A synthetic lethal drug combination mimics glucose deprivation-induced cancer cell death in the presence of glucose

Rab11a-dependent recycling of Glut3 inhibits seizure-induced neuronal disulfidptosis by alleviating glucose deficiency

Seizures can trigger neuronal glucose deficiency, thereby inducing disulfidptosis. Disulfidptosis is a novel cell death mechanism characterized by the abnormal accumulation of disulfide caused by glucose deficiency. However, the mechanism underlying disulfidptosis caused by glucose deficiency in seizures remains elusive. Rab11a-dependent recycling of glucose transporter 3 (Glut3) is closely related to glucose metabolism in neurons, which may contribute to neuronal disulfidptosis after seizures by abnormal glucose metabolism. So here we introduced a well-established in vitro model of seizures to evaluate cell survival, glucose levels, disulfidptosis biomarkers, Glut3 and Rab11a expression, the recycling ratio of Glut3, and the protein complex of Glut3-Rab11a. Cell survival rates and glucose levels were lower in the in vitro model of seizures, accompanied by elevated levels of disulfidptosis markers. Moreover, the surface expression and the recycling ratio of Glut3, as well as the protein complex of Glut3-Rab11a, were positively correlated with Rab11a expression. Lastly, Rab11 overexpression improved cell survival rates, increased glucose levels, and decreased the levels of disulfidptosis biomarkers in the in vitro model of seizure. Rab11a-dependent recycling of Glut3 inhibited seizure-induced neuronal disulfidptosis by alleviating glucose deficiency.

Prognostic modeling of disulfidptosis gene-associated lncRNAs aids in identifying the tumor microenvironment and guiding the selection of therapy

INTRODUCTION

Gliomas, a type of malignant tumor, are marked by a short survival period and an unfavorable prognosis. Disulfide stress, which arises from an overabundance of intracellular cystine, can initiate disulfidoptosis, an emerging form of cell death. The link between gliomas and disulfidoptosis has not been extensively explored. This study breaks new ground by investigating the correlation between glioma prognosis and lncRNAs associated with disulfidoptosis, with the aim of improving glioma treatment strategies.

METHODS

We analyzed 10 long non-coding RNAs (lncRNAs) co-expressed with disulfidoptosis genes, retrieved clinical information and gene expression profiles from glioma and normal groups in the TCGA database, and developed a prognostic model for lncRNAs based on this data. The receiver operating characteristic curve (ROC) was used to evaluate and validate the model's reliability. Furthermore, the Kaplan-Meier survival curve was employed to assess the disparity in overall survival (OS) among patients with varying risk scores. We also examined the tumor microenvironment (TME), immune cell infiltration, immune-related functions, tumor mutational burden (TMB), and OncoPredict in samples with differing risk scores. To confirm the expression variations of genes associated with prognostic models in cell lines, quantitative polymerase chain reaction (qPCR) was employed.

RESULTS

Eleven long non-coding RNAs (lncRNAs) were identified for constructing prognostic models by analyzing lncRNAs associated with disulfidoptosis genes using Cox regression and LASSO regression analyses. The study's findings indicate that these 11 key lncRNAs serve as independent predictors of overall survival (OS) in glioma patients. Moreover, the frequency with which patients of varying risk scores opt for immune checkpoint blockade (ICB) therapy and chemotherapy not only differs but also their responses to these treatments are significantly distinct, suggesting that the risk score could be a predictive factor for treatment response.

CONCLUSIONS

This research sheds light on the characteristics of disulfidoptosis in glioma, revealing that patterns of disulfidoptosis in patients can be effectively assessed using a risk score. Consequently, the judicious application of this prognostic model can significantly inform clinical treatment strategies and precision medicine for glioma, potentially improving patient outcomes.

A machine learning model and identification of immune infiltration for chronic obstructive pulmonary disease based on disulfidptosis-related genes

BACKGROUND

Chronic obstructive pulmonary disease (COPD) is a chronic and progressive lung disease. Disulfidptosis-related genes (DRGs) may be involved in the pathogenesis of COPD. From the perspective of predictive, preventive, and personalized medicine (PPPM), clarifying the role of disulfidptosis in the development of COPD could provide a opportunity for primary prediction, targeted prevention, and personalized treatment of the disease.

METHODS

We analyzed the expression profiles of DRGs and immune cell infiltration in COPD patients by using the GSE38974 dataset. According to the DRGs, molecular clusters and related immune cell infiltration levels were explored in individuals with COPD. Next, co-expression modules and cluster-specific differentially expressed genes were identified by the Weighted Gene Co-expression Network Analysis (WGCNA). Comparing the performance of the random forest (RF), support vector machine (SVM), generalized linear model (GLM), and eXtreme Gradient Boosting (XGB), we constructed the ptimal machine learning model.

RESULTS

DE-DRGs, differential immune cells and two clusters were identified. Notable difference in DRGs, immune cell populations, biological processes, and pathway behaviors were noted among the two clusters. Besides, significant differences in DRGs, immune cells, biological functions, and pathway activities were observed between the two clusters.A nomogram was created to aid in the practical application of clinical procedures. The SVM model achieved the best results in differentiating COPD patients across various clusters. Following that, we identified the top five genes as predictor genes via SVM model. These five genes related to the model were strongly linked to traits of the individuals with COPD.

CONCLUSION

Our study demonstrated the relationship between disulfidptosis and COPD and established an optimal machine-learning model to evaluate the subtypes and traits of COPD. DRGs serve as a target for future predictive diagnostics, targeted prevention, and individualized therapy in COPD, facilitating the transition from reactive medical services to PPPM in the management of the disease.

