A Novel Risk Model Identified Based on Pyroptosis-Related lncRNA Predicts Overall Survival and Associates With the Immune Landscape of GC Patients

Xu, Tingting; Gu, Hanxin; Zhang, Changsong; Zhang, Wushuang; Liang, Xiaolong; Cheng, Xiao

doi:10.3389/fgene.2022.843538

Cited by 7 publications

(7 citation statements)

References 63 publications

(76 reference statements)

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“…Cox analysis, univariate along with multivariate, validated that the 3-PRlncRNAs risk model is an independent predictor of disease outcomes in GC subjects. It is of interest that there is already a study on the lasso model of PRlncRNAs construction ( Xu et al, 2022 ). However, we found that the component lncRNAs of this model were different from the lncRNAs we used.…”

Section: Discussionmentioning

confidence: 99%

A prognostic signature of pyroptosis-related lncRNAs verified in gastric cancer samples to predict the immunotherapy and chemotherapy drug sensitivity

et al. 2022

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Background: Pyroptosis is a recently identified mode of programmed inflammatory cell death that has remarkable implications for cancer development. lncRNAs can be involved in cellular regulation through various pathways and play a critical role in gastric cancer (GC). However, pyroptosis -related lncRNAs (PRlncRNAs) have been rarely studied in GC.Methods: Pyroptosis-related gene were abstracted from the literature and GSEA Molecular Signatures data resource. PRlncRNAs were obtained using co-expression analysis. LASSO Cox regression assessment was employed to build a risk model. Kaplan-Meier (KM), univariate along with multivariate Cox regression analysis were adopted to verify the predictive efficiency of the risk model in terms of prognosis. qRT-PCR was adopted to validate the expression of PRlncRNAs in GC tissues. In addition, immune cell infiltration assessment and ESTIMATE score evaluation were adopted for assessing the relationship of the risk model with the tumor immune microenvironment (TME). Finally, immune checkpoint gene association analysis and chemotherapy drug sensitivity analysis were implemented to assess the worthiness of our risk model in immunotherapy and chemotherapy of GC.Results: We identified 3 key PRlncRNAs (PVT1, CYMP-AS1 and AC017076.1) and testified the difference of their expression levels in GC tumor tissues and neighboring non-malignant tissues (p < 0.05). PRlncRNAs risk model was able to successfully estimate the prognosis of GC patients, and lower rate of survival was seen in the high-GC risk group relative to the low-GC risk group (p < 0.001). Other digestive system tumors such as pancreatic cancer further validated our risk model. There was a dramatic difference in TMB level between high-GC and low-GC risk groups (p < 0.001). Immune cell infiltration analysis and ESTIMATE score evaluation demonstrated that the risk model can be adopted as an indicator of TME status. Besides, the expressions of immunodetection site genes in different risk groups were remarkably different (CTLA-4 (r = −0.14, p = 0.010), VISTA (r = 0.15, p = 0.005), and B7-H3 (r = 0.14, p = 0.009)). PRlncRNAs risk model was able to effectively establish a connection with the sensitivity of chemotherapeutic agents.Conclusion: The 3 PRlncRNAs identified in this study could be utilized to predict disease outcome in GC patients. It may also be a potential therapeutic target in GC therapy, including immunotherapy and chemotherapy.

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Section: Discussionmentioning

confidence: 99%

A prognostic signature of pyroptosis-related lncRNAs verified in gastric cancer samples to predict the immunotherapy and chemotherapy drug sensitivity

et al. 2022

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“…Valid prognostic models based on specific biomarkers can accurately predict survival outcomes for the effective management of PCa patients ( 42 ). Pyroptosis-related lncRNA risk prediction models have been reported to be expected to assist in the treatment and management of various tumors ( 43 , 44 ). Our study used a novel risk model of six PRLs (AC129507.1, AC005253.1, AC127502.2, AC068580.3, LIMD1-AS1, and LINC01852) developed using Lasso analysis.…”

Section: Discussionmentioning

confidence: 99%

Identification of pyroptosis-related lncRNA signature and AC005253.1 as a pyroptosis-related oncogene in prostate cancer

Tang

2022

Front. Oncol.

