bluuebunny/crossref_metadata_2025_split huggingface dataset:
Abstract A005: Transcriptional profiling of tumor heterogeneity and chemoresistance in small cell lung cancer
Authors: Wollenzien Hannah , Afeworki Yohannes , Kareta Michael S. 
Published: May 2022

Abstract
Small Cell Lung Cancer (SCLC) is often a heterogeneous tumor, where multiple populations of phenotypically different cells exist and contribute differentially to tumor dynamics. This tumor is characterized by a very low 2- year survival rate, high metastatic rates, and rapid acquisition of chemoresistance. Beyond first-line chemotherapy, targeted treatment options are scarce, and none take in to consideration the complex genetics of the tumor. The heterogeneous nature of this tumor makes it difficult to study and to treat, as current attempts to understand tumor dynamics use a bulk approach that averages the contribution of all cells within a tumor. This work uses a cellular barcoding lineage tracing approach combined with single-cell RNA sequencing (scRNA-seq) to understand tumor heterogeneity and evolution of SCLC in both a xenograft of human SCLC cell lines and an in vivo system using a genetically modified mouse model with alterations in the same driver genes as the majority of humans with SCLC. Tumors are sampled pre-growth, post-growth and metastasis, and pre- and post- chemotherapy. By paring the barcode populations that exist in samples over time, in metastasis, or in chemoresistance, a clonal evolution map of growth, metastasis, and chemoresistance can be generated, based on shared barcodes and convergent or divergent transcriptomic profiles. In validation of scRNA-seq data, we have identified the cancer testis antigens (CTA) PAGE5 and GAGE2A as markers of chemoresistance in human SCLC. CTAs have been successfully targeted in other tumor types and may be a promising avenue for targeted therapy in SCLC. In mouse tumors, we have identified an AP-1-high population of early tumor cells that are maintained throughout the course of the disease. The knowledge gained in this work will pave the way for the identification of new therapeutic targets for SCLC.
Citation Format: Hannah Wollenzien, Yohannes Afeworki, Michael S. Kareta. Transcriptional profiling of tumor heterogeneity and chemoresistance in small cell lung cancer [abstract]. In: Proceedings of the AACR Special Conference on the Evolutionary Dynamics in Carcinogenesis and Response to Therapy; 2022 Mar 14-17. Philadelphia (PA): AACR; Cancer Res 2022;82(10 Suppl):Abstract nr A005.
Abstract A010: Integration of clonal composition and tumor heterogeneity reveals novel evolutionary states and intervention targets in ovarian cancer
Authors: Lahtinen Alexandra , Lavikka Kari , Li Yilin , Jamalzadeh Sanaz , Virtanen Anni , Lehtonen Rainer , Carpén Olli , Hietanen Sakari , Huhtinen Kaisa , Häkkinen Antti , Hynninen Johanna , Oikkonen Jaana , Hautaniemi Sampsa 
Published: May 2022

Abstract
This abstract is being presented as a short talk in the scientific program. A full abstract is available in the Proffered Abstracts section (PR003) of the Conference Proceedings.
Citation Format: Alexandra Lahtinen, Kari Lavikka, Yilin Li, Sanaz Jamalzadeh, Anni Virtanen, Rainer Lehtonen, Olli Carpén, Sakari Hietanen, Kaisa Huhtinen, Antti Häkkinen, Johanna Hynninen, Jaana Oikkonen, Sampsa Hautaniemi. Integration of clonal composition and tumor heterogeneity reveals novel evolutionary states and intervention targets in ovarian cancer [abstract]. In: Proceedings of the AACR Special Conference on the Evolutionary Dynamics in Carcinogenesis and Response to Therapy; 2022 Mar 14-17. Philadelphia (PA): AACR; Cancer Res 2022;82(10 Suppl):Abstract nr A010.
Abstract A023: Progression and regression dynamics of bivalve transmissible neoplasia in the soft-shell clam (Mya arenaria) after both natural and experimental exposure
Authors: Giersch Rachael M. , Yonemitsu Marisa A. , Hart Samuel F.M. , Metzger Michael J. 
Published: May 2022

