A Novel Ferroptosis-Related Gene Signature for Overall Survival Prediction in Patients With Breast Cancer

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.

TR-107, an Agonist of Caseinolytic Peptidase Proteolytic Subunit, Disrupts Mitochondrial Metabolism and Inhibits the Growth of Human Colorectal Cancer Cells

Oxidative phosphorylation is an essential metabolic process for cancer proliferation and therapy resistance. The ClpXP complex maintains mitochondrial proteostasis by degrading misfolded proteins. Madera Therapeutics has developed a class of highly potent and selective small-molecule activators (TR compounds) of the ClpXP component caseinolytic peptidase proteolytic subunit (ClpP). This approach to cancer therapy eliminates substrate recognition and activates nonspecific protease function within mitochondria, which has shown encouraging preclinical efficacy in multiple malignancies. The class-leading compound TR-107 has demonstrated significantly improved potency in ClpP affinity and activation and enhanced pharmacokinetic properties over the multitargeting clinical agent ONC201. In this study, we investigate the in vitro efficacy of TR-107 against human colorectal cancer cells. TR-107 inhibited colorectal cancer cell proliferation in a dose- and time-dependent manner and induced cell cycle arrest at low nanomolar concentrations. Mechanistically, TR-107 downregulated the expression of proteins involved in the mitochondrial unfolded protein response and mitochondrial DNA transcription and translation. TR-107 attenuated oxygen consumption rate and glycolytic compensation, confirming inactivation of oxidative phosphorylation and a reduction in total cellular respiration. Multiomics analysis of treated cells indicated a downregulation of respiratory chain complex subunits and an upregulation of mitophagy and ferroptosis pathways. Further evaluation of ferroptosis revealed a depletion of antioxidant and iron toxicity defenses that could potentiate sensitivity to combinatory chemotherapeutics. Together, this study provides evidence and insight into the subcellular mechanisms employed by colorectal cancer cells in response to potent ClpP agonism. Our findings demonstrate a productive approach to disrupting mitochondrial metabolism, supporting the translational potential of TR-107.

Identification and Validation of a Necroptosis-Related Prognostic Model in Tumor Recurrence and Tumor Immune Microenvironment in Breast Cancer Management

Background

Breast cancer is the leading cause of cancer-related death in women. Necroptosis, a form of programmed necrotic cell death, occurs in many solid tumors, including breast cancer, and influences anti-tumor immunity. The role of necroptosis in managing breast cancer recurrence remains unclear.

Methods

Gene expression profiles and clinical data of breast cancer patients were obtained from the GEO (GSE20685, GSE21653, GSE25055) and TCGA databases. Data analysis and visualization were performed using R. Unsupervised Consensus Clustering and LASSO-COX regression stratified breast cancer patients. GO, KEGG, GSVA, ESTIMATE, and ROC analyses were used to investigate necroptotic signatures. In vitro and in vivo experiments validated necroptosis's role in breast cancer immunity.

Results

The potential function of necroptotic signature in immunity was first indicated with GO analysis in BRCA cohort. Next, two prognostic models based on the necroptotic profiles both suggested a link between low-risk group with a particular necroptotic immune signature. And a variety of immune cells and immune pathways were shown to be positively associated with a patient's risk score. As an altered immune checkpoint pattern was observed after regulating necroptotic genes, where TIM-3 and LAGLS9 elevated significantly in low-risk group, further validation in vitro and in vivo demonstrated that manipulating a subset of necroptotic gene set could sensitize tumor response to the co-blockade immunotherapy of anti-TIM-3 and anti-PD-1.

Conclusion

We demonstrated two strategies to stratify breast cancer patients based on their necroptotic profiles and showed that necroptotic signature could assign patients with different tumor immune microenvironment patterns and different recurrence-related prognosis. A subset of necroptotic gene set, composed of TLR3, RIPK3, NLRP3, CASP1, ALDH2 and EZH2, was identified as a biomarker set for predicting immunotherapy-response and recurrence-related prognosis. Targeting necroptosis could helpfacilitate the development of novel breast cancer treatments and tailor personalized medical treatment.

