Evidence map›Paper›PMID 37456987›Full record

ArticleBreast cancer (Dove Medical Press)2023

Unraveling the Pivotal Network of Ultrasound and Somatic Mutations in Triple-Negative and Non-Triple-Negative Breast Cancer.

Yunxia Huang, Yi Guo, Qin Xiao, Shuyu Liang, Qiang Yu, Lang Qian, Jin Zhou, Jian Le, Yuchen Pei, Lei Wang and 3 more

Open access · goldAbstract read
In one paragraph

Article in Breast cancer (Dove Medical Press), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.4field-weighted citation impact, top 17% 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

4 citing papers in PubMed, 6 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. 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 2 institutions in 1 country.

Yunxia Huang *Department of Ultrasonography, Fudan University Shanghai Cancer Center, Shanghai Medical College, Fudan University, Shanghai, People's Republic of China.
Yi Guo *Department of Radiology, Fudan University Shanghai Cancer Center, Fudan University, Shanghai, People's Republic of China.
Qin Xiao *Department of Electronic Engineering, Fudan University and Key Laboratory of Medical Imaging Computing and Computer Assisted Intervention of Shanghai, Shanghai, People's Republic of China.ORCID 0000-0002-5587-2928
Shuyu LiangDepartment of Radiology, Fudan University Shanghai Cancer Center, Fudan University, Shanghai, People's Republic of China.
Qiang YuDepartment of Breast Surgery, Fudan University Shanghai Cancer Center, Fudan University, Shanghai, People's Republic of China.
Lang QianDepartment of Ultrasonography, Fudan University Shanghai Cancer Center, Shanghai Medical College, Fudan University, Shanghai, People's Republic of China.
Jin ZhouDepartment of Ultrasonography, Fudan University Shanghai Cancer Center, Shanghai Medical College, Fudan University, Shanghai, People's Republic of China.
Jian LeDepartment of Ultrasonography, Fudan University Shanghai Cancer Center, Shanghai Medical College, Fudan University, Shanghai, People's Republic of China.
Yuchen PeiPrecision Cancer Medical Center Affiliated to Fudan University Shanghai Cancer Center, Fudan University, Shanghai, People's Republic of China.
Lei WangDepartment of Breast Surgery, Fudan University Shanghai Cancer Center, Fudan University, Shanghai, People's Republic of China.
Cai ChangDepartment of Ultrasonography, Fudan University Shanghai Cancer Center, Shanghai Medical College, Fudan University, Shanghai, People's Republic of China.
Sheng ChenDepartment of Breast Surgery, Fudan University Shanghai Cancer Center, Fudan University, Shanghai, People's Republic of China.
Shichong ZhouDepartment of Ultrasonography, Fudan University Shanghai Cancer Center, Shanghai Medical College, Fudan University, Shanghai, People's Republic of China.
Fudan University Shanghai Cancer Center · CNShanghai Medical College of Fudan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: The emergence of genomic targeted therapy has improved the prospects of treatment for breast cancer (BC). However, genetic testing relies on invasive and sophisticated procedures. Patients and Methods: Here, we performed ultrasound (US) and target sequencing to unravel the possible association between US radiomics features and somatic mutations in TNBC (n=83) and non-TNBC (n=83) patients. Least absolute shrinkage and selection operator (Lasso) were utilized to perform radiomic feature selection. The Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis was utilized to identify the signaling pathways associated with radiomic features. Results: Thirteen differently represented radiomic features were identified in TNBC and non-TNBC, including tumor shape, textual, and intensity features. The US radiomic-gene pairs were differently exhibited between TNBC and non-TNBC. Further investigation with KEGG verified radiomic-pathway (ie, JAK-STAT, MAPK, Ras, Wnt, microRNAs in cancer, PI3K-Akt) associations in TNBC and non-TNBC. Conclusion: The pivotal network provided the connections of US radiogenomic signature and target sequencing for non-invasive genetic assessment of precise BC treatment.

Indexed as

radiomicssignaling pathwaysomatic mutationtriple-negative breast cancer

Identifiers

PMID37456987
PMCPMC10349575
OpenAlexW4383955250

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.