gene signature for the prognosis of pediatric neuroblastoma

Background

Ferroptosis-related genes are correlated with the prognosis of patients with neuroblastoma (NB) remains unknown. This study aims to establish a prognostic ferroptosis-related gene model for predicting prognostic value in pediatric NB patients.

Methods

The gene expression array and clinical characteristics of NB were downloaded from a public database. Correlations between ferroptosis-related genes and drug responses were analyzed by Childhood Cancer Therapeutics. The prognostic model was constructed by least absolute shrinkage and selection operator (LASSO) Cox regression and was validated in NB patients from the ICGC cohort. The survival analysis was performed by Cox regression analysis. single-sample gene set enrichment analysis (ssGSEA) was used to quantify the immune cell infiltration correlation.

Results

Overall, 70 genes were identified as ferroptosis-related differentially expressed genes (DEGs) from 247 samples. Then, 13 ferroptosis-related genes were correlated with OS in the univariate Cox regression analysis. Five prognostic ferroptosis-related DEGs (pFR-DEGs) (STEAP3, MAP1LC3A, ULK2, MTOR and TUBE1), which were defined as the intersection of DEGs and prognostic ferroptosis-related genes, were identified and utilized to construct the prognostic signature. The correlation between five pFR-DEGs and drug responses was analyzed, and the box plots indicated that MTOR gene expression was highest, suggesting that MTOR expression is related to progressive NB disease. The receiver operating characteristic (ROC) curve showed that the model had moderate predictive power. The survival analysis indicated that the high-risk group had poor overall survival (OS) (P=2.087×10-06). Univariate and multivariate analyses identified the risk score as a significant prognostic risk factor [P=0.003, hazard ratio (HR) =1.933]. Immune cell infiltration correlation analysis showed that the high-risk group was related to more immune cells.

Conclusions

The present study indicated a difference in ferroptosis-related gene expression between low- and high-risk NB patients. The ferroptosis-related signature could serve as a prognostic prediction tool. Additionally, immune infiltration might play an important role in different risk groups for NB patients.

A Novel Cellular Senescence-related lncRNA Signature for Predicting the Prognosis of Breast Cancer Patients

Background: Long non-coding RNA (lncRNA), a crucial regulator in breast cancer (BC) development, is intricately linked with cellular senescence. However, there is a lack of cellular senescence-related lncRNAs (CSRLs) signature to evaluate the prognosis of BC patients. Methods: Correlation analysis was conducted to identify lncRNAs associated with cellular senescence. Subsequently, a CSRL signature was crafted in the training cohort. The model's accuracy was evaluated through survival analysis and receiver operating characteristic curves. Furthermore, prognostic nomograms amalgamating cellular senescence and clinical characteristics were devised. Tumor microenvironment and checkpoint disparities were compared between low-risk and high-risk groups. The correlation between these signatures and treatment response in BC patients was also investigated. Finally, functional experiments were conducted for validation. Results: A signature comprising nine CSRLs was devised, which demonstrated adept prognostic capability in BC patients. Functional enrichment analysis revealed that tumor and immune-related pathways were predominantly enriched. Compared to the low-risk group, the high-risk group could benefit more from immunotherapy and certain chemotherapeutic agents. The expression of the 9 CSRLs was validated through in vitro experiments in different subtypes of BC cell lines and tissues. AC098484.1 was specifically verified for its association with senescence-associated secretory phenotypes. Conclusion: The CSRLs signature emerges as a promising prognostic biomarker for BC, with implications for immunological studies and treatment strategies. AC098484.1 has potential relevance in the treatment of BC cell senescence, and these findings improve the clinical treatment levels for BC patients.

Ferroptosis and hepatocellular carcinoma: the emerging role of lncRNAs

Hepatocellular carcinoma is the most common form of primary liver cancer and poses a significant challenge to the medical community because of its high mortality rate. In recent years, ferroptosis, a unique form of cell death, has garnered widespread attention. Ferroptosis, which is characterized by iron-dependent lipid peroxidation and mitochondrial alterations, is closely associated with the pathological processes of various diseases, including hepatocellular carcinoma. Long non-coding RNAs (lncRNAs), are a type of functional RNA, and play crucial regulatory roles in a variety of biological processes. In this manuscript, we review the regulatory roles of lncRNAs in the key aspects of ferroptosis, and summarize the research progress on ferroptosis-related lncRNAs in hepatocellular carcinoma.

Revolutionizing breast cancer treatment: Harnessing the related mechanisms and drugs for regulated cell death (Review)

Breast cancer arises from the malignant transformation of mammary epithelial cells under the influence of various carcinogenic factors, leading to a gradual increase in its prevalence. This disease has become the leading cause of mortality among female malignancies, posing a significant threat to the health of women. The timely identification of breast cancer remains challenging, often resulting in diagnosis at the advanced stages of the disease. Conventional therapeutic approaches, such as surgical excision, chemotherapy and radiotherapy, exhibit limited efficacy in controlling the progression and metastasis of the disease. Regulated cell death (RCD), a process essential for physiological tissue cell renewal, occurs within the body independently of external influences. In the context of cancer, research on RCD primarily focuses on cuproptosis, ferroptosis and pyroptosis. Mounting evidence suggests a marked association between these specific forms of RCD, and the onset and progression of breast cancer. For example, a cuproptosis vector can effectively bind copper ions to induce cuproptosis in breast cancer cells, thereby hindering their proliferation. Additionally, the expression of ferroptosis‑related genes can enhance the sensitivity of breast cancer cells to chemotherapy. Likewise, pyroptosis‑related proteins not only participate in pyroptosis, but also regulate the tumor microenvironment, ultimately leading to the death of breast cancer cells. The present review discusses the unique regulatory mechanisms of cuproptosis, ferroptosis and pyroptosis in breast cancer, and the mechanisms through which they are affected by conventional cancer drugs. Furthermore, it provides a comprehensive overview of the significance of these forms of RCD in modulating the efficacy of chemotherapy and highlights their shared characteristics. This knowledge may provide novel avenues for both clinical interventions and fundamental research in the context of breast cancer.

Role of ferroptosis and ferroptosis-related long non'coding RNA in breast cancer

Ferroptosis, a therapeutic strategy for tumours, is a regulated cell death characterised by the increased accumulation of iron-dependent lipid peroxides (LPO). Tumour-associated long non-coding RNAs (lncRNAs), when combined with traditional anti-cancer medicines or radiotherapy, can improve efficacy and decrease mortality in cancer. Investigating the role of ferroptosis-related lncRNAs may help strategise new therapeutic options for breast cancer (BC). Herein, we briefly discuss the genes and pathways of ferroptosis involved in iron and reactive oxygen species (ROS) metabolism, including the XC-/GSH/GPX4 system, ACSL4/LPCAT3/15-LOX and FSP1/CoQ10/NAD(P)H pathways, and investigate the correlation between ferroptosis and LncRNA in BC to determine possible biomarkers related to ferroptosis.

Novel insights into the pathogenesis of thyroid eye disease through ferroptosis-related gene signature and immune infiltration analysis

Thyroid eye disease (TED) has brought great physical and mental trauma to patients worldwide. Although a few potential signaling pathways have been reported, knowledge of TED remains limited. Our objective is to explore the fundamental mechanism of TED and identify potential therapeutic targets using diverse approaches. To perform a range of bioinformatic analyses, such as identifying differentially expressed genes (DEGs), conducting enrichment analysis, establishing nomograms, analyzing weighted gene correlation network analysis (WGCNA), and studying immune infiltration, the datasets GSE58331, GSE105149, and GSE9340 were integrated. Further validation was conducted using qPCR, western blot, and immunohistochemistry techniques. Eleven ferroptosis-related DEGs derived from the lacrimal gland were originally screened. Their high diagnostic value was proven, and diagnostic prediction nomogram models with high accuracy and robustness were established by using machine learning. A total of 15 hub gene-related DEGs were identified by WGCNA. Through CIBERSORTx, we uncovered five immune cells highly correlated with TED and found several special associations between these immune cells and the above DEGs. Furthermore, EGR2 from the thyroid sample was revealed to be closely negatively correlated with most DEGs from the lacrimal gland. High expression of APOD, COPB2, MYH11, and MYCN, as well as CD4/CD8 T cells and B cells, was verified in the periorbital adipose tissues of TED patients. To summarize, we discovered a new gene signature associated with ferroptosis that has a critical impact on the development of TED and provides valuable insights into immune infiltration. These findings might highlight the new direction and therapeutic strategies of TED.

Recent advances in the potential effects of natural products from traditional Chinese medicine against respiratory diseases targeting ferroptosis

Respiratory diseases, marked by structural changes in the airways and lung tissues, can lead to reduced respiratory function and, in severe cases, respiratory failure. The side effects of current treatments, such as hormone therapy, drugs, and radiotherapy, highlight the need for new therapeutic strategies. Traditional Chinese Medicine (TCM) offers a promising alternative, leveraging its ability to target multiple pathways and mechanisms. Active compounds from Chinese herbs and other natural sources exhibit anti-inflammatory, antioxidant, antitumor, and immunomodulatory effects, making them valuable in preventing and treating respiratory conditions. Ferroptosis, a unique form of programmed cell death (PCD) distinct from apoptosis, necrosis, and others, has emerged as a key area of interest. However, comprehensive reviews on how natural products influence ferroptosis in respiratory diseases are lacking. This review will explore the therapeutic potential and mechanisms of natural products from TCM in modulating ferroptosis for respiratory diseases like acute lung injury (ALI), asthma, pulmonary fibrosis (PF), chronic obstructive pulmonary disease (COPD), lung ischemia-reperfusion injury (LIRI), pulmonary hypertension (PH), and lung cancer, aiming to provide new insights for research and clinical application in TCM for respiratory health.