Amino acid transporters within the solute carrier superfamily: Underappreciated proteins and novel opportunities for cancer therapy

BACKGROUND

Solute carrier (SLC) transporters, a diverse family of membrane proteins, are instrumental in orchestrating the intake and efflux of nutrients including amino acids, vitamins, ions, nutrients, etc, across cell membranes. This dynamic process is critical for sustaining the metabolic demands of cancer cells, promoting their survival, proliferation, and adaptation to the tumor microenvironment (TME). Amino acids are fundamental building blocks of cells and play essential roles in protein synthesis, nutrient sensing, and oncogenic signaling pathways. As key transporters of amino acids, SLCs have emerged as crucial players in maintaining cellular amino acid homeostasis, and their dysregulation is implicated in various cancer types. Thus, understanding the intricate connections between amino acids, SLCs, and cancer is pivotal for unraveling novel therapeutic targets and strategies.

SCOPE OF REVIEW

In this review, we delve into the significant impact of amino acid carriers of the SLCs family on the growth and progression of cancer and explore the current state of knowledge in this field, shedding light on the molecular mechanisms that underlie these relationships and highlighting potential avenues for future research and clinical interventions.

MAJOR CONCLUSIONS

Amino acids transportation by SLCs plays a critical role in tumor progression. However, some studies revealed the tumor suppressor function of SLCs. Although several studies evaluated the function of SLC7A11 and SLC1A5, the role of some SLC proteins in cancer is not studied well. To exert their functions, SLCs mediate metabolic rewiring, regulate the maintenance of redox balance, affect main oncogenic pathways, regulate amino acids bioavailability within the TME, and alter the sensitivity of cancer cells to therapeutics. However, different therapeutic methods that prevent the function of SLCs were able to inhibit tumor progression. This comprehensive review provides insights into a rapidly evolving area of cancer biology by focusing on amino acids and their transporters within the SLC superfamily.

Analysis of the factors influencing moderate to poor performance status in patients with cancer after chemotherapy: a cross-sectional study comparing three models

There are no models for assessing the factors that determine moderate to poor performance status in patients with cancer after chemotherapy. This study investigated the influencing factors and identified the best model for predicting moderate-poor performance status. A convenience sampling method was used. Demographic and clinical data and evaluation results for fatigue, pain, quality of life and Eastern Cooperative Oncology Group status were collected three days after the end of chemotherapy. Decision tree, random forest and logistic regression models were constructed. Ninety-four subjects in the case group had moderate to poor performance status, and 365 subjects in the control group had no or mild activity disorders. The random forest model was the most accurate model. Physical function, total protein, general quality of life within one week before chemotherapy, hemoglobin, pain symptoms and globulin were the main factors. Total protein and hemoglobin levels reflect nutritional status, and globulin levels are an index of liver function. Therefore, physical function, nutritional status, general quality of life and pain symptoms within one week before chemotherapy and liver function can be used to predict moderate-poor performance status. Nurses should pay more attention to patients with poor physical function, poor nutritional status, lower quality of life and pain symptoms after chemotherapy.

Identification of TFR2 as a novel ferroptosis‑related gene that serves an important role in prognosis and progression of triple‑negative breast cancer

