A novel panel of 325 biomarkers is part of a large interconnected network representing multiple cell signaling pathways and allowing development of predictive tests for oncology drugs

We developed an algorithm based on the gene expression of tumor biopsies to identify the best combination of biomarkers to reliably predict a patient’s response to relevant cancer treatments. This algorithm is derived from 325 genes whose expression showed significant changes during differentiation of non-malignant human mammary epithelial cells cultured in laminin-rich extracellular matrix. Of these 325 genes, 251 are novel and not present in 9 other cancer based gene expression panels such as FoundationOne or PAM50. The objective of this study was to predict cell-signaling pathways, drug associations, and disease associations for the 325 biomarkers (BA325) in contrast to other cancer gene panels. This analysis demonstrates that the BA325 panel is useful both in understanding non-malignant mammary epithelial differentiation and breast cancer tumors.

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