Evidence map›Paper›PMID 35879685›Full record

ArticleBMC cancer2022

Nonviral mcDNA-mediated bispecific CAR T cells kill tumor cells in an experimental mouse model of hepatocellular carcinoma.

Hezhi Wang, Xiaoxiao Wang, Xueshuai Ye, Yi Ju, Nana Cao, Shuqi Wang, Jianhui Cai

Open access · goldAbstract read
In one paragraph

Article in BMC cancer, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.8field-weighted citation impact, top 13% 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

9 citing papers in PubMed, 19 citations in OpenAlex.

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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

7 authors at 7 institutions in 1 country.

Hezhi Wang *Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
Xiaoxiao Wang *Department of Endocrinology, People's Hospital of Longhua, Shenzhen, 518109, China.
Xueshuai YeDepartment of Surgery, Hebei Medical University, Shijiazhuang, 050000, China.
Yi JuDepartment of Medicine, Medical College of Hebei University of Engineering, Handan, 056002, China.
Nana CaoCollege of Life Sciences, Hebei Normal University, Shijiazhuang, 050000, China.
Shuqi WangDepartment of Anorectal Surgery, Shijiazhuang Traditional Chinese Medicine Hospital, Shijiazhuang, 050000, China.
Jianhui CaiDepartment of Surgery, Hebei Medical University, Shijiazhuang, 050000, China. jianhuicai201@163.com.
Hebei General Hospital · CNHebei Medical University · CNHebei Normal University · CNHebei University of Engineering · CNJining Traditional Chinese Medicine Hospital · CNShenZhen People’s Hospital · CNZhongshan Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHepatocellular carcinoma (HCC) is one of the most common cancers worldwide and the adoptive immunotherapy of which is worth studying. CD133, a kind of cancer stem cell (CSC) antigen, together with glypican-3 (GPC3) has been proved to be highly expressed in HCC cells and both of them are used as targets to generate chimeric antigen receptor (CAR) T cells. But there are limitations like "off-target" toxicity, low transfection efficacy and weak antitumor ability in CAR T cells treatment.

methodsThe peripheral blood was acquired from healthy donors and T cells were separated by density-gradient centrifugation. We used an electroporation system to deliver anti-CD133 and anti-GPC3 single chain Fragment variable (scFv) structures as target genes into the T cells. The cell membrane was opened by the momentary electric current effect, and the target gene was delivered into the cell by non-viral minicircle DNA (mcDNA) vector. The flow cytometry and western blot assays were used to detect whether the two scFv were simultaneously transfected and the transfection efficacy of this bispecific CAR T cell generation method. We respectively detected the in vitro and in vivo tumor-suppression efficacy of CAR T cells through the CCK-8 assays and the HCC xenograft mice models. The CoG133-CAR T cells containing both CD133 and GPC3 antigen recognition sites were the effector cells. CD133-CAR T cells and GPC3-CAR T cells were defined as single-targeted control groups, normal T and mock T cells were defined as blank control groups.

resultsThe mcDNA vector accommodated two target gene structures successfully transfected to generate bispecific CAR T cells. The detection methods on gene level and protein level confirmed that CoG133-CAR T cells had considerable transfection efficiency and exhibited both antigen-binding capacity of CD133 and GPC3. Compared to single-targeted CAR T cells or control T cells, CoG133-CAR T cells performed enhanced eliminated efficacy against CD133 and GPC3 double-positive HCC cell line in vitro and HCC xenograft mice in vivo. Hematoxylin and eosin (H&E) staining indicated no fatal "off-target" combination existed on CoG133-CAR T cells and major organs.

conclusionOur study suggests that it is with higher efficiency and more safety to prepare bispecific CAR T cells through non-viral mcDNA vectors. CoG133-CAR T cells have enhanced tumor-suppression capacity through dual antigen recognition and internal activation. It provides an innovative strategy for CAR T therapy of HCC, even solid tumors.

Indexed as

Carcinoma, HepatocellularLiver NeoplasmsAnimalsCell Line, TumorDisease Models, AnimalDNAGlypicansHumansImmunotherapy, AdoptiveMiceT-LymphocytesXenograft Model Antitumor AssaysDNAGlypicansGPC3 protein, humanBispecific CAR T cellsCancer immunotherapyCancer stem cellsHepatocellular carcinomaNon-viral mcDNA vector

Identifiers

PMID35879685
PMCPMC9310485
OpenAlexW4287307426

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.