Evidence map›Paper›PMID 25500646›Full record

ReviewIntegrative biology : quantitative biosciences from nano to macro2015

A journey to uncharted territory: new technical frontiers in studying tumor-stromal cell interactions.

Ian H Guldner, Siyuan Zhang

Abstract readReview
In one paragraph

Review in Integrative biology : quantitative biosciences from nano to macro, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. 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

2 authors.

Ian H GuldnerDepartment of Biological Science, Harper Cancer Research Institute, University of Notre Dame, A130 Harper Hall, Notre Dame, IN 46556, USA. szhang8@nd.edu.
Siyuan Zhang

Funding

(PQD-3) Spatiotemporal Molecular Interrogation of Early Metastatic Evolution In SituR01CA194697 · NCI · UNIVERSITY OF NOTRE DAME · PI ZHANG, SIYUAN · 2015 to 2018
$1.4M
Dissecting the Role of Src Family Kinases in Breast Cancer Brain MetastasisR00CA158066 · NCI · UNIVERSITY OF NOTRE DAME · PI ZHANG, SIYUAN · 2012 to 2014
$707k
Dissecting the Role of Src Family Kinases in Breast Cancer Brain MetastasisK99CA158066 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI ZHANG, SIYUAN · 2011 to 2011
$107k
NCI NIH HHS CA158066-04NCI NIH HHS K99 CA158066NCI NIH HHS R00 CA158066NCI NIH HHS R01 CA194697
6 · The paper itself

Abstract

The crosstalk between tumor cells and cells of the tumor stroma dictate malignant progression and represent an intriguing and viable anticancer therapeutic target. The successful development of therapeutics targeting tumor-stroma interactions is tied to the insight provided by basic research on such crosstalk. Tumor-stroma interactions can be transient and dynamic, and they occur within defined spatiotemporal contexts among genetically and compositionally heterogeneous populations of cells, yet methods currently applied to study the said crosstalk do not sufficiently address these features. Emerging imaging and genetic methods, however, can overcome limitations of traditional approaches and provide unprecedented insight into tumor-stroma crosstalk with unparalleled accuracy. The comprehensive data obtained by applying emerging methods will require processing and analysis by multidisciplinary teams, but the efforts will ultimately rejuvenate hope in developing novel therapies against pro-tumorigenic tumor-stroma crosstalk.

Indexed as

AnimalsCell CommunicationComputational BiologyDiagnostic ImagingHumansMicroscopyNeoplasmsStromal CellsTumor Microenvironment

Identifiers

PMID25500646
PMCPMC4324098

What OpenQuestion holds

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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.