Bioinformatic Identification of a Breast-Specific Transcript Profile

Abstract

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.

Keywords: ANKRD30A; LINC00993; bioinformatics; biomarkers; breast; tissue-specific.