scholarly journals EPEN-10. UNRAVELLING THE TUMOR IMMUNE MICROENVIRONMENT OF POSTERIOR FOSSA A EPENDYMOMAS ON RNA AND PROTEIN EXPRESSION LEVELS

2021 ◽  
Vol 23 (Supplement_1) ◽  
pp. i15-i15
Author(s):  
Fenna F. Feenstra ◽  
Friso Calkoen ◽  
Johan M Kros ◽  
Lennart Kester ◽  
Mariëtte Kranendonk ◽  
...  

Abstract Background Ependymomas account for 8–10% of pediatric brain tumors, and the standard therapy of surgery and radiation has not changed for the past two decades. Characterization of the tumor immune microenvironment (TIME) is of great importance in order to find better therapies. However, the TIME of ependymomas is still not defined. In this retrospective observational study we aimed to unravel the TIME of ependymomas at mRNA and protein expression levels. Methods Ependymoma samples from two locations were selected: Posterior Fossa (PF-A, n=8), and supratentorial (ST, n=5). Targeted gene expression profile using the PanCancer immune profile panel of NanoString technology was performed. Data were analyzed using the nSolver software. In addition, 8 samples were subjected to RNA bulk sequencing, and the sequenced data were connected to the expression data of the same samples. To validate some of the findings, immunohistochemistry was performed. Results Unsupervised hierarchical clustering showed that PF-A ependymomas can be divided into two groups based on the expression of their immune-related genes. PF-A that showed high immune-expression clustered closely to the ST ependymomas. Significant expressions of genes related to “antigen-processing” and “adhesion” pathways were found in the immune-active groups. On the contrary, the PF-A that had low expressions of immune-related genes showed a high expression of BMI1 that has a prognostic and therapeutic value. Connecting gene expression to bulk sequence data validated the findings. In addition, immunohistochemical analysis confirmed that protein expression for some of the findings. Conclusion The TIME varies in ependymomas based on the location of the tumor. Moreover, the immune-related expression profiles indicated that PF-A ependymomas can be divided into two groups: immune-active and immune-not active PF-A. The prognostic and therapeutic values of the immune activity of PF-A should be further studied.

2020 ◽  
Author(s):  
Wei-cheng Lu ◽  
Hui Xie ◽  
Ce Yuan ◽  
Jin-jiang Li ◽  
Zhao-yang Li ◽  
...  

Abstract Background This study was intended to investigate the genomic landscape of the immune microenvironments of brain metastases in breast cancer. Methods Three gene expression profile datasets (GSE76714, GSE125989 and GSE43837) of breast cancer with brain metastases were downloaded from Gene Expression Omnibus (GEO) database. After differential expression analysis, the tumor immune microenvironment and immune cell infiltration were analyzed. Then immune-related genes were identified, followed by function analysis, transcription factor (TF)-miRNA-mRNA co-regulatory network analysis, and survival analysis of metastatic recurrence. Results The present results showed that the tumor immune microenvironment in brain metastases was immunosuppressed compared with primary caner. Compared with primary cancer samples, the infiltration ratio of plasma cells in brain metastases samples was significantly higher, while the infiltration ratio of macrophages M2 cells in brain metastases samples was significantly lower. Total 42 immune-related genes were identified, such as THY1 and NEU2. CD1B and THY1 were found to be implicated in the metastatic recurrence of breast cancer. Conclusions Targeting macrophages or plasma cells may be new strategies for immunotherapy of breast cancer with brain metastases. THY1 and NEU2 may be potential therapeutic targets for breast cancer with brain metastases, and THY1 and CD1B may serve as potential prognostic markers for improvement of brain metastases survival.


2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Shunqiang Nong ◽  
Xiaohao Chen ◽  
Zechen Wang ◽  
Guidan Xu ◽  
Wujun Wei ◽  
...  

