Evidence map›Paper›PMID 26185419›Full record

ReviewDrug design, development and therapy2015

Reverse phase protein arrays in signaling pathways: a data integration perspective.

Chad J Creighton, Shixia Huang

Abstract readReview
In one paragraph

Review in Drug design, development and therapy, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.

0numbers the graph read from it
0cells of the map it votes in
38citing 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

38 citing papers in PubMed.

  1. Trial
  2. Article
  3. An Overview of Analytical Approaches to Cancer Proteogenomics.Methods in molecular biology (Clifton, N.J.) · 2025
    Review
  4. Article
  5. Article
  6. Article
  7. Article
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  13. Experimental MicroRNA Targeting Validation.Methods in molecular biology (Clifton, N.J.) · 2022
    Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
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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.

Chad J CreightonDepartment of Medicine, Baylor College of Medicine, Houston, TX, USA ; Dan L Duncan Cancer Center, Baylor College of Medicine, Houston, TX, USA.
Shixia HuangDepartment of Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX, USA ; Dan L Duncan Cancer Center, Baylor College of Medicine, Houston, TX, USA.

Funding

Tumor BiologyP30CA125123 · NCI · BAYLOR COLLEGE OF MEDICINE · PI DAVID R ROWLEY · 2007 to 2026
$73.9M
The BCM Tumor Genome Characterization CenterU24CA143843 · NCI · BAYLOR COLLEGE OF MEDICINE · PI GIBBS, RICHARD A, WHEELER, DAVID ANDREW · 2009 to 2013
$9.5M
NCI NIH HHS P30 CA125123NCI NIH HHS P30CA125123NCI NIH HHS U24 CA143843NCI NIH HHS U24CA143843
6 · The paper itself

Abstract

The reverse phase protein array (RPPA) data platform provides expression data for a prespecified set of proteins, across a set of tissue or cell line samples. Being able to measure either total proteins or posttranslationally modified proteins, even ones present at lower abundances, RPPA represents an excellent way to capture the state of key signaling transduction pathways in normal or diseased cells. RPPA data can be combined with those of other molecular profiling platforms, in order to obtain a more complete molecular picture of the cell. This review offers perspective on the use of RPPA as a component of integrative molecular analysis, using recent case examples from The Cancer Genome Altas consortium, showing how RPPA may provide additional insight into cancer besides what other data platforms may provide. There also exists a clear need for effective visualization approaches to RPPA-based proteomic results; this was highlighted by the recent challenge, put forth by the HPN-DREAM consortium, to develop visualization methods for a highly complex RPPA dataset involving many cancer cell lines, stimuli, and inhibitors applied over time course. In this review, we put forth a number of general guidelines for effective visualization of complex molecular datasets, namely, showing the data, ordering data elements deliberately, enabling generalization, focusing on relevant specifics, and putting things into context. We give examples of how these principles can be utilized in visualizing the intrinsic subtypes of breast cancer and in meaningfully displaying the entire HPN-DREAM RPPA dataset within a single page.

Indexed as

Breast NeoplasmsFemaleGuidelines as TopicHumansNeoplasm ProteinsProtein Array AnalysisProtein Processing, Post-TranslationalProteinsProteomicsSignal TransductionNeoplasm ProteinsProteinsbreast cancerintegrative analysismolecular profilingproteomicsRPPATCGA

Identifiers

PMID26185419
PMCPMC4500628

What OpenQuestion holds

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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.