Comprehensive analysis of GSEC/miR-101-3p/SNX16/PAPOLG axis in hepatocellular carcinoma

Hu, Shangshang; Zhang, Jinyan; Guo, Guoqing; Zhang, Li; Dai, Jing; Gao, Yu Tang

doi:10.1371/journal.pone.0267117

Cited by 14 publications

(6 citation statements)

References 44 publications

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“…In the case of LUAD, GSEC played an active role in the promotion of tumor progression through the GSEC/miRNA-101-3p/CISD1 Axis and showed a significant association with ferroptosis, as confirmed by previous research 37 . Additionally, several research reported GSEC could promote the malignant process of triple-negative breast cancer and hepatocellular carcinoma via the GSEC/miR-202-5p/AXL axis and the GSEC/miR-101-3p/SNX16/PAPOLG axis 38 , 39 , respectively. Furthermore, lncRNA AL606834.1 has been used for prognostic models of lung adenocarcinoma and pancreatic cancer 40 , 41 , AL365181.2 has been applied in multiple prognostic models of lung adenocarcinoma 42 , 43 , and AC012615.1 has been studied in a prognostic model of glioblastoma 44 .…”

Section: Discussionmentioning

confidence: 99%

A disulfidptosis-related lncRNA signature for predicting prognosis and evaluating the tumor immune microenvironment of lung adenocarcinoma

Song,

Cao,

Wang

et al. 2024

Sci Rep

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As a novel form of regulated cell death (RCD), disulfidptosis offering a significant opportunity in better understanding of tumor pathogenesis and therapeutic strategies. Long non-coding RNAs (lncRNAs) regulate the biology functions of tumor cells by engaging with a range of targets. However, the prognostic value of disulfidptosis-related lncRNAs (DRlncRNAs) in lung adenocarcinoma (LUAD) remains unclear. Therefore, our study aimed at establishing a prognostic model for LUAD patients based on DRlncRNAs. RNA-seq data and clinical information were obtained from The Cancer Genome Atlas (TCGA) database. Subsequently, a prognostic model based on DRlncRNAs was constructed using LASSO and COX regression analysis. Patients were stratified into high- and low-risk groups based on their risk scores. Differences between the high-risk and low-risk groups were investigated in terms of overall survival (OS), functional enrichment, tumor immune microenvironment (TIME), somatic mutations, and drug sensitivity. Finally, the role of lncRNA GSEC in LUAD was validated through in vitro experiments. Using the prognostic model consists of 5 DRlncRNAs (AL365181.2, GSEC, AC093673.1, AC012615.1, AL606834.1), the low-risk group exhibited a markedly superior survival in comparison to the high-risk group. The significant differences were observed among patients from different risk groups in OS, immune cell infiltration, immune checkpoint expression, immunotherapy response, and mutation landscape. Experimental results from cellular studies demonstrate the knockdown of lncRNA GSEC leading to a significant reduction in the proliferation and migration abilities of LUAD cells. Our prognostic model, constructed using 5 DRlncRNAs, exhibited the capacity to independently predict the survival of LUAD patients, providing the potentially significant assistance in prognosis prediction, and treatment effects optimization. Moreover, our study established a foundation for further research on disulfidptosis in LUAD and proposed new perspectives for the treatment of LUAD.

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Section: Discussionmentioning

confidence: 99%

A disulfidptosis-related lncRNA signature for predicting prognosis and evaluating the tumor immune microenvironment of lung adenocarcinoma

Song,

Cao,

Wang

et al. 2024

Sci Rep

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“…LncRNA DLEU2 aggravates the progression of HCC ( Guo et al, 2019 ). Furthermore, the GSEC/miR-101-3p/SNX16/PAPOLG axis of the ceRNA network axis is an important factor associated with HCC prognosis and immune infiltration ( Hu et al, 2022 ). Our study revealed that these mRNA-miRNA-lncRNA networks were associated with the prognosis of HCC patients.…”

Section: Discussionmentioning

confidence: 99%

Comprehensive analysis of cuproptosis-related prognostic gene signature and tumor immune microenvironment in HCC

Qin

Sheng²,

Zhang³

et al. 2023

Front. Genet.

