A novel cuproptosis-related lncRNA nomogram to improve the prognosis prediction of gastric cancer

Mycobacterium tuberculosis stimulates cuproptosis by regulating Lnc-Gm5532 to target FDX1 for bacteria intracellular survival

Cuproptosis is a novel cell death modality but its regulatory role in tuberculosis remains obscure. This study is committed to explore the specific mechanism of cuproptosis induced by Mycobacterium tuberculosis (M.tb) infection. We confirmed that M.tb induced cuproptosis contributes to its intracellular survival. Then microarray analysis was employed to screen M.tb-infected DE mRNAs and LncRNAs which may be potential regulators of cuproptosis. We focus on a key cuproptosis gene FDX1, and 7 LncRNAs that can target FDX1. Among them, LncRNA-Gm5532 upregulated the expression of FDX1 by sponging miR-7232-5p, which further promoted the expression of cuproptosis-associated proteins, increased intracellular copper ions, worsened lipid acylation-DLAT aggregation, and resulting in cuproptosis. Meanwhile, LncRNA-Gm5532 boosts the survival of M.tb in macrophages. Collectively, LncRNA-Gm5532 exacterbates M.tb-induced cuproptosis by targeting FDX1 and promotes immune escape of M.tb. The study will provide new insights into the regulation of tuberculosis pathogenesis.

Development of a cuproptosis-related prognostic signature to reveal heterogeneity of the immune microenvironment and drug sensitivity in acute lymphoblastic leukemia

BACKGROUND

Cuproptosis is a brand-new copper-dependent type of cell death that has been linked to various tumors. However, the relationship between cuproptosis and acute lymphoblastic leukemia (ALL) remains to be further elaborated.

METHODS

In ALL, 12 cuproptosis-related genes (CRGs) were analyzed at genetic and single-cell levels. Two molecular clusters were identified using "ConsensusClusterPlus". With the least absolute shrinkage and selection operator, a prognostic signature was built based on cuproptosis. The prognosis, clinical parameters, biological function, immune cell infiltration, therapy sensitivities, and transcription factor regulation of the clusters and risk subsets were further compared. Kaplan Meier curves, time-ROC curves, and nomogram were employed to evaluate the accuracy of the signature. Lastly, qRT-PCR was used to detect prognostic genes in cell lines and clinical samples.

RESULTS

CRGs exhibited extensive genetic variations and heterogeneous expression profiles in ALL. Single-cell analysis demonstrated that CRGs were strongly correlated with the biological characteristics of cancer cells. Two clusters and risk subgroups with distinct clinicopathological features, prognoses, biological functions, and drug sensitivities were identified. The cuproptosis signature was crucial in characterizing tumor immune landscape and cancer cell self-renewal ability. Furthermore, we explored that subtype A and high-scoring groups were more sensitive to immunotherapy. Multiple drugs with higher sensitivity among high-risk subgroups have been predicted. Nomograms demonstrated the clinical applicability of cuproptosis in risk assessment. The model was further validated in the verification cohort, our clinical specimens, and cell lines.

CONCLUSIONS

The cuproptosis-based model can characterize the tumor microenvironment, forecast survival results, and aid in improving risk assessment and personalized therapy options in ALL.

A novel prognostic model based on migrasome-related LncRNAs for gastric cancer

Gastric cancer (GC) represents a substantial public health challenge, characterized by elevated morbidity and mortality rates. Migrasomes, a newly discovered type of extracellular vesicle, have been highlighted as important contributors to cancer progression, though their specific role in GC remains unclear. To address this issue, we developed the first prognostic model utilizing migrasome-related long non-coding RNAs (MRLs). This model aims to deepen the understanding of GC pathogenesis and improve patient outcomes. Clinical and transcriptional data for 407 GC patients from TCGA were classified as training and testing sets. Through Pearson correlation analysis, 537 MRLs were recognized, and LASSO and Cox regression analyses further refined the list to four key lncRNAs (AC012055.1, LINC01150, AC053503.4, AC107021.2) for constructing the prognostic model. Kaplan-Meier survival analysis indicated a significantly poorer prognosis for the high-risk group. PCA confirmed the model's robustness, and univariate and multivariate analyses validated it as an independent predictor of clinical outcomes. The ROC curve and C-index evaluations further affirmed the model's predictive power. We developed a nomogram combining the MRLs signature with clinical parameters to enhance prognostic accuracy. GO, KEGG and GSEA were performed on migrasome-related genes associated with GC. Furthermore, high-risk patients exhibited increased immune cell infiltration and reduced tumor mutation burden, both associated with poorer outcomes. Additionally, twenty-nine potential therapeutic agents were identified. This novel MRLs-based model provides crucial insights into GC biology and represents a valuable tool for improving patient management and therapeutic strategies.

Bioinformatic analysis indicated that LINC01150 might be a novel neutrophil extracellular traps-related biomarker of gastric cancer

Gastric cancer (GC) is a highly aggressive malignancy associated with poor prognosis, particularly in its advanced stages. Neutrophil extracellular traps (NETs) have been implicated in cancer progression and immune therapy responses; however, the role of NETs-related long non-coding RNAs (lncRNAs) in GC remains poorly understood. This study used data from the Cancer Genome Atlas (TCGA) and previous research to identify NETs-related lncRNAs in GC. A prognostic signature comprising four NETs-related lncRNAs (NlncSig) was developed and validated, serving as a predictor for patient survival and response to immunotherapy. The NlncSig was correlated with poorer outcomes in high-risk patients and demonstrated that those with lower risk scores exhibited more favorable responses to immunotherapy. In vitro experiments confirmed that LINC01150 enhances GC cell proliferation, migration, and invasion. This robust NlncSig provides a reliable tool for predicting survival and immune characteristics in GC, with the potential to guide personalized therapeutic approaches and improve patient care.