Background. Increasing evidence demonstrated that long noncoding RNA (lncRNA) could affect inflammatory tumor immune microenvironment by modulating gene expression and could be used as a biomarker for HBC-related hepatocellular carcinoma (HCC) but still needs further research. The aim of the present study was to determine an lncRNA signature for the diagnosis of HBV-related HCC. Methods. HBV-related HCC expression profiles (GSE55092, GSE19665, and GSE84402) were abstracted from the GEO (Gene Expression Omnibus) data resource, and R package limma and RobustRankAggreg were employed to identify common differentially expressed genes (DEGs). Using machine learning, optimal diagnostic lncRNA molecular markers for HBV-related HCC were identified. The expression of candidate lncRNAs was cross-validated in GSE121248, and an ROC (receiver operating characteristic) curve of lncRNA biomarkers was carried out. Additionally, a coexpression network and functional annotation was built, after which a PPI (protein-protein interaction) network along with module analysis were conducted with the Cytoscape open source software. Result. A total of 38 DElncRNAs and 543 DEmRNAs were identified with a fold change larger than 2.0 and a P value < 0.05. By machine learning, AL356056.2, AL445524.1, TRIM52-AS1, AC093642.1, EHMT2-AS1, AC003991.1, AC008040.1, LINC00844, and LINC01018 were screened out as optional diagnostic lncRNA biosignatures for HBV-related HCC. The AUC (areas under the curve) of the SVM (support vector machine) model and random forest model were 0.957 and 0.904, respectively, and the specificity and sensitivity were 95.7 and 100% and 94.3 and 86.5%, respectively. The results of functional enrichment analysis showed that the integrated coexpressed DEmRNAs shared common cascades in the p53 signaling pathway, retinol metabolism, PI3K-Akt signaling cascade, and chemical carcinogenesis. The integrated DEmRNA PPI network complex was found to be comprised of 87 nodes, and two vital modules with a high degree were selected with the MCODE app. Conclusion. The present study identified nine potential diagnostic biomarkers for HBV-related HCC, all of which could potentially modulated gene expression related to inflammatory conditions in the tumor immune microenvironment. The functional annotation of the target DEmRNAs yielded novel evidence in evaluating the precise functions of lncRNA in HBV-related HCC.


2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Adaugo Q. Ohandjo ◽  
Zongzhi Liu ◽  
Eric B. Dammer ◽  
Courtney D. Dill ◽  
Tiara L. Griffen ◽  
...  

Abstract The tumor immune microenvironment (TIME) consists of multiple cell types that contribute to the heterogeneity and complexity of prostate cancer (PCa). In this study, we sought to understand the gene-expression signature of patients with primary prostate tumors by investigating the co-expression profiles of patient samples and their corresponding clinical outcomes, in particular “disease-free months” and “disease reoccurrence”. We tested the hypothesis that the CXCL13-CXCR5 axis is co-expressed with factors supporting TIME and PCa progression. Gene expression counts, with clinical attributes from PCa patients, were acquired from TCGA. Profiles of PCa patients were used to identify key drivers that influence or regulate CXCL13-CXCR5 signaling. Weighted gene co-expression network analysis (WGCNA) was applied to identify co-expression patterns among CXCL13-CXCR5, associated genes, and key genetic drivers within the CXCL13-CXCR5 signaling pathway. The processing of downloaded data files began with quality checks using NOISeq, followed by WGCNA. Our results confirmed the quality of the TCGA transcriptome data, identified 12 co-expression networks, and demonstrated that CXCL13, CXCR5 and associated genes are members of signaling networks (modules) associated with G protein coupled receptor (GPCR) responsiveness, invasion/migration, immune checkpoint, and innate immunity. We also identified top canonical pathways and upstream regulators associated with CXCL13-CXCR5 expression and function.


2020 ◽  
Author(s):  
Wei-cheng Lu ◽  
Hui Xie ◽  
Ce Yuan ◽  
Jin-jiang Li ◽  
Zhao-yang Li ◽  
...  

