A Novel Pyroptosis-Related Signature for Predicting Prognosis and Indicating Immune Microenvironment Features in Osteosarcoma

Zhang, Yiming; He, Rong; Liu, Xuan; Mao, Lianghao; Jiang, Pan; Ni, Chenlie; Yin, Zhengyu; Zhong, Xinyu; Chen, Chen; Zheng, Qi; Li, Dapeng

doi:10.3389/fgene.2021.780780

Cited by 33 publications

(32 citation statements)

References 76 publications

(74 reference statements)

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“…Kaplan-Meier survival analysis in all internal and external cohorts revealed that the overall survival of patients in the high-risk group was consistently worse than that of patients in the low-risk group, indicating the promising accuracy and generalizability of the SLC-based signature in predicting the prognosis of osteosarcoma patients. Time-dependent ROC curves confirmed the specificity and accuracy of our SLC-based signature which was superior to some previously reported prognostic signatures in osteosarcoma ( Fu et al, 2021 ; Zhang et al, 2021 ), since the AUC values of the ROC curves were higher in our research. Furthermore, when patients were divided into different subgroups based on clinical parameters such as gender and age, the prognosis was still poorer in the high-risk group than in the low-risk group in all subgroups, suggesting the signature’s risk stratification utility.…”

Section: Discussionsupporting

confidence: 83%

Identification of a Solute Carrier Family-Based Signature for Predicting Overall Survival in Osteosarcoma

2022

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Given the important role of SLC family in essential physiological processes including nutrient uptake, ion transport, and waste removal, and that their dysregulation was found in distinct forms of cancer, here we identified a novel gene signature of SLC family for patient risk stratification in osteosarcoma. Gene expression data and relevant clinical materials of osteosarcoma samples were retrieved from The Cancer Genome Atlas (TCGA) database. Prognosis-related SLC genes were identified by performing univariate Cox regression analysis and were utilized to construct a four-SLC gene signature in osteosarcoma. It allowed patients to be classified into high- and low-risk groups, and Kaplan-Meier survival analysis in the training, testing, entire, and external GSE21257 cohorts suggested that the overall survival of patients in high-risk group was consistently worse than that in low-risk group, suggesting the promising accuracy and generalizability of the SLC-based signature in predicting the prognosis of patients with osteosarcoma. Moreover, univariate and multivariate Cox regression analyses indicated that the derived risk score was the only independent prognostic factor for osteosarcoma patients in TCGA and GSE21257 cohorts. Besides, a prognostic nomogram comprising the derived risk score and clinical features including gender and age was developed for clinical decision-making. Functional enrichment analyses of the differentially expressed genes between high- and low-risk group revealed that immune-related biological processes and pathways were significantly enriched. Estimation of tumor immune microenvironment using ESTIMATE algorithm revealed that patients with lower risk score had higher stromal, immune, and ESTIMATE score, and lower tumor purity. ssGSEA analyses indicated that the scores of various immune subpopulations including CD8+ T cells, DCs, and TIL were lower in high-risk group than these in low-risk group in both cohorts. As for the related immune functions, the scores of APC co-inhibition, CCR, check-point, T cell co-stimulation, and Type II IFN response were lower in high-risk group than these in low-risk group in both cohorts. In all, we identified a novel prognostic signature based on four SLC family genes that accurately predicted overall survival in osteosarcoma patients. Furthermore, the signature is linked to differences in immunological status and immune cell infiltrations in the tumor microenvironment.

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Section: Discussionsupporting

confidence: 83%

Identification of a Solute Carrier Family-Based Signature for Predicting Overall Survival in Osteosarcoma

2022

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“…where n represents the number of OS prognosis CRLncs, i is the ith CRLncs, coef is the regression coefficient, and the expression of OS prognosis CRLncs is multiplied by the corresponding regression coefficient and accumulated to obtain the sample risk score (16). The samples in the total sample, training, and test groups were divided into high-and low-risk groups according to the median of the risk score.…”

Section: Construction Of Risk Prognostic Modelmentioning

confidence: 99%

“…Studies have identified pyroptosis-and autophagy-related genes that can predict OS prognosis by using risk prognostic models (16,17). In this study, a novel OS prognosis model was established to explore cuproptosis-related lncRNAs (CRLncs) that can guide OS prognosis and immune microenvironment.…”

Section: Introductionmentioning

confidence: 99%

A novel signature to guide osteosarcoma prognosis and immune microenvironment: Cuproptosis-related lncRNA

Yang

Zheng

et al. 2022

Front. Immunol.

