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Jason Reed, Ph.D.

Massey Cancer Center research program membership

Cancer Biology

Department affiliations

Associate Professor, Department of Physics, College of Humanities and Sciences


PhD, New York University (1998)

Research description

My lab is researching the utility of real-time, live cell biomass profiling to address critical shortcomings in predicting therapeutic responses to anticipate tumor recurrence, which is usually based on tumor heterogeneity. This approach can non-invasively measure the cell mass in real-time of living cells. Those cells that are growing, gain mass, while those dying in response to a drug will lose mass. This technology is different than using metabolism-based proliferation assays or luciferase reporter-based quantification of cell viability because it provides data at an individual-cell level. This information is important because it may be helpful in identifying drug combinations that impact all cells, compared with other combinations that may clearly affect 80% of cells, but have no impact on the remaining 20%. Another focus area for my lab is the use of high-speed atomic force microscopy (HSAFM) as a rapid, low cost method to quantify nucleic acid abundance in minute samples. Detection of and counting the copy number of a particular species of DNA molecule in a heterogeneous mixture of relatively small sample quantity, such as might be derived from a tissue biopsy, occupies a central role in many biotechnology applications (e.g. transcription profiling, exome sequencing, polymorphism detection, RNA seq, chromatin immunoprecipitation seq, and so on). In these applications, detection methods require very high signal-to-noise ratios and the ability to yield a signal from small numbers (<100) of positive events. Over the last decades, these applications have been addressed by PCR, in situ hybridization of species-specific fluorescent oligos, microarrays and next-generation sequencing, but not without certain shortfalls and shortcomings. Chief among these limitations is their relative insensitivity, requiring enzymatic amplification of low-abundance samples. Nanotechnology-based single molecule approaches we are developing provide a competing approach to such applications requiring molecular recognition, thus opening new avenues to medical diagnostics, genetic tests, and pathogen detection.

Disease focus of research

Breast, Hematologic Malignancies, Prostate

Research keywords

Animal models,Autophagy,Bioinformatics,Biomarkers,Cancer diagnostics,Cancer disparities,Cancer therapy resistance,Drug discovery,Genomics,Precision medicine,Senescence,Targeted therapies

Published research (during tenure as a Massey Cancer Center member)

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Contact information


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