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On chip analysis of CNS lymphoma in cerebrospinal fluid.

Turetsky A, Lee K, Song J, Giedt RJ, Kim E, Kovach AE, Hochberg EP, Castro CM, Lee H, Weissleder R - Theranostics (2015)

Bottom Line: Molecular profiling of central nervous system lymphomas in cerebrospinal fluid (CSF) samples can be challenging due to the paucicellular and limited nature of the samples.The system can detect scant lymphoma cells and quantitate their kappa/lambda immunoglobulin light chain restriction patterns.The approach can be further customized for measurement of additional biomarkers, such as those for differential diagnosis of lymphoma subtypes or for prognosis, as well as for imaging exposure to experimental drugs.

View Article: PubMed Central - PubMed

Affiliation: 1. Center for Systems Biology, Massachusetts General Hospital, 185 Cambridge St, CPZN 5206, Boston, MA 02114, USA.

ABSTRACT
Molecular profiling of central nervous system lymphomas in cerebrospinal fluid (CSF) samples can be challenging due to the paucicellular and limited nature of the samples. Presented herein is a microfluidic platform for complete CSF lymphoid cell analysis, including single cell capture in sub-nanoliter traps, and molecular and chemotherapeutic response profiling via on-chip imaging, all in less than one hour. The system can detect scant lymphoma cells and quantitate their kappa/lambda immunoglobulin light chain restriction patterns. The approach can be further customized for measurement of additional biomarkers, such as those for differential diagnosis of lymphoma subtypes or for prognosis, as well as for imaging exposure to experimental drugs.

No MeSH data available.


Related in: MedlinePlus

Cell profiling for kappa/lambda monoclonality by image analysis. (A) Sample image analysis using an in-house image processing algorithm. Thresholding in the PE channel (CD19, CD20) is used to select B cells, and size-based filtering removes non-cell debris (white arrow). Target channels are analyzed within masks created from PE channel gating. (B) Scatterplots of mean pixel intensities from target imaging channels show clear separation of populations based on kappa and lambda light chain expression; top, DB cells; middle, Daudi cells; bottom, 1:1 mixture of DB and Daudi cells.
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Figure 5: Cell profiling for kappa/lambda monoclonality by image analysis. (A) Sample image analysis using an in-house image processing algorithm. Thresholding in the PE channel (CD19, CD20) is used to select B cells, and size-based filtering removes non-cell debris (white arrow). Target channels are analyzed within masks created from PE channel gating. (B) Scatterplots of mean pixel intensities from target imaging channels show clear separation of populations based on kappa and lambda light chain expression; top, DB cells; middle, Daudi cells; bottom, 1:1 mixture of DB and Daudi cells.

Mentions: As a proof-of-concept of lymphocyte analysis from clinical samples, we developed an image-processing algorithm for clonality assessment. Following the workflow described in Fig. 2, we first made a mask around cells expressing CD19 and/or CD20, and then quantified the mean fluorescence intensity from our target channels in each individual cell (Fig. 5A). A size filter was also included to exclude non-cell debris from analysis (Fig. 5A, white arrow). We then analyzed images of a single cell-type population (either Daudi or DB; Fig. 5B). From ~600 individual cell images, we determined the threshold (Th) values of mean fluorescence intensities to distinguish each cell type (Daudi, Thkappa = 50; DB, Thlambda = 20). When these criteria were applied to another validation samples (>2,000 cells), we obtained high sensitivities (Daudi, 96%; DB, 99%) and specificities (Daudi, 98%; DB, 98%).


On chip analysis of CNS lymphoma in cerebrospinal fluid.

Turetsky A, Lee K, Song J, Giedt RJ, Kim E, Kovach AE, Hochberg EP, Castro CM, Lee H, Weissleder R - Theranostics (2015)

Cell profiling for kappa/lambda monoclonality by image analysis. (A) Sample image analysis using an in-house image processing algorithm. Thresholding in the PE channel (CD19, CD20) is used to select B cells, and size-based filtering removes non-cell debris (white arrow). Target channels are analyzed within masks created from PE channel gating. (B) Scatterplots of mean pixel intensities from target imaging channels show clear separation of populations based on kappa and lambda light chain expression; top, DB cells; middle, Daudi cells; bottom, 1:1 mixture of DB and Daudi cells.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4440438&req=5

Figure 5: Cell profiling for kappa/lambda monoclonality by image analysis. (A) Sample image analysis using an in-house image processing algorithm. Thresholding in the PE channel (CD19, CD20) is used to select B cells, and size-based filtering removes non-cell debris (white arrow). Target channels are analyzed within masks created from PE channel gating. (B) Scatterplots of mean pixel intensities from target imaging channels show clear separation of populations based on kappa and lambda light chain expression; top, DB cells; middle, Daudi cells; bottom, 1:1 mixture of DB and Daudi cells.
Mentions: As a proof-of-concept of lymphocyte analysis from clinical samples, we developed an image-processing algorithm for clonality assessment. Following the workflow described in Fig. 2, we first made a mask around cells expressing CD19 and/or CD20, and then quantified the mean fluorescence intensity from our target channels in each individual cell (Fig. 5A). A size filter was also included to exclude non-cell debris from analysis (Fig. 5A, white arrow). We then analyzed images of a single cell-type population (either Daudi or DB; Fig. 5B). From ~600 individual cell images, we determined the threshold (Th) values of mean fluorescence intensities to distinguish each cell type (Daudi, Thkappa = 50; DB, Thlambda = 20). When these criteria were applied to another validation samples (>2,000 cells), we obtained high sensitivities (Daudi, 96%; DB, 99%) and specificities (Daudi, 98%; DB, 98%).

Bottom Line: Molecular profiling of central nervous system lymphomas in cerebrospinal fluid (CSF) samples can be challenging due to the paucicellular and limited nature of the samples.The system can detect scant lymphoma cells and quantitate their kappa/lambda immunoglobulin light chain restriction patterns.The approach can be further customized for measurement of additional biomarkers, such as those for differential diagnosis of lymphoma subtypes or for prognosis, as well as for imaging exposure to experimental drugs.

View Article: PubMed Central - PubMed

Affiliation: 1. Center for Systems Biology, Massachusetts General Hospital, 185 Cambridge St, CPZN 5206, Boston, MA 02114, USA.

ABSTRACT
Molecular profiling of central nervous system lymphomas in cerebrospinal fluid (CSF) samples can be challenging due to the paucicellular and limited nature of the samples. Presented herein is a microfluidic platform for complete CSF lymphoid cell analysis, including single cell capture in sub-nanoliter traps, and molecular and chemotherapeutic response profiling via on-chip imaging, all in less than one hour. The system can detect scant lymphoma cells and quantitate their kappa/lambda immunoglobulin light chain restriction patterns. The approach can be further customized for measurement of additional biomarkers, such as those for differential diagnosis of lymphoma subtypes or for prognosis, as well as for imaging exposure to experimental drugs.

No MeSH data available.


Related in: MedlinePlus