Project description:Metal regulatory transcription factor 1 (MTF1) has been reported to induce the expression of metallothionein and other genes involved in metal homeostasis. However, the role of MTF1 in pan-cancer and tumor immunity remains unclear. In this study, we conducted a series of bioinformatics analyses to investigate the clinical significance and potential functions of MTF1 across various types of cancer. By employing bioinformatics algorithms and immunofluorescence assays, we analyzed the associations between MTF1 and immune infiltration in the tumor microenvironment as well as the expression levels of immune-related molecules. Our findings revealed dysregulation of MTF1 in pan-cancer along with its correlation with certain clinicopathological features, suggesting its diagnostic and prognostic value for multiple cancer types. Furthermore, our immune-associated analyses and assays demonstrated strong correlations between MTF1 expression and plasmacytoid dendritic cells (pDC), central memory T cells (Tcm), as well as several immune biomarkers. Subsequent in vitro assays indicated that MTF1 reduced the sensitivity of cancer cells to cuproptosis. Overall, our study highlights that MTF1 may serve as a promising biomarker for prognosis assessment and a potential therapeutic target for more effective treatment strategies against various cancers.
Project description:Cuproptosis, a newly suggested mechanism of controlled cellular demise, which has been extensively associated with aspects of occurrence and development in breast cancer. The aim of this study was to conduct a comprehensive multi-group bioinformatics analysis based on the expression of cuproptosis-related genes (CRGs) to identify novel breast cancer subtypes to guide clinical practice. We collected TCGA-BRCA and GSE42568 datasets to investigate the expression patterns of CRGs in breast cancer. Consensus cluster analysis was performed to identify distinct subtypes. Subsequently, an investigation was carried out to examine the disparities between CRGclusters through functional enrichment analysis. Finally, we examined microsatellite instability, tumor mutation burden, drug sensitivity, infiltration of immune cells and cancer cell stemness across different CRGclusters. We identified two subtypes, where CRGcluster S2 exhibits a poorer prognosis compared to CRGcluster S1. Moreover, CRGcluster S2 demonstrated lower immune infiltration scores, higher cancer cell stemness index, and increased tumor mutation burden relative to CRGcluster S1, with the most frequently mutated gene being ATP7A. Notably, breast cancer chemotherapy drugs such as docetaxel, doxorubicin, and paclitaxel exhibited reduced sensitivity towards CRGcluster S2 when compared to CRGcluster S1. We have identified two CRGclusters in breast cancer that could serve as potential therapeutic targets and warrant further investigation in clinical trial studies for breast cancer.
Project description:PurposeThe serine protease inhibitor clade E member 1 (SERPINE1) has been studied as a potential biomarker in a variety of cancers, but poorly studied in gastric cancer (GC). The purpose of this study was to explore the prognostic value of SERPINE1 in GC and primarily analyze its functions.MethodsWe analyzed the the prognostic value of SERPINE1 and studied the relationship with clinicopathologic biomarkers in gastric cancer. The expression of SERPINE1 was analyzed by GEO and TCGA databases. Moreover, we validated the results by immunohistochemistry. Next, the correlation analysis between SERPINE1 and the cuproptosis-related genes was analyzed by the "Spearman" method. CIBERSORT and TIMER algorithms were used to analyze the correlation of SERPINE1 with immune infiltration. Furthermore, GO and KEGG gene enrichment analyses were used to study the functions and pathways that SERPINE1 might be involved in. Then, drug sensitivity analysis was performed using CellMiner database. Finally, a cuproptosis-immune-related prognostic model was constructed using genes related to immune and cuproptosis, and verified against external datasets.ResultsSERPINE1 was up-regulated in gastric cancer tissues, which tends toward poor prognosis. Using immunohistochemistry experiment, the expression and prognostic value of SERPINE1 were verified. Then, we found that SERPINE1 was negatively correlated with cuproptosis-related genes FDX1, LIAS, LIPT1, and PDHA1. On the contrary, SERPINE1 was positively correlated with APOE. This indicates the effect of SERPINE1 on the cuproptosis process. Furthermore, by conducting immune-related analyses, it was revealed that SERPINE1 may promote the inhibitory immune microenvironment. The infiltration level of resting NK cells, neutrophils, activated mast cells, and macrophages M2 was positively correlated with SERPINE1. However, B cell memory and plasma cells were negatively correlated with SERPINE1. Functional analysis showed that SERPINE1 was closely related to angiogenesis, apoptosis, and ECM degradation. The KEGG pathway analysis showed that SERPINE1 may be associated with P53, Pi3k/Akt, TGF-β, and other signaling pathways. Drug sensitivity analysis showed that SERPINE1 could be also seen as a potential treatment target. The risk model based on SERPINE1 co-expression genes could better predict the survival of GC patients than SERPINE1 alone. We also verified the prognostic value of the risk score by GEO external datasets.ConclusionSERPINE1 is highly expressed in gastric cancer and related to poor prognosis. SERPINE1 may regulate cuproptosis and the immune microenvironment by a series of pathways. Therefore, SERPINE1 as a prognostic biomarker and potential therapeutic target deserves further study.
