bluuebunny/crossref_metadata_2025_split huggingface dataset:
Abstract IA19: Role of autophagy in cancer metabolism
Authors: White Eileen P. 
Published: June 2020

Abstract
Autophagy captures intracellular components and delivers them to lysosomes, where they are degraded and recycled to sustain metabolism and enable survival in starvation. Acute, whole-body deletion of the essential autophagy gene Atg7 in adult mice causes a systemic metabolic defect manifested by starvation intolerance and gradual loss of white adipose tissue, liver glycogen, and muscle mass. Cancer cells benefit from autophagy as deletion of essential autophagy genes impairs spontaneous tumor growth in autochthonous cancer models. Tumor cell autonomous autophagy is required to recycle macromolecules to sustain mitochondrial substrate supply and thereby energy and nucleotide pools essential for survival during nutrient limitation. In addition to promoting tumor cell survival, autophagy in the host also promotes tumorigenesis. Host-specific Atg7 or Atg5 deletion impairs growth of multiple different allografted tumors, by preventing the release of Arginase 1 from hepatocytes. Arginase 1 degrades circulating arginine that is essential for the growth of tumors, most of which are auxotrophic for arginine. Thus, autophagy sustains both tumor cell and host metabolism to enable tumor growth. In tumors with a high neoantigen load that can be recognized and killed by T cells, autophagy suppresses an antitumor T-cell response. Autophagy prevents tumor killing by T cells by suppressing production of interferon gamma in a T cell-dependent manner. Thus, autophagy promotes tumorigenesis by promoting intrinsic and extrinsic tumor metabolism and by suppressing the ability of the immune system to eliminate tumors. This suggests that autophagy inhibitors may be especially useful for cancer therapy when combined with immunotherapy. To better understand the toxicity of autophagy inhibition to normal tissues, we have examined the functional consequence of conditional Atg7 or Atg5 deletion in adult mice. Whereas Atg7 deletion causes neurodegeneration in 2-3 months, Atg5 deletion causes very specific loss of telocytes and stem cells in the ileum part of the intestine and rapid death due to a more abrupt loss of autophagy function. This indicates that there is a difference in the sensitivity of cell types and tissues to the loss of autophagy and that there are discrete functional dependencies on different ATGs.
Citation Format: Eileen P. White. Role of autophagy in cancer metabolism [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 IA19.
Abstract IA21: Elucidating and targeting mechanisms of single-cell state maintenance: From N-of-1 to N-of-1-of-1 studies
Authors: Califano Andrea 
Published: June 2020

Abstract
We have developed network-based methodologies for the systematic identification, validation, and pharmacologic targeting of a new class of therapeutic targets. These targets comprise Master Regulator proteins, whose concerted aberrant activity within tightly regulated modules (tumor checkpoints) is responsible for the mechanistic implementation and maintenance of specific tumor cell states. By leveraging these methodologies, we have developed OncoTreat, a NY CLIA-certified test that leverages large-scale drug-perturbation assays to systematically identify drugs and drug combinations whose mechanism of action is specifically effective in abrogating tumor checkpoint activity, on an individual patient basis. These tests have shown 60% validation rate across 39 predicted drugs that were validated in PDX models from patients who had failed multiple standard-of-care therapies. In this talk, we will introduce these concepts and then demonstrate their application to elucidating drugs capable of targeting transcriptionally distinct tumor niches by single-cell analysis (N-of-1-of-1 studies). In particular, we will show identification and validation, in vivo, of drugs targeting the stemlike progenitor niche of breast adenocarcinomas and the four transcriptionally distinct single-cell subtypes identified in glioblastoma patients.
Citation Format: Andrea Califano. Elucidating and targeting mechanisms of single-cell state maintenance: From N-of-1 to N-of-1-of-1 studies [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 IA21.
Abstract IA23: Single cell-resolution lineage tracing of tumors in a mouse xenograft model reveals rapid and multidirectional metastasis
Authors: Weissman Jonathan S. 
Published: June 2020

Abstract
The pairing of CRISPR/Cas9-based gene editing with massively parallel single-cell readouts now enables large-scale, single-cell lineage tracing exploration of the phylogenetic principles that govern important biologic processes at unprecedented resolution and scale. We recently described a flexible, high-information, multichannel molecular recorder with a single-cell readout and applied it as an evolving lineage tracer to define a mouse cell fate map from fertilization through gastrulation. In the present study, we now apply our Cas9-based lineage tracer to investigate metastatic progression in a lung cancer xenograft model in mouse. We describe &gt;100 single cell-resolution phylogenies for tens of thousands of cancer cells from multiple tumors, and we observe a wide range of clade-specific behaviors. From these family trees, we infer the number of ancestral metastatic events and thus calculate the metastatic potential for every population, the frequency of metastasis, and the tissue routes through which metastases transit. We overlay single-cell transcriptomic signatures on the phylogenies and find distinct clone- or clade-specific expression signatures that correlate with metastatic potential, highlighting the diversity of cancer phenotypes even within this single xenograft model. We illustrate numerous examples of complex, multidirectional metastatic architectures, including self-seeding, monoclonal seeding, and seeding cascades. More generally, our approach provides an unprecedented ability to monitor tumor formation, evolution, growth, and spread in an in vivo setting.
Citation Format: Jonathan S. Weissman. Single cell-resolution lineage tracing of tumors in a mouse xenograft model reveals rapid and multidirectional metastasis [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 IA23.
Abstract IA24: Interrogating therapy response and resistance in engineered preclinical models
Authors: Dow Lukas E. 
Published: June 2020

