Cancer & Graphs: More in Common than You Might Think
Acute myeloid leukemia (AML), the most common form of acute leukemia in adults, is characterized by defective differentiation and excessive accumulation of immature blood cells in bone marrow and blood. One of the most successful treatments of AML is of its subtype, acute promyelocytic leukemia (APL). APL is characterized by an arrest of white blood cell differentiation at the promyelocyte stage. Once considered one of the most lethal forms of acute leukemia, the advent of all trans-retinoic acid (RA) therapy has revolutionized treatment of this disease. Now, APL is characterized by complete remission rates of 90% and cure rates of around 80%.
RA therapy relies on manipulation of the blood cell differentiation pathway. This pathway can be represented by a graph in which the types of blood cells are the nodes and the various treatments are the edges. Left untreated, APL cells continue to proliferate and are extremely lethal. However, treatment with RA causes these cancer cells to differentiate along a granulocytic pathway, essentially turning the cancer cells into healthy, functioning blood cells called neutrophils. The mechanism of action of RA is not well understood as the graph of the signaling pathways is extremely complex.
Unfortunately, around 10% of patients who were initially responsive to treatment relapse and subsequent treatment with RA is not effective due to resistance. This paper focused on the effects of altering a signaling pathway known to be involved in cell differentiation. This pathway was altered using a protein called cbl. It was found that cbl enhanced RA-induced differentiation in resistant cell lines. Again, the complete pathway is not well understood so we have an incomplete picture of the graph. While we understand the nodes as the cell types that differentiate from cancerous to normal, we lack understanding of what edges they are connected by. Ultimately, there are many interconnected graphs involved in APL-related research and the continued analysis of these networks is critical in understanding ways to develop novel treatments of this lethal disease.
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4896297/