Project description:Background: Extensive research revealed copper and lncRNA can regulate tumor progression. Additionally, cuproptosis has been proven can cause cell death that may affect the development of tumor. However, there is little research focused on the potential prognostic and therapeutic role of cuproptosis-related lncRNA in OSCC patients. Methods: Data used were for bioinformatics analyses were downloaded from both the TCGA database and GEO database. The R software were used for statistical analysis. Mapping was done using the tool of FigureYa. Results: The signature consist of 7 cuproptosis-related lncRNA was identified through lasso and Cox regression analysis and a nomogram was developed. In addition, we performed genomic analyses including pathway enrichment analysis and mutation analysis between two groups. It was found that OSCC patients were prone to TP53, TTN, FAT1 and NOTCH1 mutations and a difference of mutation analysis between the two groups was significant. Results of TIDE analysis indicating that patients in low risk group were more susceptible to immunotherapy. Accordingly, results of subclass mapping analysis confirmed our findings, which revealed that patients with low riskscore were more likely to respond to immunotherapy. Conclusion: We have successfully identified and validated a novel prognostic signature with a strong independent predictive capacity. And we have found that patients with low riskscore were more susceptible to immunotherapy, especially PD-1 inhibitor therapy.
Project description:Cuprotosis is a novel mechanism of cell death that differs from known mechanisms, which depends on mitochondrial respiration and is closely related to lipoylated components of the tricarboxylic acid (TCA) cycle. However, it is unclear whether cuprotosis-related genes (CRGs) affect the tumor microenvironment (TME) and prognosis of patients with gastric cancer. In this study, the genetic and transcriptional characteristics of CRGs in gastric cancer (GC) were analyzed, and five CRGs that were differentially expressed and correlated with the survival of patients were obtained. Two different molecular subtypes were identified according to the five CRGs. Then, we constructed a CRG_score applied to patients of any age, gender, and stage. Subsequently, we found that cluster B and a high CRG_score had a worse prognosis, fewer immune checkpoints, and higher tumor immune dysfunction and exclusion (TIDE) compared to cluster A and a low CRG_score. In addition, two subtypes and the CRG_score were closely associated with clinicopathological characteristics, human leukocyte antigens (HLAs) and TME cell infiltration. A high CRG_score was featured with decreased microsatellite instability-high (MSI-H) and mutational burden. Meanwhile, the CRG_score was significantly related to the cancer stem cell (CSC) index and chemotherapeutic response. Moreover, we developed a nomogram to predict the survival probability of patients. Our study explained the role of CRGs in GC, and the prognostic signature could potentially provide an approach for personalized tumor therapy.
