System analysis based on the cuproptosis-related genes identifies LIPT1 as a novel therapy target for liver hepatocellular carcinoma

NMF typing and machine learning algorithm-based exploration of preeclampsia-related mechanisms on ferroptosis signature genes

BACKGROUND

Globally, pre-eclampsia (PE) poses a major threat to the health and survival of pregnant women and fetuses, contributing significantly to morbidity and mortality. Recent studies suggest a pathological link between PE and ferroptosis. We aim to utilize non-negative matrix factorization (NMF) clustering and machine learning algorithms to pinpoint disease-specific genes related to the process of ferroptosis in PE and investigate likely underlying biochemistry mechanisms.

METHODS

The acquisition of four microarray datasets from the Gene Expression Omnibus (GEO) repository, the integration of these datasets, and the elimination of batch effects formed the core procedure. Genes related to ferroptosis in PE (DE-FRG) were identified. NMF clustering was performed on DE-FRG for unsupervised analysis, generating a heatmap for clustering validation via principal component analysis. Immunocyte infiltration differences between different subtypes were compared to elucidate the impact of ferroptosis on immune infiltration in the placental tissue of PE patients. The application of weighted gene co-expression network analysis (WGCNA) revealed important module genes linked to sample subtypes and disease status. The screening of PE feature genes involved employing SVM, RF, GLM, and XGB machine learning algorithms, and their predictive performance was validated using various analyses and an external dataset. The iRegulon tool was utilized to predict upstream transcription factors associated with ferroptosis feature genes, from which differentially expressed transcription factors were screened to construct a "Transcription Factor-FRG-ferroptosis" regulatory network. Finally, in vitro (cultured cells) and in vivo (rat) models were utilized to evaluate the regulatory mechanisms of ferroptosis in normal and PE placental tissues.

RESULTS

Differential analysis of the four merged GEO datasets identified 41 DE-FRGs. NMF clustering based on DE-FRGs revealed two PE subtypes. Immunocyte infiltration analysis indicated significant differences in immune levels between these subtypes. Further WGCNA analysis identified module genes associated with PE and these two subtypes. Subsequently, we developed an integrated machine learning model incorporating five FRGs and validated its predictive efficacy using various analyses and an external validation dataset. Finally, based on the transcription factor ARID3A and ferroptosis feature genes EPHB3 and PAPPA2, we constructed a "Transcription Factor-FRG-ferroptosis" regulatory network, with in vitro and in vivo experiments confirming that ARID3A promotes the progression of PE and ferroptosis by activating the expression of EPHB3 and PAPPA2.

CONCLUSION

This analytical journey illuminated a critical regulatory nexus in PE, underscoring the central influence of ARID3A on PE through ferroptosis-mediated pathways.

Cuproptosis: a promising new target for breast cancer therapy

Breast cancer (BC) is the leading cause of cancer-related mortality among women globally, affecting approximately one-quarter of all female cancer patients and accounting for one-sixth of cancer-related deaths in women. Despite significant advancements in diagnostic and therapeutic approaches, breast cancer treatment remains challenging due to issues such as recurrence and metastasis. Recently, a novel form of regulated cell death, termed cuproptosis, has been identified. This process disrupts mitochondrial respiration by targeting the copper-dependent cellular pathways. The role of cuproptosis has been extensively investigated in various therapeutic contexts, including chemotherapy, immunotherapy, radiotherapy, and nanotherapy, with the development of novel drugs significantly improving clinical outcomes. This article aims to further elucidate the connection between cuproptosis and breast cancer, focusing on its therapeutic targets, signaling pathways, and potential biomarkers that could enhance treatment strategies. These insights may offer new opportunities for improved patient care and outcomes in breast cancer therapy.

Identification of cuproptosis-related genes in septic shock based on bioinformatic analysis

BACKGROUND

Septic shock is a life-threatening condition characterized by a failure of organ systems and a high mortality rate. Cuproptosis is a new form of cell death that is triggered by copper overload. However, the relationship between cuproptosis-related genes and septic shock remains unclear.

METHODS

The GSE26440 dataset from the GEO database was used to screen differentially expressed genes (DEGs) between control and septic shock samples. Additionally, hub genes related to the progression of septic shock and cuproptosis were screened by Venn analysis. RT-qPCR was utilized to validate the expression of hub genes in peripheral blood lymphocytes from septic shock patients and healthy controls. Next, functional analysis and immune cells infiltration were performed.

RESULTS

SLC31A1 and MTF1 levels were obviously elevated and LIAS and LIPT1 levels were downregulated in septic shock samples, compared to normal controls. The diagnostic values of the four genes were confirmed with receiver operating characteristic (ROC) curves. Additionally, SLC31A1 and MTF1 showed a positive correlation with natural killer cells and LIAS and LIPT1 exhibited a positive correlation with CD8+ T cells. Furthermore, compared to low-level groups, MAPK signaling was activated in the high-SLC31A1 level group, VEGF signaling was activated in the high-MTF1 level group and lipoic acid metabolism was activated in high-LIAS and high-LIPT1 level groups.

CONCLUSION

This study demonstrates that SLC31A1, MTF1, LIAS, and LIPT1 are dysregulated in septic shock samples, and these genes exhibit potential diagnostic efficacy in septic shock, suggesting that these genes may be potential biomarkers for the diagnosis of septic shock.

HSP90AA1 is an unfavorable prognostic factor for hepatocellular carcinoma and contributes to tumorigenesis and chemotherapy resistance

Hepatocellular carcinoma (HCC) is still one of the leading causes of tumor-related deaths. Accumulating evidence indicates that immunogenic cell death (ICD) could occur in tumor cells. However, ICD-related studies are limited in HCC. This study collected HCC RNA sequencing data from the Cancer Genome Atlas, International Cancer Genome Consortium, and Gene Expression Omnibus databases. R software was used to analyze the expression of ICD in HCC and to screen essential genes with prognostic value. qRT-PCR and WB determined the mRNA and protein expressions of hub gene. Cell viability assay, Clonal formation assay, and Live/dead staining assay were employed to determine the gene functions. After cross-analysis of differentially expressed genes (DEGs) and ICD-related genes (ICDRGs), 7 differentially expressed ICDRGs were identified in HCC. Of them, HSP90AA1, with the most excellent prognostic value in HCC, was selected, whose expression was also validated in public cohorts, cell lines, and clinical tissue samples. High HSP90AA1 expression indicated an inferior prognosis of HCC, and HSP90AA1 knockdown significantly suppressed cell viability and chemotherapy resistance of HCC. ICD-related gene HSP90AA1 was an unfavorable factor for HCC, and high HSP90AA1 expression contributed to tumor cell survival and chemotherapy resistance.

Machine Learning Integration with Single-Cell Transcriptome Sequencing Datasets Reveals the Impact of Tumor-Associated Neutrophils on the Immune Microenvironment and Immunotherapy Outcomes in Gastric Cancer

The characteristics of neutrophils play a crucial role in defining the tumor inflammatory environment. However, the function of tumor-associated neutrophils (TANs) in tumor immunity and their response to immune checkpoint inhibitors (ICIs) remains incompletely understood. By analyzing single-cell RNA sequencing data from over 600,000 cells in gastric cancer (GSE163558 and GSE183904), colorectal cancer (GSE205506), and lung cancer (GSE207422), we identified neutrophil subsets in primary gastric cancer that are associated with the treatment response to ICIs. Specifically, we focused on neutrophils with high expression of CD44 (CD44_NEU), which are abundant during tumor progression and exert significant influence on the gastric cancer immune microenvironment. Machine learning analysis revealed 22 core genes associated with CD44_NEU, impacting inflammation, proliferation, migration, and oxidative stress. In addition, multiple immunofluorescence staining and gastric cancer spatial transcriptome data (GSE203612) showed a correlation between CD44_NEU and T-cell infiltration in gastric cancer tissues. A risk score model derived from seven essential genes (AQP9, BASP1, BCL2A1, PLEK, PDE4B, PROK2, and ACSL1) showed better predictive capability for patient survival compared to clinical features alone, and integrating these scores with clinical variables resulted in a prognostic nomogram. Overall, this study highlights the heterogeneity of TANs, particularly the CD44_NEU critical influence on immunotherapy outcomes, paving the way for personalized treatment strategies.

BIRC5 knockdown ameliorates hepatocellular carcinoma progression via regulating PPARγ pathway and cuproptosis

BACKGROUND

Hepatocellular carcinoma (HCC) with complex molecular carcinogenesis represents a kind of prevalent neoplasm occurring in the liver. The objective of this study is to illustrate the function of baculoviral inhibitor of apoptosis repeat containing 5 (BIRC5) and underlying action mechanisms in HCC progression.

METHODS

Comprehensive bioinformatics methods were conducted to screen differentially expressed genes (DEGs), cuproptosis-associated DEGs, and hub genes. The correlation between BIRC5 and immune cell infiltration, prognosis value was evaluated. The specific effects of BIRC5 silencing on HCC cells was validated by functional assays, and the impact on tumorigenicity and cuproptosis was also elucidated in vivo. Additionally, the effects of BIRC5 deficiency on PPAR pathway were determined using Oroxin A in vitro.

RESULTS

A total of 45 cuproptosis-associated DEGs and 9 hub genes were discovered through bioinformatics. Then 6 core genes were confirmed in Hep-3B and SK-Hep-1 cells with 4 genes upregulated and 2 genes downregulated. Therein, BIRC5 was positively correlated with the infiltration of CD8+ T cells, macrophages, and highly expressed BIRC5 exhibited poor prognosis of overall survival in HCC. Furthermore, BIRC5 deletion inhibited the PPARγ pathway, thereby restraining the malignant phenotypes of HCC cells and tumorigenesis in vivo. Additionally, silencing of BIRC5 contributed to the initiation of cuproptosis in HCC.