Cuproptosis regulation by long noncoding RNAs: Mechanistic insights and clinical implications in cancer

Although survival rates have been improved in recent years, the prognosis of many cancer types remains inadequate, mostly owing to treatment resistance. Moreover, there is a continued need for exploring novel and reliable tumor markers to achieve accurate diagnosis. Understanding the molecular complexity of cancer allows for the development of more effective and personalized treatments and facilitates the discovery of biomarkers that surpass traditional ones and assist in cancer diagnosis and monitoring disease progression and response to treatment. Recent studies exploring the complexity of cancer biology have identified a new form of cell death, known as cuproptosis, which is driven by the accumulation of copper and subsequent stress induced by dysregulation of copper homeostasis. Increased copper level enables cancer cells to maintain their accelerated growth rates and metastatic potential, yet these cells can evade cuproptosis. Long noncoding RNAs (lncRNAs) have been recognized for their pivotal role in different hallmarks of cancer, including resistance to cell death. They have been found to be implicated in controlling copper balance and cuproptosis. Besides, lncRNAs associated with cuproptosis pathway have demonstrated their potential as diagnostic and prognostic cancer biomarkers as well as indicators of treatment response. Our review aims to summarize recent studies focusing on the intricate relationship between lncRNAs and cuproptosis and explore the mechanisms by which lncRNAs can modulate copper homeostasis and regulate cuproptosis pathway. We also highlight recent discoveries concerning the role of cuproptosis-related lncRNAs in diagnosis, prognosis, and therapy of different types of cancer. By elucidating the significance of cuproptosis-related lncRNAs, this review provides insights into how these lncRNAs can be used to develop new therapeutic strategies to improve treatment outcomes.

Harnessing nanomaterials for copper-induced cell death

Copper (Cu), an essential micronutrient with redox properties, plays a pivotal role in a wide array of pathological and physiological processes across virtually all cell types. Maintaining an optimal copper concentration is critical for cellular survival: insufficient copper levels disrupt respiration and metabolism, while excess copper compromises cell viability, potentially leading to cell death. Similarly, in the context of cancer, copper exhibits a dual role: appropriate amount of copper can promote tumor progression and be an accomplice, yet beyond befitting level, copper can bring about multiple types of cell death, including autophagy, apoptosis, ferroptosis, immunogenic cell death, pyroptosis, and cuproptosis. These forms of cell death are beneficial against cancer progression; however, achieving precise copper regulation within tumors remains a significant challenge in the pursuit of effective cancer therapies. The emergence of nanodrug delivery systems, distinguished by their precise targeting, controlled release, high payload capacity, and the ability to co-deliver multiple agents, has revitalized interest in exploiting copper's precise regulatory capabilities. Nevertheless, there remains a dearth of comprehensive review of copper's bidirectional effects on tumorigenesis and the role of copper-based nanomaterials in modulating tumor progression. This paper aims to address this gap by elucidating the complex role in cancer biology and highlighting its potential as a therapeutic target. Through an exploration of copper's dualistic nature and the application of nanotechnology, this review seeks to offer novel insights and guide future research in advancing cancer treatment.

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.

The role of cuproptosis in gastric cancer

As a biologically essential transition metal, copper is widely involved in various enzymatic reactions and crucial biological processes in the body. It plays an increasingly important role in maintaining normal cellular metabolism and supporting the growth and development of the human body. As a trace element, copper maintains the dynamic balance of its concentration in body fluids through active homeostatic mechanisms. Both excess and deficiency of copper ions can impair cell function, ultimately leading to cell damage and death. Cuproptosis is a novel form of cell death where copper ions cause cell death by directly binding to the lipoylated components of the citric acid cycle (CAC) in mitochondrial respiration and interfering with the levels of iron-sulfur cluster (Fe-S cluster) proteins, ultimately causing protein toxic stress. Its primary characteristics are Cu2+ concentration dependence and high expression in mitochondrial respiratory cells. Recent research has revealed that, compared to other forms of programmed cell death such as apoptosis, necrosis, and autophagy, cuproptosis has unique morphological and biochemical features. Cuproptosis is associated with the occurrence and development of various diseases, including cancer, neurodegenerative diseases, and cardiovascular diseases. This article focuses on a review of the relevance of cuproptosis in gastric cancer (GC).

lncRNAs as prognostic markers and therapeutic targets in cuproptosis-mediated cancer

