bluuebunny/crossref_metadata_2025_split huggingface dataset:
Abstract A47: In silico organoids: A model for deconvolution of microenvironmental and drug effects on tumor growth
Authors: Rejniak Katarzyna A. , Poonja Sharan , Kingsley Jessica , Mathur Shreya , Chamseddine Ibrahim , Karolak Aleksandra , Markov Dmitry A. , McCawley Lisa J. 
Published: June 2020

Abstract
In vivo tumor microenvironments are heterogeneous in their architecture, cellular contents, metabolic landscape, and extracellular matrix (ECM) composition. Moreover, these microenvironments can undergo temporal and spatial changes. This may alter tumor responses to anticancer therapies. To examine the complex and dynamic changes within tumors and in tumor microenvironments, we developed a computational single cell-based model of the three-dimensional multicellular organotypic cultures: Organoid3D. This model was calibrated to experimental data and reproduced growth dynamics and morphologies of four human breast cell lines: a nontumorigenic epithelial MCF-10A, a mildly tumorigenic MCF-10AT1, and metastatic MCF-10CA-1a and MCF-10CA-1d lines grown in various microenvironmental conditions. By explicitly including the fibril structure of the ECM in the model, we examined how ECM properties promote or suppress the growth of in silico tumor organoids. The quantitative integration of experimental data for organoids exposed to different concentrations of doxorubicin allowed us to derive hypotheses on relative importance of microenvironmental factors and chemotherapeutic treatments on organoid growth. Thus, the in silico organoid model interrogated with experimental data provides a tool for fast and broad hypotheses testing and presents an opportunity to explore experimental conditions beyond what is physically feasible in laboratory experiments.
Citation Format: Katarzyna A. Rejniak, Sharan Poonja, Jessica Kingsley, Shreya Mathur, Ibrahim Chamseddine, Aleksandra Karolak, Dmitry A. Markov, Lisa J. McCawley. In silico organoids: A model for deconvolution of microenvironmental and drug effects on tumor growth [abstract]. In: Proceedings of the AACR Special Conference on the Evolving Landscape of Cancer Modeling; 2020 Mar 2-5; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2020;80(11 Suppl):Abstract nr A47.
Abstract A52: Deciphering MET-dependent modulation of global cellular responses to DNA damage by quantitative phosphoproteomics reveals Ser1016 as a novel MET phosphosite that regulates cellular response to irradiation
Authors: Koch Jonas P. , Bensimon Ariel , Roth Selina M. , Medo Matúš , Francica Paola , Orlando Eleonora , Riedo Rahel , Gavini Jacopo , Quintin Aurélie , Glück Astrid A. , Stroka Deborah M. , Blaukat Andree , Aebersold Daniel M. , Zimmer Yitzhak , Aebersold Ruedi , Medová Michaela 
Published: June 2020

Abstract
There is emerging evidence that DNA damage response (DDR) intertwines with signaling pathways downstream of oncogenic receptor tyrosine kinases (RTKs). Two complementary phosphoproteomic approaches revealed global networks and identified and validated core phosphosites that participate in a crosstalk between the MET RTK and the DDR, including a newly discovered phosphosite on MET itself, Ser1016. DNA-PK phosphorylates Ser1016, and this phosphorylation is increased following irradiation. Cell lines as well as animal models expressing Ser1016Ala phosphodeficient receptor exhibit greater sensitivity to irradiation. MET Ser1016Ala mutants fail to undergo proper radiation-induced cell cycle arrest by bypassing the G2 checkpoint with a premature entry into mitosis and abnormal mitotic spindles, leading to a lower proliferation rate of Ser1016-deficient cells. Regulation of MET activity through Ser1016 phosphorylation by a DDR core kinase represents a critical event involved in DNA repair signaling through a growth factor receptor that frequently functions as a tumor driver.
Citation Format: Jonas P. Koch, Ariel Bensimon, Selina M. Roth, Matúš Medo, Paola Francica, Eleonora Orlando, Rahel Riedo, Jacopo Gavini, Aurélie Quintin, Astrid A. Glück, Deborah M. Stroka, Andree Blaukat, Daniel M. Aebersold, Yitzhak Zimmer, Ruedi Aebersold, Michaela Medová. Deciphering MET-dependent modulation of global cellular responses to DNA damage by quantitative phosphoproteomics reveals Ser1016 as a novel MET phosphosite that regulates cellular response to irradiation [abstract]. In: Proceedings of the AACR Special Conference on the Evolving Landscape of Cancer Modeling; 2020 Mar 2-5; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2020;80(11 Suppl):Abstract nr A52.
Abstract B28: Development and validation of a novel organotypic in vitro model of the tumor-lymph-immune interface for predicting immunotherapy resistance
Authors: Zhou Ruolan , Weathered Rachel , Kurtanich Trevin , Mezyk-Kopec Renata , Mansurov Aslan , Hubbell Jeffrey , Swartz Melody A. 
Published: June 2020

