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Wang Y, Chen X, Jiang F, Shen Y, Fang F, Li Q, Yang C, Dong Y, Shen X. A prognostic signature of pyroptosis-related lncRNAs verified in gastric cancer samples to predict the immunotherapy and chemotherapy drug sensitivity. Front Genet 2022; 13:939439. [PMID: 36147488 PMCID: PMC9485603 DOI: 10.3389/fgene.2022.939439] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Accepted: 08/09/2022] [Indexed: 11/13/2022] Open
Abstract
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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Xu Y, Chen Y, Niu Z, Xing J, Yang Z, Yin X, Guo L, Zhang Q, Qiu H, Han Y. A Novel Pyroptotic and Inflammatory Gene Signature Predicts the Prognosis of Cutaneous Melanoma and the Effect of Anticancer Therapies. Front Med (Lausanne) 2022; 9:841568. [PMID: 35492358 PMCID: PMC9053829 DOI: 10.3389/fmed.2022.841568] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Accepted: 03/04/2022] [Indexed: 11/13/2022] Open
Abstract
PurposeThe purpose of this study was to construct a gene signature comprising genes related to both inflammation and pyroptosis (GRIPs) to predict the prognosis of patients with cutaneous melanoma patients and the efficacy of immunotherapy, chemotherapy, and targeted therapy in these patients.MethodsGene expression profiles were collected from The Cancer Genome Atlas. Weighted gene co-expression network analysis was performed to identify GRIPs. Univariable Cox regression and Lasso regression further selected key prognostic genes. Multivariable Cox regression was used to construct a risk score, which stratified patients into high- and low-risk groups. Areas under the ROC curves (AUCs) were calculated, and Kaplan-Meier analyses were performed for the two groups, following validation in an external cohort from Gene Expression Omnibus (GEO). A nomogram including the GRIP signature and clinicopathological characteristics was developed for clinical use. Gene set enrichment analysis illustrated differentially enriched pathways. Differences in the tumor microenvironment (TME) between the two groups were assessed. The efficacies of immune checkpoint inhibitors (ICIs), chemotherapeutic agents, and targeted agents were predicted for both groups. Immunohistochemical analyses of the GRIPs between the normal and CM tissues were performed using the Human Protein Atlas data. The qRT-PCR experiments validated the expression of genes in CM cell lines, Hacat, and PIG1 cell lines.ResultsA total of 185 GRIPs were identified. A novel gene signature comprising eight GRIPs (TLR1, CCL8, EMP3, IFNGR2, CCL25, IL15, RTP4, and NLRP6) was constructed. The signature had AUCs of 0.714 and 0.659 for predicting 3-year overall survival (OS) in the TCGA entire and GEO validation cohorts, respectively. Kaplan-Meier analyses revealed that the high-risk group had a poorer prognosis. Multivariable Cox regression showed that the GRIP signature was an independent predictor of OS with higher accuracy than traditional clinicopathological features. The nomogram showed good accuracy and reliability in predicting 3-year OS (AUC = 0.810). GSEA and TME analyses showed that the high-risk group had lower levels of pyroptosis, inflammation, and immune response, such as lower levels of CD8+ T-cell infiltration, CD4+ memory-activated T-cell infiltration, and ICI. In addition, low-risk patients whose disease expressed PD-1 or CTLA-4 were likely to respond better to ICIs, and several chemotherapeutic and targeted agents. Immunohistochemical analysis confirmed the distinct expression of five out of the eight GRIPs between normal and CM tissues.ConclusionOur novel 8-GRIP signature can accurately predict the prognosis of patients with CM and the efficacies of multiple anticancer therapies. These GRIPs might be potential prognostic biomarkers and therapeutic targets for CM.
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Affiliation(s)
- Yujian Xu
- Department of Plastic and Reconstructive Surgery, The First Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Youbai Chen
- Department of Plastic and Reconstructive Surgery, The First Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Zehao Niu
- Department of Plastic and Reconstructive Surgery, The First Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Jiahua Xing
- Department of Plastic and Reconstructive Surgery, The First Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Zheng Yang
- Department of Plastic and Reconstructive Surgery, The First Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Xiangye Yin
- Department of Plastic and Reconstructive Surgery, The First Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Lingli Guo
- Department of Plastic and Reconstructive Surgery, The First Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Qixu Zhang
- Department of Plastic Surgery, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Haixia Qiu
- Department of Laser Medicine, The First Medical Center of Chinese PLA General Hospital, Beijing, China
- *Correspondence: Haixia Qiu
| | - Yan Han
- Department of Plastic and Reconstructive Surgery, The First Medical Center of Chinese PLA General Hospital, Beijing, China
- Yan Han
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