CONCLUSIONS

BIRC5 silencing attenuated HCC through blocking PPARγ pathway and regulating cuproptosis, which may offer therapeutic implications against HCC.

Cuproptosis, ferroptosis and PANoptosis in tumor immune microenvironment remodeling and immunotherapy: culprits or new hope

Normal life requires cell division to produce new cells, but cell death is necessary to maintain balance. Dysregulation of cell death can lead to the survival and proliferation of abnormal cells, promoting tumor development. Unlike apoptosis, necrosis, and autophagy, the newly recognized forms of regulated cell death (RCD) cuproptosis, ferroptosis, and PANoptosis provide novel therapeutic strategies for tumor treatment. Increasing research indicates that the death of tumor and immune cells mediated by these newly discovered forms of cell death can regulate the tumor microenvironment (TME) and influence the effectiveness of tumor immunotherapy. This review primarily elucidates the molecular mechanisms of cuproptosis, ferroptosis, and PANoptosis and their complex effects on tumor cells and the TME. This review also summarizes the exploration of nanoparticle applications in tumor therapy based on in vivo and in vitro evidence derived from the induction or inhibition of these new RCD pathways.

Integration of bioinformatics analysis reveals ZNF248 as a potential prognostic and immunotherapeutic biomarker for LIHC: machine learning and experimental evidence

Liver hepatocellular carcinoma (LIHC) is a major contributor to cancer-related mortality worldwide, posing substantial diagnostic and therapeutic challenges. Although zinc finger proteins (ZNFs) are known to play a role in LIHC, the specific function of ZNF248 remains poorly understood. In this study, we analyzed genomic and clinical data from The Cancer Genome Atlas (TCGA) to elucidate the role of ZNF248 through differential expression analysis, bioenrichment, immune response correlation, and drug sensitivity evaluation. Machine learning was employed to identify prognostic signatures derived from ZNF248, which were further validated using Receiver Operating Characteristic (ROC) analysis. Functional assays, including Western blot and rescue experiments, were performed to assess the impact of ZNF248 on the PI3K/AKT signaling pathway. Our results demonstrate that ZNF248 is significantly overexpressed in LIHC patients and is associated with poor prognosis. Bioenrichment analysis revealed activation of oncogenic pathways, and elevated ZNF248 expression correlated with increased immune cell infiltration and enhanced immune scores, thereby influencing both immunotherapy response and drug sensitivity. Functional assays further confirmed that ZNF248 promotes LIHC progression and invasion, while silencing ZNF248 inhibited the PI3K/AKT pathway - a phenomenon reversible by the AKT activator SC79. These findings suggest that ZNF248 contributes to LIHC progression through the PI3K/AKT pathway and may represent a novel immunotherapeutic target and prognostic biomarker for LIHC.

Integrated multiomics characterization reveals cuproptosis-related hub genes for predicting the prognosis and clinical efficacy of ovarian cancer

Background

As a prevalent malignancy in women, ovarian cancer (OC) presents a challenge in clinical practice because of its poor prognosis and poor therapeutic efficacy. The mechanism by which cuproptosis activity is accompanied by immune infiltration in OC remains unknown. Here, we investigated cuproptosis-related OC subtypes and relevant immune landscapes to develop a risk score (RS) model for survival prediction.

Methods

Cuproptosis-related genes (CRGs) were identified to construct molecular subtypes via an unsupervised clustering algorithm based on the expression profiles of survival-related CRGs in the GEO database. Single-cell datasets were used to estimate immune infiltration among subtypes. The RS oriented from molecular subtypes was developed via LASSO Cox regression in the TCGA OC dataset and independently validated in the GEO and TCGA datasets. Hub markers from RS were identified in tissues and cell lines. The function of the key gene from RS was identified in vitro.

Results

We investigated cuproptosis activity and immune infiltration to establish three clinical subtypes of OC based the differentially expressed genes (DEGs) from CRGs to create an RS model validated for clinical efficacy and prognosis. Six hub genes from the RS served as ongenic markers in OC tissues and cell lines. The function of GAS1 in the RS model revealed that it exerts oncogenic effects.

Conclusions

Our study provides a novel RS model including 6 hub genes associated with cuproptosis and immune infiltration to predict OC prognosis as well as clinical efficacy.

Copper homeostasis and copper-induced cell death in tumor immunity: implications for therapeutic strategies in cancer immunotherapy

Copper is an important trace element for maintaining key biological functions such as cellular respiration, nerve conduction, and antioxidant defense. Maintaining copper homeostasis is critical for human health, and its imbalance has been linked to various diseases, especially cancer. Cuproptosis, a novel mechanism of copper-induced cell death, provides new therapeutic opportunities for metal ion regulation to interact with cell fate. This review provides insights into the complex mechanisms of copper metabolism, the molecular basis of cuproptosis, and its association with cancer development. We assess the role of cuproptosis-related genes (CRGs) associated with tumorigenesis, their importance as prognostic indicators and therapeutic targets, and the impact of copper homeostasis on the tumor microenvironment (TME) and immune response. Ultimately, this review highlights the complex interplay between copper, cuproptosis, and cancer immunotherapy.

Copper homeostasis and cuproptosis in health and disease

Copper is a vital trace element in human physiology, essential for the synthesis of numerous crucial metabolic enzymes and facilitation of various biological processes. Regulation of copper levels within a narrow range is imperative for maintaining metabolic homeostasis. Numerous studies have demonstrated the significant roles of copper homeostasis and cuproptosis in health and disease pathogenesis. However, a comprehensive and up-to-date systematic review in this domain remains absent. This review aims to consolidate recent advancements in understanding the roles of cuproptosis and copper homeostasis in health and disease, focusing on the underlying mechanisms and potential therapeutic interventions. Dysregulation of copper homeostasis, manifesting as either copper excess or deficiency, is implicated in the etiology of various diseases. Cuproptosis, a recently identified form of cell death, is characterized by intracellular copper overload. This phenomenon mediates a diverse array of evolutionary processes in organisms, spanning from health to disease, and is implicated in genetic disorders, liver diseases, neurodegenerative disorders, and various cancers. This review provides a comprehensive summary of the pathogenic mechanisms underlying cuproptosis and copper homeostasis, along with associated targeted therapeutic agents. Furthermore, it explores future research directions with the potential to yield significant advancements in disease treatment, health management, and disease prevention.

Identification of diagnostic markers and molecular clusters of cuproptosis-related genes in alcohol-related liver disease based on machine learning and experimental validation

Background and aims

Alcohol-related liver disease (ALD) is a worldwide burden. Cuproptosis has been shown to play a key role in the development of several diseases. However, the role and mechanisms of cuproptosis in ALD remain unclear.

Methods

The RNA-sequencing data of ALD liver samples were downloaded from the Gene Expression Omnibus (GEO) database. Bioinformatical analyses were performed using the R data package. We then identified key genes through multiple machine learning methods. Immunoinfiltration analyses were used to identify different immune cells in ALD patients and controls. The expression levels of key genes were further verified.

Results

We identified three key cuproptosis-related genes (CRGs) (DPYD, SLC31A1, and DBT) through an in-depth analysis of two GEO datasets, including 28 ALD samples and eight control samples. The area under the curve (AUC) value of these three genes combined in determining ALD was 1.0. In the external datasets, the three key genes had AUC values as high as 1.0 and 0.917, respectively. Nomogram, decision curve, and calibration curve analyses also confirmed these genes' ability to predict the diagnosis. These three key genes were found to be involved in multiple pathways associated with ALD progression. We confirmed the mRNA expression of these three key genes in mouse ALD liver samples. Regarding immune cell infiltration, the numbers of B cells, CD8 (+) T cells, NK cells, T-helper cells, and Th1 cells were significantly lower in ALD patient samples than in control liver samples. Single sample gene set enrichment analysis (ssGSEA) was then used to estimate the immune microenvironment of different CRG clusters and CRG-related gene clusters. In addition, we calculated CRG scores through principal component analysis (PCA) and selected Sankey plots to represent the correlation between CRG clusters, gene clusters, and CRG scores. Finally, the three key genes were confirmed in mouse ALD liver samples and liver cells treated with ethanol.

Conclusions

We first established a prognostic model for ALD based on 3 CRGs and robust prediction efficacy was confirmed. Our investigation contributes to a comprehensive understanding of the role of cuproptosis in ALD, presenting promising avenues for the exploration of therapeutic strategies.

Construction and validation of a TAMRGs prognostic signature for gliomas by integrated analysis of scRNA and bulk RNA sequencing data

BACKGROUND

This study aimed to construct and validate a prognostic model based on tumor associated macrophage-related genes (TAMRGs) by integrating single-cell RNA sequencing (scRNA-seq) and bulk RNA sequencing (bulk RNA-seq) data.

METHODS

The scRNA-seq data of three inhouse glioma tissues were used to identify the tumor-associated macrophages (TAMs) marker genes, the DEGs from the The Cancer Genome Atlas (TCGA) - Genotype-Tissue Expression (GTEx) dataset were used to further select TAMs marker genes. Subsequently, a TAMRG-score was constructed by Least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox regression analysis in the TCGA dataset and validated in the Chinese Glioma Genome Atlas (CGGA) dataset.

