A novel signature to guide osteosarcoma prognosis and immune microenvironment: Cuproptosis-related lncRNA

Machine learning-based identification of cuproptosis-related lncRNA biomarkers in diffuse large B-cell lymphoma

Multiple machine learning techniques were employed to identify key long non-coding RNA (lncRNA) biomarkers associated with cuproptosis in Diffuse Large B-Cell Lymphoma (DLBCL). Data from the TCGA and GEO databases facilitated the identification of 126 significant cuproptosis-related lncRNAs. Various feature selection methods, such as Univariate Filtering, Lasso, Boruta, and Random Forest, were integrated with a Transformer-based model to develop a robust prognostic tool. This model, validated through fivefold cross-validation, demonstrated high accuracy and robustness in predicting risk scores. MALAT1 was pinpointed using permutation feature importance from machine learning methods and was further validated in DLBCL cell lines, confirming its substantial role in cell proliferation. Knockdown experiments on MALAT1 led to reduced cell proliferation, underscoring its potential as a therapeutic target. This integrated approach not only enhances the precision of biomarker identification but also provides a robust prognostic model for DLBCL, demonstrating the utility of these lncRNAs in personalized treatment strategies. This study highlights the critical role of combining diverse machine learning methods to advance DLBCL research and develop targeted cancer therapies.

Cuproptosis and its potential role in musculoskeletal disease

Cuproptosis, a recently identified form of copper-dependent cell death, arises from intracellular copper dyshomeostasis. As an essential trace element, copper plays a critical role in bioenergetic metabolism, redox regulation, and synaptic transmission. However, excessive copper exerts cytotoxic effects through multiple pathways, including increased reactive oxygen species (ROS) production, apoptotic cascade activation, necrotic membrane rupture, inflammatory responses, and mitochondrial dysfunction. Distinct from other cell death mechanisms, cuproptosis is characterized by copper ion binding to acetylated mitochondrial respiratory chain proteins, leading to pathogenic protein aggregation, iron-sulfur cluster depletion, and cellular collapse. Emerging evidence underscores aberrant copper accumulation and resultant proteotoxic stress as pivotal contributors to the pathogenesis of multiple musculoskeletal pathologies, including osteoporosis, osteoarthritis, sarcopenia, osteosarcoma, intervertebral disc degeneration, spinal cord injury, and biofilm-associated orthopedic infections. Understanding the spatiotemporal regulation of cuproptosis may provide novel opportunities for advancing diagnostic and therapeutic approaches in orthopedic medicine. This review synthesizes current insights into the molecular mechanisms of cuproptosis, its pathogenic role in musculoskeletal diseases, and the potential for biomarker-driven therapeutic interventions.

Long non-coding RNA BCAR4 regulates osteosarcoma progression by targeting microRNA-1260a

Long non-coding RNAs (lncRNAs) play a crucial role in modulating cancer progression and metastasis. This study investigates the tumor-promoting function of long non-coding RNA BCAR4 in osteosarcoma and elucidates its regulatory mechanism. Although BCAR4 acts as a tumor promoter in osteosarcoma, its regulatory mechanism remains unclear. Bioinformatic analysis revealed a specific interaction between BCAR4 and miR-1260a, with osteosarcoma exhibiting elevated miR-1260a expression inversely correlated with BCAR4 expression. Overexpression of BCAR4 significantly suppressed miR-1260a expression, indicating regulation between BCAR4 and miR-1260a. Luciferase reporter assays confirmed a direct association between miR-1260a and BCAR4 at the sequence level. Silencing of BCAR4 inhibited osteosarcoma cell proliferation and migration while promoting cellular apoptosis, primarily mediated by miR-1260a. Our findings demonstrate that BCAR4 functions as a tumor promotor in osteosarcoma, and that its activity is regulated by miR-1260a. This study also proposes a potential therapeutic approach for treating osteosarcoma by targeting the BCAR4/miR-1260a axis. These different insights shed light on the intricate regulatory network underlying osteosarcoma pathogenesis and offer promising avenues for developing targeted therapies against this aggressive cancer.

The neutrophil extracellular trap-related gene FPR1 (formyl peptide receptor 1) as a potential prognostic and therapeutic target in osteosarcoma

BACKGROUND

Neutrophil extracellular trap (NET) has been implicated in cancer progression and metastasis. Nevertheless, the role of the NET-related gene, formyl peptide receptor 1 (FPR1), in osteosarcoma (OS) remains largely unexplored. This study aimed to investigate the prognostic significance and biological function of FPR1 in OS.

METHODS

The least absolute shrinkage and selection operator (LASSO) algorithm was employed to construct a NET-related prognostic model utilizing OS datasets from TARGET and GEO (GSE21257) databases. The scRNA-seq dataset GSE162454 was then used for verifying the role of NET-related model in OS at single-cell resolution. Next, survival analysis and multivariate cox regression analysis were performed to evaluate the prognostic value of FPR1 in OS patients. The CIBERSORT algorithm was conducted to evaluate the relationship between FPR1 levels and immune cell abundance. Subsequently, the biological role of FPR1 was explored through CCK-8, and transwell assays in OS cell lines.

RESULTS

A signature NET score, comprising four NET-related genes (TNFRSF10C, FPR1, BST1 and SELPLG), was constructed to predict the prognosis of OS. The survival outcomes for patients in high-NET score group were markedly worse than that in the low-NET score group. Meanwhile, at single cell resolution, OS cells progressively evolved into tumors with elevated NET scores. Furthermore, FPR1 levels were markedly reduced in OS cells when compared to normal osteoblast cells, and the overexpression of FPR1 notably suppressed OS cell viability, migration and invasion. Additionally, OS patients exhibiting high levels of FPR1 demonstrated a favorable overall survival. Moreover, these patients also had a higher proportion of M1 macrophages and a lower proportion of M0 macrophages.

CONCLUSION

Collectively, our study indicates that the NET-related gene FPR1 is closely related to tumor progression, prognosis and immune infiltration in OS.

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.

Subtype cluster analysis unveiled the correlation between m6A- and cuproptosis-related lncRNAs and the prognosis, immune microenvironment, and treatment sensitivity of esophageal cancer

Objective

Esophageal cancer (EC) is characterized by a high degree of malignancy and poor prognosis. N6-methyladenosine (m6A), a prominent post-transcriptional modification of mRNA in mammalian cells, plays a pivotal role in regulating various cellular and biological processes. Similarly, cuproptosis has garnered attention for its potential implications in cancer biology. This study seeks to elucidate the impact of m6A- and cuproptosis-related long non-coding RNAs (m6aCRLncs) on the prognosis of patients with EC.

Methods

The EC transcriptional data and corresponding clinical information were retrieved from The Cancer Genome Atlas (TCGA) database, comprising 11 normal samples and 159 EC samples. Data on 23 m6A regulators and 25 cuproptosis-related genes were sourced from the latest literature. The m6aCRLncs linked to EC were identified through co-expression analysis. Differentially expressed m6aCRLncs associated with EC prognosis were screened using the limma package in R and univariate Cox regression analysis. Subtype clustering was performed to classify EC patients, enabling the investigation of differences in clinical outcomes and immune microenvironment across patient clusters. A risk prognostic model was constructed using least absolute shrinkage and selection operator (LASSO) regression. Its robustness was evaluated through survival analysis, risk stratification curves, and receiver operating characteristic (ROC) curves. Additionally, the model's applicability across various clinical features and molecular subtypes of EC patients was assessed. To further explore the model's utility in predicting the immune microenvironment, single-sample gene set enrichment analysis (ssGSEA), immune cell infiltration analysis, and immune checkpoint differential expression analysis were conducted. Drug sensitivity analysis was performed to identify potential therapeutic agents for EC. Finally, the mRNA expression levels of m6aCRLncs in EC cell lines were validated using reverse transcription quantitative polymerase chain reaction (RT-qPCR).

Results

We developed a prognostic risk model based on five m6aCRLncs, namely ELF3-AS1, HNF1A-AS1, LINC00942, LINC01389, and MIR181A2HG, to predict survival outcomes and characterize the immune microenvironment in EC patients. Analysis of molecular subtypes and clinical features revealed significant differences in cluster distribution, disease stage, and N stage between high- and low-risk groups. Immune profiling further identified distinct immune cell populations and functional pathways associated with risk scores, including positive correlations with naive B cells, resting CD4+ T cells, and plasma cells, and negative correlations with macrophages M0 and M1. Additionally, we identified key immune checkpoint-related genes with significant differential expression between risk groups, including TNFRSF14, TNFSF15, TNFRSF18, LGALS9, CD44, HHLA2, and CD40. Furthermore, nine candidate drugs with potential therapeutic efficacy in EC were identified: Bleomycin, Cisplatin, Cyclopamine, PLX4720, Erlotinib, Gefitinib, RO.3306, XMD8.85, and WH.4.023. Finally, RT-qPCR validation of the mRNA expression levels of m6aCRLncs in EC cell lines demonstrated that ELF3-AS1 expression was significantly upregulated in the EC cell lines KYSE-30 and KYSE-180 compared to normal esophageal epithelial cells.

Conclusion

This study elucidates the role of m6aCRLncs in shaping the prognostic outcomes and immune microenvironment of EC. Furthermore, it identifies potential therapeutic agents with efficacy against EC. These findings hold significant promise for enhancing the survival of EC patients and provide valuable insights to inform clinical decision-making in the management of this disease.

