scholarly journals Mouse Breast Carcinoma Monocytic/Macrophagic Myeloid-Derived Suppressor Cell Infiltration as a Consequence of Endothelial Dysfunction in Shb-Deficient Endothelial Cells Increases Tumor Lung Metastasis

2021 ◽  
Vol 22 (21) ◽  
pp. 11478
Author(s):  
Qi He ◽  
Maria Jamalpour ◽  
Eric Bergquist ◽  
Robin L. Anderson ◽  
Karin Gustafsson ◽  
...  

Metastasis reflects both the inherent properties of tumor cells and the response of the stroma to the presence of the tumor. Vascular barrier properties, either due to endothelial cell (EC) or pericyte function, play an important role in metastasis in addition to the contribution of the immune system. The Shb gene encodes the Src homology-2 domain protein B that operates downstream of tyrosine kinases in both vascular and immune cells. We have investigated E0771.lmb breast carcinoma metastasis in mice with conditional deletion of the Shb gene using the Cdh5-CreERt2 transgene, resulting in inactivation of the Shb-gene in EC and some hematopoietic cell populations. Lung metastasis from orthotopic tumors, tumor vascular and immune cell characteristics, and immune cell gene expression profiles were determined. We found no increase in vascular leakage that could explain the observed increase in metastasis upon the loss of Shb expression. Instead, Shb deficiency in EC promoted the recruitment of monocytic/macrophagic myeloid-derived suppressor cells (mMDSC), an immune cell type that confers a suppressive immune response, thus enhancing lung metastasis. An MDSC-promoting cytokine/chemokine profile was simultaneously observed in tumors grown in mice with EC-specific Shb deficiency, providing an explanation for the expanded mMDSC population. The results demonstrate an intricate interplay between tumor EC and immune cells that pivots between pro-tumoral and anti-tumoral properties, depending on relevant genetic and/or environmental factors operating in the microenvironment.

2015 ◽  
Vol 5 (1) ◽  
Author(s):  
Pingzhang Wang ◽  
Yehong Yang ◽  
Wenling Han ◽  
Dalong Ma

Abstract Gene expression is highly dynamic and plastic. We present a new immunological database, ImmuSort. Unlike other gene expression databases, ImmuSort provides a convenient way to view global differential gene expression data across thousands of experimental conditions in immune cells. It enables electronic sorting, which is a bioinformatics process to retrieve cell states associated with specific experimental conditions that are mainly based on gene expression intensity. A comparison of gene expression profiles reveals other applications, such as the evaluation of immune cell biomarkers and cell subsets, identification of cell specific and/or disease-associated genes or transcripts, comparison of gene expression in different transcript variants and probe set quality evaluation. A plasticity score is introduced to measure gene plasticity. Average rank and marker evaluation scores are used to evaluate biomarkers. The current version includes 31 human and 17 mouse immune cell groups, comprising 10,422 and 3,929 microarrays derived from public databases, respectively. A total of 20,283 human and 20,963 mouse genes are available to query in the database. Examples show the distinct advantages of the database. The database URL is http://immusort.bjmu.edu.cn/.


2019 ◽  
Vol 12 (S8) ◽  
Author(s):  
Yen-Jung Chiu ◽  
Yi-Hsuan Hsieh ◽  
Yen-Hua Huang

