Construction of a Prognostic Model Based on Cuproptosis-Related lncRNA Signatures in Pancreatic Cancer

Jiang, Wenkai; Du, Yuchen; Zhang, Wenlong; Zhou, Wence

doi:10.1155/2022/4661929

Cited by 10 publications

(4 citation statements)

References 43 publications

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“…One of them was the prognostic protective factor lncRNA AC091057.1, which was associated with 68.87% of mRNAs in our study. The expression of AC091057.1 was experimentally verified and was consistent with the results of a pancreatic cancer study indicating it as a protective factor in cancer 36 . In a diffuse large B cell lymphoma (DLBCL) study, the knockdown of ARRDC1-AS1 exacerbated proliferation, inhibited apoptosis, and promoted invasion and migration 37 .…”

Section: Discussionsupporting

confidence: 84%

Construction of an oxidative stress-related lncRNAs signature to predict prognosis and the immune response in gastric cancer

Zhang

Feng

et al. 2023

Sci Rep

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Oxidative stress, as a characteristic of cellular aerobic metabolism, plays a crucial regulatory role in the development and metastasis of gastric cancer (GC). Long noncoding RNAs (lncRNAs) are important regulators in GC development. However, research on the prognostic patterns of oxidative stress-related lncRNAs (OSRLs) and their functions in the immune microenvironment is currently insufficient. We identified the OSRLs signature (DIP2A-IT1, DUXAP8, TP53TG1, SNHG5, AC091057.1, AL355001.1, ARRDC1-AS1, and COLCA1) from 185 oxidative stress-related genes in The Cancer Genome Atlas (TCGA) cohort via random survival forest and Cox analyses, and the results were subsequently validated in the Gene Expression Omnibus (GEO) dataset. The patients were divided into high- and low-risk groups by the risk score of the OSRLs signature. Longer overall survival was detected in the low-risk group than in the high-risk group in both the TCGA cohort (P < 0. 001, HR = 0.43, 95% CI 0.31–0.62) and the GEO cohort (P = 0.014, HR = 0.67, 95% CI 0.48–0.93). Next, multivariate Cox analysis identified that the risk model was an independent prognostic characteristic (HR > 1, P = 0.005), and time-dependent receiver operating characteristic (ROC) curve analysis and nomogram analysis were utilized to evaluate the predictive ability of the risk model. Next, gene set enrichment analysis revealed that the immune-related pathway, Wnt/$$\upbeta$$ β -catenin signature, mammalian target of rapamycin complex 1 signature, and cytokine‒cytokine receptor interaction was enriched. High-risk patients were more responsive to CD200, TNFSF4, TNFSF9, and BTNL2 immune checkpoint blockade. The results of qRT‒PCR further proved the accuracy of our bioinformatic analysis. Overall, our study identified a novel OSRLs signature that can serve as a promising biomarker and prognostic indicator, which provides a personalized predictive approach for patient prognosis evaluation and treatment.

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Section: Discussionsupporting

confidence: 84%

Construction of an oxidative stress-related lncRNAs signature to predict prognosis and the immune response in gastric cancer

Zhang

Feng

et al. 2023

Sci Rep

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“…4 D). [ 23 , 24 ] Kaplan–Meier analysis confirmed that prognosis was improved in the low-risk group compared with the high-risk group in the training, testing and all cohorts ( P < .05) (Fig. 4 E–G).…”

Section: Resultsmentioning

confidence: 72%

The potential use and experimental validation of genomic instability-related lncRNA in pancreatic carcinoma

