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Synthetic biology, genetic circuits and machine learning: a new age of cancer therapy

Synthetic biology has made it possible to rewire natural cellular responses to treat disease, notably demonstrated by chimeric antigen receptor (CAR) T cells as cancer immunotherapy. Building on the success of T‐cell activation using synthetic receptors, the field is now investigating how induction...

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Detalles Bibliográficos
Autores principales: Prasad, Krishneel, Cross, Ryan S., Jenkins, Misty R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10257410/
https://www.ncbi.nlm.nih.gov/pubmed/37002698
http://dx.doi.org/10.1002/1878-0261.13420
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author Prasad, Krishneel
Cross, Ryan S.
Jenkins, Misty R.
author_facet Prasad, Krishneel
Cross, Ryan S.
Jenkins, Misty R.
author_sort Prasad, Krishneel
collection PubMed
description Synthetic biology has made it possible to rewire natural cellular responses to treat disease, notably demonstrated by chimeric antigen receptor (CAR) T cells as cancer immunotherapy. Building on the success of T‐cell activation using synthetic receptors, the field is now investigating how induction of noncanonical signalling pathways and sophisticated synthetic gene circuitry can enhance the antitumour phenotype of engineered T cells. This commentary explores two recently published studies that provide proof of concept for how new technologies achieve this. The first demonstrated that non‐naturally occurring combinations of signalling motifs derived from various immune receptors and arranged as a CAR drove unique signal transduction pathways in T cells and improved their tumour killing ability. Here, machine learning complemented the screening process and successfully predicted CAR T‐cell phenotype dependent on signalling motif choice. The second explored how synthetic zinc fingers can be engineered into controllable transcriptional regulators, where their activity was dependent on the presence or absence of FDA‐approved small‐molecule drugs. These studies are pivotal in expanding the design choices available for gene circuits of the future and highlight how a single cellular therapy could respond to multiple environmental cues including target cell antigen expression, the tumour microenvironment composition and small molecule drugs.
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spelling pubmed-102574102023-06-11 Synthetic biology, genetic circuits and machine learning: a new age of cancer therapy Prasad, Krishneel Cross, Ryan S. Jenkins, Misty R. Mol Oncol Commentary Synthetic biology has made it possible to rewire natural cellular responses to treat disease, notably demonstrated by chimeric antigen receptor (CAR) T cells as cancer immunotherapy. Building on the success of T‐cell activation using synthetic receptors, the field is now investigating how induction of noncanonical signalling pathways and sophisticated synthetic gene circuitry can enhance the antitumour phenotype of engineered T cells. This commentary explores two recently published studies that provide proof of concept for how new technologies achieve this. The first demonstrated that non‐naturally occurring combinations of signalling motifs derived from various immune receptors and arranged as a CAR drove unique signal transduction pathways in T cells and improved their tumour killing ability. Here, machine learning complemented the screening process and successfully predicted CAR T‐cell phenotype dependent on signalling motif choice. The second explored how synthetic zinc fingers can be engineered into controllable transcriptional regulators, where their activity was dependent on the presence or absence of FDA‐approved small‐molecule drugs. These studies are pivotal in expanding the design choices available for gene circuits of the future and highlight how a single cellular therapy could respond to multiple environmental cues including target cell antigen expression, the tumour microenvironment composition and small molecule drugs. John Wiley and Sons Inc. 2023-04-01 /pmc/articles/PMC10257410/ /pubmed/37002698 http://dx.doi.org/10.1002/1878-0261.13420 Text en © 2023 The Authors. Molecular Oncology published by John Wiley & Sons Ltd on behalf of Federation of European Biochemical Societies. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Commentary
Prasad, Krishneel
Cross, Ryan S.
Jenkins, Misty R.
Synthetic biology, genetic circuits and machine learning: a new age of cancer therapy
title Synthetic biology, genetic circuits and machine learning: a new age of cancer therapy
title_full Synthetic biology, genetic circuits and machine learning: a new age of cancer therapy
title_fullStr Synthetic biology, genetic circuits and machine learning: a new age of cancer therapy
title_full_unstemmed Synthetic biology, genetic circuits and machine learning: a new age of cancer therapy
title_short Synthetic biology, genetic circuits and machine learning: a new age of cancer therapy
title_sort synthetic biology, genetic circuits and machine learning: a new age of cancer therapy
topic Commentary
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10257410/
https://www.ncbi.nlm.nih.gov/pubmed/37002698
http://dx.doi.org/10.1002/1878-0261.13420
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