Project description:Patients with recurrent or metastatic cervical cancer are in urgent need of novel prognosis assessment or treatment approaches. In this study, a novel prognostic gene signature was discovered by utilizing cuproptosis-related angiogenesis (CuRA) gene scores obtained through weighted gene co-expression network analysis (WGCNA) of The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets. To enhance its reliability, the gene signature was refined by integrating supplementary clinical variables and subjected to cross-validation. Meanwhile, the activation of the VEGF pathway was inferred from an analysis of cell-to-cell communication, based on the expression of ligands and receptors in cell transcriptomic datasets. High-CuRA patients had less infiltration of CD8 + T cells and reduced expression of most of immune checkpoint genes, which indicated greater difficulty in immunotherapy. Lower IC50 values of imatinib, pazopanib, and sorafenib in the high-CuRA group revealed the potential value of these drugs. Finally, we verified an independent prognostic gene SFT2D1 was highly expressed in cervical cancer and positively correlated with the microvascular density. Knockdown of SFT2D1 significantly inhibited ability of the proliferation, migration, and invasive in cervical cancer cells. CuRA gene signature provided valuable insights into the prediction of prognosis and immune microenvironment of cervical cancer, which could help develop new strategies for individualized precision therapy for cervical cancer patients.
Project description:Cuproptosis is a novel form of cell death, correlated with the tricarboxylic acid (TCA) cycle. However, the metabolic features and the benefit of immune checkpoint inhibitor (ICI) therapy based on cuproptosis have not yet been elucidated in Hepatocellular carcinoma (HCC). First, we identified and validated three cuproptosis subtypes based on 10 cuproptosis-related genes (CRGs) in HCC patients. We explored the correlation between three cuproptosis subtypes and metabolism-related pathways. Besides, a comprehensive immune analysis of three cuproptosis subtypes was performed. Then, we calculated the cuproptosis-related gene prognostic index (CRGPI) score for predicting prognosis and validated its predictive capability by Decision curve analysis (DCA). We as well explored the benefit of ICI therapy of different CRGPI subgroups in two anti-PD1/PD-L1 therapy cohorts (IMvigor210 cohort and GSE176307). Finally, we performed the ridge regression algorithm to calculate the IC50 value for drug sensitivity and Gene set enrichment analysis (GSEA) analysis to explore the potential mechanism. We found that cluster A presented a higher expression of FDX1 and was correlated with metabolism, glycolysis, and TCA cycle pathways, compared with the other two clusters. HCC patients with high CRGPI scores had a worse OS probability, and we further found that the CRGPI-high group had high expression of PD1/PDL1, TMB, and better response (PR/CR) to immunotherapy in the IMvigor210 cohort and GSE176307. These findings highlight the importance of CRGPI serving as a potential biomarker for both prognostic and immunotherapy for HCC patients. Generally, our results provide novel insights about cuproptosis into immune therapeutic strategies.
Project description:BackgroundCuproptosis is a copper-dependent cell death mechanism that is associated with tumor progression, prognosis, and immune response. However, the potential role of cuproptosis-related genes (CRGs) in the tumor microenvironment (TME) of triple-negative breast cancer (TNBC) remains unclear.Patients and methodsIn total, 346 TNBC samples were collected from The Cancer Genome Atlas database and three Gene Expression Omnibus datasets, and were classified using R software packages. The relationships between the different subgroups and clinical pathological characteristics, immune infiltration characteristics, and mutation status of the TME were examined. Finally, a nomogram and calibration curve were constructed to predict patient survival probability to improve the clinical applicability of the CRG_score.ResultsWe identified two CRG clusters with immune cell infiltration characteristics highly consistent with those of the immune-inflamed and immune-desert clusters. Furthermore, we demonstrated that the gene signature can be used to evaluate tumor immune cell infiltration, clinical features, and prognostic status. Low CRG_scores were characterized by high tumor mutation burden and immune activation, good survival probability, and more immunoreactivity to CTLA4, while high CRG_scores were characterized by the activation of stromal pathways and immunosuppression.ConclusionThis study revealed the potential effects of CRGs on the TME, clinicopathological features, and prognosis of TNBC. The CRGs were closely associated with the tumor immunity of TNBC and are a potential tool for predicting patient prognosis. Our data provide new directions for the development of novel drugs in the future.