Abstract Background: This study was intended to investigate the genomic landscape of the immune microenvironments of brain metastases in breast cancer. Methods: Three gene expression profile datasets (GSE76714, GSE125989 and GSE43837) of breast cancer with brain metastases were downloaded from Gene Expression Omnibus (GEO) database. After differential expression analysis, the tumor immune microenvironment and immune cell infiltration were analyzed. Then immune-related genes were identified, followed by function analysis, transcription factor (TF)-miRNA-mRNA co-regulatory network analysis, and survival analysis of metastatic recurrence. Results: The present results showed that the tumor immune microenvironment in brain metastases was immunosuppressed compared with primary caner. Compared with primary cancer samples, the infiltration ratio of plasma cells in brain metastases samples was significantly higher, while the infiltration ratio of macrophages M2 cells in brain metastases samples was significantly lower. Total 42 immune-related genes were identified, such as THY1 and NEU2. CD1B, THY1 and DOCK2 were found to be implicated in the metastatic recurrence of breast cancer. Conclusions: Targeting macrophages or plasma cells may be new strategies for immunotherapy of breast cancer with brain metastases. THY1 and NEU2 may be potential therapeutic targets for breast cancer with brain metastases, and THY1, CD1B and DOCK2 may serve as potential prognostic markers for improvement of brain metastases survival.


2021 ◽  
Vol 9 (Suppl 1) ◽  
pp. A10.1-A10
Author(s):  
J Lammers ◽  
F Calkoen ◽  
M Kranendonk ◽  
A Federico ◽  
M Kool ◽  
...  

BackgroundEpendymoma is the third most common brain tumor in children. At the moment, surgery and radiotherapy are the only effective treatments that can be offered, and despite this, a significant part of the patients relapse with no therapeutic salvage options. Therefore, new treatment modalities are needed. To develop immunotherapies for these children, knowledge of the tumor microenvironment is crucial. The current study aims to unravel the tumor immune microenvironment (TIME) of pediatric posterior fossa A (PFA) ependymomas.Materials and MethodsWe used bulk RNA sequencing data of 22 pediatric ependymomas. We defined two groups, hereafter called PFA immune+ (PFAI+) and PFAI-, based on the RNA expression levels of the NanoString panel of Human PanCancer Immune Profiling genes. We performed gene set enrichment analysis and deconvoluted the bulk RNA samples with ependymoma-specific single-cell RNA sequencing datasets. To validate our findings on a protein level, we applied immunohistochemistry with antibodies recognizing tumor-infiltrating lymphocytes, tumor-associated macrophages and microglia.ResultsUnsupervised hierarchical clustering of RNA expression of immune-related genes revealed two distinct PFA groups. Differential gene expression analysis showed that PFAI+ have a significantly higher expression of genes associated with immune functions, such as CD3E, CCR2, GZMA, CXCL9 and TRBC2. Accordingly, gene set enrichment analysis demonstrated that several immune pathways, including T-cell signalling, interferon-gamma response and TNFα signalling are enriched in PFAI+ ependymomas. RNA expression of immune checkpoints was also higher in PFAI+ tumors, indicating that these tumors might be more responsive to combinational therapies including immune checkpoint inhibitors. While immunohistochemistry showed low amounts of infiltrating CD3+, CD8+ and CD20+ cells, high numbers of CD163+ and HLA-DRA+ cells were detected. These cells were mainly located in regions of tumor necrosis. Increased amounts of CD4+ and CD8+ lymphocytes were present in PFAI+ tumors compared to PFAI- tumors. Deconvolution of the bulk RNA samples based on single-cell RNA sequencing data revealed an enrichment of myeloid cell populations, especially microglia and macrophages. Furthermore, PFAI+ tumors were found to contain significantly higher relative proportions of T-cells compared to PFAI- tumors (median of 3.76% for PFAI+ compared to 0.03% for PFAI-).ConclusionsWe suggest that pediatric posterior fossa A ependymomas can be divided into two groups based on the expression of immune-related genes, in which PFAI+ ependymomas are characterized by higher RNA expression levels of these genes and greater amounts of tumor-infiltrating immune cells. Several techniques showed an enrichment of T-lymphocytes in the PFAI+ ependymomas relative to the PFAI- ependymomas.Disclosure InformationJ. Lammers: None. F. Calkoen: None. M. Kranendonk: None. A. Federico: None. M. Kool: None. L. Kester: None. J. van der Lugt: None.


2021 ◽  
Author(s):  
Xiaofeng Nian ◽  
Li Li ◽  
Xusheng Ma ◽  
Xiurong Li ◽  
Wenhui Li ◽  
...  