RESULTS

We identified 186 TAMs marker genes, and a total of 6 optimal prognostic genes including CKS2, LITAF, CTSB, TWISTNB, PPIF and G0S2 were selected to construct a TAMRG-score. The high TAMRG-score was significantly associated with worse prognosis (log-rank test, P<0.001). Moreover, the TAMRG-score outperformed the other three models with AUC of 0.808. Immune cell infiltration, TME scores, immune checkpoints, TMB and drug susceptibility were significantly different between TAMRG-score groups. In addition, a nomogram were constructed by combing the TAMRG-score and clinical information (Age, Grade, IDH mutation and 1p19q codeletion) to predict the survival of glioma patients with AUC of 0.909 for 1-year survival.

CONCLUSION

The high TAMRG-score group was associated with a poor prognosis. A nomogram by incorporating TMARG-score could precisely predict glioma survival, and provide evidence for personalized treatment of glioma.

Transcriptomic profiling and risk assessment in bladder cancer: Insights from copper death-related genes

BACKGROUND

The study aimed to investigate the role of copper death-related genes (CRGs) in bladder cancer (BC) for improved prognosis assessment.

METHODS

Multi-omics techniques were utilized to analyze CRG expression in BC tissues from TCGA and GEO databases. Consensus clustering categorized patients into molecular subtypes based on clinical characteristics and immune cell infiltration.

RESULTS

An innovative risk assessment model identified eight critical genes associated with BC risk. In vitro and in vivo experiments validated LIPT1's significant impact on copper-induced cell death, proliferation, migration, and invasion in BC.

CONCLUSION

This multi-omics analysis elucidates the pivotal role of CRGs in BC progression, suggesting enhanced risk assessment through molecular subtype categorization and identification of key genes like LIPT1. Insights into these mechanisms offer the potential for improved diagnosis and treatment strategies for BC patients.

Construction of a prognostic model for ovarian cancer based on a comprehensive bioinformatics analysis of cuproptosis-associated long non-coding RNA signatures

Ovarian cancer (OCa) is a common malignancy in women, and the role of cuproptosis and its related genes in OCa is unclear. Using the GSE14407 dataset, we analyzed the expression and correlation of cuproptosis-related genes (CRGs) between tumor and normal groups. From the TCGA-OV dataset, we identified 20 cuproptosis-related long non-coding RNAs (CuLncs) associated with patient survival through univariate Cox analysis. OCa patients were divided into early-stage and late-stage groups to analyze CuLncs expression. Cluster analysis classified patients into two clusters, with Cluster1 having a poorer prognosis. Significant differences in "Lymphatic Invasion" and "Cancer status" were observed between clusters. Seven CRGs showed significant expression differences, validated using the human protein atlas (HPA) databases. Immune analysis revealed a higher ImmuneScore in Cluster1. GSEA identified associated signaling pathways. LASSO regression included 11 CuLncs to construct and validate a survival prediction model, classifying patients into high-risk and low-risk groups. Correlations between riskScore, Cluster phenotype, ImmuneScore, and immune cell infiltration were explored. Cell experiments showed that knocking down AC023644.1 decreases OCa cell viability. In conclusion, we constructed an accurate prognostic model for OCa based on 11 CuLncs, providing a basis for prognosis assessment and potential immunotherapy targets.

Mechanisms of cuproptosis and its relevance to distinct diseases

Copper is a trace element required by the organism, but once the level of copper exceeds the threshold, it becomes toxic and even causes death. The underlying mechanisms of copper-induced death are inconclusive, with different studies showing different opinions on the mechanism of copper-induced death. Multiple investigations have shown that copper induces oxidative stress, endoplasmic reticulum stress, nucleolar stress, and proteasome inhibition, all of which can result in cell death. The latest research elucidates a copper-dependent death and denominates it as cuproptosis. Cuproptosis takes place through the combination of copper and lipoylated proteins of the tricarboxylic acid cycle, triggering agglomeration of lipoylated proteins and loss of iron-sulfur cluster proteins, leading to proteotoxic stress and ultimately death. Given the toxicity and necessity of copper, abnormal levels of copper lead to diseases such as neurological diseases and cancer. The development of cancer has a high demand for copper, neurological diseases involve the change of copper contents and the binding of copper to proteins. There is a close relationship between these two kinds of diseases and copper. Here, we summarize the mechanisms of copper-related death, and the association between copper and diseases, to better figure out the influence of copper in cell death and diseases, thus advancing the clinical remedy of these diseases.

The functions of cuproptosis in gastric cancer: therapy, diagnosis, prognosis

Gastric cancer (GC) is the fifth most prevalent type of cancer in the whole world. Cuproptosis is discovered as a programmed cell death pathway and connected to cells' growth and death, as well as tumorigenesis. The relationship between cuproptosis and GC is still elusive. Two aspects of this study will elaborate the relationship between cuproptosis and immunotherapy as well as biomarkers in GC. Notably, the herein review is intended to highlight what has been accomplished regarding the cuproptosis for the diagnosis, immunotherapy, and prognosis in GC. The aim of this study is to offer a potential directions and the strategies for future research regarding cuproptosis inside the GC.

Cuproptosis, the novel type of oxidation-induced cell death in thoracic cancers: can it enhance the success of immunotherapy?

Copper is an important metal micronutrient, required for the balanced growth and normal physiological functions of human organism. Copper-related toxicity and dysbalanced metabolism were associated with the disruption of intracellular respiration and the development of various diseases, including cancer. Notably, copper-induced cell death was defined as cuproptosis which was also observed in malignant cells, representing an attractive anti-cancer instrument. Excess of intracellular copper leads to the aggregation of lipoylation proteins and toxic stress, ultimately resulting in the activation of cell death. Differential expression of cuproptosis-related genes was detected in normal and malignant tissues. Cuproptosis-related genes were also linked to the regulation of oxidative stress, immune cell responses, and composition of tumor microenvironment. Activation of cuproptosis was associated with increased expression of redox-metabolism-regulating genes, such as ferredoxin 1 (FDX1), lipoic acid synthetase (LIAS), lipoyltransferase 1 (LIPT1), dihydrolipoamide dehydrogenase (DLD), drolipoamide S-acetyltransferase (DLAT), pyruvate dehydrogenase E1 subunit alpha 1 (PDHA1), and pyruvate dehydrogenase E1 subunit beta (PDHB)). Accordingly, copper-activated network was suggested as an attractive target in cancer therapy. Mechanisms of cuproptosis and regulation of cuproptosis-related genes in different cancers and tumor microenvironment are discussed in this study. The analysis of current findings indicates that therapeutic regulation of copper signaling, and activation of cuproptosis-related targets may provide an effective tool for the improvement of immunotherapy regimens.

Cuproptosis in cancer: biological implications and therapeutic opportunities

Cuproptosis, a newly identified copper (Cu)-dependent form of cell death, stands out due to its distinct mechanism that sets it apart from other known cell death pathways. The molecular underpinnings of cuproptosis involve the binding of Cu to lipoylated enzymes in the tricarboxylic acid cycle. This interaction triggers enzyme aggregation and proteotoxic stress, culminating in cell death. The specific mechanism of cuproptosis has yet to be fully elucidated. This newly recognized form of cell death has sparked numerous investigations into its role in tumorigenesis and cancer therapy. In this review, we summarized the current knowledge on Cu metabolism and its link to cancer. Furthermore, we delineated the molecular mechanisms of cuproptosis and summarized the roles of cuproptosis-related genes in cancer. Finally, we offered a comprehensive discussion of the most recent advancements in Cu ionophores and nanoparticle delivery systems that utilize cuproptosis as a cutting-edge strategy for cancer treatment.

Identification and experimental validation of cuproptosis regulatory program in a sepsis immune microenvironment through a combination of single-cell and bulk RNA sequencing

Background

In spite of its high mortality rate and poor prognosis, the pathogenesis of sepsis is still incompletely understood. This study established a cuproptosis-based risk model to diagnose and predict the risk of sepsis. In addition, the cuproptosis-related genes were identified for targeted therapy.

Methods

Single-cell sequencing analyses were used to characterize the cuproptosis activity score (CuAS) and intercellular communications in sepsis. Differential cuproptosis-related genes (CRGs) were identified in conjunction with single-cell and bulk RNA sequencing. LASSO and Cox regression analyses were employed to develop a risk model. Three external cohorts were conducted to assess the model's accuracy. Differences in immune infiltration, immune cell subtypes, pathway enrichment, and the expression of immunomodulators were further evaluated in distinct groups. Finally, various in-vitro experiments, such as flow cytometry, Western blot, and ELISA, were used to explore the role of LST1 in sepsis.

Results

ScRNA-seq analysis demonstrated that CuAS was highly enriched in monocytes and was closely related to the poor prognosis of sepsis patients. Patients with higher CuAS exhibited prominent strength and numbers of cell-cell interactions. A total of five CRGs were identified based on the LASSO and Cox regression analyses, and a CRG-based risk model was established. The lower riskScore cohort exhibited enhanced immune cell infiltration, elevated immune scores, and increased expression of immune modulators, indicating the activation of an antibacterial response. Ultimately, in-vitro experiments demonstrated that LST1, a key gene in the risk model, was enhanced in the macrophage in response to LPS, which was closely related to the decrease of macrophage survival rate, the enhancement of apoptosis and oxidative stress injury, and the imbalance of the M1/M2 phenotype.

Conclusions

This study constructed a cuproptosis-related risk model to accurately predict the prognosis of sepsis. We further characterized the cuproptosis-related gene LST1 to provide a theoretical framework for sepsis therapy.