Effective targeted therapeutic strategies for triple-negative breast cancer (TNBC), the most malignant subtype of breast cancer, are currently lacking. Ferroptosis has been reported to be associated with the onset and advancement of various cancer types, including TNBC. However, there are limited studies on the correlation between TNBC and ferroptosis-related genes. In addition, the potential biomarkers of ferroptosis in TNBC need further investigation. The present study aimed to assess the prognostic role of a novel ferroptosis-related gene signature in the context of TNBC. The signature was established utilizing The Cancer Genome Atlas dataset. This three-gene model [transferrin receptor 2 (TFR2), regulator of G protein signaling 4 and zinc finger protein 36] was developed utilizing least absolute shrinkage and selection operator regression analysis and demonstrated satisfactory predictive performance in TNBC. The area under the curve values of the receiver operating characteristic curves in this model concerning the 1-, 2- and 3-year survival prediction were 0.721, 0.840 and 0.856, respectively. The predictive performance of the model was verified using the TNBC dataset GSE25307. Gene set enrichment analysis (GSEA) demonstrated the enrichment of genes in the low-risk group in a number of important metabolic pathways. Single-sample GSEA demonstrated a variation in the expression levels of immune checkpoint molecules between the high- and low-risk groups. The inhibitory impact of TFR2 knockdown on the proliferative capacity of TNBC cells was verified through in vitro experiments. The data also demonstrated that TFR2 knockdown facilitated the ferroptosis of TNBC cells. Additional assessments indicated that the effects of TFR2 knockdown were partially reversed upon treatment with the ferroptosis inhibitor ferrostatin-1. In conclusion, in the present study, a novel and accurate ferroptosis-related predictive signature was established for TNBC with potential future clinical applications. To the best of our knowledge, the present study is the first to report that TFR2 regulated ferroptosis in TNBC cells in vitro.

Identification of a novel five ferroptosis-related gene signature as a promising prognostic model for breast cancer

BACKGROUND

Breast cancer (BCa) is a major challenge for women's health worldwide. Ferroptosis is closely related to tumorigenesis and cancer progression. However, the prognostic value of ferroptosis-related genes in BCa remains unclear, and more accurate prognostic models are urgently needed.

METHODS

Gene expression profiles and clinical information of BCa patients were collected from public databases. LASSO and multivariate Cox regression analysis were utilized to construct the prognostic gene signature. Kaplan-Meier plotter, receiver operating characteristic (ROC) curves, and nomogram were used to validate the prognostic value of the gene signature. Gene set enrichment analysis was performed to explore the molecular functions and signaling pathways.

RESULTS

Differentially expressed ferroptosis-related genes between BCa samples and normal tissues were obtained. A novel five-gene signature including BCL2, SLC40A1, TFF1, APOOL, and PRAME was established for prognosis prediction. Patients stratified into high-risk or low-risk group displayed significantly different survival. Kaplan-Meier and ROC curves showed a good performance for survival prediction in different cohorts. Biological function analysis revealed that the five-gene signature was associated with cancer progression, immune infiltration, immune response, and drug resistance. Nomogram including the five-gene signature was established.

CONCLUSION

A novel five ferroptosis-related gene signature and nomogram could be used for prognostic prediction in BCa.

Identification of disulfidptosis-related subtypes, characterization of tumor microenvironment infiltration, and development of a prognosis model in breast cancer

Introduction

Breast cancer (BC) is now the most common type of cancer in women. Disulfidptosis is a new regulation of cell death (RCD). RCD dysregulation is causally linked to cancer. However, the comprehensive relationship between disulfidptosis and BC remains unknown. This study aimed to explore the predictive value of disulfidptosis-related genes (DRGs) in BC and their relationship with the TME.

Methods

This study obtained 11 disulfidptosis genes (DGs) from previous research by Gan et al. RNA sequencing data of BC were downloaded from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus database (GEO) databases. First, we examined the effect of DG gene mutations and copy number changes on the overall survival of breast cancer samples. We then used the expression profile data of 11 DGs and survival data for consensus clustering, and BC patients were divided into two clusters. Survival analysis, gene set variation analysis (GSVA) and ss GSEA were used to compare the differences between them. Subsequently, DRGs were identified between the clusters used to perform Cox regression and least absolute shrinkage and selection operator regression (LASSO) analyses to construct a prognosis model. Finally, the immune cell infiltration pattern, immunotherapy response, and drug sensitivity of the two subtypes were analyzed. CCK-8 and a colony assay obtained by knocking down genes and gene sequencing were used to validate the model.

