Evidence map›Paper›PMID 26088008›Full record

ReviewTrends in biotechnology2015

Synthetic biology in cell-based cancer immunotherapy.

Deboki Chakravarti, Wilson W Wong

Abstract readReview
In one paragraph

Review in Trends in biotechnology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

33 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Engineering Versatile Nanomedicines for Ultrasonic Tumor Immunotherapy.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024
    Review
  8. Review
  9. Review
  10. Article
  11. Article
  12. Article
  13. Article
  14. Sentinel cells enable genetic detection of SARS-CoV-2 Spike protein.bioRxiv : the preprint server for biology · 2021
    Article
  15. Article
  16. Review
  17. Review
  18. Dissecting the Tumor-Immune Landscape in Chimeric Antigen Receptor T-cell Therapy: Key Challenges and Opportunities for a Systems Immunology Approach.Clinical cancer research : an official journal of the American Association for Cancer Research · 2020
    Review
  19. Review
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Deboki ChakravartiDepartment of Biomedical Engineering, Boston University, Boston, MA 02215, USA.
Wilson W WongDepartment of Biomedical Engineering, Boston University, Boston, MA 02215, USA. Electronic address: wilwong@bu.edu.

Funding

Synthetically Reengineered T cells as the Next Generation of Smart Cancer TherapyDP2CA186574 · NCI · BOSTON UNIVERSITY (CHARLES RIVER CAMPUS) · PI WONG, WILSON · 2013 to 2013
$2.5M
NCI NIH HHS DP2 CA186574NCI NIH HHS DP2CA186574
6 · The paper itself

Abstract

The adoptive transfer of genetically engineered T cells with cancer-targeting receptors has shown tremendous promise for eradicating tumors in clinical trials. This form of cellular immunotherapy presents a unique opportunity to incorporate advanced systems and synthetic biology approaches to create cancer therapeutics with novel functions. We first review the development of synthetic receptors, switches, and circuits to control the location, duration, and strength of T cell activity against tumors. In addition, we discuss the cellular engineering and genome editing of host cells (or the chassis) to improve the efficacy of cell-based cancer therapeutics, and to reduce the time and cost of manufacturing.

Indexed as

Cell- and Tissue-Based TherapyImmunotherapySynthetic BiologyAnimalsHumansMiceNeoplasmscancerchimeric antigen receptorsgenetic circuitsimmunotherapysynthetic biology

Identifiers

PMID26088008
PMCPMC4509852

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.