Evidence map›Paper›PMID 41659619›Full record

ArticlebioRxiv : the preprint server for biology2026

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 readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 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.
Sara J AdairDepartment of Surgery, University of Virginia, Charlottesville, VA, USA.
Olivia S PembertonDepartment of Biochemistry and Molecular Genetics.
Todd W BauerDepartment of Surgery, University of Virginia, Charlottesville, VA, USA.
David WottonDepartment of Biochemistry and Molecular Genetics.ORCID 0000-0002-4652-5350

Funding

Women's Oncology Program - WONP30CA044579 · NCI · UNIVERSITY OF VIRGINIA CHARLOTTESVILLE · PI Jay William FOX · 1987 to 2026
$72.1M
Systems Analysis of Stress-adapted Cancer Organelles (SASCO) CenterU54CA274499 · NCI · UNIVERSITY OF VIRGINIA · PI Kevin A Janes, Matthew J Lazzara · 2022 to 2026
$13.4M
The role of ACSS2 in colon cancerR01CA259571 · NCI · UNIVERSITY OF VIRGINIA · PI TODD W BAUER, David Wotton · 2022 to 2026
$2.3M
NCI NIH HHS P30 CA044579NCI NIH HHS R01 CA259571NCI NIH HHS U54 CA274499
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

Identifiers

PMID41659619
PMCPMC12873974

What OpenQuestion holds

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LicenceCC BY
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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.