Cuproptosis/ferroptosis-related gene signature is correlated with immune infiltration and predict the prognosis for patients with breast cancer

Identification of JAZF1, KNOP1, and PLEKHA1 as causally associated genes and drug targets for Alzheimer's disease: a summary data-based Mendelian randomization study

BACKGROUND

There is a growing body of evidence indicating the significant role of the immune system and immune cells in the progression of Alzheimer's disease (AD). However, the exact role of genes from various immune cell types in AD remains unclear. We aimed to utilize summary data-based Mendelian randomization (SMR) to explore the potential causal relationships between genes in specific immune cells and the risk of AD.

METHODS

By utilizing data sets of expression quantitative trait loci (eQTL) for 14 different immune cell types and large-scale AD genome-wide association study (GWAS), we employed SMR to identify key genes associated with AD within specific immune cells. Sensitivity analyses, including F-statistic, colocalization, and assessment of horizontal pleiotropy, were further conducted to validate the discovered genes. In addition, replication analyses were performed in AD GWAS from the FinnGen consortium. Finally, we further identified existing drugs that target or interact with the druggable genes and reviewed the studies about the associations between these drugs and AD.

RESULTS

SMR analysis revealed 342 genes associated with AD across 14 immune cell types. Further sensitivity analyses identified nine genes, CTSH, FCER1G, FNBP4, HLA-E, JAZF1, KNOP1, PLEKHA1, RP11-960L18.1, and ZNF638 that had significant associations with AD across nine specific immune cell types. JAZF1, KNOP1 and PLEKHA1 were replicated in an independent analysis using the GWAS data. The review on gene-related drugs also supported these findings.

CONCLUSIONS

Our research suggests that the expression of the genes JAZF1, KNOP1, and PLEKHA1 in specific immune cell types is related to the risk of AD.

Development of prognostic model incorporating a ferroptosis/cuproptosis-related signature and mutational landscape analysis in muscle-invasive bladder cancer

BACKGROUND

Muscle-invasive bladder cancer (MIBC) is a prevalent and aggressive malignancy. Ferroptosis and cuproptosis are recently discovered forms of programmed cell death (PCD) that have attracted much attention. However, their interactions and impacts on MIBC overall survival (OS) and treatment outcomes remain unclear.

METHODS

Data from the TCGA-BLCA project (as the training set), cBioPortal database, and GEO datasets (GSE13507 and GSE32894, as the test sets) were utilized to identify hub ferroptosis/cuproptosis-related genes (FRGs and CRGs) and develop a prognostic signature. Differential expression analysis (DEA) was conducted, followed by univariate and multivariate Cox's regression analyses and multiple machine learning (ML) techniques to select genetic features. The performance of the ferroptosis/cuproptosis-related signature was evaluated using Kaplan-Meier (K-M) survival analysis and receiver-operating characteristics (ROC) curves. Mutational and tumour immune microenvironment landscapes were also explored. Real-time quantitative reverse transcription polymerase chain reaction (RT-qPCR) experiments confirmed the expression patterns of the hub genes, and functional assays assessed the effects of SCD knockdown on cell viability, proliferation, and migration.

RESULTS

DEA revealed dysregulated FRGs and CRGs in the TCGA MIBC cohort. SCD, DDR2, and MT1A were identified as hub genes. A prognostic signature based on the sum of the weighted expression of these genes demonstrated strong predictive efficacy in the training and test sets. Nomogram incorporating this signature accurately predicted 1-, 3-, and 5-year survival probabilities in the TCGA cohort and GSE13507 dataset. Copy number variation (CNV) and tumour immune microenvironment analysis revealed that high risk score level groups were associated with immunosuppression and lower tumour purity. The associations of risk scores with immunotherapy and chemical drugs were also explored, indicating their potential for guiding treatment for MIBC patients. The dysregulated expression patterns of three hub genes were validated by RT-qPCR experiments.

CONCLUSIONS

Targeting hub FRGs and CRGs could be a promising therapeutic approach for MIBC. Our prognostic model offers a new framework for MIBC subtyping and can inform personalized therapeutic strategies.

