scholarly journals Phenotype stability under dynamic brain-tumor environment stimuli maps glioblastoma progression in patients

2020 ◽  
Vol 6 (22) ◽  
pp. eaaz4125 ◽  
Author(s):  
Vinodh N. Rajapakse ◽  
Sylvia Herrada ◽  
Orit Lavi
Keyword(s):  
Brain Tumor ◽  
Phenotypic Plasticity ◽  
Patient Survival ◽  
Cell Types ◽  
Patient Data ◽  
Tumor Invasiveness ◽  
Tumor Environment ◽  
Transition Map ◽  
Phenotype Transition

Although tumor invasiveness is known to drive glioblastoma (GBM) recurrence, current approaches to treatment assume a fairly simple GBM phenotype transition map. We provide new analyses to estimate the likelihood of reaching or remaining in a phenotype under dynamic, physiologically likely perturbations of stimuli (“phenotype stability”). We show that higher stability values of the motile phenotype (Go) are associated with reduced patient survival. Moreover, induced motile states are capable of driving GBM recurrence. We found that the Dormancy and Go phenotypes are equally represented in advanced GBM samples, with natural transitioning between the two. Furthermore, Go and Grow phenotype transitions are mostly driven by tumor-brain stimuli. These are difficult to regulate directly, but could be modulated by reprogramming tumor-associated cell types. Our framework provides a foundation for designing targeted perturbations of the tumor-brain environment, by assessing their impact on GBM phenotypic plasticity, and is corroborated by analyses of patient data.

scholarly journals APELA Expression in Glioma, and Its Association with Patient Survival and Tumor Grade

2019 ◽  
Vol 12 (1) ◽  
pp. 45 ◽  
Author(s):  
Debolina Ganguly ◽  
Chun Cai ◽  
Michelle Sims ◽  
Chuan Yang ◽  
Matthew Thomas ◽  
...  
Keyword(s):  
Gene Expression ◽  
Brain Tumor ◽  
Patient Survival ◽  
Receptor Gene ◽  
Embryonic Stem ◽  
Tumor Grade ◽  
Adult Brain ◽  
Tumor Initiating Cells ◽  
Apelin Receptor ◽  
Cell Niche

Glioblastoma (GBM) is the most common and deadliest primary adult brain tumor. Invasion, resistance to therapy, and tumor recurrence in GBM can be attributed in part to brain tumor-initiating cells (BTICs). BTICs isolated from various patient-derived xenografts showed high expression of the poorly characterized Apelin early ligand A (APELA) gene. Although originally considered to be a non-coding gene, the APELA gene encodes a protein that binds to the Apelin receptor and promotes the growth of human embryonic stem cells and the formation of the embryonic vasculature. We found that both APELA mRNA and protein are expressed at high levels in a subset of brain tumor patients, and that APELA is also expressed in putative stem cell niche in GBM tumor tissue. Analysis of APELA and the Apelin receptor gene expression in brain tumor datasets showed that high APELA expression was associated with poor patient survival in both glioma and glioblastoma, and APELA expression correlated with glioma grade. In contrast, gene expression of the Apelin receptor or Apelin was not found to be associated with patient survival, or glioma grade. Consequently, APELA may play an important role in glioblastoma tumorigenesis and may be a future therapeutic target.

scholarly journals Hypoxic Roadmap of Glioblastoma—Learning about Directions and Distances in the Brain Tumor Environment

Cancers ◽  
2020 ◽  
Vol 12 (5) ◽  
pp. 1213 ◽  
Author(s):  
Agnieszka Bronisz ◽  
Elżbieta Salińska ◽  
E. Antonio Chiocca ◽  
Jakub Godlewski
Keyword(s):  
Brain Tumor ◽  
Immune Escape ◽  
Differential Expression Analysis ◽  
Metabolic Stress ◽  
The Cancer Genome Atlas ◽  
Adaptation To Hypoxia ◽  
Sequencing Data ◽  
Immune Therapies ◽  
Tumor Environment ◽  
Cancer Genome Atlas

Malignant brain tumor—glioblastoma is not only difficult to treat but also hard to study and model. One of the reasons for these is their heterogeneity, i.e., individual tumors consisting of cancer cells that are unlike each other. Such diverse cells can thrive due to the simultaneous co-evolution of anatomic niches and adaption into zones with distorted homeostasis of oxygen. It dampens cytotoxic and immune therapies as the response depends on the cellular composition and its adaptation to hypoxia. We explored what transcriptome reposition strategies are used by cells in the different areas of the tumor. We created the hypoxic map by differential expression analysis between hypoxic and cellular features using RNA sequencing data cross-referenced with the tumor’s anatomic features (Ivy Glioblastoma Atlas Project). The molecular functions of genes differentially expressed in the hypoxic regions were analyzed by a systematic review of the gene ontology analysis. To put a hypoxic niche signature into a clinical context, we associated the model with patients’ survival datasets (The Cancer Genome Atlas). The most unique class of genes in the hypoxic area of the tumor was associated with the process of autophagy. Both hypoxic and cellular anatomic features were enriched in immune response genes whose, along with autophagy cluster genes, had the power to predict glioblastoma patient survival. Our analysis revealed that transcriptome responsive to hypoxia predicted worse patients’ outcomes by driving tumor cell adaptation to metabolic stress and immune escape.