Long non-coding RNAs (lncRNAs) have emerged as crucial regulators in various cellular processes, including cancer progression and stress response. Recent studies have demonstrated that copper accumulation induces a unique form of cell death known as cuproptosis, with lncRNAs playing a key role in regulating cuproptosis-associated pathways. These lncRNAs may trigger cell-specific responses to copper stress, presenting new opportunities as prognostic markers and therapeutic targets. This paper delves into the role of lncRNAs in cuproptosis-mediated cancer, underscoring their potential as biomarkers and targets for innovative therapeutic strategies. A thorough review of scientific literature was conducted, utilizing databases such as PubMed, Google Scholar, and ScienceDirect, with search terms like 'lncRNAs,' 'cuproptosis,' and 'cancer.' Studies were selected based on their relevance to lncRNA regulation of cuproptosis pathways and their implications for cancer prognosis and treatment. The review highlights the significant contribution of lncRNAs in regulating cuproptosis-related genes and pathways, impacting copper metabolism, mitochondrial stress responses, and apoptotic signaling. Specific lncRNAs are potential prognostic markers in breast, lung, liver, ovarian, pancreatic, and gastric cancers. The objective of this article is to explore the role of lncRNAs as potential prognostic markers and therapeutic targets in cancers mediated by cuproptosis.

Focus on cuproptosis: Exploring new mechanisms and therapeutic application prospects of cuproptosis regulation

Cuproptosis is a novel form of regulated cell death, which plays an important role in the physiological and pathological processes of the human body. Despite the increasing research on cuproptosis-related genes (CRGs) and their correlation with diseases, the pathogenesis of cuproptosis-related diseases remains unclear. Furthermore, there is a lack of reviews on the emerging technologies for regulating cuproptosis in disease treatment. This study delves into the copper-induced cell death mechanism, distinguishing cuproptosis from mechanisms like oxidative stress, glutathione synthesis inhibition, and ubiquitin-proteasome system inhibition. Several long-standing mysteries of diseases such as Wilson's disease and Menkes disease may be attributed to the occurrence of cuproptosis. In addition, we also review the detection indicators related to cuproptosis, providing targets for the diagnosis of cuproptosis-related diseases, and summarize the application value of cuproptosis in tumor therapy to better elucidate the impact of copper in cell death and diseases, and thus to promote the application prospects and possible strategies of cuproptosis-related substances, such as copper ion chelators, copper ion carriers, and copper nanomaterials, in disease therapy.

A depression-related lncRNA signature predicts the clinical outcome and immune characteristics of gastric cancer

Background

Depression and long non-coding RNA (lncRNA) have been reported to be associated with tumor progression and prognosis in gastric cancer (GC). This study aims to build a GC risk classification and prognosis model based on depression-related lncRNAs (DRLs).

Methods

To develop a risk model, we performed univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression analyses using RNA sequencing data of GC from The Cancer Genome Atlas (TCGA) and depression-related genes (DRGs) from previous studies. Kaplan-Meier analysis, receiver operating characteristic (ROC) curve analysis, nomogram construction, pathway enrichment analysis, assessment of immunological features, and drug sensitivity testing were conducted using a series of bioinformatics methods.

Results

Seven DRLs were identified to build a prognostic model, whose robustness was verified in an internal cohort. Subsequent prognostic analyses found that high risk scores were associated with worse overall survival (OS). Univariate and multivariate analyses revealed that the risk score could be used as an independent prognostic factor. Furthermore, the ROC curve indicated that the risk score had higher diagnostic efficiency than traditional clinicopathological features. The calibration curve confirmed the accuracy and reliability of the nomogram. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses showed that there were differences in digestive system and nervous system-related pathways between the high- and low-risk groups. Results of tumor mutational burden (TMB) and tumor immune dysfunction and exclusion (TIDE) analyses indicated that patients in the low-risk group had a better response rate to immunotherapy. Finally, the results of drug sensitivity analysis showed that risk score could influence sensitivity to EHT 1864 in GC.

Conclusion

We have successfully developed and verified a 7-DRL risk model which can assess the prognosis and immunological features and guide individualized therapy of GC patients.

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

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

Cuproptosis in cancers: Function and implications from bench to bedside

Copper, an indispensable micronutrient, is implicated in numerous vital biological processes and is essential for all physiological activities. Recently, the discovery of a novel type of copper-dependent cell death, known as cuproptosis, has shed light on its role in cancer development. Extensive research is currently underway to unravel the mechanisms underlying cuproptosis and its correlation with various cancer types. In this review, we summarize the findings regarding the roles and mechanisms of cuproptosis in various cancer types, including colorectal cancer, lung cancer, gastric cancer, breast cancer, liver cancer and cutaneous melanoma. Furthermore, the effects of copper-related agents such as copper chelators and copper ionophores on cell proliferation, apoptosis, angiogenesis, tumor immunity, and chemotherapy resistance have been explored in cancer preclinical and clinical trials. These insights provide promising avenues for the development of prospective anticancer drugs aimed at inducing cuproptosis.

Multi-omics analysis of the prognostic and biological role of cuproptosis-related gene in gastric cancer

Background

A considerable number of gastric cancer (GC) patients cannot receive benefits from current treatments. We aimed to identify possible biomarkers of cuproptosis-related genes (CRGs) in GC patients, which may help guide precision medicine-based decision-making.

Methods

RNA sequencing data, copy number variations (CNVs) data, and single nucleotide variant (SNV) data were obtained from The Cancer Genome Atlas (TCGA) database and Gene Set Cancer Analysis (GSCA) database. Chi-squared test was adopted to screen differentially expressed CRGs (DE-CRGs) between samples from 14 kinds of carcinoma and adjacent tissue samples. Then, GC samples were divided into high- and low-expressed groups based on DE-CRGs for further survival analyses and the selection of biomarkers. Methylation sites related with biomarkers were acquired. The correlation between immune cells and biomarkers was verified. Finally, miRNA-mRNA, TFs-mRNA, and co-expression networks were established to detect factors with regulating effects on biomarkers.