Investigating the Potential Mechanisms of Ferroptosis and Autophagy in the Pathogenesis of Gestational Diabetes

Ferroptosis and autophagy are two different cellular processes that have recently been highlighted for their potential roles in the pathogenesis and progression of gestational diabetes (GD). This research sought to uncover the crucial genes tied to ferroptosis and autophagy in GD, further investigating their mechanisms. Differentially expressed genes (DEGs) linked to ferroptosis and autophagy in GD were identified using publicly available data. Pathway enrichment, protein interactions, correlation with immune cell infiltration, and diagnostic value of DEGs were analyzed. HTR-8/SVneo cells were subjected to varying glucose levels to evaluate cell viability and the expression of markers related to ferroptosis and proteins associated with autophagy. Crucial DEGs were validated in vitro. A total of 12 DEGs associated with ferroptosis and autophagy in GD were identified, enriched in the PI3K-AKT signaling pathway. These genes exhibited significant correlations with monocyte infiltration, resting CD4 memory T cells, and follicular helper T cells. They exhibited high diagnostic value for GD (AUC: 0.77-0.97). High glucose treatment inhibited cell viability, induced ferroptosis, and activated autophagy in HTR-8/SVneo cells. Validation confirmed altered expression of SNCA, MTDH, HMGB1, TLR4, SOX2, SESN2, and HMOX1 after glucose treatments. In conclusion, ferroptosis and autophagy may play a role in GD development through key genes (e.g., TLR4, SOX2, SNCA, HMOX1, HMGB1). These genes could serve as promising biomarkers for GD diagnosis.

Novel Insights on Ferroptosis Modulation as Potential Strategy for Cancer Treatment: When Nature Kills

Significance: The multifactorial nature of the mechanisms implicated in cancer development still represents a major issue for the success of established antitumor therapies. The discovery of ferroptosis, a novel form of programmed cell death distinct from apoptosis, along with the identification of the molecular pathways activated during its execution, has led to the uncovering of novel molecules characterized by ferroptosis-inducing properties. Recent advances: As of today, the ferroptosis-inducing properties of compounds derived from natural sources have been investigated and interesting findings have been reported both in vitro and in vivo. Critical Issues: Despite the efforts made so far, only a limited number of synthetic compounds have been identified as ferroptosis inducers, and their utilization is still limited to basic research. In this review, we analyzed the most important biochemical pathways involved in ferroptosis execution, with particular attention to the newest literature findings on canonical and non-canonical hallmarks, together with mechanisms of action of natural compounds identified as novel ferroptosis inducers. Compounds have been classified based on their chemical structure, and modulation of ferroptosis-related biochemical pathways has been reported. Future Directions: The outcomes herein collected represent a fascinating starting point from which to take hints for future drug discovery studies aimed at identifying ferroptosis-inducing natural compounds for anticancer therapies. Antioxid. Redox Signal. 40, 40-85.

FZD7: A potential biomarker for endometriosis

BACKGROUND

Endometriosis is a chronic inflammatory, benign disorder that often co-occurs with adenomyosis and/or leiomyoma. The overall incidence of endometriosis in reproductive period women was nearly 10%. However, the exact mechanisms of endometriosis-associated pathogenesis are still unknown.

METHODS

In this study, we aimed to investigate whether Frizzled-7 (FZD7) would effectively promote the development of endometriosis. The microarray-based data analysis was performed to screen endometriosis-related differentially expressed genes. This process uncovered specific hub genes, and the nexus of vital genes and ferroptosis-related genes were pinpointed. Then, we collected human endometrial and endometriotic tissues from patients with endometriosis of the ovary (n = 39) and control patients without endometriosis (n = 10, who underwent hysterectomy for uterine fibroids) to compare the expression of FZD7.

RESULTS

These findings indicated that the expression of FZD7 was high compared with normal endometrium, and FZD7 may promote the progression of endometriosis.

CONCLUSION

FZD7 may serve as a potential therapeutic target for endometriosis treatment.

The current advances of lncRNAs in breast cancer immunobiology research

Breast cancer is the most frequently diagnosed malignancy and the leading cause of cancer-related death in women worldwide. Breast cancer development and progression are mainly associated with tumor-intrinsic alterations in diverse genes and signaling pathways and with tumor-extrinsic dysregulations linked to the tumor immune microenvironment. Significantly, abnormal expression of lncRNAs affects the tumor immune microenvironment characteristics and modulates the behavior of different cancer types, including breast cancer. In this review, we provide the current advances about the role of lncRNAs as tumor-intrinsic and tumor-extrinsic modulators of the antitumoral immune response and the immune microenvironment in breast cancer, as well as lncRNAs which are potential biomarkers of tumor immune microenvironment and clinicopathological characteristics in patients, suggesting that lncRNAs are potential targets for immunotherapy in breast cancer.

The epigenetic regulatory mechanisms of ferroptosis and its implications for biological processes and diseases

Ferroptosis is a form of regulated cell death triggered by the iron-dependent peroxidation of phospholipids. Interactions of iron and lipid metabolism factors jointly promote ferroptosis. Ferroptosis has been demonstrated to be involved in the development of various diseases, such as tumors and degenerative diseases (e.g., aortic dissection), and targeting ferroptosis is expected to be an effective strategy for the treatment of these diseases. Recent studies have shown that the regulation of ferroptosis is affected by multiple mechanisms, including genetics, epigenetics, posttranscriptional modifications, and protein posttranslational modifications. Epigenetic changes have garnered considerable attention due to their importance in regulating biological processes and potential druggability. There have been many studies on the epigenetic regulation of ferroptosis, including histone modifications (e.g., histone acetylation and methylation), DNA methylation, and noncoding RNAs (e.g., miRNAs, circRNAs, and lncRNAs). In this review, we summarize recent advances in research on the epigenetic mechanisms involved in ferroptosis, with a description of RNA N6-methyladenosine (m6A) methylation included, and the importance of epigenetic regulation in biological processes and ferroptosis-related diseases, which provides reference for the clinical application of epigenetic regulators in the treatment of related diseases by targeting ferroptosis.

Development and validation of ferroptosis-related lncRNA signature and immune-related gene signature for predicting the prognosis of cutaneous melanoma patients

Ferroptosis, a form of cell death caused by iron-dependent peroxidation of lipids, plays an important role in cancer. Recent studies have shown that long noncoding RNAs (lncRNAs) are involved in the regulation of ferroptosis in tumor cells and are also closely related to tumor immunity. Immune cell infiltration in the tumor microenvironment affects the prognosis and clinical outcome of immunotherapy in melanoma patients, and immune cell classification may be able to accurately predict the prognosis of melanoma patients. However, the prognostic value of ferroptosis-related lncRNAs (FRLs) in melanoma has not been thoroughly explored, and it is difficult to define the immune characteristics of melanoma. We used The Cancer Genome Atlas (TCGA), the Genotype-Tissue Expression (GTEx) database, and the FerrDb database to identify FRLs. FRLs with prognostic value were evaluated in an experimental cohort utilizing univariate, LASSO (least absolute shrinkage and selection operator) and multivariate Cox regression, followed by in vitro assays evaluating the expression levels and the biological functions of three candidate FRLs. Kaplan-Meier (K-M) and receiver operating characteristic (ROC) curve analyses were used to assess the validity of the risk model, and the drug sensitivity of FRLs was examined by drug sensitivity analysis. The differentially expressed genes between the high- and low-risk groups in the risk model were enriched in the immune pathway, and we further found immune gene signatures (IRGs) that could predict the prognosis of melanoma patients through a series of methods including single-sample Gene Set Enrichment Analysis (ssGSEA). Finally, two GEO cohorts were used to validate the predictive accuracy and reliability of these two signature models. Our findings suggest that FRLs and IRGs have the potential to predict the prognosis of patients with cutaneous melanoma.

Regulatory roles of ferroptosis-related non-coding RNAs and their research progress in urological malignancies

Ferroptosis is a new type of cell death characterized by damage to the intracellular microenvironment, which causes the accumulation of lipid hydroperoxide and reactive oxygen species to cause cytotoxicity and regulated cell death. Non-coding RNAs (ncRNAs) play an important role in gene expression at the epigenetic, transcriptional, and post-transcriptional levels through interactions with different DNAs, RNAs, or proteins. Increasing evidence has shown that ferroptosis-related ncRNAs are closely related to the occurrence and progression of several diseases, including urological malignancies. Recently, the role of ferroptosis-associated ncRNAs (long non-coding RNAs, micro RNAs, and circular RNAs) in the occurrence, drug resistance, and prognosis of urological malignancies has attracted widespread attention. However, this has not yet been addressed systematically. In this review, we discuss this issue as much as possible to expand the knowledge and understanding of urological malignancies to provide new ideas for exploring the diagnosis and treatment of urological malignancies in the future. Furthermore, we propose some challenges in the clinical application of ferroptosis-associated ncRNAs.

