Decreased CXCR2 expression on circulating monocytes of colorectal cancer impairs recruitment and induces Re-education of tumor-associated macrophages

Shao, Qianqian; Wang, Jiaoyang; Zhao, Lei; Wang, Liyang; Cheng, Zhiqiang; Yue, Congbo; Chen, Wendan; Wang, Hongchun; Zhang, Yi

doi:10.1016/j.canlet.2022.01.004

Cited by 13 publications

(8 citation statements)

References 26 publications

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“…Many pathways are associated with the pathogenesis of CD. [124], TLR8 [125], HTRA3 [126], CEBPB (CCAAT enhancer binding protein beta) [127], CD55 [128], CXCR2 [129], CCL28 [130], CBR3 [131], CCL3 [132], FCGR2A [48], ACSL1 [133], CCL2 [134], SOD2 [135], CD14 [136], IGFBP2 [137], CD274 [138], DERL3 [139], SERPINE1 [140], IDO1 [141], PDK1 [142] [156], TYMP (thymidine phosphorylase) [144], S100P [157], PDPN (podoplanin) [158], ADAMTS1 [159], ATF3 [160], TIMP1 [161], UCN2 [162], SELE (selectin E) [163], ICAM1 [164], FOSL1 [165], AREG (amphiregulin) [166], PIM2 [167], SLC7A5 [168], CH25H [169], COL5A2 [170], SNAI1 [171], MXRA5 [172], EGR1 [173], TNFRSF17 [174], MDFI (MyoD family inhibitor) [175], SRGN (serglycin) [176], CEACAM6 [177], CCL11 [178], IFNG (interferon gamma) [179], TREM2 [180], INHBA (inhibin subunit beta A) [181], APOE (apolipoprotein E) [182], FGR (FGR proto-oncogene, Src family tyrosine kinase) GBP5 [465], HGF (hepatocyte growth factor) [466], CXCL9 [467], SLC11A1 [468], IL1RN [469], STAT1 [470], CYP27B1 [471], MMP1 [472], SOCS3 [473], TLR8 [474], CD55 [475], CCL28 [476], FCGR2A [477], CCL2 [478],...…”

Section: Discussionmentioning

confidence: 99%

“…Many pathways are associated with the pathogenesis of CD. Signaling pathway include immune system [69], neutrophil degranulation [114], GDF15 [115], IL1RN [116] STAT1 [117], SLAMF7 [105], CYP27B1 [118], NETO2 [119], TFPI2 [120], ZC3H12A [121], MMP1 [122], CSF3 [123], SOCS3 [124], TLR8 [125], HTRA3 [126], CEBPB (CCAAT enhancer binding protein beta) [127], CD55 [128], CXCR2 [129], CCL28 [130], CBR3 [131], CCL3 [132], FCGR2A [48], ACSL1 [133], CCL2 [134], SOD2 [135] [150], CCR2 [151], VWF (von Willebrand factor) [152], SLC7A11 [153], NOD2 [154], DMBT1 [155], IL20RA [156], TYMP (thymidine phosphorylase) [144], S100P [157], PDPN (podoplanin) [158], ADAMTS1 [159], ATF3 [160], TIMP1 [161], UCN2 [162], SELE (selectin E) [163], ICAM1 [164], FOSL1 [165], AREG (amphiregulin) [166], PIM2 [167], SLC7A5 [168], CH25H [169], COL5A2 [170], SNAI1 [171], MXRA5 [172], EGR1 [173], TNFRSF17 [174], MDFI (MyoD family inhibitor) [175], SRGN (serglycin) [176], CEACAM6 [177], CCL11…”

