Evidence map›Paper›PMID 26087699›Full record

ArticleGenome biology2015

Extensive rewiring of epithelial-stromal co-expression networks in breast cancer.

Eun-Yeong Oh, Stephen M Christensen, Sindhu Ghanta, Jong Cheol Jeong, Octavian Bucur, Benjamin Glass, Laleh Montaser-Kouhsari, Nicholas W Knoblauch, Nicholas Bertos, Sadiq Mi Saleh and 3 more

Open access · hybridAbstract read
In one paragraph

Article in Genome biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed
3.2field-weighted citation impact, top 6% 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

25 citing papers in PubMed, 68 citations in OpenAlex.

  1. Trial
  2. Trial
  3. Article
  4. Article
  5. Cell-cell communication: new insights and clinical implications.Signal transduction and targeted therapy · 2024
    Review
  6. Frontiers in cell and developmental biology · 2024
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Review
  12. Article
  13. Article
  14. Review
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. 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

13 authors at 4 institutions in 2 countries.

Eun-Yeong OhCancer Research Institute, Beth Israel Deaconess Cancer Center, Boston, MA, 02215, USA. eoh1@bidmc.harvard.edu.
Stephen M ChristensenCancer Research Institute, Beth Israel Deaconess Cancer Center, Boston, MA, 02215, USA. djscristo@gmail.com.
Sindhu GhantaCancer Research Institute, Beth Israel Deaconess Cancer Center, Boston, MA, 02215, USA. sghanta2@bidmc.harvard.edu.
Jong Cheol JeongCancer Research Institute, Beth Israel Deaconess Cancer Center, Boston, MA, 02215, USA. jjeong1@bidmc.harvard.edu.
Octavian BucurCancer Research Institute, Beth Israel Deaconess Cancer Center, Boston, MA, 02215, USA. obucur@bidmc.harvard.edu.
Benjamin GlassCancer Research Institute, Beth Israel Deaconess Cancer Center, Boston, MA, 02215, USA. bglass@bidmc.harvard.edu.
Laleh Montaser-KouhsariCancer Research Institute, Beth Israel Deaconess Cancer Center, Boston, MA, 02215, USA. lmontase@bidmc.harvard.edu.
Nicholas W KnoblauchCancer Research Institute, Beth Israel Deaconess Cancer Center, Boston, MA, 02215, USA. nwknoblauch@gmail.com.
Nicholas BertosGoodman Cancer Research Centre, McGill University, Montreal, QC, Canada. nicholas.bertos@mcgill.ca.
Sadiq Mi SalehGoodman Cancer Research Centre, McGill University, Montreal, QC, Canada. sadiq.saleh@gmail.com.
Benjamin Haibe-KainsPrincess Margaret Cancer Centre, University Health Network, Toronto, ON, M5G 1L7, Canada. bhaibeka@uhnresearch.ca.
Morag ParkGoodman Cancer Research Centre, McGill University, Montreal, QC, Canada. morag.park@mcgill.ca.
Andrew H BeckCancer Research Institute, Beth Israel Deaconess Cancer Center, Boston, MA, 02215, USA. abeck2@bidmc.harvard.edu.
Beth Israel Deaconess Medical Center · USMcGill University Health Centre · CACancer Research Institute · USPrincess Margaret Cancer Centre · CA

Funding

Tissue and Pathology CoreP50CA168504 · NCI · DANA-FARBER CANCER INST · PI MYLES A BROWN · 2013 to 2026
$30.1M
Suppression of Mammary Tumorigenesis by Stromal p53P01CA097189 · NCI · OHIO STATE UNIVERSITY · PI LEONE, GUSTAVO WALTER · 2004 to 2016
$16.1M
INFORMATICS METHODS AND MODELS FOR COMPUTATIONAL PATHOLOGYK22LM011931 · NLM · BETH ISRAEL DEACONESS MEDICAL CENTER · PI BECK, ANDREW H · 2014 to 2016
$476k
NCI NIH HHS P01 CA097189NCI NIH HHS P50 CA168504NCI NIH HHS P50CA168504NLM NIH HHS K22 LM011931NLM NIH HHS K22LM011931
6 · The paper itself

Abstract

backgroundEpithelial-stromal crosstalk plays a critical role in invasive breast cancer pathogenesis; however, little is known on a systems level about how epithelial-stromal interactions evolve during carcinogenesis.

resultsWe develop a framework for building genome-wide epithelial-stromal co-expression networks composed of pairwise co-expression relationships between mRNA levels of genes expressed in the epithelium and stroma across a population of patients. We apply this method to laser capture micro-dissection expression profiling datasets in the setting of breast carcinogenesis. Our analysis shows that epithelial-stromal co-expression networks undergo extensive rewiring during carcinogenesis, with the emergence of distinct network hubs in normal breast, and estrogen receptor-positive and estrogen receptor-negative invasive breast cancer, and the emergence of distinct patterns of functional network enrichment. In contrast to normal breast, the strongest epithelial-stromal co-expression relationships in invasive breast cancer mostly represent self-loops, in which the same gene is co-expressed in epithelial and stromal regions. We validate this observation using an independent laser capture micro-dissection dataset and confirm that self-loop interactions are significantly increased in cancer by performing computational image analysis of epithelial and stromal protein expression using images from the Human Protein Atlas.

conclusionsEpithelial-stromal co-expression network analysis represents a new approach for systems-level analyses of spatially localized transcriptomic data. The analysis provides new biological insights into the rewiring of epithelial-stromal co-expression networks and the emergence of epithelial-stromal co-expression self-loops in breast cancer. The approach may facilitate the development of new diagnostics and therapeutics targeting epithelial-stromal interactions in cancer.

Indexed as

Gene Expression Regulation, NeoplasticGene Regulatory NetworksBreastBreast NeoplasmsEpithelial CellsFemaleGene Expression ProfilingGenomicsHumansImmunohistochemistryReceptors, EstrogenStromal CellsTissue Array AnalysisReceptors, Estrogen

Identifiers

PMID26087699
PMCPMC4471934
OpenAlexW2162376722

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.