Abstract
Tumor-associated lymphatics and their connection to the tumor-draining lymph node (TdLN) play important roles in cancer metastasis as well as in modulating the tumor immune microenvironment. They bathe the TdLN in cytokines, exosomes, antigens, and suppressive factors from the tumor microenvironment (TME) to alter the antitumor immune response. Such interactions are complex and difficult to study in vivo, yet currently they cannot be readily explored in vitro either. To address this need, we developed a novel in vitro model system of the tumor-lympho-immune (TLI) circuit. These in vitro ”avatars,” dubbed TLI-Ivatars, can sustain ex vivo cocultures of tumors and their TdLNs in a parallelized format, within perfused 3D matrices and communicating channels in a flexible manner. The TLI-Ivatar platform has been shown to sustain long-term cultures (&gt; 3 weeks) of a number of tumor cell lines, which form complex architectures reminiscent of actual tumors, as well as of ex vivo tumor tissue. It also supports the function and viability of immune cells (such as T lymphocytes and dendritic cells) and stromal cells (such as lymphatic endothelial cells and fibroblasts). To validate the modeling of the crosstalk between the tumor and TdLN, we demonstrate that TLI-Ivatar can faithfully recapitulate major in vivo immunotherapy responses with the B16 melanoma model, including (i) dampened cytotoxic T-cell function in tumor-conditioned tdLNs, (ii) enhanced tumor invasion to TdLN of lymphangiogenic (and more metastatic) tumors (compared to the TdLN of non-lymphangiogenic tumors), and (iii) immunotherapy potentiation by factors known to enhance immunotherapy efficacy in vivo, such as lymphangiogenic growth factors and matrix-binding immunomodulatory cytokines. Together, these data highlight the potential of TLI-Ivatar for long-term study of the complex tumor-host cell interplay in TME to gain mechanistic insight and pave the way for patient-specific screening of cancer immunotherapy.
Citation Format: Ruolan Zhou, Rachel Weathered, Trevin Kurtanich, Renata Mezyk-Kopec, Aslan Mansurov, Jeffrey Hubbell, Melody A. Swartz. Development and validation of a novel organotypic in vitro model of the tumor-lymph-immune interface for predicting immunotherapy resistance [abstract]. In: Proceedings of the AACR Special Conference on the Evolving Landscape of Cancer Modeling; 2020 Mar 2-5; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2020;80(11 Suppl):Abstract nr B28.
Abstract B31: A preprocessing filter to improve superparamagnetic relaxometry (SPMR)-based early tumor detection
Authors: Baqri Mehdi , Kandala Sri , Fuentes David 
Published: June 2020

Abstract
The early detection of aggressive forms of ovarian cancer before they metastasize is critical for reducing overall mortality from the disease. Superparamagnetic relaxometry (SPMR) is an imaging technique useful for visualizing early-stage tumors with high sensitivity and specificity. It uses superconducting quantum interference devices (SQUIDs) to detect targeted superparamagnetic iron oxide nanoparticles (SPIONs) that visualize tumors ten times smaller than what conventional imaging techniques can. However, the ultra-sensitivity of SQUIDs increases their risk of distortion due to far-field artifacts. Therefore, a preprocessing filter was developed to mitigate far-field, low-frequency disturbances to SQUID signal acquisition. This is based on the hypothesis that correcting SQUID signal acquisition using a magnetometer for far-field detection will increase the accuracy of SPMR for early tumor detection. The hypothesis was tested in three steps. First, it was shown that the magnetometer (MAG) could specifically detect far-field noise and effectively avoid nanoparticle signatures. Second, high- and low-frequency noise was induced to show that far-field artifacts in the MAG signal correlated with distortions in the SQUID channels. Therefore, a processing filter was developed to parse through and parameterize MAG signal extrema to SQUID signal distortions. A series of further optimization steps included anchoring the MAG signal to respective channels, modeling and subtracting the component of structural (environmental) relaxation, and constraining a general subtraction window. Third, success was measured by the image reconstruction accuracy of sources with various nanoparticle concentrations, using the HSPMR dipole-fitting technique. Overall, the MAG-filter increased reconstruction accuracy more effectively with decreasing nanoparticle signal; accuracy increased the most at very low concentrations (~1ug). Therefore, these preliminary data indicate that the MAG-filter increases SPMR sensitivity for low concentrations representative of very small clusters of cells, typical of early disease stages. Future work will further optimize this initial filter to work uniformly and effectively across different nanoparticle concentrations (and tumor sizes) and translate this technology to highly sensitive early and sparse tumor detection.
Note: This abstract was not presented at the conference.
Citation Format: Mehdi Baqri, Sri Kandala, David Fuentes. A preprocessing filter to improve superparamagnetic relaxometry (SPMR)-based early tumor detection [abstract]. In: Proceedings of the AACR Special Conference on the Evolving Landscape of Cancer Modeling; 2020 Mar 2-5; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2020;80(11 Suppl):Abstract nr B31.
Abstract IA01: Modeling and understanding tumor biologic mechanisms
Authors: Boutin Adam , Chen Peiwen , Dey Prasenjit , Hou Pingping , Liao Wen-Ting , Lu Xin , Ying Haoqiang , Zhao Di , DePinho Ronald A. 
Published: June 2020