Abstract Background To facilitate the investigation of the pathogenic roles played by various immune cells in complex tissues such as tumors, a few computational methods for deconvoluting bulk gene expression profiles to predict cell composition have been created. However, available methods were usually developed along with a set of reference gene expression profiles consisting of imbalanced replicates across different cell types. Therefore, the objective of this study was to create a new deconvolution method equipped with a new set of reference gene expression profiles that incorporate more microarray replicates of the immune cells that have been frequently implicated in the poor prognosis of cancers, such as T helper cells, regulatory T cells and macrophage M1/M2 cells. Methods Our deconvolution method was developed by choosing ε-support vector regression (ε-SVR) as the core algorithm assigned with a loss function subject to the L1-norm penalty. To construct the reference gene expression signature matrix for regression, a subset of differentially expressed genes were chosen from 148 microarray-based gene expression profiles for 9 types of immune cells by using ANOVA and minimizing condition number. Agreement analyses including mean absolute percentage errors and Bland-Altman plots were carried out to compare the performances of our method and CIBERSORT. Results In silico cell mixtures, simulated bulk tissues, and real human samples with known immune-cell fractions were used as the test datasets for benchmarking. Our method outperformed CIBERSORT in the benchmarks using in silico breast tissue-immune cell mixtures in the proportions of 30:70 and 50:50, and in the benchmark using 164 human PBMC samples. Our results suggest that the performance of our method was at least comparable to that of a state-of-the-art tool, CIBERSORT. Conclusions We developed a new cell composition deconvolution method and the implementation was entirely based on the publicly available R and Python packages. In addition, we compiled a new set of reference gene expression profiles, which might allow for a more robust prediction of the immune cell fractions from the expression profiles of cell mixtures. The source code of our method could be downloaded from https://github.com/holiday01/deconvolution-to-estimate-immune-cell-subsets.


2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Xizhe Sun ◽  
Lijia Zhang ◽  
Songjiang Liu

Background. Being potential field of research for tumor immunological therapy, the head and neck squamous cell carcinoma (HNSCC) is one of most discussed types of tumor. Recently, some clinical trials have also used immunological therapy and demonstrated a subset of HNSCC patients who have shown a clear longer survival time. Objective. To conduct further studies and deeper research in the immunological oncology of HNSCC, a more detailed description and comprehending of the complicated landscape of immune infiltrative may be required. Methods. Firstly, we have described the fraction of different infiltrating immune cells in the HNSCC tumor and then compared it to the normal tissue, and secondly, we have explored the clinical implications of various infiltrated immune cell fractions meticulously. The gene expression profiles of HNSCC tissue were obtained from databases of TCGA and GEO and utilized the deconvolution algorithm (CIBERSORT) to presume the fractions of 22 several immune sensitive cells. Results. Our results indicated that the immune infiltrating cell fractions were considerably different between HNSCC tumor tissue and paired normal tissue, but at the same time, we found a potential internal correlation among the immune cells and also showed the association between immune infiltrating cells and their clinical characteristics. It is worth noting that the resting dendritic cells and M1 macrophages were linked with a favorable prognosis, while the CD4+ T cells with a poorer outcome. Conclusion. Fractions of immune cell percentage were also associated with tumors’ pathological grade, age, and TNM stage.


2021 ◽  
Vol 49 (5) ◽  
pp. 030006052110162
Author(s):  
Lin Peng ◽  
Wenwu He ◽  
Feng Ye ◽  
Yane Song ◽  
Xinying Shi ◽  
...  

Objective To identify biomarkers related to esophageal squamous cell carcinoma (ESCC) prognosis by analyzing genetic variations and the infiltration levels of tumor-infiltrating lymphocytes (TILs) in patients. Methods The clinical features of 61 patients with ESCC were collected. DNA panel sequencing was performed to screen differentially expressed genes (DEGs). Transcriptome sequencing was performed to identify gene expression profiles, and subsequent enrichment analysis of DEGs was conducted using Metascape. Results We identified 488 DEGs between patients with ESCC with distinct prognoses that were mainly enriched in the human immune response, fibrinogen complex, and protein activation cascade pathways. Among patients with ESCC treated with postoperative chemotherapy, those with a high infiltration level of myeloid-derived suppressor cells (MDSCs) had longer overall survival (OS), and OS was positively correlated with the infiltration level of T helper type 2 (Th2) cells among patients treated without chemotherapy after surgery. Additionally, in the case of MDSCs >0.7059 or Th2 cells <0.6290, patients receiving postoperative chemotherapy had a longer OS than those treated without chemotherapy following surgery. Conclusion The level of MDSCs or Th2 cells can be used as a biomarker for assessing the prognosis of patients with ESCC treated with or without postoperative chemotherapy, respectively.


2021 ◽  
Vol 12 ◽  
Author(s):  
Binghao Zhao ◽  
Yuekun Wang ◽  
Yaning Wang ◽  
Congxin Dai ◽  
Yu Wang ◽  
...  

