A recent study highlights a new scoring system, LSC17, which identifies 17-gene prognostic acute myeloid leukemia (AML) biomarkers to aid clinicians in determining which patients may not benefit from standard induction therapies.
The primary issues in curing acute myeloid leukemia (AML) are insensitivity to induction chemotherapy and relapse after remission – often attributed to persistent leukemia stem cells (LSCs) linked to resistance to therapy. Post-remission strategies are allocated to patients after induction chemotherapy based on molecular abnormalities or risk factors present. However, some patients’ lack of response to chemotherapy demonstrates a need for more sensitive prognostic biomarkers in order to recognize patients of higher risk for relapse prior to starting induction therapies. The LSC17 (17-gene LSC) score is highly predictive in identifying AML patients who may be resistant to initial therapy. This tool stands to allow clinicians to design more effective treatment plans for AML patients, including enrolment in more intensive trials and exclusion from unnecessary chemotherapy treatments that would prove ineffective.
In a recent study in Nature (2016), researchers sorted 83 cell samples from 78 AML patients into fractions based on gene expression (GE) of glycoproteins and cell-to-cell adhesion markers CD34 and CD38, and assessed the LSC activity in each. 495 diagnostic AML samples were also analyzed to calculate the LSC17 score, or linear combination, of the expression of 17 genes estimated in signature training data. The LSC17 score was found to improve predictive ability with regard to therapy resistance in patients newly diagnosed with AML.
Furthermore, using data from the ALFA-0701 trial, researchers tested the LSC17 score’s ability to predict patients’ responses to gemtuzumab ozogamicin (GO), a drug shown to increase chances of survival when used in addition to standard induction chemotherapy. Patients with lower LSC17 scores tended to benefit from the use of GO with chemotherapy. These results suggest that the 17-gene prognostic leukemia biomarkers could also allow clinicians to more efficiently ration GO to patients more likely to benefit from it, while also decreasing potential toxicities in patients with high LSC17 scores who would not likely benefit from the drug.
Ultimately, researchers hope to incorporate LSC17 scores into algorithms for determining risk in newly diagnosed patients with AML in order to facilitate the most effective treatment plans to prevent relapse after remission and increase the cure rates for AML. Not only do these scores have the potential to assist in upfront clinical decisions regarding patient therapies, but they may also assist in the development of new anti-leukemia therapies that may also reduce relapse rates.
Written By: Jennifer Newton