Cuproptosis-associated genes and immune microenvironment characterization in breast cancer

Excess Cu can cause cell death as a cofactor for essential enzymes. The relationship between cuproptosis-associated genes (CAGs) and breast cancer (BR) is not completely investigated. Here, the transcriptome expression and mutation profile data of BR samples from the Cancer Genome Atlas database were retrieved to identify CAGs. Patients with BR were clustered using consensus clustering. A least absolute shrinkage and selection operator analysis was then performed to construct a CAGs risk signature. As a result, all 13 cuproptosis regulators were significantly differentially expressed between BR and normal samples; among them, 9 cuproptosis genes were correlated with prognoses. Patients with BR were separated into 2 clusters that were associated with patient survival, clinical phenotypes, and immune infiltration, Based on the components of cuproptosis. Subsequently, genes differentially expressed between clusters were obtained, and 11 CAGs were ultimately incorporated into the risk signature. Functional analyses revealed that the risk signature correlated with patient outcomes, ER, PR, HER2 expression, and BR IHC subtypes. Additionally, immune microenvironment analyses showed that CAGs-high-risk patients exhibited lower immune cell infiltration and immune functions. Furthermore, high-risk BR patients had higher TMB, lower immune checkpoint expression, higher m6A gene expression, and higher tumor stemness. Finally, the immunophenoscore analysis revealed that the risk signature could potentially predict the immune response in BR and help guide the application of various immunotherapeutic drugs. Overall, the newly constructed CAGs risk signature presented a predictive value for the prognosis and tumor microenvironment of BR patients and can be further used in the guidance of immunotherapy for BR.

Induction mechanism of ferroptosis: A novel therapeutic target in lung disease

Ferroptosis is a newly discovered form of non-apoptotic regulatory cell death driven by iron-dependent lipid peroxidation. Ferroptosis significantly differs from other forms of cell death in terms of biochemistry, genetics, and morphology. Ferroptosis affects many metabolic processes in the body, resulting in disruption of homeostasis, and is related to many types of lung disease. Although current research on ferroptosis remains in the early stage, existing studies have confirmed that ferroptosis is regulated by a variety of genes, mainly involving changes in genes involved in iron homeostasis and lipid peroxidation metabolism. Furthermore, the mechanism of ferroptosis is complex. This review summarizes the confirmed mechanisms that can cause ferroptosis, including activation of glutathione peroxidase 4, synthesis of glutathione, accumulation of reactive oxygen species, and the influence of ferrous ions and p53 proteins. In recent years, the mechanism of ferroptosis in the occurrence and development of many diseases has been studied; the occurrence of ferroptosis will produce an inflammatory storm, and most of the inducing factors and pathological manifestations of lung diseases are also inflammatory reactions. Therefore, we believe that the association between ferroptosis and lung disease deserves further study. This article aims to help readers to better understand the mechanism of ferroptosis, provide new ideas and targets for the treatment of lung diseases, and point out the direction for the development of new targeted drugs for the clinical treatment of lung diseases.

Ferroptosis-related long non-coding RNA signature predicts the prognosis of hepatocellular carcinoma: A Review

INTRODUCTION

Hepatocellular carcinoma (HCC) is a liver cancer. In contrast, ferroptosis is a novel iron-dependent and ROS reliant type of cell death that is observed under various disease conditions.

METHODS AND ANALYSIS

RNA sequencing data from HCC patients were downloaded from The Cancer Genome Atlas (TCGA) database. Ferroptosis-related long non-coding RNAs (lncRNAs) were screened by Pearson correlation analysis. Patients were randomized into training or testing sets in a 1:1 ratio. They were constructed in the training set using univariate-Lasso and multivariate Cox regression analysis and further tested for prognostic values in the testing set. Four lncRNAs were identified. Kaplan-Meier analysis showed that patients in the high-risk group had a worse prognosis than those in the low-risk group. Following differentially expressed genes analysis of these two groups. Functional analysis showed association with oxidative stress response. Cox regression analyses showed that risk score was an independent prognostic indicator. Receiver operating characteristic curve (ROC) and decision curve analysis demonstrated the accuracy of prediction. Four ferroptosis-related lncRNAs based on differential expression of HCC were screened by bioinformatic methods to construct a prognostic risk model and accurately predict the prognosis of HCC patients. Four lncRNAs may have a potential role in the anti-tumor immune process and serve as therapeutic targets for HCC. To lay the foundation for subsequent studies.

Identification of cuproptosis-related subtypes, construction of a prognosis model, and tumor microenvironment landscape in gastric cancer

Introduction

Cuproptosis is a novel identified regulated cell death (RCD), which is correlated with the development, treatment response and prognosis of cancer. However, the potential role of cuproptosis-related genes (CRGs) in the tumor microenvironment (TME) of gastric cancer (GC) remains unknown.

Methods

Transcriptome profiling, somatic mutation, somatic copy number alteration and clinical data of GC samples were downloaded from the Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) database to describe the alterations of CRGs from genetic and transcriptional fields. Differential, survival and univariate cox regression analyses of CRGs were carried out to investigate the role of CRGs in GC. Cuproptosis molecular subtypes were identified by using consensus unsupervised clustering analysis based on the expression profiles of CRGs, and further analyzed by GO and KEGG gene set variation analyses (GSVA). Genes in distinct molecular subtypes were also analyzed by GO and KEGG gene enrichment analyses (GSEA). Differentially expressed genes (DEGs) were screened out from distinct molecular subtypes and further analyzed by GO enrichment analysis and univariate cox regression analysis. Consensus clustering analysis of prognostic DEGs was performed to identify genomic subtypes. Next, patients were randomly categorized into the training and testing group at a ratio of 1:1. CRG Risk scoring system was constructed through logistic least absolute shrinkage and selection operator (LASSO) cox regression analysis, univariate and multivariate cox analyses in the training group and validated in the testing and combined groups. Real-time quantitative polymerase chain reaction (RT-qPCR) was used to evaluate the expression of key Risk scoring genes. Sensitivity and specificity of Risk scoring system were examined by using receiver operating characteristic (ROC) curves. pRRophetic package in R was used to investigate the therapeutic effects of drugs in high- and low- risk score group. Finally, the nomogram scoring system was developed to predict patients' survival through incorporating the clinicopathological features and CRG Risk score.

Results

Most CRGs were up-regulated in tumor tissues and showed a relatively high mutation frequency. Survival and univariate cox regression analysis revealed that LIAS and FDX1 were significantly associated with GC patients' survival. After consensus unsupervised clustering analysis, GC patients were classified into two cuproptosis molecular subtypes, which were significantly associated with clinical features (gender, age, grade and TNM stage), prognosis, metabolic related pathways and immune cell infiltration in TME of GC. GO enrichment analyses of 84 DEGs, obtained from distinct molecular subtypes, revealed that DEGs primarily enriched in the regulation of metabolism and intracellular/extracellular structure in GC. Univariate cox regression analysis of 84 DEGs further screened out 32 prognostic DEGs. According to the expression profiles of 32 prognostic DEGs, patients were re-classified into two gene subtypes, which were significantly associated with patients' age, grade, T and N stage, and survival of patients. Nest, the Risk score system was constructed with moderate sensitivity and specificity. A high CRG Risk score, characterized by decreased microsatellite instability-high (MSI-H), tumor mutation burden (TMB) and cancer stem cell (CSC) index, and high stromal and immune score in TME, indicated poor survival. Four of five key Risk scoring genes expression were dysregulated in tumor compared with normal samples. Moreover, CRG Risk score was greatly related with sensitivity of multiple drugs. Finally, we established a highly accurate nomogram for promoting the clinical applicability of the CRG Risk scoring system.

Discussion

Our comprehensive analysis of CRGs in GC demonstrated their potential roles in TME, clinicopathological features, and prognosis. These findings may improve our understanding of CRGs in GC and provide new perceptions for doctors to predict prognosis and develop more effective and personalized therapy strategies.

Identification of cuproptosis-related long non-coding ribonucleic acid signature as a novel prognosis model for colon cancer

Cuproptosis is a novel type of cell death that may play a vital role in preventing various types of cancer. Studies examining cuproptosis are limited, and the cuproptosis-related lncRNAs (long non-Coding ribonucleic acids) involved in the regulation of colon cancer remain unclear. This study aimed to identify the prognostic signature of cupronosis-related lncRNAs and explore their potential molecular functions in colon cancer. Data on the clinical correlation were obtained from The Cancer Genome Atlas (TCGA) database. The differentially expressed cuproptosis-related long non-coding ribonucleic acids (lncRNAs) were analyzed using the "limma" package. Then, the prognostic cuproptosis-related lncRNA signature (CupRLSig) was identified through univariate Cox and co-expression analyses, and a prognostic model was constructed based on CupRLSig using the least absolute shrinkage selection operator (LASSO) algorithm and Cox regression analysis. The Kaplan-Meier survival curve and receiver operating characteristic (ROC) curve were used for evaluating the model's capacity for prognosis prediction. In addition, the immune landscape, and drug sensitivity of CupRLSig were analyzed. Finally, the functions of AL512306.3 and ZEB1-AS1 were verified through in vitro experiments. The high- or low-risk groups were classified according to the risk score. The signature-based risk score showed a stronger ability to predict patient's survival compared with the traditional clinicopathological features. In addition, immune responses, such as inflammation-promoting response and T-cell co-inhibition, were significantly different between the two groups. Moreover, chemotherapy drugs or inhibitors, such as axitinib, cisplatin, doxorubicin, and elesclomol, may be considered as potential therapeutic drugs for patients in high-risk groups. Finally, inhibition of AL512306.3 and ZEB1-AS1 significantly suppressed the cell proliferation in colon cancer cells. These results provide novel insights into the pathogenesis of colon cancer and offer promising biomarkers with the potential to guide research on carcinogenesis and cancer treatment.

