Evidence map›Paper›PMID 32973401›Full record

ReviewCancer cell international2020

CRISPR-Cas, a robust gene-editing technology in the era of modern cancer immunotherapy.

Seyed Mohammad Miri, Elham Tafsiri, William Chi Shing Cho, Amir Ghaemi

Erratum issuedOpen access · goldAbstract readReview
In one paragraph

Review in Cancer cell international, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.8field-weighted citation impact, top 30% of its field
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

7 citing papers in PubMed, 14 citations in OpenAlex.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors at 3 institutions in 2 countries.

Seyed Mohammad MiriDepartment of Chemistry, Sharif University of Technology, Tehran, Iran.
Elham TafsiriMolecular Medicine Department, Biotechnology Research Center, Pasteur Institute of Iran, Tehran, Iran.
William Chi Shing ChoDepartment of Clinical Oncology, Queen Elizabeth Hospital, Hong Kong, China.
Amir GhaemiDepartment of Virology, Pasteur Institute of Iran, Tehran, P.O.Box: 1316943551, Iran.ORCID 0000-0001-7793-2920
Pasteur Institute of Iran · IRQueen Elizabeth Hospital · CNSharif University of Technology · IR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cancer immunotherapy has been emerged as a promising strategy for treatment of a broad spectrum of malignancies ranging from hematological to solid tumors. One of the principal approaches of cancer immunotherapy is transfer of natural or engineered tumor-specific T-cells into patients, a so called "adoptive cell transfer", or ACT, process. Construction of allogeneic T-cells is dependent on the employment of a gene-editing tool to modify donor-extracted T-cells and prepare them to specifically act against tumor cells with enhanced function and durability and least side-effects. In this context, CRISPR technology can be used to produce universal T-cells, equipped with recombinant T cell receptor (TCR) or chimeric antigen receptor (CAR), through multiplex genome engineering using Cas nucleases. The robust potential of CRISPR-Cas in preparing the building blocks of ACT immunotherapy has broaden the application of such therapies and some of them have gotten FDA approvals. Here, we have collected the last investigations in the field of immuno-oncology conducted in partnership with CRISPR technology. In addition, studies that have addressed the challenges in the path of CRISPR-mediated cancer immunotherapy, as well as pre-treatment applications of CRISPR-Cas have been mentioned in detail.

Indexed as

Allogeneic T-cellCancer immunotherapyCAR T-cellCas9CRISPR-CasTCR T-cell

Identifiers

PMID32973401
PMCPMC7493839
OpenAlexW3086596089

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.