Comprehensive analysis of the prognostic signature and tumor microenvironment infiltration characteristics of cuproptosis-related lncRNAs for patients with colon adenocarcinoma

Cui, Guoliang; Liu, Jinhui; Wang, Can; Gu, Renjun; Wang, Manli; Sun, Ziying; Wei, Fei

doi:10.3389/fonc.2022.1007918

Cited by 11 publications

(4 citation statements)

References 68 publications

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“…The calibration curve shows the deviation between the predicted value of the model and the actual value, which is another way to test the prediction ability of the model ( Gittleman et al, 2020 ). Similar to the results of other studies ( Liu et al, 2021b ; Cui et al, 2022 ), the calibration curve showed that the observed OS ratios in 1, 3 and 5 years were in good agreement with the predicted ratios.…”

Section: Discussionsupporting

confidence: 89%

A neutrophil extracellular traps-associated lncRNA signature predicts the clinical outcomes in patients with lung adenocarcinoma

Ding

Zhang

et al. 2022

Front. Genet.

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Backgrounds: Neutrophil extracellular traps (NETs) play an important role in the occurrence, metastasis, and immune escape of cancers. We aim to investigate Long non-coding RNAs (lncRNAs) that are correlated to NETs to find some potentially useful biomarkers for lung adenocarcinoma (LUAD), and to explore their correlations with immunotherapy and chemotherapy, as well as the tumor microenvironment.Methods: Based on the The Cancer Genome Atlas (TCGA) database, we identified the prognosis-related lncRNAs which are associated with NETs using cox regression. The patients were then separated into two clusters based on the expression of NETs-associated lncRNAs to perform tumor microenvironment analysis and immune-checkpoint analysis. Least absolute shrinkage and selection operator (LASSO) regression was then performed to establish a prognostic signature. Furthermore, nomogram analysis, tumor mutation burden analysis, immune infiltration analysis, as well as drug sensitivity analysis were performed to test the signature.Results: Using univariate cox regression, we found 10 NETs-associated lncRNAs that are associated with the outcomes of LUAD patients. Also, further analysis which separated the patients into 2 clusters showed that the 10 lncRNAs had significant correlations with the tumor microenvironment. Using LASSO regression, we finally constructed a signature to predict the outcomes of the patients based on 4 NETs-associated lncRNAs. The 4 NETs-associated lncRNAs were namely SIRLNT, AL365181.3, FAM83A-AS1, and AJ003147.2. Using Kaplan-Meier (K-M) analysis, we found that the risk model was strongly associated with the survival outcomes of the patients both in the training group and in the validation group 1 and 2 (p < 0.001, p = 0.026, and p < 0.01). Using receiver operating characteristic (ROC) curve, we tested the sensitivity combined with the specificity of the model and found that the risk model had a satisfactory level of 1-year, 3-year, and 5-year concordance index (C-index) (C = 0.661 in the training group, C = 0.679 in validation group 1, C = 0.692 in validation group 2). We also explored the immune microenvironment and immune checkpoint correlation of the risk model and found some significant results.Conclusion: We constructed a NETs-associated lncRNA signature to predict the outcome of patients with LUAD, which is associated with immunephenoscores and immune checkpoint-gene expression.

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Section: Discussionsupporting

confidence: 89%

A neutrophil extracellular traps-associated lncRNA signature predicts the clinical outcomes in patients with lung adenocarcinoma

Ding

Zhang

et al. 2022

Front. Genet.