Section: Discussionmentioning

confidence: 99%

“…Signaling pathway include immune system [69], neutrophil degranulation [70], cytokine signaling in immune system [71], extracellular matrix organization [72], post-translational protein phosphorylation [73], biological oxidations [74], metabolism [75] and metabolism of lipids [76] were responsible for progression of CD. CXCL5 [77], CXCL3 [78], PROK2 [79], CXCR1 [80], PYCR1 [81], OSM (oncostatin M) [82], IL15RA [83], LRG1 [84], LCN2 [85], BATF2 [86], CXCL1 [87], S100A9 [88], IFITM1 [89], MYOF (myoferlin) [90], XBP1 [91], MMP3 [92], TAP1 [93], FPR2 [94], CXCL6 [95], C2CD4A [96], IFITM3 [97], IL1B [98], SLC6A14 [99], FPR1 [100], NOS2 [101], CHI3L1 [102], TGM2 [103], MUC4 [104], TREM1 [105], WNT5A [106], HGF (hepatocyte growth factor) [107], CXCL9 [108], GBP1 [109], S100A11 [110], ADM (adrenomedullin) [111], CXCL11 [112], CXCL10 [113], LILRB2 [114], GDF15 [115], IL1RN [116] STAT1 [117], SLAMF7 [105], CYP27B1 [118], NETO2 [119], TFPI2 [120], ZC3H12A [121], MMP1 [122], CSF3 [123], SOCS3 [124], TLR8 [125], HTRA3 [126], CEBPB (CCAAT enhancer binding protein beta) [127], CD55 [128], CXCR2 [129], CCL28 [130], CBR3 [131], CCL3 [132], FCGR2A [48], ACSL1 [133], CCL2 [134], SOD2 [135], CD14 [136], IGFBP2 [137], CD274 [138], DERL3 [139], SERPINE1 [140], IDO1 [141], PDK...…”

Section: Discussionmentioning

confidence: 99%

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Identification of hub genes and key pathways in pediatric Crohn’s disease using next generation sequencing and bioinformatics analysis

Vastrad¹,

Vastrad²

2022

Preprint

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Pediatric Crohn's Disease (CD) also known as inflammatory bowel diseases, affects millions of people all over the world. The aim of this investigation is to identify the key genes in CD and uncover their potential functions. We downloaded the next generation sequencing (NGS) dataset GSE73374 from the Gene Expression Omnibus (GEO) database. The NGS dataset GSE73374 was used to screen differentially expressed genes (DEGs) between samples from patients with CD and healthy controls. Gene ontology (GO) and REACTOME pathway enrichment analyses were applied for the DEGs. Subsequently, a protein - protein interaction (PPI) network, modules, miRNA- hub gene regulatory network and TF - hub gene regulatory network were constructed to identify hub genes, miRNAs and TFs. Receiver operating characteristic curve (ROC) analysis was applied to validate the hub genes. A total of 957 DEGs were identified, including 478 up regulated genes and 479 down regulated genes. GO and REACTOME results suggested that several Go terms and pathways are involved in response to stimulus, extracellular region, signaling receptor binding, small molecule metabolic process, membrane, transporter activity, immune system and biological oxidations. The top centrality hub genes MDFI, MNDA, FBXO6, TFRC, STAT1, DPP4, MME, SLC39A4, APOA1 and TMEM25 were screened out as the critical genes among the DEGs from the PPI network, modules, miRNA-hub gene regulatory network and TF-hub gene regulatory network. This investigation identified key genes and signal pathways, which might help us improve our understanding of the molecular mechanisms of CD and identify some novel therapeutic targets for CD.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Identification of hub genes and key pathways in pediatric Crohn’s disease using next generation sequencing and bioinformatics analysis

Vastrad¹,

Vastrad²

2022

Preprint

View full text Add to dashboard Cite

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“…Notably, it is pointed out that PMN-MDSCs and tumor-associated neutrophils have some similarities in origin, morphology, and molecular phenotype and also have some functional overlap (67). Similarly, previous studies have confirmed that the number of circulating monocytes determines the number of tumor-associated macrophages (68)(69)(70). As for TAM, it is able to induce apoptosis of T cells with anticancer functions and promote tumor angiogenesis, thereby promoting tumor growth, invasion, and migration, resulting in a poor prognosis (71,72).…”

mentioning

confidence: 89%

Preoperative systemic inflammatory response index predicts the prognosis of patients with hepatocellular carcinoma after liver transplantation