Immunometabolism in the tumor microenvironment and its related research progress

The tumor immune microenvironment has been a research hot spot in recent years. The cytokines and metabolites in the microenvironment can promote the occurrence and development of tumor in various ways and help tumor cells get rid of the surveillance of the immune system and complete immune escape. Many studies have shown that the existence of tumor microenvironment is an important reason for the failure of immunotherapy. The impact of the tumor microenvironment on tumor is a systematic study. The current research on this aspect may be only the tip of the iceberg, and a relative lack of integrity, may be related to the heterogeneity of tumor. This review mainly discusses the current status of glucose metabolism and lipid metabolism in the tumor microenvironment, including the phenotype of glucose metabolism and lipid metabolism in the microenvironment; the effects of these metabolic methods and their metabolites on three important immune cells Impact: regulatory T cells (Tregs), tumor-associated macrophages (TAM), natural killer cells (NK cells); and the impact of metabolism in the targeted microenvironment on immunotherapy. At the end of this article,the potential relationship between Ferroptosis and the tumor microenvironment in recent years is also briefly described.

Iron metabolism, ferroptosis, and lncRNA in cancer: knowns and unknowns

Cancer cells undergo substantial metabolic alterations to sustain increased energy supply and uncontrolled proliferation. As an essential trace element, iron is vital for many biological processes. Evidence has revealed that cancer cells deploy various mechanisms to elevate the cellular iron concentration to accelerate proliferation. Ferroptosis, a form of cell death caused by iron-catalyzed excessive peroxidation of polyunsaturated fatty acids (PUFAs), is a promising therapeutic target for therapy-resistant cancers. Previous studies have reported that long noncoding RNA (lncRNA) is a group of critical regulators involved in modulating cell metabolism, proliferation, apoptosis, and ferroptosis. In this review, we summarize the associations among iron metabolism, ferroptosis, and ferroptosis-related lncRNA in tumorigenesis. This information will help deepen understanding of the role of lncRNA in iron metabolism and raise the possibility of targeting lncRNA and ferroptosis in cancer combination therapy.

Characterization of peripheral white blood cells transcriptome to unravel the regulatory signatures of bovine subclinical mastitis resistance

Subclinical bovine mastitis is a pathogenic infection of the breast characterized by a marked decrease in milk production and quality. As it has no obvious clinical symptoms, diagnosis and treatment are challenging. Therefore, searching for biomarkers in cows’ peripheral white blood cells is valuable for preventing and treating subclinical mastitis. Thus, in this study, the transcriptome of peripheral blood from healthy and subclinical mastitis cows was characterized to find the regulatory signatures of bovine subclinical mastitis using RNA-seq. A total of 287 differentially expressed genes (DEGs) and 70 differentially expressed lncRNAs (DELs) were detected, and 37 DELs were documented near known Quantitative Trait Loci (QTL) associated with the mastitis of cows. Bioinformatic analysis indicated that lncRNAs MSTRG25101.2, MSTRG.56327.1, and MSTRG.18968.1, which are adjacent to the SCS QTL and SCC QTL, may be candidate lncRNAs that influence the pathogenesis of mastitis in cows by up-regulating the expression of genes TLR4, NOD2, CXCL8, and OAS2. Moreover, the alternative splicing (AS) pattern of transcriptional sequence differences between healthy cows and subclinical mastitis cows suggested a molecular mechanism of mastitis resistance and susceptibility. A total of 2,212 differential alternative splicing (DAS) events, corresponding to 1,621 unique DAS genes, were identified in both groups and significantly enriched in immune and inflammatory pathways. Of these, 29 DAS genes were subject to regulation by 32 alternative splicing SNPs, showing diverse and specific splicing patterns and events. It is hypothesized that the PIK3C2B and PPRPF8 splice variants associated with AS SNPs (rs42705933 and rs133847062) may be risk factors for susceptibility to bovine subclinical mastitis. Altogether, these key blood markers associated with resistance to subclinical mastitis and SNPs associated with alternative splicing of genes provide the basis for genetic breeding for resistance to subclinical mastitis in cows.

Cooperation effects of radiation and ferroptosis on tumor suppression and radiation injury

Ferroptosis is a kind of oxidative stress-dependent cell death characterized by iron accumulation and lipid peroxidation. It can work in conjunction with radiation to increase reactive oxygen species (ROS) generation and disrupt the antioxidant system, suppressing tumor progression. Radiation can induce ferroptosis by creating ROS, depleting glutathione, activating genes linked to DNA damage and increasing the expression of acyl-CoA synthetase long-chain family member 4 (ACSL4) in tumor cells. Furthermore, ferroptosis can enhance radiosensitivity by causing an iron overload, destruction of the antioxidant system, and lipid peroxidation. Radiation can also cause ferroptosis in normal cells, resulting in radiation injury. The role of ferroptosis in radiation-induced lung, intestinal, skin, and hematological injuries have been studied. In this review, we summarize the potential mechanisms linking ferroptosis, oxidative stress and radiation; analyze the function of ferroptosis in tumor suppression and radiation injury; and discuss the potential of ferroptosis regulation to improve radiotherapy efficacy and reduce adverse effects.

m6A-Related lncRNAs Predict Overall Survival of Patients and Regulate the Tumor Immune Microenvironment in Osteosarcoma

Background

m6A-related lncRNAs have demonstrated great potential tumor diagnostic and therapeutic targets. The goal of this work was to find m6A-regulated lncRNAs in osteosarcoma patients.

Method

The Cancer Genome Atlas (TCGA) database was used to retrieve RNA sequencing and medical information from osteosarcoma sufferers. The Pearson's correlation test was used to identify the m6A-related lncRNAs. A risk model was built using univariate and multivariable Cox regression analysis. Kaplan–Meier survival analysis and receiver functional requirements were used to assess the risk model's performance (ROC). By using the CIBERSORT method, the associations between the relative risks and different immune cell infiltration were investigated. Lastly, the bioactivities of high-risk and low-risk subgroups were investigated using Gene Set Enrichment Analysis (GSEA).

Result

A total of 531 m6A-related lncRNAs were obtained from TCGA. Seven lncRNAs have demonstrated prognostic values. A total of 88 OS patients were separated into cluster 1, cluster 2, and cluster 3. The overall survival rate of OS patients in cluster 3 was more favorable than that of those in cluster 1 and cluster 2. The average Stromal score was much higher in cluster 1 than in cluster 2 and cluster 3 (P < 0.05). The expression levels of lncRNAs used in the construction of the risk prediction model in the high-risk group were generally lower than those in the low-risk group. Analysis of patient survival indicated that the survival of the low-risk group was higher than that of the high-risk group (P < 0.0001) and the area under the curve (AUC) of the ROC curve was 0.719. Using the CIBERSORT algorithm, the results revealed that Macrophages M0, Macrophages M2, and T cells CD4 memory resting accounted for a large proportion of immune cell infiltration. By GSEA analysis, our results implied that the high-risk group was mainly involved in unfolded protein response, DNA repair signaling, and epithelial-mesenchymal transition signaling pathway and glycolysis pathway; meanwhile, the low-risk group was mainly involved in estrogen response early and KRAS signaling pathway.

Conclusion

Our investigation showed that m6A-related lncRNAs remained tightly connected to the immunological microenvironment of osteosarcoma tumors, potentially influencing carcinogenesis and development. The immune microenvironment and immune-related biochemical pathways can be changed by regulating the transcription of M6A modulators or lncRNAs. In addition, we looked for risk-related signaling of m6A-related lncRNAs in osteosarcomas and built and validated the risk prediction system. The findings of our current analysis will facilitate the assessment of outcomes and the development of immunotherapies for sufferers of osteosarcomas.