Xia,

Zhao,

Song

et al. 2023

Medicine

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This study explored the potential role of long noncoding RNA (lncRNAs) associated with genomic instability in the diagnosis and treatment of pancreatic adenocarcinoma (PAAD). Transcriptome and single-nucleotide variation data of PAAD samples were downloaded from the cancer genome atlas database to explore genomic instability-associated lncRNAs. We constructed a genomic instability-associated lncRNA prognostic signature. Then gene ontology and Kyoto encyclopedia of genes and genomes enrichment analyses were used to explore the physiological role of lncRNAs involved in genomic instability. Tumor microenvironments, immunotherapy response, immune cell infiltration, immune checkpoint, and drug sensitivity were compared between high-risk and low-risk groups. In vitro experiments were performed for external validation. Six lncRNAs associated with genomic instability were identified, capable of predicting the prognosis of PAAD. Patients were assigned to low-risk or high-risk groups using these biomarkers, with better or worse prognosis, respectively. The tumor immune score, immune cell infiltration, and efficacy of immunotherapy were worse in the high-risk group. A drug sensitivity analysis revealed the high- and low-risk groups had different half-maximal inhibitory concentrations. The expression of cancer susceptibility candidate 8 was significantly higher in tumor tissues than in normal tissues, while the expression of LYPLAL1-AS1 exhibited an opposite pattern. They may be potential diagnostic or prognostic biomarkers for patients with pancreatic cancer. Genomic instability-associated lncRNAs were explored in this study and predicted the prognosis of PAAD and stratified patients risk in PAAD. These lncRNAs also predicted the efficacy of immunotherapy and potential therapeutic targets in PAAD.

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“…were identi ed as lncRNAs associated with cuproptosis, pyroptosis, and ferroptosis, respectively, and showed promising prognostic evaluation characteristics [29][30][31]. Previous research has shown that TDRKH-AS1 promotes tumorigenesis by activating the Wnt pathway in colorectal cancer, and its high expression is associated with poor prognosis in colorectal cancer patients [32].…”

Section: Discussionmentioning

confidence: 99%

A Novel Aging-Related lncRNAs Signature-Based Model for Prognosis Prediction in Pancreatic Cancer

李,

wang,

Zhang

et al. 2023

Preprint

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Objective To identify aging-related long non-coding RNAs (ARLs) with prognostic significance and construct a prognostic model for pancreatic cancer (PC) patients. Methods Transcriptome information from PC samples and normal samples was obtained from the Cancer Genome Atlas Database (TCGA) and the Genotypic Tissue Expression Database (GTEx). Aging-related genes (ARGs) were obtained from the Human Aging Genome Resources (HAGR) and GeneCards. Correlation analysis was performed to screen out ARLs. Univariate regression, lasso regression, and multivariate regression were used to identify the target ARLs and construct the prognostic model for aging-related PC. Results A total of 1109 ARLs were identified, and 9 target ARLs were obtained to construct the risk score prognostic model. These target ARLs include AC245041.2, AC244153.1, AC091057.1, MIR3142HG, AL137779.2, AC145207.5, TDRKH-AS1, AC068620.2, and AC127024.6. The model showed an area under the curve (AUC) of 0.798 on the receiver operating curve (ROC) curve, indicating its effectiveness in predicting prognosis. Kaplan-Meier analysis demonstrated a significant difference in overall survival (OS) between the two groups based on the median risk (P＜0.001). To further assess prognosis, the risk score was combined with clinicopathological features to construct a nomogram for PC. Additionally, gene enrichment analysis (GSEA) and immunological correlation analysis revealed differences in gene enrichment level, immune infiltration, and the expression of immune checkpoint genes between the two groups. Conclusion The constructed prognostic model based on nine ARLs provides valuable insights for the prognosis management of PC patients and the development of promising biomarkers in the diagnosis and treatment of PC.

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Construction of a Prognostic Model Based on Cuproptosis-Related lncRNA Signatures in Pancreatic Cancer

Cited by 10 publications

References 43 publications

Construction of an oxidative stress-related lncRNAs signature to predict prognosis and the immune response in gastric cancer

Construction of an oxidative stress-related lncRNAs signature to predict prognosis and the immune response in gastric cancer

The potential use and experimental validation of genomic instability-related lncRNA in pancreatic carcinoma

A Novel Aging-Related lncRNAs Signature-Based Model for Prognosis Prediction in Pancreatic Cancer

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