A multi-cellular molecular signaling and functional network map of C-C motif chemokine ligand 18 (CCL18): a chemokine with immunosuppressive and pro-tumor functions

Long non-coding RNA MIR600HG as a ceRNA inhibits the pancreatic cancer progression through regulating the miR-1197/PITPNM3 axis

Objective

Pancreatic cancer (PC) is considered to be a highly malignant cancer with poor prognosis. Long non-coding RNAs (lncRNAs) is the potential factor to predict cancer prognosis. The effect of MIR600HG in PC needs to be further studied. Our work mainly focused on the importance of MIR600HG for PC prognosis and its underlying molecular mechanism of regulating PC progression.

Methods

Data set was acquired from TCGA database to find differentially expressed genes and prognostic significance of MIR600HG in PC, and to construct the MIR600HG competitive endogenous RNA (ceRNA). Clinical specimens were collected to prove the analysis results. Vector over-expressed MIR600HG was transfected to study the roles of MIR600HG in proliferation, apoptosis, invasion and migration. The methods of CCK-8, flow cytometry, Transwell and scratch assays were all used in order to explore the apoptosis, migration and invasion. We evaluated the proliferation-related genes (PCNA, CyclinD1 and P27), as well as invasion and migration-related genes such as MMP-9, MMP-7 and ICAM-1. The transcriptional regulation between MIR600HG and miR-1197/PITPNM3 axis was determined with luciferase reporter assays.

Results

In present study, MIR600HG was dropped in both PC tissues and cells, and the down-regulated MIR600HG was closely related to the poor clinical outcomes in PC patients. MIR600HG could inhibit proliferation, migration and invasion in PC cells. We also investigated whether MIR600HG acting as a sponge of microRNA-1197 (miR-1197) and miR-1197 acting on PITPNM3. We found the positive association between MIR600HG and PITPNM3, as well as the negative association of miR-1197 and MIR600HG (or PITPNM3). Moreover, PITPNM3 mRNA and protein expression saw a simultaneous increase after the MIR600HG-overexpression (MIR600HG-OE), but this result partially diminished in MIR600HG-OE cells and miR-1197 mimics.

Conclusions

Our study explored the anticancer action of MIR600HG in PC by regulating miR-1197 to increase the expression of PITPNM3, which might help the diagnosis and therapy of PC.

An assembly of TROP2-mediated signaling events

Trophoblast cell surface antigen 2 (TROP2) is a calcium-transducing transmembrane protein mainly involved in embryo development. The aberrant expression of TROP2 is observed in numerous cancers, including triple-negative breast cancer, gastric, colorectal, pancreatic, squamous cell carcinoma of the oral cavity, and prostate cancers. The main signaling pathways mediated by TROP2 are calcium signaling, PI3K/AKT, JAK/STAT, MAPKs, and β-catenin signaling. However, collective information about the TROP2-mediated signaling pathway is not available for visualization or analysis. In this study, we constructed a TROP2 signaling map with respect to its role in different cancers. The data curation was done manually by following the NetPath annotation criteria. The described map consists of different molecular events, including 8 activation/inhibition, 16 enzyme catalysis, 19 gene regulations, 12 molecular associations, 39 induced-protein expressions, and 2 protein translocation. The data of the TROP2 pathway map is made freely accessible through the WikiPathways Database ( https://www.wikipathways.org/index.php/Pathway:WP5300 ). Development of TROP2 signaling pathway map.

A comprehensive network map of IL-17A signaling pathway

Interleukin-17A (IL-17A) is one of the member of IL-17 family consisting of other five members (IL-17B to IL-17F). The Gamma delta (γδ) T cells and T helper 17 (Th17) cells are the major producers of IL-17A. Aberrant signaling by IL-17A has been implicated in the pathogenesis of several autoimmune diseases including idiopathic pulmonary fibrosis, acute lung injury, chronic airway diseases, and cancer. Activation of the IL-17A/IL-17 receptor A (IL-17RA) system regulates phosphoinositide 3-kinase/AKT serine/threonine kinase/mammalian target of rapamycin (PI3K/AKT/mTOR), mitogen-activated protein kinases (MAPKs) and activation of nuclear factor-κB (NF-κB) mediated signaling pathways. The IL-17RA activation orchestrates multiple downstream signaling cascades resulting in the release of pro-inflammatory cytokines such as interleukins (IL)-1β, IL-6, and IL-8, chemokines (C-X-C motif) and promotes neutrophil-mediated immune response. Considering the biomedical importance of IL-17A, we developed a pathway resource of signaling events mediated by IL-17A/IL-17RA in this study. The curation of literature data pertaining to the IL-17A system was performed manually by the NetPath criteria. Using data mined from the published literature, we describe an integrated pathway reaction map of IL-17A/IL-17RA consisting of 114 proteins and 68 reactions. That includes detailed information on IL-17A/IL-17RA mediated signaling events of 9 activation/inhibition events, 17 catalysis events, 3 molecular association events, 68 gene regulation events, 109 protein expression events, and 6 protein translocation events. The IL-17A signaling pathway map data is made freely accessible through the WikiPathways Database ( https://www.wikipathways.org/index.php/Pathway : WP5242).