Project description:BackgroundGastric cancer is a fatal gastrointestinal cancer with high morbidity and poor prognosis. The dismal 5-year survival rate warrants reliable biomarkers to assess and improve the prognosis of gastric cancer. Distinguishing driver mutations that are required for the cancer phenotype from passenger mutations poses a formidable challenge for cancer genomics.MethodsWe integrated the multi-omics data of 293 primary gastric cancer patients from The Cancer Genome Atlas (TCGA) to identify key driver genes by establishing a prognostic model of the patients. Analyzing both copy number alteration and somatic mutation data helped us to comprehensively reveal molecular markers of genomic variation. Integrating the transcription level of genes provided a unique perspective for us to discover dysregulated factors in transcriptional regulation.ResultsWe comprehensively identified 31 molecular markers of genomic variation. For instance, the copy number alteration of WASHC5 (also known as KIAA0196) frequently occurred in gastric cancer patients, which cannot be discovered using traditional methods based on significant mutations. Furthermore, we revealed that several dysregulation factors played a hub regulatory role in the process of biological metabolism based on dysregulation networks. Cancer hallmark and functional enrichment analysis showed that these key driver (KD) genes played a vital role in regulating programmed cell death. The drug response patterns and transcriptional signatures of KD genes reflected their clinical application value.ConclusionsThese findings indicated that KD genes could serve as novel prognostic biomarkers for further research on the pathogenesis of gastric cancers. Our study elucidated a multidimensional and comprehensive genomic landscape and highlighted the molecular complexity of GC.
Project description:BackgroundThe mechanism of copper-induced cellular death was newly discovered and termed cuproptosis. Inducing cuproptosis in cancer cells is well anticipated for its curative potential in treating tumor diseases. However, ferredoxin 1 (FDX1), the core regulatory gene in cuproptosis, is rarely studied, and the regulation of FDX1 in tumor biology remains obscure. A comprehensive pan-cancer analysis of FDX1 is needed.MethodsThirty-three types of tumors were included with paired normal tissues in The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) datasets. The interaction between transcription, protein, phosphorylation, and promoter methylation levels was analyzed. Survival, immune infiltration, single-cell FDX1 expression, FDX1-related tumor mutational burden (TMB), microsatellite instability (MSI), stemness, tumor immune dysfunction and exclusion (TIDE), and immunotherapy-related analyses were performed. FDX1 protein expression was assessed by kidney renal clear cell carcinoma (KIRC) tissue microarray immunohistochemistry. The function of FDX1 in KIRC was further explored by experiments in 786-O cell lines in vitro.ResultsFDX1 is highly expressed in 15 tumor types and lowly expressed in 11 tumor types. The corresponding changes in protein expression, phosphorylation, and promoter methylation level of FDX1 have been described in several tumors. Survival analysis showed that FDX1 was related to favorable or poor overall survival in eight tumors and progression-free survival in nine tumors. Immune infiltration and single-cell analysis indicated the indispensable role of FDX1 expression in macrophages and monocytes. Multiple established immunotherapy cohorts suggested that FDX1 may be a potential predictor of treatment effects for tumor patients. Tissue microarray analysis showed decreased FDX1 expression in KIRC patients' tumor tissues. Knockdown of FDX1 resulted in the downregulation of cuproptosis in kidney renal clear tumor cells. Mechanistically, the FDX1-associated gene expression signature in KIRC is related to the enrichment of genes involved in the tricarboxylic acid (TCA) cycle, NOTCH pathway, etc. Several NOTCH pathway genes were differentially expressed in the high- and low-FDX1 groups in KIRC.ConclusionOur analysis showed that the central regulatory gene of cuproptosis, FDX1, has differential expression and modification levels in various tumors, which is associated with cellular function, immune modulation, and disease prognosis. Thus, FDX1-dependent cuproptosis may serve as a brand-new target in future therapeutic approaches against tumors.