July 2019
Volume 60, Issue 9
Open Access
ARVO Annual Meeting Abstract  |   July 2019
Single immune-cell based diagnosis of ocular liquid biopsies with small volume and sample size using DEPArray technology
Author Affiliations & Notes
  • TongSeng Lim
    Menarini Biomarkers Singapore, Singapore, Singapore
  • Wei Jian Tan
    Menarini Biomarkers Singapore, Singapore, Singapore
  • Mona Meng Wang
    Translational Ophthalmic Pathology, Singapore Eye Research Institute, Singapore
  • Paola Ricciardi-Castagnoli
    Menarini Biomarkers Singapore, Singapore, Singapore
  • Anita SY Chan
    Translational Ophthalmic Pathology, Singapore Eye Research Institute, Singapore
  • Footnotes
    Commercial Relationships   TongSeng Lim, A. Menarini Biomarkers Singapore Pte Ltd (E), A. Menarini Biomarkers Singapore Pte Ltd (P); Wei Jian Tan, A. Menarini Biomarkers Singapore Pte Ltd (E), A. Menarini Biomarkers Singapore Pte Ltd (P); Mona Wang, A. Menarini Biomarkers Singapore Pte Ltd (F), A. Menarini Biomarkers Singapore Pte Ltd (P); Paola Ricciardi-Castagnoli, A. Menarini Biomarkers Singapore Pte Ltd (C), A. Menarini Biomarkers Singapore Pte Ltd (P); Anita Chan, A. Menarini Biomarkers Singapore Pte Ltd (F), A. Menarini Biomarkers Singapore Pte Ltd (P)
  • Footnotes
    Support  This study was supported by the funding of research collaboration agreement between Menarini Biomarkers Singapore and Singapore Eye Research Institution.
Investigative Ophthalmology & Visual Science July 2019, Vol.60, 813. doi:
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      TongSeng Lim, Wei Jian Tan, Mona Meng Wang, Paola Ricciardi-Castagnoli, Anita SY Chan; Single immune-cell based diagnosis of ocular liquid biopsies with small volume and sample size using DEPArray technology. Invest. Ophthalmol. Vis. Sci. 2019;60(9):813.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose : The ability to sort and recover rare target immune cells from small volume of liquid biopsies such as ocular fluids poses unique challenges that impede diagnostic accuracy. Heterogeneous cell populations with non-target immunoreactive cells in paucicellular liquid biopsies complicate conventional bulk-cell analysis, and could lead to disease misdiagnosis. This study tested the hypothesis that comprehensive molecular and genetic characterization of pathogenic immune cells at single cell resolution enables the precision diagnosis of ocular malignancies.

Methods : Study was performed in compliance with the Declaration of Helsinki with informed consent and Singhealth institutional review board approval. We provided proof-of-concept that DEPArray™ technology enabled automated isolation and recovery of rare B cells or T cells from small volumes of ocular aqueous/ vitreous fluids from vitreoretinal lymphoma (VRL) or uveitis patients for single cell analysis. Using immunoglobulin clonality assay, chromosomal translocation, genetic mutation and copy number aberration analysis, we characterized the molecular and genetic profiling of sorted immune cells at single cell resolution.

Results : Our results showed that DEPArray could distinguished, select and sort single B cells (CD3-/CD19+/CD20+) from heterogeneous cellular samples containing non-target CD3+ T cells. Identical DNA sequences of paired immunoglobulin heavy chain (IgH) and light chain (IgK) were discovered in B cells isolated from vitreous fluids of VRL patients. BCL2/JH (t14;18) translocation and genome-wide copy number aberration were detected in VRL but not in uveitis patients. Different CD3+ T cell subtypes including CD4+, CD8+ and FoxP3+ regulatory T cells were identified and sorted at single cell resolution using DEPArray technology, providing novel tools for single-cell based diagnostics of ocular liquid biopsies

Conclusions : Using real-time imaging-based, single-cell sorting DEPArray™, we provided unprecedented genomic and molecular characterizations for rare cell analysis at single cell resolution. The single immune-cell based diagnosis using digital sorting DEPArray technology could potentially revolutionize precision diagnostics of ocular malignancies in future.

This abstract was presented at the 2019 ARVO Annual Meeting, held in Vancouver, Canada, April 28 - May 2, 2019.

 

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