9 Papers
66 Citations
Aimee Iberg is an academic researcher from University of Texas MD Anderson Cancer Center. The author has contributed to research in topics: Cancer & Immunology. The author has an hindex of 3, co-authored 7 publications.
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Papers
Increased thymus- and decreased parathyroid-fated organ domains in Splotch mutant embryos
Ann V. Griffith,Kim Cardenas,Carla Carter,Julie Gordon,Aimee Iberg,Kurt A. Engleka,Jonathan A. Epstein,Nancy R. Manley,Ellen R. Richie +8 more
TL;DR: These findings implicate NCCs in regulating patterning of third pouch endoderm into thymus- versus parathyroid-specified domains, and suggest that organ size is determined in part by the number of progenitor cells specified to a given fate.
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Abstract P1-18-35: MT-5111, a novel HER2 targeting engineered toxin body, under clinical development to overcome mechanisms of resistance to existing HER2 targeted therapies
TL;DR: MT-5111 represents a novel Her2 targeted therapy which could provide benefit in subjects with HER2-positive cancers and potentially overcome mechanisms of tumor resistance to existing HER2 targeted therapies.
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Abstract 3366: In vivo efficacy of a PD-L1 targeted, antigen seeding engineered toxin body
Hilario J. Ramos,Brigitte Brieschke,Sara LeMar,Joseph D. Dekker,Aimee Iberg,Garrett L. Robinson,Asis K. Sarkar,Banmeet Anand,Melissa M. Singh,Jay Zhao,Jack P. Higgins,Erin Willert +11 more
TL;DR: The combination of a PD-L1 specific direct cell kill and redirection of a robust effector T cell response to the tumor has potential benefit in solid tumor indications, including in the relapsed setting, when disease has progressed after checkpoint and/or other therapies.
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Abstract 2060: Combination of CD20 targeted engineered toxin body, MT-3724, with chemotherapy or IMiDs for the treatment of non Hodgkin's lymphoma
TL;DR: MT-3724 has demonstrated good tolerability and early signs of clinical activity as monotherapy in patients with R/R NHL along with additive and/or synergistic effects in combination with chemotherapy and IMiDs preclinically.
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Abstract LB071: A phenomics platform combining imaging and artificial intelligence for rapid validation and advancement of novel oncology targets
Jenny A. Rudnick,Kiran S. Nadella,Shane Rowley,Ethan Gardner,Shadi Swaidani,Aimee Iberg,Daria Beshnova,Aurora Blucher,Rebecca Sarto Basso,Malini Rajan,Ashraf Abbas Saeed,John H. Ansede,Pouya Hadipour,Kevin W. Jessing,Janet L. Paulsen,Paul Rearden,Vamshi K. Manda,Sashi G. Kasimsetty,Harish Shankaran,Meenakshy Iyer,Ashish Bhandari,Irit Rappley,Laura Schaevitz,Imran Haque,Hayley J. Donnella,Michael F. Cuccarese,Marie Evangelista +26 more
TL;DR: Rudnick et al. as mentioned in this paper combined high-content microscopy with arrayed CRISPR genome editing techniques and machine learning (ML) to build a rigorously controlled dataset enabling exploration of biology and chemistry at scale.
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