Evidence map›Paper›PMID 32782610›Full record

ArticleOncology letters2020

Selection of a malignant subpopulation from a colorectal cancer cell line.

Pei-Lun Lai, Ting-Chun Chen, Chun-Yen Feng, Hsuan Lin, Chi-Hou Ng, Yun Chen, Michael Hsiao, Jean Lu, Hsiao-Chun Huang

Open access · diamondAbstract read
In one paragraph

Article in Oncology letters, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.1field-weighted citation impact, top 55% 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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. 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

9 authors at 2 institutions in 1 country.

Pei-Lun LaiInstitute of Molecular and Cellular Biology, College of Life Science, National Taiwan University, Taipei 10617, Taiwan, R.O.C.
Ting-Chun ChenInstitute of Molecular and Cellular Biology, College of Life Science, National Taiwan University, Taipei 10617, Taiwan, R.O.C.
Chun-Yen FengInstitute of Molecular and Cellular Biology, College of Life Science, National Taiwan University, Taipei 10617, Taiwan, R.O.C.
Hsuan LinGenomics Research Center, Academia Sinica, Taipei 11529, Taiwan, R.O.C.
Chi-Hou NgGenomics Research Center, Academia Sinica, Taipei 11529, Taiwan, R.O.C.
Yun ChenInstitute of Molecular and Cellular Biology, College of Life Science, National Taiwan University, Taipei 10617, Taiwan, R.O.C.
Michael HsiaoGenomics Research Center, Academia Sinica, Taipei 11529, Taiwan, R.O.C.
Jean LuGenomics Research Center, Academia Sinica, Taipei 11529, Taiwan, R.O.C.
Hsiao-Chun HuangInstitute of Molecular and Cellular Biology, College of Life Science, National Taiwan University, Taipei 10617, Taiwan, R.O.C.
National Taiwan University · TWGenomics Research Center, Academia Sinica · TW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Colorectal cancer (CRC) is a leading cause of cancer-associated mortality worldwide; therefore, there is an emerging need for novel experimental models that allow for the identification and validation of biomarkers for CRC-specific progression. In the present study, a repeated sphere-forming assay was used as a strategy to select a malignant subpopulation from a CRC cell line, namely HCT116. The assay was validated by confirming that canonical stemness markers were upregulated in the sphere state at every generation of the selection assay. The resulting subpopulation, after eight rounds of selection, exhibited increased sphere-forming capacity

Indexed as

cell linecolorectal cancerDPEP1malignant subpopulationsphere-forming

Identifiers

PMID32782610
PMCPMC7399770
OpenAlexW3042204919

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.