Result

Two DG clusters were identified based on the expression of 11DGs. Then, 225 DRGs were identified between them. RS, composed of six genes, showed a significant relationship with survival, immune cell infiltration, clinical characteristics, immune checkpoints, immunotherapy response, and drug sensitivity. Low-RS shows a better prognosis and higher immunotherapy response than high-RS. A nomogram with perfect stability constructed using signature and clinical characteristics can predict the survival of each patient. CCK-8 and colony assay obtained by knocking down genes have demonstrated that the knockdown of high-risk genes in the RS model significantly inhibited cell proliferation.

Discussion

This study elucidates the potential relationship between disulfidptosis-related genes and breast cancer and provides new guidance for treating breast cancer.

The recent advancements of ferroptosis in the diagnosis, treatment and prognosis of ovarian cancer

Ovarian cancer affects the female reproductive system and is the primary cause of cancer related mortality globally. The imprecise and non-specific nature of ovarian cancer symptoms often results in patients being diagnosed at an advanced stage, with metastatic lesions extending beyond the ovary. This presents a significant clinical challenge and imposes a substantial economic burden on both patients and society. Despite advancements in surgery, chemotherapy, and immunotherapy, the prognosis for most patients with ovarian cancer remains unsatisfactory. Therefore, the development of novel treatment strategies is imperative. Ferroptosis, a distinct form of regulated cell death, characterized by iron-dependent lipid peroxidation, differs from autophagy, apoptosis, and necrosis, and may hold promise as a novel cell death. Numerous studies have demonstrated the involvement of ferroptosis in various conventional signaling pathways and biological processes. Recent investigations have revealed the significant contribution of ferroptosis in the initiation, progression, and metastasis of diverse malignant tumors, including ovarian cancer. Moreover, ferroptosis exhibits a synergistic effect with chemotherapy, radiotherapy, and immunotherapy in restraining the proliferation of ovarian cancer cells. The aforementioned implies that ferroptosis holds considerable importance in the management of ovarian cancer and has the potential to serve as a novel therapeutic target. The present review provides a comprehensive overview of the salient features of ferroptosis, encompassing its underlying mechanisms and functional role in ovarian cancer, along with the associated signaling pathways and genes. Furthermore, the review highlights the prospective utility of ferroptosis in the treatment of ovarian cancer.

Identification and verification of novel ferroptosis biomarkers predicts the prognosis of hepatocellular carcinoma

BACKGROUND

Big data mining and experiments are widely used to mine new prognostic markers.

METHODS

Candidate genes were identified from CROEMINE and FerrDb. Kaplan-Meier survival and Cox regression analysis were applied to assess the association of genes with Overall survival time (OS) and Disease-free survival time (DFS) in two HCC cohorts. Real-time quantitative polymerase chain reaction (RT-qPCR) and Immunohistochemistry were performed in HCC samples.

RESULTS

21 and 15 genes that can predict OS and DFS, which had not been reported before, were identified from 719 genes, respectively. Survival analysis showed elevated mRNA expression of GLMP, SLC38A6, and WDR76 were associated with poor prognosis, and three genes combination signature was an independent prognostic factor in HCC. RT-qPCR and Immunohistochemistry confirmed the results.

CONCLUSIONS

We established a novel computational process, which identified the expression levels of GLMP, SLC38A6, and WDR76 as potential ferroptosis-related biomarkers indicating the prognosis of HCC.

Identification of an exosome-related signature associated with prognosis and immune infiltration in breast cancer