Results

Three CRGs including LIAS, GLS, and CDKN2A were identified as biomarkers in GC patients. Three methylation sites with a significant survival effect including cg13601799, 07562918, and 07253264 were acquired. Then, we found that B cells native was significantly correlated with CDKN2A, four immune cells such as T cells regulatory are significantly correlated with GLS, and two immune cells such as T cells CD4 memory activated were significantly correlated with LIAS. Moreover, 10 miRNAs in the miRNA-mRNA network and three transcription factors (TFs) in the TFs-mRNA network had a significant correlation with overall survival (OS). Finally, 20 enrichment functions were obtained on the basis of the co-expression network.

Conclusions

Three biomarkers with a prognosis prediction value of GC were found, and multi-factor regulatory networks were constructed to screen out 13 factors with regulating influences of biomarkers.

Predictors based on cuproptosis closely related to angiogenesis predict colorectal cancer recurrence

Up to one-third of colorectal cancer (CRC) patients experience recurrence after radical surgery, and it is still very difficult to assess and predict the risk of recurrence. Angiogenesis is the key factor of recurrence as metastasis of CRC is closely related to copper metabolism. Expression profiling by microarray from two datasets in Gene Expression Omnibus (GEO) was selected for quality control, genome annotation, normalization, etc. The identified angiogenesis-derived and cuproptosis-related Long non-coding RNAs (lncRNAs) and clinical data were screened and used as predictors to construct a Cox regression model. The stability of the model was evaluated, and a nomogram was drawn. The samples were divided into high-risk and low-risk groups according to the linear prediction of the model, and a Kaplan-Meier survival analysis was performed. In this study, a model was established to predict the postoperative recurrence of colon cancer, which exhibits a high prediction accuracy. Furthermore, the negative correlation between cuproptosis and angiogenesis was validated in colorectal cancer cell lines and the expression of lncRNAs in vitro was examined.

Screening of Cu4 O3 NPs efficacy and its anticancer potential against cervical cancer

Cu4 O3 is the least explored copper oxide, and its nanoformulation is anticipated to have important therapeutic potential especially against cancer. The current study aimed to biosynthesize Cu4 O3 nanoparticles (NPs) using an aqueous extract of pumpkin seeds and evaluate its antiproliferative efficacy against cervical cells after screening on different cancer cell lines. The obtained NPs were characterized by different spectroscopic analyses, such as UV-vis, thermogravimetric, energy dispersive X-ray, and Fourier-transform infrared spectroscopy (FTIR). In addition, high-resolution transmission electron microscopes (HR-TEM) were used to observe the morphology of the biosynthesized NPs. The UV-vis spectra showed a peak at around 332 nm, confirming the formation of Cu4 O3 NPs. Moreover, FTIR and TAG analyses identified the presence of various bioactive phytoconstituents that might have worked as capping and stabilization agents and comparative stable NPs at very high temperatures, respectively. The HR-TEM data showed the spherical shape of Cu4 O3 NPs in the range of 100 nm. The Cu4 O3 NPs was screened on three different cancer cell lines viz., Hela, MDA-MB-231, and HCT-116 using cytotoxicity (MTT) reduction assay. In addition, Vero was taken as a normal epithelial (control) cell. The high responsive cell line in terms of least IC50 was further assessed for its anticancer potential using a battery of biological tests, including morphological alterations, induction of apoptosis/ROS generation, regulation of mitochondrial membrane potential (MMP), and suppression of cell adhesion/migration. Vero cells (control) showed a slight decline in % cell viability even at the highest tested Cu4 O3 NPs concentration. However, all the studied cancer cells viz., MDA-MB-231, HCT 116, and HeLa cells showed a dose-dependent decline in cell viability after the treatment with Cu4 O3 NPs with a calculated IC50 value of 10, 11, and 7.2 µg/mL, respectively. Based on the above data, Hela cells were chosen for further studies, that showed induction of apoptosis from 3.5 to 9-folds by three different staining techniques acridine orange/ethidium bromide (AO/EB), 4',6-diamidino-2-phenylindole (DAPI), and propidium iodide (PI). The enhanced production of reactive oxygen species (>3.5-fold), modulation in MMP, and suppression of cell adhesion/migration were observed in the cells treated with Cu4 O3 NPs. The current study obtained the significant antiproliferative potential of Cu4 O3 NPs against the cervical cancer cell line, which needs to be confirmed further in a suitable in vivo model. Based on our results, we also recommend the green-based, eco-friendly, and cost-effective alternative method for synthesizing novel nanoformulation.

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.

