CXCL2-mediated ATR/CHK1 signaling pathway and platinum resistance in epithelial ovarian cancer

Nie, Song; Wan, Yicong; Wang, Hui; Liu, Jinhui; Yang, Jing; Sun, Rui; Meng, Hua; Ma, Xiaolin; Jiang, Yi; Cheng, Wenjun

doi:10.1186/s13048-021-00864-3

Cited by 9 publications

(5 citation statements)

References 41 publications

(30 reference statements)

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“…As a class of chemokines, CXCL2 is involved in the repair process of in ammatory injury and is involved in cell migration, adhesion and immune response. A large number of studies have shown that CXCL2 plays a role in promoting the occurrence and development of cancer in colorectal cancer, ovarian cancer, prostate cancer and chronic lymphocytic leukemia [29] . CXCL2 is involved in cell proliferation, apoptosis, tumor formation and development, and is closely related to the generation and differentiation of megakaryocytes [30] .…”

Section: Discussionmentioning

confidence: 99%

Integrating Single-cell RNA-seq to construct a Neutrophil prognostic model for predicting immune responses in cervical carcinoma

Qian,

Xieyidai,

Han

et al. 2023

Preprint

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Objective: The objective of this study is to comprehensively investigate the communication network within the tumor immune microenvironment (Tumor Immune Microenvironment, TIME) of cervical carcinoma (CC). This involves elucidating the intricate relationships among cells to gain a profound understanding of the interactions between immune cells and tumor cells，as well as the assessment of neutrophil differentiation characteristics and the selection of prognostic genes, the primary goal is to establish a risk model with the ability to predict patients' immune responses and prognosis. Additionally, this model seeks to uncover innovative diagnostic and therapeutic targets for cervical carcinoma, thereby furnishing clinicians with dependable strategies for treatment. Methods: Using single-cell RNA sequencing data (scRNA-seq) obtained from CC samples (E-MTAB-11948), this study employed the Seurat(4.3.0) package to integrate data, remove batch effects, and annotate cell types. A cell communication network was constructed using the iTAKL(0.1.0) package for the analysis of intercellular communication. Neutrophil subpopulations were analyzed utilizing the Monocle2(2.26.0) package to discern various cellular states and conduct pathway analysis using KEGG/GO annotations. Results: we successfully distinguished and further categorized 32 cell populations into 9 major cell types, encompassing T cells, B cells, Mast cells, Neutrophils, Epithelial cells, Endothelial cells, Monocytes, Fibroblasts, and Smooth muscle cells. Furthermore, we ascertained that five subgroups of Neutrophils, each representing diverse differentiation states, exhibit close associations with immune regulatory and metabolic pathways.From our analysis of intersecting genes in the TCGA-CESC dataset, we successfully identified four prognostic genes: C5AR1, HSPA5, CXCL2, and OLR1. The stability of our prognostic risk model has been reiterated through internal and external validation, demonstrating its high consistency, differentiation, and clinical applicability. Notably, the CIRBESORT analysis divulged diminished immune cell content within the tumor immune microenvironment of the high-risk group, correlating with an unfavorable prognosis. Low expression of C5AR1 and high expression of HSPA5, CXCL2, and OLR1 were significantly associated with shorter survival and poorer prognosis.Conclusion: This study elucidated the intricate regulatory network governing the immune microenvironment in CC and comprehensively analyzed intercellular interactions.highlighting the significant roles of C5AR1, HSPA5, CXCL2, and OLR1 in predicting patient prognosis and responsiveness to immunotherapy. These findings offer novel insights and potential strategies for identifying fresh treatment targets in CC. Conclusion: This study elucidated the regulatory network of immune microenvironment in CC, and analyzed the interaction between cells. the key roles of C5AR1, HSPA5, CXCL2 and OLR1 in predicting patient prognosis and response to immunotherapy were revealed. This provides new insights and possible strategies for finding new CC treatment targets.

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Section: Discussionmentioning

confidence: 99%

Integrating Single-cell RNA-seq to construct a Neutrophil prognostic model for predicting immune responses in cervical carcinoma

Qian,

Xieyidai,

Han

et al. 2023

Preprint

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“…CCL21 can be regulated by ACKR4 to suppress antitumor immunity [ 37 ]. Additionally, Nei et al [ 38 ] found that CXCL2 overexpression can maintain the stemness of cells in epithelial ovarian cancer while activating ATR/CHK1 signaling pathway and promoting cell resistance to cisplatin. Group-2 innate lymphoid cells promote HCC progression through CXCL2-neutrophil-induced immunosuppression [ 39 ].…”

Section: Discussionmentioning

confidence: 99%

Hepatocellular Carcinoma Subtyping and Prognostic Model Construction Based on Chemokine-Related Genes