Cuproptosis in lung cancer: mechanisms and therapeutic potential

Cuproptosis, a recently identified form of cell death that differs from other forms, is induced by the disruption of the binding of copper to mitochondrial respiratory acylation components. Inducing cell cuproptosis and targeting cell copper death pathways are considered potential directions for treating tumor diseases. We have provided a detailed introduction to the metabolic process of copper. In addition, this study attempts to clarify and summarize the relationships between cuproptosis and therapeutic targets and signaling pathways of lung cancer. This review aims to summarize the theoretical achievements for translating the results of lung cancer and cuproptosis experiments into clinical treatment.

Clinical features and molecular landscape of cuproptosis signature-related molecular subtype in gastric cancer

Recent studies have highlighted the biological significance of cuproptosis in disease occurrence and development. However, it remains unclear whether cuproptosis signaling also has potential impacts on tumor initiation and prognosis of gastric cancer (GC). In this study, 16 cuproptosis-related genes (CRGs) transcriptional profiles were harnessed to perform the regularized latent variable model-based clustering in GC. A cuproptosis signature risk scoring (CSRS) scheme, based on a weighted sum of principle components of the CRGs, was used to evaluate the prognosis and risk of individual tumors of GC. Four distinct cuproptosis signature-based clusters, characterized by differential expression patterns of CRGs, were identified among 1136 GC samples across three independent databases. The four clusters were also associated with different clinical outcomes and tumor immune contexture. Based on the CSRS, GC patients can be divided into CSRS-High and CSRS-Low subtypes. We found that DBT, MTF1, and ATP7A were significantly elevated in the CSRS-High subtype, while SLC31A1, GCSH, LIAS, DLAT, FDX1, DLD, and PDHA1 were increased in the CSRS-Low subtype. Patients with CSRS-Low score were characterized by prolonged survival time. Further analysis indicated that CSRS-Low score also correlated with greater tumor mutation burden (TMB) and higher mutation rates of significantly mutated genes (SMG) in GC. In addition, the CSRS-High subtype harbored more significantly amplified focal regions related to tumorigenesis (3q27.1, 12p12.1, 11q13.3, etc.) than the CSRS-Low tumors. Drug sensitivity analyses revealed the potential compounds for the treatment of gastric cancer with CSRS-High score, which were experimentally validated using GC cells. This study highlights that cuproptosis signature-based subtyping is significantly associated with different clinical features and molecular landscape of GC. Quantitative evaluation of the CSRS of individual tumors will strengthen our understanding of the occurrence and development of cuproptosis and the treatment progress of GC.

Distinct cuproptosis patterns in hepatocellular carcinoma patients correlate with unique immune microenvironment characteristics and cell-cell communication, contributing to varied overall survival outcomes

Background

Hepatocellular carcinoma (HCC), a prevalent cancer, is linked to cuproptosis in tumor progression. However, cuproptosis's impact on HCC prognosis and its role in the tumor microenvironment remain unclear. We aimed to explore the correlation between cellular cuproptosis and the immune microenvironment in HCC, providing potential immunotherapeutic insights.

Methods

Examining cuproptosis-related genes and the immune microenvironment through consensus clustering and WGCNA. Risk models were constructed using LASSO Cox analysis and validated in an independent cohort. Gene expression data from The Cancer Genome Atlas (TCGA) database and single-cell RNA sequencing (scRNA-seq) data from the Gene Expression Omnibus (GEO) database were utilized. We scored cuproptosis expression and explored immunoinfiltration and cell-cell communication. Differential signals in T_memory cells were compared across different cuproptosis levels.

Results

Cuproptosis genes associated with fibroblast recruitment (GLS) and macrophage infiltration (FDX1). Liver cancer patients categorized into two subtypes based on cuproptosis gene expression. High expression of DLAT, GLS, and CDKN2A linked to immunosuppression (TGF-β), while high FDX1, MTF1, LIAS, and LIPT1 expression enhanced communication with non-immune cells. Developed reliable prognostic signature score and nomogram using cuproptosis-related genes. Single-cell analysis revealed differences in T_memory and TAM infiltration based on cuproptosis scores, with SPP1 and MIF as dominant signaling molecules. Finally, the results of in vitro experiments showed that when DLAT or CDKN2A was knocked down, the proliferation, migration, and invasion of HCC cells were significantly decreased.

Conclusion

Our study demonstrates that cuproptosis affects the immune microenvironment and cell-cell communication. Identified 9 genetic markers predicting survival outcomes and immunotherapy responses. Evaluating cuproptosis signaling can optimize immunotherapeutic strategies for hepatocellular carcinoma.

Targeting PRKDC activates the efficacy of antitumor immunity while sensitizing to chemotherapy and targeted therapy in liver hepatocellular carcinoma

BACKGROUND

Liver hepatocellular carcinoma (LIHC) ranks among the malignancies with the highest mortality rates, primarily due to chemoresistance culminating in treatment failure. Despite its impact, predictive models addressing disease progression, tumor microenvironment, and drug sensitivity remain elusive for LIHC patients. Recognizing the significant influence of various programmed cell death (PCD) modes on tumor evolution, this study investigates PCD genes to elucidate their implications on the prognosis and immune landscape of LIHC.

METHODS

To develop the classification and model, we employed a total of 17 genes associated with PCD patterns. To collect data, we acquired gene expression profiles, somatic mutation information, copy number variation data, and corresponding clinical data from the TCGA database, specifically from LIHC patients. Moreover, we obtained spatial transcriptome data and additional bulk datasets from the Gene Expression Omnibus (GEO) database to conduct further analysis. Various experiments were conducted to validate the role of the PCD gene PRKDC in proliferation, migration, invasion, EMT, cell cycle, therapeutic sensitivity, and antitumor immunity.

RESULTS

A novel LIHC classification based on these genes divided patients into two clusters, C1 and C2. The C2 cluster exhibited characteristics indicative of poor prognosis and an immune-activated microenvironment. This group showed greater response potential to immune checkpoint inhibitors, displaying higher levels of certain immune signatures and receptors. A programmed cell death index (PCDI) was constructed using 17 selected PCD genes. This index could effectively predict patient prognosis, with higher PCDI indicating poorer survival rates and a more pro-tumor microenvironment. Immune landscapes revealed varying interactions with PCDI, suggesting therapeutic targets and insights into treatment resistance. Moreover, experiments results suggested that PRKDC can augment the invasive nature and growth of malignant cells and it can serve as a potential target for therapy, offering hope for ameliorating the prognosis of LIHC patients.

CONCLUSIONS

The study uncovers the insights of programmed cell death in the prognosis and potential therapeutic interventions. And we found that PRKDC can serve as a target for enhancing the efficacy of antitumor immunity while sensitizing chemotherapy and targeted therapy in liver hepatocellular carcinoma.

A cuproptosis-based prognostic model for predicting survival in low-grade glioma

BACKGROUND

It is unknown what variables contribute to the formation and multiplication of low-grade gliomas (LGG). An emerging process of cell death is called cuproptosis. Our research aims to increase therapeutic options and gain a better understanding of the role that cuproptosis-related genes play in the physical characteristics of low-grade gliomas.

METHODS

The TCGA database was utilized to find cuproptosis genes that may be used to develop LGG risk model. Cox analysis in three different formats: univariate, multivariate, and LASSO. The gene signature's independent predictive ability was assessed using ROC curves and Cox regression analysis based on overall survival. Use of CGGA data and nomogram model for external validation Immunohistochemistry, gene mutation, and functional enrichment analysis are also employed to clarify risk models' involvement. Next, we analyzed changes in the immunological microenvironment in the risk model and forecasted possible chemotherapeutic drugs to target each group. Finally, we validated the protein expression levels of cuproptosis-related genes using LGG and adjacent normal tissues in a small self-case-control study.

RESULTS

This study developed a glioma predictive model based on five cuproptosis-associated genes. Compared to the high-risk group, the low-risk group's OS was significantly longer. The ROC curves showed high genetic signature performance in both groups. The signature-based categorisation was also linked to clinical characteristics and molecular subgroups. The prognosis of individuals with grade 2 or 3 glioma is also influenced by our risk model. Immunological testing revealed that the high-risk group had more immune cells and immunological function. The risk model also predicted immunotherapy and chemotherapy medication results. Also, this study confirmed that the expression of cuproptosis-related genes by Western blot.

CONCLUSION

We developed a prediction model for LGG patients using genes associated with cuproptosis. With acceptable prediction performance, this risk model may effectively stratify the prognosis of glioma patients.

Epigenetic regulation of diverse cell death modalities in cancer: a focus on pyroptosis, ferroptosis, cuproptosis, and disulfidptosis

Tumor is a local tissue hyperplasia resulted from cancerous transformation of normal cells under the action of various physical, chemical and biological factors. The exploration of tumorigenesis mechanism is crucial for early prevention and treatment of tumors. Epigenetic modification is a common and important modification in cells, including DNA methylation, histone modification, non-coding RNA modification and m6A modification. The normal mode of cell death is programmed by cell death-related genes; however, recent researches have revealed some new modes of cell death, including pyroptosis, ferroptosis, cuproptosis and disulfidptosis. Epigenetic regulation of various cell deaths is mainly involved in the regulation of key cell death proteins and affects cell death by up-regulating or down-regulating the expression levels of key proteins. This study aims to investigate the mechanism of epigenetic modifications regulating pyroptosis, ferroptosis, cuproptosis and disulfidptosis of tumor cells, explore possible triggering factors in tumor development from a microscopic point of view, and provide potential targets for tumor therapy and new perspective for the development of antitumor drugs or combination therapies.

Prognostic prediction using a gene signature developed based on exhausted T cells for liver cancer patients

Background

Liver hepatocellular carcinoma (LIHC) is a solid primary malignancy with poor prognosis. This study discovered key prognostic genes based on T cell exhaustion and used them to develop a prognostic prediction model for LIHC.