Cuproptosis: emerging biomarkers and potential therapeutics in cancers

The sustenance of human life activities depends on copper, which also serves as a crucial factor for vital enzymes. Under typical circumstances, active homeostatic mechanisms keep the intracellular copper ion concentration low. Excess copper ions cause excessive cellular respiration, which causes cytotoxicity and cell death as levels steadily rise above a threshold. It is a novel cell death that depends on mitochondrial respiration, copper ions, and regulation. Cuproptosis is now understood to play a role in several pathogenic processes, including inflammation, oxidative stress, and apoptosis. Copper death is a type of regulatory cell death(RCD).Numerous diseases are correlated with the development of copper homeostasis imbalances. One of the most popular areas of study in the field of cancer is cuproptosis. It has been discovered that cancer angiogenesis, proliferation, growth, and metastasis are all correlated with accumulation of copper ions. Copper ion concentrations can serve as a crucial marker for cancer development. In order to serve as a reference for clinical research on the product, diagnosis, and treatment of cancer, this paper covers the function of copper ion homeostasis imbalance in malignant cancers and related molecular pathways.

Cuproptosis-related gene SLC31A1: prognosis values and potential biological functions in cancer

Cuproptosis is a unique type of cell death that may influence tumour formation by targeting lipoylated tricarboxylic acid cycle proteins. Solute carrier family 31 member 1 (SLC31A1), an important copper transporter, influences dietary copper absorption in the cell membrane. However, various SLC31A1 properties in pan-cancer profiles remain unknown. This study investigated the role of SLC31A1 in human malignancies and analysed its prognostic value. Raw data were obtained from The Cancer Genome Atlas database and processed using numerous internet databases, including UALCAN, GEPIA, cBioPortal, TIMER2.0, and Human Protein Atlas. SLC31A1 expression was found to be elevated in cervical, endometrial, and breast cancers compared to that in normal tissues, but reduced in clear cell renal cell carcinoma, liver hepatocellular carcinoma, and lung adenocarcinoma. Furthermore, SLC31A1 expression was strongly associated with overall survival and disease-free survival in several cancers. SLC31A1 gene mutations and methylations were identified in 33 cancers. SLC31A1 expression was positively correlated with immune cells in immune infiltration data. Single-cell sequencing revealed that SLC31A1 may play key roles in DNA repair, DNA damage, and proliferation. These findings may lead to better understanding of SLC31A1 in pan-cancer profiles and suggest that SLC31A1 could be a viable predictive biomarker, particularly in gynaecological cancers.

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.

Construction of prognostic risk model of bladder cancer based on cuproptosis-related long non-coding RNAs

OBJECTIVES

To construct a prognosis risk model based on long noncoding RNAs (lncRNAs) related to cuproptosis and to evaluate its application in assessing prognosis risk of bladder cancer patients.

METHODS

RNA sequence data and clinical data of bladder cancer patients were downloaded from the Cancer Genome Atlas database. The correlation between lncRNAs related to cuproptosis and bladder cancer prognosis was analyzed with Pearson correlation analysis, univariate Cox regression, Lasso regression, and multivariate Cox regression. Then a cuproptosis-related lncRNA prognostic risk scoring equation was constructed. Patients were divided into high-risk and low-risk groups based on the median risk score, and the immune cell abundance between the two groups were compared. The accuracy of the risk scoring equation was evaluated using Kaplan-Meier survival curves, and the application of the risk scoring equation in predicting 1, 3 and 5-year survival rates was evaluated using receiver operating characteristic (ROC) curves. Univariate and multivariate Cox regression were used to screen for prognostic factors related to bladder cancer patients, and a prognostic risk assessment nomogram was constructed, the accuracy of which was evaluated with calibration curves.

RESULTS

A prognostic risk scoring equation for bladder cancer patients was constructed based on nine cuproptosis-related lncRNAs. Immune infiltration analysis showed that the abundances of M0 macrophages, M1 macrophages, M2 macrophages, resting mast cells and neutrophils in the high-risk group were significantly higher than those in the low-risk group, while the abundances of CD8+ T cells, helper T cells, regulatory T cells and plasma cells in the low-risk group were significantly higher than those in the high-risk group (all P<0.05). Kaplan-Meier survival curve analysis showed that the total survival and progression-free survival of the low-risk group were longer than those of the high-risk group (both P<0.01). Univariate and multivariate Cox analysis showed that the risk score, age and tumor stage were independent factors for patient prognosis. The ROC curve analysis showed that the area under the curve (AUC) of the risk score in predicting 1, 3 and 5-year survival was 0.716, 0.697 and 0.717, respectively. When combined with age and tumor stage, the AUC for predicting 1-year prognosis increased to 0.725. The prognostic risk assessment nomogram for bladder cancer patients constructed based on patient age, tumor stage, and risk score had a prediction value that was consistent with the actual value.

CONCLUSIONS

A bladder cancer patient prognosis risk assessment model based on cuproptosis-related lncRNA has been successfully constructed in this study. The model can predict the prognosis of bladder cancer patients and their immune infiltration status, which may also provide a reference for tumor immunotherapy.

Development and validation of cuproptosis-related lncRNA signatures for prognosis prediction in colorectal cancer

BACKGROUND

Cuproptosis, a novel form of programmed cell death, plays an essential role in various cancers. However, studies of the function of cuproptosis lncRNAs (CRLs) in colorectal cancer (CRC) remain limited. Thus, this study aims to identify the cuprotosis-related lncRNAs (CRLs) in CRC and to construct the potential prognostic CRLs signature model in CRC.