Abstract
This abstract is being presented as a short talk in the scientific program. A full abstract is available in the Proffered Abstracts section (PR017) of the Conference Proceedings.
Citation Format: Rachael M. Giersch, Marisa A. Yonemitsu, Samuel F.M. Hart, Michael J. Metzger. Progression and regression dynamics of bivalve transmissible neoplasia in the soft-shell clam (Mya arenaria) after both natural and experimental exposure [abstract]. In: Proceedings of the AACR Special Conference on the Evolutionary Dynamics in Carcinogenesis and Response to Therapy; 2022 Mar 14-17. Philadelphia (PA): AACR; Cancer Res 2022;82(10 Suppl):Abstract nr A023.
Abstract B001: Developing adaptive therapy to suppress the evolution of treatment resistance in high-grade serous ovarian cancer
Authors: Hockings Helen , Lockley Michelle , Graham Trevor , Lakatos Eszter , Huang Weini 
Published: May 2022

Abstract
This abstract is being presented as a short talk in the scientific program. A full abstract is available in the Proffered Abstracts section (PR015) of the Conference Proceedings.
Citation Format: Helen Hockings, Michelle Lockley, Trevor Graham, Eszter Lakatos, Weini Huang. Developing adaptive therapy to suppress the evolution of treatment resistance in high-grade serous ovarian cancer [abstract]. In: Proceedings of the AACR Special Conference on the Evolutionary Dynamics in Carcinogenesis and Response to Therapy; 2022 Mar 14-17. Philadelphia (PA): AACR; Cancer Res 2022;82(10 Suppl):Abstract nr B001.
Abstract B004: Adaptive therapy in preclinical models of hormone-refractory breast cancer
Authors: Seyedi Sareh , Maley Carlo 
Published: May 2022

Abstract
The goal of this study was to test whether adaptive therapy works in preclinical mouse models with hormone-refractory breast cancer and compare adaptive therapy with standard therapy. Specifically, we tested whether the drugs gemcitabine and/or capecitabine can control the MCF7 cancer cell line which is resistant to palbociclib and fulvestrant. We treated MCF7 resistant breast cancers growing orthotopically in the mammary fat pads of NSG immunodeficient mice with gemcitabine, capecitabine, or both drugs together. In the combined drug treatment, we switched drugs in every application (every 3 days) (“ping-pong”) or applied the drugs together (in tandem). In both single and multi-drug therapy, we applied drugs by either adjusting their doses or applying intermittently. We measured tumor size by bioluminescence imaging and caliper. We saw a reduction in the tumor burden of most mice treated with adaptive therapy along with prolonging overall survival. We found that the combination of gemcitabine and capecitabine in both intermittent and dose adjustment protocols significantly increased the survival of mice in comparison to standard therapy when we applied the drugs in a ping-pong strategy. The combination therapy in tandem was less successful compared to dose adjustment, but better than standard therapy in increasing overall survival. Moreover, we had several weeks off-treatment in most of the mice when the tumor was under the threshold, therefore lower drug doses were used. Among single drug therapies, capecitabine dose adjustment protocol was better than using both intermittent and the maximum tolerated dose in terms of increasing overall survival of mice and accumulating less dose of the drug. However, the capecitabine intermittent treatment was better compared to the capecitabine maximum tolerated dose. In contrast, there were no significant differences between adaptive protocols and standard therapy. However, in both intermittent and dose adjustment protocols we had several weeks off-treatment in most of the mice, so lower drug doses were used. In conclusion, we found that lower drug doses can be used under adaptive therapy, once the tumor is controlled. We had several weeks off- treatment for some cases and we saw a continued decline in tumor size. Overall, adaptive therapy strategies could prolong progression-free survival besides reduction in the tumor burden.
Citation Format: Sareh Seyedi, Carlo Maley. Adaptive therapy in preclinical models of hormone-refractory breast cancer [abstract]. In: Proceedings of the AACR Special Conference on the Evolutionary Dynamics in Carcinogenesis and Response to Therapy; 2022 Mar 14-17. Philadelphia (PA): AACR; Cancer Res 2022;82(10 Suppl):Abstract nr B004.
Abstract B005: Uncovering polygenic signatures of Ewings Sarcoma drug sensitivity during the evolution of resistance
Authors: Lin-Rahardja Kristi , Scarborough Jessica , Hitomi Masahiro , Scott Jacob 
Published: May 2022