Abstract
This presentation will highlight our use of mouse models to dissect molecular and cellular interactions in the tumor microenvironment, including (i) the illumination of the role of myeloid cells in driving immune suppression in prostate cancer, and the impact of combined MDSC-targeted and immune checkpoint blockade therapies in the treatment of metastatic castration-resistant prostate cancer; (ii) the generation and analysis of oncogenic Kras in an inducible colorectal cancer mouse model, revealing the role of IRF2 in the recruitment of myeloid cells into the tumor microenvironment and informing patient selection for more effective ICB therapy in CRC; (iii) the concept of “synthetic essentiality” (a means by which to target specific tumor-suppressor gene deficiencies in cancer), exemplified by the identification of the role of CHD1 in modulation of the tumor microenvironment in Pten-deficient prostate cancer; (iv) the discovery of a symbiotic interaction between glioma cell (LOX) and macrophage (SPP1) in PTEN-null glioma, as well as macrophage reprogramming in immune suppression in glioblastoma; and (v) the role of KRAS in cancer metabolism, in particular how the tumor microenvironment may support KRAS-directed cancer cell metabolism and provide a nonautonomous mechanism enabling escape from Kras-dependent tumor growth. These illustrative examples provide translational opportunities to improve cancer patient treatment and survival.
Citation Format: Adam Boutin, Peiwen Chen, Prasenjit Dey, Pingping Hou, Wen-Ting Liao, Xin Lu, Haoqiang Ying, Di Zhao, Ronald A. DePinho. Modeling and understanding tumor biologic mechanisms [abstract]. In: Proceedings of the AACR Special Conference on the Evolving Landscape of Cancer Modeling; 2020 Mar 2-5; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2020;80(11 Suppl):Abstract nr IA01.
Abstract IA09: Tumor organoid cultures as a platform for functional genomics
Authors: Garnett Mathew 
Published: June 2020

Abstract
In an era of genomics-guided precision medicine, there is an increasing need for models that reflect the hallmarks of cancer and the molecular diversity of patient tumors. New cell culturing methods are transforming our ability to derive cell models from healthy and diseased tissues, with increased success rates, and linked to patient genomic and clinical data. I will update on our efforts as part of the Human Cancer Models Initiative (HCMI) to create a new biobank of molecularly annotated tumor organoids as a community resource. Furthermore, I will present how we are beginning to use these organoid cultures for chemical and genetic screens to identify new molecular targets and biomarkers of therapy response. These early studies are laying the foundation for a next-generation tumor organoid functional genomics platform to help guide the development of future precision cancer medicines.
Citation Format: Mathew Garnett. Tumor organoid cultures as a platform for functional genomics [abstract]. In: Proceedings of the AACR Special Conference on the Evolving Landscape of Cancer Modeling; 2020 Mar 2-5; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2020;80(11 Suppl):Abstract nr IA09.
Abstract IA10: Modeling sensitivity and resistance to systemic therapies in lung cancer
Authors: Politi Katerina A. 
Published: June 2020

