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  1. Article: Ferroptosis-Mediated Formation of Tumor-Promoting Immune Microenvironment.

    Bi, Qing / Sun, Ze-Jia / Wu, Ji-Yue / Wang, Wei

    Frontiers in oncology

    2022  Volume 12, Page(s) 868639

    Abstract: Ferroptosis is a newly proposed programmed cell death that has great potential in limiting tumor progression and malignancies that are resistant to conventional therapies. However, recent reports have shown that ferroptosis in the tumor microenvironment ... ...

    Abstract Ferroptosis is a newly proposed programmed cell death that has great potential in limiting tumor progression and malignancies that are resistant to conventional therapies. However, recent reports have shown that ferroptosis in the tumor microenvironment can provide a favorable environment to promote tumor survival and progression, which is induced by the infiltration and polarization of pro-tumor immune cells and the dysfunction of anti-tumor immunity. In this mini-review, we introduce the mechanisms of ferroptosis, describe the crosstalk between ferroptosis and cancer, demonstrate the potential ways in which ferroptosis shapes the pro-tumor immune microenvironment, and present our thoughts on ferroptosis-based cancer therapies.
    Language English
    Publishing date 2022-03-17
    Publishing country Switzerland
    Document type Journal Article ; Review
    ZDB-ID 2649216-7
    ISSN 2234-943X
    ISSN 2234-943X
    DOI 10.3389/fonc.2022.868639
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: Tumor-Associated Inflammation: The Tumor-Promoting Immunity in the Early Stages of Tumorigenesis.

    Bi, Qing / Wu, Ji-Yue / Qiu, Xue-Meng / Zhang, Jian-Dong / Sun, Ze-Jia / Wang, Wei

    Journal of immunology research

    2022  Volume 2022, Page(s) 3128933

    Abstract: Tumorigenesis is a multistage progressive oncogenic process caused by alterations in the structure and expression level of multiple genes. Normal cells are continuously endowed with new capabilities in this evolution, leading to subsequent tumor ... ...

    Abstract Tumorigenesis is a multistage progressive oncogenic process caused by alterations in the structure and expression level of multiple genes. Normal cells are continuously endowed with new capabilities in this evolution, leading to subsequent tumor formation. Immune cells are the most important components of inflammation, which is closely associated with tumorigenesis. There is a broad consensus in cancer research that inflammation and immune response facilitate tumor progression, infiltration, and metastasis
    MeSH term(s) Carcinogenesis/metabolism ; Cell Transformation, Neoplastic ; Humans ; Inflammasomes ; Inflammation/pathology ; Neoplasms
    Chemical Substances Inflammasomes
    Language English
    Publishing date 2022-06-13
    Publishing country Egypt
    Document type Journal Article ; Review
    ZDB-ID 2817541-4
    ISSN 2314-7156 ; 2314-7156
    ISSN (online) 2314-7156
    ISSN 2314-7156
    DOI 10.1155/2022/3128933
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article: Identification of potential necroinflammation-associated necroptosis-related biomarkers for delayed graft function and renal allograft failure: a machine learning-based exploration in the framework of predictive, preventive, and personalized medicine.

    Bi, Qing / Wu, Ji-Yue / Qiu, Xue-Meng / Li, Yu-Qing / Yan, Yu-Yao / Sun, Ze-Jia / Wang, Wei

    The EPMA journal

    2023  Volume 14, Issue 2, Page(s) 307–328

    Abstract: Delayed graft function (DGF) is one of the key post-operative challenges for a subset of kidney transplantation (KTx) patients. Graft survival is significantly lower in recipients who have experienced DGF than in those who have not. Assessing the risk of ...