A unified framework harnessing multi-scale feature ensemble and attention mechanism for gastric polyp and protrusion identification in gastroscope imaging

This study aims to address the diagnostic challenges in distinguishing gastric polyps from protrusions, emphasizing the need for accurate and cost-effective diagnosis strategies. It explores the application of Convolutional Neural Networks (CNNs) to improve diagnostic accuracy. This research introduces MultiAttentiveScopeNet, a deep learning model that incorporates multi-layer feature ensemble and attention mechanisms to enhance gastroscopy image analysis accuracy. A weakly supervised labeling strategy was employed to construct a large multi-class gastroscopy image dataset for training and validation. MultiAttentiveScopeNet demonstrates significant improvements in prediction accuracy and interpretability. The integrated attention mechanism effectively identifies critical areas in images to aid clinical decisions. Its multi-layer feature ensemble enables robust analysis of complex gastroscopy images. Comparative testing against human experts shows exceptional diagnostic performance, with accuracy, micro and macro precision, micro and macro recall, and micro and macro AUC reaching 0.9308, 0.9312, 0.9325, 0.9283, 0.9308, 0.9847 and 0.9853 respectively. This highlights its potential as an effective tool for primary healthcare settings. This study provides a comprehensive solution to address diagnostic challenges differentiating gastric polyps and protrusions. MultiAttentiveScopeNet improves accuracy and interpretability, demonstrating the potential of deep learning for gastroscopy image analysis. The constructed dataset facilitates continued model optimization and validation. The model shows promise in enhancing diagnostic outcomes in primary care.

Cuproptosis: molecular mechanisms, cancer prognosis, and therapeutic applications

Cuproptosis differs from other forms of cell death, such as apoptosis, necroptosis, and ferroptosis, in its unique molecular mechanisms and signaling pathways. In this review, we delve into the cellular metabolic pathways of copper, highlighting the role of copper in biomolecule synthesis, mitochondrial respiration, and antioxidant defense. Furthermore, we elucidate the relationship between cuproptosis-related genes (CRGs) and cancer prognosis, analyzing their expression patterns across various tumor types and their impact on patient outcomes. Our review also uncovers the potential therapeutic applications of copper chelators, copper ionophores, and copper-based nanomaterials in oncology. In addition, we discuss the emerging role of cuproptosis in remodeling the tumor microenvironment, enhancing immune cell infiltration, and converting "cold tumors" into "hot tumors" that respond better to immunotherapy. In short, this review underscores the pivotal importance of cuproptosis in cancer biology and highlights its translational potential as a novel therapeutic target.

Osteosarcoma biomarker analysis and drug targeting prediction based on pyroptosis-related genes

Osteosarcoma is a malignant bone tumor originating from mesenchymal tissue. Recent studies have found that the tumor inflammatory microenvironment plays an important role in promoting the malignant characteristics and metastatic potential of malignant tumors. Pyroptosis, an inflammatory programmed cell death, elicits immune responses that exhibit anti-tumor effects through released factors and contents. Therefore, improving anti-tumor immunity by targeting osteosarcoma-related pyroptosis genes and pathways may be of great significance in delaying early metastasis of osteosarcoma and improving patient survival rate. The study aimed to identify pyroptosis-related genes and biomarkers in osteosarcoma, predicting therapeutic drugs targeting these genes. Gene expression profiles of osteosarcoma were retrieved from Gene Expression Omnibus and cross-referenced with GeneCards and Comparative Toxicogenomics Database to identify differentially expressed pyroptosis-related genes. We conducted enrichment analysis on intersecting genes to identify their biological processes and signaling pathways and assessed immune cell composition in the tumor microenvironment through immune infiltration analysis. In addition, we further utilized Cytoscape software to screen out the top 10 genes with Degree values among the intersected genes as hub genes and performed GSEA analysis and drug prediction based on the hub genes. A total of 22 differentially expressed pyroptosis-related genes were identified in osteosarcoma, with 10 of them (TP53, CYCS, IL-1A, IL-1B, IL-18, CASP-3, CASP-8, IL-6, TNF, CASP-1) pinpointed as hub genes. Enrichment analysis found that the 22 intersection genes are mainly associated with pyroptosis, apoptosis, immune regulation, and related biological processes. The results of data validation targeting hub genes suggest that IL-18, CASP-1, and CASP-8 may be key genes involved in the regulation of pyroptosis in osteosarcoma. Immune infiltration analysis shows statistical differences in the distribution of immune cells like naive B cells, monocytes, M2 macrophages, and dendritic/mast cells, suggesting they play a role in the osteosarcoma tumor microenvironment. Hub gene drug targets suggest Triethyl phosphate, Plinabulin, and Siltuximab as potential osteosarcoma treatments. Our findings suggest potential mechanisms of action for 22 pyroptosis-related genes in osteosarcoma and preliminarily predicted that the occurrence of osteosarcoma is closely related to pyroptosis, apoptosis, and immune regulation. Predicted Triethyl phosphate, Plinabulin, Siltuximab as potential osteosarcoma treatments.

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

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

Clinical Significance and Pathogenic Mechanisms of Long Non-Coding RNA TRPM2-AS in Cancers

Long non-coding RNAs (lncRNAs) are known to play vital roles in human cancers. LncRNA TRPM2-AS has been found to be upregulated in various types of cancers. The elevated levels of TRPM2-AS are associated with important clinicopathological parameters such as tumor size, tumor stage, and lymph node metastasis, revealing that TRPM2-AS could be a potential target for cancer diagnosis, prognosis and treatment. Moreover, TRPM2-AS is involved in regulating the cell proliferation, migration, invasion, apoptosis, drug or radio resistance by serving as a competing endogenous RNA, directly bounding to proteins and regulating multiple signaling pathways. In this review, we comprehensively summarize the latest knowledge on the aberrant expression of TRPM2-AS, the relationship between TRPM2-AS and clinical features, and the detailed mechanisms of potential functions of TRPM2-AS in various cancer types. The current study highlights the potential of TRPM2-AS as a prognostic and therapeutic target in cancers.

The role of disulfidptosis-associated LncRNA-LINC01137 in Osteosarcoma Biology and its regulatory effects on macrophage polarization

The objective of this research is to investigate the function of long non-coding RNA (lncRNA) associated with disulfidptosis, particularly LINC01137, in osteosarcoma (OS), and its impact on macrophage polarization and the tumor immune microenvironment (TME), with the goal of identifying new prognostic biomarkers and therapeutic targets. Utilizing the OS transcriptome dataset from the TARGET database, differentially expressed lncRNAs related to disulfidptosis were identified. The functional mechanisms of LINC01137, which affect cell proliferation, migration, invasiveness, programmed cell death, and macrophage orientation, were explored using the full suite of analyses provided by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG), alongside a diverse array of laboratory experiments, including an in vivo osteosarcoma xenograft model in BALB/c nude mice to assess the impact of LINC01137 knockdown on tumor growth. Among three lncRNAs identified that were distinctly linked to disulfidptosis, LINC01137 showed a notable increase in expression within OS cell lines. Silencing LINC01137 led to a marked decrease in the abilities of cell proliferation, migration, and invasiveness, simultaneously enhancing programmed cell death and facilitating the process of epithelial-mesenchymal transition (EMT). In vivo experiments further confirmed that LINC01137 knockdown significantly suppressed tumor growth in osteosarcoma xenograft models, aligning with the in vitro findings. Associated with disulfidptosis, LINC01137 is pivotal in osteosarcoma development through its enhancement of tumor cell proliferation, migration, and invasiveness, as well as its modification of macrophage orientation within the TME. Given its significance, LINC01137 merits exploration as a prognostic indicator, necessitating detailed studies on its regulatory functions and potential in therapy.

A comprehensive and systematic analysis of Dihydrolipoamide S-acetyltransferase (DLAT) as a novel prognostic biomarker in pan-cancer and glioma

Background

Dihydrolipoamide S-acetyltransferase (DLAT) is a subunit of the pyruvate dehydrogenase complex (PDC), a rate-limiting enzyme complex, that can participate in either glycolysis or the tricarboxylic acid cycle (TCA). However, the pathogenesis is not fully understood. We aimed to perform a more systematic and comprehensive analysis of DLAT in the occurrence and progression of tumors, and to investigate its function in patients' prognosis and immunotherapy.

Methods

The differential expression, diagnosis, prognosis, genetic and epigenetic alterations, tumor microenvironment, stemness, immune infiltration cells, function enrichment, single-cell analysis, and drug response across cancers were conducted based on multiple computational tools. Additionally, we validated its carcinogenic effect and possible mechanism in glioma cells.

Results

We exhibited that DLAT expression was increased in most tumors, especially in glioma, and affected the survival of tumor patients. DLAT was related to RNA modification genes, DNA methylation, immune infiltration, and immune infiltration cells, including CD4+ T cells, CD8+ T cells, Tregs, and cancer-associated fibroblasts. Single-cell analysis displayed that DLAT might regulate cancer by mediating angiogenesis, inflammation, and stemness. Enrichment analysis revealed that DLAT might take part in the cell cycle pathway. Increased expression of DLAT leads tumor cells to be more resistant to many kinds of compounds, including PI3Kβ inhibitors, PKC inhibitors, HSP90 inhibitors, and MEK inhibitors. In addition, glioma cells with DLAT silence inhibited proliferation, migration, and invasion ability, and promoted cell apoptosis.

Conclusion

We conducted a comprehensive analysis of DLAT in the occurrence and progression of tumors, and its possible functions and mechanisms. DLAT is a potential diagnostic, prognostic, and immunotherapeutic biomarker for cancer patients.

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.

Novel Insights Into DLAT's Role in Alzheimer's Disease-Related Copper Toxicity Through Microglial Exosome Dynamics

BACKGROUND

Alzheimer's disease (AD) is a complex neurodegenerative disorder, with recent research emphasizing the roles of microglia and their secreted extracellular vesicles in AD pathology. However, the involvement of specific molecular pathways contributing to neuronal death in the context of copper toxicity remains largely unexplored.