Identification and validation of a CCL18-related signature for prediction of overall survival in patients with uveal melanoma

Uveal melanoma (UM), the most frequent primary intraocular tumor in adults, has poor prognosis. High C-C motif chemokine ligand 18 (CCL18) has been detected in various tumors and is closely correlated with patients' clinicopathological characteristics. However, the essential role of CCL18 in UM remains unclear. Therefore, this study aimed to explore the prognostic value of CCL18 in UM. Uveal melanoma cells (M17) were transfected with pcDNA3.1-CCL18 si-RNA using Lipofectamine™ 2000. Cell growth and invasion abilities were measured through Cell Counting Kit-8 assay and invasion assay. RNA expression data and clinical and histopathological details were downloaded from the UM in The Cancer Genome Atlas (TCGA-UM) and GSE22138 datasets, which were defined as the training and validation cohorts, respectively. Univariate and multivariate Cox regression analyses were performed to identify significant prognostic biomarkers. The coefficients of these significant biomarkers generated by multivariate Cox proportional hazard regression analysis were used to establish a risk score formula. Functional enrichment analyses were also carried out. We found that downregulated CCL18 inhibits M17 cell growth and invasion in vitro. CCL18 may affect UM progression by altering C-C motif receptor 8 related pathways. Higher CCL18 expression was associated with worse clinical outcomes and tumor-specific death in the TCGA-UM dataset. Based on the coefficients obtained from the Cox proportional hazard regression analysis, a CCL18-related prognostic signature formula was constructed as follows: risk score = 0.05590 × age +2.43437 × chromosome 3 status +0.39496 × Expression^CCL18. Notably, in this formula, the normal chromosome 3 was coded as 0, whereas the chromosome 3 loss was coded as 1. Each patient was assigned to either low-risk or high-risk groups using the median cut-off in the training cohort. High-risk patients survived for a shorter time than low-risk patients. The time-dependent and multivariate receiver operating characteristic curves showed promising diagnostic efficacy. Multivariate Cox regression analysis demonstrated the potential of this CCL18-related signature as an independent prognostic indicator. These results were validated using the GSE22138 dataset. In addition, in both TCGA-UM and GSE22138 datasets, stratification of clinical correlations and survival analyses based on this signature indicated the involvement of clinical progression and survival outcome in UM. In the high-risk group, Gene Ontology analyses mainly indicated the enrichment of immune response pathways, such as the T cell activation, response to interferon-gamma, antigen processing and presentation, interferon-gamma-mediated signaling pathway, MHC protein complex, MHC class II protein complex, antigen binding, and cytokine binding. Meanwhile, Kyoto Encyclopedia of Genes and Genomes analyses showed enrichments of pathways in cancer, cell adhesion, cytokine-cytokine receptor interaction, chemokine signaling pathway, Th1 and Th2 cell differentiation, and chemokine signaling pathway. Moreover, single-sample gene set enrichment analysis demonstrated the enrichment of almost all immune cells and immune functions in the high-risk group. In summary, a new prognostic CCL18-related signature was successfully established using the TCGA-UM dataset and validated using the GSE22138 dataset with meaningful predictive and diagnostic efficacies. This signature could serve as an independent and promising prognostic biomarker for patients with UM.

CCL18 signaling from tumor-associated macrophages activates fibroblasts to adopt a chemoresistance-inducing phenotype

The heterogeneity of cancer-associated fibroblasts (CAFs) might be ascribed to differences in origin. CD10 and GPR77 have been reported to identify a chemoresistance-inducing CAF subset in breast cancer. However, the precise mechanism for the formation of the CD10⁺GPR77⁺ CAFs remains unknown. In this study, we found that CCL18 expression was positively correlated with the density of CD10⁺GPR77⁺ CAFs in breast cancer and associated with a poor response to chemotherapy. Moreover, CCL18 secreted by tumor-associated macrophages (TAMs) activated a CD10⁺GPR77⁺ CAF phenotype in normal breast-resident fibroblasts (NBFs), which could then enrich cancer stem cells (CSCs) and induce chemoresistance in breast cancer cells. Mechanistically, CCL18 activated NF-κB signaling via PITPNM3 and thus enhanced the production of IL-6 and IL-8. Furthermore, intratumoral CCL18 injection significantly induced the activation of NBFs and the chemoresistance of xenografts in vivo. In addition, targeting CCL18 by anti-CCL18 antibody could inhibit the formation of CD10⁺GPR77⁺ CAFs and recover the chemosensitivity in vivo, leading to effective tumor control. Collectively, these findings reveal that inflammatory signaling crosstalk between TAMs and fibroblasts is responsible for the formation of the CD10⁺GPR77⁺ CAFs, suggesting CCL18-PITPNM3 signaling is a potential therapeutic target to block the activation of this specific CAF subtype and tumor chemoresistance.