Inhibition of cell survival and invasion by Tanshinone IIA via FTH1: A key therapeutic target and biomarker in head and neck squamous cell carcinoma

Head and neck squamous cell carcinoma (HNSCC) is a worldwide public health problem; its incidence is increasing and it is now the sixth most common cancer type worldwide. As indicated by existing studies, ferroptosis contributes to HNSCC progression and Tanshinone IIA (TanIIA) may exert therapeutic effects via affecting ferroptosis. However, the underlying mechanisms have remained to be clarified. Therefore, the main aim of the present study was to screen and investigate the key genes in regulating ferroptosis of the human hypopharynx squamous carcinoma cell line FaDu and further elucidate the mechanism of action of TanIIA. A list of ferroptosis-related genes was obtained from the FerrDb database. RNA-sequencing expression (level 3) profiles and corresponding clinical information (cases, n=502; normal controls, n=44) were downloaded from The Cancer Genome Atlas dataset for HNSCC (https://portal.gdc.com). The limma package in R software was used to study the differentially expressed mRNAs. Adjusted P<0.05 and Log2(fold change) >1 or <-1 were defined as the threshold for the differential expression of mRNAs. The ClusterProfiler package (version 3.18.0) in R was employed to analyze the Gene Ontology functional terms associated with potential targets and perform a Kyoto Encyclopedia of Genes and Genomes pathway analysis. The R package ggplot2 was used to draw the boxplot and the pheatmap package was used to draw the heatmap. The DEG-related protein-protein interaction network was built with the Search Tool for the Retrieval of Interacting Genes and proteins database and then the visualization was performed using Cytoscape. Ferritin heavy chain 1 (FTH1), transferrin (TF) and TF receptor were screened out using a Wayne diagram, which was drawn by the Venn Diagram package in R. Kaplan-Meier survival analysis and the log-rank test were used to compare differences in survival between the groups. The receiver operating characteristic (v 0.4) (ROC) curve analysis was used to compare the predictive accuracy of mRNAs. FTH1 was screened out and the expression results were verified using The Human Protein Atlas data. Immunohistochemistry and immunofluorescence were used to localize FTH1 expression in FaDu cells. Furthermore, Cell Counting Kit-8 and Transwell assays were used to detect the cell survival and invasion ability, respectively. Furthermore, western blot analysis was performed to analyze protein expression. The results of the present study indicated that three validated ferroptosis marker genes were differentially expressed in HNSCC, among which FTH1 was significantly associated with poorer survival. TanIIA was demonstrated to significantly affect FaDu cell survival and invasiveness and markedly attenuate FTH1 expression. To conclude, the ferroptosis gene FTH1 is highly expressed in HNSCC and TanIIA significantly inhibited HNSCC, partially by suppressing FTH1.

Ferroptosis-related lncRNA signature predicts prognosis and immunotherapy efficacy in cutaneous melanoma

Purpose

Ferroptosis-related lncRNAs are promising biomarkers for predicting the prognosis of many cancers. However, a ferroptosis-related signature to predict the prognosis of cutaneous melanoma (CM) has not been identified. The purpose of this study was to construct a ferroptosis-related lncRNA signature to predict prognosis and immunotherapy efficacy in CM.

Methods

Ferroptosis-related differentially expressed genes (FDEGs) and lncRNAs (FDELs) were identified using TCGA, GTEx, and FerrDb datasets. We performed Cox and LASSO regressions to identify key FDELs, and constructed a risk score to stratify patients into high- and low-risk groups. The lncRNA signature was evaluated using the areas under the receiver operating characteristic curves (AUCs) and Kaplan-Meier analyses in the training, testing, and entire cohorts. Multivariate Cox regression analyses including the lncRNA signature and common clinicopathological characteristics were performed to identify independent predictors of overall survival (OS). A nomogram was developed for clinical use. We performed gene set enrichment analyses (GSEA) to identify significantly enriched pathways. Differences in the tumor microenvironment (TME) between the 2 groups were assessed using 7 algorithms. To predict the efficacy of immune checkpoint inhibitors (ICI), we analyzed the association between PD1 and CTLA4 expression and the risk score. Finally, differences in Tumor Mutational Burden (TMB) and molecular drugs Sensitivity between the 2 groups were performed.

Results

We identified 5 lncRNAs (AATBC, AC145423.2, LINC01871, AC125807.2, and AC245041.1) to construct the risk score. The AUC of the lncRNA signature was 0.743 in the training cohort and was validated in the testing and entire cohorts. Kaplan-Meier analyses revealed that the high-risk group had poorer prognosis. Multivariate Cox regression showed that the lncRNA signature was an independent predictor of OS with higher accuracy than traditional clinicopathological features. The 1-, 3-, and 5-year survival probabilities for CM patients were 92.7%, 57.2%, and 40.2% with an AUC of 0.804, indicating a good accuracy and reliability of the nomogram. GSEA showed that the high-risk group had lower ferroptosis and immune response. TME analyses confirmed that the high-risk group had lower immune cell infiltration (e.g., CD8+ T cells, CD4+ memory-activated T cells, and M1 macrophages) and lower immune functions (e.g., immune checkpoint activation). Low-risk patients whose disease expressed PD1 or CTLA4 were likely to respond better to ICIs. The analysis demonstrated that the TMB had significantly difference between low- and high- risk groups. Chemotherapy drugs, such as sorafenib, Imatinib, ABT.888 (Veliparib), Docetaxel, and Paclitaxel showed Significant differences in the estimated IC50 between the two risk groups.

Conclusion

Our novel ferroptosis-related lncRNA signature was able to accurately predict the prognosis and ICI outcomes of CM patients. These ferroptosis-related lncRNAs might be potential biomarkers and therapeutic targets for CM.

Identification of Ferroptosis-Related lncRNA Pairs for Predicting the Prognosis of Head and Neck Squamous Cell Carcinoma

Background

Ferrogenesis was strongly associated with tumorigenesis and development, and activating the ferrogenic process was a novel regimen in treating cancer, especially conventional treatment-resistant cancers. The purpose of the article was to construct a ferroptosis-related long noncoding RNAs (FRlncRNAs) signature, regardless of expression levels to effectively predict prognosis and immunotherapeutic response for head and neck squamous cell carcinoma (HNSCC).

Methods

The RNA-seq data for HNSCC and corresponding clinical information were obtained in the TCGA database, and ferroptosis-related genes (FRGs) were extracted in the ferroptosis database. On this basis, differentially expressed FRlncRNAs (DEFRlncRNAs) pairs were identified through coexpression analysis, differential expression analysis, and a fresh pairing algorithm. Then, a risk assessment model was established with univariate Cox, LASSO, and multivariate Cox regression analysis. Finally, we evaluated the model from various aspects, including survival status, clinicopathological characteristics, infiltration status of immune cells, immune functions, chemotherapeutic sensitivity, immune checkpoint inhibitors (ICIs)-related molecules, and N6-methyladenosine (m⁶A) mRNA status.

Result

We established a signature of 11-DEFRlncRNA pairs related to the prognosis of HNSCC that had AUC values above 0.75 in the one-, three-, and five-year ROC curves, underscoring the high susceptibility and specifiability of predicting HNSCC prognosis. Survival rates were remarkably higher for the low-risk patients than for the high-risk patients, and the signature was significantly correlated with survival, clinical, T, and N stages. Finally, immune cell infiltration status, immune functions, chemotherapeutic sensitivity, and expression levels of ICIs-related and m⁶A-related molecules were statistically different among different groups.

Conclusion

Our study established a novel lncRNA signature, which is independent of specific expression levels, could predict patient prognosis, and might have promising clinical applications in HNCSS.

Ferroptosis-Related lncRNA Signature Correlates with the Prognosis, Tumor Microenvironment, and Therapeutic Sensitivity of Esophageal Squamous Cell Carcinoma

Esophageal squamous cell carcinoma (ESCC) is the most prevalent form of esophageal cancer in China and is closely associated with malignant biological characteristics and poor survival. Ferroptosis is a newly discovered iron-dependent mode of cell death that plays an important role in the biological behavior of ESCC cells. The clinical significance of ferroptosis-related long noncoding RNAs (FRLs) in ESCC remains unknown and warrants further research. The current study obtained RNA sequencing profiles and corresponding clinical data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, and FRLs were obtained through coexpression analysis. Consensus clustering was employed to divide the subjects into clusters, and immune-associated pathways were identified by functional analysis. The current study observed significant differences in the enrichment scores of immune cells among different clusters. Patients from TCGA-ESCC database were designated as the training cohort. A ten-FRL prediction signature was established using the least absolute shrinkage and selection operator Cox regression model and validated using the GEO cohort and our own independent validation database. Real-time quantitative polymerase chain reaction was used to verify the expression of the ten FRLs, and the ssGSEA analysis was employed to evaluate their function. In addition, the IMvigor database was used to assess the predictive value of the signature in terms of immunotherapeutic responses. Multivariate Cox and stratification analyses revealed that the ten-FRL signature was an independent predictor of the overall survival (OS). Patients with ESCC in the high-risk group displayed worse survival, a characteristic tumor immune microenvironment, and low immunotherapeutic benefits compared to those in the low-risk group. Collectively, the risk model established in this study could serve as a promising predictor of prognosis and immunotherapeutic response in patients with ESCC.