Abstract
The past decade has produced a vast amount of clinical sequencing data that have defined the genetic landscape of human cancers. We know with greater detail than ever the number and type of mutation in any given gene, yet we have a limited understanding of how this mutational heterogeneity impacts cancer initiation, progression, or therapeutic response. Thus, despite the enormous resources invested in genome sequencing, the vast amount of information gathered is uninformative as we simply do not know how most cancer-associated mutations dictate tumor behavior. Even extremely well-studied genes such as KRAS and APC harbor an array of mutational variants that may have significant prognostic and therapeutic relevance but remain scarcely characterized. Further complicating the challenge is the number of mutational combinations that impact cancer behavior. To meet this challenge, we develop and exploit new genetic technologies to engineer organoid and animal model systems that faithfully represent the mutational events in human cancer. We use these tools to determine how specific mutational variants in major oncogenic pathways shape cancer progression and influence cancer cell vulnerabilities and response to therapy. I will describe our efforts to understand the contribution of recurrent alterations in APC and KRAS, as well as our ongoing work to prospectively define mechanism of response and resistance to new WNT-targeted therapies now entering clinical trials.
Citation Format: Lukas E. Dow. Interrogating therapy response and resistance in engineered preclinical models [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 IA24.
Abstract IA26: Multiplexed functional cancer genomics
Authors: Cai Hongchen , Li Chuan , Chew Su Kit , Yousefi Maryam , Foggetti Giorgia , Lin Wen-Yang , Rogers Zoë N. , Winters Ian P. , McFarland Christopher D. , Politi Katherina , Swanton Charlie , Petrov Dmitri A. , Winslow Monte M. 
Published: June 2020

Abstract
Extensive cancer genotyping has identified a large number of putative tumor-suppressor genes. However, genome sequencing data alone are insufficient to uncover the importance and role of these genes during carcinogenesis. Moreover, whether tumor suppressors restrict the rate of tumor growth, decrease the probability of incipient tumorigenesis, or limit the emergence of particularly fast-growing clones remains unknown for even the most well-studied tumor suppressors. I will discuss the development and use of multiplexed autochthonous mouse models of human lung adenocarcinoma that integrate tumor barcoding, CRISPR/Cas9-based genome editing, and high-throughput barcode sequencing (Tuba-seq). Using these methods, the impact of large panels of putative tumor suppressor genes can be quantified in parallel. We find that many previously understudied genes have strong effects on multiple aspects of tumor growth in vivo. While some functional tumor-suppressor genes have particularly strong effects only during some but not other phases of tumorigenesis, many genes impacted multiple facets of cancer development. Tuba-seq-based studies across oncogenic contexts and with combinatorial tumor suppressor gene inactivation further highlight the context dependency of gene function during carcinogenesis. These cause-and-effect analyses uncover an unexpectedly complex taxonomy of tumor suppression. We have further employed these multiplexed and quantitative in vivo models to assess the relationship between tumor genotype and therapeutic responses at scale. We coupled Tuba-seq with robust statistical methods to enable the generation of a pharmacogenomic map of lung cancer treatment responses in vivo. We uncover a surprisingly informative map of genotype-specific therapeutic responses, which highlights the importance of tumor-suppressor genotype in driving precision treatment approaches. These blueprints of the multifaceted nature of carcinogenesis have implications for understanding cancer evolution, interpreting clinical cancer genome sequencing data, and directing approaches for precision cancer treatment.
Citation Format: Hongchen Cai, Chuan Li, Su Kit Chew, Maryam Yousefi, Giorgia Foggetti, Wen-Yang Lin, Zoë N. Rogers, Ian P. Winters, Christopher D. McFarland, Katherina Politi, Charlie Swanton, Dmitri A. Petrov, Monte M. Winslow. Multiplexed functional cancer 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 IA26.
Abstract PHA01: Modeling the tissue-specific oncogenesis of mutant RAS
Authors: Moore Amanda R. , McGinnis Lisa , Malek Shiva 
Published: June 2020