Abstract Background: Echinococcus multilocularis (Em) infection and the growth and proliferation of its metacestode within the internal organs of hosts are related to complex host–parasite interactions at the molecular level. Previous studies reported the profiles of long non-coding RNAs (lncRNAs) and mRNAs in Echinococcus granulosus-infected mice or cells, suggesting the potential role of lncRNAs in regulating host-parasite interplay. However, the profiles of lncRNAs and mRNAs of mice in response to Em are poorly understood. Methods: Numerous differentially expressed lncRNAs (DELs) and mRNAs (DEMs) in the mouse liver at eight time points after Em infection were identified by microarray. Functional Annotation of dysregulated DEMs was conducted by gene ontology (GO) classification and the Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. The potential function of DELs was predicted by constructing lncRNA-mRNA co-expression network and Transcription factor (TF)-lncRNA-mRNA Ternary Network. Additionally, qRT-PCR and western blotting were used to validate the upregulated DEMs at 30 days post-infection (dpi), which were enriched in Toll-like and RIG-I-like receptor signaling pathways. Cytokines and chemokines involved in these two pathways were determined by ELISA.Results: Thirty-one DEMs and 68 DELs were found continuously dysregulated. These DEMs were notably enriched in the “antigen processing and presentation,” “Th1 and Th2 cell differentiation” and “Th17 cell differentiation” pathways. The potential function prediction of DELs revealed that most DELs might influence the differentiation of Th17 cell and TGF-β/Smad pathway through trans regulating the SMAD3, STAT1, and early growth response (EGR) genes. Additionally, the validated results by qRT-PCR and western blotting showed that the mRNA expression levels of these genes increased while the corresponding protein expression levels were unaltered except c-Jun amino-terminal kinase (JNK). Regardless, phospho-nuclear factor Kappa B (p-NF-κB) downstream of these two pathways was induced at 15 and 30 dpi, which led to the elevated levels of IL-1 beta and IL-6 in the serum. Conclusion: Our data provide novel clues in understanding the roles of lncRNAs in the host–Em interplay and the influence of Em infection on host innate immunity.


2021 ◽  
Vol 9 (Suppl 3) ◽  
pp. A954-A955
Author(s):  
Jacob Kaufman ◽  
Doug Cress ◽  
Theresa Boyle ◽  
David Carbone ◽  
Neal Ready ◽  
...  

