CAR T cell controls, evolving enzymes for new functions, mosaicism in ASD, and more
Research Roundup: January 15, 2021
Welcome to the January 15, 2021 installment of Research Roundup, a recurring snapshot of recent studies published by scientists at the Broad Institute and their collaborators.
Switching the CAR T on and off
Max Jan, associate member Marcela Maus, institute member Ben Ebert of the Cancer Program and Dana-Farber Cancer Institute (DFCI), and colleagues have created molecular switches that regulate the activity of CAR T cells — modified T cells used to treat some advanced cancers, but can cause dangerous inflammation. To control the cells’ activity, the researchers used an approved drug called lenalidomide, which causes the proteasomal degradation of proteins with specific tags. The team designed and attached such a tag to the CAR protein in CAR T cells and introduced the drug, causing the destruction of CAR and turning off the cells’ cancer-killing activity. The team engineered a separate system that turned the cells on in the presence of lenalidomide. Read more in Science Translational Medicine and a Dana-Farber story.
An evolved enzyme can target and modify amyloid-β
Current approaches for site-specific protein modification often require genetic manipulation, with associated limitations. A team led by graduate student Christopher Podracky and core institute member and Merkin Institute for Transformative Technologies director David Liu circumvented this roadblock by evolving an enzyme that can modify an endogenous protein in a targeted fashion. The team evolved a sortase, an enzyme that naturally cuts and pastes specific proteins on the surface of a cell, to recognize and modify the Alzheimer’s disease-associated protein amyloid-β instead of its native target. The new sortase can label amyloid-β in cerebrospinal fluid and modify amyloid-β to impede its aggregation, demonstrating the potential of this strategy for more general protein modification. Read more in Nature Chemical Biology.
Think outside of the CellBox
Bo Yuan, Ciyue Shen, and Augustin Luna in a team led by Cancer Program associate member Chris Sander of Harvard Medical School (HMS) and DFCI, along with John Ingraham in the lab of associate member Debora Marks of HMSl and the Klarman Cell Observatory, developed a hybrid approach for predicting cell behavior to previously untested perturbations, which could help in the discovery of combination therapies in cancer. Described in Cell Systems, CellBox combines explicit models of cell dynamics with a machine-learning framework, enabling the simulation of dynamic cellular behavior. The method helps overcome the lack of interpretability of traditional deep neural network methods, i.e., black-box models. CellBox predicts molecular interactions that generally agree with known biological pathways and may be applicable to other biological systems with suitable perturbation-response data.
Resistance to pharmacological “degraders”
Compounds that induce degradation of target oncoproteins are being studied in a range of cancers. Ryosuke Shirasaki, Geoffrey Matthews, Sara Gandolfi, Ricardo de Matos Simoes, and Cancer Program associate member Constantine Mitsiades of DFCI and HMS led CRISPR-based studies to dissect the mechanisms regulating tumor cell sensitivity to different classes of pharmacological “degraders” of oncoproteins. They showed that resistance to various degraders occurs from dysregulation of the intracellular degradation machinery itself rather than adaptation to loss of the target oncoprotein. Read more in Cell Reports.
To persist, they pause
Constantine Mitsiades, Eugen Dhimolea, and their colleagues generated models of treatment-resistant residual tumor cells that simulate the tumors that persist in patients after chemotherapy. Reporting in Cancer Cell, the team observed that these residual cancer cells can persist through chemotherapy by transiently suppressing Myc activity, even in Myc-amplified cells, and entering a “survival-mode” dormancy state, with distinct dependencies compared to treatment-naive cells. They also observed that this adaptive mechanism mimics embryonic diapause, a survival state in early mammalian embryos activated during stress.
Mapping mosaic mutations in ASD
How somatic mosaic mutations, which arise early in development, contribute to autism spectrum disorders' (ASD) complex genetic architecture has been unclear. In two Nature Neuroscience studies, teams led by Program in Medical and Population Genetics (MPG) associate member Christopher Walsh of Boston Children's Hospital (BCH) and Peter Park of HMS systematically mapped two classes of mosaic mutations — small single nucleotide and large copy number variations (SNVs and CNVs) — in ASD. In the SNV study, together with Rachel Rodin of BCH and Yanmei Dou of HMS, and colleagues, they studied mosaicism in ASD and the neurotypical brain through whole genome sequencing of cortical tissue from 59 individuals with ASD and 15 without. In the CNV study, with Maxwell Sherman of MIT, MPG associate member Po-Ru Loh of Brigham and Women's Hospital, and others, they used genotype data from more than 11,000 ASD-affected families and the same 59 ASD brain samples to reveal a significant CNV burden in ASD patients compared to family members.