Evidence map›Paper›PMID 28820179›Full record

ArticleCancer gene therapy2017

Effects of DCK knockdown on proliferation, apoptosis and tumorigenicity in vivo of cervical cancer HeLa cells.

Q-Y Shang, C-S Wu, H-R Gao

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Article in Cancer gene therapy, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

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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

5 citing papers in PubMed.

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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

3 authors.

Q-Y ShangDepartment of Clinical Laboratory, Ganyu District People's Hospital of Lianyungang City, Lianyungang, China.
C-S WuDepartment of Clinical Laboratory, Ganyu District People's Hospital of Lianyungang City, Lianyungang, China.
H-R GaoDepartment of Gynaecology, Ganyu District People's Hospital of Lianyungang City, Lianyungang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The present study explored the effect that deoxycytidine kinase (DCK) knockdown had on proliferation, apoptosis and tumorigenicity in vivo of cervical cancer HeLa cells. Human cervical cancer HeLa cells that had received no prior treatment were selected from the HeLa group. The HeLa-negative control (NC) group consisted of cells that had undergone an empty vector treatment, and finally the HeLa-short hairpin RNA (shRNA) group included cells that were treated by means of shRNA-DCK expression. DCK expressions were evaluated by quantitative real-time polymerase chain reaction in addition to western blotting assays. Cell proliferation was estimated using the Cell Counting Kit-8 (CCK-8) assay and cell cycle progression. Cell apoptosis was determined by flow cytometry. BALB/c nude mice (n=24) were selected to establish transplanted tumor models, with gross tumor volume measured every 3 days. The results in vitro were as follows: compared with the HeLa group, the HeLa-shRNA group exhibited downregulation of DCK expression and inhibition of cell proliferation at 48, 72 and 96 h. Additionally, more cells in the HeLa-shRNA group were arrested in G0/G1 stage and less in S and G2/M stages, as well as in promotion of cell apoptosis. In vivo results are as follows: when comparing the HeLa and HeLa-NC groups, the gross tumor volume of the transplanted tumor in nude mice in the HeLa-shRNA group was found to have decreased in 13, 16, 19 and 22 days. Based on these findings, our study suggests that DCK knockdown facilitates apoptosis while inhibiting proliferation and tumorigenicity in vivo of cervical cancer HeLa cells.

Indexed as

Uterine Cervical NeoplasmsAnimalsApoptosisCell ProliferationDeoxycytidine KinaseFemaleGene Expression Regulation, EnzymologicGene Expression Regulation, NeoplasticGene Knockdown TechniquesHeLa CellsHeterograftsHumansMiceMice, Inbred BALB CMice, NudeNeoplasm ProteinsDeoxycytidine KinaseNeoplasm Proteins

Identifiers

PMID28820179

What OpenQuestion holds

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Registered trials

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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.