Abstract
Targeted therapies have transformed the landscape for the treatment of metastatic lung cancer. Despite their success, targeted therapies are not curative and acquired resistance is a major impediment to cures for patients treated with these therapies. A paradigm for the success of targeted therapies in lung cancer comes from epidermal growth factor receptor (EGFR) mutant lung cancer where mutations in exons encoding the tyrosine kinase domain of EGFR confer sensitivity to tyrosine kinase inhibitors (TKIs), and several TKIs are currently approved for the first-line treatment of EGFR mutant lung cancer. Moreover, there is heterogeneity in the durability and depth of responses between patients and at different metastatic sites within individual patients. Therefore, there is a need to understand the biology of EGFR mutant tumors and identify factors that affect TKI sensitivity. We developed transgenic mouse models of EGFR mutant lung cancer and have used them to study tumor progression and TKI resistance. When we modeled acquired resistance to the TKI osimertinib as a first-line therapy in transgenic mouse models of EGFRL858R-induced lung adenocarcinoma, we found that it is mediated largely through secondary mutations in EGFR—either C797S or L718V/Q or Kras mutations. We also identified a therapeutic approach to prevent the emergence of secondary mutations in EGFR. To determine whether the presence of co-occurring genetic alterations contributes to a more complex spectrum of resistance mechanisms in vivo, we have developed new mouse models to specifically evaluate the consequences of co-occurring tumor suppressor gene alterations on the progression and TKI sensitivity of EGFR mutant tumors. Collectively, our findings highlight how genetically engineered mouse models of lung cancer, including those with complex genotypes, can be leveraged to study tumor progression and drug resistance in vivo.
Citation Format: Katerina A. Politi. Modeling sensitivity and resistance to systemic therapies in lung cancer [abstract]. In: Proceedings of the AACR Special Conference on the Evolving Landscape of Cancer Modeling; 2020 Mar 2-5; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2020;80(11 Suppl):Abstract nr IA10.
Abstract IA22: Systems approach to rational combination therapy
Authors: Mills Gordon B. 
Published: June 2020

Abstract
Tumors evolve under therapeutic pressure both through rapid epigenomic mechanisms primarily at the protein network level and long-term genomic evolution. The realization of the promise of personalized molecular medicine will require efficient development and implementation of effective combination therapies able to capitalize on or interdict tumor evolution under therapeutic pressure. While we are beginning to develop a series of biomarkers able to predict which patients will benefit from monotherapy, our ability to predict which combination therapies will be active in particular patients is in its infancy. Integration of spatially oriented DNA, RNA, and protein information content as they change under therapeutic pressure has the potential to help identify patients likely to respond to combination therapy.
Therapy resistance can be pre-existing, adaptive, or acquired. Resistance can also occur through a heterogeneity of molecular changes within the tumor and metastases. Adaptive resistance, which is the consequence of activation of homeostatic loops and phylogenetically conserved stress responses, provides a potential therapeutic liability that can be leveraged for rational combinatorial therapy. Thus, a comprehensive analysis of patient tumors before, during, and after treatment should become the standard of practice to enable identification of mechanisms of resistance as well as to allow rapid evolution of patient therapy. Testing these precepts will require the development and implementation of novel biopsy-driven trial designs and CLIA-compliant analytics that can be deployed in real time to allow rapid evolution of therapeutic approaches. We have implemented a suite of biopsy-driven trials linked to deep molecular analysis with the goal of rapid identification of tumor evolution to enable change in therapy to counter tumor evolution as it arises. We have implemented a series of studies based on PARP inhibitors as a backbone with the goal of increasing the depth and duration of response while at the same time extending the population of patients who benefit beyond those with homologous recombination defects. Concurrently, we have a series of n-of-one studies with combinations of FDA-approved drugs. Early data suggest that these approaches have the potential to greatly improve patient outcomes.
Citation Format: Gordon B. Mills. Systems approach to rational combination therapy [abstract]. In: Proceedings of the AACR Special Conference on the Evolving Landscape of Cancer Modeling; 2020 Mar 2-5; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2020;80(11 Suppl):Abstract nr IA22.
Abstract PHB01: The zebrafish as a mechanical filter: Using zebrafish xenografts to model Ewing sarcoma metastasis in vivo
Authors: Segal Dagan , Chang Bo-Jui , Mazloom-Farsibaf Hanieh , Fiolka Reto , Amatruda James , Danuser Gaudenz 
Published: June 2020

