Evidence map›Paper›PMID 26490514›Full record

ArticleScientific reports2015

The influence of cancer tissue sampling on the identification of cancer characteristics.

Hui Xu, Xin Guo, Qiang Sun, Mengmeng Zhang, Lishuang Qi, Yang Li, Libin Chen, Yunyan Gu, Zheng Guo, Wenyuan Zhao

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
0.7field-weighted citation impact, top 25% 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

9 citing papers in PubMed, 14 citations in OpenAlex.

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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

10 authors at 1 institution in 1 country.

Hui XuCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150086, China.
Xin GuoCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150086, China.
Qiang SunGenomics Research Center, Harbin Medical University, Harbin, 150086, China.
Mengmeng ZhangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150086, China.
Lishuang QiCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150086, China.
Yang LiCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150086, China.
Libin ChenCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150086, China.
Yunyan GuCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150086, China.
Zheng GuoCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150086, China.
Wenyuan ZhaoCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150086, China.
Harbin Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cancer tissue sampling affects the identification of cancer characteristics. We aimed to clarify the source of differentially expressed genes (DEGs) in macro-dissected cancer tissue and develop a robust prognostic signature against the effects of tissue sampling. For estrogen receptor (ER)+ breast cancer patients, we identified DEGs in macro-dissected cancer tissues, malignant epithelial cells and stromal cells, defined as Macro-Dissected-DEGs, Epithelial-DEGs and Stromal-DEGs, respectively. Comparing Epithelial-DEGs to Stromal-DEGs (false discovery rate (FDR) < 10%), 86% of the overlapping genes exhibited consistent dysregulation (defined as Consistent-DEGs), and the other 14% of genes were dysregulated inconsistently (defined as Inconsistent-DEGs). The consistency score of dysregulation directions between Macro-Dissected-DEGs and Consistent-DEGs was 91% (P-value < 2.2 × 10(-16), binomial test), whereas the score was only 52% between Macro-Dissected-DEGs and Inconsistent-DEGs (P-value = 0.9, binomial test). Among the gene ontology (GO) terms significantly enriched in Macro-Dissected-DEGs (FDR < 10%), 18 immune-related terms were enriched in Inconsistent-DEGs. DEGs associated with proliferation could reflect common changes of malignant epithelial and stromal cells; DEGs associated with immune functions are sensitive to the percentage of malignant epithelial cells in macro-dissected tissues. A prognostic signature which was insensitive to the cellular composition of macro-dissected tissues was developed and validated for ER+ breast patients.

Indexed as

Breast NeoplasmsComputational BiologyDisease-Free SurvivalEstrogen Receptor alphaFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticHumansKaplan-Meier EstimateNeoplasm ProteinsOligonucleotide Array Sequence AnalysisPrognosisStromal CellsEstrogen Receptor alphaNeoplasm Proteins

Identifiers

PMID26490514
PMCPMC4614546
OpenAlexW2416857650

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.