OBJECTIVE

This study investigates the interaction between pyruvate kinase M2 (PKM2) and dihydrolipoamide S-acetyltransferase (DLAT), particularly focusing on copper-induced neuronal death in Alzheimer's disease.

METHODS

Gene expression datasets were analyzed to identify key factors involved in AD-related copper toxicity. The role of DLAT was validated using 5xFAD transgenic mice, while in vitro experiments were conducted to assess the impact of microglial exosomes on neuronal PKM2 transfer and DLAT expression. The effects of inhibiting the PKM2 transfer via microglial exosomes on DLAT expression and copper-induced neuronal death were also evaluated.

RESULTS

DLAT was identified as a critical factor in the pathology of AD, particularly in copper toxicity. In 5xFAD mice, increased DLAT expression was linked to hippocampal damage and cognitive decline. In vitro, microglial exosomes were shown to facilitate the transfer of PKM2 to neurons, leading to upregulation of DLAT expression and increased copper-induced neuronal death. Inhibition of PKM2 transfer via exosomes resulted in a significant reduction in DLAT expression, mitigating neuronal death and slowing AD progression.

CONCLUSION

This study uncovers a novel pathway involving microglial exosomes and the PKM2-DLAT interaction in copper-induced neuronal death, providing potential therapeutic targets for Alzheimer's disease. Blocking PKM2 transfer could offer new strategies for reducing neuronal damage and slowing disease progression in AD.

Gene Expression Regulation and the Signal Transduction of Programmed Cell Death

Cell death is of great significance in maintaining tissue homeostasis and bodily functions. With considerable research coming to the fore, it has been found that programmed cell death presents in multiple modalities in the body, which is not only limited to apoptosis, but also can be divided into autophagy, pyroptosis, ferroptosis, mitotic catastrophe, entosis, netosis, and other ways. Different forms of programmed cell death have disparate or analogous characteristics with each other, and their occurrence is accompanied by multiple signal transduction and the role of a myriad of regulatory factors. In recent years, scholars across the world have carried out considerable in-depth research on programmed cell death, and new forms of cell death are being discovered continually. Concomitantly, the mechanisms of intricate signaling pathways and regulators have been discovered. More critically, cancer cells tend to choose distinct ways to evade cell death, and different tumors adapt to different manners of death. Therefore, targeting the cell death network has been regarded as an effective tumor treatment strategy for a long time. The objective of our paper is to review the signaling pathways and gene regulation in several typical types of programmed cell death and their correlation with cancer.

Disulfidptosis‑related lncRNA prognosis model to predict survival therapeutic response prediction in lung adenocarcinoma

Lung adenocarcinoma (LUAD) is the most common pathological type of lung cancer, and disulfidptosis is a newly discovered mechanism of programmed cell death. However, the effects of disulfidptosis-related lncRNAs (DR-lncRNAs) in LUAD have yet to be fully elucidated. The aim of the present study was to identify and validate a novel lncRNA-based prognostic marker that was associated with disulfidptosis. RNA-sequencing and associated clinical data were obtained from The Cancer Genome Atlas database. Univariate Cox regression and lasso algorithm analyses were used to identify DR-lncRNAs and to establish a prognostic model. Kaplan-Meier curves, receiver operating characteristic curves, principal component analysis, Cox regression, nomograms and calibration curves were used to assess the reliability of the prognostic model. Functional enrichment analysis, immune infiltration analysis, somatic mutation analysis, tumor microenvironment and drug predictions were applied to the risk model. Reverse transcription-quantitative PCR was subsequently performed to validate the mRNA expression levels of the lncRNAs in normal cells and tumor cells. These analyses enabled a DR-lncRNA prognosis signature to be constructed, consisting of nine lncRNAs; U91328.1, LINC00426, MIR1915HG, TMPO-AS1, TDRKH-AS1, AL157895.1, AL512363.1, AC010615.2 and GCC2-AS1. This risk model could serve as an independent prognostic tool for patients with LUAD. Numerous immune evaluation algorithms indicated that the low-risk group may exhibit a more robust and active immune response against the tumor. Moreover, the tumor immune dysfunction exclusion algorithm suggested that immunotherapy would be more effective in patients in the low-risk group. The drug-sensitivity results showed that patients in the high-risk group were more sensitive to treatment with crizotinib, erlotinib or savolitinib. Finally, the expression levels of AL157895.1 were found to be lower in A549. In summary, a novel DR-lncRNA signature was constructed, which provided a new index to predict the efficacy of therapeutic interventions and the prognosis of patients with LUAD.

CXCL6-CXCR2 axis-mediated PD-L2+ mast cell accumulation shapes the immunosuppressive microenvironment in osteosarcoma

Osteosarcoma (OS) is the most common primary bone malignancy and has a high propensity for local invasion and metastasis. The tumour microenvironment of OS is infiltrated by a large number of immune cells, which play a crucial role in its progression and prognosis. Mast cells are important innate immune cells in the tumour stroma and exhibit different phenotypes in diverse tumour microenvironments. However, the underlying mechanisms of mast cell accumulation and the phenotypic characteristics of mast cells in OS remain poorly understood. In this article, we found for the first time that mast cell accumulation in osteosarcoma tissue was modulated by the CXCL6-CXCR2 axis and that the number of infiltrating mast cells was significantly greater in tumour tissues than in adjacent nontumour tissues. These tumour-infiltrating mast cells express high levels of the immunosuppressive molecule PD-L2, and survival analyses revealed that patients in the PD-L2+ high-expression group had a worse prognosis. In vitro, mast cells were induced to express PD-L2 in a time- and dose-dependent manner using OS tissue culture supernatants to mimic the tumour microenvironment. Mechanistic studies revealed that tumour cell-derived G-CSF significantly induced mast cell PD-L2 expression by activating STAT3. Importantly, mast cells overexpressing PD-L2 inhibit tumour-specific CD8+ T-cell proliferation and tumour-killing cytokine secretion, which is reversed by blocking PD-L2 on mast cells. Therefore, our findings provide new insight into the immunosuppressive and tumorigenic roles of mast cells, as well as a novel mechanism by which PD-L2-expressing mast cells mediate immune tolerance.

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.

LncRNA CARD8-AS1 suppresses lung adenocarcinoma progression by enhancing TRIM25-mediated ubiquitination of TXNRD1

Long non-coding RNAs (lncRNAs) play crucial roles in the tumorigenesis and progression of lung adenocarcinoma (LUAD). However, little was known about the role of lncRNAs in high-risk LUAD subtypes: micropapillary-predominant adenocarcinoma (MPA) and solid-predominant adenocarcinoma (SPA). In this study, we conducted a systematic screening of differentially expressed lncRNAs using RNA sequencing in 10 paired MPA/SPA tumor tissues and adjacent normal tissues. Consequently, 110 significantly up-regulated lncRNAs and 288 aberrantly down-regulated lncRNAs were identified (|Log2 Foldchange| ≥ 1 and corrected P < 0.05). The top 10 lncRNAs were further analyzed in 89 MPA/SPA tumor tissues and 59 normal tissues from The Cancer Genome Atlas database. Among them, CARD8-AS1 showed the most significant differential expression, and decreased expression of CARD8-AS1 was significantly associated with a poorer prognosis. Functionally, CARD8-AS1 overexpression remarkably suppressed the proliferation, migration and invasion of LUAD cells both in vitro and in vivo. Conversely, inhibition of CARD8-AS1 yielded opposite effects. Mechanistically, CARD8-AS1 acted as a scaffold to facilitate the interaction between TXNRD1 and E3 ubiquitin ligase TRIM25, thereby promoting the degradation of TXNRD1 through the ubiquitin-proteasome pathway. Additionally, TXNRD1 was found to promote LUAD cell proliferation, migration and invasion in vitro. Furthermore, the suppressed progression of LUAD cells resulting from CARD8-AS1 overexpression could be significantly reversed by simultaneous overexpression of TXNRD1. In conclusion, this study revealed that the lncRNA CARD8-AS1 played a suppressive role in the progression of LUAD by enhancing TRIM25-mediated ubiquitination of TXNRD1. The CARD8-AS1-TRIM25-TXNRD1 axis may represent a promising therapeutic target for LUAD.

Analysis and validation of biomarkers of immune cell-related genes in postmenopausal osteoporosis: An observational study

Postmenopausal osteoporosis (PMOP) is a common metabolic inflammatory disease. In conditions of estrogen deficiency, chronic activation of the immune system leads to a hypo-inflammatory phenotype and alterations in its cytokine and immune cell profile, although immune cells play an important role in the pathology of osteoporosis, studies on this have been rare. Therefore, it is important to investigate the role of immune cell-related genes in PMOP. PMOP-related datasets were downloaded from the Gene Expression Omnibus database. Immune cells scores between high bone mineral density (BMD) and low BMD samples were assessed based on the single sample gene set enrichment analysis method. Subsequently, weighted gene co-expression network analysis was performed to identify modules highly associated with immune cells and obtain module genes. Differential analysis between high BMD and low BMD was also performed to obtain differentially expressed genes. Module genes are intersected with differentially expressed genes to obtain candidate genes, and functional enrichment analysis was performed. Machine learning methods were used to filter out the signature genes. The receiver operating characteristic (ROC) curves of the signature genes and the nomogram were plotted to determine whether the signature genes can be used as a molecular marker. Gene set enrichment analysis was also performed to explore the potential mechanism of the signature genes. Finally, RNA expression of signature genes was validated in blood samples from PMOP patients and normal control by real-time quantitative polymerase chain reaction. Our study of PMOP patients identified differences in immune cells (activated dendritic cell, CD56 bright natural killer cell, Central memory CD4 T cell, Effector memory CD4 T cell, Mast cell, Natural killer T cell, T follicular helper cell, Type 1 T-helper cell, and Type 17 T-helper cell) between high and low BMD patients. We obtained a total of 73 candidate genes based on modular genes and differential genes, and obtained 5 signature genes by least absolute shrinkage and selection operator and random forest model screening. ROC, principal component analysis, and t-distributed stochastic neighbor embedding down scaling analysis revealed that the 5 signature genes had good discriminatory ability between high and low BMD samples. A logistic regression model was constructed based on 5 signature genes, and both ROC and column line plots indicated that the model accuracy and applicability were good. Five signature genes were found to be associated with proteasome, mitochondria, and lysosome by gene set enrichment analysis. The real-time quantitative polymerase chain reaction results showed that the expression of the signature genes was significantly different between the 2 groups. HIST1H2AG, PYGM, NCKAP1, POMP, and LYPLA1 might play key roles in PMOP and be served as the biomarkers of PMOP.

