Abstract IA20: Aberrant leukemic developmental hierarchies and MRD-specific targeting informed by single-cell biophysical and molecular profiling
العنوان: | Abstract IA20: Aberrant leukemic developmental hierarchies and MRD-specific targeting informed by single-cell biophysical and molecular profiling |
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المؤلفون: | Alex K. Shalek, Peter S. Dennis, Kristen E. Stevenson, Andrew W. Navia, Peter S. Winter, Mahnoor Mirza, Haley Strouf, Nolawit Mulugeta, Nicholas L. Calistri, Kay Shigemori, Nezha Senhaji, Jennyfer Galvez-Reyes, Laura L. Bilal, Mark L. Stevens, Scott R. Manalis, David M. Weinstock, Alejandro J. Gupta, Alex Van Scoyk, Foster Powers, Catharine S. Leahy, Robert J. Kimmerling, Huiyun Liu, Mark A. Murakami, Kristen L Jones |
المصدر: | Cancer Research. 80:IA20-IA20 |
بيانات النشر: | American Association for Cancer Research (AACR), 2020. |
سنة النشر: | 2020 |
مصطلحات موضوعية: | High rate, Cancer Research, Lymphoblastic Leukemia, Cell, Biology, Therapeutic resistance, Phenotype, Tumor heterogeneity, Minimal residual disease, medicine.anatomical_structure, Multiple factors, Oncology, hemic and lymphatic diseases, medicine, Cancer research |
الوصف: | Targeted inhibitors of essential oncogenic kinases induce high rates of clinical response but cure few patients due to the persistence of minimal residual disease (MRD). BCR-ABL mutant leukemias are a classic example of this paradigm where patients usually achieve deep remissions followed by near inevitable relapses. Multiple factors have been shown to influence how an individual patient’s leukemic cells will navigate treatment including differentiation state, mutational background, and communication with the microenvironment. Here, we use BCR-ABL-rearranged acute lymphoblastic leukemia (BCR-ABL ALL) to interrogate cell-autonomous features leading to therapeutic resistance using low-input single-cell assays. Specifically, we use a combination of primary samples and PDX models to dissect aberrant developmental hierarchies and monitor leukemic cell transcriptional and biophysical phenotype at pretreatment, MRD, and relapse. Using machine learning, we relate malignant B cells to normal development, allowing us to define leukemic developmental programs and demonstrate that these have consequences for the time to progression as well as the genetic alterations seen at relapse. Further, we determine that there are unique biophysical features tied to leukemic developmental states and that these integrative properties co-evolve with transcriptional state over the course of treatment. Finally, we demonstrate in PDX studies that it may be possible to intercept relapse by targeting specific features of MRD cells. Together, these data suggest that significant developmental hierarchies exist in ALL, tumor subpopulations can be identified directly within MRD, and their phenotypic and molecular characterization can be exploited to therapeutic effect. Citation Format: Peter S. Winter, Andrew Navia, Haley Strouf, Mahnoor Mirza, Jennyfer Galvez-Reyes, Nolawit Mulugeta, Laura Bilal, Nezha Senhaji, Peter Dennis, Catharine S. Leahy, Kay Shigemori, Foster Powers, Alejandro Gupta, Nicholas Calistri, Alex Van Scoyk, Kristen Jones, Huiyun Liu, Kristen E. Stevenson, Robert Kimmerling, Mark Stevens, David M. Weinstock, Scott R. Manalis, Mark A. Murakami, Alex K. Shalek. Aberrant leukemic developmental hierarchies and MRD-specific targeting informed by single-cell biophysical and molecular profiling [abstract]. In: Proceedings of the AACR Virtual Special Conference on Tumor Heterogeneity: From Single Cells to Clinical Impact; 2020 Sep 17-18. Philadelphia (PA): AACR; Cancer Res 2020;80(21 Suppl):Abstract nr IA20. |
تدمد: | 1538-7445 0008-5472 |
URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_________::2a39c0cc185d741942493ae5bfa2977f https://doi.org/10.1158/1538-7445.tumhet2020-ia20 |
رقم الأكسشن: | edsair.doi...........2a39c0cc185d741942493ae5bfa2977f |
قاعدة البيانات: | OpenAIRE |
تدمد: | 15387445 00085472 |
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