scholarly journals Patient Survival Following Malignant Brain Tumor Resection Using A Linked Claims Database

2013 ◽  
Vol 16 (3) ◽  
pp. A130-A131
Author(s):  
M.M. Bonafede ◽  
G.M. Lenhart ◽  
S. Chang
Keyword(s):  
Brain Tumor ◽  
Patient Survival ◽  
Tumor Resection ◽  
Malignant Brain Tumor ◽  
Claims Database ◽  
Brain Tumor Resection

scholarly journals Deconvolution of heterogeneous tumor samples using partial reference signals

2020 ◽  
Vol 16 (11) ◽  
pp. e1008452
Author(s):  
Yufang Qin ◽  
Weiwei Zhang ◽  
Xiaoqiang Sun ◽  
Siwei Nan ◽  
Nana Wei ◽  
...  
Keyword(s):  
Significant Contribution ◽  
Patient Survival ◽  
Expression Profiles ◽  
Cell Types ◽  
Cancer Type ◽  
Deconvolution Method ◽  
Cell Component ◽  
Bulk Data ◽  
Heterogeneous Tumor ◽  
Non Negative Matrix Factorization

Deconvolution of heterogeneous bulk tumor samples into distinct cellular populations is an important yet challenging problem, particularly when only partial references are available. A common approach to dealing with this problem is to deconvolve the mixed signals using available references and leverage the remaining signal as a new cell component. However, as indicated in our simulation, such an approach tends to over-estimate the proportions of known cell types and fails to detect novel cell types. Here, we propose PREDE, a partial reference-based deconvolution method using an iterative non-negative matrix factorization algorithm. Our method is verified to be effective in estimating cell proportions and expression profiles of unknown cell types based on simulated datasets at a variety of parameter settings. Applying our method to TCGA tumor samples, we found that proportions of pure cancer cells better indicate different subtypes of tumor samples. We also detected several cell types for each cancer type whose proportions successfully predicted patient survival. Our method makes a significant contribution to deconvolution of heterogeneous tumor samples and could be widely applied to varieties of high throughput bulk data. PREDE is implemented in R and is freely available from GitHub (https://xiaoqizheng.github.io/PREDE).

scholarly journals Breast tumor IGF-1R regulates cell adhesion and metastasis: Alignment of mouse single cell and human breast cancer transcriptomics

2021 ◽  
Author(s):  
Alison E Obr ◽  
Yung-Jun Chang ◽  
Virginia Ciliento ◽  
Alexander Lemenze ◽  
Krystopher Maingrette ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Tyrosine Kinases ◽  
Immune Cell ◽  
Patient Survival ◽  
Patient Data ◽  
Critical Event ◽  
Breast Cancers ◽  
Human Breast ◽  
Metastatic Phenotype ◽  
Human Patient

The acquisition of a metastatic phenotype is the critical event that determines patient survival from breast cancer. Several receptor tyrosine kinases have functions both in promoting and inhibiting metastasis in breast tumors. Although the insulin-like growth factor 1 receptor (IGF-1R) has been considered a target for inhibition in breast cancer, low levels of IGF-1R expression are associated with worse overall patient survival. To determine how reduced IGF-1R impacts tumor phenotype, we used weighted correlation gene network analysis (WCGNA) of METABRIC patient data and identified gene modules specific to cell cycle, adhesion, and immune cell signaling inversely correlated with IGF-1R expression in human breast cancers. Integration of human patient data with data from mouse tumors revealed similar pathways necessary for promoting metastasis in basal-like tumors with reduced signaling or expression of the IGF-1R. Functional analyses revealed the basis for the enhanced metastatic phenotype including alterations in E- and P-cadherins.

scholarly journals OTME-18. Targeted CRISPR/Cas9 gene-editing regulates the brain tumor environment

2021 ◽  
Vol 3 (Supplement_2) ◽  
pp. ii17-ii17
Author(s):  
Joshua Perez ◽  
Javier Fierro ◽  
Rocio Aguilar ◽  
Huanyu Dou
Keyword(s):  
Brain Tumor ◽  
Gene Editing ◽  
Transfection Efficacy ◽  
Programmed Death ◽  
Tumor Environment ◽  
Human Gbm ◽  
And Migration ◽  
The Brain ◽  
U87 Cells