A Novel Ferroptosis-Related LncRNA Pair Prognostic Signature Predicts Immune Landscapes and Treatment Responses for Gastric Cancer Patients

Background: The construction of ferroptosis-related lncRNA prognostic models in malignancies has been an intense area of research recently. However, most of the studies focused on the exact expression of lncRNAs and had limited application values. Herein, we aim to establish a novel prognostic model for gastric cancer (GC) patients and discuss its correlation with immune landscapes and treatment responses. Methods: The present study retrieved transcriptional data of GC patients from the Cancer Genome Atlas (TCGA) database. We identified differentially expressed ferroptosis-related lncRNAs between tumor and normal controls of GC samples. Based on a new method of cyclically single pairing, we constructed a 0 or 1 matrix of ferroptosis-related lncRNA pairs (FRLPs). A risk score signature consisting of 10 FRLPs was established using multi-step Cox regression analysis. Next, we performed a series of systematic analyses to investigate the association of the FRLP model and tumor microenvironment, biological function, and treatment responses. An alternative model to the FRLP risk score signature, the gene set score (GS) model was also constructed, which could represent the former when lncRNA expression was not available. Results: We established a novel prognostic signature of 10 ferroptosis-related lncRNA pairs. High-risk patients in our risk score model were characterized by high infiltration of immune cells, upregulated carcinogenic and stromal activities, and heightened sensitivity to a wide range of anti-tumor drugs, whereas low-risk patients were associated with better responses to methotrexate treatment and elevated immunotherapeutic sensitivity. The practicability of the FRLP risk score model was also validated in two independent microarray datasets downloaded from Gene Expression Omnibus (GEO) using the GS model. Finally, two online dynamic nomograms were built to enhance the clinical utility of the study. Conclusion: In this study, we developed a ferroptosis-related lncRNA pair-based risk score model that did not rely on the exact lncRNA expression level. This novel model might provide insights for the accurate prediction and comprehensive management for GC patients.

Non-coding RNAs and ferroptosis: potential implications for cancer therapy

Ferroptosis is a recently defined form of regulated cell death, which is biochemically and morphologically distinct from traditional forms of programmed cell death such as apoptosis or necrosis. It is driven by iron, reactive oxygen species, and phospholipids that are oxidatively damaged, ultimately resulting in mitochondrial damage and breakdown of membrane integrity. Numerous cellular signaling pathways and molecules are involved in the regulation of ferroptosis, including enzymes that control the cellular redox status. Alterations in the ferroptosis-regulating network can contribute to the development of various diseases, including cancer. Evidence suggests that ferroptosis is commonly suppressed in cancer cells, allowing them to survive and progress. However, cancer cells which are resistant to common chemotherapeutic drugs seem to be highly susceptible to ferroptosis inducers, highlighting the great potential of pharmacologic modulation of ferroptosis for cancer treatment. Non-coding RNAs (ncRNAs) are considered master regulators of various cellular processes, particularly in cancer where they have been implicated in all hallmarks of cancer. Recent work also demonstrated their involvement in the molecular control of ferroptosis. Hence, ncRNA-based therapeutics represent an exciting alternative to modulate ferroptosis for cancer therapy. This review summarizes the ncRNAs implicated in the regulation of ferroptosis in cancer and highlights their underlying molecular mechanisms in the light of potential therapeutic applications.

Identification of CD4+ Conventional T Cells-Related lncRNA Signature to Improve the Prediction of Prognosis and Immunotherapy Response in Breast Cancer

BACKGROUND

Breast cancer (BC) is one of the most common malignancies in women, and long non-coding RNAs (lncRNAs) are key regulators of its development. T cells can recognize and kill cancer cells, and CD4+ T conventional (Tconv) cells are the main orchestrators of cancer immune function. However, research on CD4+ Tconv-related lncRNAs (CD4TLAs) prognostic signature in patients with BC is still lacking.

METHOD

A TCGA database and a GEO database were used to collect the BC patients. Through LASSO Cox regression analysis CD4TLAs-related prognostic models were further constructed, and risk scores (RS) were generated and developed a nomogram based on CD4TLAs. The accuracy of this model was validated in randomized cohorts and different clinical subgroups. Gene set enrichment analysis (GSEA) was used to explore potential signature-based functions. The role of RS has been further explored in the tumor microenvironment (TME), immunotherapy, and chemotherapy.

RESULT

A prognostic model based on 16 CD4TLAs was identified. High-RS was significantly associated with a poorer prognosis. RS was shown to be an independent prognostic indicator in BC patients. The low-RS group had a significant expression of immune infiltrating cells and significantly enriched immune-related functional pathways. In addition, the results of immunotherapy prediction indicated that patients with low-RS were more sensitive to immunotherapy.

CONCLUSIONS

Our signature has potential predictive value for BC prognosis and immunotherapy response. The findings of this work have greatly increased our understanding of CD4TLA in BC.

Pan-Cancer Analyses Confirmed the Ferroptosis-Related Gene SLC7A11 as a Prognostic Biomarker for Cancer

Purpose

Ferroptosis is an iron-dependent and reactive oxygen species (ROS)-reliant form of cell death, exhibiting cellular, molecular, and gene-level characteristics distinct from those of necrosis, autophagy, apoptosis, and pyroptosis. Solute carrier family 7 member 11 (SLC7A11), which encodes a cystine/glutamate antiporter transmembrane protein, inhibits ferroptosis by importing cystine and promoting glutathione (GSH) biosynthesis and was found to be overexpressed in multiple human cancers. However, the specific role and underlying mechanism of SLC7A11 in cancers remains poorly characterized. This research aimed to identify the relationship between SLC7A11 expression and tumor microenvironment and visualize its prognostic value in pan-cancer.

Patients and Methods

Transcriptomic data for 6313 tumors and normal samples across 20 cancer types were acquired from The Cancer Genome Atlas (TCGA) database. Besides, we presented a novel bioinformatics pipeline that uncovered the impacts of SLC7A11 on cancer prognosis, tumor mutational burden (TMB), immune cell infiltration in tumor microenvironment, and drug responses. The Genotype-Tissue Expression (GTEx), cBioportal, TCGA and Connectivity Map (CMap) databases were used to explore the expression, genetic alterations, immune microenvironment, and drug responses of SLC7A11. A series of deconvolution algorithms, including EPIC, CIBERSORT and GSEA, were utilized for multidimensional analyses of the cancer transcriptomic data.

Results

SLC7A11 was found to be highly expressed in the 20 types of cancer, especially in solid tumors. Survival analysis uncovered that most cancer patients with up-regulated expression of SLC7A11 showed poor prognosis, suggesting that SLC7A11 is a potential oncogene in most cancer types. Furthermore, the expression level of SLC7A11 was confirmed to be associated with immune cell infiltration in tumor microenvironment, TMB, and drug responses. Gene set enrichment analysis (GESA) revealed that dysregulation of SLC7A11 was associated with metabolic and immunity-related signaling pathways in the cancers.

Conclusion

The comprehensive pan-cancer analyses identified SLC7A11 as an attractive biomarker for immune infiltration and poor prognosis in cancers, shedding new light on the therapeutics of cancers.

Identification and Validation of a Ferroptosis-Related Signature for Predicting Prognosis and Immune Microenvironment in Papillary Renal Cell Carcinoma

Objective

We aimed to explore the prognostic patterns of ferroptosis-related genes in papillary renal cell carcinoma (PRCC) and investigate the relationship between ferroptosis-related genes and PRCC tumor immune microenvironment.

Methods

We obtained the mRNA expression and corresponding clinical data of PRCC from the public tumor cancer genome atlas database (TCGA). The PRCC patients were randomly divided into two cohort, training cohort and verification cohort, respectively. Univariate Cox regression, LASSO Cox regression, multivariate Cox regression analysis were utilized to construct ferroptosis signature for PRCC patients. And then, risk prognostic model was established and verified. The correlation of ferroptosis-related signature with survival and immune microenvironment was systematically analyzed.

Results

A 4-genes ferroptosis signature (CDKN1A, MIOX, PSAT1, and RRM2) was constructed. Multivariate Cox regression assay indicates that the risk score of ferroptosis signature was an independent prognostic indicator (HR=1.391, p<0.001). The survival curve shows that the high-risk group has a poorer prognosis than the low-risk group (p<0.001). The risk prognostic model was established based on prognostic factors of clinical-stage, hemoglobin, and risk score. The time-dependent receiver operating characteristic curve (ROC) analysis proves the predictive capacity of the ferroptosis signature, the 3 years area under the curve (AUC) is 0.890, and the 5 years AUC is 0.733. Further analysis suggested that cell cycle, pentose phosphate pathway, P53 signaling pathway were significantly enriched in the high-risk group. The significantly different fractions of dendritic cells resting, macrophage cells, and T cells follicular helper were observed in risk groups.

Conclusion

This study implicates a ferroptosis signature which has a good predict capacity of the prognosis in PRCC patients. Ferroptosis-related genes may have a key role in the process of anti-tumor and serve as therapeutic targets for PRCC.

Identification of Ferroptosis-Related Biomarkers for Prognosis and Immunotherapy in Patients With Glioma

Ferroptosis is a novel type of iron- and ROS-dependent cell death and is involved in various diseases. LncRNAs are involved and play important roles in the occurrence and development of several cancers. However, researches about the role of ferroptosis-related lncRNAs in glioma are relatively rare. Here, we identified nine ferroptosis-related lncRNAs and then constructed a prognostic model by the LASSO and Cox analysis. The model could predict overall survival with high sensitivity and specificity according to ROC curves. In addition, the cell cycle, p53 signaling, apoptosis, and oxidative phosphorylation pathways were obviously enriched in the pathogenesis of glioma by gene set enrichment analysis. A nomogram was constructed by integrating several independent prognostic clinicopathological features, and it could provide a valuable predictive tool for overall survival. Furthermore, a strong correlation between these nine lncRNAs and immunotherapy was found. Glioma patients in the high-risk group had higher TMB using somatic mutation data, different immune infiltration, and higher expression of immune checkpoints, indicating these patients might benefit from immune checkpoint inhibitor therapy. In summary, these nine ferroptosis-related lncRNAs were promising biomarkers for predicting overall survival and guiding immunotherapy or future immune checkpoint inhibitor development for glioma patients.