Disulfidptosis and Its Hub Gene Slc3a2 Involved in Ulcerative Colitis Pathogenesis, Disease Progression, and Patient Responses to Biologic Therapies

To analyze the role of disulfidptosis in ulcerative colitis (UC), large-scale datasets combined with weighted gene co-expression network analysis (WGCNA) and machine learning were utilized and analyzed. When the hub genes that are associated with UC disease phenotypes and have predictive performance were identified, immune cell infiltration and the CeRNA network were constructed, the role of hub genes in UC pathogenies and biotherapy were investigated, and molecular docking studies and mice-verified tests were carried out to further explore the potential core genes and potential target. Finally, we found 21 DRGs involved in UC pathogenesis, including SLC3A2, FLNA, CAPZB, TLN1, RPN1, etc. Moreover, SLC3A2, TLN1, and RPN1 show a notable correlation with UC inflammatory state, and the expression of DRGs is closely related to the response to UC biotherapy. Our study suggests that disulfidptosis plays a crucial role in the pathogenesis and disease progression of UC. Higher expression of DRGs is commonly observed in moderate to severe UC patients, which may also affect their response to biologic therapies. Among the identified genes, SLC3A2 stands out, providing new insights into the underlying mechanisms of UC and potentially serving as a novel therapeutic target for the treatment of UC.

Development of a novel disulfidptosis-correlated m6A/m1A/m5C/m7G gene signature to predict prognosis and therapeutic response for lung adenocarcinoma patients by integrated machine-learning

BACKGROUND

Lung adenocarcinoma (LUAD) represents a significant global health burden, necessitating advanced prognostic tools for improved patient management. RNA modifications (m6A, m1A, m5C, m7G), and disulfidptosis, a novel cell death mechanism, have emerged as promising biomarkers and therapeutic targets in cancer.

METHODS

We systematically compiled disulfidptosis-correlated genes and RNA modification-related genes from existing literature. A novel disulfidptosis-correlated m6A/m1A/m5C/m7G riskscore was computed using integrated machine-learning algorithms. Transcriptomic data from TCGA and GEO databases were downloaded analyzed. Single-cell RNA-sequencing data from the TISCH database was processed using the Seurat package. Genes' protein-protein interaction network was constructed using the String database. Functional phenotype analysis was performed using GSVA, ClusterProfiler, and IOBR packages. Consensus clustering divided patients into two distinct groups. Drug sensitivity predictions were obtained from the GDSC1 database and predicted using the Oncopredict package.

RESULTS

The disulfidptosis-correlated m6A/m1A/m5C/m7G risk score effectively stratified LUAD patients into prognostically distinct groups, demonstrating superior predictive accuracy compared to conventional clinical parameters. Patients in different risk groups exhibited significant molecular and clinical differences. Subsequent analyses identified two molecular subtypes associated with RNA modification and disulfidptosis, revealing differences in immune infiltration and prognosis. Functional enrichment analyses highlighted pathways involving RNA modification and disulfidptosis, underscoring their roles in LUAD pathogenesis. Single-cell analysis revealed distinct features between high- and low-risk status cells.

CONCLUSION

This study introduces a novel disulfidptosis-correlated m6A/m1A/m5C/m7G risk score as a robust prognostic tool for LUAD, integrating insights from RNA modifications and cell death mechanisms. The risk score enhances prognostic stratification and identifies potential targets for personalized therapeutic strategies in LUAD. This comprehensive approach emphasizes the critical roles of RNA modifications and disulfidptosis in LUAD biology, paving the way for future research and clinical applications aimed at improving patient outcomes.

The Complex Roles of Redox and Antioxidant Biology in Cancer

Redox reactions control fundamental biochemical processes, including energy production, metabolism, respiration, detoxification, and signal transduction. Cancer cells, due to their generally active metabolism for sustained proliferation, produce high levels of reactive oxygen species (ROS) compared to normal cells and are equipped with antioxidant defense systems to counteract the detrimental effects of ROS to maintain redox homeostasis. The KEAP1-NRF2 system plays a major role in sensing and regulating endogenous antioxidant defenses in both normal and cancer cells, creating a bivalent contribution of NRF2 to cancer prevention and therapy. Cancer cells hijack the NRF2-dependent antioxidant program and exploit a very unique metabolism as a trade-off for enhanced antioxidant capacity. This work provides an overview of redox metabolism in cancer cells, highlighting the role of the KEAP1-NRF2 system, selenoproteins, sulfur metabolism, heme/iron metabolism, and antioxidants. Finally, we describe therapeutic approaches that can be leveraged to target redox metabolism in cancer.

Metabolic cell death in cancer: ferroptosis, cuproptosis, disulfidptosis, and beyond

Cell death resistance represents a hallmark of cancer. Recent studies have identified metabolic cell death as unique forms of regulated cell death resulting from an imbalance in the cellular metabolism. This review discusses the mechanisms of metabolic cell death-ferroptosis, cuproptosis, disulfidptosis, lysozincrosis, and alkaliptosis-and explores their potential in cancer therapy. Our review underscores the complexity of the metabolic cell death pathways and offers insights into innovative therapeutic avenues for cancer treatment.

Disulfidptosis: A Novel Prognostic Criterion and Potential Treatment Strategy for Diffuse Large B-Cell Lymphoma (DLBCL)

Diffuse Large B-cell Lymphoma (DLBCL), with its intrinsic genetic and epigenetic heterogeneity, exhibits significantly variable clinical outcomes among patients treated with the current standard regimen. Disulfidptosis, a novel form of regulatory cell death triggered by disulfide stress, is characterized by the collapse of cytoskeleton proteins and F-actin due to intracellular accumulation of disulfides. We investigated the expression variations of disulfidptosis-related genes (DRGs) in DLBCL using two publicly available gene expression datasets. The initial analysis of DRGs in DLBCL (GSE12453) revealed differences in gene expression patterns between various normal B cells and DLBCL. Subsequent analysis (GSE31312) identified DRGs strongly associated with prognostic outcomes, revealing eight characteristic DRGs (CAPZB, DSTN, GYS1, IQGAP1, MYH9, NDUFA11, NDUFS1, OXSM). Based on these DRGs, DLBCL patients were stratified into three groups, indicating that (1) DRGs can predict prognosis, and (2) DRGs can help identify novel therapeutic candidates. This study underscores the significant role of DRGs in various biological processes within DLBCL. Assessing the risk scores of individual DRGs allows for more precise stratification of prognosis and treatment strategies for DLBCL patients, thereby enhancing the effectiveness of clinical practice.