Abstract
Evolution of chemotherapeutic resistance can cause treatment failure in patients with metastatic Ewings sarcoma (EWS). As resistance to the first-line therapy evolves, there is potential for the tumor to develop sensitivities to other chemotherapeutic agents besides the active treatment. This concept is known as collateral sensitivity, and it presents an opportunity for medical providers to plan more effective treatment regimens. However, it can be difficult to predict due to the stochastic nature of evolution. By analyzing gene expression patterns among independent populations of an EWS cell line that have repeatedly evolved collateral responses, we aim to extract a collection of gene signatures, or sets of genes, that will predict states of collateral sensitivity against various existing chemotherapies. To accomplish this, we will treat independently evolving replicates of an EWS cell line (A673) with the standard of care therapy (alternating combinations of vincristine, doxorubicin, cyclophosphamide, and etoposide and cyclophosphamide) to evolve resistance. Throughout this treatment regimen, we will regularly screen for collateral sensitivity against 128 chemotherapeutic agents and perform bulk RNA-sequencing. When collateral sensitivity against a drug is observed in multiple replicates, we will utilize the RNA-sequencing data to extract gene signatures using differential expression analysis. The signatures will then be validated using patient-derived xenografts collected in our lab as well as from collaborators. When completed, the sizable archive of sensitivity signatures we expect to assemble could greatly streamline the process of treatment planning for EWS patients, especially those with advanced disease. When a patient's response to primary therapy begins to decline, RNA- sequencing can be performed on a tumor biopsy, gene expression patterns can be compared with the validated signature library, and the most appropriate drug for the individual patient can be determined and used for subsequent treatment. This proposed method of treatment planning mitigates the need for excessive treatment regimens that are not guaranteed to be effective for every patient, thereby expanding the reach of precision medicine and potentially improving outcomes for EWS patients.
Citation Format: Kristi Lin-Rahardja, Jessica Scarborough, Masahiro Hitomi, Jacob Scott. Uncovering polygenic signatures of Ewings Sarcoma drug sensitivity during the evolution of resistance [abstract]. In: Proceedings of the AACR Special Conference on the Evolutionary Dynamics in Carcinogenesis and Response to Therapy; 2022 Mar 14-17. Philadelphia (PA): AACR; Cancer Res 2022;82(10 Suppl):Abstract nr B005.
Abstract B006: Evolutionary Tumor Board: Implementing dynamic personalized therapy using evolutionary theory and mathematical modeling for clinical decision support
Authors: Robertson-Tessi Mark , Brown Joel , Poole Maria , Luddy Kimberly , Marusyk Andriy , Gallaher Jill , West Jeffrey , Johnson Matthew , Enderling Heiko , Makanji Rikesh , Farinhas Joaquim , Gatenby Robert , Reed Damon , Chung Christine , Anderson Alexander 
Published: May 2022

Abstract
This abstract is being presented as a short talk in the scientific program. A full abstract is available in the Proffered Abstracts section (PR010) of the Conference Proceedings.
Citation Format: Mark Robertson-Tessi, Joel Brown, Maria Poole, Kimberly Luddy, Andriy Marusyk, Jill Gallaher, Jeffrey West, Matthew Johnson, Heiko Enderling, Rikesh Makanji, Joaquim Farinhas, Robert Gatenby, Damon Reed, Christine Chung, Alexander Anderson. Evolutionary Tumor Board: Implementing dynamic personalized therapy using evolutionary theory and mathematical modeling for clinical decision support [abstract]. In: Proceedings of the AACR Special Conference on the Evolutionary Dynamics in Carcinogenesis and Response to Therapy; 2022 Mar 14-17. Philadelphia (PA): AACR; Cancer Res 2022;82(10 Suppl):Abstract nr B006.
Abstract B008: Man vs machine: Crowdsourcing vs deep learning of adaptive therapy strategies
Authors: Bravo Rafael R. , Peterson Brenden K. , Robertson-Tessi Mark , Faissol Daniel M. , Anderson Alexander R.A. 
Published: May 2022

