Evidence map›Paper›PMID 29050296›Full record

ArticleOncotarget2017

Reverse phase protein array identification of triple-negative breast cancer subtypes and comparison with mRNA molecular subtypes.

Hiroko Masuda, Yuan Qi, Shuying Liu, Naoki Hayashi, Takahiro Kogawa, Gabriel N Hortobagyi, Debu Tripathy, Naoto T Ueno

Abstract read
In one paragraph

Article in Oncotarget, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Article
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  12. Network-Based Matching of Patients and Targeted Therapies for Precision Oncology.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing · 2020
    Article
  13. 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

8 authors.

Hiroko MasudaDepartment of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Yuan QiDepartment of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Shuying LiuDepartment of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Naoki HayashiDepartment of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Takahiro KogawaDepartment of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Gabriel N HortobagyiDepartment of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Debu TripathyDepartment of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Naoto T UenoDepartment of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.

Funding

Tumor Evolution and Metastasis ProgramP30CA016672 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Scott Kopetz · 1985 to 2026
$290.8M
NCI NIH HHS P30 CA016672
6 · The paper itself

Abstract

backgroundReverse phase protein array (RPPA) analysis, allows investigation of potential targets at the functional protein level,. We identified TNBC subtypes at the protein level using RPPA and compared them with mRNA molecular subtypes (TNBCtype, TNBCtype-4, and PAM50) that is unique in its availability of both RPPA and mRNA analyses.

methodsWe classified the samples from 80 TNBC patients using both k-means and hierarchical consensus clustering analysis and performed Ingenuity Pathway Analysis. We also investigated whether we could reproduce the mRNA molecular subtypes using the RPPA dataset.

resultsBoth clustering methods divided all samples into 2 clusters that were biologically the same. The top canonical pathways included inflammation, hormonal receptors, and MAPK signaling pathways for the first cluster ["inflammation and hormonal-related (I/H) subtype"] and the GADD45, DNA damage, and p53 signaling pathways for the second cluster ["DNA damage (DD)-related subtype"]. Further k-means cluster analysis identified 5 TNBC clusters. Comparison between sample classification using the 5 RPPA-based k-means cluster subtypes and 6 gene-expression-based TNBCtype molecular subtypes showed significant association between the 2 classifications (p = 0.017).

conclusionsThe I/H and DD subtypes identified by RPPA advance our understanding of TNBC's heterogeneity from the functional proteomic perspective.

Indexed as

functionalmolecular subtypemRNA microarrayproteomicstriple-negative breast cancer

Identifiers

PMID29050296
PMCPMC5642571

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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.