A new perspective: deciphering the aberrance and clinical implication of disulfidptosis signatures in clear cell renal cell carcinoma

Recent research has discovered disulfidptosis as a form of programmed cell death characterized by disulfide stress. However, its significance in clear cell renal cell carcinoma (ccRCC) remains unclear. To investigate this, data from The Cancer Genome Atlas were collected and used to identify ccRCC subgroups. Unsupervised clustering was employed to determine ccRCC heterogeneity. The mutation landscape and immune microenvironment of the subgroups were analyzed. The Disulfidptosis-Related Score was calculated using the LASSO-penalized Cox regression algorithm. The E-MATB-1980 cohort was used to validate the signature. The role of SLC7A11 in ccRCC metastasis was explored using western blotting and Transwell assays. Disulfidptosis-related genes are commonly downregulated in cancers and are linked to hypermethylation and copy number variation. The study revealed that ccRCC is divided into two sub-clusters: the disulfidptosis-desert sub-cluster, which is associated with a poor prognosis, a higher mutation frequency, and an immunosuppressive microenvironment. A 14-gene prognostic model was developed using differentially expressed genes and was validated in the E-MATB-1980 cohort. The low-risk group demonstrated longer overall and disease-free survival and responded better to targeted immunotherapy. Results from in vitro experiments identified SLC7A11 as a key participant in ccRCC metastasis.

Identification of a disulfidptosis-related prognostic signature for prediction of the effect of treatment in patients with endometrial carcinoma

Background

Disulfide, an essential compounds family, has diverse biological activity and can affect the dynamic balance between physiological and pathological states. A recently published study found that aberrant accumulation of disulfide had a lethal effect on cells. This mechanism of cell death, named disulfidptosis, differs from other known cell death mechanisms, including cuproptosis, apoptosis, necroptosis, and pyroptosis. The relationship between disulfidptosis and development of cancer, in particular endometrial carcinoma, remains unclear.

Methods

To address this knowledge gap, we performed a preliminary analysis of samples from The Cancer Genome Atlas database. The samples were divided equally into a training group and a test group. A total of 2308 differentially expressed genes were extracted, and 11 were used to construct a prognostic model.

Results

Based on the risk score calculated using the prognostic model, the samples were divided into a high-risk group and a low-risk group. Survival time, tumor mutation burden, and microsatellite instability scores differed significantly between the two groups. Furthermore, a between-group difference in treatment effect was predicted. Comparison with other models in the literature indicated that this prognostic model had better predictive anility.

Conclusion

The results of this study provide a general framework for understanding the relationship between disulfidptosis and endometrial cancer that could be used for clinical evaluation and selection of appropriate personalized treatment strategies.

Disulfidptosis decoded: a journey through cell death mysteries, regulatory networks, disease paradigms and future directions

Cell death is an important part of the life cycle, serving as a foundation for both the orderly development and the maintenance of physiological equilibrium within organisms. This process is fundamental, as it eliminates senescent, impaired, or aberrant cells while also promoting tissue regeneration and immunological responses. A novel paradigm of programmed cell death, known as disulfidptosis, has recently emerged in the scientific circle. Disulfidptosis is defined as the accumulation of cystine by cancer cells with high expression of the solute carrier family 7 member 11 (SLC7A11) during glucose starvation. This accumulation causes extensive disulfide linkages between F-actins, resulting in their contraction and subsequent detachment from the cellular membrane, triggering cellular death. The RAC1-WRC axis is involved in this phenomenon. Disulfidptosis sparked growing interest due to its potential applications in a variety of pathologies, particularly oncology, neurodegenerative disorders, and metabolic anomalies. Nonetheless, the complexities of its regulatory pathways remain elusive, and its precise molecular targets have yet to be definitively identified. This manuscript aims to meticulously dissect the historical evolution, molecular underpinnings, regulatory frameworks, and potential implications of disulfidptosis in various disease contexts, illuminating its promise as a groundbreaking therapeutic pathway and target.

Transcriptome and single-cell analysis reveal disulfidptosis-related modification patterns of tumor microenvironment and prognosis in osteosarcoma

Osteosarcoma (OS) is the most common malignant bone tumor with high pathological heterogeneity. Our study aimed to investigate disulfidptosis-related modification patterns in OS and their relationship with survival outcomes in patients with OS. We analyzed the single-cell-level expression profiles of disulfidptosis-related genes (DSRGs) in both OS microenvironment and OS subclusters, and HMGB1 was found to be crucial for intercellular regulation of OS disulfidptosis. Next, we explored the molecular clusters of OS based on DSRGs and related immune cell infiltration using transcriptome data. Subsequently, the hub genes of disulfidptosis in OS were screened by applying multiple machine models. In vitro and patient experiments validated our results. Three main disulfidptosis-related molecular clusters were defined in OS, and immune infiltration analysis suggested high immune heterogeneity between distinct clusters. The in vitro experiment confirmed decreased cell viability of OS after ACTB silencing and higher expression of ACTB in patients with lower immune scores. Our study systematically revealed the underlying relationship between disulfidptosis and OS at the single-cell level, identified disulfidptosis-related subtypes, and revealed the potential role of ACTB expression in OS disulfidptosis.