BackgroundLKB1 (STK11) is a commonly disrupted tumor suppressor in NSCLC. Its loss promotes an immune exclusion phenotype with evidence of low expression of interferon stimulated genes (ISG) and decreased microenvironment immune infiltration.1 2 Clinically, LKB1 loss induces primary immunotherapy resistance.3 LKB1 is a master regulator of a complex downstream kinase network and has pleiotropic effects on cell biology. Understanding the heterogeneous phenotypes associated with LKB1 loss and their influence on tumor-immune biology will help define and overcome mechanisms of immunotherapy resistance within this subset of lung cancer.MethodsWe applied multi-omic analyses across multiple lung adenocarcinoma datasets2 4–6 (>1000 tumors) to define transcriptional and genetic features enriched in LKB1-deficient lung cancer. Top scoring phenotypes exhibited heterogeneity across LKB1-loss tumors, and were further interrogated to determine association with increased or decreased markers of immune activity. Further, immune cell-types were estimated by Cibersort to identify effects of LKB1 loss on the immune microenvironment. Key conclusions were confirmed by blinded pathology review.ResultsWe show that LKB1 loss significantly affects differentiation patterns, with enrichment of ASCL1-expressing tumors with putative neuroendocrine differentiation. LKB1-deficient neuroendocrine tumors had lower expression of Interferon Stimulated Genes (ISG), MHC1 and MHC2 components, and immune infiltration compared to LKB1-WT and non-neuroendocrine LKB1-deficient tumors (figure 1).The abundances of 22 immune cell types assessed by Cibersort were compared between LKB1-deficient and LKB1-WT tumors. We observe skewing of immune microenvironmental composition by LKB1 loss, with lower abundance of dendritic cells, monocytes, and macrophages, and increased levels of neutrophils and plasma cells (table 1). These trends were most pronounced among tumors with neuroendocrine differentiation, and were concordant across three independent datasets. In a confirmatory subset of 20 tumors, plasma cell abundance was assessed by a blinded pathologist. Pathologist assessment was 100% concordant with Cibersort prediction, and association with LKB1 loss was confirmed (P=0.001).Abstract 909 Figure 1Immune-associated Gene Expression Profiles Affected by Neuroendocrine Differentiation within LKB1-Deficient Lung Adenocarcinomas. Gene expression profiles corresponding to five immune-associated phenotypes are shown with bars indicating average GEP scores for tumors grouped according to LKB1 and neuroendocrine status as indicated. P-values represent results from Student’s T-test between groups as indicated.Abstract 909 Table 1LKB1 Loss Affects Composition of Immune Microenvironment. Values indicate log10 P-values comparing LKB1-loss to LKB1-WT tumors. Positive (red) indicates increased abundance in LKB1 loss. Negative (blue) indicates decreased abundance.ConclusionsWe conclude that tumor differentiation patterns strongly influence the immune microenvironment and immune exclusion characteristics of LKB1-deficient tumors. Neuroendocrine differentiation is associated with the strongest immune exclusion characteristics and should be evaluated clinically for evidence of immunotherapy resistance. A novel observation of increased plasma cell abundance is observed across multiple datasets and confirmed by pathology. Causal mechanisms linking differentiation status to immune activity is not well understood, and the functional role of plasma cells in the immune biology of LKB1-deficient tumors is undefined. These questions warrant further study to inform precision immuno-oncology treatments for these patients.AcknowledgementsThis work was funded by SITC AZ Immunotherapy in Lung Cancer grant (SPS256666) and DOD Lung Cancer Research Program Concept Award (LC180633).ReferencesSkoulidis F, Byers LA, Diao L, et al. Co-occurring genomic alterations define major subsets of KRAS-mutant lung adenocarcinoma with distinct biology, immune profiles, and therapeutic vulnerabilities. Cancer Discov 2015;5:860–77.Schabath MB, Welsh EA, Fulp WJ, et al. Differential association of STK11 and TP53 with KRAS mutation-associated gene expression, proliferation and immune surveillance in lung adenocarcinoma. Oncogene 2016;35:3209–16.Skoulidis F, Goldberg ME, Greenawalt DM, et al. STK11/LKB1 mutations and PD-1 inhibitor resistance in KRAS-mutant lung adenocarcinoma. Cancer Discovery 2018;8:822-835.Cancer Genome Atlas Research Network. Comprehensive molecular profiling of lung adenocarcinoma. Nature 2014;511:543–50.Chitale D, Gong Y, Taylor BS, et al. An integrated genomic analysis of lung cancer reveals loss of DUSP4 in EGFR-mutant tumors. Oncogene 2009;28:2773–83.Shedden K, Taylor JM, Enkemann SA, et al. Gene expression-based survival prediction in lung adenocarcinoma: a multi-site, blinded validation study. Nat Med 2008;14:822–7.


2020 ◽  
Vol 40 (11) ◽  
Author(s):  
Xiaofei Wang ◽  
Jie Qiao ◽  
Rongqi Wang

Abstract The present study aimed to construct a novel signature for indicating the prognostic outcomes of hepatocellular carcinoma (HCC). Gene expression profiles were downloaded from Gene Expression Omnibus (GEO), The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) databases. The prognosis-related genes with differential expression were identified with weighted gene co-expression network analysis (WGCNA), univariate analysis, the least absolute shrinkage and selection operator (LASSO). With the stepwise regression analysis, a risk score was constructed based on the expression levels of five genes: Risk score = (−0.7736* CCNB2) + (1.0083* DYNC1LI1) + (−0.6755* KIF11) + (0.9588* SPC25) + (1.5237* KIF18A), which can be applied as a signature for predicting the prognosis of HCC patients. The prediction capacity of the risk score for overall survival was validated with both TCGA and ICGC cohorts. The 1-, 3- and 5-year ROC curves were plotted, in which the AUC was 0.842, 0.726 and 0.699 in TCGA cohort and 0.734, 0.691 and 0.700 in ICGC cohort, respectively. Moreover, the expression levels of the five genes were determined in clinical tumor and normal specimens with immunohistochemistry. The novel signature has exhibited good prediction efficacy for the overall survival of HCC patients.