Integrated Analysis of RNA Binding Protein-Related lncRNA Prognostic Signature for Breast Cancer Patients

Long non-coding RNAs (lncRNAs) have been well known for their multiple functions in the tumorigenesis, development, and prognosis of breast cancer (BC). Mechanistically, their production, function, or stability can be regulated by RNA binding proteins (RBPs), which were also involved in the carcinogenesis and progression of BC. However, the roles and clinical implications of RBP-related lncRNAs in BC remain largely unknown. Therefore, we herein aim to construct a prognostic signature with RBP-relevant lncRNAs for the prognostic evaluation of BC patients. Firstly, based on the RNA sequencing data of female BC patients from The Cancer Genome Atlas (TCGA) database, we screened out 377 differentially expressed lncRNAs related to RBPs. The univariate, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analyses were then performed to establish a prognostic signature composed of 12-RBP-related lncRNAs. Furthermore, we divided the BC patients into high- and low-risk groups by the prognostic signature and found the overall survival (OS) of patients in the high-risk group was significantly shorter than that of the low-risk group. Moreover, the 12-lncRNA signature exhibited independence in evaluating the prognosis of BC patients. Additionally, a functional enrichment analysis revealed that the prognostic signature was associated with some cancer-relevant pathways, including cell cycle and immunity. In summary, our 12-lncRNA signature may provide a theoretical reference for the prognostic evaluation or clinical treatment of BC patients.

Construction of a Ferroptosis-Related Gene Signature for Head and Neck Squamous Cell Carcinoma Prognosis Prediction

Background

Head and neck squamous cell carcinoma (HNSCC) is one of the most common malignant cancers, and few studies have demonstrated the value of ferroptosis-related genes in prognosis.

Methods

The original counts of RNA sequencing data and clinicopathological data were obtained from TCGA and GSE65858 datasets. Common ferroptosis-related genes related to prognosis were identified from the training set and were included in LASSO to determine the best prognosis. To evaluate the efficacy, time-dependent ROC and Kaplan–Meier (KM) survival analyses were applied. Moreover, univariate and multivariate Cox regression analyses were used to screen independent parameters of prognosis and build a nomogram. Eventually, possible biological pathways were proposed based on GSEA.

Results

Among 242 ferroptosis-related genes, we identified that the FLT3, IL6, Keap1, NQO1, SOCS1 and TRIB3 genes were significantly connected with HNSCC patient prognosis as a six-gene signature. After, the patients were divided into high- and low-risk groups based on the six-gene signature. The KM survival curves demonstrated that the high-risk group had worse OS (p < 0.0001) and higher AUC values (0.654, 0.735, and 0.679 for 1-, 3-, and 5-year survival, respectively) for the prognostic signature of the six genes compared with other genes, which were also validated in the GSE65858 dataset. Moreover, GSEA suggested that the epithelial mesenchymal transition pathway was abundant and that the mesenchymal status in the high-risk group was substantially higher than that in the low-risk group. Finally, the immune microenvironment and differences in the content of immune cell types were demonstrated.

Conclusion

We established a six-ferroptosis-related-gene model crossing clinical prognostic parameters that can predict HNSCC patient prognosis and provide a reliable prognostic evaluation tool to assist clinical treatment decisions.

Expression of Ferroptosis-Related Genes is Correlated with Immune Microenvironment in Diabetic Kidney Disease

OBJECTIVE

This study aims to explore the correlation between ferroptosis and immune microenvironment (IME) in diabetic kidney disease (DKD) to provide a new clue for exploring the underlying molecular mechanisms.

METHODS

Corresponding RNA data of DKD patients were downloaded from GEO databases. The weighted gene co-expression network analysis (WGCNA) was used to construct the network, and the selected hub genes, then, overlapped with ferroptosis-related genes (FRGs) from FerrDb. Consensus clustering was performed to identify new molecular subgroups. ESTIMATE, TIMER and ssGSEA analyses were applied to determinate the IME and immune status. Functional analyses including GO, KEGG and GSEA were conducted to elucidate the underlying mechanisms.

RESULTS

Two molecular subtypes were identified based on the expression of FRGs. ESTIMATE algorithm revealed that there were significant differences in ESTIMATE score between these two clusters of DKD patients, with no significant difference found in stromal score and immune score. In addition, TIMER algorithm indicated there was a significant difference in the degree of T cell infiltration. The ssGSEA algorithm showed immunity was mainly concentrated in thick ascending limb and distal convoluted tubule in adult kidney. GO, KEGG and GSEA analyses revealed that the differentially expressed genes (DEGs) were mainly enriched in immune and metabolism associated pathways.

CONCLUSION

The ferroptosis may be induced by dysregulation of IME, thereby accelerating the progression of DKD. Our work could be applied to provide a new clue for exploring the underlying molecular mechanisms and sheds novel light on the therapy strategy of DKD.

Prognostic Model Construction and Immune Microenvironment Analysis of Breast Cancer Based on Ferroptosis-Related lncRNAs

Purpose

To construct a prognostic model of breast cancer using ferroptosis-related lncRNAs and explore novel therapeutic targets.

Materials and Methods

A prognostic characteristic model based on differential expression of ferroptosis-related lncRNAs in breast cancer was established based on TCGA data.

Results

Eleven ferroptosis-related lncRNAs associated with breast cancer prognosis were identified. Kaplan–Meier analysis suggested that high-risk lncRNA signatures correspond to a poor prognosis. The AUC of the signature lncRNAs was 0.682, demonstrating that it is accurate in predicting BC prognosis. GSEA showed that ferroptosis-related lncRNAs in high-risk individuals are mainly enriched in cell cycle, cell adhesion and tumor pathways. Immunity and gene expression analysis revealed that APC co-inhibition, check-point, HLA, inflammation-promoting and T cell co-stimulation among others were significantly different between the high-and low-risk group. Three immune checkpoints were highly expressed in the high-risk group.

Conclusion

Ferroptosis-related lncRNAs can be used as a prognostic feature to construct a prognostic model of breast cancer, based on which early detection markers, therapeutic targets and anti-tumor immune microenvironment can be studied, and clinical treatment can also be instructive.

Construction and validation of a risk scoring model for diffuse large B-cell lymphoma based on ferroptosis-related genes and its association with immune infiltration

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Categorization of DLBCL into four clusters based on survival- and ferroptosis-related factors.

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Establishment of an efficient risk scoring model is established for patients with DLBCL.

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Ferroptosis-based risk scoring model reveals immune infiltration correlation in DLBCL.

Backgrounds

The prognostic significance of ferroptosis-related genes is well known. However, survival- and ferroptosis-related genes are not currently considered in risk scoring models for diffuse large B-cell lymphoma (DLBCL).

Materials and methods

Ferroptosis regulators and markers were downloaded from the FerrDb database. The transcriptome profiling data were collected from the cancer genome atlas (TCGA). Transcriptome data and corresponding clinical information of DLBCL were downloaded from the gene expression omnibus (GEO). The validation data were downloaded using the UCSC Xena browser. ConsensusClusterPlus was used to categorize DLBCL samples according to gene expression profiles. The survival function was plotted with the Kaplan-Meier plots. The nomogram was built using multivariate logistic regression analysis and the Cox proportional hazards regression model.

Results

Based on the GSE11318 dataset of 203 samples and 267 ferroptosis-related gene expression profiles, we identified four clusters. A total of 19 survival-related genes were found associated with ferroptosis. The prognostic risk scoring model was constructed based on the regression coefficients. The obtained area under the receiver operating characteristic curve (AUC) values were 0.769, 0.801, and 0.791 for 1-, 3-, and 5-year survival, respectively. DLBCL samples with cluster 2 or cancer stage IV have shorter survival. Correlations between the immune infiltration and risk scores of the 12 immune cells were demonstrated. The response of DLBCL to doxorubicin was effectively validated by the risk scoring model.

Conclusions

In this study, a ferroptosis-based risk scoring model for patients with DLBCL was constructed and validated in an independent dataset. This risk score model has a better efficacy in predicting survival compared to clinical characteristics.

Identification of a N6-Methyladenosine (m6A)-Related lncRNA Signature for Predicting the Prognosis and Immune Landscape of Lung Squamous Cell Carcinoma

Background

m6A-related lncRNAs emerged as potential targets for tumor diagnosis and treatment. This study aimed to identify m6A-regulated lncRNAs in lung squamous cell carcinoma (LUSC) patients.

