Transcriptome Signatures of Canine Mammary Gland Tumors and Its Comparison to Human Breast Cancers.
Kang-Hoon LeeHyoung-Min ParkKeun-Hong SonTae-Jin ShinJe-Yeol ChoPublished in: Cancers (2018)
Breast cancer (BC)/mammary gland carcinoma (MGC) is the most frequently diagnosed and leading cause of cancer-related mortality in both women and canines. To better understand both canine MGC and human BC-specific genes, we sequenced RNAs obtained from eight pairs of carcinomas and adjacent normal tissues in dogs. By comprehensive transcriptome analysis, 351 differentially expressed genes (DEGs) were identified in overall canine MGCs. Based on the DEGs, comparative analysis revealed correlation existing among the three histological subtypes of canine MGC (ductal, simple, and complex) and four molecular subtypes of human BC (HER2+, ER+, ER&HER2+, and TNBC). Eight DEGs shared by all three subtypes of canine MGCs had been previously reported as cancer-associated genes in human studies. Gene ontology and pathway analyses using the identified DEGs revealed that the biological processes of cell proliferation, adhesion, and inflammatory responses are enriched in up-regulated MGC DEGs. In contrast, fatty acid homeostasis and transcription regulation involved in cell fate commitment were down-regulated in MGC DEGs. Moreover, correlations are demonstrated between upstream promoter transcripts and DEGs. Canine MGC- and subtype-enriched gene expression allows us to better understand both human BC and canine MGC, yielding new insight into the development of biomarkers and targets for both diseases.
Keyphrases
- endothelial cells
- gene expression
- genome wide
- induced pluripotent stem cells
- cell proliferation
- transcription factor
- pluripotent stem cells
- fatty acid
- magnetic resonance
- type diabetes
- computed tomography
- escherichia coli
- magnetic resonance imaging
- pregnant women
- single cell
- genome wide identification
- skeletal muscle
- signaling pathway
- polycystic ovary syndrome
- cell fate
- coronary artery disease
- risk factors
- biofilm formation
- single molecule
- cardiovascular events
- bioinformatics analysis
- genome wide analysis
- estrogen receptor
- cell migration