Evidence map›Paper›PMID 28708462›Full record

ArticleRadiology2017

Heterogeneous Enhancement Patterns of Tumor-adjacent Parenchyma at MR Imaging Are Associated with Dysregulated Signaling Pathways and Poor Survival in Breast Cancer.

Jia Wu, Bailiang Li, Xiaoli Sun, Guohong Cao, Daniel L Rubin, Sandy Napel, Debra M Ikeda, Allison W Kurian, Ruijiang Li

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

Article in Radiology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 76 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
76citing papers in PubMed, 4 pooled it
9.0field-weighted citation impact, top 2% 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

76 citing papers in PubMed, 4 syntheses or guidelines pooled it, 120 citations in OpenAlex.

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  4. TCGA-TCIA Impact on Radiogenomics Cancer Research: A Systematic Review.International journal of molecular sciences · 2019
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  18. The impact of radiogenomics on breast cancer.American journal of cancer research · 2025
    Review
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16 more citing papers are in PubMed but not listed here.

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

9 authors at 4 institutions in 2 countries.

Jia WuFrom the Department of Radiation Oncology (J.W., B.L., R.L.), Department of Radiology (D.L.R., S.N., D.M.I.), Department of Biomedical Data Science and Medicine (Biomedical Informatics Research) (D.L.R.), Department of Medicine (A.W.K.), Department of Health Research and Policy (A.W.K.), and Stanford Cancer Institute (A.W.K., R.L.), Stanford University School of Medicine, 1070 Arastradero Rd, Stanford, CA 94305; Department of Radiotherapy, the First Affiliated Hospital of Zhejiang University, Hangzhou, Zhejiang, China (X.S.); and Department of Radiology, International Hospital of Zhejiang University, Hangzhou, Zhejiang, China (G.C.).
Bailiang LiFrom the Department of Radiation Oncology (J.W., B.L., R.L.), Department of Radiology (D.L.R., S.N., D.M.I.), Department of Biomedical Data Science and Medicine (Biomedical Informatics Research) (D.L.R.), Department of Medicine (A.W.K.), Department of Health Research and Policy (A.W.K.), and Stanford Cancer Institute (A.W.K., R.L.), Stanford University School of Medicine, 1070 Arastradero Rd, Stanford, CA 94305; Department of Radiotherapy, the First Affiliated Hospital of Zhejiang University, Hangzhou, Zhejiang, China (X.S.); and Department of Radiology, International Hospital of Zhejiang University, Hangzhou, Zhejiang, China (G.C.).
Xiaoli SunFrom the Department of Radiation Oncology (J.W., B.L., R.L.), Department of Radiology (D.L.R., S.N., D.M.I.), Department of Biomedical Data Science and Medicine (Biomedical Informatics Research) (D.L.R.), Department of Medicine (A.W.K.), Department of Health Research and Policy (A.W.K.), and Stanford Cancer Institute (A.W.K., R.L.), Stanford University School of Medicine, 1070 Arastradero Rd, Stanford, CA 94305; Department of Radiotherapy, the First Affiliated Hospital of Zhejiang University, Hangzhou, Zhejiang, China (X.S.); and Department of Radiology, International Hospital of Zhejiang University, Hangzhou, Zhejiang, China (G.C.).
Guohong CaoFrom the Department of Radiation Oncology (J.W., B.L., R.L.), Department of Radiology (D.L.R., S.N., D.M.I.), Department of Biomedical Data Science and Medicine (Biomedical Informatics Research) (D.L.R.), Department of Medicine (A.W.K.), Department of Health Research and Policy (A.W.K.), and Stanford Cancer Institute (A.W.K., R.L.), Stanford University School of Medicine, 1070 Arastradero Rd, Stanford, CA 94305; Department of Radiotherapy, the First Affiliated Hospital of Zhejiang University, Hangzhou, Zhejiang, China (X.S.); and Department of Radiology, International Hospital of Zhejiang University, Hangzhou, Zhejiang, China (G.C.).
Daniel L RubinFrom the Department of Radiation Oncology (J.W., B.L., R.L.), Department of Radiology (D.L.R., S.N., D.M.I.), Department of Biomedical Data Science and Medicine (Biomedical Informatics Research) (D.L.R.), Department of Medicine (A.W.K.), Department of Health Research and Policy (A.W.K.), and Stanford Cancer Institute (A.W.K., R.L.), Stanford University School of Medicine, 1070 Arastradero Rd, Stanford, CA 94305; Department of Radiotherapy, the First Affiliated Hospital of Zhejiang University, Hangzhou, Zhejiang, China (X.S.); and Department of Radiology, International Hospital of Zhejiang University, Hangzhou, Zhejiang, China (G.C.).
Sandy NapelFrom the Department of Radiation Oncology (J.W., B.L., R.L.), Department of Radiology (D.L.R., S.N., D.M.I.), Department of Biomedical Data Science and Medicine (Biomedical Informatics Research) (D.L.R.), Department of Medicine (A.W.K.), Department of Health Research and Policy (A.W.K.), and Stanford Cancer Institute (A.W.K., R.L.), Stanford University School of Medicine, 1070 Arastradero Rd, Stanford, CA 94305; Department of Radiotherapy, the First Affiliated Hospital of Zhejiang University, Hangzhou, Zhejiang, China (X.S.); and Department of Radiology, International Hospital of Zhejiang University, Hangzhou, Zhejiang, China (G.C.).
Debra M IkedaFrom the Department of Radiation Oncology (J.W., B.L., R.L.), Department of Radiology (D.L.R., S.N., D.M.I.), Department of Biomedical Data Science and Medicine (Biomedical Informatics Research) (D.L.R.), Department of Medicine (A.W.K.), Department of Health Research and Policy (A.W.K.), and Stanford Cancer Institute (A.W.K., R.L.), Stanford University School of Medicine, 1070 Arastradero Rd, Stanford, CA 94305; Department of Radiotherapy, the First Affiliated Hospital of Zhejiang University, Hangzhou, Zhejiang, China (X.S.); and Department of Radiology, International Hospital of Zhejiang University, Hangzhou, Zhejiang, China (G.C.).
Allison W KurianFrom the Department of Radiation Oncology (J.W., B.L., R.L.), Department of Radiology (D.L.R., S.N., D.M.I.), Department of Biomedical Data Science and Medicine (Biomedical Informatics Research) (D.L.R.), Department of Medicine (A.W.K.), Department of Health Research and Policy (A.W.K.), and Stanford Cancer Institute (A.W.K., R.L.), Stanford University School of Medicine, 1070 Arastradero Rd, Stanford, CA 94305; Department of Radiotherapy, the First Affiliated Hospital of Zhejiang University, Hangzhou, Zhejiang, China (X.S.); and Department of Radiology, International Hospital of Zhejiang University, Hangzhou, Zhejiang, China (G.C.).
Ruijiang LiFrom the Department of Radiation Oncology (J.W., B.L., R.L.), Department of Radiology (D.L.R., S.N., D.M.I.), Department of Biomedical Data Science and Medicine (Biomedical Informatics Research) (D.L.R.), Department of Medicine (A.W.K.), Department of Health Research and Policy (A.W.K.), and Stanford Cancer Institute (A.W.K., R.L.), Stanford University School of Medicine, 1070 Arastradero Rd, Stanford, CA 94305; Department of Radiotherapy, the First Affiliated Hospital of Zhejiang University, Hangzhou, Zhejiang, China (X.S.); and Department of Radiology, International Hospital of Zhejiang University, Hangzhou, Zhejiang, China (G.C.).
Stanford University · USArista (United States) · USFirst Affiliated Hospital Zhejiang University · CNZhejiang University · CN