Abstract
Cancer Crusade is a citizen science game in which players design treatment strategies to influence a virtual tumor growth model. The treatment regimens that the players construct are collected and sent to an online database for analysis, which may give insights into clinically effective adaptive strategies. In parallel, a machine learning-based approach was applied to the game to find optimal treatment policies, and the optimized therapy approaches generated are compared to those generated by the human players. For the core game engine in Cancer Crusade, we started with a previously published hybrid cellular automata model of tumor metabolism and growth. The original model was used to study how tumor cells evolve acid-mediated invasion and the impact of treatment on these metabolic processes. We expanded the model by adding more drugs and cell phenotypes, including drug-resistant cells. The game was released on mobile platforms and has been generating data from plays for several years. The treatment strategies were analyzed using dendrogram clustering to find key decision differences and profile their relative performance. We also performed network analysis to observe treatment transitions. These analyses indicated several effective adaptive strategies, which tended to oscillate between chemotherapy and a pro-angiogenic drug, or chemotherapy and a hypoxia-activated prodrug, or combinations of all three of these drugs. These results parallel a machine learning (Q-learning) approach to the problem, which yielded a preferred strategy based on chemotherapy combined with a pro-angiogenic drug. The existence of several human-discovered alternative strategies suggests that in general human players may offer greater variety of successful strategies via citizen science games than Q-learning. The human and machine learning approaches also excelled in different areas. Human players tended to use less drug overall, and perform best on less aggressive tumors, while the Q-learning approach used more drug overall and performed best on more aggressive tumors.
Citation Format: Rafael R. Bravo, Brenden K. Peterson, Mark Robertson-Tessi, Daniel M. Faissol, Alexander R.A. Anderson. Man vs machine: Crowdsourcing vs deep learning of adaptive therapy strategies [abstract]. In: Proceedings of the AACR Special Conference on the Evolutionary Dynamics in Carcinogenesis and Response to Therapy; 2022 Mar 14-17. Philadelphia (PA): AACR; Cancer Res 2022;82(10 Suppl):Abstract nr B008.
Abstract B016: Selection and reprogramming contribute to the evolution of targeted therapy resistance
Authors: Velde Robert Vander , Shaffer Sydney 
Published: May 2022

Abstract
Targeted therapies provide substantial benefits to cancer patients by shrinking and controlling tumors. However, the long-term efficacy of targeted therapy is limited by the development of resistance. Once a tumor is fully resistant, it continues to grow despite the presence of the targeted therapy, leading to disease relapse in the patient. When the therapy is first applied, a number of studies have now shown that there is initially a selection for cells that are able to tolerate the drug (termed “tolerant cells”). This contrasts with selection of fully resistant cells. More recently our studies have suggested that the transition from tolerance to resistance is not binary and involves multiple changes. These changes can be propelled by the stochastic generation of heritable heterogeneity followed by selection (Darwinian evolution), by long-term changes in signaling networks (reprogramming) and by combinations of these two. The contribution of these factors determines the usefulness of strategies using either evolutionary dynamics (such as reducing population size or changing selective pressures on tumor cells) or therapies that alter cell states (such as inhibiting or activating key signaling nodes). We are using colony assays and developing barcoding techniques to address the role of selection and clonality in the evolution of full resistance to BRAF inhibitors in melanoma from a tolerant state. Early results show a rapid increase in fitness (relative to surviving tolerant cells) suggesting a role for selection immediately after the first selective event. These changes are followed by slow changes that may be the result of mostly reprogramming. This implies that strategies that manipulate evolutionary dynamics are most effective early in resistance evolution while later changes can be manipulated by altering signaling nodes.
Citation Format: Robert Vander Velde, Sydney Shaffer. Selection and reprogramming contribute to the evolution of targeted therapy resistance [abstract]. In: Proceedings of the AACR Special Conference on the Evolutionary Dynamics in Carcinogenesis and Response to Therapy; 2022 Mar 14-17. Philadelphia (PA): AACR; Cancer Res 2022;82(10 Suppl):Abstract nr B016.
Abstract B030: Mimicking the evolution of doxorubicin resistance in triple negative breast cancer
Authors: Pearson Kashenya , Everett Terrence , Rorie Checo J. 
Published: May 2022

