Programmed Cell Death Tunes Tumor Immunity

Liu, Jing; Hong, Minjing; Li, Yijia; Chen, Dan; Wu, Yangzhe; Hu, Yi

doi:10.3389/fimmu.2022.847345

Cited by 131 publications

(120 citation statements)

References 233 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Accumulating evidence has revealed that necroptosis genes play an important role in cancer initiation and progression ( 9 , 10 ). Necroptosis genes are also involved in tumorigenesis, distant metastasis and immunosuppression ( 11 ).…”

Section: Introductionmentioning

confidence: 99%

Identification and analysis of necroptosis-associated signatures for prognostic and immune microenvironment evaluation in hepatocellular carcinoma

Bao

et al. 2022

Front. Immunol.

View full text Add to dashboard Cite

BackgroundHepatocellular carcinoma remains the third most common cause of cancer-related deaths worldwide. Although great achievements have been made in resection, chemical therapies and immunotherapies, the pathogenesis and mechanism of HCC initiation and progression still need further exploration. Necroptosis genes have been reported to play an important role in HCC malignant activities, thus it is of great importance to comprehensively explore necroptosis-associated genes in HCC.MethodsWe chose the LIHC cohort from the TCGA, ICGC and GEO databases for this study. ConsensusClusterPlus was adopted to identify the necroptosis genes-based clusters, and LASSO cox regression was applied to construct the prognostic model based on necroptosis signatures. The GSEA and CIBERSORT algorithms were applied to evaluate the immune cell infiltration level. QPCR was also applied in this study to evaluate the expression level of genes in HCC.ResultsWe identified three clusters, C1, C2 and C3. Compared with C2 and C3, the C1 cluster had the shortest overall survival time and highest immune score. The C1 was samples were significantly enriched in cell cycle pathways, some tumor epithelial-mesenchymal transition related signaling pathways, among others. The DEGs between the 3 clusters showed that C1 was enriched in cell cycle, DNA replication, cellular senescence, and p53 signaling pathways. The LASSO cox regression identified KPNA2, SLC1A5 and RAMP3 as prognostic model hub genes. The high risk-score subgroup had an elevated expression level of immune checkpoint genes and a higher TIDE score, which suggested that the high risk-score subgroup had a lower efficiency of immunotherapies. We also validated that the necroptosis signatures-based risk-score model had powerful prognosis prediction ability.ConclusionBased on necroptosis-related genes, we classified patients into 3 clusters, among which C1 had significantly shorter overall survival times. The proposed necroptosis signatures-based prognosis prediction model provides a novel approach in HCC survival prediction and clinical evaluation.

show abstract

Section: Introductionmentioning

confidence: 99%

Identification and analysis of necroptosis-associated signatures for prognostic and immune microenvironment evaluation in hepatocellular carcinoma

Bao

et al. 2022

Front. Immunol.

View full text Add to dashboard Cite

show abstract

“…This may be related to the data sample size and other factors. However, NRGs have been reported to influence the tumor microenvironment 47 , 48 . In addition, tumor microenvironment and immune cells have influenced prognosis in different tumors 49 , 50 .…”

Section: Discussionmentioning

confidence: 99%

Construction and validation model of necroptosis-related gene signature associates with immunity for osteosarcoma patients

Liu

Lei

2022

Sci Rep

View full text Add to dashboard Cite

Osteosarcoma is the most common malignant tumor in children and adolescents and its diagnosis and treatment still need to be improved. Necroptosis has been associated with many malignancies, but its significance in diagnosing and treating osteosarcoma remains unclear. The objective is to establish a predictive model of necroptosis-related genes (NRGs) in osteosarcoma for evaluating the tumor microenvironment and new targets for immunotherapy. In this study, we download the osteosarcoma data from the TARGET and GEO websites and the average muscle tissue data from GTEx. NRGs were screened by Cox regression analysis. We constructed a prediction model through nonnegative matrix factorization (NMF) clustering and the least absolute shrinkage and selection operator (LASSO) algorithm and verified it with a validation cohort. Kaplan–Meier survival time, ROC curve, tumor invasion microenvironment and CIBERSORT were assessed. In addition, we establish nomograms for clinical indicators and verify them by calibration evaluation. The underlying mechanism was explored through the functional enrichment analysis. Eight NRGs were screened for predictive model modeling. NRGs prediction model through NMF clustering and LASSO algorithm was established. The survival, ROC and tumor microenvironment scores showed significant statistical differences among subgroups (P < 0.05). The validation model further verifies it. By nomogram and calibration, we found that metastasis and risk score were independent risk factors for the poor prognosis of osteosarcoma. GO and KEGG analyses demonstrate that the genes of osteosarcoma cluster in inflammatory, apoptotic and necroptosis signaling pathways. The significant role of the correlation between necroptosis and immunity in promoting osteosarcoma may provide a novel insight into detecting molecular mechanisms and targeted therapy.

show abstract

“…Ethanol exposure can also overexpress thioredoxin-interacting protein (TXNIP) by stimulating liver cells, which, in turn, activates NLRP3 inflammasomes and caspase-1-mediated cell typical pyroptosis [ 33 ]. Autophagy, a mechanism of cell survival under conditions of nutritional stress, has also been implicated in the progression of ALD [ 34 ]. It is noteworthy that autophagy regulation is different between acute and chronic ethanol exposure [ 35 ].…”

Section: Pathogenesis Of Aldmentioning

confidence: 99%

Advancements in the Alcohol-Associated Liver Disease Model

Zhu

et al. 2022

Biomolecules

View full text Add to dashboard Cite

Alcohol-associated liver disease (ALD) is an intricate disease that results in a broad spectrum of liver damage. The presentation of ALD can include simple steatosis, steatohepatitis, liver fibrosis, cirrhosis, and even hepatocellular carcinoma (HCC). Effective prevention and treatment strategies are urgently required for ALD patients. In previous decades, numerous rodent models were established to investigate the mechanisms of alcohol-associated liver disease and explore therapeutic targets. This review provides a summary of the latest developments in rodent models, including those that involve EtOH administration, which will help us to understand the characteristics and causes of ALD at different stages. In addition, we discuss the pathogenesis of ALD and summarize the existing in vitro models. We analyse the pros and cons of these models and their translational relevance and summarize the insights that have been gained regarding the mechanisms of alcoholic liver injury.

show abstract

Programmed Cell Death Tunes Tumor Immunity

Cited by 131 publications

References 233 publications

Identification and analysis of necroptosis-associated signatures for prognostic and immune microenvironment evaluation in hepatocellular carcinoma

Identification and analysis of necroptosis-associated signatures for prognostic and immune microenvironment evaluation in hepatocellular carcinoma

Construction and validation model of necroptosis-related gene signature associates with immunity for osteosarcoma patients

Advancements in the Alcohol-Associated Liver Disease Model

Contact Info

Product

Resources

About