Evidence map›Paper›PMID 26319982›Full record

SynthesisMedical science monitor : international medical journal of experimental and clinical research2015

Identification of Aberrant Chromosomal Regions in Human Breast Cancer Using Gene Expression Data and Related Gene Information.

Hong-Jiu Wang, Meng Zhou, Li Jia, Jie Sun, Hong-Bo Shi, Shu-Lin Liu, Zhen-Zhen Wang

Open access · hybridAbstract readMeta-Analysis
In one paragraph

Synthesis in Medical science monitor : international medical journal of experimental and clinical research, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.2field-weighted citation impact, top 44% 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

4 citing papers in PubMed, 4 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

7 authors at 2 institutions in 1 country.

Hong-Jiu WangCollege of Science, Heilongjiang University of Science and Technology, Harbin, Heilongjiang, China (mainland).
Meng ZhouCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, China (mainland).
Li JiaDepartment of Environmental Health, Public health Institute of Harbin Medical University, Harbin, Heilongjiang, China (mainland).
Jie SunCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, China (mainland).
Hong-Bo ShiCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, China (mainland).
Shu-Lin LiuGenomics Research Center (one of The State-Province Key Laboratories of Biomedicine-Pharmaceutics of China), Harbin Medical University, Harbin, Heilongjiang, China (mainland).
Zhen-Zhen WangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, China (mainland).
Harbin Medical University · CNHeilongjiang University of Science and Technology · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundChromosomal instability is a hallmark of cancer. Chromosomal imbalances, like amplifications and deletions, influence the transcriptional activity of genes. These imbalances affect not only the expression of genes in the aberrant chromosomal regions, but also that of related genes, and may be relevant to the cancer status. MATERIAL AND

methodsHere, we used the 7 publicly available microarray studies in breast cancer tissues and propose a general and unsupervised method by using the gene expression data and related gene information to systematically identify aberrant chromosomal regions. This method aimed to identify the chromosomal regions where the genes and their related genes both show consistent changes in the expression levels. Such patterns have been reported to be associated with the chromosomal aberrations and may be used in cancer diagnosis.

resultsWe compared 488 tumor and 222 normal samples from 7 microarray-based human breast cancer studies and detected the amplifications of 8q11.21, 14q32.11, 4q21.23, 18q11.2, Xq28, and the deletions of 3p24.1, 10q23.2 (BSCG1), 20p11.21, 9q21.13, and 1q41, which may be involved in the novel mechanisms of tumorigenesis. In addition, several known pathogenic genes, transcription factors (TFs), and microRNAs (miRNAs) associated with breast cancer were found.

conclusionsThis approach can be applied to other microarray studies, which provide a new and useful method for exploring chromosome structural variations in different types of diseases.

Indexed as

Chromosome AberrationsGene ExpressionAlgorithmsBreast NeoplasmsChromosome MappingFemaleHumans

Identifiers

PMID26319982
PMCPMC4557392
OpenAlexW1949838554

What OpenQuestion holds

Textmetadata
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Registered trials

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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.