Novel macrophage-related gene prognostic index for glioblastoma associated with M2 macrophages and T cell dysfunction

This study aims to construct a Macrophage-Related Gene Prognostic Index (MRGPI) for glioblastoma (GBM) and explore the underlying molecular, metabolic, and immunological features. Based on the GBM dataset from The Cancer Genome Atlas (n = 156), 13 macrophage-related hub genes were identified by weighted gene co-expression network (WGCNA) analysis. 5 prognostic genes screened by Kaplan-Meire (K-M) analysis and Cox regression model were used to construct the MRGPI, including GPR84, NCF2, HK3, LILRB2, and CCL18. Multivariate Cox regression analysis found that the MRGPI was an independent risk factor (HR = 2.81, CI95: 1.13-6.98, p = 0.026), leading to an unfavorable outcome for the MRGPI-high group, which was further validated by 4 validation GBM cohorts (n = 728). Thereafter, the molecular, metabolic, and immune features and the clinical implications of the MRGPI-based groups were comprehensively characterized. Gene set enrichment analysis (GSEA) found that immune-related pathways, including inflammatory and adaptive immune response, and activated eicosanoid metabolic pathways were enriched in the MRGPI-high group. Besides, genes constituting the MRGPI was primarily expressed by monocytes and macrophages at single-cell scope and was associated with the alternative activation of macrophages. Moreover, correlation analysis and receiver operating characteristic (ROC) curves revealed the relevance between the MRGPI with the expression of immune checkpoints and T cell dysfunction. Thus, the responsiveness of samples in the MRGPI-high group to immune checkpoint inhibitors (ICI) was detected by algorithms, including Tumor Immune Dysfunction and Exclusion (TIDE) and Submap. In contrast, the MRGPI-low group had favorable outcome, was less immune active and insensitive to ICI. Together, we have developed a promising biomarker to classify the prognosis, metabolic and immune features for GBM, and provide references for facilitating the personalized application of ICI in GBM.

Chemokine (C-C motif) ligand 18/membrane-associated 3/forkhead box O1 axis promotes the proliferation, migration, and invasion of intrahepatic cholangiocarcinoma

Phosphatidylinositol Transfer Protein, Membrane-Associated 3 (PITPNM3) often bind with chemokine (C-C motif) ligand 18 (CCL18) to promote tumor progression. However, the role of PITPNM3 in intrahepatic cholangiocarcinoma (ICC) is unclear. We first searched GEPIA database and detected the PITPNM3 expression using immunohistochemistry and real-time quantitative PCR. The results showed that PITPNM3 is high expression in ICC tissues and cells. Then we investigated the cell function of CLL18 and PITPNM3 through cell clone formation assay and transwell assay. The results indicated that CCL18 treatment promoted the proliferation, migration, and invasion of ICC cells. Silence of PITPNM3 reversed the effect of CCL18 on cell function. Simultaneously, we detected key protein expression of forkhead box O1 (FOXO1) and nuclear factor kappa B (NF-KB) through western blotting and found that CCL18 activated NF-KB pathway while inhibited FOXO1 pathway, the effect of which were attenuated by silence of PITPNM3. Finally, we confirmed which pathway affected the cell function using inhibitor of FOXO1 (AS1842856) and activator of NF-KB (Asatone). The results showed that AS1842856, not Asatone, relieved the inhibitory effect of si-PITPNM3 on the cell function of CCL18. In short, CCL18 treatment activated PITPNM3 to promote the proliferation, migration, and invasion of ICC via FOXO1 signaling pathway. These results provided a new insight for the diagnosis and therapy of ICC.

Feature screening for survival trait with application to TCGA high-dimensional genomic data

Background

In high-dimensional survival genomic data, identifying cancer-related genes is a challenging and important subject in the field of bioinformatics. In recent years, many feature screening approaches for survival outcomes with high-dimensional survival genomic data have been developed; however, few studies have systematically compared these methods. The primary purpose of this article is to conduct a series of simulation studies for systematic comparison; the second purpose of this article is to use these feature screening methods to further establish a more accurate prediction model for patient survival based on the survival genomic datasets of The Cancer Genome Atlas (TCGA).

Results

Simulation studies prove that network-adjusted feature screening measurement performs well and outperforms existing popular univariate independent feature screening methods. In the application of real data, we show that the proposed network-adjusted feature screening approach leads to more accurate survival prediction than alternative methods that do not account for gene-gene dependency information. We also use TCGA clinical survival genetic data to identify biomarkers associated with clinical survival outcomes in patients with various cancers including esophageal, pancreatic, head and neck squamous cell, lung, and breast invasive carcinomas.

Conclusions

These applications reveal advantages of the new proposed network-adjusted feature selection method over alternative methods that do not consider gene-gene dependency information. We also identify cancer-related genes that are almost detected in the literature. As a result, the network-based screening method is reliable and credible.