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ObjectiveOsteosarcoma (OS) is a common bone malignancy with poor prognosis. We aimed to investigate the relationship between cuproptosis-related lncRNAs (CRLncs) and the survival outcomes of patients with OS.MethodsTranscriptome and clinical data of 86 patients with OS were downloaded from The Cancer Genome Atlas (TCGA). The GSE16088 dataset was downloaded from the Gene Expression Omnibus (GEO) database. The 10 cuproptosis-related genes (CRGs) were obtained from a recently published article on cuproptosis in Science. Combined analysis of OS transcriptome data and the GSE16088 dataset identified differentially expressed CRGs related to OS. Next, pathway enrichment analysis was performed. Co-expression analysis obtained CRLncs related to OS. Univariate COX regression analysis and least absolute shrinkage and selection operator (LASSO) regression analysis were used to construct the risk prognostic model of CRLncs. The samples were divided evenly into training and test groups to verify the accuracy of the model. Risk curve, survival, receiver operating characteristic (ROC) curve, and independent prognostic analyses were performed. Next, principal component analysis (PCA) and t-distributed stochastic neighbor embedding (t-SNE) analysis were performed. Single-sample gene set enrichment analysis (ssGSEA) was used to explore the correlation between the risk prognostic models and OS immune microenvironment. Drug sensitivity analysis identified drugs with potential efficacy in OS. Real-time quantitative PCR, Western blotting, and immunohistochemistry analyses verified the expression of CRGs in OS. Real-time quantitative PCR was used to verify the expression of CRLncs in OS.ResultsSix CRLncs that can guide OS prognosis and immune microenvironment were obtained, including three high-risk CRLncs (AL645608.6, AL591767.1, and UNC5B-AS1) and three low-risk CRLncs (CARD8-AS1, AC098487.1, and AC005041.3). Immune cells such as B cells, macrophages, T-helper type 2 (Th2) cells, regulatory T cells (Treg), and immune functions such as APC co-inhibition, checkpoint, and T-cell co-inhibition were significantly downregulated in high-risk groups. In addition, we obtained four drugs with potential efficacy for OS: AUY922, bortezomib, lenalidomide, and Z.LLNle.CHO. The expression of LIPT1, DLAT, and FDX1 at both mRNA and protein levels was significantly elevated in OS cell lines compared with normal osteoblast hFOB1.19. The mRNA expression level of AL591767.1 was decreased in OS, and that of AL645608.6, CARD8-AS1, AC005041.3, AC098487.1, and UNC5B-AS1 was upregulated in OS.ConclusionCRLncs that can guide OS prognosis and the immune microenvironment and drugs that may have a potential curative effect on OS obtained in this study provide a theoretical basis for OS survival research and clinical decision-making.

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“…KIRP has a better prognosis in the early stages than clear cell malignancies, but the situation changes drastically after the cancer has spread to distant sites ( Zhao and Eyzaguirre, 2019 ). Pyroptosis has been linked to the emergence and progression of cancers in a growing body of data ( Liu et al, 2021 ; Zhang et al, 2021 ; Zhou et al, 2021 ). Pyroptosis has been found to slow the development of tumors in multiple cancers ( Sharma et al, 2019 ; Chen et al, 2020 ; Fenini et al, 2020 ).…”

Section: Discussionmentioning

confidence: 99%

Comprehensive Analysis of Pyroptosis-Related Genes and Tumor Microenvironment Infiltration Characterization in Papillary Renal Cell Carcinoma

Zhang

Huang

2022

Front. Mol. Biosci.

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Background: Immunotherapy has emerged as an important technique for treating a variety of cancers. The dynamic interplay between tumor cells and invading lymphocytes in the tumor microenvironment is responsible for the good response to immunotherapy (TME). Pyroptosis, or inflammation-induced cell death, is closely linked to a number of cancers. However, in papillary renal cell carcinoma (KIRP), the association between pyroptosis and clinical prognosis, immune cell infiltration, and immunotherapy impact remains unknown.Methods: We carefully investigated the link between pyroptosis and tumor growth, prognosis, and immune cell infiltration by evaluating 52 pyroptosis-related genes. The PRG score was utilized to measure a single tumor patient’s pyroptosis pattern. After that, we looked at how well these values predicted prognoses and therapy responses in KIRP.Results: We discovered that PRG differences between subgroups were linked to clinical and pathological aspects, prognosis, and TME in two separate genetic subtypes. After that, a PRG score for estimating overall survival (OS) was developed, and its predictive potential in KIRP patients was confirmed. As a result, we developed a very precise nomogram to improve the PRG score’s clinical usefulness. A low PRG score, which is determined by mutation load and immune activation, suggests a good chance of survival. Furthermore, the PRG score was linked to chemotherapeutic drug sensitivity in a substantial way.Conclusions: The possible functions of PRGs in the TME, clinical and pathological characteristics, and prognosis were established in our thorough investigation of PRGs in KIRP. These results might help us better understand PRGs in KIRP and offer a new avenue for prognostic evaluation and the development of more effective immunotherapy treatments.

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A Novel Pyroptosis-Related Signature for Predicting Prognosis and Indicating Immune Microenvironment Features in Osteosarcoma

Cited by 33 publications

References 76 publications

Identification of a Solute Carrier Family-Based Signature for Predicting Overall Survival in Osteosarcoma

Identification of a Solute Carrier Family-Based Signature for Predicting Overall Survival in Osteosarcoma

A novel signature to guide osteosarcoma prognosis and immune microenvironment: Cuproptosis-related lncRNA

Comprehensive Analysis of Pyroptosis-Related Genes and Tumor Microenvironment Infiltration Characterization in Papillary Renal Cell Carcinoma

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