Exosomes, nanosized vesicles, play a vital role in breast cancer (BC) occurrence, development, and drug resistance. Hence, we proceeded to study the potential prognostic value of exosome-related genes and their relationship to the immune microenvironment in BC. 121 exosome-related genes were provided by the ExoBCD database, and 7 final genes were selected to construct the prognostic signature. Besides, the expression levels of the 7 exosome-related genes were validated by the experiment in BC cell lines. Based on the signature, BC patients from the training and validation cohorts were separated into low- and high-risk groups. Subsequently, the R clusterProfiler package was applied to identify the distinct enrichment pathways between high-risk groups and low-risk groups. The relevance of the tumor immune microenvironment and exosome-related gene risk score were analyzed in BC. Eventually, the different expression levels of immune checkpoint-related genes were compared between the two risk groups. Based on the risk model, the low-risk groups were identified with a higher survival rate both in the training and validation cohorts. A better overall survival was revealed in patients with higher scores evaluated by the estimation of stromal and immune cells in malignant tumor tissues using expression (ESTIMATE) algorithm. Subsequently, BC patients with lower risk scores were indicated by higher expression levels of some immune checkpoint-related genes and immune cell infiltration. Exosomes are closely associated with the prognosis and immune cell infiltration of BC. These findings may contribute to improving immunotherapy and provide a new vision for BC treatment strategies.

Natural compound So-2 suppresses triple-negative breast cancer through inducing ferroptosis via downregulating transcription factor E2F7

Triple-negative breast cancer (TNBC), accounting for about 15∼18% of all breast cancers, is notorious for its poor prognosis, high rate of relapse and short overall survival. Because of lacking effective therapeutic targets or drugs, treatment of TNBC in clinical encounters great obstacle. Siegesbeckiaorientalis L. have been used as a traditional Chinese medicine "Xi-Xian-Cao" for centuries with multiple medicinal benefits including cancerous treatment. We have reported the isolation of twenty-seven germacranolides including So-2 from the aerial parts of S. orientalis with potent cytotoxicity against breast cancer cells. The studyaims to verified the anti-TNBC function of the natural compound So-2 both in vitro and vivo and uncover the underlying mechanism. The results showed that So-2 caused cell cycle arrest and suppress TNBC cell proliferation and migration. Also, So-2 was first identified to be a bona fide ferroptosis inducer in TNBC cells. So-2 effectively suppressed tumor growth of TNBC by using an orthotopic transplantation tumor model. We also characterized the oncogenic role of the transcription factor E2F7 in TNBC. E2F7 was demonstrated to be involved in the ferroptosis-inducing and tumor suppression effect of So-2. Altogether, So-2 exhibits inhibitory effect on TNBC both in vitro and vivo by inducing TNBC ferroptosis via downregulating the expression of E2F7. These findings provide valuable insight into the pathogenesis of TNBC. The natural compound So-2, isolated from Chinese traditional medicine, might be a prospective drug candidate in TNBC therapy.

Identification and Validation of a Novel Prognostic Signature Based on Ferroptosis-Related Genes in Ovarian Cancer

BACKGROUND

Ovarian cancer is the most lethal gynecological tumor, with a poor prognosis due to the lack of early symptoms, resistance to chemotherapy, and recurrence. Ferroptosis belongs to the regulated cell death family, and is characterized by iron-dependent processes. Here, comprehensive bioinformatics analysis was applied to explore a valuable prognostic model based on ferroptosis-related genes, which was further validated in clinical OC samples.

METHODS

mRNA data of normal and ovarian tumor samples were obtained separately from the GTEx and TCGA databases. The least absolute shrinkage and selection operator (LASSO) cox regression was applied to construct the prognostic model based on ferroptosis-associated genes. Expression of ALOX12 in OC cell lines, as well as cell functions, including proliferation and migration, were examined. Finally, the prognostic efficiency of the model was assessed in the clinical tissues of OC patients.

RESULTS

A gene signature consisting of ALOX12, RB1, DNAJB6, STEAP3, and SELENOS was constructed. The signature divided TCGA, ICGC, and GEO cohorts into high-risk and low-risk groups separately. Receiver operating characteristic (ROC) curves and independent prognostic factor analysis were carried out, and the prognostic efficacy was validated. The expression levels of ALOX12 in cell lines were examined. Inhibition of ALOX12 attenuated cell proliferation and migration in HEY cells. Moreover, the prognostic value of ALOX12 expression was examined in clinical samples of OC patients.

