CSIG-13. A DYNAMIC CAUSAL MODEL OF GLIOBLASTOMA STEM CELL SIGNALING PREDICTS EFFECTS OF KINASE INHIBITORS

2021 ◽  
Vol 23 (Supplement_6) ◽  
pp. vi35-vi36
Author(s):  
Emilee Holzapple ◽  
Natasa Miskov-Zivanov ◽  
Brent Cochran

Abstract Glioblastomas and glioblastoma stem cells are heterogeneous with respect to mutations, gene expression, and response to drugs. To make predictive responses of individual GBM stem cell lines to kinase inhibitors, we have constructed a causal model of glioblastoma stem cell signaling. The core model was built starting from pathways identified from TCGA mutation data with the addition of the Jak/STAT, Hedgehog, and Notch pathways. Elements and relations between them were validated and extended using the PCNet interaction database and the INDRA database which includes machine read extractions from the biomedical literature. The result is a high confidence executable model consisting of 209 elements (proteins, genes, RNAs) and 370 regulatory logic rules between the elements. Stochastic simulations of the model provide dynamic (quantile) changes in time and responses to perturbations. The output simulates activity of individual nodes as well as cell cycle progression, apoptosis, and differentiation. To simulate the responses of individual cell lines to kinase inhibitors, the model was initialized using DNA sequencing data, RNA-seq, and reverse phase protein array (RPPA) data from each cell line. Comparing the results of the simulations to the drug responses of 11 different kinase targets in 3 cell lines, the model was 88% accurate in predicting effects on growth and survival. The model was further tested by comparing the effects of Mek inhibition of each of the cell lines in the model to the results observed in the RPPA data which overlap by 127 elements. In this case, there was less than 65% concordance between the model and the data for individual nodes. Discrepancies between the model predictions and the data are being investigated to determine whether the model logic or extent needs to be revised to improve the model. This modeling approach is a step toward developing algorithms for personalized therapeutics for GBM.

2021 ◽  
Vol 3 (Supplement_2) ◽  
pp. ii5-ii5
Author(s):  
Emilee Holtzapple ◽  
Natasa Miskov-Zivanov ◽  
Brent Cochran

Abstract Glioblastomas and glioblastoma stem cells are heterogeneous with respect to mutations, gene expression, and response to drugs. To make predictive responses of individual GBM stem cell lines to drugs, we have constructed a causal model of glioblastoma stem cell signaling. The core model was built starting from pathways identified from TCGA mutation data with the addition of the Jak/STAT, Hedgehog, and Notch pathways. Elements and relations between them were validated and extended using the PCNet interaction database and the INDRA database which includes machine read extractions from the biomedical literature. The result is a high confidence executable model consisting of 209 element and 370 rules of interaction between the elements. Stochastic simulations of the model provide dynamic (quantile) changes in time and responses to perturbations. The output provides activity of individual nodes as well as a cellular output state of cell cycle progression, apoptosis, or differentiation. To simulate the responses of individual cell lines to kinase inhibitors, the model was initialized using DNA sequencing data, RNA-seq, and reverse phase protein array (RPPA) data from each cell line. Comparing the results of the simulations to the drug responses of 11 different kinase targets, the model was 88% accurate in predicting effects on growth and survival. The model was further tested by comparing the effects of Mek inhibition of each of the cell lines in model to the results observed in the RPPA data which overlap by 127 elements. In this case, there was 62% concordance between the model and data when binned into quintiles. Discrepancies between the model predictions and the data are being investigated to determine whether the model logic or extent needs to be revised to improve the model. This modeling approach is a step toward developing algorithms for personalized therapeutics for GBM based on multi-omics data.


2018 ◽  
Vol 20 (suppl_6) ◽  
pp. vi43-vi43
Author(s):  
Elise Fernandez ◽  
Anne Steino ◽  
Glenn Lesser ◽  
Jeffrey Bacha ◽  
Dennis Brown ◽  
...  

2018 ◽  
Vol 20 (suppl_6) ◽  
pp. vi45-vi45
Author(s):  
Emilee Holtzapple ◽  
Natasa Miskov-Zivanov ◽  
Kenneth Jahan ◽  
Yahan Zhang ◽  
Steven Young ◽  
...  

2021 ◽  
Vol 23 (Supplement_2) ◽  
pp. ii36-ii36
Author(s):  
S G Schwab ◽  
K Sarnow ◽  
F A Thorsen ◽  
J A Hossain ◽  
R Goldbrunner ◽  
...  

