Cells rely on phosphorylation signaling pathways, wherein proteins play a game of telephone and pass along a phosphate modification, to control processes such as growth. It is, therefore, no surprise that cancer cells frequently hijack these pathways to promote uncontrolled, accelerated growth.
Many treatments targeting phosphorylation signaling have been developed. However, due to cancer’s high patient-to-patient variability, it is often difficult to determine which treatment will be effective. First author Zachary Kipp and a team of researchers from the Hinds Lab at the University of Kentucky recognized this obstacle and developed a solution: moving the testing phase onto a microarray chip. This study was recently published in the Journal of Biological Chemistry.
Their approach added tissue from nine individual liver cancer patients to wells on microarray chips. Each well allows measurement of kinase activity, enzymes that transfer phosphate groups during cell signaling. The team then assessed which kinases show increased activity in tumor tissue relative to normal tissue. Multiple promising kinase targets were identified as elevated in both male and female patients. Of these, the researchers selected Abelson tyrosine kinase, or ABL, for follow-up as a high-activity target with a proven connection to liver cancer proliferation.
This “Clinical-Trial-on-a-PamChip” approach also enables researchers to screen the effectiveness of treatments in each individual patient. Using the same microarray chip technology, the team tested three ABL inhibitor treatments. The results varied: the first inhibitor was less effective, the second showed consistent ABL inhibition and the third showed pronounced ABL inhibition in female patients. The researchers were further able to determine the off-target effects of these inhibitors on other kinases. For example, protein kinase B (AKT2) showed decreased activity with ABL inhibitor treatment in some female patients but was not significantly affected in male patients. As AKT2 reduces blood glucose levels, this may indicate an undesirable side effect of hypoglycemia in some patient populations.
The microarray approach allowed researchers to evaluate potential therapies and side effects before patients received treatment; thus, significantly lightening patient burden. This could improve patient outcomes and time spent in treatment within the clinic, making it a promising direction for the field of cancer and personalized medicine.