Evidence map›Paper›PMID 35242697›Full record

ArticleFrontiers in oncology2021

From Mouse to Human: Cellular Morphometric Subtype Learned From Mouse Mammary Tumors Provides Prognostic Value in Human Breast Cancer.

Hang Chang, Xu Yang, Jade Moore, Xiao-Ping Liu, Kuang-Yu Jen, Antoine M Snijders, Lin Ma, William Chou, Roberto Corchado-Cobos, Natalia García-Sancha and 4 more

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.3field-weighted citation impact, top 19% 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

5 citing papers in PubMed, 13 citations in OpenAlex.

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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

14 authors at 8 institutions in 3 countries.

Hang ChangBiological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, CA, United States.
Xu YangBiological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, CA, United States.
Jade MooreDepartment of Radiation Oncology and Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, United States.
Xiao-Ping LiuBiological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, CA, United States.
Kuang-Yu JenDepartment of Pathology and Laboratory Medicine, School of Medicine, University of California, Davis, Davis, CA, United States.
Antoine M SnijdersBiological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, CA, United States.
Lin MaDepartment of Radiation Oncology and Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, United States.
William ChouDepartment of Radiation Oncology and Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, United States.
Roberto Corchado-CobosInstituto de Biología Molecular y Celular del Cáncer, Universidad de Salamanca/Consejo Superior de Investigaciones Científicas (CSIC), Salamanca, Spain.
Natalia García-SanchaInstituto de Biología Molecular y Celular del Cáncer, Universidad de Salamanca/Consejo Superior de Investigaciones Científicas (CSIC), Salamanca, Spain.
Marina Mendiburu-EliçabeInstituto de Biología Molecular y Celular del Cáncer, Universidad de Salamanca/Consejo Superior de Investigaciones Científicas (CSIC), Salamanca, Spain.
Jesus Pérez-LosadaInstituto de Biología Molecular y Celular del Cáncer, Universidad de Salamanca/Consejo Superior de Investigaciones Científicas (CSIC), Salamanca, Spain.
Mary Helen Barcellos-HoffDepartment of Radiation Oncology and Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, United States.
Jian-Hua MaoBiological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, CA, United States.
Lawrence Berkeley National Laboratory · USUCSF Helen Diller Family Comprehensive Cancer Center · USUniversidad de Salamanca · ESUniversity of California, San Francisco · USCentro de Investigación del Cáncer · ESConsejo Superior de Investigaciones Científicas · ESNanjing Medical University · CNUniversity of California, Davis · US

Funding

Molecular and Cellular Mechanisms in CancerT32CA108462 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI GOGA, ANDREI · 2004 to 2024
$10.4M
Molecular and Therapeutic Basis of Morphometric Aberrations in Brain TumorsR01CA184476 · NCI · UNIVERSITY OF CALIF-LAWRENC BERKELEY LAB · PI CHANG, HANG · 2015 to 2019
$2.0M
NCI NIH HHS R01 CA184476NCI NIH HHS T32 CA108462
6 · The paper itself

Abstract

Mouse models of cancer provide a powerful tool for investigating all aspects of cancer biology. In this study, we used our recently developed machine learning approach to identify the cellular morphometric biomarkers (CMB) from digital images of hematoxylin and eosin (H&E) micrographs of orthotopic

Indexed as

cellular morphometric biomarkerscellular morphometric subtypeshuman breast cancersmetastasismouse mammary tumoroverall survival (OS)transfer learning

Identifiers

PMID35242697
PMCPMC8886672
OpenAlexW4211115457

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.