The role of programmed cell death in osteosarcoma: From pathogenesis to therapy

Osteosarcoma (OS) is a prevalent bone solid malignancy that primarily affects adolescents, particularly boys aged 14-19. This aggressive form of cancer often leads to deadly lung cancer due to its high migration ability. Experimental evidence suggests that programmed cell death (PCD) plays a crucial role in the development of osteosarcoma. Various forms of PCD, including apoptosis, ferroptosis, autophagy, necroptosis, and pyroptosis, contribute significantly to the progression of osteosarcoma. Additionally, different signaling pathways such as STAT3/c-Myc signal pathway, JNK signl pathway, PI3k/AKT/mTOR signal pathway, WNT/β-catenin signal pathway, and RhoA signal pathway can influence the development of osteosarcoma by regulating PCD in osteosarcoma cell. Therefore, targeting PCD and the associated signaling pathways could offer a promising therapeutic approach for treating osteosarcoma.

LncRNA MALAT1 promotes osteogenic differentiation through the miR-93-5p/SMAD5 axis

OBJECTIVES

Promoting the osteogenic differentiation of periodontal ligament stem cells (PDLSCs) is a way to regenerate periodontal bone. This study aimed to determine whether lncRNA MALAT1 promotes the osteogenic differentiation of human PDLSCs in vitro.

MATERIALS AND METHODS

Human PDLSCs were extracted from the human periodontal ligament, and after osteogenic differentiation was induced using osteogenic medium, the human PDLSCs were transfected with siRNA-MALAT1, miR-93-5p mimics, and miR-93-5p inhibitors. The expression of osteogenesis-related genes was assessed by RT-qPCR and western blotting, alkaline phosphatase (ALP) activity was assessed by ALP activity assay, and the formation of mineralized nodules was assessed by alizarin red S (ARS) staining. RNA immunoprecipitation (RIP) and luciferase assays were performed to assess the binding of MALAT1, miR-93-5p, and SMAD5.

RESULTS

The expression of lncRNA metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) was upregulated, while that of miR-93-5p was downregulated after PDLSC osteogenic differentiation. Knockdown of MALAT1 inhibited the osteogenic differentiation of PDLSCs, and MALAT1 expression negatively correlated with miR-93-5p expression. miR-93-5p inhibited the osteogenic differentiation of human PDLSCs by specifically binding to SMAD5.

CONCLUSION

MALAT1 regulates human PDLSC differentiation by regulating the miR-93-5p/SMAD5 axis.

The roles of essential trace elements in T cell biology

T cells are crucial for adaptive immunity to regulate proper immune response and immune homeostasis. T cell development occurs in the thymus and mainly differentiates into CD4+ and CD8+ T cell subsets. Upon stimulation, naive T cells differentiate into distinct CD4+ helper and CD8+ cytotoxic T cells, which mediate immunity homeostasis and defend against pathogens or tumours. Trace elements are minimal yet essential components of human body that cannot be overlooked, and they participate in enzyme activation, DNA synthesis, antioxidant defence, hormone production, etc. Moreover, trace elements are particularly involved in immune regulations. Here, we have summarized the roles of eight essential trace elements (iron, zinc, selenium, copper, iodine, chromium, molybdenum, cobalt) in T cell development, activation and differentiation, and immune response, which provides significant insights into developing novel approaches to modulate immunoregulation and immunotherapy.

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.

Crosstalk between metabolism and cell death in tumorigenesis

It is generally recognized that tumor cells proliferate more rapidly than normal cells. Due to such an abnormally rapid proliferation rate, cancer cells constantly encounter the limits of insufficient oxygen and nutrient supplies. To satisfy their growth needs and resist adverse environmental events, tumor cells modify the metabolic pathways to produce both extra energies and substances required for rapid growth. Realizing the metabolic characters special for tumor cells will be helpful for eliminating them during therapy. Cell death is a hot topic of long-term study and targeting cell death is one of the most effective ways to repress tumor growth. Many studies have successfully demonstrated that metabolism is inextricably linked to cell death of cancer cells. Here we summarize the recently identified metabolic characters that specifically impact on different types of cell deaths and discuss their roles in tumorigenesis.

Single-Cell RNA Sequencing Pro-angiogenic Macrophage Profiles Reveal Novel Prognostic Biomarkers and Therapeutic Targets for Osteosarcoma

Osteosarcoma (OS) is a malignant bone tumor that most commonly occurs in children and adolescents. OS patients have a poor prognosis, and 5-year survival rates have rarely improved significantly over the past few decades. OS prognosis may be related to the infiltration of tumor-associated macrophages (TAMs). However, the role of proangiogenic macrophages, a subtype of TAMs, in OS prognosis has not been reported. In this study, seven subtypes of TAMs were identified from single-cell RNA sequencing (scRNA-seq) data that we propose defining as proangiogenic TAMs (Angio-TAMs), interferon-primed TAMs (IFN-TAMs), inflammatory cytokine-enriched TAMs (Inflam-TAMs), immune regulatory TAMs (Reg-TAMs), lipid-associated TAMs (LA-TAMs), and resident-tissue macrophages like TAMs (RTM-TAMs) (containing two subcellular types). In the survival analysis of each macrophage subtype, it was found that patients with Angio-TAMs had the most significant difference in survival. Eight genes associated with Angio-TAMs were obtained by differential expression analysis, and these genes were built into a prognostic model using the LASSO algorithm. Clinical OS case samples were categorized into high-risk and low-risk subgroups using median risk scores. In comparison to the low-risk subgroup, the survival time of the high-risk subgroup was much shorter. Additional studies on immune cell infiltration and immune checkpoint molecule expression in the two risk subgroups were carried out. In immunotherapy response prediction, the Angio-TAM-associated gene risk signature was found to be negatively correlated with immune checkpoint responses. In addition, the associated enriched GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways were mainly involved in the malignant progression of tumors. As suggested by these findings, the Angio-TAM gene risk signature may be an underlying prognostic biomarker and novel therapeutic target for OS patients.Kindly check and confirm whether the ESM file is correctly identifiedWe have checked this file and confirmed that it can be correctly identified.

Develop a Novel Signature to Predict the Survival and Affect the Immune Microenvironment of Osteosarcoma Patients: Anoikis-Related Genes

Objective

Osteosarcoma (OS) represents a prevalent primary bone neoplasm predominantly affecting the pediatric and adolescent populations, presenting a considerable challenge to human health. The objective of this investigation is to develop a prognostic model centered on anoikis-related genes (ARGs), with the aim of accurately forecasting the survival outcomes of individuals diagnosed with OS and offering insights into modulating the immune microenvironment.

Methods

The study's training cohort comprised 86 OS patients sourced from The Cancer Genome Atlas database, while the validation cohort consisted of 53 OS patients extracted from the Gene Expression Omnibus database. Differential analysis utilized the GSE33382 dataset, encompassing three normal samples and 84 OS samples. Subsequently, the study executed gene ontology and Kyoto encyclopedia of genes and genomes enrichment analyses. Identification of differentially expressed ARGs associated with OS prognosis was carried out through univariate COX regression analysis, followed by LASSO regression analysis to mitigate overfitting risks and construct a robust prognostic model. Model accuracy was assessed via risk curves, survival curves, receiver operating characteristic curves, independent prognostic analysis, principal component analysis, and t-distributed stochastic neighbor embedding (t-SNE) analysis. Additionally, a nomogram model was devised, exhibiting promising potential in predicting OS patient prognosis. Further investigations incorporated gene set enrichment analysis to delineate active pathways in high- and low-risk groups. Furthermore, the impact of the risk prognostic model on the immune microenvironment of OS was evaluated through tumor microenvironment analysis, single-sample gene set enrichment analysis (ssGSEA), and immune infiltration cell correlation analysis. Drug sensitivity analysis was conducted to identify potentially effective drugs for OS treatment. Ultimately, the verification of the implicated ARGs in the model construction was conducted through the utilization of real-time quantitative polymerase chain reaction (RT-qPCR).