Abstract BACKGROUND Despite aggressive tumor behavior, extracranial metastases rarely develop in glioblastoma (GBM) patients. Two potential explanations have been suggested: 1) The blood-brain-barrier functions as a physical barrier that prevents the dissemination of GBM cells out of the central nervous system (CNS) or 2) that extracranial metastasis do occur, but the patients die before extracranial metastases manifest themselves. The first theory has been questioned based on the fact that circulating tumor cells (CTC) were found in blood samples of GBM patients without systemic metastases. To date it has not been proven if CTCs are able to reenter the brain and to what extent they are able to form systemic extracranial metastatic lesions. Therefore, the current study aimed at analyzing the dissemination patterns and the underlying mechanisms associated with the ability of GBM CTCs to form extracranial metastases. MATERIAL AND METHODS Five highly characterized human GBM stem cell (GSC) lines (P3, BG5, BG7, GG6, GG16), displaying GBM CNV patterns, were intracranially implanted in a first cohort, then transduced with a lentiviral Firefly Luciferase-eGFP vector and injected into the left cardiac ventricle of NOD/SCID mice in a second cohort. Mice were observed closely and tumor burden was assessed using in vivo as well as ex vivo bioluminescence imaging, MRI and PET. Mice were euthanized when the objective endpoint criteria (tumor burden) was met, then organs were harvested and fixed for further analysis. RESULTS First, a detailed characterization of the GSC line invasion patterns were assessed when grown as orthotopic xenografts in vivo dividing them into three categories: 1) Highly invasive without apparent angiogenesis (BG5) 2) Invasive with perivascular infiltration and angiogenesis (P3, BG7 and GG16) and 3) Angiogenic and highly circumscribed (GG6). Following intracardial injection, (7 out of 8) P3 animals developed extracranial and intracranial tumors with a distinctive pattern. Brain, adrenal gland, ovary and liver were amongst the organs most susceptible for tumor growth in the P3 group. For the BG5 and BG7 cell lines, no metastases were observed whereas only 1 animal out of 10 developed metastases in both groups GG16 and GG6. CONCLUSION Only one out of 5 GSC lines exhibited a strong metastatic potential when injected into the left cardiac ventricle. Compared to other tumors which exhibit a strong metastatic potential from the circulation, GSC lines do only to a very limited extent show this potential reflecting observations made in the clinic.


Circulation ◽  
2018 ◽  
Vol 138 (Suppl_1) ◽  
Author(s):  
Matthew C White ◽  
Praful Aggarwal ◽  
Andrea Matter ◽  
Amy Turner ◽  
William B Mattes ◽  
...  

Introduction: Human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) provide unprecedented opportunities for novel investigations into the impact of individual heterogeneity on drug response. Cardio-oncology is a field of growing clinical importance due to the significant, but often sporadic, incidence of cardiotoxicity among cancer patients, including those receiving targeted therapeutics such as kinase inhibitors (KIs). Current commercially-available hiPSC-CMs are typically derived from single donors, and thus do not capture the inherent heterogeneity of patient populations. Hypothesis: We hypothesized that hiPSC-CMs derived from different individuals would display heterogeneous sensitivities to KIs. Methods: We tested iPSC-CMs from six individual participants as part of the NHLBI HyperGEN cohort. Cells were plated on 96-well ePlates (ACEA Biosciences, San Diego, CA) per manufacturer’s instructions and allowed to mature for 10-14 days prior to use. Four KIs were tested (sunitinib, vandetanib, nilotinib, and gefitinib) at concentrations ranging from Cmax to 30-fold Cmax. Toxicity was assessed using non-invasive impedance-based endpoints (beating rate, beat amplitude, and cell index) and ATP levels (Promega, Madison, WI). Results: We observed differences in baseline beating rates (BRs) among the hiPSC-CMs despite similar morphology and cardiac troponin expression levels. Following drug exposure, cell-line and drug- dependent differences in BR and cell index/viability (CI) became apparent. For example, the relatively non-cardiotoxic KI gefitinib produced few significant changes in BR or CI across all 6 cell lines, whereas KIs with black-box warnings for cardiotoxicity severely impacted these endpoints. For both vandetanib and nilotinib, statistically significant differences (p ≤ 0.05) in BR were observed between multiple cell lines at 24 hours post-exposure. Furthermore, nilotinib induced significant differences (p ≤ 0.05) in CI between multiple cell lines after 24 hours. Conclusions: Taken together, these results strongly suggest that inter-individual differences impact hiPSC-CM cardiotoxicity assessments, and support the need to test multiple cell lines during in vitro toxicity screens.


2021 ◽  
Author(s):  
Attila Gabor ◽  
Marco Tognetti ◽  
Alice Driessen ◽  
Jovan Tanevski ◽  
Baosen Guo ◽  
...  

