Evidence map›Paper›PMID 35875052›Full record

ArticleNAR cancer2022

DNA barcoded competitive clone-initiating cell analysis reveals novel features of metastatic growth in a cancer xenograft model.

Syed Mohammed Musheer Aalam, Xiaojia Tang, Jianning Song, Upasana Ray, Stephen J Russell, S John Weroha, Jamie Bakkum-Gamez, Viji Shridhar, Mark E Sherman, Connie J Eaves and 3 more

Open access · goldAbstract read
In one paragraph

Article in NAR cancer, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.4field-weighted citation impact, top 47% 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

1 citing paper in PubMed, 4 citations in OpenAlex.

  1. Clonal tracking in cancer and metastasis.Cancer metastasis reviews · 2024
    Review
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

13 authors at 4 institutions in 2 countries.

Syed Mohammed Musheer AalamDivision of Experimental Pathology and Laboratory Medicine, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA.
Xiaojia TangDepartment of Health Sciences Research, Mayo Clinic, Rochester, MN, USA.
Jianning SongDivision of Experimental Pathology and Laboratory Medicine, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA.
Upasana RayDivision of Experimental Pathology and Laboratory Medicine, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA.
Stephen J RussellDepartment of Molecular Medicine, Mayo Clinic, MN 55905, USA.
S John WerohaDepartment of Oncology, Mayo Clinic, Rochester, MN, USA.
Jamie Bakkum-GamezDivision of Gynecologic Oncology Surgery, Department of Obstetrics and Gynecology, Mayo Clinic, Rochester, MN, USA.
Viji ShridharDivision of Experimental Pathology and Laboratory Medicine, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA.
Mark E ShermanDepartment of Quantitative Health Sciences, Mayo Clinic, Jacksonville, FL, USA.
Connie J EavesTerry Fox Laboratory, British Columbia Cancer Research Institute, Vancouver, BC, Canada.
David J H F KnappDivision of Experimental Pathology and Laboratory Medicine, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA.
Krishna R KalariDepartment of Health Sciences Research, Mayo Clinic, Rochester, MN, USA.
Nagarajan KannanDivision of Experimental Pathology and Laboratory Medicine, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA.ORCID https://orcid.org/0000-0002-8825-2178
Mayo Clinic · USMayo Clinic in Florida · USMayo Clinic in Arizona · USUniversity of British Columbia · CA

Funding

Women's Cancer ProgramP30CA015083 · NCI · MAYO CLINIC ROCHESTER · PI AKHILESH PANDEY · 1985 to 2026
$151.3M
NCI NIH HHS P30 CA015083
6 · The paper itself

Abstract

A problematic feature of many human cancers is a lack of understanding of mechanisms controlling organ-specific patterns of metastasis, despite recent progress in identifying many mutations and transcriptional programs shown to confer this potential. To address this gap, we developed a methodology that enables different aspects of the metastatic process to be comprehensively characterized at a clonal resolution. Our approach exploits the application of a computational pipeline to analyze and visualize clonal data obtained from transplant experiments in which a cellular DNA barcoding strategy is used to distinguish the separate clonal contributions of two or more competing cell populations. To illustrate the power of this methodology, we demonstrate its ability to discriminate the metastatic behavior in immunodeficient mice of a well-established human metastatic cancer cell line and its co-transplanted

Identifiers

PMID35875052
PMCPMC9303272
OpenAlexW4286424215

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.