Results

The ARGs risk prognostic model was developed, comprising seven high-risk ARGs (CBS, MYC, MMP3, CD36, SCD, COL13A1, and HSP90B1) and four low-risk ARGs (VASH1, TNFRSF1A, PIP5K1C, and CTNNBIP1). This prognostic model demonstrates a robust capability in predicting overall survival among patients. Analysis of immune correlations revealed that the high-risk group exhibited lower immune scores compared to the low-risk group within our prognostic model. Specifically, CD8+ T cells, neutrophils, and tumor-infiltrating lymphocytes were notably downregulated in the high-risk group, alongside significant downregulation of checkpoint and T cell coinhibition mechanisms. Additionally, three immune checkpoint-related genes (CD200R1, HAVCR2, and LAIR1) displayed significant differences between the high- and low-risk groups. The utilization of a nomogram model demonstrated significant efficacy in prognosticating the outcomes of OS patients. Furthermore, tumor metastasis emerged as an independent prognostic factor, suggesting a potential association between ARGs and OS metastasis. Notably, our study identified eight drugs-Bortezomib, Midostaurin, CHIR.99021, JNK.Inhibitor.VIII, Lenalidomide, Sunitinib, GDC0941, and GW.441756-as exhibiting sensitivity toward OS. The RT-qPCR findings indicate diminished expression levels of CBS, MYC, MMP3, and PIP5K1C within the context of OS. Conversely, elevated expression levels were observed for CD36, SCD, COL13A1, HSP90B1, VASH1, and CTNNBIP1 in OS.

Conclusion

The outcomes of this investigation present an opportunity to predict the survival outcomes among individuals diagnosed with OS. Furthermore, these findings hold promise for progressing research endeavors focused on prognostic evaluation and therapeutic interventions pertaining to this particular ailment.

miR-488-3p Represses Malignant Behaviors and Facilitates Autophagy of Osteosarcoma Cells by Targeting Neurensin-2

OBJECTIVES

Osteosarcoma (OS) is a primary bone sarcoma that primarily affects children and adolescents and poses significant challenges in terms of treatment. microRNAs (miRNAs) have been implicated in OS cell growth and regulation. This study sought to investigate the role of hsa-miR-488-3p in autophagy and apoptosis of OS cells.

METHODS

The expression of miR-488-3p was examined in normal human osteoblasts and OS cell lines (U2OS, Saos2, and OS 99-1) using RT-qPCR. U2OS cells were transfected with miR-488- 3p-mimic, and cell viability, apoptosis, migration, and invasion were assessed using CCK-8, flow cytometry, and Transwell assays, respectively. Western blotting and immunofluorescence were employed to measure apoptosis- and autophagy-related protein levels, as well as the autophagosome marker LC3. The binding sites between miR-488-3p and neurensin-2 (NRSN2) were predicted using online bioinformatics tools and confirmed by a dual-luciferase assay. Functional rescue experiments were conducted by co-transfecting miR-488-3p-mimic and pcDNA3.1-NRSN2 into U2OS cells to validate the effects of the miR-488-3p/NRSN2 axis on OS cell behaviors. Additionally, 3-MA, an autophagy inhibitor, was used to investigate the relationship between miR- 488-3p/NRSN2 and cell apoptosis and autophagy.

RESULTS

miR-488-3p was found to be downregulated in OS cell lines, and its over-expression inhibited the viability, migration, and invasion while promoting apoptosis of U2OS cells. NRSN2 was identified as a direct target of miR-488-3p. Over-expression of NRSN2 partially counteracted the inhibitory effects of miR-488-3p on malignant behaviors of U2OS cells. Furthermore, miR- 488-3p induced autophagy in U2OS cells through NRSN2-mediated mechanisms. The autophagy inhibitor 3-MA partially reversed the effects of the miR-488-3p/NRSN2 axis in U2OS cells.

CONCLUSION

Our findings demonstrate that miR-488-3p suppresses malignant behaviors and promotes autophagy in OS cells by targeting NRSN2. This study provides insights into the role of miR-488-3p in OS pathogenesis and suggests its potential as a therapeutic target for OS treatment.

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.

Identification and validation of a seven cuproptosis-associated lncRNA signature to predict the prognosis of endometrial cancer

OBJECTIVE

Endometrial cancer (EC) is one of the most prevalent cancers in women. Long non-coding RNAs (lncRNAs) are potential diagnostic biomarkers in patients with EC.

METHODS

We obtained clinical information and transcriptome data for 552 patients with EC from The Cancer Genome Atlas database. Cuproptosis-associated lncRNAs were obtained through Pearson's correlation analysis. Univariate and multivariate Cox regression analyses were applied and a signature predicting overall survival (OS) among patients with EC was constructed. We also analyzed the tumor immune microenvironment and drug sensitivity. The results were validated by quantitative real time-polymerase chain reaction, and 5-ethynyl-2'-deoxyuridine and wound-healing assays.

RESULTS

Seven cuproptosis-associated lncRNAs related to prognosis were screened out and a signature was constructed. OS was significantly superior in the low-risk group. In addition, patients in the low-risk group had more CD8+ T cell infiltration, a stronger type II interferon response, and greater cisplatin sensitivity. Expression levels of some of the lncRNAs were significantly increased by cuproptosis. Furthermore, silencing of lncRNA AC084117.1 significantly inhibited the proliferation and migration of EC cells.

CONCLUSION

We constructed a seven cuproptosis-associated lncRNA signature to predict the prognosis of patients with EC with good predictive power.

Contribution of cuproptosis and Cu metabolism-associated genes to chronic obstructive pulmonary disease

Airway epithelial cell injury plays a crucial role in the pathogenesis of chronic obstructive pulmonary disease (COPD). However, a novel form of Cu-induced programmed cell death known as cuproptosis has not yet been thoroughly investigated in the context of COPD. Clinical reports have suggested that high copper exposure may increase the risk of COPD. In this study, we aimed to determine the expression and potential functions of cuproptosis-related genes and genes associated with copper metabolism in COPD. We initially identified 52 copper metabolism-related genes based on a review of the literature. Subsequently, we calculated the expression levels of these genes using data from four GEO datasets. To gain insights into the activated signalling pathways and underlying mechanisms in COPD patients, we conducted Gene Ontology (GO) and KEGG pathway analyses, examined protein-protein interactions, and performed weighted correlation network analysis. Our findings revealed that 18 key copper metabolism-related genes, including 5 cuproptosis-related genes, were significantly enriched in signalling pathways and biological processes associated with the development of COPD. Further analysis of clinical data and animal experiments confirmed the high expression of certain cuproptosis key regulators, such as DLD and CDKN2A, in both healthy smokers and COPD smokers. Additionally, these regulators exhibited abnormal expression in a COPD rat model. Notably, copper content was found to be elevated in the lung tissues of COPD rats, suggesting its potential involvement in cuproptosis. These findings provide an experimental foundation for further research into the role of cuproptosis in COPD. Targeting copper metabolism-related genes may represent an effective approach for the treatment of COPD.

Comprehensive bioinformatics analysis reveals the oncogenic role of FoxM1 and its impact on prognosis, immune microenvironment, and drug sensitivity in osteosarcoma

Osteosarcoma, a highly malignant bone tumor primarily affecting adolescents, presents a significant challenge in cancer therapy due to its resistance to chemotherapy. This study explores the multifaceted impact of the transcription factor FoxM1 on osteosarcoma, shedding light on its pivotal role in tumor progression, immune microenvironment modulation, and drug response. Utilizing publicly available datasets from the Gene Expression Omnibus (GEO) and Therapeutically Applicable Research To Generate Effective Treatments (TARGET) databases, we conducted an in-depth bioinformatics analysis. Our findings illuminate the far-reaching implications of FoxM1 in osteosarcoma, emphasizing its significance as a potential therapeutic target. Differential expression analysis and Gene Set Enrichment Analysis (GSEA) revealed FoxM1's influence on critical pathways related to apoptosis, cell cycle regulation, and DNA repair. Notably, FoxM1 expression correlated with poor clinical outcomes in osteosarcoma patients, highlighting its prognostic relevance. Additionally, FoxM1 was found to modulate the immune microenvironment within tumor tissues, impacting immune cell infiltration, immunomodulators, immune checkpoints, and chemokines. Furthermore, a prognostic model based on FoxM1-coexpressed genes demonstrated its effectiveness in predicting patient survival. Drug sensitivity analysis indicated FoxM1's association with drug response, potentially guiding personalized treatment approaches. Hub gene screening identified RAB23 as a key target regulated by FoxM1, with RAB23 shown to influence osteosarcoma cell growth. This study also confirmed FoxM1's overexpression in osteosarcoma tissues compared to normal tissues, and its association with clinicopathological characteristics, including clinical stage, pathological type, and lung metastasis. In conclusion, FoxM1 emerges as a central player in the pathogenesis of osteosarcoma, impacting gene expression, immune responses, and therapeutic outcomes. This comprehensive analysis deepens our understanding of FoxM1's role in osteosarcoma and offers potential avenues for improved diagnosis and treatment.

Novel cuproptosis-related lncRNAs can predict the prognosis of patients with multiple myeloma

Background

Cuproptosis-related long-stranded non-coding RNAs (lncRNAs) have several implications for the prognosis of multiple myeloma (MM). This research aimed to construct a prognostic risk model for MM patients and explore the potential signaling pathways in the risk group.

Methods

Cuproptosis-related lncRNAs were obtained from the co-expression analysis of cuproptosis-related genes and lncRNAs. Subsequently, twelve cuproptosis-related lncRNAs were selected to construct a prognostic risk model of MM patients by the least absolute shrinkage and selection operator (LASSO) regression. Then, the clinical data of these patients were randomly divided into the training group and the testing group. Next, patients were divided into the low- and high-risk groups according to the median risk score. The Kaplan-Meier survival analysis was performed to clarify the prognostic differences between risk subtypes. Besides, the Cox analysis was conducted to identify whether the risk score can be used as an independent prognostic factor. In addition, the receiver operating characteristic (ROC) curve analysis and the concordance index (C-index) curve analysis were performed to elucidate the value of risk score as a prognostic indicator. Finally, the differential risk analysis and functional enrichment analysis were carried out to identify the potential signaling pathways in the low- and high-risk groups.