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“…Previous studies have showed that cuproptosis related lncRNAs were closely associated with head and neck squamous cell cancer [18], hepatocellular carcinoma [19], colon adenocarcinoma [20], and glioma [21]. However, the correlation between cuproptosis related lncRNAs and ESCA remains unclear.…”

Section: Discussionmentioning

confidence: 99%

A novel cuproptosis-related LncRNA signature predicts prognosis inpatients with esophageal carcinoma

Shang

Min

et al. 2023

Preprint

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Background: Esophageal cancer (ESCA) is a significant cause of tumor-related mortality worldwide. Cuproptosis is a novel cell death which is different from other regulate cell death, including ferroptosis, pyroptosis and apoptosis. However, the role of cuproptosis in the initiation and progression of ESCA remains unknown. Methods: The transcriptome data and clinical data of 173 patients with esophageal cancer in TCGA database were sorted and extracted with Perl software. Pearson correlation analysis was performed on cuproptosis related genes and all lncRNAs. The prognostic related lncRNAs were determined by univariate and multivariate Cox regression analysis, and a new prognostic model was constructed to calculate the risk score of each patient. C-Index curve, PCA analysis and ROC curve analysis were used to evaluate the prognosis prediction performance of 3- cuproptosis related lncRNAs (CRLs) model. In addition, multivariate Cox analysis was used to assess the prognostic value of the model in the entire cohort and in different subgroups. Results: The 3-CRLs risk scoring criteria including EWSAT1, AC125437.1 and GK-IT1 was established to evaluate the overall survival (OS) of ESCA. Survival analysis and ROC curve showed that the score had good prediction performance in TCGA train group and test group. The coefficients of each lncRNAs were analyzed using Lasso regression and lambda values were determined. principal component analysis was used to determine whether 3-CRLs can clearly distinguish the gap between high and low risk samples. Multivariate Cox regression showed that 3-CRLs characteristics were independent prognostic factors of OS. Norman map showed robust effectiveness in prognosis prediction. Conclusion: The risk characteristics based on 3-CRLs may be used to predict the prognosis of esophageal carcinoma patients

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“…In addition, gene set enrichment analysis (GSEA) was performed to identify biological processes between two risk groups based on the file ““c2.cp.kegg.v6.2.symbols.gmts” from the MSigDB database. Significance was determined based on a threshold of p < 0.05 25 .…”

Section: Methodsmentioning

confidence: 99%

Identification of anoikis-related subtypes and immune landscape in kidney renal clear cell carcinoma

Ding,

Zhang,

Zhang

et al. 2023

Sci Rep

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Anoikis is a specific form of programmed cell death induced by the loss of cell contact with the extracellular matrix and other cells, and plays an important role in organism development, tissue homeostasis, disease development and tumor metastasis. We comprehensively investigated the expression patterns of anoikis-related genes (ARGs) in kidney renal clear cell carcinoma (KIRC) from public databases. Anoikis-related prognostic signatures were established based on four ARGs expression, in which KIRC patients were assigned different risk scores and divided into two different risk groups. In addition, four ARGs expression was validated by qRT-PCR. A better prognosis was observed in the low-risk group, but with lower immune activity (including immune cells and immune-related functions) in the tumor microenvironment. Combined with the relevant clinical characteristics, a nomogram for clinical application was established. Receiver operating characteristics (ROC) and calibration curves were constructed to demonstrate the predictive power of this risk signature. In addition, higher risk scores were significantly and positively correlated with higher gene expression of tumor mutation load (TMB), immune checkpoints (ICPs) and mismatch repair (MMR)-related proteins in general. The results also suggested that the high-risk group was more sensitive to immunotherapy and certain chemotherapeutic agents. Anoikis-related prognostic signatures may provide a better understanding of the roles of ARGs and offer new perspectives for clinical prognosis and individualized treatment.

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Comprehensive analysis of the prognostic signature and tumor microenvironment infiltration characteristics of cuproptosis-related lncRNAs for patients with colon adenocarcinoma

Cited by 11 publications

References 68 publications

A neutrophil extracellular traps-associated lncRNA signature predicts the clinical outcomes in patients with lung adenocarcinoma

A neutrophil extracellular traps-associated lncRNA signature predicts the clinical outcomes in patients with lung adenocarcinoma

A novel cuproptosis-related LncRNA signature predicts prognosis inpatients with esophageal carcinoma

Identification of anoikis-related subtypes and immune landscape in kidney renal clear cell carcinoma

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