Materials and Methods

RNA sequencing and the clinical data of LUSC patients were downloaded from The Cancer Genome Atlas (TCGA) database. The m6A-related lncRNAs were identified by using Pearson correlation assay. Univariate and multivariate Cox regression analyses were utilized to construct a risk model. The performance of the risk model was validated using Kaplan–Meier survival analysis and receiver operating characteristics (ROC). Immune estimation of LUSC was downloaded from TIMER, and the correlations between the risk score and various immune cells infiltration were analyzed using various methods. Differences in immune functions and expression of immune checkpoint inhibitors and m6A regulators between high-risk and low-risk groups were further explored. Finally, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were utilized to explore the biological functions of AL122125.1.

Results

A total of 351 m6A-related lncRNAs were obtained from TCGA. Seven lncRNAs demonstrated prognostic values. A further multivariate Cox regression assay constructed a risk model consisting of two lncRNAs (AL122125.1 and HORMAD2-AS1). The Kaplan–Meier analysis and area under the curve indicated that this risk model could be used to predict the prognosis of LUSC patients. The m6A-related lncRNAs were immune-associated. There were significant correlations between risk score and immune cell infiltration, immune functions, and expression of immune checkpoint inhibitors. Meanwhile, there were significant differences in the expression of m6A regulators between the high- and low-risk groups. Moreover, GO and KEGG analyses revealed that the upregulated expression of AL122125.1 was tumor-related.

Conclusion

In this study, we constructed an m6A-related lncRNA risk model to predict the survival of LUSC patients. This study could provide a novel insight to the prognosis and treatment of LUSC patients.

Pre-Clinical Insights into the Iron and Breast Cancer Hypothesis

Population studies, systematic reviews, and meta-analyses have revealed no relationship between iron status and breast cancer, a weak positive association, or a small protective effect of low iron status. However, in those studies, the authors concluded that further investigation was merited. The set of experiments reported here used preclinical models to assess the likely value of further investigation. The effects of iron status on the initiation and promotion stage of mammary carcinogenesis are reported. Using the classical model of cancer initiation in the mammary gland, 7,12 dimethyl-benz[α]anthracene-induced carcinogenesis was unaffected by iron status. Similarly, excess iron intake showed no effect on the promotion stage of 1-methyl-1-nitrosurea-induced mammary carcinogenesis, though iron deficiency exerted a specific inhibitory effect on the carcinogenic process. Though iron-mediated cellular oxidation is frequently cited as a potential mechanism for effects on breast cancer, no evidence of increased oxidative damage to DNA attributable to excess iron intake was found. The reported preclinical data fail to provide convincing evidence that the further evaluation of the iron–breast cancer risk hypotheses is warranted and underscore the value of redefining the referent group in population-based studies of iron–cancer hypotheses in other tissues.

The Ferroptosis-Related Noncoding RNA Signature as a Novel Prognostic Biomarker in the Tumor Microenvironment, Immunotherapy, and Drug Screening of Gastric Adenocarcinoma

BACKGROUND

Ferroptosis is a new type of cell death different from apoptosis, necrosis, autophagy, and pyroptosis. This study aimed to explore the relationship between ferroptosis-related noncoding RNA (ncRNA) and gastric adenocarcinoma with regard to immunity and prognosis.

METHODS

Ferroptosis-related ncRNA expression profiles and clinical pathology and overall survival information were collected from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus database. The ferroptosis-related ncRNA signature was identified by Cox regression analysis and the least absolute shrinkage and selection operator analysis. The survival analysis, receiver operating characteristic (ROC) analysis, and decision curve analysis were adopted to evaluate the prognostic prediction performance of the signature. The correlation between risk and multiple clinical characteristics was analyzed using the chi-square test. The Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and gene set enrichment analysis were used for mining functions and pathways. The CIBERSORT, ssGSEA, and ESTIMATE algorithms were used to assess immune infiltration and the tumor microenvironment. The response of immunotherapy was predicted using the Submap algorithm, and the Connectivity Map and the ridge regression model were used to screen and evaluate drugs.

RESULTS

A carcinogenic risk signature was constructed using five ferroptosis-related ncRNAs. It showed an extraordinary ability to predict the prognoses of patients with gastric adenocarcinoma [area under the ROC curve (AUC) after 6 years = 0.689; GSE84426, AUC after 6 years = 0.747]. The lower ferroptosis potential level and lower tumor mutation burden were related to the poor prognoses of patients. The high-risk group had more immune cell recruitment, and the overall effect of the anti-immune checkpoint immunotherapy was not as good as that of the low-risk group. The high- and low-risk groups were enriched in tumor- and immune-related pathways, respectively. The screened antitumor drugs, such as genistein, guanabenz, and betulinic acid, improved the survival of the patients.

CONCLUSIONS

The ferroptosis-related ncRNA signature is a potential carcinogenic prognostic biomarker of gastric adenocarcinoma.

Comprehensive Analysis of Ferroptosis-Related LncRNAs in Breast Cancer Patients Reveals Prognostic Value and Relationship With Tumor Immune Microenvironment

Background: Breast cancer (BC) is a heterogeneous malignant tumor, leading to the second major cause of female mortality. This study aimed to establish an in-depth relationship between ferroptosis-related LncRNA (FRlncRNA) and the prognosis as well as immune microenvironment of the patients with BC. Methods: We downloaded and integrated the gene expression data and the clinical information of the patients with BC from The Cancer Genome Atlas (TCGA) database. The co-expression network analysis and univariate Cox regression analysis were performed to screen out the FRlncRNAs related to prognosis. A cluster analysis was adopted to explore the difference of immune microenvironment between the clusters. Furthermore, we determined the optimal survival-related FRLncRNAs for final signature by LASSO Cox regression analysis. Afterward, we constructed and validated the prediction models, which were further tested in different subgroups. Results: A total of 31 FRLncRNAs were filtrated as prognostic biomarkers. Two clusters were determined, and C1 showed better prognosis and higher infiltration level of immune cells, such as B cells naive, plasma cells, T cells CD8, and T cells CD4 memory activated. However, there were no significantly different clinical characters between the clusters. Gene Set Enrichment Analysis (GSEA) revealed that some metabolism-related pathways and immune-associated pathways were exposed. In addition, 12 FRLncRNAs were determined by LASSO analysis and used to construct a prognostic signature. In both the training and testing sets, patients in the high-risk group had a worse survival than the low-risk patients. The area under the curves (AUCs) of receiver operator characteristic (ROC) curves were about 0.700, showing positive prognostic capacity. More notably, through the comprehensive analysis of heatmap, we regarded LINC01871, LINC02384, LIPE-AS1, and HSD11B1-AS1 as protective LncRNAs, while LINC00393, AC121247.2, AC010655.2, LINC01419, PTPRD-AS1, AC099329.2, OTUD6B-AS1, and LINC02266 were classified as risk LncRNAs. At the same time, the patients in the low-risk groups were more likely to be assigned to C1 and had a higher immune score, which were consistent with a better prognosis. Conclusion: Our research indicated that the ferroptosis-related prognostic signature could be used as novel biomarkers for predicting the prognosis of BC. The differences in the immune microenvironment exhibited by BC patients with different risks and clusters suggested that there may be a complementary synergistic effect between ferroptosis and immunotherapy.

Identification of Key lncRNA-mRNA Pairs and Functional lncRNAs in Breast Cancer by Integrative Analysis of TCGA Data

Long non-coding RNAs (lncRNAs) play an important role in many diseases and are involved in the post-transcriptional regulatory network of tumors. The purpose of this study is to mine new lncRNA–mRNA regulatory pairs and analyze the new mechanism of lncRNA involvement in breast cancer progression. Using breast cancer miRNA and mRNA expression profiling from The Cancer Genome Atlas (TCGA), we identified 59 differentially expressed lncRNAs, 88 differentially expressed miRNAs, and 1,465 differentially expressed mRNAs between breast cancer tissue and adjacent normal breast cancer. Whereafter, four candidate lncRNAs (FGF14-AS2, LINC01235, AC055854.1, and AC124798.1) were identified by the Kaplan–Meier (K–M) plotter. Furthermore, we screened the hub lncRNA (LINC01235) through univariate Cox analysis, multivariate Cox analysis, and qPCR validation, which was significantly correlated with breast cancer stage, ER status, and pathological N. Subsequently, 107 LINC01235-related mRNAs were obtained by combining differentially expressed miRNAs, differentially expressed mRNAs, and LINC01235 targeting miRNAs and mRNAs. The protein–protein interaction (PPI) network was established by Cytoscape software, and 53 key genes were screened. Function and pathway enrichment showed that LINC01235-related key genes might be involved in the process of cell differentiation, cell proliferation, and p53 signal pathway. In addition, LINC01235 has been confirmed to regulate the proliferation, migration, and invasion of MCF-7 cells in in vitro experiments. Furthermore, we screened three mRNAs (ESR1, ADRA2A, and DTL) associated with breast cancer drug resistance from key genes. Through RNA interference experiments in vitro and correlation analysis, we found that there was a negative feedback mechanism between LINC01235 and ESR1/ADRA2A. In conclusion, our results suggest that LINC01235-ESR1 and LINC01235-ADRA2A could serve as important co-expression pairs in the progression of breast cancer, and LINC01235 plays a key role as an independent prognostic factor in patients with breast cancer. The findings of this work greatly increase our understanding of the molecular regulatory mechanisms of lncRNA in breast cancer.