Abstract
Abstract Background: 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. These differentiated cells formed multicellular structures with defined lumens and tight junctions and with specific localizations of cadherin and integrins. In contrast, cells from breast cancers displayed a general loss of structure. Previous work showed that different sets of these 325 biomarkers accurately predicted overall breast cancer patients' survival or response to neoadjuvant therapy in multiple independent studies. Objective: Predict cell-signaling pathways, drug associations, and disease associations for the 325 biomarkers (BA325) in contrast to other cancer gene panels. Methods and Results: The Qiagen Ingenuity program was used to identify pathways and disease states containing significant overlap with BA325. Multiple cell signaling pathways including cell proliferation, migration, invasion, and metabolism were found in BA325, while most other cancer biomarker panels were highly concentrated in cell proliferation. Examples of significant pathway associations relevant for oncology drug discovery and targeted treatments include Cell Cycle Control of Chromosomal Replication (p=8.1E-14), Polo-like-kinase and HSP90 complex (p=6.3E-07), G2/M DNA Damage Checkpoint (p=6.4E-07), Integrin Signaling (p=3E-05), Integrin Linked Kinase Signaling (p=4.51E-05), BRCA1 DNA Damage Response (p=1.75E-04), Estrogen Mediated S-phase entry (p=4.24E-04), Regulation of Actin Based Motility by RHO (p=4.55E-04), Adherins Junction Remodeling (p=5.6E-04), Actin Cytoskeleton Signaling (p=7.25E-04), Mismatch Repair (p=1.6E-03), RAN Signaling (p=1.64E-03), Protein Ubiquitination (p=1.78E-03) and Cholesterol Biosynthesis (p=4.8E-03). This wide coverage of cellular signaling pathways provides an advantage in developing predictive tests for treatments targeting highly complex cell signaling networks. Surprisingly, even though the BA325 panel was obtained during non-malignant differentiation, the most significant disease state associated with these genes was mammary tumor, demonstrating the validity of this approach to probe breast cancer biology. Conclusion: This analysis demonstrates that the BA325 panel is useful both in understanding non-malignant mammary epithelial differentiation and breast cancer tumors. Citation Format: Edward C. Goodwin, Said Attiya, Marcia Fournier. 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 [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 405. doi:10.1158/1538-7445.AM2017-405
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