Effective prognostic risk model with cuproptosis-related genes in laryngeal cancer

Abstract Objective Laryngeal cancer, characterized by high recurrence rates and a lack of effective biomarkers, has been associated with cuproptosis, a regulated cell death process linked to cancer progression. In this study, we aimed to explore the roles of cuproptosis-related genes in laryngeal cancer and their potential as prognostic markers and therapeutic targets. Methods We collected comprehensive data from The Cancer Genome Atlas and Gene Expression Omnibus databases, including gene expression profiles and clinical data of laryngeal cancer patients. Using clustering and gene analysis, we identified cuproptosis-related genes with prognostic significance. A risk model was constructed based on these genes, categorizing patients into high- and low-risk groups for outcome comparison. Univariate and multivariate analyses were conducted to identify independent prognostic factors, which were then incorporated into a nomogram. Gene Set Enrichment Analysis was employed to explore pathways distinguishing high- and low-risk groups. Results Our risk model, based on four genes, including transmembrane 2, dishevelled binding antagonist of β-catenin 1, stathmin 2, and G protein-coupled receptor 173, revealed significant differences in patient outcomes between high- and low-risk groups. Independent prognostic factors were identified and integrated into a nomogram, providing a valuable tool for prognostic prediction. Gene Set Enrichment Analysis uncovered up-regulated pathways specifically associated with high-risk patient samples. Conclusion This study highlights the potential of cuproptosis-related genes as valuable prognostic markers and promising therapeutic targets in the context of laryngeal cancer. This research sheds light on new avenues for understanding and managing this challenging disease. Level of evidence: Level 4.

Construction of Prognostic Prediction Model for Lung Squamous Cell Carcinoma Based on Cuproptosis-related LncRNAs / 肿瘤防治研究

Objective To develop a new risk scoring model based on cuproptosis-related lncRNAs (CRLs) to predict the prognosis of lung squamous cell carcinoma (LUSC). Methods Data were obtained mainly from TCGA and GTEx databases. Univariate Cox, Lasso, and multivariate Cox regression analyses were conducted to determine CRLs that affect the prognosis of LUSC and establish a risk scoring model. The ability of risk score characteristics to independently predict LUSC survival was compared with that of clinical characteristics by calculating the area under the ROC curve (AUC). Immune-related functions and immune checkpoint differences were compared between high- and low-risk groups. Results Nine CRLs were selected as independent prognostic lncRNAs for LUSC, and a risk scoring model was developed. Risk score was the influence factor for the prognosis of LUSC. The AUC values predicted by the risk score model for 1-, 3-, and 5-year survival rates of patients with LUSC were 0.710, 0.718, and 0.743, respectively. The high- and low-risk groups were partly statistically different in terms of immune-related functional assays and immune checkpoint assays (P < 0.05). Conclusion The risk scoring model developed based on nine CRLs could predict the prognosis and immune therapy response of patients with LUSC in clinical practice.

Construction of Lung Adenocarcinoma Prognosis Model and Drug Sensitivity Analysis Based on Cuproptosis Related Genes / 中国肺癌杂志

BACKGROUND@#Lung cancer is one of the most common malignant tumors in the world, and the current lung cancer screening and treatment strategies are constantly improving, but its 5-year survival rate is still very low, which seriously endangers human health. Therefore, it is critical to explore new biomarkers to provide personalized treatment and improve the prognosis. Cuproptosis is a newly discovered type of cell death, which is due to the accumulation of excess copper ions in the cell, eventually leading to cell death, which has been suggested by studies to be closely related to the occurrence and development of lung adenocarcinoma (LUAD). Based on The Cancer Genome Atlas (TCGA) database, this study explored the association between cuproptosis-related genes (CRGs) and LUAD prognosis, established a prognostic risk model, and analyzed the interaction between CRGs and LUAD immune cell infiltration.@*METHODS@#The RNA-seq data of LUAD tissue and paracancerous or normal lung tissue were downloaded from the TCGA database; the RNA-seq data of normal lung tissue was downloaded from the Genotype-tissue Expression (GTEx) database, and the data of 462 lung adenocarcinoma cases were downloaded from the Gene Expression Omnibus repository (GEO) as verification. T the risk score model to assess prognosis was constructed by univariate Cox and Lasso-Cox regression analysis, and the predictive ability of the model was evaluated by receiver operating characteristic (ROC) curve and calibration curve. Immune-related and drug susceptibility analysis was further performed on high- and low-risk groups.@*RESULTS@#A total of 1656 CRGs and 1356 differentially expressed CRGs were obtained, and 13 CRGs were screened out based on univariate Cox and Lasso-Cox regression analysis to construct a prognostic risk model, and the area under the curves (AUCs) of ROC curves 1-, 3- and 5- year were 0.749, 0.740 and 0.689, respectively. Further study of immune-related functions and immune checkpoint differential analysis between high- and low-risk groups was done. High-risk groups were more sensitive to drugs such as Savolitinib, Palbociclib, and Cytarabine and were more likely to benefit from immunotherapy.@*CONCLUSIONS@#The risk model constructed based on 13 CRGs has good prognostic value, which can assist LUAD patients in individualized treatment, and provides an important theoretical basis for the treatment and prognosis of LUAD.

