Abstract

Breast cancer is the second most prevalent cancer overall among newly diagnosed cases and the most common cancer among women. 90% of cancer deaths are caused by metastasis, which is a factor that precedes local invasion, but very little is understood about the molecular mechanisms of invasion and metastasis. Thus, uncovering the root causes of this illness at the Transcriptomics level may result in a cutting-edge method of treating breast cancer. The total RNA microarray processed data from GEO for breast cancer patients was analyzed to discover hidden differences between epithelial breast cancer tissues (ET), stromal breast cancer tissues (ST), normal control epithelial breast cancer tissue samples (EC), and normal control stromal breast cancer tissue samples (SC) at the Transcriptomics level. Therefore, multiple bioinformatics analyses of the transcriptional profiles of 64 samples—including 28 TEC, 28 SCC, 5 EN, and 5 SN controls—received from the NCBI-Bio project were performed in the current study (PRJNA107497). First, ET versus EC and ST vs SC samples showed significant patterns in exploratory data analysis based on gene expression data using principal component analysis (PCA). Following this, 13512 substantially differentially expressed genes (Fold change (>= 1.5), p.adj value 0.1) between these conditions were found by Welch's T-test differential gene expression analysis. This study identifies the main element that may significantly contribute to the spread of breast cancer from epithelial cells to stromal cells in the mammary glands as the gene like the GBRP. This study was also able to identify the affected biological pathways for both the ST vs. SC samples and the ET vs. EC samples as a result of the up-regulated and down-regulated genes. This most surely provides a crucial hint about the cause of the deadly metastatic cancer problem. Finally, the results presented here provide novel insights on breast cancer metastasis.

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