Methods

SingleR's annotations combined with Seurat was used to automatically annotate the single-cell clustering results of the LIHC dataset GSE166635 downloaded from the Gene Expression Omnibus (GEO) database and to identify clusters related to exhausted T cells. Patients were classified using ConsensusClusterPlus package. Next, weighted gene co-expression network analysis (WGCNA) package was employed to distinguish key gene module, based on which least absolute shrinkage and selection operator (Lasso) and multi/univariate cox analysis were performed to construct a RiskScore system. Kaplan-Meier (KM) analysis and receiver operating characteristic curve (ROC) were employed to evaluate the efficacy of the model. To further optimize the risk model, a nomogram capable of predicting immune infiltration and immunotherapy sensitivity in different risk groups was developed. Expressions of genes were measured by quantitative real-time polymerase chain reaction (qRT-PCR), and immunofluorescence and Cell Counting Kit-8 (CCK-8) were performed for analyzing cell functions.

Results

We obtained 18,413 cells and clustered them into 7 immune and non-immune cell subpopulations. Based on highly variable genes among T cell exhaustion clusters, 3 molecular subtypes (C1, C2 and C3) of LIHC were defined, with C3 subtype showing the highest score of exhausted T cells and a poor prognosis. The Lasso and multivariate cox analysis selected 7 risk genes from the green module, which were closely associated with the C3 subtype. All the patients were divided into low- and high-risk groups based on the medium value of RiskScore, and we found that high-risk patients had higher immune infiltration and immune escape and poorer prognosis. The nomogram exhibited a strong performance for predicting long-term LIHC prognosis. In vitro experiments revealed that the 7 risk genes all had a higher expression in HCC cells, and that both liver HCC cell numbers and cell viability were reduced by knocking down MMP-9.

Conclusion

We developed a RiskScore model for predicting LIHC prognosis based on the scRNA-seq and RNA-seq data. The RiskScore as an independent prognostic factor could improve the clinical treatment for LIHC patients.

Development of machine learning-based malignant pericardial effusion-related model in breast cancer: Implications for clinical significance, tumor immune and drug-therapy

Background

Malignant pericardial effusion (MPE) is a common complication of advanced breast cancer (BRCA) and plays an important role in BRCA. This study is aims to construct a prognostic model based on MPE-related genes for predicting the prognosis of breast cancer.

Methods

The BRCA samples are analyzed based on the expression of MPE-related genes by using an unsupervised cluster analysis method. This study processes the data by least absolute shrinkage and selection operator and multivariate Cox analysis, and uses machine learning algorithms to construct BRCA prognostic model and develop web tool.

Results

BRCA patients are classified into three clusters and a BRCA prognostic model is constructed containing 9 MPE-related genes. There are significant differences in signature pathways, immune infiltration, immunotherapy response and drug sensitivity testing between the high and low-risk groups. Of note, a web-based tool (http://wys.helyly.top/cox.html) is developed to predict overall survival as well as drug-therapy response of BRCA patients quickly and conveniently, which can provide a basis for clinicians to formulate individualized treatment plans.

Conclusion

The MPE-related prognostic model developed in this study can be used as an effective tool for predicting the prognosis of BRCA and provides new insights for the diagnosis and treatment of BRCA patients.

Creation of signatures and identification of molecular subtypes based on disulfidptosis-related genes for glioblastoma patients' prognosis and immunological activity

BACKGROUND

In recent times, disulfidptosis, an intricate form of cellular demise, has garnered attention due to its impact on prognosis, tumor progression and treatment response. Nevertheless, the exact significance of disulfidptosis-related genes (DisRGs) in glioblastoma (GBM) remains enigmatic.

METHODS

The GEO and TCGA databases provided transcriptional and clinically relevant data on tumor samples, while the GTEx database provided data on healthy tissues. Disulfidptosis-related genes (DisRGs) were procured from previous scholarly investigations. The expression profile of DisRGs was initially scrutinized among patients diagnosed with GBM, subsequent to which their prognostic value was explored. Through consensus clustering, we constructed DisRGs-related clusters and gene subtypes. Our results established that the DisRG-related clusters had differentially expressed genes, resulting in a DisulfidptosisScore model, which had a positive prognostic value.

RESULTS

The differential expression profile of 24 DisRGs between GBM samples and healthy samples was acquired. Through consensus cluster analysis, two distinct disulfidptosis subtypes, namely DisRGcluster A and DisRGcluster B, were identified. Then, the DisulfidptosisScore model including 4 characteristic genes was constructed.Notably, patients with GBM assigned with lower score demonstrated a considerably longer overall survival (OS) compared to those with higher score.

CONCLUSION

We have effectively devised a prognostic model associated with disulfidptosis, presenting autonomous prognostic predictions for patients with GBM. These findings serve as a valuable addition to the current comprehension of disulfidptosis and offer fresh theoretical substantiation for the development of enhanced treatment strategies.

Construction of a Lung Adenocarcinoma Prognostic Model Utilizing Serine and Glycine Metabolism-Related Genes

The objective of this study was to construct a prognostic model by utilizing serine/glycine metabolism-related genes (SGMGs), thus establishing a risk score for lung adenocarcinoma (LUAD). Based on the TCGA-LUAD and SGMG data set, two subtypes with different SGMG expression levels were identified by clustering analysis. Thirteen differential expression genes were used to construct RiskScore by Cox regression. GSE72094 data set was used for validation. The survival characteristics, immune features, and potential benefits of chemotherapy drugs were analyzed for two risk groups. RiskScore was constructed based on the genes ABCC12, RIC3, CYP4B1, SFTPB, CACNA2D2, IGF2BP1, NTSR1, DKK1, CREG2, PITX3, RGS20, FETUB, and IGFBP1. Patients in the low-risk (LR) group exhibited a superior overall survival. In addition, aDCs, iDSs, mast cells, neutrophils, HLA, and type II IFN were more abundant in the LR group with higher IPS scores and lower TIDE scores. In contrast, NK cells, APC coinhibition, and MHC-I were more common in the high-risk (HR) group, which may be more sensitive to chemotherapy drugs such as cisplatin, oxaliplatin, and nilotinib. RiskScore was a promising biomarker that can be used to distinguish LUAD prognosis, immune features, and sensitivity to chemotherapy drugs.

Copper Metabolism and Cuproptosis: Molecular Mechanisms and Therapeutic Perspectives in Neurodegenerative Diseases

Copper is an essential trace element, and plays a vital role in numerous physiological processes within the human body. During normal metabolism, the human body maintains copper homeostasis. Copper deficiency or excess can adversely affect cellular function. Therefore, copper homeostasis is stringently regulated. Recent studies suggest that copper can trigger a specific form of cell death, namely, cuproptosis, which is triggered by excessive levels of intracellular copper. Cuproptosis induces the aggregation of mitochondrial lipoylated proteins, and the loss of iron-sulfur cluster proteins. In neurodegenerative diseases, the pathogenesis and progression of neurological disorders are linked to copper homeostasis. This review summarizes the advances in copper homeostasis and cuproptosis in the nervous system and neurodegenerative diseases. This offers research perspectives that provide new insights into the targeted treatment of neurodegenerative diseases based on cuproptosis.

Pathogenomics model for personalized medicine in cervical cancer: Cross-talk of gene expressions and pathological images related to oxidative stress

An increasing number of studies have shown that oxidative stress plays an important role in the development and progression of cancer. Cervical cancer (CC) is a disease of unique complexity that tends to exhibit high heterogeneity in molecular phenotypes. We aim here to characterize molecular features of cervical cancer by developing a classification system based on oxidative stress-related gene expression profiles. In this study, we obtained gene expression profiling data for cervical cancer from the TCGA (The Cancer Genome Atlas) and GEO (Gene Expression Omnibus) (GSE44001) databases. Oxidative stress-related genes used for clustering were obtained from GeneCards. Patients with cervical cancer were divided into two subtypes (C1 and C2) by non-negative matrix factorization (NMF) classification. By performing Kaplan-Meier survival analysis, differential expression analysis, and gene set enrichment analysis (GSEA) between the two subtypes, we found that subtype C2 had a worse prognosis and was highly enriched for immune-related pathways as well as epithelial-mesenchymal transition (EMT) pathways. Subsequently, we performed metabolic pathway analysis, gene mutation landscape analysis, immune microenvironment analysis, immunotherapy response analysis, and drug sensitivity analysis of the two isoforms. The results showed that the isoforms were significantly different between metabolic pathway enrichment and the immune microenvironment, and the chromosomes of subtype C1 were more unstable. In addition, we found that subtype C2 tends to respond to treatment with anti-CTLA4 agents, a conclusion that coincides with high chromosomal variation in C1, as well as C2 enrichment of immune-related pathways. Then, we screened 10 agents that were significantly susceptible to C2 subtype. Finally, we constructed pathogenomics models based on pathological features and linked them to molecular subtypes. This study establishes a novel CC classification based on gene expression profiles of oxidative stress-related genes and elucidates differences between immune microenvironments between CC subtypes, contributing to subtype-specific immunotherapy and drug therapy.

Immunomodulation of cuproptosis and ferroptosis in liver cancer

According to statistics, the incidence of liver cancer is increasing yearly, and effective treatment of liver cancer is imminent. For early liver cancer, resection surgery is currently the most effective treatment. However, resection does not treat the disease in advanced patients, so finding a method with a better prognosis is necessary. In recent years, ferroptosis and cuproptosis have been gradually defined, and related studies have proved that they show excellent results in the therapy of liver cancer. Cuproptosis is a new form of cell death, and the use of cuproptosis combined with ferroptosis to inhibit the production of hepatocellular carcinoma cells has good development prospects and is worthy of in-depth discussion by researchers. In this review, we summarize the research progress on cuproptosis combined with ferroptosis in treating liver cancer, analyze the value of cuproptosis and ferroptosis in the immune of liver cancer, and propose potential pathways in oncotherapy with the combination of cuproptosis and ferroptosis, which can provide background knowledge for subsequent related research.