The immunosuppressive mechanisms of the surrounding microenvironment and distinct immunogenomic features in glioblastoma (GBM) have not been elucidated to date. To fill this gap, useful data were extracted from The Cancer Genome Atlas (TCGA), the Chinese Glioma Genome Atlas (CGGA), GSE16011, GSE43378, GSE23806, and GSE12907. With the ssGSEA method and the ESTIMATE and CIBERSORT algorithms, four microenvironmental signatures were used to identify glioma microenvironment genes, and the samples were reasonably classified into three immune phenotypes. The molecular and clinical features of these phenotypes were characterized via key gene set expression, tumor mutation burden, fraction of immune cell infiltration, and functional enrichment. Exhausted CD8+ T cell (GET) signature construction with the predictive response to commonly used antitumor drugs and peritumoral edema assisted in further characterizing the immune phenotype features. A total of 2,466 glioma samples with gene expression profiles were enrolled. Tumor purity, ESTIMATE, and immune and stromal scores served as the 4 microenvironment signatures used to classify gliomas into immune-high, immune-middle and immune-low groups, which had distinct immune heterogeneity and clinicopathological characteristics. The immune-H phenotype had higher expression of four immune signatures; however, most checkpoint molecules exhibited poor survival. Enriched pathways among the subtypes were related to immunity. The GET score was similar among the three phenotypes, while immune-L was more sensitive to bortezomib, cisplatin, docetaxel, lapatinib, and rapamycin prescriptions and displayed mild peritumor edema. The three novel immune phenotypes with distinct immunogenetic features could have utility for understanding glioma microenvironment regulation and determining prognosis. These results contribute to classifying glioma subtypes, remodeling the immunosuppressive microenvironment and informing novel cancer immunotherapy in the era of precision immuno-oncology.


2021 ◽  
Vol 9 (Suppl 1) ◽  
pp. A12.1-A12
Author(s):  
Y Arjmand Abbassi ◽  
N Fang ◽  
W Zhu ◽  
Y Zhou ◽  
Y Chen ◽  
...  

Recent advances of high-throughput single cell sequencing technologies have greatly improved our understanding of the complex biological systems. Heterogeneous samples such as tumor tissues commonly harbor cancer cell-specific genetic variants and gene expression profiles, both of which have been shown to be related to the mechanisms of disease development, progression, and responses to treatment. Furthermore, stromal and immune cells within tumor microenvironment interact with cancer cells to play important roles in tumor responses to systematic therapy such as immunotherapy or cell therapy. However, most current high-throughput single cell sequencing methods detect only gene expression levels or epigenetics events such as chromatin conformation. The information on important genetic variants including mutation or fusion is not captured. To better understand the mechanisms of tumor responses to systematic therapy, it is essential to decipher the connection between genotype and gene expression patterns of both tumor cells and cells in the tumor microenvironment. We developed FocuSCOPE, a high-throughput multi-omics sequencing solution that can detect both genetic variants and transcriptome from same single cells. FocuSCOPE has been used to successfully perform single cell analysis of both gene expression profiles and point mutations, fusion genes, or intracellular viral sequences from thousands of cells simultaneously, delivering comprehensive insights of tumor and immune cells in tumor microenvironment at single cell resolution.Disclosure InformationY. Arjmand Abbassi: None. N. Fang: None. W. Zhu: None. Y. Zhou: None. Y. Chen: None. U. Deutsch: None.


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.


2021 ◽  
Vol 12 ◽  
Author(s):  
Shenglan Cai ◽  
Xingwang Hu ◽  
Ruochan Chen ◽  
Yiya Zhang