Abstract
Ewing Sarcoma (ES), a pediatric cancer driven by the oncogenic fusion protein EWS-FLI1, recurs or metastasizes in 1 in 3 patients with no clear correlation to accumulation of secondary mutations, raising the possibility that environmental cues may drive metastasis. Previous work in the field has observed distinct cellular morphologies of ES cells in cell culture as a function of EWS-FLI1 level and posited the idea that this may correlate with distinct functional cellular states.
In this work, we use zebrafish xenografts to investigate the effect of variable microenvironments on cellular morphologies of ES cells. We use high resolution light-sheet microscopy to focus on specific recurring seeding sites within the 3-day old zebrafish larvae. We then implement a unique cell-shape classification method to distinguish discrete 3D cellular morphologies in these datasets.
Using this workflow, we observe a variety of cellular morphologies within the fish, including elongated cellular protrusions, blebbing, and rounded cells. We demonstrate that ES cells take on distinct morphological states as a function of the region in which they reside. We find cell proliferation, but not cell death, vary greatly in the different regions, suggesting differences in the functional state of the ES cells. Interestingly, knockdown of EWS-FLI1 in xenografted cells leads to discrete switches between cellular morphologies, but only as a function of seeding site within the fish, suggesting a previously undescribed environmental cue that modulates cellular effects of EWS-FLI1. Overall, the xenograft model for ES in zebrafish embryos can be viewed as a “mechanical filter”, which provides unique, complex 3-dimensional environments to study cell behavior within an organism, while leveraging the advantages of the zebrafish system, namely higher throughput and high resolution in vivo imaging capabilities. This work establishes a pipeline for classification and distinction of morphological states within a living organism, and, more specifically, helps our understanding of cellular plasticity of ES cells in response to microenvironment.
Citation Format: Dagan Segal, Bo-Jui Chang, Hanieh Mazloom-Farsibaf, Reto Fiolka, James Amatruda, Gaudenz Danuser. The zebrafish as a mechanical filter: Using zebrafish xenografts to model Ewing sarcoma metastasis in vivo [abstract]. In: Proceedings of the AACR Special Conference on the Evolving Landscape of Cancer Modeling; 2020 Mar 2-5; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2020;80(11 Suppl):Abstract nr PHB01.
Abstract PR05: A metabolomics discovery profiling approach identifies an E2F1-associated purine synthesis pathway as a major component of the MET-DNA damage response network
Authors: Poliaková Michaela , Medo Matúš , Koch Jonas , Coggins SiAna , Kim Baek , Aebersold Daniel M. , Zamboni Nicola , Medová Michaela , Zimmer Yitzhak 
Published: June 2020

Abstract
Various lines of investigation support a signaling interphase shared by various receptor tyrosine kinases and the DNA damage response. However, the underlying driving network nodes and their contribution to the maintenance of DNA integrity remain unknown. We used discovery metabolomics combined with transcriptomics to identify changes in global metabolic pathways that are relevant to DNA repair following MET inhibition (METi). METi was associated with formation of γH2AX foci together with significant alterations in major metabolic circuits. Remarkably, 5′-phosphoribosyl-N-formylglycinamide (FGAR), a de novo purine synthesis pathway metabolite, was decreased in MET-dependent cancer models and a METi-related depletion of dNTPs was observed. Likewise, METi instigated the downregulation of critical purine synthesis enzymes including phosphoribosylglycinamide formyltransferase (GART), which is responsible for FGAR synthesis. Genes encoding these enzymes are regulated through the E2F1 transcription factor, whose levels decreased upon METi in MET-driven cells. To validate those findings, a transient E2F1 overexpression was sufficient to prevent MET targeting-dependent dNTPs depletion and the concomitant METi-associated DNA damage in MET-driven tumor cells. These novel observations support the notion that METi-mediated sensitization to DNA-damaging agents commonly used in cancer therapeutics is largely linked to the depletion of critical metabolites used in DNA repair due to downregulation of key metabolic enzymes whose expression is regulated through MET signaling.
This abstract is also being presented as Poster A51.
Citation Format: Michaela Poliaková, Matúš Medo, Jonas Koch, SiAna Coggins, Baek Kim, Daniel M. Aebersold, Nicola Zamboni, Michaela Medová, Yitzhak Zimmer. A metabolomics discovery profiling approach identifies an E2F1-associated purine synthesis pathway as a major component of the MET-DNA damage response network [abstract]. In: Proceedings of the AACR Special Conference on the Evolving Landscape of Cancer Modeling; 2020 Mar 2-5; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2020;80(11 Suppl):Abstract nr PR05.