Guo,

Huang,

Zhan

2023

Med Princ Pract

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Background: Chemokines not only regulate immune cells but also play significant roles in development and treatment of tumors and patient prognoses. However, these effects have not been fully explained in hepatocellular carcinoma (HCC). Materials and Methods: We conducted a clustering analysis of chemokine-related genes. We then examined the differences in survival rates and analyzed immune levels using single sample gene set enrichment analysis (ssGSEA) for each subtype. Based on chemokine-related genes of different subtypes, we built a prognostic model in The Cancer Genome Atlas (TCGA) dataset using the survival package and glmnet package and validated it in the Gene Expression Omnibus (GEO) dataset. We used univariate and multivariate regression analyses to select independent prognostic factors and used R package rms to draw a nomogram reflecting patient survival rates at 1, 3, and 5 years. Results: We identified two chemokine subtypes, and after screening, found that Cluster1 had higher survival rates than Cluster2. In addition, in terms of immune evaluation, stromal evaluation, ESTIMATE evaluation, immune abundance, immune function, and expressions of various immune checkpoints, immune levels of Cluster1 were significantly better than those of Cluster2. The immunophenoscore (IPS) of HCC patients in Cluster1 was significantly higher than that in Cluster2. Furthermore, we established a prognostic model consisting of 9 genes, which correlated with chemokines. Through testing, RiskScore was revealed as an independent prognostic factor, and the model could effectively predict HCC patients’ prognoses in both TCGA and GEO datasets. Conclusion: This study resulted in the development of a novel prognostic model related to chemokine genes, providing new targets and theoretical support for HCC patients.

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“…Abnormal immune-related gene expression is strongly associated with immune infiltrating cells in various ways, making it a potential diagnostic and therapeutic target that provides new avenues for studying tumor molecular mechanisms of tumors [30][31][32]. Additionally, tumor-related genes influence various biological processes involved in tumor formation and treatment though activating distinct signaling pathways [33][34][35]. In this study, ADGRD1 was significantly linearly correlated with 149 immune-related genes in NSCLC, and for GO functional annotation analysis, these genes were most enriched in terms "positive regulation of leukocyte activation", "positive regulation of cell activation" , and "leukocyte migration" in BP category, "external side of plasma membrane", "secretory granule lumen", and "cytoplasmic vesicle lumen" in CC category, and "receptor ligand activity", "cytokine activity", and "cytokine receptor binding" in MF category.…”

Section: Discussionmentioning

confidence: 99%

ADGRD1 as a Potential Prognostic and Immunological Biomarker in Non-Small-Cell Lung Cancer

Tian

et al. 2022

BioMed Research International

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ADGRD1 (GPR133), an adhesion G protein-coupled receptor (GPCR), has been linked to cancer. However, the prognostic value and regulatory function within non-small-cell lung cancer (NSCLC) is still unclear. This work adopted various bioinformatics methods, including publicly available databases as well as real-time PCR (RT-PCR), for detecting ADGRD1 expression level and investigating the correlation between ADGRD1 expression level and prognosis, tumor mutational burden (TMB), microsatellite instability (MSI), immune infiltrating cells, immune-related genes, and targeted regulation mechanisms in NSCLC. According to the results, ADGRD1 expression decreased within NSCLC, which might be the factor predicting prognosis of NSCLC. Meanwhile, ADGRD1 showed significant correlation with TMB and MSI, respectively, as well as immune cell infiltrating levels in lung adenocarcinoma (LUAD), which were primarily linked to macrophage M1, mast cell resting, T cell CD4 memory activated, and T cell CD4 memory resting and were associated with mast cell activated and mast cell resting in lung squamous cell carcinoma (LUSC). The most promising upstream regulation pathways of ADGRD1 were likely miR-142-5p, miR-93-5p, and miR-17-5p, which were overexpressed and associated with poor prognosis in NSCLC. ADGRD1 and immune-related genes correlated with ADGRD1 were shown to be enriched in “positive regulation of leukocyte activation,” “external side of plasma membrane,” “receptor ligand activity,” and “cytokine-cytokine receptor interaction” pathways. ADGRD1 expression and regulation may be critical in determining NSCLC prognosis.

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CXCL2-mediated ATR/CHK1 signaling pathway and platinum resistance in epithelial ovarian cancer

Cited by 9 publications

References 41 publications

Integrating Single-cell RNA-seq to construct a Neutrophil prognostic model for predicting immune responses in cervical carcinoma

Integrating Single-cell RNA-seq to construct a Neutrophil prognostic model for predicting immune responses in cervical carcinoma

Hepatocellular Carcinoma Subtyping and Prognostic Model Construction Based on Chemokine-Related Genes

ADGRD1 as a Potential Prognostic and Immunological Biomarker in Non-Small-Cell Lung Cancer

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