Differentiation of malignant B-lymphoma cells from normal and activated T-cell populations by their intrinsic autofluorescence

Seth M. Pantanelli, Zhuqing Li, Robert Fariss, Sankaranarayana P. Mahesh, Baoying Liu, Robert B. Nussenblatt

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15 Scopus citations


Patients with active posterior and intermediate uveitis have inflammatory cells in their vitreous; those with primary intraocular lymphoma have malignant B-lymphoma cells concomitantly. These cell types cannot be distinguished clinically. The goal of this study was to investigate intrinsic autofluorescence as a noninvasive way of differentiating immune and lymphomatous cell populations. Human primary T cells were stimulated with or without anti-CD3 plus anti-CD28 stimulation. B-lymphoma cells (CA46) were cultured separately. Five experimental groups were prepared: unstimulated T cells, stimulated T cells, CA46 cells, and stimulated T cells mixed with CA46 cells at a ratio of 1:3 or mixed at a ratio of 3:1. Samples were excited with three wavelengths and imaged with a confocal microscope. For each condition, the autofluorescent emissions from the sample were measured. In separate experiments, T cells or CA46 cells were injected into the anterior chamber of a BALB/c mouse eye and autofluorescence was measured. Pure T-cell and lymphoma populations were clearly distinguishable based on autofluorescence intensity spectra. CA46 cells were the least fluorescent when excited with 351-nm light, but most fluorescent when excited with longer wavelengths like 488 nm. Mixed populations of T cells and CA46 cells had emission intensities that fell predictably in between those of the pure populations. An ex vivo study showed that CA46 cells could be detected based on their intrinsic autofluorescence. Our studies showed that normal activated and malignant lymphocyte populations can be distinguished based on their intrinsic autofluorescent properties. Future work with in vivo models may prove useful in facilitating the diagnosis of uveitis and other ocular diseases.

Original languageEnglish (US)
Pages (from-to)4911-4917
Number of pages7
JournalCancer Research
Issue number11
StatePublished - Jun 1 2009

All Science Journal Classification (ASJC) codes

  • Oncology
  • Cancer Research


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