Conclusion
Altogether, the exposure of SKBR3/HER2+ cells to Lapatinib and Ipatasertib kinase inhibitors uncovered a broad plethora of yet untapped opportunities that can be further explored for enhancing the anti-cancer effects of each drug as well as of many other multi-drug therapies that target the EGFR/ERBB2 and PI3K/AKT pathways.
Methods
Two critical pathways that sustain the growth and survival of cancer cells, EGFR and PI3K/AKT, were inhibited in SKBR3/HER2+ breast cancer cells with Lapatinib (Tyr kinase inhibitor) and Ipatasertib (Ser/Thr kinase inhibitor), and the landscape of the affected biological processes was investigated with proteomic technologies.
Objective
The objective of this study was to use high-throughput data generation technologies such as mass spectrometry and proteomics to investigate the broader implications, and to expand the outlook, of such therapeutic approaches. Specifically, we investigated the systems-level response of a breast cancer cell line model to a mixture of kinase inhibitors that has not been adopted yet as a standard therapeutic regime.
Results
Over 800 proteins matched by three unique peptide sequences were affected by exposing the cells to the drugs. The work corroborated the anti-proliferative activity of Lapatinib and Ipatasertib and uncovered a range of impacted cancer-supportive hallmark processes, among which immune response, adhesion, and migration emerged as particularly relevant to the ability of drugs to effectively suppress the proliferation and dissemination of cancer cells. Changes in the expression of key cancer drivers such as oncogenes, tumor suppressors, EMT and angiogenesis regulators underscored the inhibitory effectiveness of drugs on cancer proliferation. The supplementation of Lapatinib with Ipatasertib further affected additional transcription factors and proteins involved in gene expression, trafficking, DNA repair, and development of multidrug resistance. Furthermore, over fifty of the impacted proteins represent approved or investigational targets in the DrugBank database, which through their protein-protein interaction networks can inform the selection of effective therapeutic partners.