Results

The results demonstrated that the overall survival (OS) of patients in the high-risk group was shorter than that in the low-risk group. There were significant differences in the expression of genes in MM patients between the high- and low-risk groups. The Gene Ontology (GO) analysis results showed that the differentially expressed risk-related genes (DERGs) were mainly concentrated on the collagen-containing extracellular matrix. According to the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis results, the DERGs may be related to the neuroactive ligand-receptor interaction and mitogen-activated protein kinase (MAPK) signaling pathway, indicating that they may be involved in the progression of tumors.

Conclusions

The findings of this study suggest that cuproptosis-related lncRNAs may be effective biomarkers for predicting the prognosis of MM patients, which is anticipated to contribute to the improvement of clinical outcomes.

Comprehensive exploration of the involvement of cuproptosis in tumorigenesis and progression of neuroblastoma

BACKGROUND

Copper-induced cell death, or "cuproptosis," as an apoptotic process, has recently received much attention in human diseases. Recent studies on cuproptosis have provided novel insights into the pathogenesis of various diseases, especially cancers. However, the association between neuroblastoma (NB) and cuproptosis in terms of their clinical outcomes, tumorigenesis, and treatment response remains unclear.

METHODS

To determine the role of cuproptosis in NB tumorigenesis and progression, this study employed a systematic technique to explore the characteristic patterns of 10 key cuproptosis-related genes (CUGs) in NB. Consensus clustering analysis of the TARGET and GEO databases divided the NB patients into two subgroups that showed different clinicopathological attributes, molecular patterns, survival outcomes, disease-associated pathways, tumor immune microenvironment (TIME) features, and treatment responses. Moreover, a cuproptosis scoring scheme was established, which divided the patients with NB into two groups with high scores and low scores as per the median score. Furthermore, this research developed a nomogram and risk signature on the basis of this cuproptosis score to better elucidate its function in predicting NB prognosis. In vitro experiments were carried out using Transwell Assay, HLECs tube formation assay, Colony formation assay, Western Blotting Assay, Immunohistochemical (IHC) Staining, Immunofluorescence (IF) Staining and Flow Cytometry Analysis.

RESULTS

The results demonstrated that the established cuproptosis score and prediction model could effectively distinguish between the individuals in low and high-risk groups and had a high predictive value. Lastly, bioinformatics analysis and in vitro experiments enabled the identification of PDHA1, a key CUG, which was involved in both DNA replication-related pathways and the cell cycle. It was also associated with tumorigenesis and progression of NB.

CONCLUSION

Cuproptosis, especially PDHA1, play a crucial role in the TIME characteristics, tumor progression, and long-term prognosis of NB. The patterns of cuproptosis assessed in this research may improve the understanding of the overall concept of NB tumorigenesis, thus facilitating the development of more effective therapeutic interventions.

High expression of integrin-binding sialoprotein (IBSP) is associated with poor prognosis of osteosarcoma

INTRODUCTION

Osteosarcoma is a malignant tumor, accounting for 20% of primary malignant bone tumors worldwide. However, the role of IBSP as a biomarker in osteosarcoma progression has not been studied yet.

METHODS

85 cases of IBSP expression and clinical characteristics were obtained from TARGET database. Through the Kaplan-Meier curve, subgroup analysis, and univariate and multivariate Cox analysis, we further assessed the independent predictive capacity of IBSP expression for overall survival (OS) and relapse-free survival (RFS).

RESULTS

The mRNA expression of IBSP was higher in osteosarcoma than normal tissue (P < 0.0001). IBSP expression grouped by vital status showed statistical differences (P = 0.042). The race (P = 0.0183), vital status (P = 0.0034), and sample type (P = 0.0020) showed significant differences. IBSP expression exhibited satisfied diagnostic ability for osteosarcoma. The univariate and multivariate analysis confirmed that IBSP expression was an independent risk factor for OS (HR = 3.425, 95% CI: 1.604-7.313, P = 0.002) and RFS (HR = 3.377, 95% CI: 1.775-6.424, P < 0.001) in osteosarcoma patients. High IBSP expression was significantly associated with poor OS and RFS (P < 0.0001). The higher IBSP expression was observed in osteosarcoma (P < 0.001), confirmed by the IHC staining. The CCK-8 and colony formation assay showed that IBSP knockdown inhibits cell proliferation while overexpression promotes cell proliferation (P < 0.05).

CONCLUSION

High expression of IBSP was associated with poor OS and RFS. IBSP could serve as a potential biomarker for osteosarcoma, which could aid in early detection and disease monitoring.

Research trends and hotspots in the immune microenvironment related to osteosarcoma and tumor cell aging: a bibliometric and visualization study

Background

It is well known that cancers have a common feature that even if the environment is extremely poor in nutrients, they can still make good use of them to maintain viability as well as to produce new biomass, which is one of the reasons why tumor cells are powerfully less susceptible to senescence and death. The microenvironment has a profound impact on the senescence as well as the growth and development of tumor cells, and it is also the focus of scientists' research because it may even affect the discovery of the treatment and pathogenesis of cancer. And so the study of the microenvironment in the tumor cells is of great significance to the analysis of the tumor cells as well as to the impact of their senescence. Similarly, the microenvironment of osteosarcoma is also crucial for its impact, but to our knowledge, there is no bibliometric study that systematically analyzes and describes the trends and future hotspots in this field of research as we do, and we are going to fill this gap in this study.

Methods

We searched the Web Science Core Collection 2010-2023 in WOS on August 1, 2023. Based on the criteria needed for the search, we retained articles that matched the topic, excluded studies other than articles and reviews, and selected only studies whose language was English. We performed an intuitive visualization and bibliometric approach to analyze the research content in this field and a systematic visualization of global trends and hotspots in the research of osteosarcoma and the microenvironment, for which we used multiple specialized For this purpose, we used several specialized software packages, such as VOSviewer and the Bibliometrix package for R software. Because research in this area of osteosarcoma and the microenvironment has begun to gain popularity in the last 10 years or so, and is a very novel piece of research, there were almost no studies in this area prior to 2010 and they were not very informative, and in the end, we chose to look at studies from after 2010.

Results

Based on the criteria needed for the search, resulting in a final selection of 821 articles. In the research area related to osteosarcoma and microenvironment, we found that China in Asia and the United States in North America and Italy in Europe were the three countries or regions with the highest number of published articles. In addition, the institution that published the most research in this area was Shanghai Jiao Tong University. In terms of publications in the field of osteosarcoma and microenvironmental research, Baldini, Heymann, and Avnet are among the top 3 authors. The terms "cancer", "cells" and "expression" are found to be more commonly employed.

Conclusion

Using a variety of highly specialized software, we have undertaken a visual and bibliometric study of the current state of research and potential future hotspots in the field of osteosarcoma and microenvironment research. The microenvironment has a profound impact on the senescence and growth and development of cells in tumors, including osteosarcoma, and may even influence the discovery of cancer treatment and pathogenesis, and is also a hotspot and focus that scientists have begun to gradually study in recent years. This analysis and visualization will help guide future research in the field.

CDKN2A was a cuproptosis-related gene in regulating chemotherapy resistance by the MAGE-A family in breast cancer: based on artificial intelligence (AI)-constructed pan-cancer risk model

BACKGROUND

Before the discovery of cuproptosis, copper-loaded nanoparticle is a wildly applied strategy for enhancing the tumor-cell-killing effect of chemotherapy. Although copper(ii)-related researches are wide, details of cuproptosis-related bioprocess in pan-cancer are not clear yet now, especially for prognosis and drug sensitivity prediction yet now.

METHODS

In this study, VOSviewer is used for the literature review, and R4.2.0 is used for data analysis. Public data are collected from TCGA and GEO, local breast cancer cohort is collected to verify the expression level of CDKN2A.

RESULTS

7036 published articles exhibited a time-dependent linear relationship (R=0.9781, p<0.0001), and breast cancer (33.4%) is the most researched topic. Cuproptosis-related-genes (CRGs)-based unsupervised clustering divides pan-cancer subgroups into four groups (CRG subgroup) with differences in prognosis and tumor immunity. 44 tumor-driver-genes (TDGs)-based prediction model of drug sensitivity and prognosis is constructed by artificial intelligence (AI). Based on TDGs and clinical features, a nomogram is (C- index: 0.7, p= 6.958e- 12) constructed to predict the prognosis of breast cancer. Importance analysis identifies CDKN2A has a pivotal role in AI modeling, whose higher expression indicates worse prognosis in breast cancer. Furthermore, inhibition of CDKN2A down-regulates decreases Snail1, Twist1, Zeb1, vimentin and MMP9, while E-cadherin is increased. Besides, inhibition of CDKN2A also decreases the expression of MEGEA4, phosphorylated STAT3, PD-L1, and caspase3, while cleaved-caspase3 is increased. Finally, we find down-regulation of CDKN2A or MAGEA inhibits cell migration and wound healing, respectively.

CONCLUSIONS

AI identified CRG subgroups in pan-cancer based on CRGs-related TDGs, and 44-gene-based AI modeling is a novel tool to identify chemotherapy sensitivity in breast cancer, in which CDKN2A/MAGEA4 pathway played the most important role.

A cuproptosis-related lncRNA signature predicts the prognosis and immune cell status in head and neck squamous cell carcinoma

Introduction

The incidence of head and neck squamous cell carcinoma (HNSCC), one of the most prevalent tumors, is increasing rapidly worldwide. Cuproptosis, as a new copper-dependent cell death form, was proposed recently. However, the prognosis value and immune effects of cuproptosis-related lncRNAs (CRLs) have not yet been elucidated in HNSCC.