Copper homeostasis and cuproptosis in cancer immunity and therapy

Copper is an essential nutrient for maintaining enzyme activity and transcription factor function. Excess copper results in the aggregation of lipoylated dihydrolipoamide S-acetyltransferase (DLAT), which correlates to the mitochondrial tricarboxylic acid (TCA) cycle, resulting in proteotoxic stress and eliciting a novel cell death modality: cuproptosis. Cuproptosis exerts an indispensable role in cancer progression, which is considered a promising strategy for cancer therapy. Cancer immunotherapy has gained extensive attention owing to breakthroughs in immune checkpoint blockade; furthermore, cuproptosis is strongly connected to the modulation of antitumor immunity. Thus, a thorough recognition concerning the mechanisms involved in the modulation of copper metabolism and cuproptosis may facilitate improvement in cancer management. This review outlines the cellular and molecular mechanisms and characteristics of cuproptosis and the links of the novel regulated cell death modality with human cancers. We also review the current knowledge on the complex effects of cuproptosis on antitumor immunity and immune response. Furthermore, potential agents that elicit cuproptosis pathways are summarized. Lastly, we discuss the influence of cuproptosis induction on the tumor microenvironment as well as the challenges of adding cuproptosis regulators to therapeutic strategies beyond traditional therapy.

Cuproptosis and physical training

Copper is an essential element in the human body, involved in many physiological and metabolic functions, including coagulation, oxidative metabolism, and hormone production. The maintenance of copper homeostasis within cells is a complex procedure that is intrinsically controlled by a multitude of intricate mechanisms. Disorders of copper homeostasis encompass a wide range of pathological conditions, including degenerative neurological diseases, metabolic disorders, cardio-cerebrovascular diseases, and tumors. Cuproptosis, a recently identified non-apoptotic mode of cell death mode, is characterized by copper dependence and the regulation of mitochondrial respiration. Cuproptosis represents a novel form of cell death distinct from the previously described modes, including apoptosis, necrosis, pyroptosis, and ferroptosis. Excess copper has been shown to induce cuproptosis by stimulating protein toxic stress responses via copper-dependent abnormal oligomerization of lipoylation proteins within the tricarboxylic acid cycle and the subsequent reduction of iron-sulfur cluster protein levels. Ferredoxin1 facilitates the lipoacylation of dihydrolipoyl transacetylase, which in turn degrades iron-sulfur cluster proteins by reducing Cu2+ to Cu+, thereby inducing cell death. Furthermore, copper homeostasis is regulated by the copper transporter, and disturbances in this homeostasis result in cuproptosis. Current evidence suggests that cuproptosis plays an important role in the onset and development of several cardiovascular diseases. Copper-chelating agents, including ammonium tetrathiomolybdate (VI) and DL-penicillamine, have been shown to facilitate the alleviation of cardiovascular disease by inhibiting cuproptosis. It is hypothesized that oxidative phosphorylation inhibitors such as physical training may inhibit cuproptosis by inhibiting the protein stress response. In conclusion, the implementation of physical training may be a viable strategy to reducte the incidence of cuproptosis.

Cuproptosis Related Gene DLD Associated with Poor Prognosis and Malignant Biological Characteristics in Lung Adenocarcinoma

PURPOSE

Cuproptosis plays a crucial role in the biological function of cells. The subject of this work was to analyze the effects of cuproptosis-related genes (CRGs) on the prognosis and biological function in lung adenocarcinoma (LUAD).

METHODS

In this study, RNA sequencing and clinical data of LUAD samples were screened from public databases and our institution. A CRG signature was identified by least absolute shrinkage and selection operator and Cox regression. In addition, this study analyzed the correlation between prognostic CRGs and clinicopathological features. Finally, this study studied the effect of inhibiting dihydrolipoamide dehydrogenase (DLD) expression on cell biological function.

RESULTS

There were 10 CRGs that showed differential expression between LUAD and normal tissues (p<0.05). A prognostic signature (DLD and lipoyltransferase 1 [LIPT1]) was constructed. Survival analysis suggested that patients with LUAD in the high-risk group had shorter overall survival (OS) (p<0.05). High expression of DLD and low expression of LIPT1 were significantly associated with shorter OS (p<0.05). Immunohistochemical analysis revealed that, in LUAD tissues, DLD was highly expressed, whereas LIPT1 was not detected. Finally, inhibition of DLD expression could significantly restrain cell proliferation, invasion and migration.

CONCLUSION

Overall, this prognostic CRG signature may play a pivotal role in LUAD outcome, while oncogene DLD may be a future therapeutic candidate for LUAD.

Systematic analysis based on the cuproptosis-related genes identifies ferredoxin 1 as an immune regulator and therapeutic target for glioblastoma

Glioblastoma multiforme (GBM) is recognized as the prevailing malignant and aggressive primary brain tumor, characterized by an exceedingly unfavorable prognosis. Cuproptosis, a recently identified form of programmed cell death, exhibits a strong association with cancer progression, therapeutic response, and prognostic outcomes. However, the specific impact of cuproptosis on GBM remains uncertain. To address this knowledge gap, we obtained transcriptional and clinical data pertaining to GBM tissues and their corresponding normal samples from various datasets, including TCGA, CGGA, GEO, and GTEx. R software was utilized for the analysis of various statistical techniques, including survival analysis, cluster analysis, Cox regression, Lasso regression, gene enrichment analysis, drug sensitivity analysis, and immune microenvironment analysis. Multiple assays were conducted to investigate the expression of genes related to cuproptosis and their impact on the proliferation, invasion, and migration of glioblastoma multiforme (GBM) cells. The datasets were obtained and prognostic risk score models were constructed and validated using differentially expressed genes (DEGs) associated with cuproptosis. To enhance the practicality of these models, a nomogram was developed.Patients with glioblastoma multiforme (GBM) who were classified as high risk exhibited a more unfavorable prognosis and shorter overall survival compared to those in the low risk group. Additionally, we specifically chose FDX1 from the differentially expressed genes (DEGs) within the high risk group to assess its expression, prognostic value, biological functionality, drug responsiveness, and immune cell infiltration. The findings demonstrated that FDX1 was significantly upregulated and associated with a poorer prognosis in GBM. Furthermore, its elevated expression appeared to be linked to various metabolic processes and the susceptibility to chemotherapy drugs. Moreover, FDX1 was found to be involved in immune cell infiltration and exhibited correlations with multiple immunosuppressive genes, including TGFBR1 and PDCD1LG2. The aforementioned studies offer substantial assistance in informing the chemotherapy and immunotherapy approaches for GBM. In summary, these findings contribute to a deeper comprehension of cuproptosis and offer novel perspectives on the involvement of cuproptosis-related genes in GBM, thereby presenting a promising therapeutic strategy for GBM patients.

Integrated bioinformatics and experiment revealed that cuproptosis is the potential common pathogenesis of three kinds of primary cardiomyopathy

Cuproptosis is a recently reported new mode of programmed cell death which might be a potential co-pathogenesis of three kinds of primary cardiomyopathy. However, no investigation has reported a clear relevance between primary cardiomyopathy and cuproptosis. In this study, the differential cuproptosis-related genes (CRGs) shared by three kinds of primary cardiomyopathy were identified in training sets. As a result, four CRGs shared by three kinds of primary cardiomyopathy were acquired and they were mainly related to biological processes such as cell death and immuno-inflammatory response through differential analysis, correlation analysis, GSEA, GSVA and immune cell infiltration analysis. Then, three key CRGs (K-CRGs) with high diagnostic value were identified by LASSO regression. The results of nomogram, machine learning, ROC analysis, calibration curve and decision curve indicated that the K-CRGs exhibited outstanding performance in the diagnosis of three kinds of primary cardiomyopathy. After that, in each disease, two molecular subtypes clusters were distinguished. There were many differences between different clusters in the biological processes associated with cell death and immunoinflammation and K-CRGs had excellent molecular subtype identification efficacy. Eventually, results from validation datasets and in vitro experiments verified the role of K-CRGs in diagnosis of primary cardiomyopathy, identification of primary cardiomyopathic molecular subtypes and pathogenesis of cuproptosis. In conclusion, this study found that cuproptosis might be the potential common pathogenesis of three kinds of primary cardiomyopathy and K-CRGs might be promising biomarkers for the diagnosis and molecular subtypes identification of primary cardiomyopathy.

Research progress in cuproptosis in liver cancer

Copper, like iron, is an essential trace metal element for human cells. The role of iron overload and ferroptosis has been gradually clarified in tumors, but the role of copper overload and cuproptosis is still being explored. Cuproptosis is a novel mode of cell death, secondary to impaired mitochondrial function induced by copper overload, and characterized by copper-dependent and programmed. The excessive copper leads to protein toxicity stress by binding to sulfhydryl proteins in the tricarboxylic acid (TCA) cycle of mitochondria, disrupting cellular homeostasis and triggering cuproptosis. Copper accumulation has carcinogenic effects on normal cells, dual effects on tumor cells. Liver cancer is one of the most common malignant tumors in China and even globally, with hepatocellular carcinoma (HCC) being the most common histological subtype. Copper exhibits dualism in HCC, as it both contributes to the growth and invasion of HCC cells, and exerts anticancer effects by inducing cuproptosis. Also, cuproptosis-related genes can be the evaluation of immunotherapy effect and the construction of prognostic models. Clarifying the role of copper death in liver cancer can help explore new methods for liver cancer screening, treatment, and prognosis evaluation.

