A Necroptosis-Related Prognostic Model of Uveal Melanoma Was Constructed by Single-Cell Sequencing Analysis and Weighted Co-Expression Network Analysis Based on Public Databases

Xie, Jiaheng; Chen, Liang; Tang, Qikai; Wei, Wei; Cao, Yuan; Wu, Chuyan; Hang, Jing; Zhang, Kai; Shi, Jingping; Wang, Ming

doi:10.3389/fimmu.2022.847624

Cited by 42 publications

(43 citation statements)

References 34 publications

(43 reference statements)

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“…Notably, the high-risk and low-risk groups showed significant differences in immunocyte infiltration. These differences in immunocyte infiltration between the high-risk and low-risk groups has been found to exist in a variety of tumors [ 21 – 24 ]. Our results showed that the high-risk group presented relatively high distribution levels of monocytes, activated dendritic cells, activated mast cells, and eosinophils but relatively low distribution levels of resting NK cells and resting mast cells.…”

Section: Discussionmentioning

confidence: 99%

Pyroptosis-related prognosis model, immunocyte infiltration characterization, and competing endogenous RNA network of glioblastoma

Ding

Xiao

et al. 2022

BMC Cancer

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Background Glioblastoma (GBM) has a high incidence rate, invasive growth, and easy recurrence, and the current therapeutic effect is less than satisfying. Pyroptosis plays an important role in morbidity and progress of GBM. Meanwhile, the tumor microenvironment (TME) is involved in the progress and treatment tolerance of GBM. In the present study, we analyzed prognosis model, immunocyte infiltration characterization, and competing endogenous RNA (ceRNA) network of GBM on the basis of pyroptosis-related genes (PRGs). Methods The transcriptome and clinical data of 155 patients with GBM and 120 normal subjects were obtained from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx). Lasso (Least absolute shrinkage and selection operator) Cox expression analysis was used in predicting prognostic markers, and its predictive ability was tested using a nomogram. A prognostic risk score formula was constructed, and CIBERSORT, ssGSEA algorithm, Tumor IMmune Estimation Resource (TIMER), and TISIDB database were used in evaluating the immunocyte infiltration characterization and tumor immune response of differential risk samples. A ceRNA network was constructed with Starbase, mirtarbase, and lncbase, and the mechanism of this regulatory axis was explored using Gene Set Enrichment Analysis (GSEA). Results Five PRGs (CASP3, NLRP2, TP63, GZMB, and CASP9) were identified as the independent prognostic biomarkers of GBM. Prognostic risk score formula analysis showed that the low-risk group had obvious survival advantage compared with the high-risk group, and significant differences in immunocyte infiltration and immune related function score were found. In addition, a ceRNA network of messenger RNA (CASP3, TP63)–microRNA (hsa-miR-519c-5p)–long noncoding RNA (GABPB1-AS1) was established. GSEA analysis showed that the regulatory axis played a considerable role in the extracellular matrix (ECM) and immune inflammatory response. Conclusions Pyroptosis and TME-related independent prognostic markers were screened in this study, and a prognosis risk score formula was established for the first time according to the prognosis PRGs. TME immunocyte infiltration characterization and immune response were assessed using ssGSEA, CIBERSORT algorithm, TIMER, and TISIDB database. Besides a ceRNA network was built up. This study not only laid foundations for further exploring pyroptosis and TME in improving prognosis of GBM, but also provided a new idea for more effective guidance on clinical immunotherapy to patients and developing new immunotherapeutic drugs.

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Section: Discussionmentioning

confidence: 99%

Pyroptosis-related prognosis model, immunocyte infiltration characterization, and competing endogenous RNA network of glioblastoma

Ding

Xiao

et al. 2022

BMC Cancer

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“…These results indicated that SLC25A13 might be a good diagnostic molecule for SKCM. To further determine the survival of SKCM patients, we drew a nomogram combining the risk value and clinical characteristics of the model [ 28 ]. As shown in Figure 4 , we found that the 1-, 3-, and 5-year mortality rates of patient “TCGA-EE-A2A2-06” were 0.102, 0.478 and 0.64, respectively.…”

Section: Resultsmentioning

confidence: 99%

The Overexpression of SLC25A13 Predicts Poor Prognosis and Is Correlated with Immune Cell Infiltration in Patients with Skin Cutaneous Melanoma