Development and experimental verification of a prognosis model for disulfidptosis-associated genes in HNSCC

Disulfidptosis is a newly discovered cell death pattern that has been less studied in head and neck squamous carcinoma (HNSCC). Exploring the molecular features of different subtypes of HNSCC based on disulfidptosis-associated genes (DAGs) is important for HNSCC. In addition, immunotherapy plays a pivotal role in the treatment of HNSCC. Exploring the sensitivity of immunotherapies and developing predictive models is essential for HNSCC. We analyzed the expression and mutational status of DAGs in 790 HNSCC patients and correlated the dates with clinical prognosis. HNSCC patients were divided into 2 groups based on their DAG expression. The relationship between DAGs, risk genes, and the immune microenvironment was analyzed using the CIBERSORT algorithm. A disulfidptosis risk model was constructed based on 5 risk genes using the LASSO COX method. To facilitate the clinical applicability of the proposed risk model, we constructed column line plots and performed stem cell correlation analysis and antitumor drug sensitivity analysis. Two different disulfidptosis-associated clusters were identified using consistent unsupervised clustering analysis. Correlations between multilayer DAG alterations and clinical characteristics and prognosis were observed. Then, a well-performing disulfidptosis-associated risk model (DAG score) was developed to predict the prognosis of HNSCC patients. We divided patients into high-risk and low-risk groups based on the DAG score and found that patients in the low-risk group were more likely to survive than those in the high-risk group (P < .05). A high DAG score implies higher immune cell infiltration and increased mutational burden. Also, univariate and multivariate Cox regression analyses revealed that the DAG score was an independent prognostic predictor for patients with HNSCC. Subsequently, a highly accurate predictive model was developed to facilitate the clinical application of DAG scores, showing good predictive and calibration power. Overall, we present a comprehensive overview of the DAG profile in HNSCC and develop a new risk model for the therapeutic status and prognosis of patients with HNSCC. Our findings highlight the potential clinical significance of DAG and suggest that disulfidptosis may be a potential therapeutic target for patients with HNSCC.

A novel disulfidptosis-related lncRNAs signature for predicting survival and immune response in hepatocellular carcinoma

The accumulation of intracellular disulfides induces a novel and unique form of metabolic-related cell death known as disulfidptosis. A previous study revealed the prognostic value of a risk model of disulfidptosis-related genes in hepatocellular carcinoma (HCC). However, to date, no studies have investigated the relationship between disulfidptosis-related long non-coding RNAs (DRLs) and HCC. In this study, we collected and analyzed RNA sequencing data from 370 HCC samples to explore the DRLs in the tumorigenesis and development of HCC. By employing Lasso Cox regression and multivariate Cox regression analyses, we identified five prognostic DRLs, which were used to construct a prognostic signature. The signature was subsequently validated using receiver operating characteristic (ROC) curves, Kaplan-Meier analysis, Cox regression analyses, nomograms, and calibration curves. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and gene set enrichment analysis (GSEA) were performed, revealing that the DRLs signature was associated with HCC and several cancer-related pathways. Furthermore, the DRLs signature showed correlations with the infiltration of M0 and M1 macrophages, immune-related functions, and multiple immune checkpoints, including PDCD1, LAG3, CTLA4, TIGIT, CD47, and others. Analysis using the tumor immune dysfunction and exclusion (TIDE) approach demonstrated that the DRLs signature could predict the response to immunotherapy. Finally, we screened potential chemotherapy drugs that could sensitize HCC. In conclusion, our novel DRLs signature provides valuable insights into predicting patient survival and immunotherapy responses.

Impact of disulfidptosis-associated clusters on breast cancer survival rates and guiding personalized treatment

Background

Breast cancer (BC) poses a serious threat to human health. Disulfidptosis is a recently discovered form of cell death associated with cancer prognosis and progression. However, the relationship between BC and disulfidptosis remains unclear.

Methods

We integrated single-cell sequencing and transcriptome sequencing in BC to assess the abundance and mutation status of disulfidptosis-associated genes (DAGs). Subsequently, we clustered the samples based on DAGs and constructed a prognostic model associated with disulfidptosis. Additionally, we performed pathway enrichment, immune response, and drug sensitivity analyses on the model. Finally, we validated the prognostic genes through Immunohistochemistry (IHC).

Results

The single-cell analysis identified 21 cell clusters and 8 cell types. By evaluating the abundance of DAGs in different cell types, we found specific expression of the disulfidoptosis core gene SLC7A11 in mesenchymal stem cells (MSCs). Through unsupervised clustering of DAGs, we identified two clusters. Utilizing differentially expressed genes from these clusters, we selected 7 genes (AFF4, SLC7A11, IGKC, IL6ST, LIMD2, MAT2B, and SCAND1) through Cox and Lasso regression to construct a prognostic model. External validation demonstrated good prognostic prediction of our model. BC patients were stratified into two groups based on riskscore, with the high-risk group corresponding to a worse prognosis. Immune response analysis revealed higher TMB and lower TIDE scores in the high-risk group, while the low-risk group exhibited higher CTLA4/PD-1 expression. This suggests that both groups may respond to immunotherapy, necessitating further research to elucidate potential mechanisms. Drug sensitivity analysis indicated that dasatinib, docetaxel, lapatinib, methotrexate, paclitaxel, and sunitinib may have better efficacy in the low-risk group. Finally, Immunohistochemistry (IHC) validated the expression of prognostic genes, demonstrating higher levels in tumor tissue compared to normal tissue.

Conclusion

Our study has developed an effective disulfidptosis-related prognostic prediction tool for BC and provides personalized guidance for the clinical management and immunotherapy selection of BC patients.

A novel disulfidptosis-related immune checkpoint genes signature: forecasting the prognosis of hepatocellular carcinoma

BACKGROUND

HCC is an extremely malignant tumor with a very poor prognosis. In 2023, a brand-new kind of cell death known as disulfidptosis was identified. Although, the prognosis as well as expression of immune checkpoints that are closely connected with it in HCC remain unknown.

METHODS

In this work, we identified 49 genes with abnormal expression in liver cancer and normal liver tissue, with 23 of them being differentially expressed genes. To create a signature, we classified all HCC cases into three subtypes and used the TCGA database to evaluate each relevant gene's prognostic value for survival.

RESULTS

Five gene signatures were identified using the LASSO Cox regression approach, while those diagnosed with HCC were split into either low- or high-risk groups. Patients having low-risk HCC showed a much greater likelihood of surviving than those with high risk (p < 0.05). Through immune cell infiltration analysis, it was found that immune-related genes were abundant in high-risk groups and had reduced immune status.