Single-cell and bulk RNA-seq unveils the immune infiltration landscape associated with cuproptosis in cerebral cavernous malformations

BACKGROUND

Cerebral cavernous malformations (CCMs) are vascular abnormalities associated with deregulated angiogenesis. Their pathogenesis and optimal treatment remain unclear. This study aims to investigate the molecular signatures of cuproptosis, a newly identified type of cell death, associated with CCMs development.

METHODS

Bulk RNA sequencing (RNA-seq) from 15 CCM and 6 control samples were performed with consensus clustering and clustered to two subtypes based on expression levels of cuproptosis-related genes (CRGs). Differentially expressed genes and immune infiltration between subtypes were then identified. Machine learning algorithms including the least absolute shrinkage and selection operator and random forest were employed to screen for hub genes for CCMs associated with cuproptosis. Furthermore, Pathway enrichment and correlation analysis were used to explore the functions of hub genes and their association with immune phenotypes in CCMs. An external dataset was then employed for validation. Finally, employing the Cellchat algorithm on a single-cell RNA-seq dataset, we explored potential mechanisms underlying the participation of these hub genes in cell-cell communication in CCMs.

RESULTS

Our study revealed two distinct CCM subtypes with differential pattern of CRG expression and immune infiltration. Three hub genes (BTBD10, PFDN4, and CEMIP) were identified and validated, which may significantly associate with CCM pathogenesis. These genes were found to be significantly upregulated in CCM endothelial cells (ECs) and were validated through immunofluorescence and western blot analysis. Single-cell RNA-seq analysis revealed the cellular co-expression patterns of these hub genes, particularly highlighting the high expression of BTBD10 and PFDN4 in ECs. Additionally, a significant co-localization was also observed between BTBD10 and the pivotal cuproptosis gene FDX1 in Mki67+ tip cells, indicating the crucial role of cuproptosis for angiogenesis in CCMs. The study also explored the cell-cell communication between subcluster of ECs expressing these hub genes and immune cells, particularly M2 macrophages, suggesting a role for these interactions in CCM pathogenesis.

CONCLUSION

This study identifies molecular signatures linking cuproptosis to CCMs pathogenesis. Three hub genes-PFDN4, CEMIP, and BTBD10-may influence disease progression by modulating immunity. Further research is needed to understand their precise disease mechanisms and evaluate their potential as biomarkers or therapeutic targets for CCMs.

Cuproptosis: unveiling a new frontier in cancer biology and therapeutics

Copper plays vital roles in numerous cellular processes and its imbalance can lead to oxidative stress and dysfunction. Recent research has unveiled a unique form of copper-induced cell death, termed cuproptosis, which differs from known cell death mechanisms. This process involves the interaction of copper with lipoylated tricarboxylic acid cycle enzymes, causing protein aggregation and cell death. Recently, a growing number of studies have explored the link between cuproptosis and cancer development. This review comprehensively examines the systemic and cellular metabolism of copper, including tumor-related signaling pathways influenced by copper. It delves into the discovery and mechanisms of cuproptosis and its connection to various cancers. Additionally, the review suggests potential cancer treatments using copper ionophores that induce cuproptosis, in combination with small molecule drugs, for precision therapy in specific cancer types.

Crosstalk between ferroptosis and cuproptosis: From mechanism to potential clinical application

Ferroptosis and cuproptosis, regulated forms of cell death resulting from metal ion accumulation, are closely related in terms of occurrence, cell metabolism, signaling pathways, and drug resistance. Notably, it is now understood that these processes play crucial roles in regulating physiological and pathological processes, especially in tumor development. Consequently, ferroptosis and cuproptosis have gained increasing significance as potential targets for anti-cancer drug development. This article systematically outlines the molecular mechanisms and cross-talk components of both ferroptosis and cuproptosis, elucidating their impacts on cancer. Furthermore, it investigates the clinical perspective of targeted ferroptosis and cuproptosis in cancer chemotherapy, immunotherapy, and radiotherapy. Our discussion extends to a comparative analysis of nanoparticles developed based on the mechanisms of ferroptosis and cuproptosis in cancer, contrasting them with current conventional therapies. Opportunities and challenges in cancer treatment are explored, emphasizing the potential therapeutic direction of co-targeting ferroptosis and cuproptosis. The article also attempts to analyze the clinical applications of this co-targeting approach for cancer treatment while summarizing the existing barriers that require overcoming.