Abstract
RAS mutations are highly prevalent in tumors, especially those of the lung, colon, skin, and pancreas. The tissues in which these tumors arise are enriched for specific RAS isoform and codon preferences. For example, mutations in KRAS are prevalent in lung, colon, and pancreas, while NRAS mutations are predominantly found in melanoma. Additionally, mutations in KRAS predominantly occur at codons 12 and NRAS mutations at codon 61. Independent of the RAS isoform, the mutated codon contributes to distinct biochemical differences, with codon 61 mutations largely viewed as more biochemically active than codon 12 mutations. Previous RAS-mutant genetically engineered mouse (GEM) models resembled the tissue specificity observed in patients. In the colon, expression of KrasG12D but not NrasG12D induced colonic hyperplasia. While in melanocytes, the expression of NrasQ61R, but not NrasG12D, led to melanoma development. Given these data, we developed RAS-mutant GEM models to identify the tissues susceptible to RAS mutations and the differences among these animal models. To achieve this, we generated four conditional knockin GEM models to directly compare Kras and Nras mutations in codons 12 and 61; G12D and Q61R. To robustly determine the effects of mutant expression across a wide range of tissues, we utilized the ubiquitous and temporally expressed Cre, Rosa26-CreERT2. Following the induction of recombination by tamoxifen treatment, we observed rapid mortality in Kras-mutant animals. KrasQ61R mice survived to a median of 13 days while KrasG12D mice survived to a median of 22 days post-tamoxifen. However, the Nras-mutant mice have extended survival. While ongoing, these survival data suggest tissues acutely sensitive to Kras-mutant expression can tolerate or are resistant to Nras-mutant expression. When comparing the two Kras conditional knockin GEM models, we found expression of KrasG12D and KrasQ61R drove hyperproliferation in both lung and colon tissues to varying degrees and different tissue types in the colon. For instance, we observe colonic hyperplasia in KrasG12D mice and polypoid hyperplasia in KrasQ61R mice. Interestingly, the hematopoietic cells were exquisitely sensitive to expression of KrasQ61R, and these animals rapidly developed acute myeloid leukemia leading to death. These data illustrate how the strength of the constitutive activation of RAS proteins drives differential tumorigenesis. We plan to further our understanding of the tissue-specific tumorigenesis of mutant-RAS proteins by comparing the Kras- and Nras-mutant GEM models.
This abstract is also being presented as Poster A01.
Citation Format: Amanda R. Moore, Lisa McGinnis, Shiva Malek. Modeling the tissue-specific oncogenesis of mutant RAS [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 PHA01.
Abstract PHA03: Coordinate translational control of KRAS signaling pathway in pancreatic adenocarcinoma
Authors: Singh Kamini , Wendel Hans-Guido 
Published: June 2020

Abstract
G-quadruplex (GQ) elements are conserved translational control elements that induce a requirement for RNA helicase activity for efficient mRNA translation. Computational structure analyses identify GQ elements in the 5´UTRs of mRNAs encoding KRAS and key downstream signaling molecules. KRAS is a key oncogene in pancreatic ductal adenocarcinoma (PDAC) and many other cancers, and except for the specific G12C KRAS mutation we do not have pharmacologic inhibitors. We find that KRAS and downstream signaling molecules, including PI3K, RALA, RAC2, MYC, MET, and YAP1, strictly depend on the RNA helicase eIF4A for their translation. This implies a potential utility for eIF4A/DDX2 inhibitors such as the silvestrol analogue CR31B. Indeed, CR31B shows nanomolar cell kill in vitro and in vivo efficacy across xenograft, primary PDX, and murine PDAC models. Together, our study reveals a signature of coordinate and eIF4A/DDX2 dependent oncogene translation in PDAC that is potentially accessible to therapeutic attack.
This abstract is also being presented as Poster A18.
Citation Format: Kamini Singh, Hans-Guido Wendel. Coordinate translational control of KRAS signaling pathway in pancreatic adenocarcinoma [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 PHA03.
Abstract PHA05: Strategies to improve engineering cancer-associated SNVs with base editing
Authors: Katti Alyna , Foronda Miguel , Zimmerman Jill , Diaz Bianca , Zafra Maria Paz , Goswami Sukanya , Piskounova Elena , Dow Lukas E. 
Published: June 2020