Abstract
Chemotherapy resistance presents a major challenge in the treatment of triple negative breast cancer (TNBC), which is characterized by low or no expression of the estrogen receptor (ER), the progesterone receptor (PR), and the human epidermal growth factor receptor-2 (HER2). Because TNBC tumors do not express these receptors, there has been little to no advancement in the establishment of drug therapies to specifically target this breast cancer subtype. Additionally, unfavorable side effects and drug resistance reveal an urgent need for safer, more effective therapeutic options. In this study, we aim to mimic cancer recurrence by establishing doxorubicin (DOX) resistance in TNBC cell lines, HCC1806 and HCC70 and investigate the effect on cell survival, cell migration, and changes in gene expression. Here we show that TNBC cell growth was sustained after pulse treatments with increasing concentrations of DOX. HCC1806 and HCC70 cells treated with DOX titrants (0.5 µM-2.0 µM) demonstrate cell growth sustainability after 3h treatments. The DOX-treated TNBC cells also demonstrate anti-migratory potential. RNA sequencing analysis show that IL6, TP53, and TNFSF12 are uniquely expressed after 24h exposure to 0.5uM DOX. We plan to further investigate the roles these genes play in chemoresistance. Understanding changes in the gene network, as a result of doxorubicin-resistance, may help to establish biomarkers that could represent targets for drug therapies to overcome chemoresistance in TNBC.
Citation Format: Kashenya Pearson, Terrence Everett, Checo J. Rorie. Mimicking the evolution of doxorubicin resistance in triple negative breast cancer [abstract]. In: Proceedings of the AACR Special Conference on the Evolutionary Dynamics in Carcinogenesis and Response to Therapy; 2022 Mar 14-17. Philadelphia (PA): AACR; Cancer Res 2022;82(10 Suppl):Abstract nr B030.
Abstract B033: Immunosuppressive niche engineering at the onset of human colorectal cancer
Authors: Gatenbee Chandler D. , Baker Ann-Marie , Schenck Ryan O. , Strobl Maximilian , West Jeffrey , Robertson-Tessi Mark , Graham Trevor A. , Anderson Alexander R.A. 
Published: May 2022

Abstract
This abstract is being presented as a short talk in the scientific program. A full abstract is available in the Proffered Abstracts section (PR0081) of the Conference Proceedings.
Citation Format: Chandler D. Gatenbee, Ann-Marie Baker, Ryan O. Schenck, Maximilian Strobl, Jeffrey West, Mark Robertson-Tessi, Trevor A. Graham, Alexander R.A. Anderson. Immunosuppressive niche engineering at the onset of human colorectal cancer [abstract]. In: Proceedings of the AACR Special Conference on the Evolutionary Dynamics in Carcinogenesis and Response to Therapy; 2022 Mar 14-17. Philadelphia (PA): AACR; Cancer Res 2022;82(10 Suppl):Abstract nr B033.
Abstract B034: Targeting cellular plasticity-driven metabolic adaptation to overcome chemoresistance in GBM
Authors: Ahmed Atique U. , Shireman Jack M. , Atash Fatemeh , Lee Gina , Ali Eunus S. , Saathoff Miranda R. , Park Cheol H. , Savchuk Sol , Baisiwala Shivani , Miska Jason , Lesniak Maciej S. , James C. David , Stupp Roger , Kumthekar Priya , Horbinski Craig M. , Ben-Sahra Issam 
Published: May 2022

Abstract
This abstract is being presented as a short talk in the scientific program. A full abstract is available in the Proffered Abstracts section (PR011) of the Conference Proceedings.
Citation Format: Atique U. Ahmed, Jack M. Shireman, Fatemeh Atash, Gina Lee, Eunus S. Ali, Miranda R. Saathoff, Cheol H. Park, Sol Savchuk, Shivani Baisiwala, Jason Miska, Maciej S. Lesniak, C. David James, Roger Stupp, Priya Kumthekar, Craig M. Horbinski, Issam Ben-Sahra. Targeting cellular plasticity-driven metabolic adaptation to overcome chemoresistance in GBM [abstract]. In: Proceedings of the AACR Special Conference on the Evolutionary Dynamics in Carcinogenesis and Response to Therapy; 2022 Mar 14-17. Philadelphia (PA): AACR; Cancer Res 2022;82(10 Suppl):Abstract nr B034.