    Abstract Delayed graft function (DGF) is one of the key post-operative challenges for a subset of kidney transplantation (KTx) patients. Graft survival is significantly lower in recipients who have experienced DGF than in those who have not. Assessing the risk of chronic graft injury, predicting graft rejection, providing personalized treatment, and improving graft survival are major strategies for predictive, preventive, and personalized medicine (PPPM/3PM) to promote the development of transplant medicine. However, since PPPM aims to accurately identify disease by integrating multiple omics, current methods to predict DGF and graft survival can still be improved. Renal ischemia/reperfusion injury (IRI) is a pathological process experienced by all KTx recipients that can result in varying occurrences of DGF, chronic rejection, and allograft failure depending on its severity. During this process, a necroinflammation-mediated necroptosis-dependent secondary wave of cell death significantly contributes to post-IRI tubular cell loss. In this article, we obtained the expression matrices and corresponding clinical data from the GEO database. Subsequently, nine differentially expressed necroinflammation-associated necroptosis-related genes (NiNRGs) were identified by correlation and differential expression analysis. The subtyping of post-KTx IRI samples relied on consensus clustering; the grouping of prognostic risks and the construction of predictive models for DGF (the area under the receiver operating characteristic curve (AUC) of the internal validation set and the external validation set were 0.730 and 0.773, respectively) and expected graft survival after a biopsy (the internal validation set's 1-year AUC: 0.770; 2-year AUC: 0.702; and 3-year AUC: 0.735) were based on the least absolute shrinkage and selection operator regression algorithms. The results of the immune infiltration analysis showed a higher infiltration abundance of myeloid immune cells, especially neutrophils, macrophages, and dendritic cells, in the cluster A subtype and prognostic high-risk groups. Therefore, in the framework of PPPM, this work provides a comprehensive exploration of the early expression landscape, related pathways, immune features, and prognostic impact of NiNRGs in post-KTx patients and assesses their capabilities as.predictors of post-KTx DGF and graft loss,targets of the vicious loop between regulated tubular cell necrosis and necroinflammation for targeted secondary and tertiary prevention, andreferences for personalized immunotherapy.
    Supplementary information: The online version contains supplementary material available at 10.1007/s13167-023-00320-w.
    Language English
    Publishing date 2023-04-28
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2545928-4
    ISSN 1878-5085 ; 1878-5077
    ISSN (online) 1878-5085
    ISSN 1878-5077
    DOI 10.1007/s13167-023-00320-w
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: A promising Prognostic risk model for advanced renal cell carcinoma (RCC) with immune-related genes.

    Cao, Peng / Wu, Ji-Yue / Zhang, Jian-Dong / Sun, Ze-Jia / Zheng, Xiang / Yu, Bao-Zhong / Cao, Hao-Yuan / Zhang, Fei-Long / Gao, Zi-Hao / Wang, Wei

    BMC cancer

    2022  Volume 22, Issue 1, Page(s) 691

    Abstract: Background: Renal cell carcinoma (RCC) is a third most common tumor of the urinary system. Nowadays, Immunotherapy is a hot topic in the treatment of solid tumors, especially for those tumors with pre-activated immune state.: Methods: In this study, ... ...

    Abstract Background: Renal cell carcinoma (RCC) is a third most common tumor of the urinary system. Nowadays, Immunotherapy is a hot topic in the treatment of solid tumors, especially for those tumors with pre-activated immune state.
    Methods: In this study, we downloaded genomic and clinical data of RCC samples from The Cancer Genome Atlas (TCGA) database. Four immune-related genetic signatures were used to predict the prognosis of RCC by Cox regression analysis. Then we established a prognostic risk model consisting of the genes most related to prognosis from four signatures to value prognosis of the RCC samples via Kaplan-Meier (KM) survival analysis. An independent data from International Cancer Genome Consortium (ICGC) database were used to test the predictive stability of the model. Furthermore, we performed landscape analysis to assess the difference of gene mutant in the RCC samples from TCGA. Finally, we explored the correlation between the selected genes and the level of tumor immune infiltration via Tumor Immune Estimation Resource (TIMER) platform.
    Results: We used four genetic signatures to construct prognostic risk models respectively and found that each of the models could divide the RCC samples into high- and low-risk groups with significantly different prognosis, especially in advanced RCC. A comprehensive prognostic risk model was constructed by 8 candidate genes from four signatures (HLA-B, HLA-A, HLA-DRA, IDO1, TAGAP, CIITA, PRF1 and CD8B) dividing the advanced RCC samples from TCGA database into high-risk and low-risk groups with a significant difference in cancer-specific survival (CSS). The stability of the model was verified by independent data from ICGC database. And the classification efficiency of the model was stable for the samples from different subgroups. Landscape analysis showed that mutation ratios of some genes were different between two risk groups. In addition, the expression levels of the selected genes were significantly correlated with the infiltration degree of immune cells in the advanced RCC.
    Conclusions: Sum up, eight immune-related genes were screened in our study to construct prognostic risk model with great predictive value for the prognosis of advanced RCC, and the genes were associated with infiltrating immune cells in tumors which have potential to conduct personalized treatment for advanced RCC.
    MeSH term(s) Biomarkers, Tumor/genetics ; Carcinoma, Renal Cell/pathology ; Gene Expression Regulation, Neoplastic ; Humans ; Kaplan-Meier Estimate ; Kidney Neoplasms/pathology ; Prognosis ; Risk Factors
    Chemical Substances Biomarkers, Tumor
    Language English
    Publishing date 2022-06-23
    Publishing country England
    Document type Journal Article
    ZDB-ID 2041352-X
    ISSN 1471-2407 ; 1471-2407
    ISSN (online) 1471-2407
    ISSN 1471-2407
    DOI 10.1186/s12885-022-09755-2
    Database MEDical Literature Analysis and Retrieval System OnLINE

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