et al. 2023

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BackgroundPreoperative inflammatory status plays an important role in the prognosis of malignancy. We sought to explore the value of preoperative inflammatory biomarkers in predicting long-term outcomes of liver transplantation (LT) in patients with hepatocellular carcinoma (HCC).MethodPatients who underwent LT for HCC in our hospital between January 2010 and June 2020 were included in this study. Demographic, clinical, laboratory, and outcome data were obtained. The area under the curve (AUC) of the receiver operating characteristic curve was used to evaluate the predictive value of inflammatory biomarkers. The effectiveness of inflammatory biomarkers in predicting outcomes was analyzed by univariate and multivariate Cox proportional hazards analyses.ResultsA total of 218 patients were included in the study, with a mean age of 53.9 ± 8.5 years. The AUC of neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), systemic immune inflammation index (SII), and systemic inflammatory response index (SIRI) for overall survival (OS) were 0.741, 0.731, 0.756, 0.746, and 0.749, respectively. Cox proportional hazards model indicated that SIRI > 1.25 was independently associated with low OS [hazard ratio (HR) = 2.258, P = 0.024]. PLR > 82.15 and SIRI > 0.95 were independently associated with low disease-free survival (HR = 1.492, P = 0.015; and HR = 1.732, P = 0.008, respectively). In the survival analysis, the prognosis of patients with high preoperative SIRI and PLR was significantly worse (P < 0.001).ConclusionSIRI and PLR were useful prognostic markers for predicting patients with HCC after LT.

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“…Other chemokines have also been suggested to play a role on monocyte recruitment (Table 1). Some examples are CCR6 (42), CCR7 (43), CCR8 (44), and CXC-chemokine receptor 2 (CXCR2) (45). Circulating monocytes express low levels of CCR6 and do not respond to CCL20, which explains that CCR6 does not display a significant role on the extravasation of monocytes from the circulation to the tissues, but it does on the migration or function of monocytes in inflammation (46,47).…”

Section: Monocyte-attracting Chemokinesmentioning

confidence: 99%

Monocyte-endothelial cell interactions in vascular and tissue remodeling

Medrano-Bosch,

Simón-Codina,

Jiménez

et al. 2023

Front. Immunol.

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Monocytes are circulating leukocytes of innate immunity derived from the bone marrow that interact with endothelial cells under physiological or pathophysiological conditions to orchestrate inflammation, angiogenesis, or tissue remodeling. Monocytes are attracted by chemokines and specific receptors to precise areas in vessels or tissues and transdifferentiate into macrophages with tissue damage or infection. Adherent monocytes and infiltrated monocyte-derived macrophages locally release a myriad of cytokines, vasoactive agents, matrix metalloproteinases, and growth factors to induce vascular and tissue remodeling or for propagation of inflammatory responses. Infiltrated macrophages cooperate with tissue-resident macrophages during all the phases of tissue injury, repair, and regeneration. Substances released by infiltrated and resident macrophages serve not only to coordinate vessel and tissue growth but cellular interactions as well by attracting more circulating monocytes (e.g. MCP-1) and stimulating nearby endothelial cells (e.g. TNF-α) to expose monocyte adhesion molecules. Prolonged tissue accumulation and activation of infiltrated monocytes may result in alterations in extracellular matrix turnover, tissue functions, and vascular leakage. In this review, we highlight the link between interactions of infiltrating monocytes and endothelial cells to regulate vascular and tissue remodeling with a special focus on how these interactions contribute to pathophysiological conditions such as cardiovascular and chronic liver diseases.

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Decreased CXCR2 expression on circulating monocytes of colorectal cancer impairs recruitment and induces Re-education of tumor-associated macrophages

Cited by 13 publications

References 26 publications

Identification of hub genes and key pathways in pediatric Crohn’s disease using next generation sequencing and bioinformatics analysis

Identification of hub genes and key pathways in pediatric Crohn’s disease using next generation sequencing and bioinformatics analysis

Preoperative systemic inflammatory response index predicts the prognosis of patients with hepatocellular carcinoma after liver transplantation

Monocyte-endothelial cell interactions in vascular and tissue remodeling

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