CONCLUSION

In conclusion, immune checkpoint genes highly associated with disulfidptosis contribute to tumor immunity and can be used to evaluate HCC prognosis. When it comes to predicting overall survival (OS) time in HCC, risk score has been set to be a separate predictor. Through immune cell infiltration analysis, it was found that immune-related genes were abundant in high-risk groups and had reduced immune status. It is possible to measure the prognosis of HCC based on immune checkpoints genes strongly linked to disulfidptosis.

Integrated single-cell and bulk RNA sequencing in pancreatic cancer identifies disulfidptosis-associated molecular subtypes and prognostic signature

Pancreatic cancer (PC) is known for its high degree of heterogeneity and exceptionally adverse outcome. While disulfidptosis is the most recently identified form of cell death, the predictive and therapeutic value of disulfidptosis-related genes (DRGs) for PC remains unknown. RNA sequencing data with the follow-up information, were retrieved from the TCGA and ICGC databases. Consensus clustering analysis was conducted on patient data using R software. Subsequently, the LASSO regression analysis was conducted to create a prognostic signature for foreseeing the outcome of PC. Differences in relevant pathways, mutational landscape, and tumor immune microenvironment were compared between PC samples with different risk levels. Finally, we experimentally confirmed the impact of DSG3 on the invasion and migration abilities of PC cells. All twenty DRGs were found to be hyperexpressed in PC tissues, and fourteen of them significantly associated with PC survival. Using consensus clustering analysis based on these DRGs, four DRclusters were identified. Additionally, altogether 223 differential genes were evaluated between clusters, indicating potential biological differences between them. Four gene clusters (geneClusters) were recognized according to these genes, and a 10-gene prognostic signature was created. High-risk patients were found to be primarily enriched in signaling pathways related to the cell cycle and p53. Furthermore, the rate of mutations was markedly higher in high-risk patients, besides important variations were present in terms of immune microenvironment and chemotherapy sensitivity among patients with different risk levels. DSG3 could appreciably enhance the invasion and migration of PC cells. This work, based on disulfidoptosis-related genes (DRGs), holds the promise of classifying PC patients and predicting their prognosis, mutational landscape, immune microenvironment, and drug therapy. These insights could boost an improvement in a better comprehension of the role of DRGs in PC as well as provide new opportunities for prognostic prediction and more effective treatment strategies.

Identification of disulfidptosis-related subgroups and prognostic signatures in lung adenocarcinoma using machine learning and experimental validation

Background

Disulfidptosis is a newly identified variant of cell death characterized by disulfide accumulation, which is independent of ATP depletion. Accordingly, the latent influence of disulfidptosis on the prognosis of lung adenocarcinoma (LUAD) patients and the progression of tumors remains poorly understood.

Methods

We conducted a multifaceted analysis of the transcriptional and genetic modifications in disulfidptosis regulators (DRs) specific to LUAD, followed by an evaluation of their expression configurations to define DR clusters. Harnessing the differentially expressed genes (DEGs) identified from these clusters, we formulated an optimal predictive model by amalgamating 10 distinct machine learning algorithms across 101 unique combinations to compute the disulfidptosis score (DS). Patients were subsequently stratified into high and low DS cohorts based on median DS values. We then performed an exhaustive comparison between these cohorts, focusing on somatic mutations, clinical attributes, tumor microenvironment, and treatment responsiveness. Finally, we empirically validated the biological implications of a critical gene, KYNU, through assays in LUAD cell lines.

Results

We identified two DR clusters and there were great differences in overall survival (OS) and tumor microenvironment. We selected the "Least Absolute Shrinkage and Selection Operator (LASSO) + Random Survival Forest (RFS)" algorithm to develop a DS based on the average C-index across different cohorts. Our model effectively stratified LUAD patients into high- and low-DS subgroups, with this latter demonstrating superior OS, a reduced mutational landscape, enhanced immune status, and increased sensitivity to immunotherapy. Notably, the predictive accuracy of DS outperformed the published LUAD signature and clinical features. Finally, we validated the DS expression using clinical samples and found that inhibiting KYNU suppressed LUAD cells proliferation, invasiveness, and migration in vitro.

Conclusions

The DR-based scoring system that we developed enabled accurate prognostic stratification of LUAD patients and provides important insights into the molecular mechanisms and treatment strategies for LUAD.

SLC7A11 expression level dictates differential responses to oxidative stress in cancer cells

The cystine transporter solute carrier family 7 member 11 (SLC7A11; also called xCT) protects cancer cells from oxidative stress and is overexpressed in many cancers. Here we report a surprising finding that, whereas moderate overexpression of SLC7A11 is beneficial for cancer cells treated with H2O2, a common oxidative stress inducer, its high overexpression dramatically increases H2O2-induced cell death. Mechanistically, high cystine uptake in cancer cells with high overexpression of SLC7A11 in combination with H2O2 treatment results in toxic buildup of intracellular cystine and other disulfide molecules, NADPH depletion, redox system collapse, and rapid cell death (likely disulfidptosis). We further show that high overexpression of SLC7A11 promotes tumor growth but suppresses tumor metastasis, likely because metastasizing cancer cells with high expression of SLC7A11 are particularly susceptible to oxidative stress. Our findings reveal that SLC7A11 expression level dictates cancer cells' sensitivity to oxidative stress and suggests a context-dependent role for SLC7A11 in tumor biology.

piTracer - Automatic reconstruction of molecular cascades for the identification of synergistic drug targets

Cancer cells frequently undergo metabolic reprogramming as a mechanism of resistance against chemotherapeutic drugs. Metabolomic profiling provides a direct readout of metabolic changes and can thus be used to identify these tumor escape mechanisms. Here, we introduce piTracer, a computational tool that uses multi-scale molecular networks to identify potential combination therapies from pre- and post-treatment metabolomics data. We first demonstrate piTracer’s core ability to reconstruct cellular cascades by inspecting well-characterized molecular pathways and previously studied associations between genetic variants and metabolite levels. We then apply a new gene ranking algorithm on differential metabolomic profiles from human breast cancer cells after glutaminase inhibition. Four of the automatically identified gene targets were experimentally tested by simultaneous inhibition of the respective targets and glutaminase. Of these combination treatments, two were be confirmed to induce synthetic lethality in the cell line. In summary, piTracer integrates the molecular monitoring of escape mechanisms into comprehensive pathway networks to accelerate drug target identification. The tool is open source and can be accessed at https://github.com/krumsieklab/pitracer .