BackgroundEnhancer RNAs (eRNAs) are intergenic long non-coding RNAs (lncRNAs) that participate in the progression of malignancies by targeting tumor-related genes and immune checkpoints. However, the potential role of eRNAs in hepatocellular carcinoma (HCC) is unclear. In this study, we aimed to construct an immune-related eRNA prognostic model that could be used to prospectively assess the prognosis of patients with HCC.MethodsGene expression profiles of patients with HCC were downloaded from The Cancer Genome Atlas (TCGA). The eRNAs co-expressed from immune genes were identified as immune-related eRNAs. Cox regression analyses were applied in a training cohort to construct an immune-related eRNA signature (IReRS), that was subsequently used to analyze a testing cohort and combination of the two cohorts. Kaplan-Meier and receiver operating characteristic (ROC) curves were used to validate the predictive effect in the three cohorts. Gene Set Enrishment Analysis (GSEA) computation was used to identify an IReRS-related signaling pathway. A web-based cell type identification by estimating relative subsets of RNA transcripts (CIBERSORT) computation was used to evaluate the relationship between the IReRS and infiltrating immune cells.ResultsA total of sixty-four immune-related eRNAs (IReRNAs) was identified in HCC, and 14 IReRNAs were associated with overall survival (OS). Five IReRNAs were used for constructing an immune-related eRNA signature (IReRS), which was shown to correlate with poor survival and to be an independent prognostic biomarker for HCC. The GSEA results showed that the IReRS was correlated to cancer-related and immune-related pathways. Moreover, we found that IReRS was correlated to infiltrating immune cells, including CD8+ T cells and M0 macrophages. Finally, differential expressions of the five risk IReRNAs in tumor tissues vs. adjacent normal tissues and their prognostic values were verified, in which the AL445524.1 may function as an oncogene that affects prognosis partly by regulating CD4-CLTA4 related genes.ConclusionOur results suggest that the IReRS could serve as a biomarker for predicting prognosis in patients with HCC. Additionally, it may be correlated to the tumor immune microenvironment and could also be used as a biomarker in immunotherapy for HCC.


2021 ◽  
Vol 12 ◽  
Author(s):  
Deepali K. Bhat ◽  
Purevdorj B. Olkhanud ◽  
Arunakumar Gangaplara ◽  
Fayaz Seifuddin ◽  
Mehdi Pirooznia ◽  
...  

Haploidentical hematopoietic stem cell transplantation (haplo-HSCT) is a widely available curative option for patients with sickle cell disease (SCD). Our original non-myeloablative haplo-HSCT trial employing post-transplant (PT) cyclophosphamide had a low incidence of GVHD but had high rejection rates. Here, we aimed to evaluate immune reconstitution following haplo-HSCT and identify cytokines and cells associated with graft rejection/engraftment. 50 cytokines and 10 immune cell subsets were screened using multiplex-ELISA and flow cytometry, respectively, at baseline and PT-Days 30, 60, 100, and 180. We observed the most significant differences in cytokine levels between the engrafted and rejected groups at PT-Day 60, corresponding with clinical findings of secondary graft rejection. Of the 44 cytokines evaluated, plasma concentrations of 19 cytokines were different between the two groups at PT-Day 60. Factor analysis suggested two independent factors. The first factor (IL-17A, IL-10, IL-7, G-CSF, IL-2, MIP-1a, VEGF, and TGFb1 contributed significantly) was strongly associated with engraftment with OR = 2.7 (95%CI of 1.4 to 5.4), whereas the second factor (GROa and IL-18 contributed significantly) was not significantly associated with engraftment. Sufficient donor myeloid chimerism (DMC) is critical for the success of HSCT; here, we evaluated immune cells among high (H) DMC (DMC≥20%) and low (L) DMC (DMC&lt;20%) groups along with engrafted and rejected groups. We found that early myeloid-derived suppressor cell (eMDSC) frequencies were elevated in engrafted patients and patients with HDMC at PT-Day 30 (P&lt; 0.04 &amp; P&lt; 0.003, respectively). 9 of 20 patients were evaluated for the source of eMDSCs. The HDMC group had high mixed chimeric eMDSCs as compared to the LDMC group (P&lt; 0.00001). We found a positive correlation between the frequencies of eMDSCs and Tregs at PT-Day 100 (r=0.72, P &lt;0.0007); eMDSCs at BSL and Tregs at PT-Day 100 (r=0.63, P &lt;0.004). Of 10 immune regulatory cells and 50 cytokines, we observed mixed chimeric eMDSCs and IL-17A, IL-10, IL-7, G-CSF, IL-2, MIP-1a, VEGF, TGFb1 as potential hits which could serve as prognostic markers in predicting allograft outcome towards engraftment following haploidentical HSCT employing post-transplant cyclophosphamide. The current findings need to be replicated and further explored in a larger cohort.


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