Evidence map›Paper›PMID 23874578›Full record

ArticlePloS one2013

Cancer stem cell-like side population cells in clear cell renal cell carcinoma cell line 769P.

Bin Huang, Yi Jun Huang, Zhi Jun Yao, Xu Chen, Sheng Jie Guo, Xiao Peng Mao, Dao Hu Wang, Jun Xing Chen, Shao Peng Qiu

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed
3.5field-weighted citation impact, top 7% 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

32 citing papers in PubMed, 44 citations in OpenAlex.

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  11. Biomarker discovery for renal cancer stem cells.The journal of pathology. Clinical research · 2018
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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

9 authors at 2 institutions in 1 country.

Bin HuangDepartment of Urology, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China.
Yi Jun Huang
Zhi Jun Yao
Xu Chen
Sheng Jie Guo
Xiao Peng Mao
Dao Hu Wang
Jun Xing Chen
Shao Peng Qiu
Sun Yat-sen University · CNThe First Affiliated Hospital, Sun Yat-sen University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Although cancers are widely considered to be maintained by stem cells, the existence of stem cells in renal cell carcinoma (RCC) has seldom been reported, in part due to the lack of unique surface markers. We here identified cancer stem cell-like cells with side population (SP) phenotype in five human RCC cell lines. Flow cytometry analysis revealed that 769P, a human clear cell RCC cell line, contained the largest amount of SP cells as compared with other four cell lines. These 769P SP cells possessed characteristics of proliferation, self-renewal, and differentiation, as well as strong resistance to chemotherapy and radiotherapy that were possibly related to the ABCB1 transporter. In vivo experiments with serial tumor transplantation in mice also showed that 769P SP cells formed tumors in NOD/SCID mice. Taken together, these results indicate that 769P SP cells have the properties of cancer stem cells, which may play important roles in tumorigenesis and therapy-resistance of RCC.

Indexed as

AnimalsATP Binding Cassette Transporter, Subfamily BATP Binding Cassette Transporter, Subfamily B, Member 1Carcinoma, Renal CellCell DifferentiationCell Growth ProcessesCell Line, TumorCell Transformation, NeoplasticDrug Resistance, NeoplasmFemaleHumansKidney NeoplasmsMiceMice, Inbred NODMice, SCIDNeoplasm TransplantationABCB1 protein, humanATP Binding Cassette Transporter, Subfamily BATP Binding Cassette Transporter, Subfamily B, Member 1

Identifiers

PMID23874578
PMCPMC3708929
OpenAlexW2008912323

What OpenQuestion holds

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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.