Evidence map›Paper›PMID 26043652›Full record

ArticleBMC medical genomics2015

Relating hepatocellular carcinoma tumor samples and cell lines using gene expression data in translational research.

Bin Chen, Marina Sirota, Hua Fan-Minogue, Dexter Hadley, Atul J Butte

Abstract read
In one paragraph

Article in BMC medical genomics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers.

0numbers the graph read from it
0cells of the map it votes in
51citing 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

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

51 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Hepatocellular carcinoma drug resistance models.Cancer cell international · 2025
    Review
  5. Article
  6. Review
  7. Article
  8. Article
  9. Research advances of tissue-derived extracellular vesicles in cancers.Journal of cancer research and clinical oncology · 2024
    Review
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Investigating the suitability ofFrontiers in cell and developmental biology · 2023
    Article
  17. Review
  18. Review
  19. Review
  20. 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

5 authors.

Bin Chen
Marina Sirota
Hua Fan-Minogue
Dexter Hadley
Atul J Butte

Funding

POSTDOCTORAL TRAINING IN MEDICAL INFORMATION SCIENCEST15LM007033 · NLM · STANFORD UNIVERSITY · PI SYLVIA KATINA PLEVRITIS · 1985 to 2026
$25.5M
Repositioning drugs for the treatment of small cell lung cancerR01GM079719 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI BUTTE, ATUL J · 2006 to 2015
$4.4M
Crowd-sourcing A STAR Functional Genomic Characterization of Cancer with Open Big DataUH2CA203792 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI HADLEY, DEXTER D · 2016 to 2017
$634k
NCI NIH HHS UH2 CA203792NIGMS NIH HHS R01 GM079719NLM NIH HHS T15 LM007033
6 · The paper itself

Abstract

Cancer cell lines are used extensively to study cancer biology and to test hypotheses in translational research. The relevance of cell lines is dependent on how closely they resemble the tumors being studied. Relating tumors and cell lines, and recognizing their similarities and differences are thus very important for translational research. Rapid advances in genomics have led to the generation of large volumes of genomic and transcriptomic data for a diverse set of primary cancer samples, normal tissue samples and cancer cell lines. Hepatocellular Carcinoma (HCC) is one of the most common tumors worldwide, with high occurrence in Asia and sub-Saharan regions. The current effective treatments of HCC remain limited. In this work, we compared the gene expression measurements of 200 HCC tumor samples from The Cancer Genome Atlas and over 1000 cancer cell lines including 25 HCC cancer cell lines from Cancer Cell Line Encyclopedia. We showed that the HCC tumor samples correlate closely with HCC cell lines in comparison to cell lines derived from other tumor types. We further demonstrated that the most commonly used HCC cell lines resemble HCC tumors, while we identified nearly half of the cell lines that do not resemble primary tumors. Interestingly, a substantial number of genes that are critical for disease development or drug response are either expressed at low levels or absent among highly correlated cell lines; additional attention should be paid to these genes in translational research. Our study will be used to guide the selection of HCC cell lines and pinpoint the specific genes that are differentially expressed in either tumors or cell lines.

Indexed as

Gene Expression Regulation, NeoplasticTranslational Research, BiomedicalCarcinoma, HepatocellularCell Line, TumorGene OntologyHumansLiver NeoplasmsStatistics, Nonparametric

Identifiers

PMID26043652
PMCPMC4460709

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.