TAMI-11. INCREASED M1 MACROPHAGE INFILTRATION CORRELATED WITH POOR PROGNOSIS OF WHO IV GLIOMAS

2021 ◽  
Vol 23 (Supplement_6) ◽  
pp. vi200-vi200
Author(s):  
zhaoming Zhou ◽  
Mingyao Lai ◽  
Jiangfen Zhou ◽  
Qingjun Hu ◽  
Ruyu Ai ◽  
...  

Abstract BACKGROUND Gliomas are the malignancy with a poor prognosis. Our previous database mining study demonstrated that M1 macrophage infiltration predicted the survival of GBM patients. Here in this study, we further explored the findings. METHODS RNA-seq was performed on 90 WHO IV glioma tissue samples. The sequencing data was investigated with xCell for the cell infiltration levels, and the M1 macrophage infiltration was further analyzed for the prognostic prediction effect with overall survival (OS) data. Differentially expressed genes (DEGs) were calculated between groups and the hub genes were determined by the MCC models in Cytoscape. The survival risk score (SRS) calculating models were established by several machine learning methods, including the least absolute shrinkage and selection operator (LASSO), generalized linear model (GLM), and linear discriminant analysis (LDA). RESULTS Compared with M1 macrophages none infiltration, WHO IV gliomas with M1 macrophages infiltration was associated with poor prognosis, and this result remained significant in multivariate analyses (hazard ratio [HR], 0.219; 95% CI, 0.047–0.723; P = 0.035). Protein-to-protein (PPI) network analysis of top 200 up-regulated DEGs determined 10 hub genes (P4HB, PDIA6, LAMB1, PRKCSH, CSF1, LAMB2, LGALS1, RCN1, CALU, and TNC). Further analysis determined that the 10 hub genes were enriched in the ECM-receptor interaction signaling pathway, and six out of the ten gene expressions were confirmed by immunohistochemistry staining. Based on the 6 genes, a survival risk score (SRS) was established by machine learning methods. SRS was able to distinguish the high-risk and low-risk WHO IV gliomas with an AUC = 0.80 [95% CI: 0.74 – 0.86, P < 0.01]. CONCLUSIONS M1 macrophage infiltration was an unfavorable prognostic biomarker for WHO IV gliomas. ECM-receptor interaction signaling pathway was involved in M1 macrophage infiltration. Hub genes in the signaling pathway could be the potential therapeutic targets for WHO IV gliomas.

2020 ◽  
Vol 43 (12) ◽  
pp. 656-671
Author(s):  
Xiangxin Zhang ◽  
Liu Yang ◽  
Wei Chen ◽  
Ming Kong

<b><i>Introduction:</i></b> Malignant pleural mesothelioma (MPM) is closely linked to asbestos exposure and is an extremely aggressive tumor with poor prognosis. <b><i>Objective:</i></b> Our study aimed to elucidate hub genes and potential drugs in MPM by integrated bioinformatics analysis. <b><i>Methods:</i></b> GSE42977 was download from the Gene Expression Omnibus (GEO) database; the differentially expressed genes (DEGs) with adj.<i>p</i> value &#x3c;0.05 and |logFC| ≥2 were identified. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed by DAVID database. The STRING database was used to construct a protein-protein interaction network, and modules analysis and hub genes acquisition were performed by Cytoscape. The Gene Expression Profiling Interactive Analysis (GEPIA) database was used to assess the impact of hub genes on the prognosis of MPM patients. The Drug-Gene Interaction database (DGIdb) was used to select the related drugs. <b><i>Results:</i></b> A total of 169 upregulated and 70 downregulated DEGs were identified. These DEGs are enriched in the pathway of extracellular matrix-receptor interaction, focal adhesion, PI3K-Akt signaling pathway, and PPAR signaling pathway. Finally, 10 hub genes (CDC20, CDK1, UBE2C, TOP2A, CCNB2, NUSAP1, KIF20A, AURKA, CEP55, and ASPM) were identified, which are considered to be closely related to the poor prognosis of MPM. In addition, 119 related drugs that may have a therapeutic effect on MPM were filtered out. <b><i>Conclusion:</i></b> These discovered genes and small-molecule drugs provide some new ideas for further research on MPM.