Machine learning- and WGCNA-mediated double analysis based on genes associated with disulfidptosis, cuproptosis and ferroptosis for the construction and validation of the prognostic model for breast cancer

BACKGROUND

Disulfidptosis, a recently discovered cellular death mechanism, has not been extensively studied in relation to breast cancer (BC). Specifically, no previous research has integrated disulfidptosis-related genes (DRGs), cuproptosis-related genes (CRGs), and ferroptosis-related genes (FRGs) to construct a prognostic signature for BC.

METHODS

DRGs, CRGs and FRGs with prognostic potential were identified through Cox regression analysis. A predictive model was constructed by intersecting the core genes obtained from unsupervised cluster analysis and weighted correlation network analysis (WGCNA). Differences in chemotherapy drug sensitivity, immune checkpoint levels were analyzed according to different risk score groups. The expression of the core disulfidptosis gene, SLC7A11, was analyzed using immunofluorescence.

RESULTS

Single-cell RNA sequencing analysis revealed differential expression of DRGs in the BC tumor microenvironment. We developed a prognostic model, consisting of six genes, based on machine learning which included unsupervised cluster analysis and Lasso-Cox analysis. An internal training set and a validation set, both derived from the Cancer Genome Atlas-Breast Cancer (TCGA-BRCA) database, GSE20685 and GSE42568 as external validation sets all verified the model's validity. The low-risk group exhibited increased sensitivity to paclitaxel. Additionally, the high-risk group demonstrated significantly higher expression of tumor mutation burden and microsatellite instability compared to the low-risk group. A nomogram confirmed that the risk score can be an independent risk factor for BC. Notably, our findings highlighted the impact of SLC7A11 on the BC tumor microenvironment. Immunofluorescence analysis revealed significantly higher expression of SLC7A11 in BC tissues compared to paracancerous tissues.

CONCLUSION

Multiplex analysis based on DRGs, CRGs and FRGs correlated strongly with BC, providing new insights for developing clinical prognostic tools and designing immunotherapy regimens for BC patients.

Cuproptosis as the new kryptonite of cancer: a copper-dependent novel cell death mechanism with promising implications for the treatment of hepatocellular carcinoma

Copper is an essential element for critical cellular functions such as mitochondrial respiration, cholesterol biosynthesis and immune response. Altered copper homeostasis has been associated with various disorders, including cancer. The copper overload is known to contribute to tumorigenesis, angiogenesis and metastasis, and recently it has been suggested that the elevated level of this element may also create vulnerability to a novel cell death mechanism, named cuproptosis. Excessive amount of copper in mitochondria binds to lipoylated enzymes of the TCA cycle and forms insoluble oligomers. The aggregation of these oligomers and subsequent iron-sulfur cluster protein loss results in proteotoxic stress and eventual cell death. Hepatocellular carcinoma is a common malignancy with a low survival rate, despite the available treatment options. The discovery of cuproptosis led many researchers to explore its potential use in hepatocellular cancer therapy due to the rich mitochondria content of hepatic cells. In this regard, a number of genomic studies were conducted to discover several cuproptosis-related genes and explored their association with prognosis, survival and immunotherapy response. This review brings together the available data on the relationship between cuproptosis and hepatocellular cancer for the first time, and highlights some of the potential biomarkers or target molecules that may be useful in the treatment.

Cuproptosis and its application in different cancers: an overview

Heavy metal ions are essential micronutrients for human health. They are also indispensable to maintaining health and regular operation of organs. Increasing or decreasing these metal ions will lead to cell death, such as ferroptosis. Tsvetkov et al. have recently proposed a novel cell death method called "Cuproptosis". Many researchers have linked this form of death to the diagnosis, prognosis, microenvironment infiltration, and prediction of immunotherapeutic efficacy of various tumors to better understand these tumors. Similarly, with the proposal of this mechanism, the killing effect of copper ionophores on cancer cells has come to our attention again. We introduced the mechanism of cuproptosis in detail and described the establishment of the corresponding prognostic model and risk score for uveal melanoma through cuproptosis. In addition, we describe the current progress in the study of cancer in other organs through cuproptosis and summarize the treatment of tumours by copper ionophore and its future research direction. With further research, the concept of cuproptosis may help us understand cancer and guide its clinical treatment.

Aberrant expression of cuproptosis‑related gene LIPT1 is associated with metabolic dysregulation of fatty acid and prognosis in hepatocellular carcinoma

PURPOSE

Lipoyltransferase 1 (LIPT1) has been recently identified as a cuproptosis‑related gene. As a key enzyme of lipoic acid metabolism, LIPT1 has been revealed to play important roles in hereditary diseases involved with lipoic acid biosynthesis defects, while its roles in hepatocellular carcinoma (HCC) remain to be elucidated. Hence, we aimed to explore the roles and mechanisms of LIPT1 in HCC progression.

METHODS

The expression of LIPT1 in HCC tissues and its clinical significance for HCC were evaluated by bioinformatic analysis and in our patient cohort. The influences of LIPT1 on the growth, migration, and lipid metabolism of HCC cells were assessed in vitro. The underlying mechanisms were explored using gene set enrichment analysis (GSEA) and molecular experiments.

RESULTS

LIPT1 expression was significantly elevated in HCC tissues compared to the normal tissues, and such upregulation was associated with more malignant pathological features and poor prognosis of patients with HCC. LIPT1 silencing significantly inhibited cell proliferation, migration, and lipid content. GSEA revealed that LIPT1 upregulation was significantly associated with various cancer-associated signaling pathways, including the PI3K-AKT signaling pathway and the Wnt/β-catenin pathway. Further molecular experiments indicated that LIPT1 silencing repressed the expression of peroxisome proliferator-activated receptor gamma (PPARγ) and inactivated the AKT/GSK-3β/β-catenin signaling axis.

CONCLUSIONS

Upregulation of LIPT1 is involved in metabolic dysregulation of fatty acid and poor prognosis of HCC patients, which suggests that LIPT1 plays an important role in reprogramming lipid metabolism and could act as a potential prognostic marker and therapeutic target for HCC.

Cuproptosis and cuproptosis-related genes: Emerging potential therapeutic targets in breast cancer

Breast cancer is one of the most common malignant tumors in women worldwide, and thus, it is important to enhance its treatment efficacy [1]. Copper has emerged as a critical trace element that affects various intracellular signaling pathways, gene expression, and biological metabolic processes [2], thereby playing a crucial role in the pathogenesis of breast cancer. Recent studies have identified cuproptosis, a newly discovered type of cell death, as an emerging therapeutic target for breast cancer treatment, thereby offering new hope for breast cancer patients. Tsvetkov's research has elucidated the mechanism of cuproptosis and uncovered the critical genes involved in its regulation [3]. Manipulating the expression of these genes could potentially serve as a promising therapeutic strategy for breast cancer treatment. Additionally, using copper ionophores and copper complexes combined with nanomaterials to induce cuproptosis may provide a potential approach to eliminating drug-resistant breast cancer cells, thus improving the therapeutic efficacy of chemotherapy, radiotherapy, and immunotherapy and eventually eradicating breast tumors. This review aims to highlight the practical significance of cuproptosis-related genes and the induction of cuproptosis in the clinical diagnosis and treatment of breast cancer. We examine the potential of cuproptosis as a novel therapeutic target for breast cancer, and we explore the present challenges and limitations of this approach. Our objective is to provide innovative ideas and references for the development of breast cancer treatment strategies based on cuproptosis.

Comprehensive analysis identifies DNA damage repair-related gene HCLS1 associated with good prognosis in lung adenocarcinoma

Background

Lung cancer is the leading cause of cancer-associated mortality. Lung adenocarcinoma (LUAD) amounts to more than 40% of all lung malignancies. Therefore, developing clinically useful biomarkers for this disease is critical. DNA damage repair (DDR) is a complicated signal transduction process that ensures genomic stability. DDR should be comprehensively analyzed to elucidate their clinical significance and tumor immune microenvironment interactions.

Methods

In this study, DDR-related genes (DRGs) were selected to investigate their prognostic impact on LUAD. A regression-based prognostic model was established based on The Cancer Genome Atlas (TCGA)-LUAD cohort and three external Gene Expression Omnibus (GEO) validation cohorts (GSE31210, GSE68465, and GSE72094). The robust, established model could independently predict the clinical outcomes in patients. Then, the prognostic performance of risk profiles was assessed using a time-dependent receiver operating characteristic (ROC) curve, Cox regression, nomogram, and Kaplan-Meier analyses. Furthermore, the potential biological functions and infiltration status of DRGs in LUAD were investigated with ESTIMATE and CIBERSORT. Finally, the effects of HCLS1 on the clinical features, prognosis, biological function, immune infiltration, and treatment response in LUAD were systematically analyzed.

Results

Eleven DRGs were constructed to categorize patients into high- and low-risk groups. The risk score was an independent predictor of overall survival (OS). HCLS1 expression was downregulated in LUAD samples and linked with clinicopathological features. Multivariate Cox regression analysis using the Kaplan-Meier plotter revealed that low HCLS1 expression was independently associated with poor OS. Moreover, the HCLS1 high-expression group had higher immune-related gene expression and ESTIMATE scores. It was positively correlated with the infiltration of M1 macrophages, activated memory CD4 T cells, CD8 T cells, memory B cells, resting dendritic cells, and memory CD4 T cells, Tregs, and neutrophils.

