Lab-on-a-Chip Assay Aims to Predict Childhood Leukemia Treatment Response at Diagnosis

Every year in the United States, about 6,000 people are diagnosed with acute lymphoblastic leukemia, and more than 3,500 of them are children. More than 120,000 Americans are living with the disease now. It accounts for 75% of all pediatric leukemia diagnoses, and it moves fast: it can keep the body from producing mature, infection-fighting white blood cells within a matter of months.

That speed means treatment starts immediately, usually some mix of chemotherapy, targeted therapy, immunotherapy and, in some cases, bone marrow transplant. What clinicians cannot do today is know in advance how a particular drug combination and dose will affect a particular patient, or whether it will work. Treatment is personalized to a degree, based on leukemia subtype and risk classification, but most patients still end up on similar regimens. Genomic sequencing has raised hopes of something more tailored, yet the source notes that two patients with the same genetic mutation can respond very differently to targeted therapy. What is missing are functional assays that expose live cancer cells to treatments and see what actually happens.

A team from Emory University, Children's Healthcare of Atlanta and Georgia Tech has built one. It is called GradientScreen, a microfluidic assay, or lab-on-a-chip, that measures how a patient's leukemia cells respond to drug combinations using a single blood or bone marrow sample. The aim is to give clinicians this information at diagnosis, rather than after standard chemotherapy has already been given.

The design solves a practical problem. Testing every drug pair at every dose ratio one at a time would be slow and resource-intensive. GradientScreen instead covers the full range of combination ratios within a three-drug regimen in one experiment. It exposes leukemia cells to the three-drug combinations and counts how many cancer cells survive. By comparing single-drug responses with combination responses, it identifies which drugs and ratios work better together, producing detailed response patterns that reflect how that patient's leukemia might react.

The tool was developed by Kendall Williams, PhD, and Dan Zhang, PhD, graduates of Emory and Georgia Tech's biomedical engineering and bioengineering programs. The principal investigator is Wilbur Lam, MD, PhD, a professor of pediatrics and biomedical engineering at Emory and Georgia Tech and a pediatric oncologist at Children's Healthcare of Atlanta. Lam called identifying likely non-responders before therapy begins one of the "Holy Grails" of oncology, along with choosing which standard chemotherapies to pair with newer targeted or biological agents, and at what dose.

The stakes are visible in relapse figures. Roughly 50% of adults with ALL experience relapse or refractory disease, where the cancer fails to respond or grows during treatment. In children, about 15% relapse.

The evidence so far is modest. The retrospective study used 17 leukemia cell and bone marrow samples from ALL patients, supplied by the Aflac Cancer and Blood Disorders Center of Children's Healthcare of Atlanta. Results from the platform correlated with patient outcomes, including the amount of residual disease after induction, the first month of chemotherapy, and whether the patient relapsed. Williams said the goal is to broaden access to precision medicine by helping clinicians spot harder-to-treat patients earlier and match them with alternative approaches.

Next, the team plans to extend the assay to other leukemias, including acute myeloid leukemia, and to adults as well as children. They also intend to establish it within the Emory Lab for Innovative Assay Development, a collaboration between Emory Healthcare and Emory University that supports diagnostic tests usable immediately in patient care. The study was funded by an NSF GRFP award (No. 1937971) and NIH NHLBI grant R35HL145000.