An appraisal of the current status of inhibition of glucose transporters as an emerging antineoplastic approach: Promising potential of new pan-GLUT inhibitors

Neoplastic cells displayed altered metabolism with accelerated glycolysis. Therefore, these cells need a mammoth supply of glucose for which they display an upregulated expression of various glucose transporters (GLUT). Thus, novel antineoplastic strategies focus on inhibiting GLUT to intersect the glycolytic lifeline of cancer cells. This review focuses on the current status of various GLUT inhibition scenarios. The GLUT inhibitors belong to both natural and synthetic small inhibitory molecules category. As neoplastic cells express multiple GLUT isoforms, it is necessary to use pan-GLUT inhibitors. Nevertheless, it is also necessary that such pan-GLUT inhibitors exert their action at a low concentration so that normal healthy cells are left unharmed and minimal injury is caused to the other vital organs and systems of the body. Moreover, approaches are also emerging from combining GLUT inhibitors with other chemotherapeutic agents to potentiate the antineoplastic action. A new pan-GLUT inhibitor named glutor, a piperazine-one derivative, has shown a potent antineoplastic action owing to its inhibitory action exerted at nanomolar concentrations. The review discusses the merits and limitations of the existing GLUT inhibitory approach with possible future outcomes.

MiR-129-3p regulates ferroptosis in the liver of Selenium-deficient broilers by targeting SLC7A11

Selenium (Se) has been proven to be an essential trace element for organism. Se deficiency in poultry can cause widespread damage, such as exudative diathesis. The liver is not only the main organ of metabolism, but also one of the organs with high Se content in organism. Recent studies have shown that solute carrier family 7 member 11 (SLC7A11) plays a key role in the negative regulation of ferroptosis. In order to explore the mechanism of Se deficiency induces liver ferroptosis in broilers, and the role of microRNAs (miRNAs) in this process, we divided broilers into 2 groups: control group (0.2 mg/kg Se) and Se deficiency group (0.03 mg/kg Se). Hematoxylin-Eosin staining detected liver tissue damage in broilers. Predicted and verified the targeting relationship between miR-129-3p and SLC7A11 through miRDB and dual luciferase report experiments. The genes related to ferroptosis were detected by qRT-PCR and Western Blot. The results showed that the expression level of miR-129-3p mRNA in Se-deficient liver was significantly increased. To understand whether the miR-129-3p/SLC7A11 axis could involve in the process of ferroptosis, our further research showed that overexpression of miR-129-3p could reduce the expression of SLC7A11 and its downstream GCL, GSS, and GPX4, thereby inducing ferroptosis. These data indicates that miR-129-3p affected ferroptosis under Se deficiency conditions through the SLC7A11 pathway. Our research provides a new perspective for the mechanism of Se deficiency on the liver damage.

The Role of Cystine/Glutamate Antiporter SLC7A11/xCT in the Pathophysiology of Cancer

SLC7A11/xCT is an antiporter that mediates the uptake of extracellular cystine in exchange for glutamate. Cystine is reduced to cysteine, which is a rate-limiting precursor in glutathione synthesis; a process that protects cells from oxidative stress and is, therefore, critical to cell growth, proliferation, and metabolism. SLC7A11 is expressed in different tissues and plays diverse functional roles in the pathophysiology of various diseases, including cancer, by regulating the processes of redox homeostasis, metabolic flexibility/nutrient dependency, immune system function, and ferroptosis. SLC7A11 expression is associated with poor prognosis and drug resistance in cancer and, therefore, represents an important therapeutic target. In this review, we discuss the molecular functions of SLC7A11 in normal versus diseased tissues, with a special focus on how it regulates gastrointestinal cancers. Further, we summarize current therapeutic strategies targeting SLC7A11 as well as novel avenues for treatment.

Thiol profiling in cancer cell lines by HPLC-mass spectrometry

We describe a protocol for identifying cellular thiol metabolites such as cysteine and cystine in adherent cells using high performance liquid chromatography (HPLC) tandem mass spectrometry-based metabolomics. We applied a modified extraction and sample derivatization protocol to accurately quantify the intracellular levels of labile thiol species and to inhibit oxidation prior to analysis.

For complete details on the use and execution of this protocol, please refer to Liu et al. (2020) and Koppula et al. (2021).

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LC-MS-based quantification of labile thiol species

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Modified extraction and derivatization procedure to prevent sample oxidation

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Protocol for quantification of reduced and oxidized thiol species

Multistability maintains redox homeostasis in human cells

Cells metabolize nutrients through a complex metabolic and signaling network that governs redox homeostasis. At the core of this, redox regulatory network is a mutually inhibitory relationship between reduced glutathione and reactive oxygen species (ROS)-two opposing metabolites that are linked to upstream nutrient metabolic pathways (glucose, cysteine, and glutamine) and downstream feedback loops of signaling pathways (calcium and NADPH oxidase). We developed a nutrient-redox model of human cells to understand system-level properties of this network. Combining in silico modeling and ROS measurements in individual cells, we show that ROS dynamics follow a switch-like, all-or-none response upon glucose deprivation at a threshold that is approximately two orders of magnitude lower than its physiological concentration. We also confirm that this ROS switch can be irreversible and exhibits hysteresis, a hallmark of bistability. Our findings evidence that bistability modulates redox homeostasis in human cells and provide a general framework for quantitative investigations of redox regulation in humans.