Conclusions

A new classification system was developed for LUAD according to DDR characteristics. This stratification has important clinical values, reliable prognosis, and immunotherapy in patients with LUAD. Moreover, HCLS1 is a potential prognostic biomarker of LUAD that correlates with the extent of immune cell infiltration in the tumor microenvironment (TME).

Multi-omics analysis of MRPL-13 as a tumor-promoting marker from pan-cancer to lung adenocarcinoma

BACKGROUND

As a member of the mitochondrial ribosomal protein family, mitochondrial ribosomal protein L13 (MRPL13) is responsible for synthesizing mitochondrial proteins in cells. Several studies have indicated that MRPL13 is associated with the proliferation cycle, migration ability, apoptosis and autophagy of cancer cells. However, a thorough examination of MRPL13 across cancers remains uncertain. Therefore, we tried to clarify the relationship between MRPL13 and pan-cancer, and verified it in lung adenocarcinoma by various methods. Finally, our research is expected to reveal new targets for pan-cancer treatment and improve the prognosis of cancer patients.

METHODS

Using bioinformatics tools, we quantified the differential expression of MRPL13 between cancer tissues and corresponding or noncorresponding normal tissues across cancers. We also analyzed the relationships between MRPL13 expression levels and several factors, including diagnosis, prognosis, mutation, functional signaling pathways, immune infiltration, RNA modification, and the relationship with cuproptosis-related genes. Furthermore, we studied the relationship between the expression level of MRPL13 across cancers and the change in cancer functional status through single-cell data. In addition, quantitative experiments (PCR and Western blot) proved that the expression of MRPL13 was significantly different between LUAD and control samples. Finally, the effect of knocking out MRPL13 on cancer cells was compared by gene silencing experiments. In summary, we used a combination of bioinformatics and experimental applications to study the potential roles of MRPL13 in cancer.

RESULTS

After conducting a multidimensional analysis, we found that the application of MRPL13 multigroup analysis can effectively improve the diagnostic efficiency of various cancers and predict the prognosis of cancer. Moreover, MRPL13 in pan-cancer is related to the cancer immune infiltration pattern, methylation level and cuproptosis-related genes. Furthermore, single-cell data analysis showed that the modules of metastasis, EMT, cell cycle, DNA repair, invasion, DNA damage and proliferation were positively correlated with the expression of MRPL13 in LUAD (Lung adenocarcinoma), while the modules of hypoxia and inflammation were negatively correlated. Moreover, through quantitative experiments, we observed higher expression of MRPL13 in cancer tissues at the RNA or protein level. Knockdown of MRPL13 in LUAD led to decreased cancer cell survival, delayed tumor division and migration, reduced invasion, and increased cancer cell apoptosis.

CONCLUSIONS

Our study demonstrates the potential of using MRPL13 as a molecular biomarker for diagnosing and suggesting the prognosis of certain malignant tumors. Furthermore, our research shows that MRPL13 may be an effective therapeutic target for lung adenocarcinoma.

Copper homeostasis and cuproptosis in tumor pathogenesis and therapeutic strategies

Copper is an indispensable micronutrient for the development and replication of all eukaryotes, and its redox properties are both harmful and beneficial to cells. An imbalance in copper homeostasis is thought to be involved in carcinogenesis. Importantly, cancer cell proliferation, angiogenesis, and metastasis cannot be separated from the effects of copper. Cuproposis is a copper-dependent form of cell death that differs from other existing modalities of regulatory cell death. The role of cuproptosis in the pathogenesis of the nervous and cardiovascular systems has been widely studied; however, its impact on malignant tumors is yet to be fully understood from a clinical perspective. Exploring signaling pathways related to cuproptosis will undoubtedly provide a new perspective for the development of anti-tumor drugs in the future. Here, we systematically review the systemic and cellular metabolic processes of copper and the regulatory mechanisms of cuproptosis in cancer. In addition, we discuss the possibility of targeting copper ion drugs to prolong the survival of cancer patients, with an emphasis on the most representative copper ionophores and chelators. We suggest that attention should be paid to the potential value of copper in the treatment of specific cancers.

Single-cell and genetic multi-omics analysis combined with experiments confirmed the signature and potential targets of cuproptosis in hepatocellular carcinoma

Background: Cuproptosis, as a recently discovered type of programmed cell death, occupies a very important role in hepatocellular carcinoma (HCC) and provides new methods for immunotherapy; however, the functions of cuproptosis in HCC are still unclear. Methods: We first analyzed the transcriptome data and clinical information of 526 HCC patients using multiple algorithms in R language and extensively described the copy number variation, prognostic and immune infiltration characteristics of cuproptosis related genes (CRGs). Then, the hub CRG related genes associated with prognosis through LASSO and Cox regression analyses and constructed a prognostic prediction model including multiple molecular markers and clinicopathological parameters through training cohorts, then this model was verified by test cohorts. On the basis of the model, the clinicopathological indicators, immune infiltration and tumor microenvironment characteristics of HCC patients were further explored via bioinformation analysis. Then, We further explored the key gene biological function by single-cell analysis, cell viability and transwell experiments. Meantime, we also explored the molecular docking of the hub genes. Results: We have screened 5 hub genes associated with HCC prognosis and constructed a prognosis prediction scoring model. And the model results showed that patients in the high-risk group had poor prognosis and the expression levels of multiple immune markers, including PD-L1, CD276 and CTLA4, were higher than those patients in the low-risk group. We found a significant correlation between risk score and M0 macrophages and memory CD4+ T cells. And the single-cell analysis and molecular experiments showed that BEX1 were higher expressed in HCC tissues and deletion inhibited the proliferation, invasion and migration and EMT pathway of HCC cells. Finally, it was observed that BEX1 could bind to sorafenib to form a stable conformation. Conclusion: The study not only revealed the multiomics characteristics of CRGs in HCC but also constructed a new high-accuracy prognostic prediction model. Meanwhile, BEX1 were also identified as hub genes that can mediate the cuproptosis of hepatocytes as potential therapeutic targets for HCC.

Identification and validation of a prognostic signature of cuproptosis-related genes for esophageal squamous cell carcinoma

Esophageal squamous cell carcinoma (ESCC) is a highly lethal form of cancer. Cuproptosis is a recently discovered form of regulated cell death. However, its significance in ESCC remains largely unknown. In this study, we observed significant expression differences in most of the 12 cuproptosis-related genes (CRGs) in the TCGA-ESCC dataset, which was validated using GSE20347, GSE38129, and individual ESCC datasets. We were able to divide patients in the TCGA-ESCC cohort into two subgroups based on disease, and found significant differences in survivor outcomes and biological functions between these subgroups. Additionally, we identified 11 prognosis-related genes from the 12 CRGs using LASSO COX regression analysis and constructed a CRGs signature for ESCC. Patients were categorized into high- and low-risk subgroups based on their median risk score, with those in the high-risk subgroup having significantly worse overall survival than those in the low-risk subgroup. The CRGs signature was also highly accurate in predicting prognosis and survival outcomes. Univariate and multivariate Cox regression analyses revealed that 8 of the 11 CRGs were independent prognostic factors for predicting survival in ESCC patients. Furthermore, our nomogram performed well and could serve as a useful tool for predicting prognosis. Finally, our risk model was found to be relevant to the sensitivity of targeted agents and immune infiltration. Functional enrichment analysis demonstrated that the risk model was associated with biological pathways of tumor migration and invasion. In summary, our study may provide a promising prognostic signature based on CRGs and offers potential targets for personalized therapy.

Intratumor microbiome derived glycolysis-lactate signatures depicts immune heterogeneity in lung adenocarcinoma by integration of microbiomic, transcriptomic, proteomic and single-cell data

Introduction

Microbiome plays roles in lung adenocarcinoma (LUAD) development and anti-tumor treatment efficacy. Aberrant glycolysis in tumor might promote lactate production that alter tumor microenvironment, affecting microbiome, cancer cells and immune cells. We aimed to construct intratumor microbiome score to predict prognosis of LUAD patients and thoroughly investigate glycolysis and lactate signature's association with LUAD immune cell infiltration.

Methods

The Cancer Genome Atlas-LUAD (TCGA-LUAD) microbiome data was downloaded from cBioPortal and analyzed to examine its association with overall survival to create a prognostic scoring model. Gene Set Enrichment Analysis (GSEA) was used to find each group's major mechanisms involved. Our study then investigated the glycolysis and lactate pattern in LUAD patients based on 19 genes, which were correlated with the tumor microenvironment (TME) phenotypes and immunotherapy outcomes. We developed a glycolysis-lactate risk score and signature to accurately predict TME phenotypes, prognosis, and response to immunotherapy.

Results

Using the univariate Cox regression analysis, the abundance of 38 genera were identified with prognostic values and a lung-resident microbial score (LMS) was then developed from the TCGA-LUAD-microbiome dataset. Glycolysis hallmark pathway was significantly enriched in high-LMS group and three distinct glycolysis-lactate patterns were generated. Patients in Cluster1 exhibited unfavorable outcomes and might be insensitive to immunotherapy. Glycolysis-lactate score was constructed for predicting prognosis with high accuracy and validated in external cohorts. Gene signature was developed and this signature was elevated in epithelial cells especially in tumor mass on single-cell level. Finally, we found that the glycolysis-lactate signature levels were consistent with the malignancy of histological subtypes.

Discussion

Our study demonstrated that an 18-microbe prognostic score and a 19-gene glycolysis-lactate signature for predicting prognosis of LUAD patients. Our LMS, glycolysis-lactate score and glycolysis-lactate signature have potential roles in precision therapy of LUAD patients.