Clinical and Immunological Significance of ANKRD52 in Pan-Cancer

Ankyrin repeat domain 52 (ANKRD52) is a regulatory component of the protein phosphatase 6 (PP6) holoenzyme. Evidence has emerged to suggest involvement of ANKRD52 in tumor metastases and cancer cell escape from T cell-mediated elimination and immunotherapy but there has been no research across different cancer types. The current study explored the biological functions of ANKRD52 by combining data from many databases. The aim was to expose new diagnostic or treatment biomarkers for malignant tumors. The roles of ANKRD52 with respect to immunotherapy in 33 human cancer types were analyzed by combining data from The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), Cancer Cell Line Encyclopedia (CCLE), UCSC Xena, the Tumor Immune Estimation Resource (TIMER), TISIDB and Cellminer. Bioinformatics methods were used to analyze the association between ANKRD52 expression and prognosis, immunological indicators (immune cell infiltration, ESTIMATE scores and tumor microenvironment (TME) signatures), tumor mutational burden (TMB), microsatellite instability (MSI) and drug sensitivity. ANKRD52 expression was generally higher in 24 tumor tissues than in normal tissues and was associated with poor prognosis, especially in kidney chromophobe (KICH). Lower expression was observed in advanced cancer. ANKRD52 expression was strongly linked to major immunological indicators, such as immune cell infiltration, ESTIMATE scores, TME signatures, as well as expression of immune and tumor-related genes. Expression was also associated with indicators of immunotherapy efficacy and outcome, such as TMB in 7 cancer types and MSI in 12. In addition, ANKRD52 expression was linked to sensitivity to a number of anticancer drugs. ANKRD52 had a distinct immune function in breast invasive carcinoma (BRCA) that correlated negatively with most immune indicators. Expression was enriched in proliferation-, differentiation- and metabolism-related pathways and linked to other immune cells and TME signatures. A nomogram to predict 3- or 5-year overall survival (OS) of patients with BRCA was constructed. ANKRD52 may have utility as an oncological and immunological biomarker. New insights into oncogenesis are presented and the development of ANKRD52-targeting to increase the therapeutic efficacy of immunotherapy combined with chemotherapy explored.

A 15-Gene-Based Risk Signature for Predicting Overall Survival in SCLC Patients Who Have Undergone Surgical Resection

Small cell lung cancer (SCLC) is a malignancy with a poor prognosis whose treatment has not progressed for decades. The survival benefit of surgery and the selection of surgical candidates are still controversial in SCLC. This study is the first report to identify transcriptomic alterations associated with prognosis and propose a gene expression-based risk signature that can be used to predict overall survival (OS) in SCLC patients who have undergone potentially curative surgery. An integrative transcriptome analysis of three gene expression datasets (GSE30219, GSE43346, and GSE149507) revealed 1734 up-regulated and 2907 down-regulated genes. Cox-Mantel test, Cox regression, and Lasso regression analyses were used to identify genes to be included in the risk signature. EGAD00001001244 and GSE60052-cohorts were used for internal and external validation, respectively. Overall survival was significantly poorer in patients with high-risk scores compared to the low-risk group. The discriminatory performance of the risk signature was superior to other parameters. Multivariate analysis showed that the risk signature has the potential to be an independent predictor of prognosis. The prognostic genes were enriched in pathways including regulation of transcription, cell cycle, cell metabolism, and angiogenesis. Determining the roles of the identified prognostic genes in the pathogenesis of SCLC may contribute to the development of new treatment strategies. The risk signature needs to be validated in a larger cohort of patients to test its usefulness in clinical decision-making.