Methods

In the current study, the expression pattern, differential profile, clinical correlation, DNA methylation, functional enrichment, univariate prognosis factor, and the immune effects of CRLs were analyzed. A four-CRL signature was constructed using the least absolute shrinkage and selection operator (LASSO) algorithm.

Results

Results showed that 20 CRLs had significant effects on the stage progression of HNSCC. Sixteen CRLs were tightly correlated with the overall survival (OS) of HNSCC patients. Particularly, lnc-FGF3-4 as a single risk factor was upregulated in HNSCC tissues and negatively impacted the prognosis of HNSCC. DNA methylation probes of cg02278768 (MIR9-3HG), cg07312099 (ASAH1-AS1), and cg16867777 (TIAM1-AS1) were also correlated with the prognosis of HNSCC. The four-CRL signature that included MAP4K3-DT, lnc-TCEA3-1, MIR9-3HG, and CDKN2A-DT had a significantly negative effect on the activation of T cells follicular helper and OS probability of HNSCC. Functional analysis revealed that cell cycle, DNA replication, and p53 signal pathways were enriched.

Discussion

A novel CRL-related signature has the potential of prognosis prediction in HNSCC. Targeting CRLs may be a promising therapeutic strategy for HNSCC.

A novel cuproptosis-related lncRNAs signature predicts prognosis in bladder cancer

This study constructed a novel cuproptosis-related lncRNAs signature to predict the prognosis of BLCA patients. The Cancer Genome Atlas (TCGA) database was used to retrieve the RNA-seq data together with the relevant clinical information. The cuproptosis-related genes were first discovered. The cuproptosis-related lncRNAs were then acquired by univariate, the least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analysis to create a predictive signature. An eight cuproptosis-related lncRNAs (AC005261.1, AC008074.2, AC021321.1, AL024508.2, AL354919.2, ARHGAP5-AS1, LINC01106, LINC02446) predictive signature was created. Compared with the low-risk group, the prognosis was poorer for the high-risk group. The signature served as an independent overall survival (OS) predictor. Receiver operating characteristic (ROC) curve indicated that the signature demonstrated superior predictive ability, as evidenced by the area under the curve (AUC) of 0.782 than the clinicopathological variables. When we performed a subgroup analysis of the different variables, the high-risk group's OS for BLCA patients was lower than that of the low-risk group's patients. Gene Set Enrichment Analysis (GSEA) showed that high-risk groups were clearly enriched in many immune-related biological processes and tumor-related signaling pathways. Single sample gene set enrichment analysis (ssGSEA) revealed that the immune infiltration level was different between the two groups. Finally, quantitative RT-PCR showed that AC005261.1, AC021321.1, AL024508.2, LINC02446 and LINC01106 were lowly expressed in tumor cells, while ARHGAP5-AS1 showed the opposite trend. In summary, the predictive signature can independently predict the prognosis and provide clinical treatment guidance for BLCA patients.

Construction and validation of a cuproptosis-related five-lncRNA signature for predicting prognosis, immune response and drug sensitivity in breast cancer

BACKGROUND

Despite advances in treatment, recurrence and mortality rates from breast cancer (BrCa) continue to rise, clinical effectiveness is limited, and prognosis remains disappointing, especially for patients with HER2-positive, triple-negative, or advanced breast cancer. Based on cuproptosis-related long noncoding RNAs (CRLs), this study aims to create a predictive signature to assess the prognosis in patients with BrCa.

METHODS

The related CRLs RNA-seq data clinicopathological data were collected from The Cancer Genome Atlas (TCGA) database, and the predictive model was constructed after correlation analysis. Subsequently, we examined and validated connections and changes in the CRLs model with prognostic features (including risk curves, ROC curves and nomograms), pathway and functional enrichment, tumor mutation (TMB), tumor immune dysfunction and exclusion (TIDE) and treatment sensitivity.

RESULTS

A prediction model formula composed of 5 CRLs was obtained, and divided breast cancer patients into high and low risk subgroups according to the obtained risk scores. The results showed that the overall survival (OS) of patients in the high-risk group was lower than that in the low-risk group, and the AUC of all samples at 1, 3 and 5 years were 0.704, 0.668 and 0.647, respectively. It was indicated that CRLs prognostic model could independently predict prognostic indicators of BrCa patients. In addition, analysis of gene set enrichment, immune function, TMB, and TIDE showed that these differentially expressed CRLs had a wealth of related pathways and functions, and might be closely related to immune response and immune microenvironment. Additionally, TP53 was found to have the highest mutation frequency in high-risk group (40%), while PIK3CA was found to have the highest mutation frequency in low-risk group (42%), which might become new targets for targeted therapy. Finally, we compared susceptibility to anticancer agents to identify potential treatment options for breast cancer. Lapatinib, Sunitinib, Phenformin, Idelalisib, Ruxolitinib, Cabozantinib were more sensitive to patients in the low-risk group, while Sorafenib, Vinorelbine, Pyrimethamine were more sensitive to patients in high-risk group, namely, these drugs could potentially be used in the future to treat breast cancer patients grouped according to the risk model.

CONCLUSION

This study identified CRLs associated with breast cancer and provided a tailored tool for predicting prognosis, immune response, and drug sensitivity in patients with BrCa.

Construction and validation of a novel cuproptosis-mitochondrion prognostic model related with tumor immunity in osteosarcoma

BACKGROUND

The purpose of this study was to develop a new prognostic model for osteosarcoma based on cuproptosis-mitochondrion genes.

MATERIALS AND METHODS

The data of osteosarcoma were obtained from TARGET database. By using Cox regression and LASSO regression analysis, a novel risk score was constructed based on cuproptosis-mitochondrion genes. Kaplan-Meier, ROC curve and independent prognostic analyses were performed to validate the risk score in GSE21257 dataset. Then, a predictive nomogram was constructed and further validated by calibration plot, C-index and ROC curve. Based on the risk score, all patients were divided into high-risk and low-risk group. GO and KEGG enrichment, immune correlation and drug sensitivity analyses were performed between groups. Real-time quantitative PCR verified the expression of cuproptosis-mitochondrion prognostic model genes in osteosarcoma. And we explored the function of FDX1 in osteosarcoma by western blotting, CCK8, colony formation assay, wound healing assay and transwell assays.

RESULTS

A total of six cuproptosis-mitochondrion genes (FDX1, COX11, MFN2, TOMM20, NDUFB9 and ATP6V1E1) were identified. A novel risk score and associated prognostic nomogram were constructed with high clinical application value. Strong differences in function enrichment and tumor immune microenvironment were shown between groups. Besides, the correlation of cuproptosis-mitochondrion genes and drug sensitivity were revealed to search for potential therapeutic target. The expression of FDX1, COX11, MFN2, TOMM20 and NDUFB9 at mRNA level was elevated in osteosarcoma cells compared with normal osteoblast hFOB1.19. The mRNA expression level of ATP6V1E1 was decreased in osteosarcoma. Compared with hFOB1.19, western blotting revealed that the expression of FDX1 was significantly elevated in osteosarcoma cells. Functional experiments indicated that FDX1 mainly promoted the migration of osteosarcoma rather than proliferation.

CONCLUSIONS

We developed a novel prognostic model of osteosarcoma based on cuproptosis-mitochondrion genes, which provided great guidance in survival prediction and individualized treatment decision making for patients with osteosarcoma.

Comprehensive analysis identifies cuproptosis-related gene DLAT as a potential prognostic and immunological biomarker in pancreatic adenocarcinoma

BACKGROUND

Cuproptosis is a regulated cell death form associated with tumor progression, clinical outcomes, and immune response. However, the role of cuproptosis in pancreatic adenocarcinoma (PAAD) remains unclear. This study aims to investigate the implications of cuproptosis-related genes (CRGs) in PAAD by integrated bioinformatic methods and clinical validation.

METHODS

Gene expression data and clinical information were downloaded from UCSC Xena platform. We analyzed the expression, mutation, methylation, and correlations of CRGs in PAAD. Then, based on the expression profiles of CRGs, patients were divided into 3 groups by consensus clustering algorithm. Dihydrolipoamide acetyltransferase (DLAT) was chosen for further exploration, including prognostic analysis, co-expression analysis, functional enrichment analysis, and immune landscape analysis. The DLAT-based risk model was established by Cox and LASSO regression analysis in the training cohort, and then verified in the validation cohort. Quantitative reverse transcriptase polymerase chain reaction (RT-qPCR) and immunohistochemistry (IHC) assays were performed to examine the expression levels of DLAT in vitro and in vivo, respectively.

RESULTS

Most CRGs were highly expressed in PAAD. Among these genes, increased DLAT could serve as an independent risk factor for survival. Co-expression network and functional enrichment analysis indicated that DLAT was engaged in multiple tumor-related pathways. Moreover, DLAT expression was positively correlated with diverse immunological characteristics, such as immune cell infiltration, cancer-immunity cycle, immunotherapy-predicted pathways, and inhibitory immune checkpoints. Submap analysis demonstrated that DLAT-high patients were more responsive to immunotherapeutic agents. Notably, the DLAT-based risk score model possessed high accuracy in predicting prognosis. Finally, the upregulated expression of DLAT was verified by RT-qPCR and IHC assays.

CONCLUSIONS

We developed a DLAT-based model to predict patients' clinical outcomes and demonstrated that DLAT was a promising prognostic and immunological biomarker in PAAD, thereby providing a new possibility for tumor therapy.