METHODS

First, we downloaded RNA-Seq data and clinical information of CRC patients from TCGA database and obtained the prognostic CRLs based on typical expression analysis of cuproptosis-related genes (CRGs) and univariate Cox regression. Then, we constructed a prognostic model using the Least Absolute Shrinkage and Selection Operator algorithm combined with multiple Cox regression methods (Lasso-Cox). Next, we generated Kaplan-Meier survival and receiver operating characteristic curves to estimate the performance of the prognostic model. In addition, we also analysed the relationships between risk signatures and immune infiltration, mutation, and drug sensitivity. Finally, we performed quantitative reverse transcription polymerase chain reaction (qRT -PCR) to verify the prognostic model.

RESULT

Lasso-Cox analysis revealed that four CRLs, SNHG16, LENG8-AS1, LINC0225, and RPARP-AS1, were related to CRC prognosis. Receiver operating characteristic (ROC) and Kaplan-Meier analysis curves indicated that this model performs well in prognostic predictions of CRC patients. The DCA results also showed that the model included four gene signatures was better than the traditional model. In addition, GO and KEGG analyses revealed that DE-CRLs are enriched in critical signalling pathway, such as chemical carcinogenesis-DNA adducts and basal cell carcinoma. Immune infiltration analysis revealed significant differences in immune infiltration cells between the high-risk and low-risk groups. Furthermore, significant differences in somatic mutations were noted between the high-risk and low-risk groups. Finally, we also validated the expression of four CRLs in FHCs cell lines and CRC cell lines using qRT-PCR.

CONCLUSION

The signature composed of SNHG16, LENG8-AS1, LINC0225, and RPARP-AS1, which has better performance in predicting colorectal cancer prognosis and are promising biomarkers for prognosis prediction of CRC.

Study on the role and pharmacology of cuproptosis in gastric cancer

Objective

Gastric cancer has a poor prognosis and high mortality. Cuproptosis, a novel programmed cell death, is rarely studied in gastric cancer. Studying the mechanism of cuproptosis in gastric cancer is conducive to the development of new drugs, improving the prognosis of patients and reducing the burden of disease.

Methods

The TCGA database was used to obtain transcriptome data from gastric cancer tissues and adjacent tissues. GSE66229 was used for external verification. Overlapping genes were obtained by crossing the genes obtained by differential analysis with those related to copper death. Eight characteristic genes were obtained by three dimensionality reduction methods: lasso, SVM, and random forest. ROC and nomogram were used to estimate the diagnostic efficacy of characteristic genes. The CIBERSORT method was used to assess immune infiltration. ConsensusClusterPlus was used for subtype classification. Discovery Studio software conducts molecular docking between drugs and target proteins.

Results

We have established the early diagnosis model of eight characteristic genes (ENTPD3, PDZD4, CNN1, GTPBP4, FPGS, UTP25, CENPW, and FAM111A) for gastric cancer. The results are validated by internal and external data, and the predictive power is good. The subtype classification and immune type analysis of gastric cancer samples were performed based on the consensus clustering method. We identified C2 as an immune subtype and C1 as a non-immune subtype. Small molecule drug targeting based on genes associated with cuproptosis predicts potential therapeutics for gastric cancer. Molecular docking revealed multiple forces between Dasatinib and CNN1.

Conclusion

The candidate drug Dasatinib may be effective in treating gastric cancer by affecting the expression of the cuproptosis signature gene.

Cuproptosis: mechanisms and links with cancers

Cuproptosis was a copper-dependent and unique kind of cell death that was separate from existing other forms of cell death. The last decade has witnessed a considerable increase in investigations of programmed cell death, and whether copper induced cell death was an independent form of cell death has long been argued until mechanism of cuproptosis has been revealed. After that, increasing number of researchers attempted to identify the relationship between cuproptosis and the process of cancer. Thus, in this review, we systematically detailed the systemic and cellular metabolic processes of copper and the copper-related tumor signaling pathways. Moreover, we not only focus on the discovery process of cuproptosis and its mechanism, but also outline the association between cuproptosis and cancers. Finally, we further highlight the possible therapeutic direction of employing copper ion ionophores with cuproptosis-inducing functions in combination with small molecule drugs for targeted therapy to treat specific cancers.

Cuproptosis-related lncRNA signature for prognostic prediction in patients with acute myeloid leukemia

BACKGROUND

Long non-coding RNAs (lncRNAs) have been reported to have a crucial impact on the pathogenesis of acute myeloid leukemia (AML). Cuproptosis, a copper-triggered modality of mitochondrial cell death, might serve as a promising therapeutic target for cancer treatment and clinical outcome prediction. Nevertheless, the role of cuproptosis-related lncRNAs in AML is not fully understood.

METHODS

The RNA sequencing data and demographic characteristics of AML patients were downloaded from The Cancer Genome Atlas database. Pearson correlation analysis, the least absolute shrinkage and selection operator algorithm, and univariable and multivariable Cox regression analyses were applied to identify the cuproptosis-related lncRNA signature and determine its feasibility for AML prognosis prediction. The performance of the proposed signature was evaluated via Kaplan-Meier survival analysis, receiver operating characteristic curves, and principal component analysis. Functional analysis was implemented to uncover the potential prognostic mechanisms. Additionally, quantitative real-time PCR (qRT-PCR) was employed to validate the expression of the prognostic lncRNAs in AML samples.

