APL is a highly aggressive disease that accounts for 6-8% of all adult and 10% of all pediatric acute myeloid leukemia's (AML) in the United States. In contrast, in Latin America, APL is the most frequent subtype of AML. Left undiagnosed, APL can quickly lead to patient death, due to disseminated intravascular coagulation. If the diagnosis of APL were immediately clinically apparent to the first physician who sees the patient, then all-trans retinoic acid (ATRA) could be administered immediately. This oral medication is lifesaving if given quickly to patients with APL, as the incidence of DIC falls within hours of ATRA therapy. APL diagnosis is performed through cytogenetic detection of t(15;17) using fluorescence in situ hybridization (FISH) and/or reverse transcriptase-polymerase chain reaction (RT-PCR). If t(15;17) is identified, then a patient is immediately placed on ATRA therapy. To aid in rapid diagnosis, flow cytometry is used to immunophenotype patient cells for specific combinations of antigens that are known to be consistent with APL diagnosis. Unfortunately, molecular diagnostics and flow cytometry are not readily available to many community practices, non-specialized hospitals/clinics, and low-resource settings. Thus, in these areas especially, a new method to detect APL rapidly is imperative. To address this urgent and unmet need, we propose to develop a label-free microfluidics platform that can screen for different antigen expression combinations of APL. The platform's screening method is based on measuring the transit time of cells as they pass through a microfluidic channel functionalized with antibodies that correspond to the antigens for which we would like to screen. If cells express the specific antigen, specific interactions between the marker and the functionalized antibodies slow the cell, thereby increasing its transit time. Overall, the screening method is rapid, label free, and requires only small sample volumes. Furthermore, the device is compact, inexpensive to manufacture, and has low-power requirements. To realize the full potential of our platform we will be optimizing two devices that we have previously demonstrated: a contraction expansion array (CEA) device that separates cells based on size and can be used to perform CBCs, and a node-pore sensing (NPS) device that can screen for multiple surface markers on a cell and can be used to screen for the antigen combinations consistent with APL diagnosis. We will integrate the two devices onto a single platform and screen primary human samples (AML as a control and APL). We will benchmark our platform against flow cytometry and cytogenetic analysis. PI Lydia L. Sohn, Associate Professor of Mechanical Engineering at UC Berkeley will lead this NIH R01 project. PI James Feusner, M.D., an expert in APL and Medical Director of the Oncology Program at Children's Hospital and Research Center Oakland (CHRCO), will provide guidance on sample choice, experimental design, data analysis, and clinical relevance.

Public Health Relevance

We propose to develop a rapid label-free platform to detect and screen leukemic cells in bone marrow samples or peripheral blood of patients with acute promyelocytic leukemia (APL), a highly aggressive disease a highly that accounts for 6-8% of all adult and 10% of all pediatric acute myeloid leukemia's (AML) in the United States. If undiagnosed, APL can lead to rapid death due to disseminated intravascular coagulation, often within 24 hours of symptom presentation. Our platform will enable rapid accurate diagnosis of this disease, especially in areas such as community practices, non-specialized hospitals/clinics, and low-resource settings where conventional methods of diagnosis are not available, thus allowing for life saving therapy to be administered without delay.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project (R01)
Project #
5R01CA190843-05
Application #
9645055
Study Section
Instrumentation and Systems Development Study Section (ISD)
Program Officer
Ossandon, Miguel
Project Start
2015-03-01
Project End
2020-02-29
Budget Start
2019-03-01
Budget End
2020-02-29
Support Year
5
Fiscal Year
2019
Total Cost
Indirect Cost
Name
University of California Berkeley
Department
Engineering (All Types)
Type
Biomed Engr/Col Engr/Engr Sta
DUNS #
124726725
City
Berkeley
State
CA
Country
United States
Zip Code
94704
Kim, Junghyun; Han, Sewoon; Lei, Andy et al. (2018) Characterizing cellular mechanical phenotypes with mechano-node-pore sensing. Microsyst Nanoeng 4: