Evidence map›Paper›PMID 26208323›Full record

ArticlePloS one2015

Improved Methods to Generate Spheroid Cultures from Tumor Cells, Tumor Cells & Fibroblasts or Tumor-Fragments: Microenvironment, Microvesicles and MiRNA.

Zheng Lao, Catherine J Kelly, Xiang-Yang Yang, W Timothy Jenkins, Erik Toorens, Tapan Ganguly, Sydney M Evans, Cameron J Koch

Abstract read
In one paragraph

Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing 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

21 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
  4. Article
  5. Microfluidic Modulation of Microvasculature in Microdissected Tumors.bioRxiv : the preprint server for biology · 2024
    Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. Article
  11. Review
  12. Article
  13. Review
  14. Review
  15. Modeling neoplastic disease with spheroids and organoids.Journal of hematology & oncology · 2020
    Review
  16. Review
  17. Article
  18. Article
  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

8 authors.

Zheng LaoUniversity of Pennsylvania, Perelman School of Medicine, Dept Radiation Oncology, Philadelphia, Pennsylvania, United States of America; Fudan University, Eye & ENT Hospital, Dept Radiation Oncology, Shanghai, China.
Catherine J KellyOxford University, Gray Institute for Radiation Oncology, Oxford, United Kingdom.
Xiang-Yang YangUniversity of Pennsylvania, Perelman School of Medicine, Dept Radiation Oncology, Philadelphia, Pennsylvania, United States of America.
W Timothy JenkinsUniversity of Pennsylvania, Perelman School of Medicine, Dept Radiation Oncology, Philadelphia, Pennsylvania, United States of America.
Erik ToorensUniversity of Pennsylvania, Perelman School of Medicine, Penn Genomics Analysis Core, Philadelphia, Pennsylvania, United States of America.
Tapan GangulyUniversity of Pennsylvania, Perelman School of Medicine, Penn Genomics Analysis Core, Philadelphia, Pennsylvania, United States of America.
Sydney M EvansUniversity of Pennsylvania, Perelman School of Medicine, Dept Radiation Oncology, Philadelphia, Pennsylvania, United States of America.
Cameron J KochUniversity of Pennsylvania, Perelman School of Medicine, Dept Radiation Oncology, Philadelphia, Pennsylvania, United States of America.

Funding

UNIVERSITY OF PENNSYLVANIA CAN CTR SUPPORT GRANTP30CA016520 · NCI · UNIVERSITY OF PENNSYLVANIA · PI SHELLEY L BERGER · 1985 to 2026
$222.3M
Cancer Research UK C48264/A16614NCI NIH HHS P30 CA016520
6 · The paper itself

Abstract

Diagnostic and prognostic indicators are key components to achieve the goal of personalized cancer therapy. Two distinct approaches to this goal include predicting response by genetic analysis and direct testing of possible therapies using cultures derived from biopsy specimens. Optimally, the latter method requires a rapid assessment, but growing xenograft tumors or developing patient-derived cell lines can involve a great deal of time and expense. Furthermore, tumor cells have much different responses when grown in 2D versus 3D tissue environments. Using a modification of existing methods, we show that it is possible to make tumor-fragment (TF) spheroids in only 2-3 days. TF spheroids appear to closely model characteristics of the original tumor and may be used to assess critical therapy-modulating features of the microenvironment such as hypoxia. A similar method allows the reproducible development of spheroids from mixed tumor cells and fibroblasts (mixed-cell spheroids). Prior literature reports have shown highly variable development and properties of mixed-cell spheroids and this has hampered the detailed study of how individual tumor-cell components interact. In this study, we illustrate this approach and describe similarities and differences using two tumor models (U87 glioma and SQ20B squamous-cell carcinoma) with supporting data from additional cell lines. We show that U87 and SQ20B spheroids predict a key microenvironmental factor in tumors (hypoxia) and that SQ20B cells and spheroids generate similar numbers of microvesicles. We also present pilot data for miRNA expression under conditions of cells, tumors, and TF spheroids.

Indexed as

Spheroids, CellularBiomarkersCell Line, TumorFibroblastsHumansMicroRNAsNeoplasmsNeovascularization, PathologicStromal CellsTumor Cells, CulturedTumor MicroenvironmentBiomarkersMicroRNAs

Identifiers

PMID26208323
PMCPMC4514828

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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.