Evidence map›Paper›PMID 37445737›Full record

ArticleInternational journal of molecular sciences2023

Expression-Based Diagnosis, Treatment Selection, and Drug Development for Breast Cancer.

Qing Ye, Jiajia Wang, Barbara Ducatman, Rebecca A Raese, Jillian L Rogers, Ying-Wooi Wan, Chunlin Dong, Lindsay Padden, Elena N Pugacheva, Yong Qian and 1 more

Open access · goldAbstract read
In one paragraph

Article in International journal of molecular sciences, 2023. 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
0.5field-weighted citation impact, top 27% 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, 2 citations in OpenAlex.

  1. 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

11 authors at 2 institutions in 1 country.

Qing YeWest Virginia University Cancer Institute/Mary Babb Randolph Cancer Center, West Virginia University, Morgantown, WV 26506, USA.ORCID 0000-0002-1054-8796
Jiajia WangWest Virginia University Cancer Institute/Mary Babb Randolph Cancer Center, West Virginia University, Morgantown, WV 26506, USA.
Barbara DucatmanDepartment of Pathology, West Virginia University, Morgantown, WV 26506, USA.
Rebecca A RaeseWest Virginia University Cancer Institute/Mary Babb Randolph Cancer Center, West Virginia University, Morgantown, WV 26506, USA.
Jillian L RogersWest Virginia University Cancer Institute/Mary Babb Randolph Cancer Center, West Virginia University, Morgantown, WV 26506, USA.
Ying-Wooi WanWest Virginia University Cancer Institute/Mary Babb Randolph Cancer Center, West Virginia University, Morgantown, WV 26506, USA.
Chunlin DongWest Virginia University Cancer Institute/Mary Babb Randolph Cancer Center, West Virginia University, Morgantown, WV 26506, USA.
Lindsay PaddenWest Virginia University Cancer Institute/Mary Babb Randolph Cancer Center, West Virginia University, Morgantown, WV 26506, USA.
Elena N PugachevaWest Virginia University Cancer Institute/Mary Babb Randolph Cancer Center, West Virginia University, Morgantown, WV 26506, USA.
Yong QianPathology and Physiology Research Branch, National Institute for Occupational Safety and Health, Morgantown, WV 26505, USA.
Nancy Lan GuoWest Virginia University Cancer Institute/Mary Babb Randolph Cancer Center, West Virginia University, Morgantown, WV 26506, USA.ORCID 0000-0002-8050-6268
West Virginia University · USNational Institute for Occupational Safety and Health · US

Funding

Southeast Xlerator NetworkUT2GM130174 · NIGMS · XLERATEHEALTH, LLC · PI KRENTSEL, EUGENE, MCCLURE, IAN D · 2018 to 2020
$3.7M
A Novel Computational Framework for Individualized Clinical Decision-MakingR01LM009500 · NLM · WEST VIRGINIA UNIVERSITY · PI GUO, NANCY LAN · 2008 to 2010
$987k
NIH HHS 4UT2GM130174 I2PNIH HHS P20RR16440 & ARRA SupplementNIH HHS R01/R56LM009500
6 · The paper itself

Abstract

There is currently no gene expression assay that can assess if premalignant lesions will develop into invasive breast cancer. This study sought to identify biomarkers for selecting patients with a high potential for developing invasive carcinoma in the breast with normal histology, benign lesions, or premalignant lesions. A set of 26-gene mRNA expression profiles were used to identify invasive ductal carcinomas from histologically normal tissue and benign lesions and to select those with a higher potential for future cancer development (ADHC) in the breast associated with atypical ductal hyperplasia (ADH). The expression-defined model achieved an overall accuracy of 94.05% (AUC = 0.96) in classifying invasive ductal carcinomas from histologically normal tissue and benign lesions (

Indexed as

Breast NeoplasmsCarcinoma, Ductal, BreastCarcinoma, Intraductal, NoninfiltratingBreastDrug DevelopmentFemaleHomeodomain ProteinsHumansHyperplasiaPatient SelectionProto-Oncogene ProteinsHomeodomain ProteinsPBX2 protein, humanProto-Oncogene Proteinsatypical ductal hyperplasia (ADH)atypical ductal hyperplasia with cancer (ADHC)CRISPR-Cas9/RNAidiagnosisimmunohistochemistrytriple-negative breast cancer (TNBC)

Identifiers

PMID37445737
PMCPMC10342177
OpenAlexW4382068926

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.