Construction of five cuproptosis-related lncRNA signature for predicting prognosis and immune activity in skin cutaneous melanoma

Yang, Xiaojing; Wang, Xing; Sun, Xinti; Xiao, M.; Fan, Liyun; Su, Yunwei; Xue, Lu; Luo, Sushan; Hou, S.; Wang, Huiping

doi:10.3389/fgene.2022.972899

Cited by 11 publications

(9 citation statements)

References 53 publications

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“…Changes inside the cellular immune microenvironment (TME) have been discovered to play a critical role in regulating the progression of various cancers and can affect the prognosis of SKCM in recent years. In yang's study, lower immune cell activity was linked to a worse prognosis in SKCM (Yang et al, 2022). Furthermore, Su's research demonstrated that increased immune activity can successfully inhibit tumor progression (Su et al, 2022) and is an extremely promising cancer strategy for treating.…”

Section: Discussionmentioning

confidence: 99%

Immune-related gene signature associates with immune landscape and predicts prognosis accurately in patients with skin cutaneous melanoma

Shen¹,

Shang²,

Han³

et al. 2023

Front. Genet.

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Skin cutaneous melanoma (SKCM) is the skin cancer that causes the highest number of deaths worldwide. There is growing evidence that the tumour immune microenvironment is associated with cancer prognosis, however, there is little research on the role of immune status in melanoma prognosis. In this study, data on patients with Skin cutaneous melanoma were downloaded from the GEO, TCGA, and GTEx databases. Genes associated with the immune pathway were screened from published papers and lncRNAs associated with them were identified. We performed immune microenvironment and functional enrichment analyses. The analysis was followed by applying univariate/multivariate Cox regression algorithms to finally identify three lncRNAs associated with the immune pathway for the construction of prognostic prediction models (CXCL10, RXRG, and SCG2). This stepwise downscaling method, which finally screens out prognostic factors and key genes and then uses them to build a risk model, has excellent predictive power. According to analyses of the model’s reliability, it was able to differentiate the prognostic value and continued existence of Skin cutaneous melanoma patient populations more effectively. This study is an analysis of the immune pathway that leads lncRNAs in Skin cutaneous melanoma in an effort to open up new treatment avenues for Skin cutaneous melanoma.

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Section: Discussionmentioning

confidence: 99%

Immune-related gene signature associates with immune landscape and predicts prognosis accurately in patients with skin cutaneous melanoma

Shen¹,

Shang²,

Han³

et al. 2023

Front. Genet.

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“…Cuproptosis-associated lncRNA was a good predictor of prognosis in patients with many types of tumors, such as hepatocellular carcinoma. [26, 27], cervical cancer [28], and melanoma [29]. Prognosis of patients with EC had not been studied by constructing predictive features of lncRNA associated with cuproptosis.…”

Section: Discussionmentioning

confidence: 99%

Identification of seven cuproptosis-related lncRNAs signature and establishment of a prognostic nomogram predicting overall survival in patients with endometrial cancer

Pang

Qian

2022

Preprint

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Cuproptosis is a new modality of cell death regulation that is currently considered as a new cancer treatment strategy. However, cuproptosis-related lncRNAs (CRLs) have an unclear relationship with endometrial cancer (EC). In this study, a total of 906 CRLs were identified, and 7 specific cuproptosis-related lncRNAs (AL807761.3, AF131215.7, AC008073.2, AC009229.1, CDKN2A.DT, LINC01615, LINC01166) were selected to conduct a risk model. Patients were divided into high- and low-risk groups according to the median of risk score. The prognosis of the high-risk group was worse than that of the low-risk group, and the predictive accuracy was high (AUC = 0.781), indicating the good reliability and specificity of our risk model. According to Gene Set Variation Analysis (GSVA) and GSEA, both metabolism and cytoskeleton have CRL participation. In addition, we found that the CRLs-related scores were associated with the ESTIMATE score. Stratified survival analysis also revealed that the risk signature have has a high prediction accuracy among people with different clinicopathological characteristics. Further in vitro experimental validation indicated that LINC01615 may promote the invasion of EC cells during progression. The efficient risk model based on seven CRLs has a high prognostic accuracy, and LINC01615 may act as a novel biomarker and therapeutic target for EC patients.

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“…Not surprisingly, the oxidative phosphorylation inhibitor Gboxin analog was found to have a strong proliferation inhibitory and cell cycle blocking effect on DLBCL with specific selectivity for it ( 34 ). Several recent studies have revealed the potential role of CRGs in the prognosis of cancers, such as kidney cancer ( 35 – 42 ), hepatocellular carcinoma ( 43 – 47 ), lung cancer ( 48 – 53 ), head and neck squamous cell carcinoma ( 53 – 60 ), glioma ( 61 – 66 ), breast cancer ( 67 – 70 ), endometrial carcinoma ( 71 , 72 ), melanoma ( 73 – 75 ), pancreatic cancer ( 76 , 77 ), colorectal cancer ( 78 – 81 ) and so on. However, no reports describe any effects of the cuproptosis regulatory mechanism on DLBCL.…”

Section: Introductionmentioning

confidence: 99%

Development and validation of a cuproptosis-associated prognostic model for diffuse large B-cell lymphoma

Zhang

Zhang²,

Zheng³

et al. 2023

Front. Oncol.

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Diffuse large B-cell lymphoma (DLBCL) is a highly heterogeneous disease. Therefore, more reliable biomarkers are required to better predict the prognosis of DLBCL. Cuproptosis is a novel identified form of programmed cell death (PCD) that is different from oxidative stress-related cell death (e.g., apoptosis, ferroptosis, and necroptosis) by Tsvetkov and colleagues in a recent study released in Science. Cuproptosis is copper-dependent PCD that is closely tied to mitochondrial metabolism. However, the prognostic value of cuproptosis-related genes (CRGs) in DLBCL remains to be further elucidated. In the present study, we systematically evaluated the molecular changes of CRGs in DLBCL and found them to be associated with prognosis. Subsequently, based on the expression profiles of CRGs, we characterized the heterogeneity of DLBCL by identifying two distinct subtypes using consensus clustering. Two isoforms exhibited different survival, biological functions, chemotherapeutic drug sensitivity, and immune microenvironment. After identifying differentially expressed genes (DEGs) between CRG clusters, we built a prognostic model with the Least absolute shrinkage and selection operator (LASSO) Cox regression analysis and validated its prognostic value by Cox regression analysis, Kaplan-Meier curves, and receiver operating characteristic (ROC) curves. In addition, the risk score can predict clinical characteristics, levels of immune cell infiltration, and prognosis. Furthermore, a nomogram incorporating clinical features and risk score was generated to optimize risk stratification and quantify risk assessment. Compared to the International Prognostic Index (IPI), the nomogram has demonstrated more accuracy in survival prediction. Furthermore, we validated the prognostic gene expression levels through external experiments. In conclusion, cuproptosis-related gene signature can serve as a potential prognostic predictor in DLBCL patients and may provide new insights into cancer therapeutic targets.

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Construction of five cuproptosis-related lncRNA signature for predicting prognosis and immune activity in skin cutaneous melanoma

Cited by 11 publications

References 53 publications

Immune-related gene signature associates with immune landscape and predicts prognosis accurately in patients with skin cutaneous melanoma

Immune-related gene signature associates with immune landscape and predicts prognosis accurately in patients with skin cutaneous melanoma

Identification of seven cuproptosis-related lncRNAs signature and establishment of a prognostic nomogram predicting overall survival in patients with endometrial cancer

Development and validation of a cuproptosis-associated prognostic model for diffuse large B-cell lymphoma

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