Biological characteristics and clinical significance of cuproptosis-related genes in lung adenocarcinoma / 中国胸心血管外科临床杂志

@#Objective     To investigate the biological characteristics and clinical significance of cuproptosis-related genes in lung adenocarcinoma (LUAD) based on the multi-omics data from The Cancer Genome Atlas. Methods     The cuproptosis-related genes were obtained from a study published in Science in March 2022. The whole genome data were used to reveal the mutation spectrum and copy number variation landscape of cuproptosis-related genes in LUAD and analyze its effects on transcriptome expression. Cuproptosis-related genes were annotated using Metascape analysis to further understand the pathways or functions in which these genes were involved. Subsequent univariate Cox analysis and Kaplan-Meier methods determined the prognosis of these genes in LUAD patients, and CellMiner analysis were used to identify those potential anticancer drugs for potentially targeting cuproptosis-related genes. Results     Cuproptosis-related genes were less frequently mutated in LUAD, and the effect of gene mutations on transcriptomic expression may depend on the type of mutation. Gene copy number variation was an important factor resulting in the disordered expression of cuproptosis-related genes. The 16 cuproptosis-related genes were mainly involved in glyoxylate metabolism and glycine degradation, copper ion entry, proteolitidylation, cellular amino acid catabolism process, oxidative stress response, etc. Among them, 6 genes (DLD, FDX1, DLAT, DLST, PDHA1, CDKN2A) were prognostic risk genes in LUAD. The CellMiner analysis suggested that 13 drugs were associated with 7 cuproptosis-related genes and they might be potential  anticancer drugs for potentially targeting cuproptosis. Conclusion     This study reveals the biological characteristics and clinical significance of cuproptosis-related genes in LUAD, and provides some reference and theoretical basis for the subsequent research of cuproptosis in cancer.

A novel cuproptosis-related gene signature for prediction of prognosis, drug sensitivity and immunotherapy response in patients with hepatocellular carcinoma / 中华肝胆外科杂志

Objective:To construct a novel cuproptosis-related gene signature (CRGS) for prediction of prognosis, immunotherapy response and drug sensitivity in patients with hepatocellular carcinoma (HCC).Methods:Data materials for this study were obtained from the international cancer genome consortium (ICGC), the cancer genome atlas (TCGA) database and Migort210 database, and protein expression profiles were obtained from the human protein atlas image classification database. Based on the TCGA cohort, the least absolute shrinkage and selection operator algorithm was applied to construct the CRGS and calculate the risk score for each HCC patient. HCC patients were grouped according to the median risk score: HCC patients in the TCGA cohort were divided into a high-risk group TCGA and a low-risk group TCGA with 184 cases in each group; HCC patients in the ICGC cohort were divided into a high-risk group ICGC and a low-risk group ICGC with 116 cases in each group. Patients in the Migort210 cohort were divided into a responder group ( n=68) and a non-responder group ( n=230) based on their response to immunotherapy. We assessed the value of CRGS in predicting the prognosis of HCC patients in the TCGA cohort and validated whether CRGS could be used to predict the prognosis of HCC patients in the ICGC dataset. To explore the role of CRGS in predicting immunotherapy response and drug sensitivity in HCC patients based on data from the TCGA cohort, and to apply the Migort210 immunotherapy cohort to validate the clinical value of CRGS in predicting immunotherapy in malignant tumors. Results:CRGS consists of four copper death-related genes: GLS, CDKN2A, LIPT1, and DLAT. Patients in the high-risk group TCGA had lower overall survival (OS), disease-specifical survival, and progression-free interval than those in the low-risk group TCGA (all P<0.01). OS of patients in the high-risk group ICGC was lower than that in the low-risk group ICGC ( P=0.022). Multivariate Cox regression analysis showed that CRGS was an independent risk factor for poor prognosis in HCC patients (TCGA: HR=2.991, 95% CI: 1.781-5.049, P<0.001; ICGC: HR=4.621, 95% CI: 1.685-12.674, P=0.033). Risk scores were positively correlated with the expression levels of CTLA4, PDCD1, CD80 and HLLA2 (all P<0.001). Patients in the high-risk group TCGA had lower tumor immune dysfunction and rejection scores than those in the low-risk group TCGA [-0.04(-0.07, -0.02) vs. -0.02(-0.04, 0) points], and the difference was statistically significant ( P<0.001). Patients in the responder group had a higher risk score than the non-responder group [1.70 (1.56, 1.90) vs. 1.63 (1.52, 1.80)], with a statistically significant difference ( P<0.05). The half-inhibitory concentrations (IC 50) for sunitinib, rapamycin and etanercept were higher in the high-risk group TCGA than that in the low-risk group TCGA, while the IC 50 for erlotinib was lower than that in the low-risk group TCGA, and the differences were all statistically significant (all P<0.001). Conclusion:The CRGS might be served as a potential biomarker to predict the prognoses, immunotherapy response, and drug sensitivity of patients with HCC.

