Evidence map›Paper›PMID 38827528›Full record

ArticleFrontiers in cell and developmental biology2024

Digital droplet PCR analysis of organoids generated from mouse mammary tumors demonstrates proof-of-concept capture of tumor heterogeneity.

Katherine E Lake, Megan M Colonnetta, Clayton A Smith, Kaitlyn Saunders, Kenneth Martinez-Algarin, Sakshi Mohta, Jacob Pena, Heather L McArthur, Sangeetha M Reddy, Evanthia T Roussos Torres and 2 more

Abstract read
In one paragraph

Article in Frontiers in cell and developmental biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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

12 authors.

Katherine E LakeDepartment of Internal Medicine, Division of Hematology and Oncology, University of Texas Southwestern, Dallas, TX, United States.
Megan M ColonnettaHarold C. Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, TX, United States.
Clayton A SmithDepartment of Internal Medicine, Division of Hematology and Oncology, University of Texas Southwestern, Dallas, TX, United States.
Kaitlyn SaundersDepartment of Internal Medicine, Division of Hematology and Oncology, University of Texas Southwestern, Dallas, TX, United States.
Kenneth Martinez-AlgarinDepartment of Internal Medicine, Division of Hematology and Oncology, University of Texas Southwestern, Dallas, TX, United States.
Sakshi MohtaDepartment of Internal Medicine, Division of Hematology and Oncology, University of Texas Southwestern, Dallas, TX, United States.
Jacob PenaDepartment of Internal Medicine, Division of Hematology and Oncology, University of Texas Southwestern, Dallas, TX, United States.
Heather L McArthurDepartment of Internal Medicine, Division of Hematology and Oncology, University of Texas Southwestern, Dallas, TX, United States.
Sangeetha M ReddyDepartment of Internal Medicine, Division of Hematology and Oncology, University of Texas Southwestern, Dallas, TX, United States.
Evanthia T Roussos TorresDivision of Medical Oncology, Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States.
Elizabeth H ChenHarold C. Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, TX, United States.
Isaac S ChanDepartment of Internal Medicine, Division of Hematology and Oncology, University of Texas Southwestern, Dallas, TX, United States.

Funding

Decoding the mechanisms of cell-cell fusion - Renewal - 1R35GM136316 · NIGMS · UT SOUTHWESTERN MEDICAL CENTER · PI Elizabeth H Chen · 2020 to 2026
$3.1M
Using natural killer cells to prevent breast cancer metastasesK08CA270188 · NCI · UT SOUTHWESTERN MEDICAL CENTER · PI Isaac Chan · 2023 to 2026
$1.0M
NCI NIH HHS K08 CA270188NIGMS NIH HHS R35 GM136316
6 · The paper itself

Abstract

Breast cancer metastases exhibit many different genetic alterations, including copy number amplifications (CNA). CNA are genetic alterations that are increasingly becoming relevant to breast oncology clinical practice. Here we identify CNA in metastatic breast tumor samples using publicly available datasets and characterize their expression and function using a metastatic mouse model of breast cancer. Our findings demonstrate that our organoid generation can be implemented to study clinically relevant features that reflect the genetic heterogeneity of individual tumors.

Indexed as

breast cancerddPCRFGFR1heterogeneitymetastasis

Identifiers

PMID38827528
PMCPMC11140600

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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.