Evidence map›Paper›PMID 25521454›Full record

ArticleThe Journal of investigative dermatology2015

Assessment of cancer cell line representativeness using microarrays for Merkel cell carcinoma.

Kenneth Daily, Amy Coxon, Jonathan S Williams, Chyi-Chia R Lee, Daniel G Coit, Klaus J Busam, Isaac Brownell

Open access · greenAbstract read
In one paragraph

Article in The Journal of investigative dermatology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed
0.6field-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

33 citing papers in PubMed, 47 citations in OpenAlex.

  1. Article
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  5. Searching for biomarkers to help distinguish Merkel cell carcinoma from cutaneous small cell lung cancer with gene expression analysis.Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI) · 2024
    Article
  6. Mycophenolate mofetil inhibits Merkel cell carcinoma growth.The British journal of dermatology · 2024
    Article
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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 2 institutions in 1 country.

Kenneth DailyDermatology Branch, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA.
Amy CoxonDermatology Branch, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA.
Jonathan S WilliamsDermatology Branch, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA.
Chyi-Chia R LeeLaboratory of Pathology, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA.
Daniel G CoitDepartment of Surgery, Memorial Sloan Kettering Cancer Center, New York, New York, USA.
Klaus J BusamDepartment of Pathology, Memorial Sloan Kettering Cancer Center, New York, New York, USA.
Isaac BrownellDermatology Branch, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA; Dermatology Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York, USA. Electronic address: isaac.brownell@nih.gov.
National Institutes of Health · USMemorial Sloan Kettering Cancer Center · US

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI Nicholas D Socci · 1985 to 2026
$347.4M
Molecular pathogenesis of Merkel cell carcinomaZIABC011394 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI BROWNELL, ISAAC · 2011 to 2021
$6.8M
Intramural NIH HHS ZIA BC011394NCI NIH HHS P30 CA008748
6 · The paper itself

Abstract

When using cell lines to study cancer, phenotypic similarity to the original tumor is paramount. Yet, little has been done to characterize how closely Merkel cell carcinoma (MCC) cell lines model native tumors. To determine their similarity to MCC tumor samples, we characterized MCC cell lines via gene expression microarrays. Using whole transcriptome gene expression signatures and a computational bioinformatic approach, we identified significant differences between variant cell lines (UISO, MCC13, and MCC26) and fresh frozen MCC tumors. Conversely, the classic WaGa and Mkl-1 cell lines more closely represented the global transcriptome of MCC tumors. When compared with publicly available cancer lines, WaGa and Mkl-1 cells were similar to other neuroendocrine tumors, but the variant cell lines were not. WaGa and Mkl-1 cells grown as xenografts in mice had histological and immunophenotypical features consistent with MCC, whereas UISO xenograft tumors were atypical for MCC. Spectral karyotyping and short tandem repeat analysis of the UISO cells matched the original cell line's description, ruling out contamination. Our results validate the use of transcriptome analysis to assess the cancer cell line representativeness and indicate that UISO, MCC13, and MCC26 cell lines are not representative of MCC tumors, whereas WaGa and Mkl-1 more closely model MCC.

Indexed as

Gene Expression Regulation, NeoplasticAnimalsCarcinoma, Merkel CellCell Line, TumorCluster AnalysisFemaleGene Expression ProfilingHumansImmunohistochemistryKaryotypingLung NeoplasmsMiceMice, Inbred NODMicrosatellite RepeatsNeoplasm TransplantationOligonucleotide Array Sequence Analysis

Identifiers

PMID25521454
PMCPMC4366303
OpenAlexW2163527772

What OpenQuestion holds

Textmetadata
LicenceTDM
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.