Mechanisms of copper transporter 1 gene in regulating radiation induced intestinal injury / 中华放射医学与防护杂志

Objective:To investigate the effects and mechanisms of copper transporter 1 (CTR1) in radiation induced intestinal injury in vitro. Methods:Human small intestinal epithelial cells (HIEC) were irradiated with 2, 4, 6, 8 Gy of X-rays and rat intestinal epithelial cells (IEC-6) were irradiated with 5, 10, 15, 20 Gy of X-rays. At 2, 4, 8, 24, and 48 h after irradiation, the expression of CTR1 was detected by Western blot assay. In some experiments, HIEC and IEC-6 cells were transfected with CTR1 shRNA and then exposed to X-rays. Copper levels were detected by Inductively Coupled Plasma Mass Spectrometry (ICP-MS). The radiosensitivity of cells was verified by colonogenic assay, the cellular reactive oxygen species (ROS) level and DNA damage were detected to further explore the related mechanism. In addition, Western blot was applied to detect the expressions of antioxidants and cuproptosis associated proteins in enterocytes after silencing CTR1 or irradiation.Results:The expression of CTR1 was increased by X-ray irradiation in a dose-dependent manner ( t=3.53, 3.45, 6.37, 11.11, 11.13, P<0.05). CTR1 expression was successfully diminished by CTR1 shRNA adenovirus vectors. According to the survival curves, the enhancement ratios of the radiosensitivity of HIEC and IEC-6 cells with CTR1 knocking-down were 1.146 and 1.201, respectively. Radiation-induced copper accumulation was alleviated after CTR1 silencing in IEC-6 cells ( t=3.10, P<0.05). At 0.5 h after irradiation, the ROS production in the CTR1 knockdown group was significantly lower than that in the control group ( t=5.23, 2.96, P<0.05). At 1 h after irradiation, the protein expression of γ-H2AX in the CTR1 knockdown group was obviously lower than that in the control group ( t=7.50, 4.29, P<0.05). The expressions of Nrf2 and HO-1 were increased after irradiation, which could be further increased after CTR1 silencing. In addition, cuproptosis associated protein DLAT, LIAS and FDX1 were reduced post-irradiation, which were recovered after CTR1 silencing. Conclusions:The radioresistance of HIEC and IEC-6 cells was enhanced after CTR1 silencing, possibly through the intracellular ROS and cuproptosis pathway.

Construction of prognostic risk model of bladder cancer based on cuproptosis-related long non-coding RNAs / 浙江大学学报·医学版

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.

Cuproptosis-Related 4-Gene Risk Model for Predicting Immunotherapy Drug Response and Prognosis of Kidney Renal Clear Cell Carcinoma / 中国医学科学杂志(英文版)

Background Kidney renal clear cell carcinoma (KIRC) is one of the most common renal malignancies with a high mortality rate. Cuproptosis, a novel form of cell death, is strongly linked to mitochondrial metabolism and is mediated by protein lipoylation, leading to a proteotoxic stress response and cell death. To date, few studies have ellucidated the holistic role of cuproptosis-related genes (CRGs) in the pathogenesis of KIRC.Methods We comprehensively and completely analyzed the RNA sequencing data and corresponding clinical information from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. We screened for differentially expressed CRGs and constructed a prognostic risk model using univariate and multivariate Cox proportional regression analyses. Kaplan-Meier analysis was performed and receiver operating characteristic (ROC) curves were plotted to predict the prognosis of KIRC patients. Functional enrichment analysis was utilized to explore the internal mechanisms. Immune-related functions were analyzed using single-sample gene set enrichment analysis (ssGSEA), tumour immune dysfunction and exclusion (TIDE) scores, and drug sensitivity analysis.Results We established a concise prognostic risk model consisting of four CRGs (DBT, DLAT, LIAS and PDHB) to predict the overall survival (OS) in KIRC patients. The results of the survival analysis indicated a significantly lower OS in the high-risk group as compared to the patients in the low-risk group. The area under the time-dependent ROC curve (AUC) at 1, 3, and 5 year was 0.691, 0.618, and 0.614 in KIRC. Functional enrichment analysis demonstrated that CRGs were significantly enriched in tricarboxylic acid (TCA) cycle-related processes and metabolism-related pathways. Sorafenib, doxorubicin, embelin, and vinorelbine were more sensitive in the high-risk group.Conclusions We constructed a concise CRGs risk model to evaluate the prognosis of KIRC patients and this may be a new direction for the diagnosis and treatment of KIRC.

Research advances on the relationship between infectious diseases and programmed cell death / 中华临床感染病杂志

In recent years, with the progress of research on the molecular mechanism of cell death, it has been discovered that there are many new types of programmed cell death, including non-apoptotic (10 types) and apoptotic (2 types), which are widely involved in the pathogenesis of infectious diseases and tumors. It is also a frontier research topic and provides new ideas for disease prevention and treatment. This article reviews the published literature on programmed cell death, focusing on the characteristics of cell necrosis, apoptosis, pyroptosis, ferroptosis, neutrophil inflammatory cell death (NETosis), cuproptosis, and widespread apoptosis (PANoptosis), as well as their relationship with infectious diseases.