CONCLUSION

This work constructed a novel ferroptosis-associated gene model. Furthermore, the clinical predictive role of ALOX12 was identified in OC patients, suggesting that ALOX12 might act as a potential prognostic tool and therapeutic target for OC patients.

GAPDH Is a Novel Ferroptosis-Related Marker and Correlates with Immune Microenvironment in Lung Adenocarcinoma

Lung adenocarcinoma (LUAD) is a prevalent form of lung cancer with high morbidity and fatality rates. Ferroptosis is a type of programmed cell death that is iron-dependent. Recent findings have suggested that ferroptosis inducers have promising prospects for the therapy of LUAD. However, ferroptosis-related gene expression in LUAD and its relationship with the tumor prognosis and tumor immune microenvironment remain unknown. We identified a total of 638 ferroptosis-related genes, built a LUAD ferroptosis-related risk model (FRRM) with the help of Least Absolute Shrinkage Selection Operator (LASSO) regression analysis based on The Cancer Genome Atlas (TCGA) database, split LUAD patients into high- and low-risk clusters, and verified the model utilizing the Gene Expression Omnibus (GEO) database. The results of the FRRM's principal component analysis (PCA) demonstrated its strong predictive power. Further, univariate and multivariate Cox and AUC curve analyses demonstrated that the model was independent of other clinical traits and served as an independent prognostic factor. The nomogram demonstrated strong predictive power for overall survival, according to calibration plots. We also explored variations in clinical characteristics, immune cell infiltration, immune-related function, and functional pathways between the high- and low-risk groups. Additionally, we used a protein-protein interaction (PPI) network of various genes in the two groups to search for potential target genes. GAPDH was then chosen for a follow-up investigation. An analysis was performed on the relationship between GAPDH and variations in survival prognosis, clinical traits, immune cell infiltration, immune checkpoints, and immunotherapy. In vitro tests further supported the probable functions of GAPDH as a ferroptosis marker in LUAD. In conclusion, a novel ferroptosis-related prognostic gene, GAPDH, was discovered, whose expression was connected to the tumor immune microenvironment. The combination of immunotherapy and the targeting of GAPDH to induce ferroptosis in LUAD may provide a novel therapeutical option.

A five ferroptosis-related genes risk score for prognostic prediction of osteosarcoma

BACKGROUND

Osteosarcoma (OS) is the most common bone cancer in adolescents, and has a high propensity to metastasize. Ferroptosis is a unique modality of cell death, driving the metastasis of cancer cells. Identifying ferroptosis-related genes (FRGs) as prognostic factors will be critical to predict the outcomes of OS. This study aimed to explore the prognostic value of FRGs in OS and build a prognostic model to indirectly improve OS patients' outcomes.

METHODS

OS data were downloaded from the TARGET database and 2 Gene Expression Omnibus datasets. Univariate Cox regression was conducted to assess FRGs. A risk score model basing on 5 FRGs was constructed via LASSO-Cox regression. Multivariate Cox regression analysis was used to determine the independent prognostic factors. The Nomogram model was built using independent prognostic factors. The relationship between the risk score and the immune cell infiltration was estimated by CIBERSORT, and the correlation between the risk score and immune checkpoints was also analyzed.

RESULTS

Based on the prognosis-related FRGs, we built a regression model: Risk score = (-0.01382853 × ACSL4) - (0.05371778 × HMOX1) - (0.02434655 × GPX4) - (0.16432810 × PRNP) - (0.15567120 × ATG7). OS patients with high risk score tended to suffer from poor prognosis, validated in 2 Gene Expression Omnibus datasets. The Nomogram model showed the combination of the risk score and the tumour-node-metastasis stage improved predictive effectiveness. The risk score was also related to immune cell infiltration and immune checkpoint expression.

CONCLUSION

The risk score model based on 5 FRGs was a reliable prognostic predictive indicator for OS patients.

