Evidence map›Paper›PMID 24936222›Full record

ArticleAmerican journal of translational research2014

Pathway-based analysis of breast cancer.

Dong Song, Miao Cui, Gang Zhao, Zhimin Fan, Katherine Nolan, Ying Yang, Peng Lee, Fei Ye, David Y Zhang

Open access · greenAbstract read
In one paragraph

Article in American journal of translational research, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
0.9field-weighted citation impact, top 26% 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

12 citing papers in PubMed, 18 citations in OpenAlex.

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    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

9 authors at 3 institutions in 2 countries.

Dong SongDepartment of Breast Surgery, The First Hospital, Jilin University Changchun, Jilin 130021, China.
Miao CuiDepartment of Pathology, Mount Sinai School of Medicine New York, NY 10029, USA.
Gang ZhaoDepartment of Breast Surgery, The First Hospital, Jilin University Changchun, Jilin 130021, China.
Zhimin FanDepartment of Breast Surgery, The First Hospital, Jilin University Changchun, Jilin 130021, China.
Katherine NolanDepartment of Pathology, Mount Sinai School of Medicine New York, NY 10029, USA.
Ying YangDepartment of Pathology, Mount Sinai School of Medicine New York, NY 10029, USA.
Peng LeeDepartment of Pathology, New York University School of Medicine New York, NY 10010, USA.
Fei YeDepartment of Pathology, Mount Sinai School of Medicine New York, NY 10029, USA.
David Y ZhangDepartment of Pathology, Mount Sinai School of Medicine New York, NY 10029, USA.
Icahn School of Medicine at Mount Sinai · USJilin University · CNNew York University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionAlthough HER2 and ER pathways are predominant pathways altered in breast cancer, it is now well accepted that many other signaling pathways are also involved in the pathogenesis of breast cancer. The understanding of these additional pathways may assist in identifying new therapeutic approaches for breast cancer.

methods13 invasive ductal carcinoma tissues and 5 benign breast tissues were analyzed for the mRNA expression level of 1243 cancer pathway-related genes using SmartChip (WaferGen, CA), a real-time PCR-base method. In addition, the levels of 131 cancer pathway-related proteins and phosphoproteins in 33 paired breast cancers were measured using our innovative Protein Pathway Array.

resultsOut of 1,243 mRNAs, 68.7% (854) were detected in breast cancer and 395 mRNAs were statistically significant (fold change >2) between benign and cancer tissues. Of these mRNAs, 105 only expressed in breast cancer tissues and 33 mRNAs only expressed in normal breast tissues. Out of 131 proteins and phosphoproteins, 68% (89) were detected in cancer tissues and 57 proteins were significantly differentiated between tumor and normal tissues. Interestingly, only 3 genes (CDK6, Vimentin and SLUG) showed decreases in both protein and mRNA. Six proteins (BCL6, CCNE1, PCNA, PDK1, SRC and XIAP) were differentially expressed between tumor and normal tissues but no differences were observed at mRNA levels. Analyses of mRNA and protein data using Ingenuity Pathway Analysis showed more than 15 pathways were altered in breast cancer and 6 of which were shared between mRNAs and proteins, including p53, IL17, HGF, NGF, PTEN and PI3K/AKT pathways.

conclusionsThere is a broad dysregulation of various pathways in breast cancer both at protein levels and mRNA levels. It is important to note that mRNA expression does not correlate with protein level, suggesting different regulation mechanisms between proteins and mRNAs.

Indexed as

Breast cancergene expressionprotein abundancesignaling networksignal transduction

Identifiers

PMID24936222
PMCPMC4058311
OpenAlexW1783715038

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.