AbstractRecent technological developments allow us to measure the status of dozens of proteins in individual cells. This opens the way to understand the heterogeneity of complex multi-signaling networks across cells and cell-types, with important implications to understand and treat diseases such as cancer. These technologies are however limited to proteins for which antibodies are available and are fairly costly, making predictions of new markers and of existing markers under new conditions a valuable alternative. To assess our capacity to make such predictions and boost further methodological development, we organised the Single Cell Signaling in Breast Cancer DREAM challenge. We used a mass cytometry data set, covering 36 markers in over 4,000 conditions totalling 80 million single cells across 67 breast cancer cell lines. Through four increasingly difficult subchallenges, the participants predicted missing markers, new conditions, and the time course response of single cells to stimuli in the presence and absence of kinase inhibitors. The challenge results show that despite the stochastic nature of signal transduction in single cells, the signaling events are tightly controlled and machine learning methods can accurately predict new experimental data.Graphical AbstractKey pointsOver 80 million single-cell multiplexed measurements across 67 cell lines, 54 conditions and 10 time points to benchmark predictive models of single cell signaling73 approaches from 27 teams for predicting response to kinase inhibitors on single cell level, and dynamic response from unperturbed basal omics dataPredictions of single marker models correlate with measurements with a correlation coefficient of 0.76Top models of whole signaling response models perform almost as well as a biological replicateCell-line specific variation in dynamics can be predicted from basal omics


Blood ◽  
2005 ◽  
Vol 106 (11) ◽  
pp. 1712-1712
Author(s):  
Sergey S. Akimov ◽  
Ali Ramezani ◽  
Teresa S. Hawley ◽  
Robert G. Hawley

Abstract Besides progressive telomere shortening, human cells undergo senescence in response to various types of stress. The stress-related signaling pathways triggered converge to varying extents on the p53 and retinoblastoma (Rb) tumor suppressors, and the cyclin-dependent kinase inhibitors p21WAF1/CIP1 and p16INK4a. We therefore attempted to extend the life-span of human CD34+ cord blood (CB) progenitors by ectopically expressing the human papillomavirus type 16 (HPV16) E6 and E7 genes, which accelerate the degradation of p53 and Rb, respectively, separately and in conjunction with the gene encoding the reverse transcriptase catalytic subunit of human telomerase (hTERT). CD34+ CB cells were transduced with VSV-G glycoprotein-pseudotyped self-inactivating lentiviral vectors that express HPV16 E6/E7 or hTERT linked to downstream GFP/YFP reporter genes on bicistronic transcripts. Sorted GFP+ and/or YFP+ CB cells were maintained under serum-free conditions in the presence of stem cell factor (100 ng/ml), Flt3 ligand (100 ng/ml), thrombopoietin (20 ng/ml) plus interleukin-3 (20 ng/ml). In all cases (n = 3), control CD34+ CB cells differentiated into macrophage-like cells and underwent senescence-associated proliferation arrest after ~4 months in culture. Constitutive expression of hTERT did not increase CB cell replicative capacity in repeated attempts (n = 3), and macrophage-like cells were also the predominant cell type that accumulated in these cultures. In contrast, CB cells constitutively expressing HPV16 E6/E7 alone (n = 2) or in concert with hTERT (n = 5) continued to proliferate beyond 4 months, eventually giving rise to permanent (> 2 years) cell lines with a CD45+CD34−CD44+CD235a+CD71+ CD203+CD33+CD13+ myeloerythroid/mast cell progenitor phenotype. Interestingly, two CB cell lines coexpressing E6/E7 plus hTERT were also positive for the CD133 hematopoietic stem/progenitor cell antigen. When the immortalized CB cells were cultured in the presence of erythropoietin, slight up-regulation of the CD36 erythroid marker was observed. Moreover, when selected CB cells were subjected to a myeloid differentiation regimen, up to 90% of the cells acquired the ability to adhere to fibronectin in the best example, of which ~30% were capable of superoxide-dependent nitroblue tetrazolium reduction reflective of terminal monocytic differentiation. Notably, CB cell cultures expressing only HPV16 E6/E7 went through a crisis period and, when analyzed by spectral karyotyping, G-banding and fluorescence in situ hybridization with centromere-specific probes, were found to be highly aneuploid. By comparison, the CB cell lines obtained by coexpression of HPV16 E6/E7 plus hTERT exhibited near diploid karyotypes with minimal chromosomal aberrations, concomitant with stabilization of telomere length. Upon injection of the two CD133+ E6/E7 plus hTERT-expressing CB cell lines subcutaneously (5 x 106 cells) or intravenously (1 x 107 cells) into sublethally-irradiated (250 cGy) NOD/SCID mice, no tumors developed after 7 months of observation (n = 11), with tumorigenic conversion requiring cooperative enforced expression of a v-H-ras or BCR-ABL oncogene (n = 12). These findings establish the feasibility of bypassing senescence in human hematopoietic progenitors through genetic engineering, providing proof of principle for gene-based or other approaches that might eventually allow establishment of permanent human hematopoietic stem cell lines.


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