The cuproptosis-related signature predicts prognosis and indicates immune microenvironment in breast cancer

Breast cancer (BC) is the most diagnosed cancer in women. Cuproptosis is new regulated cell death, distinct from known death mechanisms and dependent on copper and mitochondrial respiration. However, the comprehensive relationship between cuproptosis and BC is still blank until now. In the present study, we acquired 13 cuproptosis-related regulators (CRRs) from the previous research and downloaded the RNA sequencing data of TCGA-BRCA from the UCSC XENA database. The 13 CRRs were all differently expressed between BC and normal samples. Using consensus clustering based on the five prognostic CRRs, BC patients were classified into two cuproptosis-clusters (C1 and C2). C2 had a significant survival advantage and higher immune infiltration levels than C1. According to the Cox and LASSO regression analyses, a novel cuproptosis-related prognostic signature was developed to predict the prognosis of BC effectively. The high- and low-risk groups were divided based on the risk scores. Kaplan-Meier survival analysis indicated that the high-risk group had shorter overall survival (OS) than the low-risk group in the training, test and entire cohorts. GSEA indicated that the immune-related pathways were significantly enriched in the low-risk group. According to the CIBERSORT and ESTIMATE analyses, patients in the high-risk group had higher infiltrating levels of antitumor lymphocyte cell subpopulations and higher immune score than the low-risk group. The typical immune checkpoints were all elevated in the high-risk group. Furthermore, the high-risk group showed a better immunotherapy response than the low-risk group based on the Tumor Immune Dysfunction and Exclusion (TIDE) and Immunophenoscore (IPS). In conclusion, we identified two cuproptosis-clusters with different prognoses using consensus clustering in BC. We also developed a cuproptosis-related prognostic signature and nomogram, which could indicate the outcome, the tumor immune microenvironment, as well as the response to immunotherapy.

Ferroptosis-Related Long Non-Coding RNA Signature Contributes to the Prediction of Prognosis Outcomes in Head and Neck Squamous Cell Carcinomas

Background: Head and neck squamous cell carcinoma (HNSCC) is a malignant tumor, which makes the prognosis prediction challenging. Ferroptosis is an iron-dependent form of non-apoptotic regulated cell death, which could affect cancer development. However, the prognostic value of ferroptosis-related long non-coding RNA (lncRNA) in HNSCC is still limited.

Methods: In the current study, we employed the DESeq2 method to characterize the differentially expressed ferroptosis-related genes (FEGs) between cancer and normal samples. Next, the FEG-related lncRNAs (FElncRNAs) were identified using Spearman’s correlation analysis and multiple permutation hypotheses. Subsequently, LASSO and stepwise multivariate Cox regression analyses were undertaken to recognize the prognosis-related FElncRNA signature (PFLS) and risk scores.

Results: Herein, we first identified 60 dysregulated FEGs and their co-expressed FElncRNAs in HNSCC. Then, we recognized a set of six FElncRNAs PFLS (SLCO4A1-AS1, C1RL-AS1, PCED1B-AS1, HOXB-AS3, MIR9-3HG, and SFTA1P) for predicting patients’ prognostic risks and survival outcomes. We also assessed the efficiency of PFLS in the test set and an external validation cohort. Further parsing of the tumor immune microenvironment showed the PFLS was closely associated with immune cell infiltration abundances. Notably, the low-risk group of the PFLS showed a higher MHC score and cytolytic activity (CYT) score than the high-risk group, implying the low-risk group may have greater tumor surveillance and killing ability. In addition, we observed that the expression levels of two immune checkpoints (ICPs), i.e., programmed cell death protein 1 (PD-1) and programmed cell death 1 ligand 1 (PD-L1), showed significant associations with patients’ risk score, prompting the role of the PFLS in ICP blockade therapy. Finally, we also constructed a drug–PFLS network to reinforce the clinical utilities of the PFLS.

Conclusion: In summary, our study indicated that FElncRNAs played an important role in HNSCC survival prediction. Identification of PFLS will contribute to the development of novel anticancer therapeutic strategies.