RESULTS

A signature consisting of seven cuproptosis-related lncRNAs (namely NFE4, LINC00989, LINC02062, AC006460.2, AL353796.1, PSMB8-AS1, and AC000120.1) was proposed. Multivariable cox regression analysis revealed that the proposed signature was an independent prognostic factor for AML. Notably, the nomogram based on this signature showed excellent accuracy in predicting the 1-, 3-, and 5-year survival (area under curve = 0.846, 0.801, and 0.895, respectively). Functional analysis results suggested the existence of a significant association between the prognostic signature and immune-related pathways. The expression pattern of the lncRNAs was validated in AML samples.

CONCLUSION

Collectively, we constructed a prediction model based on seven cuproptosis-related lncRNAs for AML prognosis. The obtained risk score may reveal the immunotherapy response in patients with this disease.

Cuproptosis-Related LncRNA-Based Prediction of the Prognosis and Immunotherapy Response in Papillary Renal Cell Carcinoma

Cuproptosis, a new cell death pattern, is promising as an intervention target to treat tumors. Abnormal long non-coding RNA (lncRNA) expression is closely associated with the occurrence and development of papillary renal cell carcinoma (pRCC). However, cuproptosis-related lncRNAs (CRLs) remain largely unknown as prognostic markers for pRCC. We aimed to forecast the prognosis of pRCC patients by constructing models according to CRLs and to examine the correlation between the signatures and the inflammatory microenvironment. From the Cancer Genome Atlas (TCGA), RNA sequencing, genomic mutations and clinical data of TCGA-KIRP (Kidney renal papillary cell carcinoma) were analyzed. Randomly selected pRCC patients were allotted to the training and testing sets. To determine the independent prognostic impact of the training characteristic, the least absolute shrinkage and selection operator (LASSO) algorithm was utilized, together with univariate and multivariate Cox regression models. Further validation was performed in the testing and whole cohorts. External datasets were utilized to verify the prognostic value of CRLs as well. The CRLs prognostic features in pRCC were established based on the five CRLs (AC244033.2, LINC00886, AP000866.1, MRPS9-AS1 and CKMT2-AS1). The utility of CRLs was evaluated and validated in training, testing and all sets on the basis of the Kaplan-Meier (KM) survival analysis. The risk score could be a robust prognostic factor to forecast clinical outcomes for pRCC patients by the LASSO algorithm and univariate and multivariate Cox regression. Analysis of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) data demonstrated that differentially expressed genes (DEGs) are primarily important for immune responses and the PI3K-Akt pathway. Arachidonic acid metabolism was enriched in the high-risk set by Gene Set Enrichment Analysis (GSEA). In addition, Tumor Immune Dysfunction and Exclusion (TIDE) analysis suggested that there was a high risk of immune escape in the high-risk cohort. The immune functions of the low- and high-risk sets differed significantly based on immune microenvironment analysis. Finally, four drugs were screened with a higher sensitivity to the high-risk set. Taken together, a novel model according to five CRLs was set up to forecast the prognosis of pRCC patients, which provides a potential strategy to treat pRCC by a combination of cuproptosis and immunotherapy.

A novel cuproptosis-related prognostic 2-lncRNAs signature in breast cancer

Background: Cuproptosis, a newly defined regulated form of cell death, is mediated by the accumulation of copper ions in cells and related to protein lipoacylation. Seven genes have been reported as key genes of cuproptosis phenotype. Cuproptosis may be developed by subsequent research as a target to treat cancer, such as breast cancer. Long-noncoding RNA (lncRNA) has been proved to play a vital role in regulating the biological process of breast cancer. However, the role of lncRNAs in cuproptosis is poorly studied. Methods: Based on TCGA (The Cancer Genome Atlas) database and integrated several R packages, we screened out 153 cuproptosis-related lncRNAs and constructed a novel cuproptosis-related prognostic 2-lncRNAs signature (BCCuS) in breast cancer and then verified. By using pRRophetic package and machine learning, 72 anticancer drugs, significantly related to the model, were screened out. qPCR was used to detect the differentially expression of two model lncRNAs and seven cuproptosis genes between 10 pairs of breast cancer tissue samples and adjacent samples. Results: We constructed a novel cuproptosis-related prognostic 2-lncRNAs (USP2-AS1, NIFK-AS1) signature (BCCuS) in breast cancer. Univariate COX analysis (p < .001) and multivariate COX analysis (p < .001) validated that BCCuS was an independent prognostic factor for breast cancer. Overall survival Kaplan Meier-plotter, ROC curve and Risk Plot validated the prognostic value of BCCuS both in test set and verification set. Nomogram and C-index proved that BCCuS has strong correlation with clinical decision-making. BCCuS still maintain inspection efficiency when patients were splitting into Stage I-II (p = .024) and Stage III-IV (p = .003) breast cancer. BCCuS-high group and BCCuS-low group showed significant differences in gene mutation frequency, immune function, TIDE (tumor immune dysfunction and exclusion) score and other phenotypes. TMB (tumor mutation burden)-high along with BCCuS-high group had the lowest Survival probability (p = .005). 36 anticancer drugs whose sensitivity (IC50) was significantly related to the model were screened out using pRRophetic package. qPCR results showed that two model lncRNAs (USP2-AS1, NIFK-AS1) and three Cuproptosis genes (FDX1, PDHA1, DLAT) expressed differently between 10 pairs of breast cancer tissue samples and adjacent samples. Conclusion: The current study reveals that cuproptosis-related prognostic 2-lncRNAs signature (BCCuS) may be useful in predicting the prognosis, biological characteristics, and appropriate treatment of breast cancer patients.