2019 ◽  
Vol 2019 ◽  
pp. 1-14 ◽  
Author(s):  
Rui-sheng Zhou ◽  
Xiong-Wen Wang ◽  
Qin-feng Sun ◽  
Zeng Jie Ye ◽  
Jian-wei Liu ◽  
...  

Hepatocellular carcinoma (HCC) is a primary cause of cancer-related death in the world. Despite the fact that there are many methods to treat HCC, the 5-year survival rate of HCC is still at a low level. Emodin can inhibit the growth of HCC cells invitroand invivo. However, the gene regulation of emodin in HCC has not been well studied. In our research, RNA sequencing technology was used to identify the differentially expressed genes (DEGs) in HepG2 cells induced by emodin. A total of 859 DEGs were identified, including 712 downregulated genes and 147 upregulated genes in HepG2 cells treated with emodin. We used DAVID for function and pathway enrichment analysis. The protein-protein interaction (PPI) network was constructed using STRING, and Cytoscape was used for module analysis. The enriched functions and pathways of the DEGs include positive regulation of apoptotic process, structural molecule activity and lipopolysaccharide binding, protein digestion and absorption, ECM-receptor interaction, complement and coagulation cascades, and MAPK signaling pathway. 25 hub genes were identified and pathway analysis revealed that these genes were mainly enriched in neuropeptide signaling pathway, inflammatory response, and positive regulation of cytosolic calcium ion concentration. Survival analysis showed that LPAR6, C5, SSTR5, GPR68, and P2RY4 may be involved in the molecular mechanisms of emodin therapy for HCC. A quantitative real-time PCR (qRT-PCR) assay showed that the mRNA levels of LPAR6, C5, SSTR5, GPR68, and P2RY4 were significantly decreased in HepG2 cells treated with emodin. In conclusion, the identified DEGs and hub genes in the present study provide new clues for further researches on the molecular mechanisms of emodin.


2019 ◽  
Vol 2019 ◽  
pp. 1-13 ◽  
Author(s):  
Zongfu Pan ◽  
Lu Li ◽  
Qilu Fang ◽  
Yangyang Qian ◽  
Yiwen Zhang ◽  
...  

Anaplastic thyroid carcinoma (ATC) is one of the most aggressive and rapidly lethal tumors. However, limited advances have been made to prolong the survival and to reduce the mortality over the last decades. Therefore, identifying the master regulators underlying ATC progression is desperately needed. In our present study, three datasets including GSE33630, GSE29265, and GSE65144 were retrieved from Gene Expression Omnibus with a total of 32 ATC samples and 78 normal thyroid tissues. A total of 1804 consistently changed differentially expressed genes (DEGs) were identified from three datasets. KEGG pathways enrichment suggested that upregulated DEGs were mainly enriched in ECM-receptor interaction, cell cycle, PI3K-Akt signaling pathway, focal adhesion, and p53 signaling pathway. Furthermore, key gene modules in PPI network were identified by Cytoscape plugin MCODE and they were mainly associated with DNA replication, cell cycle process, collagen fibril organization, and regulation of leukocyte migration. Additionally, TOP2A, CDK1, CCNB1, VEGFA, BIRC5, MAPK1, CCNA2, MAD2L1, CDC20, and BUB1 were identified as hub genes of the PPI network. Interestingly, module analysis showed that 8 out of 10 hub genes participated in Module 1 network and more than 70% genes of Module 2 consisted of collagen family members. Notably, transcription factors (TFs) regulatory network analysis indicated that E2F7, FOXM1, and NFYB were master regulators of Module 1, while CREB3L1 was the master regulator of Module 2. Experimental validation showed that CREB3L1, E2F7, and FOXM1 were significantly upregulated in ATC tissue and cell line when compared with normal thyroid group. In conclusion, the TFs regulatory network provided a more detail molecular mechanism underlying ATC occurrence and progression. TFs including E2F7, FOXM1, CREB3L1, and NFYB were likely to be master regulators of ATC progression, suggesting their potential role as molecular therapeutic targets in ATC treatment.