NADPH debt drives redox bankruptcy: SLC7A11/xCT-mediated cystine uptake as a double-edged sword in cellular redox regulation

Cystine/glutamate antiporter solute carrier family 7 member 11 (SLC7A11; also known as xCT) plays a key role in antioxidant defense by mediating cystine uptake, promoting glutathione synthesis, and maintaining cell survival under oxidative stress conditions. Recent studies showed that, to prevent toxic buildup of highly insoluble cystine inside cells, cancer cells with high expression of SLC7A11 (SLC7A11^high) are forced to quickly reduce cystine to more soluble cysteine, which requires substantial NADPH supply from the glucose-pentose phosphate pathway (PPP) route, thereby inducing glucose- and PPP-dependency in SLC7A11^high cancer cells. Limiting glucose supply to SLC7A11^high cancer cells results in significant NADPH “debt”, redox “bankruptcy”, and subsequent cell death. This review summarizes our current understanding of NADPH-generating and -consuming pathways, discusses the opposing role of SLC7A11 in protecting cells from oxidative stress–induced cell death such as ferroptosis but promoting glucose starvation–induced cell death, and proposes the concept that SLC7A11-mediated cystine uptake acts as a double-edged sword in cellular redox regulation. A detailed understanding of SLC7A11 in redox biology may identify metabolic vulnerabilities in SLC7A11^high cancer for therapeutic targeting.

Overview of Ferroptosis and Synthetic Lethality Strategies

Ferroptosis, a term first proposed in 2012, is iron-dependent, non-apoptotic regulatory cell death induced by erastin. Ferroptosis was originally discovered during synthetic lethal screening for drugs sensitive to RAS mutant cells, and is closely related to synthetic lethality. Ferroptosis sensitizes cancer stem cells and tumors that undergo epithelial-mesenchymal transition and are resistant to anticancer drugs or targeted therapy. Therefore, ferroptosis-inducing molecules are attractive new research targets. In contrast, synthetic lethal strategies approach mechanisms and genetic abnormalities that cannot be directly targeted by conventional therapeutic strategies, such as RAS mutations, hypoxia, and abnormalities in the metabolic environment. They also target the environment and conditions specific to malignant cells, have a low toxicity to normal cells, and can be used in combination with known drugs to produce new ones. However, the concept of synthetic lethality has not been widely adopted with ferroptosis. In this review, we surveyed the literature on ferroptosis-related factors and synthetic lethality to examine the potential therapeutic targets in ferroptosis-related molecules, focusing on factors related to synthetic lethality, discovery methods, clinical application stages, and issues in drug discovery.

KEAP1 deficiency drives glucose dependency and sensitizes lung cancer cells and tumors to GLUT inhibition

Metabolic reprogramming in cancer cells can create metabolic liabilities. KEAP1-mutant lung cancer is refractory to most current therapies. Here we show that KEAP1 deficiency promotes glucose dependency in lung cancer cells, and KEAP1-mutant/deficient lung cancer cells are more vulnerable to glucose deprivation than their WT counterparts. Mechanistically, KEAP1 inactivation in lung cancer cells induces constitutive activation of NRF2 transcription factor and aberrant expression of NRF2 target cystine transporter SLC7A11; under glucose limitation, high cystine uptake in KEAP1-inactivated lung cancer cells stimulates toxic intracellular disulfide buildup, NADPH depletion, and cell death, which can be rescued by genetic ablation of NRF2-SLC7A11 axis or treatments inhibiting disulfide accumulation. Finally, we show that KEAP1-inactivated lung cancer cells or xenograft tumors are sensitive to glucose transporter inhibitor. Together, our results reveal that KEAP1 deficiency induces glucose dependency in lung cancer cells and uncover a therapeutically relevant metabolic liability.

The landscape of metabolic pathway dependencies in cancer cell lines

The metabolic reprogramming of cancer cells creates metabolic vulnerabilities that can be therapeutically targeted. However, our understanding of metabolic dependencies and the pathway crosstalk that creates these vulnerabilities in cancer cells remains incomplete. Here, by integrating gene expression data with genetic loss-of-function and pharmacological screening data from hundreds of cancer cell lines, we identified metabolic vulnerabilities at the level of pathways rather than individual genes. This approach revealed that metabolic pathway dependencies are highly context-specific such that cancer cells are vulnerable to inhibition of one metabolic pathway only when activity of another metabolic pathway is altered. Notably, we also found that the no single metabolic pathway was universally essential, suggesting that cancer cells are not invariably dependent on any metabolic pathway. In addition, we confirmed that cell culture medium is a major confounding factor for the analysis of metabolic pathway vulnerabilities. Nevertheless, we found robust associations between metabolic pathway activity and sensitivity to clinically approved drugs that were independent of cell culture medium. Lastly, we used parallel integration of pharmacological and genetic dependency data to confidently identify metabolic pathway vulnerabilities. Taken together, this study serves as a comprehensive characterization of the landscape of metabolic pathway vulnerabilities in cancer cell lines.

A small-molecule pan-class I glucose transporter inhibitor reduces cancer cell proliferation in vitro and tumor growth in vivo by targeting glucose-based metabolism

BACKGROUND

Cancer cells drastically increase the uptake of glucose and glucose metabolism by overexpressing class I glucose transporters (GLUT1-4) to meet their energy and biomass synthesis needs and are very sensitive and vulnerable to glucose deprivation. Although targeting glucose uptake via GLUTs has been an attractive anticancer strategy, the relative anticancer efficacy of multi-GLUT targeting or single GLUT targeting is unclear. Here, we report DRB18, a synthetic small molecule, is a potent anticancer compound whose pan-class I GLUT inhibition is superior to single GLUT targeting.

METHODS

Glucose uptake and MTT/resazurin assays were used to measure DRB18's inhibitory activities of glucose transport and cell viability/proliferation in human lung cancer and other cancer cell lines. Four HEK293 cell lines expressing GLUT1-4 individually were used to determine the IC₅₀ values of DRB18's inhibitory activity of glucose transport. Docking studies were performed to investigate the potential direct interaction of DRB18 with GLUT1-4. Metabolomics analysis was performed to identify metabolite changes in A549 lung cancer cells treated with DRB18. DRB18 was used to treat A549 tumor-bearing nude mice. The GLUT1 gene was knocked out to determine how the KO of the gene affected tumor growth.