Abstract Glioblastoma multiform (GBM) is the most common malignant brain tumor. Recent immunotherapy has demonstrated potential to treat GBM. However, the immune suppressive tumor environment in the brain represents a significant barrier for the treatment of GBM. Overexpression of programmed death ligand-1 (PD-L1) in GBM tumor cells and macrophages plays a key role in GBM vitality, proliferation, and migration, while also suppressing the immune system. We developed a CRISPR/Cas9 gene-editing system to delete whole cell PD-L1. Human PD-L1 targeted sgRNA were cloned into CRISPR/Cas9 plasmids with or without an HDR templet. CRISPR/Cas9 were treated to human GBM U87 cells for 15, 30, 60, 120 and 240 minutes. The intracellular concentration of CRISPR/Cas9 exhibited a time-dependent increases. A GFP tagged CRISPR/Cas9 plasmid was developed to test the transfection efficacy. Higher levels of GFP+ U87 cells were observed at day 3. CRISPR/Cas9 showed a greater PD-L1 knockout at day 3. The PD-L1 reduction limited the proliferation of U87 cells. A scratch assay showed that PD-L1 deletion inhibited the migration of U87 cells. An in vitro GBM model was developed by co-cultivation of U87 cells and macrophages. CRISPR/Cas9 treated co-cultures changed the ratios of U87 cells and macrophages and polarized tumor associated macrophages (TAM) from M2 toward M1. CRISPR/Cas9 gene-editing effectively deleted PD-L1 in U87 cells. Successful deletion of PD-L1 prevented U87 cells growth and migration, and altered the TAMs plasticity and the tumor environment.

scholarly journals Development of a Novel Immune Infiltration-Based Gene Signature to Predict Prognosis and Immunotherapy Response of Patients With Cervical Cancer

2021 ◽  
Vol 12 ◽  
Author(s):  
Sihui Yu ◽  
Xi Li ◽  
Jiawen Zhang ◽  
Sufang Wu
Keyword(s):  
Cervical Cancer ◽  
Immune Cell ◽  
Cox Regression ◽  
Patient Survival ◽  
Checkpoint Inhibitors ◽  
Cell Types ◽  
Gene Signature ◽  
The Cancer Genome Atlas ◽  
Cervical Lesions ◽  
Immune Infiltration

Predictive models could indicate the clinical outcome of patients with carcinoma. Cervical cancer is one of the most frequently diagnosed female malignancies. Herein, we proposed an immune infiltration-related gene signature that predicts prognosis of patients with cervical cancer and depicts the immune landscape as well. We utilized the transcriptome data of The Cancer Genome Atlas (TCGA) and estimated the infiltration level of 28 immune cell types. We screened out four immune cell types conducive to patient survival and recognized their shared differentially expressed genes (DEGs). Four core genes (CHIT1, GTSF1L, PLA2G2D, and GNG8) that composed the ultimate signature were identified via univariate and multivariate Cox regression. The optimal model we built up could distinguish patients with cervical cancer into high-score and low-score subgroups. These two subgroups showed disparity in aspects of patient survival, immune infiltration landscape, and response to immune checkpoint inhibitors. Additionally, we found that GTSF1L was decreased gradually along with the severity of cervical lesions, and its potential role in immune contexture and clinical practice were also demonstrated. Our results suggested that the Immunoscore based on four immune-related genes could serve as a supplementary criterion to effectively foresee the survival outcome, tumor infiltration status, and immunotherapy efficacy of cervical cancer patients.

Brain Tumor Invasiveness.

Neurosurgery ◽  
1996 ◽  
Vol 39 (2) ◽  
pp. 417-418
Author(s):  
Kevin D. Judy
Keyword(s):  
Brain Tumor ◽  
Tumor Invasiveness

scholarly journals How are MCPIP1 and cytokines mutually regulated in cancer-related immunity?

2020 ◽  
Vol 11 (12) ◽  
pp. 881-893
Author(s):  
Ruyi Xu ◽  
Yi Li ◽  
Yang Liu ◽  
Jianwei Qu ◽  
Wen Cao ◽  
...  
Keyword(s):  
Interleukin 1 ◽  
Cell Types ◽  
Monocyte Chemoattractant Protein 1 ◽  
Monocyte Chemoattractant ◽  
Monocyte Chemoattractant Protein ◽  
Physiological Processes ◽  
Mutual Regulation ◽  
Clinical Benefits ◽  
Tumor Environment ◽  
Different Levels

AbstractCytokines are secreted by various cell types and act as critical mediators in many physiological processes, including immune response and tumor progression. Cytokines production is precisely and timely regulated by multiple mechanisms at different levels, ranging from transcriptional to post-transcriptional and posttranslational processes. Monocyte chemoattractant protein-1 induced protein 1 (MCPIP1), a potent immunosuppressive protein, was first described as a transcription factor in monocytes treated with monocyte chemoattractant protein-1 (MCP-1) and subsequently found to possess intrinsic RNase and deubiquitinase activities. MCPIP1 tightly regulates cytokines expression via various functions. Furthermore, cytokines such as interleukin 1 beta (IL-1B) and MCP-1 and inflammatory cytokines inducer lipopolysaccharide (LPS) strongly induce MCPIP1 expression. Mutually regulated MCPIP1 and cytokines form a complicated network in the tumor environment. In this review, we summarize how MCPIP1 and cytokines reciprocally interact and elucidate the effect of the network formed by these components in cancer-related immunity with aim of exploring potential clinical benefits of their mutual regulation.

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