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Background: Copper is an indispensable mineral element involved in many physiological metabolic processes. Cuproptosis is associated with a variety of cancer such as hepatocellular carcinoma (HCC). The objective of this study was to examine the relationships between the expression of cuproptosis-related genes (CRGs) and tumor characteristics, including prognosis and microenvironment of HCC.Methods: The differentially expressed genes (DEGs) between high and low CRGs expression groups in HCC samples were identified, and further were analyzed for functional enrichment analysis. Then, CRGs signature of HCC was constructed and analyzed utilizing LASSO and univariate and multivariate Cox regression analysis. Prognostic values of CRGs signature were evaluated by Kaplan-Meier analysis, independent prognostic analysis and nomograph. The expression of prognostic CRGs was verified by Real-time quantitative PCR (RT-qPCR) in HCC cell lines. In addition, the relationships between prognostic CRGs expression and the immune infiltration, tumor microenvironment, antitumor drugs response and m6A modifications were further explored using a series of algorithms in HCC. Finally, ceRNA regulatory network based on prognostic CRGs was constructed.Results: The DEGs between high and low CRG expression groups in HCC were mainly enriched in focal adhesion and extracellular matrix organization. Besides, we constructed a prognostic model that consists of CDKN2A, DLAT, DLST, GLS, and PDHA1 CRGs for predicting the survival likelihood of HCC patients. And the elevated expression of these five prognostic CRGs was substantially in HCC cell lines and associated with poor prognosis. Moreover, immune score and m6A gene expression were higher in the high CRG expression group of HCC patients. Furthermore, prognostic CRGs have higher mutation rates in HCC, and are significantly correlated with immune cell infiltration, tumor mutational burden, microsatellite instability, and anti-tumor drug sensitivity. Then, eight lncRNA-miRNA-mRNA regulatory axes that affected the progression of HCC were predicted.Conclusion: This study demonstrated that the CRGs signature could effectively evaluate prognosis, tumor immune microenvironment, immunotherapy response and predict lncRNA-miRNA-mRNA regulatory axes in HCC. These findings extend our knowledge of cuproptosis in HCC and may inform novel therapeutic strategies for HCC.

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“…Shangshang Hu et al. constructed a GSEC/Mir-101-3p/SNX16/PAPOLG network to predict the prognosis of hepatocellular carcinoma ( 43 ). Xiulin Jiang et al.…”

Section: Discussionmentioning

confidence: 99%

“…Shangshang Hu et al constructed a GSEC/Mir-101-3p/SNX16/ PAPOLG network to predict the prognosis of hepatocellular carcinoma (43). Xiulin Jiang et al also found that ferroptosis-related GSEC-lncRNAs, mirNA-101-3p, and CISD1 axis play a functional role in lung adenocarcinoma (LUAD) and may serve as useful diagnostic and therapeutic biomarkers for the disease.…”

Section: Discussionmentioning

confidence: 99%

Novel methylation-related long non-coding RNA clinical outcome prediction method: the clinical phenotype and immune infiltration research in low-grade gliomas

Li¹,

Li²,

Yu³

2023

Front. Oncol.

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BackgroundRecent studies have suggested that long non-coding RNAs (lncRNAs) may play crucial role in low-grade glioma; however, the underlying mechanisms linking them to epigenetic methylation remain unclear.MethodsWe downloaded expression level data for regulators associated with N1 methyladenosine (m1A), 5-methyladenine (m5C), and N6 methyladenosine (m6A) (M1A/M5C/M6A) methylation from the Cancer Genome Atlas-low-grade glioma (TCGA-LGG) database. We identified the expression patterns of lncRNAs, and selected methylation-related lncRNAs using Pearson correlation coefficient>0.4. Non-negative matrix dimensionality reduction was then used to determine the expression patterns of the methylation-associated lncRNAs. We constructed a weighted gene co-expression network analysis (WGCNA) network to explore the co-expression networks between the two expression patterns. Functional enrichment of the co-expression network was performed to identify biological differences between the expression patterns of different lncRNAs. We also constructed prognostic networks based on the methylation presence in lncRNAs in low-grade gliomas.ResultsWe identified 44 regulators by literature review. Using a correlation coefficient greater than 0.4, we identified 2330 lncRNAs, among which 108 lncRNAs with independent prognostic values were further screened using univariate Cox regression at P< 0.05. Functional enrichment of the co-expression networks revealed that regulation of trans-synaptic signaling, modulation of chemical synaptic transmission, calmodulin binding, and SNARE binding were mostly enriched in the blue module. The calcium and CA2 signaling pathways were associated with different methylation-related long non-coding chains. Using the Least Absolute Shrinkage Selector Operator (LASSO) regression analysis, we analyzed a prognostic model containing four lncRNAs. The model’s risk score was 1.12 *AC012063 + 0.74 * AC022382 + 0.32 * AL049712 + 0.16 * GSEC. Gene set variation analysis (GSVA) revealed significant differences in mismatch repair, cell cycle, WNT signaling pathway, NOTCH signaling pathway, Complement and Cascades, and cancer pathways at different GSEC expression levels. Thus, these results suggest that GSEC may be involved in the proliferation and invasion of low-grade glioma, making it a prognostic risk factor for low-grade glioma.ConclusionOur analysis identified methylation-related lncRNAs in low-grade gliomas, providing a foundation for further research on lncRNA methylation. We found that GSEC could serve as a candidate methylation marker and a prognostic risk factor for overall survival in low-grade glioma patients. These findings shed light on the underlying mechanisms of low-grade glioma development and may facilitate the development of new treatment strategies.

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Comprehensive analysis of GSEC/miR-101-3p/SNX16/PAPOLG axis in hepatocellular carcinoma

Cited by 14 publications

References 44 publications

A disulfidptosis-related lncRNA signature for predicting prognosis and evaluating the tumor immune microenvironment of lung adenocarcinoma

A disulfidptosis-related lncRNA signature for predicting prognosis and evaluating the tumor immune microenvironment of lung adenocarcinoma

Comprehensive analysis of cuproptosis-related prognostic gene signature and tumor immune microenvironment in HCC

Novel methylation-related long non-coding RNA clinical outcome prediction method: the clinical phenotype and immune infiltration research in low-grade gliomas

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