2021 ◽  
Author(s):  
Qiangqiang Zheng ◽  
Shihui Min ◽  
Qinghua Zhou

Accumulating evidence has demonstrated that gene alterations play a crucial role in LUAD development, progression, and prognosis. The current study aimed to identify the hub genes associated with LUAD. In the present study, we used TCGA database to screen the hub genes. Then, we validated the results by GEO datasets. Finally, we used cBioPortal, UALCAN, qRT-PCR, HPA database, TCGA database, and Kaplan-Meier plotter database to estimate the gene mutation, gene transcription, protein expression, clinical features of hub genes in patients with LUAD. A total of 5,930 DEGs were screened out in TCGA database. Enrichment analysis revealed that DEGs were involved in the transcriptional misregulation in cancer, viral carcinogenesis, cAMP signaling pathway, calcium signaling pathway, and ECM-receptor interaction. The combining results of MCODE and CytoHubba showed that ADCY8, ADRB2, CALCA, GCG, GNGT1, and NPSR1 were hub genes. Then, we verified the above results by GSE118370, GSE136043, and GSE140797 datasets. Compared with normal lung tissues, the expression level of ADCY8 and ADRB2 were lower in LUAD tissues, but the expression level of CALCA, GCG, GNGT1, and NPSR1 were higher. In the prognosis analyses, the low expression of ADCY8 and ADRB2 and the high expression of CALCA, GCG, GNGT1, and NPSR1 were correlated with poor OS and poor PFS. The significant differences in the relationship of the expression of 6 hub genes and clinical features were observed. In conclusion, 6 hub genes will not only contribute to elucidating the pathogenesis of LUAD, and may be potential therapeutic targets for LUAD.


2020 ◽  
Author(s):  
tao ming Shao ◽  
zhi yang Hu ◽  
wen wei Li ◽  
long yun Pan

Abstract Purpose. Breast cancer (BC) has a poor prognosis when brain metastases (BM) occur, and the treatment effect is limited. In this study, we aim to identify representative candidate biomarkers for clinical prognosis of patients with BM and explore the mechanisms underlying the progression of BC.Methods. Herein, we examined the Microarray datasets (GSE125989) obtained from the Gene Expression Omnibus database to find the target genes in BC patients with BM. We employed the GEO2R tool to filter the differentially expressed genes (DEGs) that participate in primary BC and BC with BM. Subsequently, using the DAVID tool, we conducted an enrichment analysis with the screened DEGs based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene Ontology (GO) functional annotation. The STRING database was employed to analyze the protein-protein interactions of the DEGs and visualized using Cytoscape software. Lastly, the Kaplan-Meier plotter database was employed to determine the prognostic potential of hub genes in BC.Results. We screened out 311 upregulated DEGs and 104 downregulated DEGs. The enrichment analyses revealed that all the DEGs were` enriched in the biological process of extracellular matrix organization, cell adhesion, proteolysis, collagen catabolic process and immune response. The significant enrichment pathways were focal adhesion, protein absorption and digestion, ECM-receptor interaction, PI3K-Akt signalling pathway, and Pathways in cancer. The top ten hub nodes screened out included FN1, VEGFA, COL1A1, MMP2, COL3A1, COL1A2, POSTN, DCN, BGN and LOX. The Kaplan-Meier plotter results showed that the three hub genes (FN1, VEGFA and DCN) are candidate biomarkers for clinical prognosis of patients with BM.Conclusion. we identified seven genes related to poor prognosis in BCBM. FN1, VEGFA and DCN can be considered as potential prognostic markers for BCBM. Meantime, COL1A1, POSTN, BGN and LOX may be linked to the distant transformation of BC.


2021 ◽  
Vol 12 (6) ◽  
Author(s):  
Zhongyang Lv ◽  
Xingquan Xu ◽  
Ziying Sun ◽  
Yannick Xiaofan Yang ◽  
Hu Guo ◽  
...  