RESULTS

DRB18 reduced glucose uptake mediated via each of GLUT1-4 with different IC₅₀s, which match with the docking glidescores with a correlation coefficient of 0.858. Metabolomics analysis revealed that DRB18 altered energy-related metabolism in A549 cells by changing the abundance of metabolites in glucose-related pathways in vitro and in vivo. DRB18 eventually led to G1/S phase arrest and increased oxidative stress and necrotic cell death. IP injection of DRB18 in A549 tumor-bearing nude mice at 10 mg/kg body weight thrice a week led to a significant reduction in the tumor volume compared with mock-treated tumors. In contrast, the knockout of the GLUT1 gene did not reduce tumor volume.

CONCLUSIONS

DRB18 is a potent pan-class I GLUT inhibitor in vitro and in vivo in cancer cells. Mechanistically, it is likely to bind the outward open conformation of GLUT1-4, reducing tumor growth through inhibiting GLUT1-4-mediated glucose transport and metabolisms. Pan-class I GLUT inhibition is a better strategy than single GLUT targeting for inhibiting tumor growth.

Identification of Predictive Biomarkers of Response to HSP90 Inhibitors in Lung Adenocarcinoma

Heat shock protein 90 (HSP90) plays an essential role in lung adenocarcinoma, acting as a key chaperone involved in the correct functioning of numerous highly relevant protein drivers of this disease. To this end, HSP90 inhibitors have emerged as promising therapeutic strategies, even though responses to them have been limited to date. Given the need to maximize treatment efficacy, the objective of this study was to use isobaric tags for relative and absolute quantitation (iTRAQ)-based proteomic techniques to identify proteins in human lung adenocarcinoma cell lines whose basal abundances were correlated with response to HSP90 inhibitors (geldanamycin and radicicol derivatives). From the protein profiles identified according to response, the relationship between lactate dehydrogenase B (LDHB) and DNA topoisomerase 1 (TOP1) with respect to sensitivity and resistance, respectively, to geldanamycin derivatives is noteworthy. Likewise, rhotekin (RTKN) and decaprenyl diphosphate synthase subunit 2 (PDSS2) were correlated with sensitivity and resistance to radicicol derivatives. We also identified a relationship between resistance to HSP90 inhibition and the p53 pathway by glucose deprivation. In contrast, arginine biosynthesis was correlated with sensitivity to HSP90 inhibitors. Further study of these outcomes could enable the development of strategies to improve the clinical efficacy of HSP90 inhibition in patients with lung adenocarcinoma.

SLC7A11/xCT in cancer: biological functions and therapeutic implications

Amino acid transporters mediate substrates across cellular membranes and their fine-tuned regulations are critical to cellular metabolism, growth, and death. As the functional component of system Xc-, which imports extracellular cystine with intracellular glutamate release at a ratio of 1:1, SLC7A11 has diverse functional roles in regulating many pathophysiological processes such as cellular redox homeostasis, ferroptosis, and drug resistance in cancer. Notably, accumulated evidence demonstrated that SLC7A11 is overexpressed in many types of cancers and is associated with patients' poor prognosis. As a result, SLC7A11 becomes a new potential target for cancer therapy. In this review, we first briefly introduce the structure and function of SLC7A11, then discuss its pathological role in cancer. We next summarize current available data of how SLC7A11 is subjected to fine regulations at multiple levels. We further describe the potential inhibitors of the SLC7A11 and their roles in human cancer cells. Finally, we propose novel insights for future perspectives on the modulation of SLC7A11, as well as possible targeted strategies for SLC7A11-based anti-cancer therapies.

Cystine transporter SLC7A11/xCT in cancer: ferroptosis, nutrient dependency, and cancer therapy

The cystine/glutamate antiporter SLC7A11 (also commonly known as xCT) functions to import cystine for glutathione biosynthesis and antioxidant defense and is overexpressed in multiple human cancers. Recent studies revealed that SLC7A11 overexpression promotes tumor growth partly through suppressing ferroptosis, a form of regulated cell death induced by excessive lipid peroxidation. However, cancer cells with high expression of SLC7A11 (SLC7A11^high) also have to endure the significant cost associated with SLC7A11-mediated metabolic reprogramming, leading to glucose- and glutamine-dependency in SLC7A11^high cancer cells, which presents potential metabolic vulnerabilities for therapeutic targeting in SLC7A11^high cancer. In this review, we summarize diverse regulatory mechanisms of SLC7A11 in cancer, discuss ferroptosis-dependent and -independent functions of SLC7A11 in promoting tumor development, explore the mechanistic basis of SLC7A11-induced nutrient dependency in cancer cells, and conceptualize therapeutic strategies to target SLC7A11 in cancer treatment. This review will provide the foundation for further understanding SLC7A11 in ferroptosis, nutrient dependency, and tumor biology and for developing novel effective cancer therapies.

AKT but not MYC promotes reactive oxygen species-mediated cell death in oxidative culture

Oncogenes can create metabolic vulnerabilities in cancer cells. We tested how AKT (herein referring to AKT1) and MYC affect the ability of cells to shift between respiration and glycolysis. Using immortalized mammary epithelial cells, we discovered that constitutively active AKT, but not MYC, induced cell death in galactose culture, where cells rely on oxidative phosphorylation for energy generation. However, the negative effects of AKT were temporary, and AKT-expressing cells recommenced growth after ∼15 days in galactose. To identify the mechanisms regulating AKT-mediated cell death, we used metabolomics and found that AKT-expressing cells that were dying in galactose culture had upregulated glutathione metabolism. Proteomic profiling revealed that AKT-expressing cells dying in galactose also upregulated nonsense-mediated mRNA decay, a marker of sensitivity to oxidative stress. We therefore measured levels of reactive oxygen species (ROS) and discovered that galactose-induced ROS exclusively in cells expressing AKT. Furthermore, ROS were required for galactose-induced death of AKT-expressing cells. We then confirmed that galactose-induced ROS-mediated cell death in breast cancer cells with upregulated AKT signaling. These results demonstrate that AKT but not MYC restricts the flexibility of cancer cells to use oxidative phosphorylation.This article has an associated First Person interview with the first author of the paper.