Evidence map›Paper›PMID 42879502›Full record

ArticlePloS one2026

A simple method for analyzing competitive growth of multiple cell types in xenograft tumors.

Tiffany A Melhuish, Sara J Adair, Olivia S Pemberton, Todd W Bauer, David Wotton

Abstract read
In one paragraph

Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Tiffany A MelhuishDepartment of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, Virginia, United States of America.
Sara J AdairDepartment of Surgery, University of Virginia, Charlottesville, Virginia, United States of America.
Olivia S PembertonDepartment of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, Virginia, United States of America.
Todd W BauerDepartment of Surgery, University of Virginia, Charlottesville, Virginia, United States of America.ORCID https://orcid.org/0000-0002-9516-1848
David WottonDepartment of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, Virginia, United States of America.ORCID https://orcid.org/0000-0002-4652-5350

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Low take rates and inter-tumor variability in growth rates can limit the effectiveness of mouse xenograft models when comparing between groups. To address this problem we developed a simple method to compare multiple cell types within a single mixed xenograft. Individual cell lines or clones were transduced with a lentiviral vector that includes a unique PCR tag, allowing the use of qPCR to determine the proportion of each tagged cell type within a mixed xenograft tumor. We generated vectors with six distinct PCR tags, and two different selectable markers, and have optimized the approach for determining their relative proportions within a mix. An initial pre-amplification step is used to increase the amount of material for subsequent qPCR reactions. This also removes the bulk of the genomic DNA, increasing the specificity of the qPCR step. Samples are then used for qPCR with specific pairs of primers that distinguish between each of the individual PCR tags, and the relative proportion of each tag is determined relative to that in the starting mix. We have tested this approach for in vitro growth of mixed cell cultures and in an orthotopic cecal xenograft model using a human colon cancer cell line. Since each individual tumor is initiated with a mix of cells, multiple tumors within a single animal can be analyzed separately, and overall tumor size is not important. Similarly, multiple metastatic lesions from the same animal can be analyzed individually. Thus, each tumor provides a direct comparison between individually tagged cell lines or clones. This low throughput "bar-coding" approach is simple and cost effective and has the potential to reduce the number of animals needed for xenograft experiments.

Indexed as

Colonic NeoplasmsAnimalsCell Line, TumorCell ProliferationGenetic VectorsHeterograftsHumansLentivirusMiceMice, NudePolymerase Chain ReactionTransplantation, Heterologous

Identifiers

PMID42879502
PMCPMC13671648

What OpenQuestion holds

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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.