AbstractOsteoarthritis (OA) is the major course of joint deterioration, in which M1 macrophage-driven synovitis exacerbates the pathological process. However, precise therapies for M1 macrophage to decrease synovitis and attenuate OA progression have been scarcely proposed. Transient receptor potential vanilloid 1 (TRPV1) is a cation channel that has been implicated in pain perception and inflammation. In this study, we investigated the role of TRPV1 in the M1 macrophage polarization and pathogenesis of OA. We demonstrated that TRPV1 expression and M1 macrophage infiltration were simultaneously increased in both human and rat OA synovium. More than 90% of the infiltrated M1 macrophages expressed TRPV1. In the rat OA model, intra-articular injection of capsaicin (CPS), a specific TRPV1 agonist, significantly attenuated OA phenotypes, including joint swelling, synovitis, cartilage damage, and osteophyte formation. CPS treatment markedly reduced M1 macrophage infiltration in the synovium. Further mechanistic analyses showed that TRPV1-evoked Ca2+ influx promoted the phosphorylation of calcium/calmodulin-dependent protein kinase II (CaMKII) and facilitated the nuclear localization of nuclear factor-erythroid 2-related factor 2 (Nrf2), which ultimately resulted in the inhibition of M1 macrophage polarization. Taken together, our findings establish that TRPV1 attenuates the progression of OA by inhibiting M1 macrophage polarization in synovium via the Ca2+/CaMKII/Nrf2 signaling pathway. These results highlight the effect of targeting TRPV1 for the development of a promising therapeutic strategy for OA.


2021 ◽  
pp. 1-17
Author(s):  
Qiaoyun Zhao ◽  
Jun Xie ◽  
Jinliang Xie ◽  
Rulin Zhao ◽  
Conghua Song ◽  
...  

BACKGROUND: Gastric cancer (GC) is one of the most deadliest tumours worldwide, and its prognosis remains poor. OBJECTIVE: This study aims to identify and validate hub genes associated with the progression and prognosis of GC by constructing a weighted correlation network. METHODS: The gene co-expression network was constructed by the WGCNA package based on GC samples and clinical data from the TCGA database. The module of interest that was highly related to clinical traits, including stage, grade and overall survival (OS), was identified. GO and KEGG pathway enrichment analyses were performed using the clusterprofiler package in R. Cytoscape software was used to identify the 10 hub genes. Differential expression and survival analyses were performed on GEPIA web resources and verified by four GEO datasets and our clinical gastric specimens. The receiver operating characteristic (ROC) curves of hub genes were plotted using the pROC package in R. The potential pathogenic mechanisms of hub genes were analysed using gene set enrichment analysis (GSEA) software. RESULTS: A total of ten modules were detected, and the magenta module was identified as highly related to OS, stage and grade. Enrichment analysis of magenta module indicated that ECM-receptor interaction, focal adhesion, PI3K-Akt pathway, proteoglycans in cancer were significantly enriched. The PPI network identified ten hub genes, namely COL1A1, COL1A2, FN1, POSTN, THBS2, COL11A1, SPP1, MMP13, COMP, and SERPINE1. Three hub genes (FN1, COL1A1 and SERPINE1) were finally identified to be associated with carcinogenicity and poor prognosis of GC, and all were independent risk factors for GC. The area under the curve (AUC) values of FN1, COL1A1 and SERPINE1 for the prediction of GC were 0.702, 0.917 and 0.812, respectively. GSEA showed that three hub genes share 15 common upregulated biological pathways, including hypoxia, epithelial mesenchymal transition, angiogenesis, and apoptosis. CONCLUSION: We identified FN1, COL1A1 and SERPINE1 as being associated with the progression and poor prognosis of GC.


Blood ◽  
2020 ◽  
Vol 136 (Supplement 1) ◽  
pp. 29-30
Author(s):  
Mark Yan ◽  
Yi Meng Chang ◽  
Vibha Raghavan ◽  
Estella Dong ◽  
Christian Klein ◽  
...  