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BackgroundPyroptosis and prostate cancer (PCa) are closely related. The role of pyroptosis-related long non-coding RNAs (lncRNAs) (PRLs) in PCa remains elusive. This study aimed to explore the relationship between PRL and PCa prognosis.MethodsGene expression and clinical signatures were obtained from The Cancer Genome Atlas and Gene Expression Omnibus databases. A PRL risk prediction model was established by survival random forest analysis and least absolute shrinkage and selection operator regression. Functional enrichment, immune status, immune checkpoints, genetic mutations, and drug susceptibility analyses related to risk scores were performed by the single-sample gene set enrichment analysis, gene set variation analysis, and copy number variation analysis. PRL expression was verified in PCa cells. Cell Counting Kit-8, 5-ethynyl-2′-deoxyuridine, wound healing, transwell, and Western blotting assay were used to detect the proliferation, migration, invasion, and pyroptosis of PCa cells, respectively.ResultsPrognostic features based on six PRL (AC129507.1, AC005253.1, AC127502.2, AC068580.3, LIMD1-AS1, and LINC01852) were constructed, and patients in the high-score group had a worse prognosis than those in the low-score group. This feature was determined to be independent by Cox regression analysis, and the area under the curve of the 1-, 3-, and 5-year receiver operating characteristic curves in the testing cohort was 1, 0.93, and 0.92, respectively. Moreover, the external cohort validation confirmed the robustness of the PRL risk prediction model. There was a clear distinction between the immune status of the two groups. The expression of multiple immune checkpoints was also reduced in the high-score group. Gene mutation proportion in the high-score group increased, and the sensitivity to drugs increased significantly. Six PRLs were upregulated in PCa cells. Silencing of AC005253.1 inhibited cell proliferation, migration, and invasion in DU145 and PC-3 cells. Moreover, silencing of AC005253.1 promoted pyroptosis and inflammasome AIM2 expression.ConclusionsOverall, we constructed a prognostic model of PCa with six PRLs and identified their expression in PCa cells. The experimental verification showed that AC005253.1 could affect the proliferation, migration, and invasion abilities of PCa cells. Meanwhile, AC005253.1 may play an important role in PCa by affecting pyroptosis through the AIM2 inflammasome. This result requires further research for verification.

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“… Programmed necrosis RNA AUC of ROC Ref. necroptosis 16 lncRNAs : LINC01829, LINC02657, RNF139-AS1, FRMD6-AS2, AGBL5-IT1, AC116914.1, AC005165.1, AL353804.2, AC004596.1, AL355574.1, AC012409.3, AC124067.4, AC015813.1, AP001189.3, AL133245.1, AC069549.1 0.770 [ 97 ] 12 lncRNAs : REPIN1-AS1, UBL7-AS1, LINC00460, LINC02773, CHROMR, LINC01094, FLNB-AS1, ITFG1-AS1, LASTR, PINK1-AS, LINC01638, PVT1 0.748 [ 98 ] pyroptotic 11 lncRNAs : AL353804.1, AC147067.2, AP001318.2, RRN3P2, UBL7-AS1, AC018752.1, ACTA2-AS1, AL121772.1, AC005332.4, HAGLR, AC245041.2 0.850 [ 99 ] ferroptosis 20 lncRNAs : AC114271.1, AC147067.2, AL353796.1, AC104958.1, AC087521.1, AL590705.3, AC068790.7, AC090772.1, LINC01094, AC007405.3, AC083902.1, LINC00460, AC005165.1, AC048382.2, AC106782.5, STX18-AS1, AL355574.1, CYMP-AS1, AC006547.1, LINC02696 0.947 [ 100 ] 17 lncRNAs : ENSG00000249835.2, ENSG0000023671 9.2, ENSG00000250241.4, ENSG00000240661.1, ENSG0000026 2061.4, ENSG00000229656.5, ENSG00000175746.6, ENSG00000 248599.1, ENSG00000254333.1, ENSG00000247134.5, and ENSG00000248362.1, ENSG00000234449.2, ENSG0000023 9513.4, ENSG00000265334.1, ENSG00000267201.1, ENSG 00000273293.1, ENSG00000230107.1 0.751 [ 101 ] 4 lncRNAs: AP003392.1, AC245041.2, AP001271.1, BOLA3-AS1 0.636 [ 102 ] 12 lncRNAs : AC026368.1, CFAP61-AS1, AC090772.1, LINC00449, AC005165.1, LINC01614, AL356215.1, REPIN1-AS1, LASTR, LINC00460, AC015712.1, PVT1. 0.734 [ 103 ] 6 lncRNAs : STX18-AS1, MIR99AHG, LINC01197, LINC00968, LINC00865, LEF1-AS1 0.640 [ 104 ] 3 lncRNAs : P000695.2, AL365181.3, LINC01615 0.670 [ 105 ] The bold values represent the number of lncRNAs in each gastric cancer prediction model.…”

Section: Regulation Of Cell Death In Gastric Cancermentioning

confidence: 99%

Cell death affecting the progression of gastric cancer

et al. 2022

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Gastric cancer is a gastrointestinal tumor with high morbidity and mortality rates. Several factors influence its progression, cell death being an important element. In this review, we summarized the effects of necrosis, apoptosis, necroptosis, pyroptosis, ferroptosis, and eight less common cell death modalities on gastric cancer cells and the tumor microenvironment, detailed the molecular mechanisms of various cell death and their major regulatory pathways in gastric cancer, explored the prevalence and complexity of cell death in gastric cancer progression and highlighted the potentials of cell death-related therapies in gastric cancer.

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A Novel Risk Model Identified Based on Pyroptosis-Related lncRNA Predicts Overall Survival and Associates With the Immune Landscape of GC Patients

Cited by 7 publications

References 63 publications

A prognostic signature of pyroptosis-related lncRNAs verified in gastric cancer samples to predict the immunotherapy and chemotherapy drug sensitivity

A prognostic signature of pyroptosis-related lncRNAs verified in gastric cancer samples to predict the immunotherapy and chemotherapy drug sensitivity

Identification of pyroptosis-related lncRNA signature and AC005253.1 as a pyroptosis-related oncogene in prostate cancer

Cell death affecting the progression of gastric cancer

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