Abstract
Base editing (BE) is a powerful tool for engineering single-nucleotide variants (SNVs) and has been used to create targeted mutations in cell lines, organoids, and animal models. Recent development of new BE enzymes has provided an extensive toolkit for genome modification; however, unlike Cas9, which shows remarkable efficacy in creating homozygous disruptive mutations following DNA double-strand breaks (DSBs), BE is relatively inefficient and identifying and isolating edited cells for analysis has proved challenging. To enable simple identification and enrichment of base editing events, we developed a “Gene On” (GO) reporter system that indicates precise cytosine or adenine base editing in situ with high sensitivity and specificity. We validate GO using an activatable GFP and use it to measure the kinetics, efficiency, PAM specificity, and fidelity of a range of new BE variants. Further, GO is flexible and can be easily adapted to induce expression of numerous genetically encoded markers, antibiotic resistance genes, or enzymes such as Cre recombinase. With these tools, GO can be exploited to functionally link BE events at endogenous genomic loci to cellular enzymatic activities in human and mouse cell lines and organoids. We further demonstrate the application of GO in detecting in vivo BE activity using a newly generated mouse model with inducible and reversible base editor expression that will enable generation of novel cancer models in vivo. GO provides a powerful approach to increase the practicality and feasibility of implementing CRISPR BE in biomedical research.
This abstract is also being presented as Poster A45.
Citation Format: Alyna Katti, Miguel Foronda, Jill Zimmerman, Bianca Diaz, Maria Paz Zafra, Sukanya Goswami, Elena Piskounova, Lukas E. Dow. Strategies to improve engineering cancer-associated SNVs with base editing [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 PHA05.
Abstract PHB02: Impact of genetic diversity on the growth of human-derived xenografts
Authors: Sargent Jennifer , Cartagena Roberto , Trowbridge Stephanie , Munger Steven , Hasham Muneer 
Published: June 2020

Abstract
The generation of human patient-derived xenograft (hPDX) models, and efficacy testing on human cell-derived xenografts (hCDX) or hPDX, are usually performed on a single mouse genetic background. Emerging evidence suggests that host genetic background underlies the variability in xenograft establishment as well as tumor response to drugs. Here we show two approaches, a genetic and a chemical one, on human-derived xenografts as proof of concept to show that xenografting can be done in genetic diverse mice and growth kinetics is different depending on the strain of the mice. The genetic approach is to use Rag1-/- mice for xenografts—Rag1-/- mice are immunodeficient and accept human cells. We found that the growth kinetics of a well-characterized hCDX is unequivocally distinct in three genetically diverse strains. The chemical approach is to use 2-deoxy glucose (2DG) to dampen the immune system in order to reduce graft rejection. We found that the growth kinetics and engraftment acceptability rates of a well-characterized hPDX were highly unique in eight genetically distinct outbred mice treated with 2DG. These findings provide proof of concept that xenografting can be conducted in genetically diverse mice. Development of these novel platforms will provide the genetic diversity necessary for the growth of any type of tumor, expanding the PDX platform to sustain cancers that have previously failed to xenograft.
This abstract is also being presented as Poster B33.
Citation Format: Jennifer Sargent, Roberto Cartagena, Stephanie Trowbridge, Steven Munger, Muneer Hasham. Impact of genetic diversity on the growth of human-derived xenografts [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 PHB02.
Abstract PHB05: Mechanism-based computational models to study interplay between EGFR inhibitors and KRAS mutants
Authors: Stites Edward C. 
Published: June 2020

Abstract
An early genotype-to-phenotype relationship in cancer personalized medicine was that KRAS mutations confer resistance to EGFR inhibitors in colorectal cancer. Confusingly, phase 3 clinical trials found that patients with the KRAS G13D mutation were an exception to this rule. That constitutively active KRAS mutants would cause resistance to EGFR inhibitors seemed intuitive, and it appeared inconsistent with known mechanisms of RAS biology for any constitutively active KRAS mutant to behave differently. We have developed a computational model that describes the biochemical mechanisms of RAS signal regulation. Simulations of this mass-action model reproduce known patterns of RAS pathway activation. The incorporation of the specific biochemical parameters for different KRAS mutants has allowed us to uncover novel, non-obvious insights into the response of KRAS G13D and KRAS G12C colorectal cancers to EGFR inhibition. For KRAS G13D, the model revealed EGFR inhibition leads to reduced wild-type HRAS and NRAS signaling in KRAS G13D cancers, but not KRAS G12D or KRAS G12V cancers. The model also revealed a critical dependence upon tumor suppressor NF1, and that the impaired binding of KRAS G13D to NF1 frees NF1 to act on wild-type RAS. Importantly, our computational predictions have been prospectively validated experimentally. Our computational model has also revealed that cotreatment of KRAS G12C colorectal cancer with EGFR and KRAS G12C inhibitors results in a depletion of the active forms of both wild-type and mutant RAS proteins, which we have also confirmed experimentally. For both KRAS G13D and KRAS G12C colorectal cancers, our work demonstrates how computational models can identify behaviors that logically follow from what is known, but which the complexity of the RAS signaling network has prevented from previously being uncovered despite extensive, empirical, experimental efforts.
This abstract is also being presented as Poster B51.
Citation Format: Edward C. Stites. Mechanism-based computational models to study interplay between EGFR inhibitors and KRAS mutants [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 PHB05.