Yuan

Han

et al. 2022

Disease Markers

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Purpose. Skin cutaneous melanoma (SKCM) is one of the most malignant and aggressive cancers with poor prognosis due to its rapid progression towards metastasis. Thus, finding clinically relevant biomarkers for early diagnosis, prognosis, and therapy prediction is essential. This study focused on the identification of SLC25A13 as a novel biomarker for SKCM and is aimed at investigating the biological functions of solute carrier family 25 member 13 (SLC25A13) in the development of SKCM. Methods. GEPIA was used to analyze the diagnostic and prognostic values of SLC25A13 in SKCM using the TCGA dataset. PrognoScan was used to validate the prognostic value of SLC25A13 and its coexpressed genes in SKCM. TISIDB was established to reveal the relationship between the expression of SLC25A13 and immune infiltration in SKCM. The protein expression of SLC25A13 in SKCM was evaluated by the Human Protein Atlas. The signaling pathways and biological functions of SLC25A13 in SKCM were analyzed by LinkOmics. Metascape was applied to analyze the functional enrichment analysis of SLC25A13. Protein-protein interaction analysis of SLC25A13 was performed by GeneMANIA. Results. The mRNA and protein levels of SLC25A13 in the SKCM were much higher than those in the normal tissue. Furthermore, the overexpression of SLC25A13 predicts worse outcomes of SKCM patients. Moreover, the SLC25A13 expression was negatively correlated with the immune infiltration level of SKCM. The overexpression of SLC25A13 coexpressed genes, such as ACLY and AFG3L2, and SCL25A13 interacting genes also predicted the unfavorable prognosis of SKCM patients. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis of SLC25A13 coexpressed genes showed that these genes are enriched in ATPase activity, cell cycle, mTOR, and VEGFA-VEGFR2 signaling pathways, which were relevant to tumor development and angiogenesis. Gene set enrichment analysis (GSEA) demonstrated that the SLC25A13 expression was related to infiltrating immune cells in SKCM. Conclusion. Our findings revealed that SLC25A13 might be a potential prognostic and therapeutic biomarker for SKCM.

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“…Its specific mechanism, such as the discovery of immune checkpoints such as PD-1/PDL-1 and CTLA-4, has brought reference for the treatment of many solid tumors ( Xie et al, 2021d ). Immunotherapy has achieved promising outcomes in tumor types such as melanoma ( Carreno et al, 2015 ; Cao et al, 2021 ; Xie et al, 2022 ). However, immunotherapy has progressed relatively slowly in breast cancer ( Emens, 2018 ).…”

Section: Discussionmentioning

confidence: 99%

Integrated Analysis of Genomic and Transcriptomic Profiles Identified the Role of GTP Binding Protein-4 (GTPBP4) in Breast Cancer

Hu¹,

Xie

Chen

et al. 2022

Front. Pharmacol.

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Purpose: To explore the significance of GTP-binding protein 4 (GTPBP4) in breast cancer.Methods: Firstly, GTPBP4 expression analysis was performed in TIMER and UALCAN databases. Subsequently, the TCGA cohort and multiple Gene Expression Omnibus Cohorts were used as validation for GTPBP4 expression. Besides, we also evaluated the diagnostic value of GTPBP4 in TCGA Cohort and multiple GEO Cohorts. The predictive effect of GTPBP4 in breast cancer was then assessed using survival analysis. Then we look at the role of GTPBP4 in the immune milieu and create a Nomogram to help patients with breast cancer understand their prognosis. Finally, in vitro tests were carried out to look at GTPBP4 expression and function in breast cancer cell lines.Results: GTPBP4 is an independent breast cancer prognostic factor that is upregulated in the disease (p < 0.05). Enrichment analysis showed that GTPBP4 was associated with multiple functions and pathways. In addition, GTPBP4 is associated with a variety of immune cell types (p < 0.05). PCR assay showed that GTPBP4 expression was up-regulated in breast cancer cell lines. The activity, migration, and proliferation of breast cancer cells were considerably reduced after GTPBP4 knockdown in the CCK-8, Transwell, and Scratch assays.Conclusions: Our research discovered a new breast cancer biomarker that can be used as a guide for breast cancer diagnosis and treatment.

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A Necroptosis-Related Prognostic Model of Uveal Melanoma Was Constructed by Single-Cell Sequencing Analysis and Weighted Co-Expression Network Analysis Based on Public Databases

Cited by 42 publications

References 34 publications

Pyroptosis-related prognosis model, immunocyte infiltration characterization, and competing endogenous RNA network of glioblastoma

Pyroptosis-related prognosis model, immunocyte infiltration characterization, and competing endogenous RNA network of glioblastoma

The Overexpression of SLC25A13 Predicts Poor Prognosis and Is Correlated with Immune Cell Infiltration in Patients with Skin Cutaneous Melanoma

Integrated Analysis of Genomic and Transcriptomic Profiles Identified the Role of GTP Binding Protein-4 (GTPBP4) in Breast Cancer

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