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Updated: Dec 18, 2025
Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
Published on: May 17, 2019
Bioinformatic Identification of a Breast-Specific Transcript Profile
Chen Chen1,2, Liwen Yang1, Mahdi Rivandi1
1Department of Obstetrics and Gynecology, Heinrich Heine University of Duesseldorf, Duesseldorf, 40225, Germany.
Purpose:
To identify a breast-specific transcript profile for the first time, and present an updated bioinformatics strategy for searching tissue-specific transcripts and predicting their significance in cancer.
Experimental Design:
The RNA-seq data of 49 311 transcripts in 88 human tissues from the GTEx, the Illumina Body Map, and the RIKEN FANTOM5 project are integrated to screen breast-specific transcripts. Gene Expression Profiling Interactive Analysis, TGCA, and Kaplan-Meier Plotter are used to examine their expression in cancer tissues and values for prognosis prediction.
Results:
Only 96 transcripts in human genome are breast-specific for women. Among them, ankyrin repeat domain 30A (ANKRD30A) and long intergenic non-protein coding RNA 993 (LINC00993) are further analyzed. The two transcripts are also breast-specific in 33 types of common female cancer and are often dysregulated in breast cancer tissues. Their expression is higher in the luminal breast cancer while significantly downregulated in triple-negative breast cancer. Moreover, the high expression levels of ANKRD30A and LINC0993 in breast cancer tissues indicate a better prognosis of patients with breast cancer.
Conclusions And Clinical Relevance:
Breast-specific transcripts in human genome are rare and poorly understood currently. The data indicate that these breast-specific biomarkers are promising candidates for screening early cancer, assessing treatment response, monitoring recurrence, identifying metastatic tumor origin, and serving as potential targets for immunotherapy.