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

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

Development and Validation of a Robust Ferroptosis-Related Gene Panel for Breast Cancer Disease-Specific Survival

Background: New biomarker combinations have been increasingly developed to improve the precision of current diagnostic and therapeutic modalities. Recently, researchers have found that tumor cells are more vulnerable to ferroptosis. Furthermore, ferroptosis-related genes (FRG) are promising therapeutic targets in breast cancer patients. Therefore, this study aimed to identify FRG that could predict disease-specific survival (DSS) in breast cancer patients. Methods: Gene expression matrix and clinical data were downloaded from public databases. We included 960, 1,900, and 234 patients from the TCGA, METABRIC, and GSE3494 cohorts, respectively. Data for FRG were downloaded from the FerrDb website. Differential expression of FRG was analyzed by comparing the tumors with adjacent normal tissues. Univariate Cox analysis of DSS was performed to identify prognostic FRG. The TCGA-BRCA cohort was used to generate a nine-gene panel with the LASSO cox regression. The METABRIC and GSE3494 cohorts were used to validate the panel. The panel's median cut-off value was used to divide the patients into high- or low-risk subgroups. Analyses of immune microenvironment, functional pathways, and clinical correlation were conducted via GO and KEGG analyses to determine the differences between the two subgroups. Results: The DSS of the low-risk subgroup was longer than that of the high-risk subgroup. The panel's predictive ability was confirmed by ROC curves (TCGA cohort AUC values were 0.806, 0.695, and 0.669 for 2, 3, and 5 years respectively, and the METABRIC cohort AUC values were 0.706, 0.734, and 0.7, respectively for the same periods). The panel was an independent DSS prognostic indicator in the Cox regression analyses. (TCGA cohort: HR = 3.51, 95% CI = 1.792-6.875, p < 0.001; METABRIC cohort: HR = 1.76, 95% CI = 1.283-2.413, p < 0.001). Immune-related pathways were enriched in the high-risk subgroup. The two subgroups that were stratified by the nine-gene panel were also associated with histology type, tumor grade, TNM stage, and Her2-positive and TNBC subtypes. The patients in the high-risk subgroup, whose CTLA4 and PD-1 statuses were both positive or negative, demonstrated a substantial clinical benefit from combination therapy with anti-CTLA4 and anti-PD-1. Conclusion: The new gene panel consisting of nine FRG may be used to assess the prognosis and immune status of patients with breast cancer. A precise therapeutic approach can also be possible with risk stratification.

An Aging-Related Gene Signature-Based Model for Risk Stratification and Prognosis Prediction in Breast Cancer

BACKGROUND

Aging, an inevitable process characterized by functional decline over time, is a significant risk factor for various tumors. However, little is known about aging-related genes (ARGs) in breast cancer (BC). We aimed to explore the potential prognostic role of ARGs and to develop an ARG-based prognosis signature for BC.

METHODS

RNA-sequencing expression profiles and corresponding clinicopathological data of female patients with BC were obtained from public databases in The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). An ARG-based risk signature was constructed in the TCGA cohort based on results of least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analysis, and its prognostic value was further validated in the GSE20685 cohort.

RESULTS

A six ARG-based signature, including CLU, DGAT1, MXI1, NFKBI, PIK3CA and PLAU, was developed in the TCGA cohort and significantly stratified patients into low- and high-risk groups. Patients in the former group showed significantly better prognosis than those in the latter. Multivariate Cox regression analysis demonstrated that the ARG risk score was an independent prognostic factor for BC. A predictive nomogram integrating the ARG risk score and three identified factors (age, N- and M-classification) was established in the TCGA cohort and validated in the GSE20685 cohort. Calibration plots showed good consistency between predicted survival probabilities and actual observations.

CONCLUSION

A novel ARG-based risk signature was developed for patients with BC, which can be used for individual prognosis prediction and promoting personalized treatment.

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

BACKGROUND

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

MATERIALS AND METHODS

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

RESULTS

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

CONCLUSIONS

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