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Progression-specific genes identified in microdissected formalin-fixed and paraffin-embedded tissue containing matched ductal carcinoma in situ and invasive ductal breast cancers

Overview of attention for article published in BMC Medical Genomics, September 2018
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Title
Progression-specific genes identified in microdissected formalin-fixed and paraffin-embedded tissue containing matched ductal carcinoma in situ and invasive ductal breast cancers
Published in
BMC Medical Genomics, September 2018
DOI 10.1186/s12920-018-0403-5
Pubmed ID
Authors

Silke Schultz, Harald Bartsch, Karl Sotlar, Karina Petat-Dutter, Michael Bonin, Steffen Kahlert, Nadia Harbeck, Ulrich Vogel, Harald Seeger, Tanja Fehm, Hans J. Neubauer

Abstract

The transition from ductal carcinoma in situ (DCIS) to invasive breast carcinoma (IBC) is an important step during breast carcinogenesis. Understanding its molecular changes may help to identify high-risk DCIS that progress to IBC. Here, we describe a transcriptomic profiling analysis of matched formalin-fixed and paraffin-embedded (FFPE) DCIS and IBC components of individual breast tumours, containing both tumour compartments. The study was performed to validate progression-associated transcripts detected in an earlier gene profiling project using fresh frozen breast cancer tissue. In addition, FFPE tissues from patients with pure DCIS (pDCIS) were analysed to identify candidate transcripts characterizing DCIS with a high or low risk of progressing to IBC. Fifteen laser microdissected pairs of DCIS and IBC were profiled by Illumina DASL technology and used for expression validation by qPCR. Differential expression was independently validated using further 25 laser microdissected DCIS/IBC sample pairs. Additionally, laser microdissected epithelial cells from 31 pDCIS were investigated for expression of candidate transcripts using qPCR. Multiple statistical calculation methods revealed 1784 mRNAs which are differentially expressed between DCIS and IBC (P < 0.05), of which 124 have also been identified in the gene profiling project using fresh frozen breast cancer tissue. Nine mRNAs that had been selected from the gene list obtained using fresh frozen tissues by applying pathway and network analysis (MMP11, GREM1, PLEKHC1, SULF1, THBS2, CSPG2, COL10A1, COL11A1, KRT14) were investigated in tissues from the same 15 microdissected specimens and the 25 independent tissue samples by qPCR. All selected transcripts were also detected in tumour cells from pDCIS. Expression of MMP11 and COL10A1 increased significantly from pDCIS to DCIS of DCIS/IBC mixed tumours. We confirm differential expression of progression-associated transcripts in FFPE breast cancer samples which might mediate the transition from DCIS to IBC. MMP11 and COL10A1 may characterize pure DCIS with a high risk developing IDC.

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Mendeley readers

The data shown below were compiled from readership statistics for 29 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 29 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 6 21%
Researcher 5 17%
Other 2 7%
Student > Ph. D. Student 2 7%
Student > Bachelor 1 3%
Other 5 17%
Unknown 8 28%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 11 38%
Agricultural and Biological Sciences 3 10%
Engineering 2 7%
Medicine and Dentistry 2 7%
Veterinary Science and Veterinary Medicine 1 3%
Other 2 7%
Unknown 8 28%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 25 September 2018.
All research outputs
#12,019,781
of 13,555,083 outputs
Outputs from BMC Medical Genomics
#605
of 690 outputs
Outputs of similar age
#228,358
of 264,839 outputs
Outputs of similar age from BMC Medical Genomics
#10
of 13 outputs
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