Introduction: The lymphoma microenvironment is increasingly recognized as crucial to sustaining lymphoma cell growth and an important contributor to treatment outcome, especially in the context of immunotherapies. CD20-targeted monoclonal antibodies (e.g. obinutuzumab [G] and rituximab [R]) function by several mechanisms, including antibody-dependent cellular cytotoxicity/phagocytosis (ADCC/ADCP). Immune effector cells, such as natural killer (NK) cells and phagocytes (i.e. macrophages and dendritic cells), and the Fc gamma receptor (FcγR) found on the surface of these cells, are critical to antibody treatment efficacy. Here we evaluated how the lymphoma microenvironment may affect clinical outcome in patients (pts) with previously untreated diffuse large B-cell lymphoma (DLBCL) receiving immunochemotherapy. Methods: We leveraged two large Phase III clinical trials of pts with previously untreated DLBCL (GOYA [NCT01287741] and MAIN [NCT00486759]) to produce comprehensive lymphoma immune microenvironment profiles from 604 tissue biopsies from pts treated with R plus cyclophosphamide, doxorubicin, vincristine and prednisone (R-CHOP) or G plus CHOP (G-CHOP) using the RNA-Seq deconvolution and marker gene methods: quanTIseq and xCell. The infiltration scores in each pt for various immune and stromal cell types were assessed, and their contribution to disease biology and treatment outcome was examined. Results: The extent of lymphoma microenvironment heterogeneity highlighted by the deconvolution analyses was consistent with previous studies (Figure A). Of the infiltrating cell types analyzed, the M1 macrophage signature quantified by either quanTIseq or xCell was most strongly associated with lower risk of progression (progression-free survival [PFS]; quanTIseq: HR, 0.596; 95% CI: 0.441-0.805; 24-month PFS: 82% [M1 high] vs 68% [M1 low] and xCell: HR, 0.627; 95% CI: 0.465-0.844; 24-month PFS: 80% [M1 high] vs 70% [M1 Low]; Figure B, C, D) and improved overall survival (OS; quanTIseq: HR, 0.465; 95% CI: 0.318-0.679; and xCell: HR, 0.527; 95% CI: 0.365-0.762). This finding was confirmed by both algorithms. This prognostic trend was stronger amongst G-treated pts than R-treated pts, consistent with the previous finding that G exhibits higher ADCC versus R (Mössner, et al. Blood 2010). Pts with PFS &gt;24 months had significantly higher levels of M1 macrophage scores than pts with PFS &lt;24 months. Despite the correlation with delayed disease progression, there was no differential enrichment of M1 macrophages in pts with complete response versus non-responders at end of treatment, or depending on International Prognostic Index. M1 scores did not significantly differ depending on cell of origin, although there was a trend for higher M1 macrophage scores in germinal center B-cell DLBCL. Aside from M1 macrophages, CD4+Th2 cells showed the strongest prognostic trend in DLBCL (PFS; HR, 0.745; 95% CI: 0.553-1.000; Figure C). In contrast to M1 macrophages, pts with M2 macrophage infiltration tended to have shorter PFS and OS although relatively low levels were observed for these signatures (Figure B, C). This suggests that lymphoma-infiltrating macrophages more commonly resemble the classically activated M1 polarization phenotype and are linked to prolonged PFS, while alternatively activated M2 macrophages, although their frequency is lower in DLBCL, are associated with shorter PFS. Consistent with previous work showing that programmed death-ligand 1 (PD-L1) levels correlate with a macrophage signature in DLBCL (McCord, et al. Blood Adv 2019), M1, but not M2, macrophage infiltration correlated with PD-L1 mRNA expression. M1 enrichment was highly correlated with CD8+ T cell signatures (including central and effector memory CD8+ T cells) in DLBCL. Conclusions: Data suggest macrophage polarization may be an important contributor to immunochemotherapy outcome in DLBCL. Previous studies aiming to link tumor-associated macrophages to R-CHOP outcome have yielded conflicting results, perhaps as most relied on CD68/CD163 staining alone as markers. Although R and G are thought to function via NK cell-mediated ADCC, FcγR-dependent stimulation of M1 macrophage-mediated ADCP may be key to sustaining their anti-lymphoma activity. Strategies facilitating the recruitment of M1 macrophages or macrophage repolarization may augment responses to immunochemotherapy in DLBCL. Disclosures Yan: F. Hoffmann-La Roche: Current Employment, Current equity holder in publicly-traded company. Chang:F. Hoffmann-La Roche: Current Employment, Current equity holder in private company. Raghavan:F. Hoffmann-La Roche: Current Employment. Dong:In graduate school: University of Toronto, MSc Biostatistics: Ended employment in the past 24 months; F. Hoffmann-La Roche, Mississauga, Biometrics: Current Employment. Klein:Roche: Current Employment, Current equity holder in publicly-traded company, Patents & Royalties. Nielsen:F. Hoffmann-La Roche: Current Employment, Current equity holder in publicly-traded company. Paulson:Genentech, Inc: Current Employment; F. Hoffmann-La Roche: Current equity holder in private company, Current equity holder in publicly-traded company. Hatzi:F. Hoffmann-La Roche: Current equity holder in publicly-traded company; Genentech, Inc.: Current Employment.