2020 ◽  
Author(s):  
Rui Zhang ◽  
Chen Chen ◽  
Qi Li ◽  
Jialu Fu ◽  
Dong Zhang ◽  
...  

Abstract Background: Immune-related genes (IRGs) play a crucial role in the initiation and progression of cholangiocarcinoma (CCA). However, immune signatures have rarely been used to predict prognosis of CCA. The aim of this study was to construct a novel model for CCA to predict survival based on IRGs expression data.Methods: The gene expression profiles and clinical data of CCA patients from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database were integrated to establish and validate prognostic IRG signatures. Differentially expressed immune-related genes were screened. Univariate and multivariate Cox analysis were performed to identify prognostic IRGs, and the risk model that predicts outcomes was constructed. Furthermore, receiver operating characteristic (ROC) and Kaplan-Meier curve were plotted to examine predictive accuracy of the model, and a nomogram was constructed based on IRGs signature, combining with other clinical characteristics. Finally, CIBERSORT was used to analyze the association of immune cells infiltration with risk score.Results: We identified that 223 IRGs were significantly dysregulated in patients with CCA, among which five IRGs (AVPR1B, CST4, TDGF1, RAET1E and IL9R) were identified as robust indicators for overall survival (OS), and a prognostic model was built based on the IRGs signature. Meanwhile, patients with high risk had worse OS in training and validation cohort, and the area under the ROC was 0.898 and 0.846, respectively. Nomogram demonstrated that immune risk score contributed much more points than other clinicopathological variables, with a C-index of 0.819 (95% CI, 0.727-0.911). Finally, we found that IRGs signature was positively correlated with the proportion of CD8+ T cells, neurophils and T gamma delta, while negatively with that of CD4+ memory resting T cells.Conclusions: We established and validated an effective five IRGs-based prediction model for CCA, which could accurately classify patients into groups with low and high risk of poor prognosis.


2021 ◽  
Vol 23 (1) ◽  
Author(s):  
Matthew Wright ◽  
Mette K. Smed ◽  
J. Lee Nelson ◽  
Jørn Olsen ◽  
Merete L. Hetland ◽  
...  

Abstract Background To evaluate our hypotheses that, when rheumatoid arthritis (RA) flares postpartum, gene expression patterns are altered compared to (a) healthy women, (b) RA women whose disease activity is low or in remission postpartum, and (c) pre-pregnancy expression profiles. Methods Twelve women with RA and five healthy women were included in this pilot study. RA disease activity and postpartum flare were assessed using the Clinical Disease Activity Index (CDAI). Total RNA from frozen whole blood was used for RNA sequencing. Differential gene expression within the same women (within-group) over time, i.e., postpartum vs. third trimester (T3) or pre-pregnancy (T0), were examined, using a significance threshold of q < 0.05 and fold-change ≥ 2. Results Nine of the women with RA experienced a flare postpartum (RAFlare), while three had low disease activity or were in remission (RANoFlare) during that time frame. Numerous immune-related genes were differentially expressed postpartum (vs. T3) during a flare. Fold-changes in expression from T3 to postpartum were mostly comparable between the RAFlare and healthy groups. At 3 months postpartum, compared to healthy women, several genes were significantly differentially expressed only among the RAFlare women, and not among the RANoFlare women. Some of these genes were among those whose “normal” expression was significantly modulated postpartum, and the postpartum expression patterns were significantly altered during the RA flare. There were also some genes that were significantly differentially expressed in RAFlare compared to both healthy and RANoFlare women, even though their expression was not significantly modulated postpartum. Furthermore, while postpartum expression profiles were similar to those at pre-pregnancy among healthy women, significant differences were found between those time points among the RAFlare women. Conclusions The large majority of gene expression changes between T3 and 3 months postpartum among RA women who flared postpartum reflected normal postpartum changes also seen among healthy women. Nonetheless, during a postpartum flare, a set of immune-related genes showed dysregulated expression compared to healthy women and women with RA whose disease activity was low or in remission during the same time frame, while other genes demonstrated significant differences in expression compared to RA pre-pregnancy levels.


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