Funding

Qualification and Deployment of Imaging Biomarkers of Cancer Treatment ResponseU01CA190214 · NCI · STANFORD UNIVERSITY · PI RUBIN, DANIEL L · 2015 to 2020
$3.1M
Tools for Linking and Mining image and Genomic Data in Non-Small Cell Lung CancerR01CA160251 · NCI · STANFORD UNIVERSITY · PI NAPEL, SANDY A., PLEVRITIS, SYLVIA KATINA · 2011 to 2015
$2.9M
Computing, Optimizing, and Evaluating Quantitative Cancer Imaging BiomarkersU01CA187947 · NCI · STANFORD UNIVERSITY · PI NAPEL, SANDY A., RUBIN, DANIEL L · 2015 to 2019
$2.9M
MRI-Based Radiation Therapy Treatment PlanningR01CA193730 · NCI · STANFORD UNIVERSITY · PI LI, RUIJIANG · 2016 to 2020
$1.8M
NCI NIH HHS R01 CA160251NCI NIH HHS R01 CA193730NCI NIH HHS U01 CA187947NCI NIH HHS U01 CA190214
6 · The paper itself

Abstract

Purpose To identify the molecular basis of quantitative imaging characteristics of tumor-adjacent parenchyma at dynamic contrast material-enhanced magnetic resonance (MR) imaging and to evaluate their prognostic value in breast cancer. Materials and Methods In this institutional review board-approved, HIPAA-compliant study, 10 quantitative imaging features depicting tumor-adjacent parenchymal enhancement patterns were extracted and screened for prognostic features in a discovery cohort of 60 patients. By using data from The Cancer Genome Atlas (TCGA), a radiogenomic map for the tumor-adjacent parenchymal tissue was created and molecular pathways associated with prognostic parenchymal imaging features were identified. Furthermore, a multigene signature of the parenchymal imaging feature was built in a training cohort (n = 126), and its prognostic relevance was evaluated in two independent cohorts (n = 879 and 159). Results One image feature measuring heterogeneity (ie, information measure of correlation) was significantly associated with prognosis (false-discovery rate < 0.1), and at a cutoff of 0.57 stratified patients into two groups with different recurrence-free survival rates (log-rank P = .024). The tumor necrosis factor signaling pathway was identified as the top enriched pathway (hypergeometric P < .0001) among genes associated with the image feature. A 73-gene signature based on the tumor profiles in TCGA achieved good association with the tumor-adjacent parenchymal image feature (R

Indexed as

Image Interpretation, Computer-AssistedMagnetic Resonance ImagingAdultAgedBiomarkers, TumorBreast NeoplasmsFemaleGene Expression ProfilingGenomicsHumansKaplan-Meier EstimateMiddle AgedMolecular ImagingParenchymal TissuePrognosisSignal TransductionBiomarkers, Tumor

Identifiers

PMID28708462
PMCPMC5673053
OpenAlexW2734865205

What OpenQuestion holds

Textmetadata
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.