2021 ◽  
Vol 12 ◽  
Author(s):  
Chaolu Chen ◽  
Shuaiying Zhu ◽  
Long Bai ◽  
Meihua Sui ◽  
Danqing Chen

Parturition involves the transformation of the quiescent myometrium into a highly excitable and contractile state, a process that is driven by changes in myometrial gene expression. This study aimed to identify myometrial transcriptomic signatures and potential novel hub genes in parturition, which have great significance for understanding the underlying mechanisms of successful parturition and treating labor-associated pathologies such as preterm birth. In our study, comparative transcriptome analysis was carried out on human myometrial tissues collected from women undergoing caesarean section at term in the presence (TL = 8) and absence of labor (TNL = 8). A total of 582 differentially expressed genes (DEGs) between TL and TNL tissues were identified. Gene ontology (GO), Kyoto encyclopedia of genes and genomes (KEGG) and gene set enrichment analysis (GSEA) revealed that the DEGs were enriched in signal transduction, regulation of signaling receptor activity, inflammatory response, cytokine-cytokine receptor interaction, IL-17 signaling pathway, TNF signaling pathway, among others. Thus, transcriptome analysis of the myometrium during term labor revealed that labor onset was associated with an inflammatory response. Moreover, protein-protein interactions network analysis identified FPR1, CXCL8, CXCL1, BDKRB2, BDKRB1, and CXCL2 as the hub genes associated with onset of labor. Formyl peptide receptor 1 (FPR1) was highly expressed in laboring myometrial tissues, with the activation of FPR1 in vitro experiments resulting in increased myometrial contraction. Our findings demonstrate the novel role of FPR1 as a modulator of myometrial contraction.


2021 ◽  
Vol 12 ◽  
Author(s):  
Nooshin Ghahramani ◽  
Jalil Shodja ◽  
Seyed Abbas Rafat ◽  
Bahman Panahi ◽  
Karim Hasanpur

Background: Mastitis is the most prevalent disease in dairy cattle and one of the most significant bovine pathologies affecting milk production, animal health, and reproduction. In addition, mastitis is the most common, expensive, and contagious infection in the dairy industry.Methods: A meta-analysis of microarray and RNA-seq data was conducted to identify candidate genes and functional modules associated with mastitis disease. The results were then applied to systems biology analysis via weighted gene coexpression network analysis (WGCNA), Gene Ontology, enrichment analysis for the Kyoto Encyclopedia of Genes and Genomes (KEGG), and modeling using machine-learning algorithms.Results: Microarray and RNA-seq datasets were generated for 2,089 and 2,794 meta-genes, respectively. Between microarray and RNA-seq datasets, a total of 360 meta-genes were found that were significantly enriched as “peroxisome,” “NOD-like receptor signaling pathway,” “IL-17 signaling pathway,” and “TNF signaling pathway” KEGG pathways. The turquoise module (n = 214 genes) and the brown module (n = 57 genes) were identified as critical functional modules associated with mastitis through WGCNA. PRDX5, RAB5C, ACTN4, SLC25A16, MAPK6, CD53, NCKAP1L, ARHGEF2, COL9A1, and PTPRC genes were detected as hub genes in identified functional modules. Finally, using attribute weighting and machine-learning methods, hub genes that are sufficiently informative in Escherichia coli mastitis were used to optimize predictive models. The constructed model proposed the optimal approach for the meta-genes and validated several high-ranked genes as biomarkers for E. coli mastitis using the decision tree (DT) method.Conclusion: The candidate genes and pathways proposed in this study may shed new light on the underlying molecular mechanisms of mastitis disease and suggest new approaches for diagnosing and treating E. coli mastitis in dairy cattle.


Sign in / Sign up

Export Citation Format

Share Document