Characteristics of Adenosine-to-Inosine RNA editing-based subtypes and novel risk score for the prognosis and drug sensitivity in stomach adenocarcinoma

Stomach adenocarcinoma (STAD) is always characterized by high mortality and poor prognosis with drug resistance and recrudescence due to individual genetic heterogeneity. Adenosine-to-Inosine RNA editing (ATIRE) has been reported associated with multiple tumors but the potential connection between ATIRE-related signatures and STAD remains unclear. In this study, we comprehensively elevated the genetic characteristics of ATIRE in STAD patients and first screened five vital survival-related ATIRE sites to identify a novel ATIRE-Risk score. Based on the risk scores, we further divided the patients into two different subtypes with diverse clinical characteristics and immune landscapes including immune cell infiltration (ICI), tumor microenvironment (TME), and immune checkpoint expression analysis. The low-risk subgroups, associated with better survival prognosis, were characterized by activated immune-cells, higher immune scores in TME, and down-expression of immunotherapy checkpoints. Moreover, different expressional genes (DEGs) between the above subtypes were further identified and the activation of immune-related pathways were found in low-risk patients. The stratified survival analysis further indicated patients with low-risk and high-tumor mutation burden (TMB) exhibited the best prognosis outcomes, implying the role of TMB and ATIRE-Risk scores was synergistic for the prognosis of STAD. Interestingly, anti-tumor chemotherapeutic drugs all exhibited lower IC50 values in low-risk subgroups, suggesting these patients might obtain a better curative response from the combined chemotherapy of STAD. Finally, combined with classical clinical features and ATIRE-Risk scores, we successfully established a promising nomogram system to accurately predict the 1/3/5-years survival ratio of STAD and this model was also estimated with high diagnostic efficiency and stable C-index with calibration curves. These significant ATIRE sites are promising to be further explored and might serve as a novel therapeutic target for STAD treatment.

Comprehensive analysis of cuproptosis-related lncRNAs model in tumor immune microenvironment and prognostic value of cervical cancer

Cervical cancer (CC) is the fourth leading gynecological malignancy in females worldwide. Cuproptosis, a form of cell death induced by copper, elicits a novel therapeutic strategy in anticancer therapy. Nonetheless, the effects of cuproptosis-related lncRNAs in CC remain unclear. Therefore, we aim to investigate cuproptosis-related lncRNAs, develop a risk model for prognostic prediction, and elucidate the immunological profile of CC. Transcription profiles and clinical follow-up data of CC were retrieved from The Cancer Genome Atlas (TCGA) database. Afterward, the risk model was built by distinguishing prognostic cuproptosis-related lncRNAs using the least absolute shrinkage and selection operator (LASSO) Cox regression. The correctness of the risk model was validated, and a nomogram was established followed by tumor immune microenvironment analysis. Tumor immune dysfunction and exclusion (TIDE) scores were used to assess immunotherapy response, and anticancer pharmaceutical half-maximal inhibitory concentration (IC50) prediction was performed for potential chemotherapy medicines. Finally, through coexpression analysis, 199 cuproptosis-related lncRNAs were collected. A unique risk model was generated using 6 selected prognostic cuproptosis-related lncRNAs. The risk score performed a reliable independent prediction of CC survival with higher diagnostic effectiveness compared to generic clinical characteristics. Immunological cell infiltration investigation indicated that the risk model was substantially linked with CC patients' immunology, and the low-risk patients had lower TIDE scores and increased checkpoint expression, suggesting a stronger immunotherapy response. Besides, the high-risk group exhibited distinct sensitivity to anticancer medications. The immune-related progression was connected to the differentially expressed genes (DEGs) between risk groups. Generally, the risk model comprised 6 cuproptosis-related lncRNAs that may help predict CC patients' overall survival, indicate immunocyte infiltration, and identify individualized treatment.

A pan-cancer analysis of copper homeostasis-related gene lipoyltransferase 1: Its potential biological functions and prognosis values

As a key copper homeostasis-related molecule, lipoyltransferase 1 (LIPT1) is an essential enzyme for the activation of mitochondrial 2-ketoacid dehydrogenase, participating in fatty acylation. However, the biological significances of LIPT1 in the pan-cancer are unclear. Here, we comprehensively analyzed the functional characteristics of LIPT1 in human cancers and its roles in immune response. We found that LIPT1 was down-regulated in some cancers. And LIPT1 overexpression is associated with favorable prognosis in these patients, such as breast cancer, clear cell renal cell carcinoma, ovarian cancer and gastric cancer. We also explored the mutational status and methylation levels of LIPT1 in human cancers. Gene enrichment analysis indicated that abnormally expressed LIPT1 was significantly associated with immune cells infiltration, such as B cells, CD8+ T cells and cancer-associated fibroblast cells. The result from single cell sequencing reflected the important roles of LIPT1 in the regulation of several biological behaviors of cancer cells, such as DNA damage response and cell apoptosis. Taken together, our research could provide a comprehensive overview about the significances of LIPT1 in human pan-cancer progression, prognosis and immune.