FDX1 serves as a prognostic biomarker and promotes glioma progression by regulating the immune response

The present study investigates the prognostic value of the FDX1 gene and its association with immune infiltration in gliomas. Gene expression profiles and corresponding clinical parameters of glioma patients were obtained from the Cancer Genome Atlas and Chinese Glioma Genome Atlas databases. In vitro experiments were also performed to validate its impact on malignant phenotypes of glioma cells. Kaplan-Meier analysis demonstrated that high FDX1 expression was associated with poor prognosis in glioma. Function and pathway enrichment for FDX1 predominantly demonstrated immunomodulatory function. In addition, the high-FDX1 expression group had higher Estimation of Stromal and Immune cells in malignant tumor tissues using Expression data, stromal, and immune scores (p<0.001). On evaluation of immunotherapy response, TIDE and dysfunction scores were higher in the low-FDX1 group, while the exclusion score demonstrated an opposite trend. In vitro tests showed that FDX1 silencing-induced inhibition of cell invasion and migration inactivated the nucleotide oligomerization domain (NOD)-like receptor signaling pathway by regulating PD-L1 expression. Notably, NOD1 expression was reversed in FDX1-knockdown cells after treatment with NOD1 agonists. In conclusion, FDX1 may play an important role in the diagnosis and treatment of gliomas. Regulating its expression may therefore help improve immunotherapy for these tumors.

Identification of an EMT-related gene-based prognostic signature in osteosarcoma

BACKGROUND

The correlation between epithelial-mesenchymal transition (EMT) and osteosarcoma (OS) has been widely reported. Integration of the EMT-related genes to predict the prognosis is significant for investigating the mechanism of EMT in OS. Here, we aimed to construct a prognostic EMT-related gene signature for OS.

METHODS

Transcriptomic and survival data of OS patients were downloaded from Therapeutically Applicable Research to Generate Effective Treatments (TARGET) and Gene Expression Omnibus (GEO). We performed univariate Cox regression, least absolute shrinkage and selection operator (LASSO) regression, and stepwise multivariate Cox regression analysis to construct EMT-related gene signatures. Kaplan-Meier analysis and time-dependent receiver operating characteristic (ROC) were applied to evaluate its predictive performance. GSVA, ssGSEA, ESTIMATE, and scRNA-seq were performed to investigate the tumor microenvironment, and the correlation between IC50 of drugs and ERG score was investigated. Furthermore, Edu and transwell experiments were conducted to assess the malignancy of OS cells.

RESULTS

We constructed a novel EMT-related gene signature (including CDK3, MYC, UHRF2, STC2, COL5A2, MMD, and EHMT2) for outcome prediction of OS. According to the signature, patients stratified into high- and low-ERG-score groups exhibited significantly different prognoses. ROC curves and Kaplan-Meier analysis revealed a promising performance of the signature with external validation. GSVA, ssGSEA, ESTIMATE algorithm, and scRNA-seq excavated EMT-related pathways and suggested the correlation between ERG score and immune activation. Notably, the pivotal gene CDK3 was upregulated in OS tissue and positively related to OS cell proliferation and migration.

CONCLUSION

Our EMT-related gene signature might reference OS risk stratification and guide clinical strategies as an independent prognostic factor in OS.

LncRNAs and regulated cell death in tumor cells

Regulated Cell Death (RCD) is a mode of cell death that occurs through drug or genetic intervention. The regulation of RCDs is one of the significant reasons for the long survival time of tumor cells and poor prognosis of patients. Long non-coding RNAs (lncRNAs) which are involved in the regulation of tumor biological processes, including RCDs occurring on tumor cells, are closely related to tumor progression. In this review, we describe the mechanisms of eight different RCDs which contain apoptosis, necroptosis, pyroptosis, NETosis, entosis, ferroptosis, autosis and cuproptosis. Meanwhile, their respective roles in the tumor are aggregated. In addition, we outline the literature that is related to the regulatory relationships between lncRNAs and RCDs in tumor cells, which is expected to provide new ideas for tumor diagnosis and treatment.

A five-cuproptosis-related LncRNA Signature: predicting prognosis, assessing immune function & drug sensitivity in lung squamous cell carcinoma

Lung squamous cell carcinoma has so far lacked effective targets for diagnosis and treatment. In cancer research, long noncoding RNAs (LncRNAs) emerge as novel therapeutic targets and biomarkers. Cuprophosis is a new death type involving multiple biological processes in tumor cells. Here, we aimed to explore whether Cuprophosis-related lncRNAs could be used to predict prognosis, assess immune function, and test drug sensitivity in LUSC patients. The Cancer Genome Map (TCGA) was used to obtain genome and clinical data, and Cuprophosis-relevant genes were found in the literature. A cuproptosis-related lncRNA risk model was built using co-expression analysis, univariate/multivariate Cox regression, and LASSO analysis. The survival analysis was used to assess the model's prognostic value. The univariate and multivariate Cox regression analyses were performed to determine whether risk score, age, gender, or clinical stages could be used as independent prognostic factors. Gene Set Enrichment Analysis and mutation analysis were performed on differentially expressed mRNA between high-risk and low-risk groups. The (TIDE) algorithm was used to conduct immunological functional analysis and drug sensitivity testing. Five cuproptosis-related LncRNAs were identified, and the selected LncRNAs constructed a prognosis model. According to the Kaplan-Meier survival analysis, the overall survival time for patients in the high-risk group was shorter than for those in the low-risk group. For LUSC patients, the risk score serves as an independent prognostic indicator. The GO and KEGG enrichment analysis revealed that the differentially expressed mRNAs between the high- and low-risk groups were enriched in several immune-related processes. The enrichment score of differentially expressed mRNAs in the high-risk group is higher than that of the low-risk group in multiple immune function pathways, including the IFN-γ and MHC I pathways. The Tumor Immune Dysfunction and Exclusion (TIDE) test revealed that the high-risk group was more likely to experience immune escape. The drug sensitivity analysis showed that patients with low-risk ratings were likely to respond to GW441756 and Salubrinal. In contrast, patients with higher risk scores were more responsive to dasatinib and Z-LLNIe CHO. The 5-Cuprophosis-related lncRNA signature can be used to predict prognosis, assess immune function, and test drug sensitivity in LUSC patients.

Role of cuproptosis in understanding diseases

Cell death is involved in a wide range of physiological and pathological processes. Recently, the term "cuproptosis" was coined to describe a novel type of cell death. This type of cell death, characterized by copper accumulation and proteotoxic stress, is a copper-dependent manner of death. Despite the progress achieved toward a better understanding of cuproptosis, mechanisms and related signaling pathways in physiology and pathology across various diseases remain to be proved. This mini review summarizes current research on cuproptosis and diseases, providing insights into prospective clinical therapies via targeting cuproptosis.

Cuproptosis-a potential target for the treatment of osteoporosis

Osteoporosis is an age-related disease of bone metabolism marked by reduced bone mineral density and impaired bone strength. The disease causes the bones to weaken and break more easily. Osteoclasts participate in bone resorption more than osteoblasts participate in bone formation, disrupting bone homeostasis and leading to osteoporosis. Currently, drug therapy for osteoporosis includes calcium supplements, vitamin D, parathyroid hormone, estrogen, calcitonin, bisphosphates, and other medications. These medications are effective in treating osteoporosis but have side effects. Copper is a necessary trace element in the human body, and studies have shown that it links to the development of osteoporosis. Cuproptosis is a recently proposed new type of cell death. Copper-induced cell death regulates by lipoylated components mediated via mitochondrial ferredoxin 1; that is, copper binds directly to the lipoylated components of the tricarboxylic acid cycle, resulting in lipoylated protein accumulation and subsequent loss of iron-sulfur cluster proteins, leading to proteotoxic stress and eventually cell death. Therapeutic options for tumor disorders include targeting the intracellular toxicity of copper and cuproptosis. The hypoxic environment in bone and the metabolic pathway of glycolysis to provide energy in cells can inhibit cuproptosis, which may promote the survival and proliferation of various cells, including osteoblasts, osteoclasts, effector T cells, and macrophages, thereby mediating the osteoporosis process. As a result, our group tried to explain the relationship between the role of cuproptosis and its essential regulatory genes, as well as the pathological mechanism of osteoporosis and its effects on various cells. This study intends to investigate a new treatment approach for the clinical treatment of osteoporosis that is beneficial to the treatment of osteoporosis.

An immune-related prognostic model predicts neoplasm-immunity interactions for metastatic nasopharyngeal carcinoma

Background

The prognosis of nasopharyngeal carcinoma (NPC) has been recognized to improve immensely owing to radiotherapy combined with chemotherapy. However, patients with metastatic NPC have a poor prognosis. Immunotherapy has dramatically prolonged the survival of patients with NPC. Hence, further research on immune-related biomarkers is imperative to establish the prognosis of metastatic NPC.

Methods

10 NPC RNA expression profiles were generated from patients with or without distant metastasis after chemoradiotherapy from the Fujian Cancer Hospital. The differential immune-related genes were identified and validated by immunohistochemistry analysis. The method of least absolute shrinkage and selection operator (LASSO)was used to further establish the immune-related prognostic model in an external GEO database (GSE102349, n=88). The immune microenvironment and signal pathways were evaluated in multiple dimensions at the transcriptome and single-cell levels.

Results

1328 differential genes were identified, out of which 520 were upregulated and 808 were downregulated. Notably, most of the immune genes and pathways were down-regulated in the metastasis group. A prognostic immune model involving nine hub genes. Patients in low-risk group were characterized by survival advantage, hot immune phenotype and benefit from immunotherapy. Compared with immune cells, malignant cell exhibited the most active levels of risk score by ssGSEA. Accordingly, intercellular communications including LT, CD70, CD40 and SPP1, and the like, between high-risk and low-risk were explored by the R package “Cellchat”.

Conclusion

We have constructed a model based on immunity of metastatic NPC and determined its prognostic value. The model identified the level of immune cell infiltration, cell-cell communication, along with potential immunotherapy for metastatic NPC.